Journal of Economic Behavior and Organization

Uncategorized

Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Contents lists available at ScienceDirect
Journal of Economic Behavior and Organization
journal homepage: www.elsevier.com/locate/jebo
Gender, age, and competition: A disappearing gap?
Jeffrey A. Florya,d,âˆ—
, Uri Gneezy b
, Kenneth L. Leonardc,âˆ—âˆ—, John A. List d
a Robert Day School of Economics and Finance, Claremont McKenna College, Claremont, CA, United States b Rady School of Management, University of California at San Diego, La Jolla, CA 92093, United States c Department of Agricultural and Resource Economics, University of Maryland, College Park, MD 20742, United States d Department of Economics, University of Chicago, Chicago, IL 60637, United States
a r t i c l e i n f o
Article history:
Received 1 April 2016
Revised 30 March 2018
Accepted 31 March 2018
Available online 2 May 2018
JEL codes:
C93
J16
J19
J33
Keywords:
Competitiveness
Gender
Age
Field experiment
a b s t r a c t
Research on competitiveness at the individual level has emphasized sex as a physiological determinant, focusing on the gap in preference for competitive environments between
men and women. This study presents evidence that womenâ€™s preferences over competition change with age such that the gender gap, while large for young adults, disappears
in older populations due to the fact that older women are much more competitive. Our
finding that tastes for competition appear just as strong among older women as they are
among men suggests a simple gender-based view of competitiveness is misleading; age
seems just as important as sex.
Â© 2018 Published by Elsevier B.V.
1. Introduction
The gender gap in willingness to enter competitive environments has captured a great deal of attention from economists.
A burgeoning literature documents the maleâ€“female gap across a wide range of settings, explores its policy implications,
and examines its role in the differential success of men and women in labor markets (Gneezy et al., 2003; Gneezy and
Rustichini, 2004; Niederle and Vesterlund, 2007; Booth and Nolen, 2012; Balafoutas et al., 2012; AlmÃ¥s et al., 2015; Niederle
et al., 2013; Buser et al., 2014; Flory et al., 2015). The existence of aversion to competition can be very costly â€“ for firms as
well as for individuals. For firms, the use of relative performance based incentives and promotions may lead to loss of talent
if highly skilled workers self-select out of competitive environments. For individuals, the widespread use of competitionbased allocation mechanisms means avoiding competition can entail large costs: whether for a high-paying job, a position
of authority, or rights to scarce resources, to opt out of competition often means foregoing large potential gains. A full
understanding of the determinants of attitudes toward competition is thus critical for understanding the costs of competition
aversion and the design of mechanisms to mitigate undesired effects of differences in competitiveness.
Experiments have consistently found that women are generally less willing than men to compete, even when it is in
their material interest to do so (see Niederle and Vesterlund (2011) for a review). However, there is surprisingly little age
âˆ— Corresponding author at: Robert Day School of Economics and Finance, Claremont McKenna College, Claremont, CA, United States.
âˆ—âˆ— Corresponding author at: Department of Agricultural and Resource Economics, University of Maryland, College Park, MD 20742, United States.
E-mail addresses: [email protected] (J.A. Flory), [email protected] (U. Gneezy), [email protected] (K.L. Leonard), [email protected] (J.A. List).
https://doi.org/10.1016/j.jebo.2018.03.027
0167-2681/Â© 2018 Published by Elsevier B.V.
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 257
diversity in existing evidence on this question when it comes to adults.1 The findings come largely from young populations
(e.g. university and primary or secondary school students), with little attention given to what happens to competitiveness
as adults grow older. Our findings show this omission is not trivial: while we replicate the standard result among young
populations that women are significantly less competitive than men, we find the gender gap disappears among more mature
adults. Focusing on competition preferenceâ€”a measure of competitiveness that controls for skill, risk appetites and other
factorsâ€”we find that the age gap between mature women and young women is just as large as the gender gap between
young women and young men. Furthermore, more mature women are just as competitive as all men. For men on the other
hand, we find no evidence that age affects preferences over competition.
One important exception to the general focus on young populations in competition experiments is Mayr et al. (2012),
who find changes in competition entry by age among adults aged 25â€“74, and a large gender gap in selecting into their
competitive task that persists across all ages. In contrast, Charness and Villeval (2009) find competitiveness does not change
with age, and finds no signs of an overall gender gap among individuals in their late teens to early seventies when controlling for risk tastes. Similarly, in one other study that includes adults of a broad age range, Buser et al. (2015) find the overall
gender gap across all ages is considerably smaller than in most studies, disappears when controlling for risk, and does not
exist among older individuals. Neither of the latter studies look at the effect of age separately for each gender.
In this paper we examine competitiveness among men and women from age 18 to 90 and find significant changes
in competition preferences for women across age but no corresponding changes for men. These findings complement
Mayr et al. (2012) by examining choices under a different structure of competition and by focusing more precisely on
changes in competition preferences (independent from risk appetite and other factors) as they impact tournament entry.
Moreover, we show that some of the age patterns they find may be driven in part by changes in tastes for competition per
se. Unlike Charness and Villeval (2009) and Buser et al. (2015) we examine the interaction of age and gender, to find that
women 50 and older are much more competitive than women under 50 and at least as competitive as men of all ages.
To test for the effects of age, we use data from laboratory experiments on competition with men and women of all adult
ages. Our main sample draws from villages in rural communities of Malawi, a country in sub-Saharan Africa. To help verify
the pattern we discover is not particular to our initial setting, we draw an auxiliary sample from an urban US population.
While the smaller size of this second sample makes its results somewhat more speculative, the sharp similarity in the effects
of age on competition preference within each gender across the two different societies is provocative. We focus on age 50
for much of the analysis (though we also test for more gradual age effects as well). For women, changes at this age would
be predicted by recent work on sharp changes in competitiveness at puberty, the role of hormones in tastes for competition,
and evolutionary psychology models. (We discuss this further in Section 5.) Theory suggests, and our data support, a strong
relationship linking sex, age, and competitiveness.
In addition to our experimental results, we also replicate with our data the main findings on gender and competition
preferences that helped launch this literature (Niederle and Vesterlund, 2007), when restricting to subjects of a similar age
range. Age is a factor that is often overlooked in experimental studies. However, doing so may prevent a full understanding
of the behaviors we wish to understand. While not the only area of importance, labor markets and the workplace have
been focal points for the implications of differences in competition preference. Adults actively participate in the labor force
throughout the middle and upper age ranges â€“ even more so as the age of retirement rises â€“ and prior work has highlighted
the need to better understand how older workers respond to competition. This study helps address that gap. Our findings
also have significance for the design of incentives, for empirical researchers and policymakers, and for the rapidly growing
body of research on competitiveness.
2. Experimental design
To test the hypothesis that the gender gap in willingness to compete is a function of age, we use data from an experiment initially designed to examine gender differences in competitiveness among adults of a broad age range in rural
Malawi. Upon discovery of a striking pattern with respect to age among women, we replicated the experiment in the US in
order to test whether the age pattern would hold when changing the cultural setting. In our procedure, we rely heavily on
the experimental protocol designed by Niederle and Vesterlund (2007; henceforth NV). We augment their design by eliminating the need for literacy, broadening the age-distribution of participants, and incorporating multiple cultures within the
experiment.
As NV emphasize in their seminal study, an important challenge in identifying the effects of a given determinant (e.g.
gender) on appetites for competition is the confounding effects of other omitted characteristics correlated with the determinant of interest. They note that gender differences in risk appetites, aversion to receiving feedback on relative performance,
and in self-confidence can all create a gender gap in willingness to compete, in addition to a gender difference in tastes for
competition itself. Their protocol resolves this problem by having subjects make two choices, both of which are affected by
risk preferences, feedback-aversion, and self-confidence, but only one of which is affected by a taste for competing against
1 Many studies examine competitiveness among children (e.g. Cardenas et al., 2012; Dreber et al., 2011; Dreber et al., 2014; Andersen et al., 2013; Sutter
and RÃ¼tzler, 2010), often identifying the absence of a gender gap among pre-adolescents and an â€˜age of onsetâ€™ of gender differences. However, almost no
studies examine the gender gap among older adults.
258 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Fig. 1. Number of participants by age. Participants over the age of 80 are included in the category 75â€“80.
others per se. The choice affected by just risk preferences, feedback preferences, and confidence is used as a control in analyses of the choice to perform a task under competition incentives, so that the residual effect of gender on the competition
choice reflects the gender difference in preferences for competition per se. In this way, changes in risk preferences with
gender (and, in our case, age) that affect the willingness to enter a competitive setting are disentangled from changes in
competition preferences with gender and age.
We specifically chose the NV design in order to control for these factors, to identify impacts on competition preferences.
To implement it in a different setting we changed the task so all adults could complete it regardless of literacy. The task
is to arrange shapes stamped on the sides of small wooden blocks in a row from smallest to largest. After completing one
shape (e.g. stars), participants then arrange the next shape (e.g. squares) in ascending size. Payment is based on the number
of shapes completed in a 3-minute interval. As in NV, there are four different rounds, and one is randomly chosen for
payment. In round 1 (piece-rate), participants are paid X for each set of shapes completed. In round 2 (tournament), they
receive 4X per success if they complete the most sets in their group of four, but receive nothing otherwise. The group is
randomly determined, and participants never know who is in their group. In round 3, they first choose which of the two
payment schemes to work under, then perform the task. In round 4, they choose to submit their past performance in round
1 to either the competition or piece-rate pay regime. At the end, they indicate how well they believe they did versus the
others in their group.
The focus of the exercise is the choice of compensation scheme for round 3 â€“ whether participants want to perform the
task under competition against others. The other decisions and actions in the protocol generate controls to clarify the drivers
of the round 3 choice and eliminate confounds in interpreting gender and age differences. The choice of this well-established
design thus allows us to measure the impacts of preferences for competitive environments, independent of ability and risk
aversion. For a more detailed discussion of the importance of removing confounds such as risk-aversion to identify effects on
competition preferences, and how conditioning on these variables achieves this, see NV and Niederle and Vesterlund (2011);
for more on our specific implementation of the NV design, see Appendix D.
3. Main experimental results
Our main subject pool includes over 700 participants from 12 villages in Malawi. As seen in Fig. 1, participants represent
a broad age distribution. With an overall mean age of 36, 39% are below age 26 (140 women and 151 men), 40% between age
26 and 49 (148 women and 140 men), and 21% age 50 or above (77 women and 74 men). They also are evenly split by sex:
50% male, 50% female. Detailed summary statistics by age groupings are shown in Table A1.1. The average success rate was
6.1 (6.5 for men, 5.7 for women, Wilcoxon rank-sum test p < 0.01) in round 1 and 7.4 in round 2 (7.8 for men, 7.1 for women,
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 259
Table 1
Effects of gender and age on tournament entry.
(1) (2) (3) (4) (5) (6)
Female âˆ’0.079âˆ—âˆ— âˆ’0.099âˆ—âˆ— âˆ’0.078âˆ—âˆ— âˆ’0.105âˆ—âˆ— âˆ’0.084âˆ—âˆ—
(0.037) (0.039) (0.039) (0.042) (0.036)
Female over 49 0.091 0.141âˆ—âˆ— 0.141âˆ—âˆ— 0.105âˆ—
(0.064) (0.071) (0.071) (0.063)
Male under 49 0.105âˆ—âˆ—
(0.045)
Male over 49 0.109
(0.073)
Piece rate 0.003 0.007 0.007 0.008
(0.008) (0.008) (0.009) (0.008)
Improvement 0.009 0.013 0.013 0.005
(0.014) (0.015) (0.015) (0.013)
Guessed rank âˆ’0.007 âˆ’0.005 âˆ’0.005 âˆ’0.01
(0.020) (0.020) (0.020) (0.018)
Submit piece-rate to tournament 0.386âˆ—âˆ—âˆ— 0.391âˆ—âˆ—âˆ— 0.391âˆ—âˆ—âˆ— 0.381âˆ—âˆ—âˆ—
(0.035) (0.035) (0.035) (0.036)
Observations 730 730 728 728 728 728
Columns 1â€“5 show the estimated marginal effects from a Probit regression of the choice to select tournament for
round 3 (main sample). Column 6 shows the result of linear probability model (OLS) with session fixed effects.
For columns 1â€“4 and 6, the omitted category is men. For column 5, the omitted category is women under the age
of 50. Piece Rate measures the number of successes in the first round, under the piece-rate regime. Improvement
measures the increase in number of successes between the first and second round. Guessed Rank indicates the
participantâ€™s belief about how well she performed, relative to the three others in her group. Submit Piece-Rate to
Tournament is an indicator for whether the participant chose to submit her past performance in round 1 (piecerate) to a tournament against the past piece-rate performance of the other members in her randomly assigned
group. Standard errors are shown in parentheses. âˆ—âˆ—âˆ— p < 0.01, âˆ—âˆ— p < 0.05, âˆ— p < 0.1.
p < 0.01). Women ranked themselves at 2.06 (2nd out of four) on average and men ranked themselves at 1.76 (p < 0.01).
For the choice to submit the past piece rate performance, 46% of men and 45% of women chose the tournament regime
(difference not significant). We thus see some differences by gender in the key variables produced by the NV protocol. Since
these variables are designed to capture the effects of other factors besides competition tastes that affect the round 3 choice,
the main estimations of the effect of age and gender on preference to compete in round 3 control for these variables.
To examine whether the gender difference is linked to participant ages, we run five Probit specifications that test for the
presence and strength of a gender gap in willingness to compete (Table 1). Column 6 adds a linear probability model (OLS)
with fixed effects for each session, to verify the results are not somehow driven by any changes in the lab environment
that might occur from session to session. Columns 1 and 2 examine the gender gap and the age gap respectively without
any controls. The remaining columns include the full set of variables available through the experimental protocol, in order
to separate the effects of sex and age on competitiveness from the confounding influences of ability, beliefs over ability,
risk aversion, and feedback aversion. As such we include the number of successes in round 1 and the change in number
of successes between rounds 1 and 2, which control for the influence of ability and any potential boost in ability under
competition. We also include participant guesses about how their performance ranked in comparison to the rest of their
group (1 = best, 4 = worst), which controls for confidence in oneâ€™s own relative ability. The final variable is the choice made
in round 4 â€“ whether to submit the round 1 piece-rate performance to a tournament pay regime. The difference between
the decision in round 4 and that in round 3 is that only in the round 3 decision does the participant choosing the tournament actually perform against others. Since risk-aversion, feedback-aversion, and confidence affect both choices, including
the round 4 decision controls for the influence of these factors on the decision to perform work in an environment of
competition against others.
Column 1 of Table 1 shows that the unconditional gender gap in tournament entry in this sample of individuals from
a broad age range is significant, though relatively small. Column 3 shows that the size of the gap remains approximately
the same for the measure of competition preference â€“ notably, it is about half the size of the gap found in NV. Accounting for age and gender together, however, reveals a striking pattern: the gap in competition preference between men and
women is larger (and much closer to that found in other studies) among younger individuals, and non-existent among older
individuals. Column 2 and columns 4 through 6 report results from a model which allows the age of women to have an independent effect on the preference for competing, in addition to gender, by including an indicator for being female and 50
or olderâ€”Female over 49 (a dummy equivalent to the interaction between Over 49 and Female). The specification in column
5 also adds indicators to test for an age effect among men.
We use age 50, as it is a widely accepted age past which significant numbers of women have experienced menopause
symptoms, the onset of menopause coincides with a drop in the production of estrogen, and prior studies document the
importance of hormonal changes in competitiveness (Wozniak et al., 2014; Buser 2012). The median age of menopause can
260 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
vary somewhat across different populations, and may be affected by socioeconomic status, geography, race, and several other
factors (Gold, 2011). However, 50 is often used as a threshold â€“ for example, the Demographic and Health Surveys (DHS), the
major source of detailed fertility data in developing countries, only interviews women who are between the ages of 15 and
49 (Rutstein and Rojas, 2006).2 We do not have information on hormone levels of our subjects or their own experience of
menopause, and we do not have enough observations to rule out other ages between 48 and 51 as ages at which the spike
in competition preference might occur. Furthermore, since menopause is often experienced as a social or cultural event as
well as a biological event, the findings of an effect at this age could come from either source. Nonetheless, as discussed in
Section 5, evolutionary psychology arguments on the gender gapâ€™s origins suggest the transition to non-childbearing years
as a natural place to test for changes in competitiveness.
Column 2 of Table 1 shows that women over the age of 49 are no less likely than men to enter tournaments (the sum
of the coefficients for Female and Female over 49 is essentially zero). That is, the gender gap in tournament-entry disappears when looking at older women. We note however that the difference in tournament-entry between older and younger
women is not statistically significant for this unconditional analysis that does not isolate competition preference. Like column 2, columns 4 and 5 report the effects of gender and age, but now on competition preferences rather than unconditional tournament-entry (using the controls described above from the NV protocol). As the estimates in both columns show,
women 50 and older are quite different from younger women in their tastes for competition. This is most clearly seen in
column 5, which breaks the sample into four groups, with women under 50 being the omitted category. We see that older
women and younger men clearly differ from younger women (the estimate for older men is similar to that for younger men,
but not statistically significant). Also note that older women are not significantly different from either older men (p = 0.709)
or younger men (p = 0.639), and that this is driven by a drop in the gender gap so large it mildly reverses its sign in the data
(if anything, the older women in the sample display a slightly stronger preference for competition than the men). Finally,
older men are not significantly different from younger men (p = 0.973).
Comparing columns 3 and 4, we see that when we control for womenâ€™s age, the effect of gender on preference for competition is nearly 35% larger than if we ignore age, and the dissuasive effect of being female on probability of tournament
entry is an 11 percentage point drop â€“ closer to the estimated 16 percentage point drop found in NV. In the coefficient estimate for Female over 49, we see the effect of being 50 or older on womenâ€™s preferences for competition is significant and
large (14 percentage points) â€“ high enough to completely erase the gap between men and women. Older women are significantly more competitive than younger women, and they are at least as competitive as men of all ages. Column 6 shows
the results when including session fixed effects (using a linear probability model), and confirms the pattern of findings in
Column 4.
This finding of a change in competitive behavior in moving from younger to older women is quite novel. To shed some
light on the underlying sources of this change, we re-run the analysis in column 4, separately interacting the indicator
variables Female over 49 and Female with each of the four standard NV controls, allowing the NV controls to have different
effects for older women (than for younger women) and for women (than for men). From this analysis, we find that the
impact of the piece-rate performance on willingness to enter tournaments is significantly higher for women 50 and older
than for younger women. (The impacts of the other NV controls on tournament-entry do not significantly differ between
young women and older women or between women and men). This suggests that older women are more likely than younger
women to seek competition when they are good at the task. (Put differently, among women good at the task, younger
women are pushed away from tournament-entry by a distaste for competition, while older women do not show signs of
a similar distaste pushing them away.) This finding is particularly important in light of one of the stronger findings in the
original NV study: that even the most able women avoid competitive settings.
In addition, as columns 2 and 4 in Table 1 show, the rise in tournament entry when moving from younger to older
women is statistically significant when including the round 4 submission choice, and not significant without it. (In the US
sample discussed below, even the unconditional rise is significant, but the pattern in magnitude of the rise is the same
as in Malawi â€“ increasing when controlling for the round 4 choice.) This suggests tastes for risk and/or feedback may not
rise with age among women in the same way that competition preference rises. It also clarifies that change in competition
preference among women (rather than change in risk or feedback preference) is what drives the disappearance we find in
the tournament-entry gender gap when looking at older women.
4. Comparisons with competitive behavior in other samples
The preceding results point to an intriguing new and overlooked aspect of the genderâ€“competition relationship. Given
the importance of this area, however, and the fact that Malawi differs in many ways from more developed countries, it is
important to confirm whether these findings extend to modern industrialized economies. To verify the genderâ€“age effects
that we identify in our main sample are not somehow particular to Malawi, we therefore run the same exact experiment
2 The 2016 DHS survey for Malawi shows that 59% of 49 year-old women in Malawi have not experienced a period in the past 6 months, never experienced a period, or have had a hysterectomy. In the US, studies show the average age for menopause is 51 (National Institute on Aging, 2013). However,
menopause is defined as 12 months following the last period (as opposed to 6 months in the DHS survey) and therefore it is reasonable to expect that a
woman who is medically declared menopausal at 51 has been experiencing symptoms or diminished hormonal levels for at least a year, or at the age of
50.
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 261
Fig. 2. Number of participants by age in the US sample.
with an auxiliary sample with a broad age range from the US. This sample is smaller, and the results thus somewhat more
exploratory in nature, yet the similarity in findings is striking.
A total of 84 individuals participated in our US version of the experiment. The age and gender distributions as shown in
Fig. 2 are similar to Malawi: with an overall mean age of 36, 33% are below the age of 26 (14 women, 14 men), 42% between
the ages of 26 and 49 (19 women, 16 men), and 25% age 50 or above (12 women, 9 men); the gender split is nearly even,
with 54% of the participants comprised by women.3
Table 2 shows estimates from regressions identical to those in Table 1, but for the US sample. With the exception that
in the US the gender gaps in tournament entry (column 1) and competition preference (column 3) are not significant in
the full sample of all ages (while in Malawi they are significant and relatively small), the results are very similar across the
two samples. In particular, when we account for the impacts of age, we see the gender gap is large and significant among
young adults, non-existent among older adults, and disappears because women over 50 are significantly more competitive
than those under 50. Despite the limitations of the constrained sample size for US subjects, the changes are large and
statistically significant for both non-parametric tests and regression estimates, and robust to several sensitivity checks.4 (See
Appendices B and C for further analysis of the US data and robustness checks.) Note that in columns 2 and 4â€“6, just like
in Malawi, older women in the sample are actually somewhat more competitive than all men (i.e. the gender gapâ€™s sign is
mildly reversed) though the difference is not significant.
To summarize, Tables 1 and 2 show a pattern which is consistent across Malawi and the US: womenâ€™s preferences for
competition significantly rise after the approximate age of menopause, menâ€™s preference for competition does not significantly change with age, and the rise for women is more than large enough to erase the gender gap. While the smaller
US sample suggests caution before drawing definitive conclusions, the sharp parallel in results across the two settings is
provocative.
We now turn to a closer look at the relationship between these data and other studies on competitiveness. First, to
verify we are indeed picking up changes in the relationship between gender and competition preference first identified
3 The sample of 12 older women in the US is sufficient to detect statistically significant differences between younger and older women under the prior
that the magnitude of the difference would erase the gender gap observed in NV for tournament entry (over a 30 percentage point difference). The sample
for older men in the US is too small to detect significant differences between older and younger men, although we note the data finds no differences by
age for men.
4 For example: 42% of women under 50 (i.e. 13 of 33) compete in round 3, compared to 67% of all men (i.e. 26 of 39) (Ï‡2-test p<0.05); among women
over 50, 75% compete (9 of 12), compared to the 42% under 50 that compete (Fisherâ€™s exact test of the difference: p-value 0.064), and the same proportion
of men under 50 as 50 or older choose to compete (67%, or 20 out of the 30 under 50, and 6 of the 9 who are 50 and older). See Appendix B for more
detailed discussion of the US results.
262 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Table 2
Effects of gender and age on tournament entry, US sample.
(1) (2) (3) (4) (5) (6)
Female âˆ’0.156 âˆ’0.237âˆ—âˆ— âˆ’0.140 âˆ’0.246âˆ—âˆ— âˆ’0.208âˆ—
(0.106) (0.111) (0.114) (0.120) (0.108)
Female over 49 0.293âˆ—âˆ— 0.339âˆ—âˆ—âˆ— 0.334âˆ—âˆ—âˆ— 0.369âˆ—âˆ—
(0.123) (0.114) (0.116) (0.158)
Male under 49 0.259âˆ—âˆ—
(0.120)
Male over 49 0.155
(0.183)
Piece Rate âˆ’0.020 âˆ’0.005 âˆ’0.01 âˆ’0.014
(0.024) (0.026) (0.028) (0.021)
Improvement âˆ’0.019 âˆ’0.01 âˆ’0.014 âˆ’0.018
(0.040) (0.041) (0.042) (0.036)
Guessed Rank âˆ’0.097 âˆ’0.121 âˆ’0.122 âˆ’0.100
(0.085) (0.090) (0.090) (0.074)
Submit piece-rate to tournament 0.365âˆ—âˆ—âˆ— 0.373âˆ—âˆ—âˆ— 0.378âˆ—âˆ—âˆ— 0.331âˆ—âˆ—âˆ—
(0.111) (0.114) (0.114) (0.115)
Observations 84 84 84 84 84 84
Columns 1â€“5 show the estimated marginal effects from a Probit regression of the choice to select tournament for round 3 (main sample). Column 6 shows the result of linear probability model (OLS) with session
fixed effects. For columns 1â€“4 and 6, the omitted category is men. For column 5, the omitted category is
women under the age of 50. Piece Rate measures the number of successes in the first round, under the piecerate regime. Improvement measures the increase in number of successes between the first and second round.
Guessed Rank indicates the participantâ€™s belief about how well she performed, relative to the three others
in her group. Submit Piece-Rate to Tournament is an indicator for whether the participant chose to submit her
past performance in round 1 (piece-rate) to a tournament against the past piece-rate performance of the other
members in her randomly assigned group. Standard errors are shown in parentheses. âˆ—âˆ—âˆ— p < 0.01, âˆ—âˆ— p < 0.05, âˆ— p < 0.1.
Table 3
Comparing results across different experimental settings.
Univ. of Pittsburgh students (Reported in NV) Malawi adults 18â€“25
(1) (2) (3) (4)
Female âˆ’0.162âˆ— âˆ’0.38âˆ—âˆ—âˆ— âˆ’0.144âˆ—âˆ— âˆ’0.180âˆ—âˆ—âˆ—
[0.05] [0.00] [0.03] [0.00]
Tournament performance âˆ’0.009 âˆ’0.015 âˆ’0.0134 âˆ’0.0204
[0.42] [0.41] [0.35] [0.13]
Improvement 0.011 âˆ’0.015 0.0402 0.0446âˆ—
[0.44] [0.50] [0.12] [0.07]
Guessed rank âˆ’0.120âˆ—âˆ— âˆ’0.0485
[0.01] [0.14]
Submit piece-rate to tournament 0.258âˆ—âˆ— 0.389âˆ—âˆ—âˆ—
[0.012] [0.00]
Observations 77 80 291 291
Estimated marginal effects from Probit regressions in 2 different samples of participants which experienced the
same basic experimental protocol. Columns 1 and 2 contain results reported in NV, for which subjects are students from the University of Pittsburgh. Columns 3 and 4 show results from the individuals between the ages of
18 and 25 from our primary sample. Brackets contain p-values, to facilitate comparison with the results reported
in NV. âˆ—âˆ—âˆ— p < 0.01, âˆ—âˆ— p < 0.05, âˆ— p < 0.1.
in NV, and as further evidence of the robustness across multiple environments of the preference difference NV identifies,
Table 3 compares the data patterns in their study to the patterns among student-age participants in our sample. We begin
with the specification that best identifies the independent impact of gender on competition preferences per se (i.e. with
the full set of controls). As shown in column 1, NV find that after conditioning on performance and the other controls to
isolate the effect of gender on tournament preference, the effect of being female is to lower the likelihood of competing by
an estimated 16.2 percentage points. We see in column 3 that the corresponding estimate is remarkably similar in Malawi
when restricting to 18â€“25 year-olds, at 14.4 percentage points. That is, for young adults, the effect of gender on competition
preferences per se leads to very similar estimated drops in propensity to compete across the two very different societies. On
the one hand, this highlights the robustness of the gender effect on competition preference originally identified in NV, across
quite different environments. It also helps verify our experimental design replicates findings on competition preferences of
previous studies when using populations of similar ages.
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 263
Columns 2 and 4 of Table 3 show how estimates of the gender effect compare when excluding the controls for the
influence on tournament entry of general factors besides competition preference (such as confidence, risk, and feedback
aversion). The results suggest the gender gap for tournament entry in Malawi is less sensitive to gender differences in other
general factors compared to the NV sample, and instead driven mostly by the preference difference for competition across
men and women.5 We also see a remarkably strong similarity when comparing the gender estimates for young adults in
our US sample with those for the students in NV, despite the limited number of subjects (see Table A2.1 and Appendix B for
discussion).
As discussed in the next section, a discontinuous change in competition preference among women around age 50, and
no change among men, is consistent with one of the leading explanations on origins of the gender gap as well as recent
evidence of an important role played by hormones. However, in a different experiment, Mayr et al. (2012) report strong
evidence of a continuous increase in the likelihood to enter tournaments up to age 50 among both men and women, with
milder evidence of a decrease thereafter. In comparing data patterns between that study and this one, it is helpful to bear
in mind two key distinctions in approach.
First, there is a structural difference in competition across the two settings in that subjects in Mayr et al. (2012) do
not compete with nearby individuals, but instead work alone to beat an unknown score drawn from a database of past
performances by others. This introduces a relational distance not present in the standard NV design â€“ one that may be
important if it deemphasizes adversarial aspects of competition, or creates other changes that could affect subjectsâ€™ choices.6
Second, the approach of Mayr et al. (2012) enables analysis of the net effects of age and gender on competition entry
(with checks to eliminate confidence or ability as drivers), whereas we focus on the effects of age and gender on competition
preference. Both approaches help us understand the role of gender and age on competitiveness and both yield insights with
important practical implications. The first approach captures the composite impacts on competition-entry of changes in
preferences over risk, feedback, and competition, as age and gender changes. The second focuses on isolating the changes
in tastes for competition as one of the fundamental constituents driving propensity to compete. This requires a method
to separate the effects of age and gender on competition preference from their effects on the other factors that impact
competition entry. Risk preference is one of the most commonly discussed: as Mayr et al. (2012) note, their findings could
be partly picking up changes in risk appetites across the age groups in their sample.7 Not only might men and women differ
in risk preferences (Croson and Gneezy, 2009), but Brinig (1995) finds experimental evidence of age effects on risk aversion
that strongly differ by gender.8 This highlights the need for some way to control for changes in these other factors in order
to isolate changes in competition preferences. NV resolves this through a clever design that we borrow.
Despite these important differences in approach, the patterns discovered in Mayr et al. (2012) are also instructive for
our analysis: since their findings may be driven in part by changes in competition taste, we examine our data for evidence
of a similar type of relationship between age and competition preferences alone. The strongest part of their findings is the
upward slope showing a continuous rise in propensity to select their competition regime, among both men and women.
Table 4 thus reports results from Probit regressions that test for evidence of a smooth change in preferences for competition as age increases among men and women in our sample. In columns 1 and 2, the estimates for Female Ã— age are
positive but insignificant, and in column 2 the estimate for Male Ã— age is similarly not significant. Columns 3 and 4 restrict
the sample to adults under the age of 50 to test for the possibility of a continuous age effect in the same ages where
Mayr et al. (2012) find an increaseâ€”the estimates for the gender-continuous age interactions are once again not significant.
Appendix B discusses results for a similar analysis among our US participants, also showing the coefficient estimates for
Female Ã— age and Male Ã— age are not significant in any of the four specifications (Table A2.2).
In addition, Appendix C tests for a quadratic relationship between age and competition tastes. As Table A3.2 shows, here
we find some evidence of a continuous quadratic effect that operates simultaneously with the discrete effect. (Notably, the
quadratic effect only exists for women; age still has no effect on men.) This is interesting, as it suggests that in addition
to the strong discrete impact we find there may also be a continuous age pattern of changes in competition preference
similar to the changes in competition entry observed by Mayr et al. (2012). However, as we discuss in Appendix C, the
effect sizes show our continuous estimates are relatively small compared to the very large discrete effect. We conclude that,
when isolating the effects of gender and age on the preference for competition (separate from their effects, for example, on
risk-aversion), the discrete age effect for women is a superior fit with our data, though it may be accompanied by a less
pronounced quadratic impact of age as well.
5 Whereas in the US the gender gap is an estimated 38 percentage points when not controlling for the other general factors and drops by 56% when
adding the controls, in Malawi the gender gap is an estimated 18 percentage points without the controls and drops by only 20% when they are included.
See Table 3, columns 2 and 4.
6 Competing without visible opponents may depersonalize competition, make it more abstract, or heighten its aspect as a risky individual challenge while
diminishing its aspect as a contest with another. Gillen et al. (2015), which also has subjects doing the task at different times against unseen opponents,
find evidence the gender gap in competition entry for their task is largely driven by risk preferences, and is much smaller than commonly found â€“ about
one third the size of that in NV.
7 Indeed, in another setting where subjects without observable opponents are also told they are competing with others doing the task at another time,
Gillen et al. (2015) argue the tournament entry gender gap they find is almost entirely driven by differences in risk appetites. This highlights the importance
of risk controls in this setting, if one wants to find impacts on competition tastes.
8 In one of the few other experiments on age and risk tastes, Harbaugh et al. (2002) find no genderâ€“age interaction.
264 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Table 4
Continuous effects of age on tournament entry.
Full sample Under 50
(1) (2) (3) (4)
Female âˆ’0.167âˆ—âˆ— âˆ’0.182âˆ—âˆ— âˆ’0.177âˆ— âˆ’0.268âˆ—
(0.073) (0.087) (0.107) (0.138)
Female Ã— age 0.002 0.002 0.003 0.002
(0.002) (0.002) (0.003) (0.003)
Male Ã— age âˆ’0.001 âˆ’0.004
(0.002) (0.004)
Piece rate 0.007 0.005 0.005 0.003
(0.008) (0.009) (0.010) (0.010)
Improvement 0.013 0.012 0.020 0.018
(0.015) (0.015) (0.016) (0.016)
Guessed rank âˆ’0.006 âˆ’0.006 âˆ’0.009 âˆ’0.009
(0.020) (0.020) (0.023) (0.023)
Submit piece-rate to tournament 0.386âˆ—âˆ—âˆ— 0.386âˆ—âˆ—âˆ— 0.374âˆ—âˆ—âˆ— 0.373âˆ—âˆ—âˆ—
(0.035) (0.035) (0.040) (0.040)
Observations 727 727 579 579
Estimated marginal effects from a Probit regression of the choice to select tournament
for round 3 (main sample). Columns 3 and 4 are restricted to participants under the
age of 50. The variable Female is an indicator for whether the participant is a woman.
Age is the continuous age of the individual, in number of years. Piece Rate measures
the number of successes in the first round, under the piece-rate regime. Improvement
measures the increase in number of successes between the first and second round.
Guessed Rank indicates the participantâ€™s stated belief about how well she performed,
relative to the three others in her group. Submit Piece-Rate to Tournament is an indicator for whether the participant chose to submit her past performance in round
1 (piece-rate) to a tournament against the past piece-rate performance of the other
members in her randomly assigned group. Standard errors shown in parentheses. âˆ—âˆ—âˆ— p < 0.01, âˆ—âˆ— p < 0.05, âˆ— p < 0.1.
5. Possible mechanisms
Discussion of the underlying drivers of gender differences in competition preferences typically falls into one of two broad
categories: (i) culture, context, and socialization; (ii) physiology and evolution. The findings of this study are consistent with
two mechanisms that fall into the latter class of explanations â€“ one that has been part of this literature since its very
beginnings and another that has surfaced more recently.9
As early as the first studies on gender differences in competition, one of the main hypotheses advanced on their
origins â€“ and consistently cited since â€“ is human evolution.10 This view holds the differences derive from natural selection
and the benefits and costs of competition for reproduction through mating, childbearing, and child rearing among human
ancestors. For males, winning competitions can increase their number of offspring. For females, however, competitiveness is
less likely to increase the number of offspring than it is for males and in fact is likely to impose a reproductive cost during
a key lifecycle stage. Due to the importance of direct maternal inputs in early life, if a competition outcome left a mother
less able to care for her very young offspring, the offspring would face higher chances of death (Campbell, 2002; Campbell,
2004). Since a motherâ€™s resources also affect her investments in offspring quality (and thus survival chances), it is not the
case that competing has no benefits. It is that the reproductive payoff of winning resources and using them to invest in
offspring quality would be weighed against the reproductive cost of losing.
Most women past their childbearing years are mothers. However, once their offspring had passed the vulnerable early
years, the reproductive cost of competing and losing would fall, while the reproductive benefits of winning would remain.11
The evolution-based argument has been used chiefly to explain greater competitiveness observed in men (among young
adults), with little attention paid to this other prediction it implies â€“ that preferences over competition among adult women
9 The fact that preferences change in women and not in men is also consistent with findings by DellaVigna et al. (2013) that explain behavior differences
by gender as the result of differences not only in means but also variances of preference distributions. They show this can result in a large proportion of
women on the margin of certain types of actions (e.g. pro-social decisions), making their choices especially sensitive to small shifts in the setting or in
preferences.
10 For summaries of the evolution viewpoint in economics, see NV and Gneezy and Rustichini (2004). Sex-based behavior in the evolutionary literature
extends back to Darwin (1871), Bateman (1948) and Trivers (1972). Dekel and Scotchmer (1999), Robson (1996), and Robson and Samuelson (2009) discuss
evolutionary models more formally in contexts of risk aversion.
11 Besides investing in her older juveniles, mothers could give resources to adult children, to be shared with their own offspring, or give resources directly
to their grandchildren. All would raise her reproductive success (and genetic bequest). Cassar et al. (2016) find empirical support for this tradeoff, showing
women can be as competitive as men if rewards go to their teenage kids.
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 265
should depend on age, not just falling when reaching childbearing age but also rising once past the age where one can have
young children. Our findings that competition preference is low among young women, increases among female participants
right at the age at which significant numbers of women have experienced or are experiencing menopause, and does not
change with age among our male participants, is consistent with these predictions. Thus, if the mechanism that decreases
competitiveness as women reach childbearing age has any link with the process of human evolution, it is plausible this
effect would dissipate after menopause.
More recently, several studies suggest hormones are pivotal in competitiveness â€“ in particular, among women. Some
(e.g. Andersen et al., 2013) show how competitiveness among girls changes at puberty while others (e.g. Wozniak
et al., 2014; Buser, 2012) more directly examine the role of hormones on competition preferences of adult women.
Wozniak et al. (2014) reviews the literature on neuroendocrinological links between hormones and brain activity, and suggests that hormones (particularly progesterone and estrogen, both of which decrease with menopause) might suppress competitive preferences in women. Recent evidence also suggests the hormone cortisol can have a positive effect on willingness
to compete among women (Buser et al., 2017; Zhong et al., 2018), and cortisol levels rise with menopause (e.g. Woods
et al., 2006; Woods et al., 2009). On the other hand, Apicella et al. (2011) find menâ€™s competitiveness is unrelated to hormone levels, suggesting that even if testosterone levels fall as men age, menâ€™s competitive preferences may not change. Thus
it is possible that the sharp change in hormone levels at adolescence suppresses competitiveness among women and that
another large change in hormone levels at menopause would be associated with a rise in competitiveness. The fact that
major hormonal changes coincide with the age at which competition preference changes for women in our results, and the
fact that among men there is neither a similar age of sharp hormonal change nor a change in competition preference, is
consistent with hormones having a strong influence.
Although this paper focuses explicitly on an effect at age 50 because this age is suggested by these literatures, in
Appendix A we examine the data for evidence of any other structural break by age (between the ages of 21 and 55). The
results show that for males, there is no evidence that being below or above any particular age threshold affects competition preference. For females, the threshold is most notable in Malawi at 50 and in the US it first appears at 48 but is also
significant at 50.
Our findings for a discrete change in behavior around age 50 therefore support two mechanisms advanced in the literature that are consistent with a biological cause.12 However, they do not preclude an important role played by culture, context, or the effects of socialization, such as those found in Gneezy et al. (2009), Niederle et al. (2013), and
Andersen et al. (2013). Cultural factors likely magnify or dampen behaviors that may originally stem from the logic of
evolution, and behavior can be jointly determined by physiological and social drivers. Further studies exploring the mechanisms through which physiological determinants and social determinants interact represent an intriguing area for future
research.
6. Conclusion
This study sheds new light on limits to gender differences in competition preferences. While other studies have shown
the difference can be influenced by culture (Gneezy et al., 2009), we find it also depends on age. These results indicate there
is at least as much difference in competitiveness between younger women and older women as there is between younger
women and men, and that more mature women are no less fond of competition than men.
Our findings reconcile the apparent inconsistencies between the many studies that show sharp and robust gender differences in competition preferences when controlling for risk, and their absence in the two studies with a broad age range that
also control for risk aversion (Charness and Villeal 2009; and Buser et al., 2015). They also complement Mayr et al. (2012) by
focusing more specifically on one of the key determinants of competition entry â€“ competition preferences â€“ as well as show
that some of the age patterns they find may be driven in part by changes in tastes for competition. These results suggest that by focusing on young populations, the early literature may be missing a broader relationship between sex, age,
and tastes for competition. This is not to challenge the importance of understanding behavioral determinants among young
adults and their impacts on early career choices: we continue to find that young women avoid competitive settings more
than men. However, the tendency to omit older populations from these studies creates a potential risk that competitiveness
may be misunderstood as a more male characteristic than it actually turns out to be. Apicella et al (2011) show no link
between testosterone and competitiveness, and we show that competitiveness is as much a feature of a grandmother as of
a young man.
Expanding the breadth of ages included in research on competitiveness also helps us identify more general relationships,
deepen our overall understanding of competitiveness, and clarify the roles of other physiological factors besides gender. It is
also important for understanding the behavior of more mature adults â€“ in labor markets, the workplace, and other economic
and social settings where competition plays a role. A clear understanding of how older employees respond to competition
is critical for personnel policies and design of incentives for more senior and experienced workers.
12 Note that the evolution and hormones mechanisms are mutually compatible.
266 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Some words of caution are in order. While the importance of the age right around 50 for womenâ€™s attitudes toward
competition fits the age at which many women have experienced or are experiencing menopause and is consistent with the
hypothesis that evolution partly explains the gender difference, our data do not permit an explicit test of menopause itself
(or its hormonal changes) as the proximal cause of the sharp rise in womenâ€™s tastes for competition. The striking similarity
of the pattern across the Malawi and US samples, the fact that a critical fertility threshold lies at the center of the pattern,
and the patternâ€™s consistency with a model of maximizing reproductive success, suggests menopause as the likely driver.
However, confirming the specific mechanism underlying the change in behavior constitutes an important avenue for further
study.
Finally, our main sample is drawn from Malawi, and while these results are interesting in their own right, the differences
from more developed economies could place constraints on broader implications of findings based on this sample alone. The
fact that genderâ€™s impact on competition preference among young adults leads to an estimated drop in tournament-entry
very close to that found among the similarly aged subjects in NV inspires confidence that our findings from Malawi yield
insights also for high-income countries. Going further, we repeated the experiment with an auxiliary sample drawn from
the US, and discovered the same age impacts on each gender as found in Malawi. Estimates of the spike in tournament
entry of women after age 50 are significant, but the number of participants is lower than we would prefer before drawing
firm conclusions. We therefore consider the US sample an exploratory one, and we interpret the results as provocative â€“ the
opening of a question rather than a definitive answer. Furthermore, we recognize that by comparing commonalities across
two very different societies this study is likely to shed the most light on age effects that are linked with physiological
transitions. This does not preclude the influence of culture or culture-based transitions, which may also help mediate the
impacts of gender on competition preference, and which may vary from one society to another. Given the relative dearth of
attention older individuals have received in this literature, additional studies with participants in the upper age ranges are
needed. We see this is as an exciting area ripe for future research.
Acknowledgments
We thank participants at ESA 2011, the World Bankâ€™s Development Economics Research Group and seminar attendees
at several universities for helpful comments. This work was funded by the NSF Grant, SES 0922460 administered at the
University of Maryland with K. Leonard as PI.
Appendix A. Patterns with age across both samples
Table A1.1 shows the distribution of choices across age groupings in both samples, as well as for the other variables
generated through the NV design.
In this paper, we focus on the discrete effect of age on competition preference among women around age 50 because
theory motivates this from two directions. In this section, we take advantage of the broad spectrum of adult ages in our data
to examine the evidence for alternative possible age thresholds, not connected to either explanation, across which behavior
might change. We test for a structural break in the effect of gender on competition preferences between younger and older
individuals, using all the data and testing discrete breaks at ages between 21 and 55 as the threshold for being categorized
as â€œyoungâ€ or â€œoldâ€.13 Beginning with the same specification for the regression reported in column 2 of Table 1 (the specification which best isolates impacts on the preference for competition), we add a term interacting gender with an indicator
for whether an individual is above a given age (i.e. in the older group):
yi = Î²0 + Î²1Femalei + Î²2Femalei Ã— Oldi + x
i
Î¸ + i
where the response variable is whether the individual chose to compete in round 3, and xi is a vector of the standard
NV controls (performance in round 1, improvement in round 2, believed relative ability, and round 4 choice of whether to
submit past performance to a competition). We run the regression 35 times â€“ once for each possible age threshold between
21 and 55. The coefficient on the interaction term represents the impact of being above the given age threshold on the effect
of being female on an individualâ€™s preference for the competitive environment. We then run the same basic specification for
males:
yi = Î²0 + Î²1Malei + Î²2Malei Ã— Oldi + x
i
Î¸ + i
This results in 137 specifications (35 each for men and women in Malawi, 35 for women in the US and 32 for men in
the US). The resulting coefficients on the interaction term thus represent the effect of being above each given age threshold
on an individualâ€™s competition preference, for men and women separately, in each society.
13 The sample of men older than 52 is too small to identify the coefficient for the US.
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 267
Table A1.1
Summary statistics by sample, gender and age group.
Age group Obervations Piece rate Tournament Improvement Guessed rank Perform in tournament
(Round 3 Choice)
Submit to tournament
(Round 4 Choice)
Malawi
Male
18â€“29 183 7.7 9.2 1.6 1.6 50% 47%
30â€“39 74 6.4 7.6 1.2 1.8 46% 36%
40â€“49 34 5.9 7 1.1 1.6 38% 47%
50â€“59 16 4.9 5.4 0.5 1.7 63% 56%
60â€“69 33 4.1 5.2 1.1 2.1 33% 55%
7 0+ 25 3.6 3.9 0.3 1.7 60% 52%
Female
18â€“29 170 6.7 8.6 1.8 2 34% 39%
30â€“39 71 5.8 6.9 1.1 2.2 49% 55%
40â€“49 47 5 6 1.0 2.1 36% 53%
50â€“59 28 5.2 6.1 0.9 1.8 46% 25%
60â€“69 23 3.7 4.7 1.0 2.2 65% 65%
7 0+ 26 2.5 2.9 0.4 2.2 31% 52%
US
Male
18â€“29 19 12.8 14.4 1.6 1.7 63% 47%
30â€“39 4 12.6 15.1 2.8 1.8 75% 50%
40â€“49 7 9.7 11.3 1.6 2 71% 29%
50â€“59 7 9.9 10.9 1.1 1.7 57% 57%
60â€“69 1 9 10.5 1.0 2 100% 100%
7 0+ 1 6.8 8.3 2.0 2 100% 0%
Female
18â€“29 19 13.1 14.6 1.6 1.9 42% 37%
30â€“39 9 11.3 12.6 1.2 2 56% 56%
40â€“49 5 11.2 13.8 2.6 2 20% 40%
50â€“59 9 10.8 12.5 1.8 1.8 78% 44%
60â€“69 2 8 9.5 1.5 3.5 100% 50%
7 0+ 1 8.8 8 0.0 3 0% 0%
Piece Rate measures the number of successes in the first round, under the piece-rate regime. Tournament measures the number of successes in the second
round, under competition incentives. Improvement measures the increase in number of successes between the first and second round. Guessed Rank indicates
the participantâ€™s belief about how well she performed, relative to the three others in her group. Perform in Tournament is an indicator for whether the
participant chose to perform the task under competition incentives. Submit to Tournament is an indicator for whether the participant chose to submit her
past performance in round 1 (piece-rate) to a tournament against the past piece-rate performance of the other members in her randomly assigned group.
The coefficient estimates and confidence intervals for Î²2 are displayed separately by gender and society in Fig. A1.1. As
shown in the figure, for women, the sign of the estimated effect of being in the older group is always positive â€“ whether
in the US or in Malawi. The largest estimate occurs at age 48 in the US, and age 50 in Malawi â€“ both estimates significant at the 0.05 level.14 For men on the other hand, the estimated effect of being in the older group is sometimes
positive and sometimes negative. More importantly, the 95% confidence interval of the estimated effect of being in the
older group always includes zero by a wide margin when looking at men. If we repeat the analysis without any controls (testing for age thresholds for a change in unconditional tournament-entry), we find the results are virtually identical, except that the only significant threshold for women in the US is at 48 years of age. These results are available on
request.
Thus, for males, there is little evidence that being below or above any particular age threshold affects their competition
preference. For females, however, we find that those older than somewhere around 48â€“50 are significantly different from
those younger than this threshold in both our main sample drawn from Malawi as well as our auxiliary sample from the
US. Notably, these ages constitute the only threshold that is significant in both societies, which provides strong support for
our rationale in studying effects around this age.
Interestingly, there is evidence in Malawi of an additional break around the age of 30. The fact that this pattern does not
exist in the US sample points to the likelihood that cultural factors still play an important role. The interaction of social and
physiological determinants of gender differences in preferences remains an important area for future research.
14 In the US, the estimated effect of age thresholds at 48, 49 and 50 are statistically indistinguishable from each other.
268 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Fig. A1.1. Coefficients from regression testing for structural break in competition preference with age. The four figures above show the estimates and 95%
confidence intervals for the coefficient on gender interacted with an indicator for being older than the given age threshold, in a regression of the choice to
perform the task under competition on gender and the standard NV controls (performance in round 1, improvement in round 2, believed relative ability,
and round 4 choice of whether to submit past performance to a competition). The estimates for the structural break parameter are shown for 35 different
regressions for each sample and gender. Where the coefficient is significantly greater than zero, it suggests the average participant above the threshold is
more likely to compete than the average participant below the threshold.
Appendix B. Gender and age effects in US sample
A. Summary statistics
Our second subject pool comes from an urban area in the US, drawing participants from staff and students at a large university and individuals in the surrounding community. In total, we had 84 US participants. As seen in Fig. 1 and Table A1.1,
the participants represent a broad age distribution. With an overall mean age of 36, 33% are below the age of 26 (14 women
and 14 men), 42% between the ages of 26 and 49 (19 women and 16 men), and 25% age 50 or above (12 women and 9 men).
The gender split is nearly even, with 54% of the participants comprised by women. Task performance in the US was higher
than in Malawi: the average success rate was 11.6 in round 1 (11.5 for men, 11.7 for women) and 13.2 in round 2 (13.1 for
men, 13.3 for women), with no significant gender difference.15 Overall willingness to compete is also higher in the US (58%).
B. Effects of gender and age
The unconditional gender gap in this sample is much smaller than that typically found in the US. While 67% of men
select into the tournament, 51% of women do (Ï‡2-test, p = 0.15; also see Table 2, column 1). This stands in stark contrast to
other studies in the US with similar sample sizes, but based on young adults, which often find gaps twice as large that are
highly significant. In their seminal study using 80 student-age subjects, for example, NV find that the percentage of men
that enter the tournament is more than twice the percentage of women, and the difference is significant at the 0.002-level.
15 The higher average number of tasks completed in the 3 min period in the US compared to Malawi may derive from several factors, such as differing experience with sedentary cognitively-intense work, or familiarity with performing timed test-like tasks for short intervals. Human capital (lower in
Malawi) may also play a role in the task. Visual pattern recognition may be a skill that is improved through schooling. Since such skills likely vary across
individuals, this helps highlight the importance of using the regression analysis to control for performance when estimating the impact of gender and age
on propensity to select into the tournament.
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 269
At first blush, these results appear inconsistent with the robust findings in the literature on large and highly significant
gender differences in preferences for competition in the US and Europe.16
However, just as in the Malawi sample, the inconsistency is immediately resolved by accounting for age: the gender gap
in competition preference exists and is strong, but only for younger women in the sample. When focusing on older women,
the gap disappears. We see this in Table 2. First, in moving from column 1 to column 3, we note that including the controls
employed through the NV experimental protocol to identify the effect of gender on competition preferences per se leaves the
estimated impact of gender essentially unchanged (small and insignificant). However, columns 2 and 4 show that as soon
as we control for womenâ€™s age, the estimated effect of being female becomes large and significant: women under the age
of 50 are 24â€“25 percentage points less likely to compete than men, after controlling for the influences of risk preferences,
feedback preferences, ability, and confidence. This estimate is consistent with the gender effect reported in other studies
in the US and Europe, which sample young individuals.17 Moreover, the estimated effect of being 50 or older on womenâ€™s
preferences for competition is significant and large (0.339) â€“ more than enough to completely erase the gap between men
and women. (Appendix C and Table A3.1 discuss estimates suggesting older womenâ€™s taste for competition may in fact
exceed that among men of all ages in this sample, though the impacts on propensity to compete are not significant.) Nonparametric tests also show significant differences in tournament entry between women in the two different age groups.
For example, 42% of women under 50 enter the tournament, compared to 75% of those 50 and older, (Fisherâ€™s exact test
p = 0.064). (The proportion of males stays fixed at 67% across the two age groups.) Exactly two thirds of men under 50
choose to compete, matching precisely the proportion of older men who choose to compete (6 out of 9), matching the
finding in Malawi that age does not have a significant effect on menâ€™s propensity to select into competition. Note also that
Table 2 column 5 shows no significant difference in the estimates for Male under 49 and Male over 49.
Thus, while overall levels differ somewhat, we observe in the US the exact same pattern of effects by sex and age on the
preference for competing that we find in Malawi.
C. Robustness checks
These results are fairly robust to a variety of sensitivity checks. To examine whether the finding that older women are
more competitive than younger women could be driven by one or two observations, we intentionally drop observations
that would make it harder to detect an effect. If we drop a non-competing woman under age 50 from the sample, estimates
from the Probit regression in Table 2 column 4 still indicate that being 50 or older makes a female subject significantly more
likely to compete (p = 0.038), and a Fisherâ€™s exact test also shows the older group of women is significantly more likely to
select into competition (p = 0.064). If we instead drop a competing woman age 50 or older from the sample, regression
estimates again still indicate that women 50 or older are significantly more likely to choose competition (p = 0.055), and
a Fisherâ€™s exact test shows the older group of women is significantly more likely to compete (p = 0.081). Alternatively, if
we drop both a competing woman 50 or older and a non-competing woman under 50, Probit estimates remain significant
(p = 0.061), and a Fisherâ€™s exact test remains significant at the 0.10-level (p = 0.095).
D. Comparing NV students to young adults in our sample
Table A2.1 compares the NV results to results for the same age group in our US sample. This comparison is noteworthy in
that these participants are all drawn from the same culture. This may explain the stronger similarity with NV in terms of the
role other general factors (besides competition tastes) seem to play in gender effects on tournament entry. Note that since
NV reports p-values and reports results both with and without the variable for submitting the piece rate performance to a
tournament, we follow the same convention here. After conditioning on performance in the task, NV finds that being female
reduces the probability of competing by an estimated 38 percentage points in their sample of 80 students (significant at the
0.01-level), while we find an estimated 41 percentage point reduction in our sample of 28 similarly aged adults (significant
at the 0.10-level). When adding the remaining NV controls that account for other factors that also affect willingness to
compete, the magnitude of the estimated effect in NV drops by over 50% and the significance reduces substantially. Similarly,
when including the full set of NV controls in our sample of 18â€“25 year-olds from the US, the estimated magnitude drops
by nearly a half and the significance drops considerably. While the relatively small sample size of young adults in our US
sample makes the estimate in column 4 imprecise, the basic pattern is remarkably similar to that of the students in the
earlier study.
There is an interesting pattern that bears mentioning across the three samples of student-age adults. On the one hand,
the estimated negative effect of Female on propensity to enter the tournament is very similar across all three samples (NV
students, US young adults, Malawi young adults) when including the full set of controls from the NV protocol to identify
16 Notably, however, these findings are consistent with the only 2 other experiments on competition using adults of a broad age range that we are aware
of, Charness and Villeval (2009), and Buser et al. (2015), who find no gender gap across their sample as a whole when controlling for risk aversion. (They
do not examine whether the gap interacts with age.)
17 For example, among studies using student-participants, Gupta et al. (2013) find a marginal effect of âˆ’.36 without controlling for performance,
Niederle and Vesterlund (2007) find a marginal effect of âˆ’.38 when controlling for performance, Niederle et al. (2013) find a marginal effect of âˆ’.36.
Flory et al. (2015) find a smaller marginal effect, âˆ’.15, among participants of a broader age range than the typical student age (mean age 28).
270 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Table A2.1
Comparing results across experimental settings within the US.
Univ. of Pittsburgh students (Reported in NV) US adults Ages 18â€“25
(1) (2) (3) (4)
Female âˆ’0.38 âˆ’0.162 âˆ’0.410 âˆ’0.242
[0.00] [0.05] [0.07] [0.43]
Tournament performance âˆ’0.015 âˆ’0.009 âˆ’0.0615 0.0313
[0.41] [0.42] [0.31] [0.75]
Improvement âˆ’0.015 0.011 âˆ’0.198 âˆ’0.170
[0.50] [0.44] [0.06] [0.24]
Guessed rank âˆ’0.120 âˆ’0.809
[0.01] [0.047]
Submit piece-rate to tournament 0.258 0.829
[0.012] [0.037]
Observations 80 77 28 28
Estimated marginal effects from Probit regressions in 2 different samples of participants which experienced
the same basic experimental protocol. Columns 1 and 2 contain results reported in NV, for which subjects are
students from the University of Pittsburgh. Columns 3 and 4 show results from the 28 individuals (14 men and
14 women) between the ages of 18 and 25 in our sample auxiliary from the US. Brackets contain p-values, to
facilitate comparison with the results reported in NV.
Table A2.2
Continuous effects of age on tournament entry, US sample.
Full sample Under 50
(1) (2) (3) (4)
Female âˆ’0.415âˆ—âˆ— âˆ’0.321 âˆ’0.089 0.076
(0.201) (0.282) (0.336) (0.475)
Female Ã— age 0.008 0.009 âˆ’0.006 âˆ’0.006
(0.006) (0.006) (0.011) (0.011)
Male Ã— age 0.004 0.006
(0.007) (0.012)
Piece rate âˆ’0.007 0.001 âˆ’0.033 âˆ’0.026
(0.026) (0.030) (0.036) (0.039)
Improvement âˆ’0.015 âˆ’0.008 0.004 0.011
(0.040) (0.042) (0.051) (0.053)
Guessed rank âˆ’0.129 âˆ’0.131 âˆ’0.225âˆ— âˆ’0.229âˆ—
(0.090) (0.091) (0.120) (0.121)
Submit piece-rate to tournament 0.349âˆ—âˆ—âˆ— 0.347âˆ—âˆ—âˆ— 0.364âˆ—âˆ— 0.369âˆ—âˆ—
(0.114) (0.114) (0.144) (0.144)
Observations 84 84 63 63
Estimated marginal effects from a Probit regression of the choice to select tournament
for round 3 (US sample). Columns 3 and 4 are restricted to participants under the
age of 50. The variable Female is an indicator for whether the participant is a woman.
Age is the continuous age of the individual, in number of years. Piece Rate measures
the number of successes in the first round, under the piece-rate regime. Improvement
measures the increase in number of successes between the first and second round.
Guessed Rank indicates the participantâ€™s stated belief about how well she performed,
relative to the three others in her group. Submit Piece-Rate to Tournament is an indicator for whether the participant chose to submit her past performance in round
1 (piece-rate) to a tournament against the past piece-rate performance of the other
members in her randomly assigned group. Standard errors shown in parentheses. âˆ—âˆ—âˆ—
p < 0.01, âˆ—âˆ— p < 0.05, âˆ— p < 0.1.
gender effects on competition tastes. On the other hand, the drop in estimated magnitude for Female by roughly a half when
moving from few controls to all the controls for other general factors (besides competition) occurs only in NV and in our
US sample of young adults. The reduction in moving from few controls to all controls does not seem to occur for the young
adults in Malawi. This suggests that, while the relationship between gender and competition preference is very similar for
young adults in Malawi and the US (NV students as well as our US young adults), the relationship between gender and the
other factors driving competition choice (such as risk and feedback preferences) may be different in Malawi than it is in the
US samples (ours as well as that in NV).
E. Continuous effects of age in US sample
Table A2.2 reports the results for the US examining the impact of a linear age term, both for the full sample and for the
sample of participants under the age of 50. This table is the analogue of Table 4 with the Malawi sample. None of the linear
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 271
age terms are significant in this sample. However with the smaller sample, it is dangerous to read too much into a series
of insignificant effects. Recall however that the inclusion of dummy for a woman over the age of 50 is highly significant in
this sample.
Appendix C. Additional robustness tests
Table A3.1 compares women over the age of 49 to men of all ages. It shows regressions identical to column 3 of
Tables 1 and 2 (the standard NV regression with the full set of controls to identify impacts on competition tastes), except that women under 50 are excluded from the sample. The coefficient estimate for Female thus represents the effect of
being female and 50 or older on propensity to enter the tournament due to changes in competition preference. In both
samples, this coefficient is positive, suggesting that women 50 and older have a stronger preference for competition than
men of all ages, holding other factors (risk aversion, feedback aversion, confidence, etc.) constant. However, while this might
be interpreted as mild evidence that older women may be more competitive than men, neither estimate is significant, so
we cannot conclude this with any degree of confidence. However, this shows very clearly that women over the age of 49
are no less competitive than men of all ages.
Table A3.2 examines the potential impact of a quadratic specification for age interacted with gender, including a discrete
effect at the age of 50, in our main sample. The table shows the coefficients (not the marginal effects) for a Probit and a
linear probability model, to allow better interpretation of the overall impact of age on preference for competition. Among
women, coefficient estimates are significant for all three age variables â€“ both the linear and quadratic terms as well as the
age 50 indicator. For men on the other hand, none of the age variables have a significant effect. To interpret the coefficient
magnitudes and the role of the quadratic term, we focus on the linear probability model. The estimate for Female implies
that a woman of age zero (outside of our sample) would be significantly less likely to compete than a man of age zero.
By the age of 18, the joint effects of gender and the linear and quadratic age terms imply that women are 20 percentage
points more likely to compete than at age zero. By the age of 49 women are 5 percentage points more likely to compete
than women at age 18 (or 25 percentage points more likely than the implied estimate for women at age zero). However,
by age 50, they are 28 percentage points more likely to compete than women at age 18 (or 48 percentage points more
likely than that implied for women at age zero). That is, the predicted change in propensity to compete, after controlling for
risk-aversion and other general factors, in moving from age 49 to 50 is an increase of 23 percentage points â€“ more than four
and a half times larger than the entire change in moving from age 18 to 49. To put these relative magnitudes in another
perspective, we note the estimates for the age variables imply that the maximum competitiveness for women under the
age of 50 occurs at age 38, and that the propensity to compete rises an estimated 7.4 percentage points in moving across
the twenty years from age 18 to the local peak at age 38. The estimated 23 percentage point rise across one year from
age 49 to 50 is over 3 times larger than the estimated 7.4 percentage point rise across the twenty years from age 18 to
38. Thus the estimated effect of the discrete change at age 50 is far larger than the estimated continuous effects of age
Table A.3.1
Comparing mature women to all men.
Main sample (MW) Auxiliary sample (US)
(1) (1)
Female 0.0737 0.107
(0.0725) (0.146)
Piece rate 0.0231âˆ—âˆ— âˆ’0.00734
(0.0110) (0.0290)
Improvement 0.0154 0.0166
(0.0208) (0.0428)
Guessed rank 0.000985 0.0324
(0.0274) (0.108)
Submit piece-rate to tournament 0.428âˆ—âˆ—âˆ— 0.458âˆ—âˆ—âˆ—
(0.0440) (0.136)
Observations 440 51
Estimated marginal effects from a Probit regression of the choice to select tournament
for round 3. The sample includes all men, but among women restricts to individuals
50 and older. Column 1 shows results from our main sample and column 2 shows
results from our US sample. The variable Female is an indicator for whether the participant is a woman. Piece Rate measures the number of successes in the first round,
under the piece-rate regime. Improvement measures the increase in number of successes between the first and second round. Guessed Rank indicates the participantâ€™s
stated belief about how well she performed, relative to the three other individuals
in her group. Submit Piece-Rate to Tournament is an indicator for whether the participant chose to submit her past performance in round 1 (piece-rate) to a tournament
against the past piece-rate performance of the other members in her randomly assigned group. Standard errors are shown in parentheses. âˆ—âˆ—âˆ— p < 0.01, âˆ—âˆ— p < 0.05, âˆ—
p < 0.1.
272 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Table A3.2
Jointly testing continuous and discrete effects of age.
Probit Linear probability
(1) (2)
Female âˆ’1.442âˆ—âˆ— âˆ’0.485âˆ—âˆ—
(0.593) (0.202)
Female Ã— Age 0.0435âˆ— 0.0144âˆ—
(0.0227) (0.00763)
Female Ã— Age2 âˆ’0.000582âˆ—âˆ— âˆ’0.000191âˆ—âˆ—
(0.000270) (8.96eâˆ’05)
Female over 49 0.684âˆ—âˆ— 0.231âˆ—âˆ—
(0.338) (0.116)
Male Ã— Age âˆ’0.0221 âˆ’0.00748
(0.0204) (0.00703)
Male Ã— Age2 0.000205 6.89eâˆ’05
(0.000227) (7.84eâˆ’05)
Male over 49 0.0872 0.0325
(0.372) (0.127)
Piece rate performance 0.0107 0.00398
(0.0240) (0.00824)
Improvement 0.0321 0.0107
(0.0390) (0.0133)
Guessed rank âˆ’0.00815 âˆ’0.00343
(0.0511) (0.0176)
Submit piece-rate to tournament 1.034âˆ—âˆ—âˆ— 0.385âˆ—âˆ—âˆ—
(0.101) (0.0347)
Constant âˆ’0.195 0.414âˆ—âˆ—
(0.488) (0.169)
Observations 727 727
Estimated coefficients from a Probit regression and Linear Probability regression of the choice to select tournament for round 3 (main sample).
The variable Female is an indicator for whether the participant is a woman.
Age is the continuous age of the individual, in number of years. Piece Rate
measures the number of successes in the first round, under the piece-rate
regime. Improvement measures the increase in number of successes between the first and second round. Guessed Rank indicates the participantâ€™s
stated belief about how well she performed, relative to the three others
in her group. Submit Piece-Rate to Tournament is an indicator for whether
the participant chose to submit her past performance in round 1 (piecerate) to a tournament against the past piece-rate performance of the other
members in her randomly assigned group. Standard errors shown in parentheses. âˆ—âˆ—âˆ— p < 0.01, âˆ—âˆ— p < 0.05, âˆ— p < 0.1.
in the quadratic specification. However both effects are statistically significant and continuous age impacts should not be
completely dismissed.
Appendix D. Experiment details and instructions
A. The task
The real effort task that we use was specifically designed to involve a simple cognitive exercise with very low education
requirements to participate â€“ arranging shapes in a row from smallest to largest. Each participant has a set of 6 blocks. Each
side of a given block has one of 6 shapes. The task is to arrange all 6 blocks such that a given shape (e.g., star) appears
facing up, and to align the 6 versions of that shape (e.g., all 6 stars) in order from smallest to largest. Upon completing one
shape, the participant moves to the next shape. The blocks are designed so that the blocks must continuously be rearranged
in moving from one shape to the next. All participants work with identical blocks and face the same order of shapes to
complete.
B. Information on choices
As in NV, before making the choice for round 3, participants are informed that if they choose competition, their group is
the same group they were placed in for round 2, and the performances they compete against are the round 2 performances.
That is, they would compete with individuals who had been forced to compete, rather than individuals who had self-selected
into competition. Before making the choice for round 4, participants are again informed that their group is the same group
they were randomly placed in for round 2, and this time the performances they compete against are the round 1 (piece-
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 273
rate) performances of the group. Thus, if they submit their piece-rate performance to competition, they compete with the
(round 1) performance of all individuals in their group, not just those who chose to compete.
C. Sampling
In Malawi, we drew participants from twelve different villages, recruiting from the entire village population. Each village
was visited a few days prior to the experiment, to notify residents and advertise the significant show up payment. We then
randomly selected participants from the large pool that arrived. In the US, we recruited participants in three waves. The
first set of sessions was conducted at a major university campus near the end of the work-day. We recruited participants
from staff, graduate students, and undergraduates. The second set of sessions was on a Saturday afternoon on campus,
with participants recruited from a farmerâ€™s market, a flea market, and a local swimming pool. This second session is the
only session in which the experiment took place in a different location than the recruitment. The third set of sessions was
conducted at a farmerâ€™s market, with participants recruited from the market, the nearby commuter rail station, and the
surrounding community.
D. Set-up and payment amounts
All sessions (Malawi and US) were conducted in a room large enough to hold all participants and that was similar in
size to standard experimental labs in the US. Since many adults are illiterate in rural Malawi, the instructions were read
aloud in both countries. Facilitators demonstrated how to perform the task, kept track of participantsâ€™ number of successes
in each round, and recorded participantsâ€™ choices. The only speaker during the session was the script-reader, who read the
instructions for the experiment. Each session lasted about an hour, and included on average 16 participants, equally balanced
between men and women. Procedures in the US were identical to those in Malawi. As in NV, participants are told they will
be paid for one of the four rounds, selected at random. At the end, they are asked how they believe their performance
compared to the others in their group for rounds 1 and 2, earning additional amount Y for correct guesses. Task payment
amounts were X = 50 kwacha (approx. $.33), Y = 20 kwacha (approx. $.13) in Malawi, and X = $1, Y = $0.50 in the US.
E. Additional explanation of protocol and controls generated
Rounds 1 and 2 serve to familiarize subjects with each pay scheme. In addition, the number of successes in the first
two rounds allows us to control for the influence of ability in the task (and any boost when competing) on the decision
to compete. This allows us to ensure, for example, that it is not simply ability that drives lower willingness to compete
among young women. The choice made in round 4 isolates the effects of sex and age on the preference for performing
in competition against others, independent from the effects they have on willingness to be rewarded based on a relative
evaluation. That is, the round 4 choice captures the influence of other factors that affect willingness to compete besides a
preference for performing under competition per se, such as risk-aversion, feedback-aversion or self-confidence. For example,
since risk preferences affect both the round 3 and round 4 choices, but only in round 3 does the participant enter and
compete in a tournament, the choice to compete in round 3 conditional on the choice in round 4 captures the preference
for competitive environments independent of risk preferences.
F. Instructions
Welcome
In the study today, we will ask you to complete a simple task in four different rounds. None of these rounds will take
more than 5 minutes. Because we are not simply asking you questions, but asking you to perform a task, we will pay your
for your work. You will receive {amount} at the beginning and at the end you will receive {amount} for having completed
the four rounds. In addition, you can earn more money based on your performance in one of the four rounds.
In order to participate in this study you must be at least 18 years old and you must agree to participate in the study or
you must have the permission of your parent or guardian.
We will now give you some information about the study today. In each round, we will ask you to do something that can
earn you money. When you are done here, you go to the cashier, he will put four cards into a bag, and you will pick one
of these cards from the bag without seeing the cards. These are the four cards, this one is for the first round, this one is
for the second round, this one is for the third round and this one is for the fourth round [speaker places cards in bag]. You
will be allowed to pick one just as this man is going to show you right now. He cannot see which card he will pick, but we
are not choosing the card. You will receive money according to how well you have done for the round that you pick from
the bag without seeing. We will explain to you exactly how you can earn money in each round. Some people will only earn
the show up fee today. Others will earn more. But everyone who begins will earn {amount} and everyone who finishes will
earn {amount} again.
This is the payment desk [speaker points]. When you are finished with the tasks, please go here to answer some questions
that we will ask and after that please come here to receive your payment.
274 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Explanation and practice round
Welcome to this study. Now your helper will give you the {amount} that we promised to give to you at the beginning of
the study. Today we will ask you to perform tasks and make decisions. If you listen carefully, you can earn a large amount
of money. So pay close attention to the instructions, and ask questions if you do not understand, because it may affect how
much money you earn.
Please do not talk with one another at any time during this study. I am happy to answer any questions you have at any
time. But please direct your questions only to me. The person sitting in front of you is here to help show you the task, and
to record the decisions that you make. They are not allowed to help you make decisions; please do not ask them for help
with the decisions we ask you to make.
You see the blocks that are in front of you. Please look at them and see the shapes and colors on each of the blocks.
Take one of the blocks and show your helper each of the shapes on the block as he points to it on the paper in front of you.
Every shape shown on the paper is shown on each of the blocks. The task we will ask you to perform today is to arrange
the shapes in order from smallest to largest. The person helping you will now demonstrate for you how to complete the
task. First, your helper will show you how to find all of the circles. When all of the circles are facing up, he or she will put
them in order from the smallest circle to the largest circle. The circles are now finished and they are finished correctly. The
task is complete.
We will now ask you to practice doing the task one time. Your helper will now turn your card to the next shape, which
is a square. We want you to perform the task for the squares. When you think you are finished, look at your helper for
confirmation. If you have completed the task correctly, your helper will nod his head. If you are incorrect, he will shake his
head, and you must continue until the squares are arranged from smallest to largest.
The way you are paid for this task will change each round. So pay close attention to these rules each round and be
sure you understand them, because they will affect how much money you can earn in that round. For each round, we will
explain the rules, before we ask you to begin. Please do not begin until we tell you to.
We will ask you to perform this task as many times as you can within 3 min. As soon as you finish arranging the blocks
for one shape, look to your helper and he or she will indicate to you whether you may move to the next shape. If he nods
his head, then turn the paper in front of you to show the next shape and then begin the next shape. If your facilitator
shakes his head this means you have not correctly completed the task and you need to keep trying. You have 3 min to
complete as many shapes as possible. The number of tasks that you complete is recorded on the paper but we will never
tell anyone else how you have done.
Does anyone have any questions about how to perform the task?
Round one: individual performance
We will now begin round one. Before we begin, we will explain how you will be paid for the tasks this round: If Round
1 is the task that you draw from the bag at the end, then you get {X} for each shape you successfully complete. For example,
if you complete one set of shapes you receive {X}, if you complete two sets of shapes you receive {2X}, if you complete three
sets of shapes you receive {3X}, if you complete four sets of shapes you receive {4X}, and so on for as many shapes as you
complete. We call this individual performance. This is represented by the single person standing alone in the picture in front
of you.
Please do not talk during the task or after you have finished. This is very important. If you have any questions, please
raise your hand and ask me now. Once we begin, you cannot ask any questions. Do you have any questions before we begin?
Are the facilitators ready? [When ready:] Okay, go. [When time is up:] Okay, everyone please stop now.
Round two: compared performance
Now we will move to the second round. For this round, the task is exactly the same. However, the way you are paid is
now different. In this round, your payment depends on your performance compared to a group of other participants. Each
group consists of four people. The three other members of your group come from other participants. Your group members
may be in this room right now, but they may not be. You will never know the names of the other people in your group and
they will never know your name. The person sitting next to you is not in your group. Do you have any questions about who
is in your group? If you have a question, please raise your hand and ask me now.
We will now explain how your payment is determined in this round. If round 2 is the task that you draw from the bag
at the end, then your earnings depend on your number of successes compared to the three other people in your group. If
you complete the most shapes in 3 min out of anyone in your group, you receive {4X} for each set you complete. But if
someone else in your group completes the most shapes, you receive nothing.
One times {4X} is {4X}. Two times {4X} is {8X}. Three times {4X} is {12X}. Four times {4X} is {16X}. And so on. We call
this compared performance. This is represented by the group of 4 people standing together in the picture in front of you. You
will not know how you did in the compared performance until the end of todayâ€™s activity, when you receive your earnings.
Please do not talk during the task or after you have finished. This is very important. If you have any questions, please
raise your hand, and ask me now. Once we begin, you cannot ask any questions. Do you have any questions before we
begin?
Are the facilitators ready? [When ready:] Okay, go. [When time is up:] Okay, everyone please stop now.
J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276 275
Round three: choice of payment scheme, before doing task
Now we will move to the third round. The task in this round is exactly the same, but now you can choose which way
you want to be paid. If round 3 is the one that you draw from the bag, then your earnings for this task are determined as
follows. If you choose individual performance, you receive {X} per success and you will not be compared to anyone else.
If you choose compared performance your payment for this round is similar to the payment in round two. The only
difference is that your performance in this round is compared to the performance of the other three members of your
group for round 2, the one we just finished, instead of being compared to their performance this round. If you complete the
task more times than the other people in your group did for round 2 then you will receive four times the payment from
the individual performance, which is {4X} per success. You will receive no earnings for this round if you choose compared
performance and you do not complete more sets of shapes than the other people in your group did for round 2.
Notice that this round is a little different than last round because nothing you do in this round can affect the earnings
of other people in your group, and nothing that other people in your group do this round can affect your earnings from this
round.
You will not know how you did in the compared performance until the end of todayâ€™s activity, when you receive your
earnings. Do you have any questions? If you have any questions, please ask me now.
Please do not talk as you are making your decision. If you would like to choose individual performance, please point to
the picture of one person. If you would like to choose compared performance please point to the picture of the group.
Please do not talk during the task or after you have finished. Are the facilitators ready? [When ready:] Okay, go. [When
time is up:] Okay, everyone please stop now.
Round four: choose scheme for past performance
For this new round, you do not have to do any tasks. Instead, you may be paid one more time for how you did in the
first round of the experiment. Now we are going to ask you how you would like to be paid for the tasks that you completed
in the first round. You can choose to be paid for your individual performance or compared performance.
If the fourth round is the one selected for payment, then your earnings for this round are determined like this. If you
choose individual performance, you receive {X} per success you had in round 1. If you choose compared performance, your
performance will be compared to the performance of the other three members of your group in the first round. If you
completed the task more times in round 1 than they did in round 1, then you receive four times the earnings of the
individual performance choice, which is {4X} per success. If you choose compared performance and you did not complete
the task more times than others did in round 1 you will receive no earnings for this round. Do you have any questions? If
you have any questions, please ask me now.
Please do not talk as you are making your decision. Now your helper will show you how many times you successfully
completed the sets of shapes in the first round. Now your helper will show you a picture. If you would like to choose
individual performance, please point to the picture of the one person. If you would like to choose compared performance
please point to the picture of the group.
Belief-assessment questions
We will now ask you how you think you performed in the tasks, compared to the 3 other people in the group we
assigned you to, for the first two rounds. You will earn {Y} for each correct guess. Please look at the picture of the four
people. The highest person completed the most sets of shapes in your group; he is first in the group. The next person
completed the second-most sets of shapes in your group; he is second. The next person completed the third-most sets of
shapes; he is third. The final person completed the least sets of shapes in your group; he is fourth.
We will first ask you how you think you performed in Round 1, the individual performance. If you are correct, you will
be paid an additional {Y} when we pay you your earnings. Before we ask you, do you have any questions? If you have any
questions, please ask me now.
Please do not talk as you are making your decision. Now please silently show your helper how you think you performed
in Round 1, the individual performance, compared to the other people in your group, by pointing to the position in the
picture. Do you think you were the best? Do you think you were the second-best? Do you think you were third-best? Or,
do you think you were last?
We will now ask you how you think you performed in Round 2, the compared performance. If you are correct, you will
be paid an additional {Y} when we pay you your earnings.
Please do not talk as you are making your decision. Now please silently show your helper how you think you performed
in Round 2, the compared performance, compared to the other people in your group, by pointing to the position in the
picture. Do you think you were the best? Do you think you were the second-best? Do you think you were third-best? Or,
do you think you were last?
Thank you very much for your participation today. You can go now. Please go to there to answer some questions for our
study.
References
AlmÃ¥s, I., Cappelen, A.W., Salvanes, K.G., SÃ¸rensen, E.Ã˜., Tungodden, B., 2015. Willingness to Compete: Family Matters. Management Science 62 (8),
2149â€“2162.
276 J.A. Flory et al. / Journal of Economic Behavior and Organization 150 (2018) 256â€“276
Andersen, S., Ertac, S., Gneezy, U., List, J.A., Maximiano, S., 2013. Gender, competitiveness, and socialization at a young age: evidence from a matrilineal and
a patriarchal society. Rev. Econ. Stat. 95 (4), 1438â€“1443.
Apicella, C.L., Dreber, A., Gray, P.B., Hoffman, M., Little, A.C., Campbell, B.C., 2011. Androgens and competitiveness in men. J. Neurosci., Psychol. Econ. 4 (1),
54.
Balafoutas, L., Kerschbamer, R., Sutter, M., 2012. Distributional preferences and competitive behavior. J. Econ. Behav. Org. 83 (1), 125â€“135.
Bateman, A.J., 1948. Intra-sexual selection in drosophila. Heredity 2, 349â€“368.
Booth, A., Nolen, P., 2012. Choosing to compete: how different are girls and boys? J. Econ. Behav. Org. 81, 542â€“555.
Brinig, M.F., 1995. Does mediation systematically disadvantage women? William Mary J. Women Law 2 (1), 1â€“34.
Buser, T., Niederle, M., Oosterbeek, H., 2014. Gender, competitiveness, and career choices. Q. J. Econ. 1409, 1447.
Buser, T., 2012. The impact of the menstrual cycle and hormonal contraceptives on competitiveness. J. Econ. Behav. Org. 83 (1), 1â€“10.
Buser, T., L. Geijtenbeek, and E. Plug. 2015. Do Gays Shy Away from Competition? Do Lesbians Compete too Much? Working Paper.
Buser, T., Dreber, A., Mollerstrom, J., 2017. The impact of stress on tournament entry. Exp. Econ. 20 (2), 506â€“530.
Campbell, A., 2002. A Mind of Her Own: The Evolutionary Psychology of Women. Oxford University Press, Oxford, UK 2002.
Campbell, A., 2004. Female competition: causes, constraints, content, and contexts. J. Sex Res. 41 (1), 16â€“26.
Cardenas, J.C., Dreber, A., von Essen, E., Ranehill, E., 2012. Gender differences in competitiveness and risk taking: comparing children in Columbia and
Sweden. J. Econ. Behav. Org. 83 (1), 11â€“23.
Cassar, A., Wordofa, F., Zhang, Y.J., 2016. Competing for the benefit of offspring eliminates the gender gap in competitiveness. Proc. Natl. Acad. Sci. 113,
5201â€“5205.
Charness, G., Villeval, M.-C., 2009. Cooperation and competition in intergenerational experiments in the field and the laboratory. Am. Econ. Rev. 99 (3),
956â€“978.
Croson, R., Gneezy, U., 2009. Gender differences in preferences. J. Econ. Lit. 47, 448â€“474.
Darwin, C., 1871. The Descent of Man, and Selection in Relation to Sex. John Murray, London.
Dekel, E., Scotchmer, S., 1999. On the evolution of attitudes towards risk in winner-take-all games. J. Econom. Theory 87 (1), 125â€“143.
DellaVigna, S., List, J.A., Malmendier, U., Rao, G., 2013. The importance of being marginal: gender differences in generosity. Am. Econ. Rev. 103 (3), 586â€“590.
Dreber, A., von Essen, E., Ranehill, E., 2011. Outrunning the gender gap â€“ boys and girls compete equally. Exp. Econ. 14 (4), 567â€“582.
Dreber, A., von Essen, E., Ranehill, E., 2014. Gender and competition in adolescence: tasks matter. Exp. Econ. 17 (1), 154â€“172.
Flory, J.A., Leibbrandt, A., List, J.A., 2015. Do competitive workplaces deter female workers? A large-scale natural field experiment on gender differences in
job-entry decisions. Rev. Econ. Stud. 82 (1), 122â€“155.
Gillen, B., Snowberg, E., Yariv, L., 2015. â€œExperimenting with Measurement Error: Techniques with Applications to the Caltech Cohort Study.â€. National
Bureau of Economic Research Working Paper No. 21517.
Gneezy, U., Rustichini, A., 2004. Gender and competition at a young age. Am. Econ. Rev. 94 (2), 377â€“381.
Gneezy, U., Leonard, K.L., List, J.A., 2009. Gender differences in competition: evidence from a matrilineal and a patriarchal society. Econometrica 77 (5),
1637â€“1664.
Gneezy, U., Niederle, M., Rustichini, A., 2003. Performance in competitive environments: gender differences. Q. J. Econ. 118 (3), 1049â€“1074.
Gold, E.B., 2011. The timing of the age at which natural menopause occurs. Obstetr. Gynecol. Clin. 38 (3), 425â€“440.
Gupta, N.D., Poulsen, A., Villeval, M.C., 2013. Gender matching and competitiveness: experimental evidence. Econ. Inq. 51 (1), 816â€“835.
Harbaugh, W.T., Krause, K., Vesterlund, L., 2002. Risk attitudes of children and adults: choices over small and large probability gains and losses. Exp. Econ.
5 (1), 53â€“84.
Mayr, U., Wozniak, D., Davidson, C., Kuhns, D., Harbaugh, W.T., 2012. Competitiveness across the life span: the feisty fifties. Psychol. Aging 27 (2), 278â€“285.
National Institute on Aging. 2013 AgePage: Menopause. https://www.nia.nih.gov/health/publication/menopause.
Niederle, M., Vesterlund, L., 2007. Do women shy away from competition? Do men compete too much? Q. J. Econ. 122, 1067â€“1101.
Niederle, M., Vesterlund, L., 2011. Gender and competition. Annu. Rev. Econ. 3, 601â€“630.
Niederle, M., Segal, C., Vesterlund, L., 2013. How costly is diversity? Affirmative action in light of gender differences in competitiveness. Manag. Sci. 59 (1),
1â€“16.
Robson, A.J., 1996. The evolution of attitudes to risk: lottery tickets and relative wealth. Games Econ. Behav. 14, 190â€“207.
Robson, A.J., Samuelson, L., 2009. The evolution of time preference with aggregate uncertainty. Am. Econ. Rev. 99 (5), 1925â€“1953.
Rutstein, S.O., Rojas, G., 2006. Guide to DHS Statistics. United States Agency for International Development.
Sutter, M., and D. RÃ¼tzler. 2010. Gender Differences in Competition Emerge Early in Life. IZA Discussion Paper 5015; available at http://ftp.iza.org/dp5015.pdf.
Trivers, R.L., 1972. Parental investment and sexual selection. In: Campbell, B. (Ed.), Sexual Selection and the Descent of Man. Aldine, Chicago, pp. 136â€“177.
Woods, N.F., Carr, M.C., Tao, E.Y., Taylor, H.J., Mitchell, E.S., 2006. Increased urinary cortisol levels during the menopause transition. Menopause 13 (2),
212â€“221.
Woods, N.F., Mitchell, E.S., Smith-DiJulio, K., 2009. Cortisol levels during the menopausal transition and early postmenopause: observations from the Seattle
Midlife Womenâ€™s Health Study. Menopause 16 (4), 708â€“718.
Wozniak, D., Harbaugh, W.T., Mayr, U., 2014. The menstrual cycle and performance feedback alter gender differences in competitive choices. J. Labor Econ.
32 (1), 161â€“198.
Zhong, S., Shalev, I., Koh, D., Ebstein, R.P., Chew, S.H., 2018. Competitiveness and stress. Int. Econ. Rev. forthcoming.

Real Reviews from our Customers

Academic Writing Service of a Professional Level

Any academic writer who wishes to join our team of professional writers must possess all the following qualities:

To write an exemplary academic paper, you must have good critical thinking skills, possess the proper knowledge of the discipline, and be knowledgeable about applying an academic writing style.

As such we have a rigorous recruitment process. We only collaborate with professional academic writers. We believe in offering the highest quality academic writing services. Our writers pass various grammar and academic writing tests. They have to provide documents about their personal information and credentials to prove their level of expertise.

As a result, our clients receive papers that are thoroughly-researched, properly cited, and written within academic standards. We are proud that any academic writer from our writer's team can complete the paper at a high standard.

We work with the student’s budget because we know that students are usually on a budget majority of the time. We do not compromise on quality because of low prices. On the contrary, we love to foster a good relationship with our clients. That is why we charge our clients reasonable prices, and we are willing to negotiate and work with their budget.

It may be quite disturbing to decide whether to hire an academic writing company. We care about our client’s privacy and confidentiality. We never disclose your information to third parties. We never publish your paper online. You can use our academic writing service without any fear or anxiety.

Many students struggle with writing academic papers. Some barely have time to do their assignments because of their job and family responsibilities. Others have difficulty applying critical thinking skills or meeting time or assignment requirements. Whatever the reason is, you can always have time to do the things you love and other important things. All you need is a reliable and quality academic writing service. Unfortunately, even if you strongly desire to write the paper yourself, you sometimes face unexpected challenges. As we all know, life is unpredictable! Your teacher may be unconcerned about helping students and may not answer your questions. The good news is that there is a way out! You can hire an online academic writer to help you with your assignments. All you need to do is stipulate your paper requirements in the order form, and you can spend your time as you like.

Our Mission

Our company commits towards delivering high-quality custom papers to our clients. We seek to offer reliable essay writing services to our customers in various subject areas. Our customers are very valuable to us. As such, we commit to ensuring that they derive the utmost satisfaction from the essays we deliver. We have a mission to promote our clients' educational and professional lives by providing high-quality essays for their use. We also have a mission to offer a convenient essay writing system where our customers can easily order and pay for the services. We value quality and professionalism in our company.

Get professional help from our brilliant, skilled, and experienced essay writers

We write papers on any subject area, and we also write various types of papers for various purposes. We have a team of able writers who are eager to help our customers with writing services of exceptional quality. We offer custom writing services for customers across the globe and charge affordable prices for our services. We are the best essay writing company offering personalized services to all our customers. We ensure our customers receive maximum satisfaction from the essays we deliver. Our website is the place to be if you are seeking high-quality essays.

By using our academic writing service, we match your paper subject with a writer with a degree in the subject. The writer is able to apply their skills, knowledge, and expertise to the paper. You receive an original, unique, well-research paper, properly cited and formatted. As such, you are assured of a high-quality paper.

Academic Writing Help From Professionals

Truth be told, writing assignments can be stressful and difficult for any student. There is no shame in getting academic writing help. When you search the term “get academic writing help” there are numerous sites that pop up on the results and our website is among them. So, why is it a great idea to choose us?

During your course, your instructor will assign various types of homework. Our academic writers can prepare essays, presentations, speeches, case studies, research papers, dissertations, thesis papers, and more. Our writer’s department is capable of tackling any assignment of any complexity easily. All you need is to give us detailed instructions to help our experts understand the task.After doing so, you can rest assured that everything is in control, and we will deliver a paper of unmatchable quality.

Expert Assignment Help for College/University Students

Are you a college or university student pursuing your Bachelor’s , Masters, PhD, or Doctorate degree? Sometimes juggling schoolwork with work, family and hobbies can seem like a daunting task. You have to sacrifice one or the other. The sole purpose of our website is to alleviate your academic burdens. We ensure that you do not fail in your classes and you get good grades consistently. We understand that there is a need for academic help.

We acknowledge that our clients are not dumb or lazy but only need academic life need help in order to live a balanced life and make ends meet. We make it our core priority to ensure that all assignments are done and submitted before the stipulated deadlines. All our writers are graduates. They are competent in handling the clients’ assignments. We step in to help you with any and all of your assignments. Our assignment help service ensures that you never miss a grade or deadline.

Proceed to order page

Online Academic Help With Different Subjects

Literature

Students barely have time to read. We got you! Have your literature essay or book review written without having the hassle of reading the book. You can get your literature paper custom-written for you by our literature specialists.

Finance

Do you struggle with finance? No need to torture yourself if finance is not your cup of tea. You can order your finance paper from our academic writing service and get 100% original work from competent finance experts.

Computer science

Computer science is a tough subject. Fortunately, our computer science experts are up to the match. No need to stress and have sleepless nights. Our academic writers will tackle all your computer science assignments and deliver them on time. Let us handle all your python, java, ruby, JavaScript, php , C+ assignments!

Psychology

While psychology may be an interesting subject, you may lack sufficient time to handle your assignments. Don’t despair; by using our academic writing service, you can be assured of perfect grades. Moreover, your grades will be consistent.

Engineering

Engineering is quite a demanding subject. Students face a lot of pressure and barely have enough time to do what they love to do. Our academic writing service got you covered! Our engineering specialists follow the paper instructions and ensure timely delivery of the paper.

Nursing

In the nursing course, you may have difficulties with literature reviews, annotated bibliographies, critical essays, and other assignments. Our nursing assignment writers will offer you professional nursing paper help at low prices.

Sociology

Truth be told, sociology papers can be quite exhausting. Our academic writing service relieves you of fatigue, pressure, and stress. You can relax and have peace of mind as our academic writers handle your sociology assignment.

Business

We take pride in having some of the best business writers in the industry. Our business writers have a lot of experience in the field. They are reliable, and you can be assured of a high-grade paper. They are able to handle business papers of any subject, length, deadline, and difficulty!

Statistics

We boast of having some of the most experienced statistics experts in the industry. Our statistics experts have diverse skills, expertise, and knowledge to handle any kind of assignment. They have access to all kinds of software to get your assignment done.

Law

Writing a law essay may prove to be an insurmountable obstacle especially when you need to know the peculiarities of the legislative framework. Take advantage of our top-notch law specialists and get superb grades and 100% satisfaction.

Affordable prices

HIGH SCHOOL

from

$10 page

COLLEGE

from

$13 page

UNIVERSITY

from

$14 page

Our prices depend on the urgency of your assignment, your academic level, the course subject, and the length of the assignment. Basically, more complex assignments will cost more than simpler ones. The level of expertise is also a major determinant of the price of your assignment.

Calculate price

Cheap essay writing service

If you need professional help with completing any kind of homework, is the right place to get it. Whether you are looking for essay, coursework, research, or term paper help, or with any other assignments, it is no problem for us. At our cheap essay writing service, you can be sure to get credible academic aid for a reasonable price, as the name of our website suggests. For years, we have been providing online custom writing assistance to students from countries all over the world, including the US, the UK, Australia, Canada, Italy, New Zealand, China, and Japan.

Our cheap essay writing service has already gained a positive reputation in this business field. Understandably so, since all custom papers produced by our academic writers are individually crafted from scratch and written according to all your instructions and requirements. We offer APA, MLA, or a Chicago style paper in almost 70 disciplines. Here, you can get quality custom essays, as well as a dissertation, a research paper, or term papers for sale. Any paper will be written on time for a cheap price.

Using our cheap essay writing help is beneficial not only because of its easy access and low cost, but because of how helpful it can be to your studies. Buy custom written papers online from our academic company and we won't disappoint you with our high quality of university, college, and high school papers. Although our writing service is one of the cheapest you can find, we have been in the business long enough to learn how to maintain a balance between quality, wages, and profit. Whenever you need help with your assignment, we will be happy to assist you.

Proceed to order page

Cheap paper writing service provides high-quality essays for affordable prices

It might seem impossible to you that all custom-written essays, research papers, speeches, book reviews, and other custom task completed by our writers are both of high quality and cheap. It is surprising, but we do have some tricks to lower prices without hindering quality.

To start using our services, it’s enough to place a request like “I need a writer to do my assignment” or “Please, write an essay for me.” We have a convenient order form, which you can complete within minutes and pay for the order via a secure payment system. The support team will view it after the order form and payment is complete and then they will find an academic writer who matches your order description perfectly. Once you submit your instructions, while your order is in progress and even after its completion, our support team will monitor it to provide you with timely assistance.

Affordable essay writing service: get custom papers created by academic experts

Hiring good writers is one of the key points in providing high-quality services. That’s why we have entry tests for all applicants who want to work for us. We try to make sure all writers working for us are professionals, so when you purchase custom-written papers, they are of high quality and non-plagiarized.

Our cheap essay writing service employs only writers who have outstanding writing skills. The quality of all custom papers written by our team is important to us; that is why we are so attentive to the application process and employ only those writers who can produce great essays and other kinds of written assignments. All our writers are graduates. They are competent in handling the clients’ assignments. We step in to help you with any and all of your assignments. Our assignment help service ensures that you never miss a grade or deadline.

Plagiarism-free affordable papers

All our cheap essays are customized to meet your requirements and written from scratch. Our writers have a lot of experience with academic papers and know how to write them without plagiarism. Moreover, at our academic service, we have our own plagiarism-detection software which is designed to find similarities between completed papers and online sources. You can be sure that our custom-written papers are original and properly cited.

Our essay writing service has a 0% plagiarism tolerance. We are well aware of the dangers of plagiarism. Plagiarism is academic suicide. Our essay writing service ensures that all papers are original. We do not sell pre-written papers. All papers are written from scratch as per the instructions. We pass our papers through powerful anti-plagiarism software such as SafeAssign and TurnItIn.

Money-back guarantee

Our cheap essay writing service tries to always be at its best performance level, so each customer who pays money for paper writing can be sure that he or she will get what is wanted. On the off chance that you don’t like your order, you can request a refund and we will return the money according to our money-back guarantee.

There can be a number of reasons why you might not like your order. If we honestly don’t meet your expectations, we will issue a refund. You can also request a free revision, if there are only slight inconsistencies in your order. Your writer will make the necessary amendments free of charge. You can find out more information by visiting our revision policy and money-back guarantee pages, or by contacting our support team via online chat or phone.

On-time Delivery

We know how important any deadline is to you; that’s why everyone in our company has their tasks and perform them promptly to provide you with the required assistance on time. We even have an urgent delivery option for short essays, term papers, or research papers needed within 8 to 24 hours.

We appreciate that you have chosen our cheap essay service, and will provide you with high-quality and low-cost custom essays, research papers, term papers, speeches, book reports, and other academic assignments for sale. We beat all deadlines. We can also handle urgent orders with deadlines as short as 1 hour. Our urgent paper writing service does not compromise on quality due to the short deadline. On the contrary, our essay writers have a lot of experience which comes in handy in such situations.

24/7 support

We provide affordable writing services for students around the world. That’s why we work without a break to help you at any time, wherever you are located. Contact us for cheap writing assistance. Our impeccable customer support team will answer all your questions and help you out with any issues.

Proceed to order page

Continue to order Get a quote

Journal of Economic Behavior and Organization

undifined, undifined

Journal of Economic Behavior and Organization 13 (1990) 145-169. North-Holland
LESSONS FROM PRIVATIZATION IN BRITAIN
State Enterprise Behavior, Public Choke, ad
Richard E. CAVES
Hmurd Uniuersity, Cambridge, MA 02138, USA
(Received February 1989, fir.& version received May 1989)
The process of privatizing most of Britains major public enterprises yields interesting conciusions on three related issues: (1) A problem of policy assignment arose in the use of privatization
and liberalization to achieve both allocative and productive efficiency. 12) Evidence on the
behavior of the public enterprises is consistent with an organizational model of the relevant
principal-agent relationships predicting certain types of dack absorption. (3) The wvatization
process entailed policy choices that bear on their future productive efiiciency (effdveness of
monitoring by the market for corporate control) and allocative efficiency (provision for
regulation).
1. Iatmduction
A principal policy of the Thatcher government has been the transfer of
public-sector enterprises and other activities and assets to the United
Kingdoms private sector. This policy is broadly a counterpart of deregulation in the United States [Swarm (1988)], and it has been in 616: vanguard
of privatizations in many other countries with . This
major change in economic organization and governance represents an
important laboratory experiment. The obvious question – the relative
performance of the privatized enterprises under public and private ownership
– unfortunately cannot receive an immediate answer, because of the time
needed for equilibrium private performance to reveal itself. Nonetheless, the
*An earlier version was presented at meetings of the American Economic Association,
December 1987. This research was supported by the Division of Research, Harvard Business
School. I am grateful for assistance and suggestions to William James Adams, Steven W. Davies,
J. Denys Gribbin and Timothy Sorenson.
The U.S. Presidents Commission on Privatizatior (1988) similarly recommended d broad
privatization or contracting out of the smaller number of public-sector firms and activities found
in the United States.
A substantial literature exists on the comparative performance of public and private
enterprises in various countries [e.g. Miilward (1982)], but it gains strong leverage only in
selected situations where public and private enterprises can be found operating in comparable
markets. Public enterprises (for obvious reasons of public choice) are often distinctive or
dominant firms in unique markets, making the assessment of their performance an imprecise
task, Most of the privatized U.K. enterprises fail into this class.
0167-2681/90/$3.50 0 1990, Eisevier Science Publishers .V. (North-Holland)
146 RX. Caves, Lessons from privatization in Britain
process of privatization itself has revealed a great deal about the behavior of
state-owned enterprises (SOEs) and the issues of corporate governance that
arise in the privatization process. These two topics possess more unity than
first appears, because the logic of the principal-agent relation between the
managers of an enterprise and the residual claimants on its income bears
strongly on both.
This paper surveys of the lessons cast up by privatization in the United
Kingdom about economic behavior and organization. The argument of its
three main sections proceeds as follows:
(I) Privatization (in Britain as elsewhere) has been driven by the belief that
private ownership changes the erstwhile SOEs motives so as to increase
its productive efftciency. But that infusion of the profit motive should
also increase its propensity to seek monopoly profits and thereby distort
allocative efficiency. The first section discusses this normative dilemma as
it affected U.K. policy makers.
(2) If privatization indeed shifts business motives so as to focus the
managers objectives more sharply on profit maximization (cost minimization), then the SOEs activities before privatization should be explicable
as behavior that pursues some goal other than profit-maximization. The
privatirzation process a;rd concurrent research on the SOEs can be
reviewed for its consistency with such a behavioral framework.
(3) The process of privatization itself has entailed many choices for British
policy-makers that will affect the efficiency of the market for corporate
control, which will serve as a regulator of the privatized SOEs efficiency.
Some decisions implicitly traded off the maximum effectiveness of the
market for corporate control against various other objectives of public
policy.
Certain features of the historical background provide perspective to the
privatization decisions of the 1980~.~ Britains SOEs came into being at
various times – mostly the 1930s and 1940s – under widely differing
circumstances, but always in response to some public dissatisfaction with the
pricing, efficiency, growth (or shrinkage) rate, or other allocations chosen by
private business. Each statute creating a public corporation included an
instruction that the directors should pursue the public interest. This interest
was specified no more precisely than that, for example, the enterprise should
operate efftciently and economically, set reasonable charges, and/or promote
the development of its market [Robson (1962)]. Ministers responsible to
Parliament were supposed to issue general instructions articulating the public
interest; they were sul_posed not to indulge in ad hoc interventions.
3The many published accounts of this background include Robson (1962); Curwen (1986); and
Vickers and Yarrow (1988).
R.E. Caves, Lessons from privatization in Britain 147
The general Bone of researchers evaluations of the SOW prfoman=
fluctuated over the years, but by the late 1970s it had settled at a low !evel.4
During that decade a series of public inquiries and reports sought to
establish either more specific economic objectives for the public enterprises
or more effective organizational arrangements for their supervision. The
economic objectives generally concerned efftcient pricing and investment
decisions, the limitation or public exposure of cross-subsidy among customer
groups, and Government scrutiny and approval of the SOEs noncommercial
objectives. But the enterprises could not, or at least did not, implement
these refined allocation rules. In fact, in the 1970s most of them ran large
deficits that lacked explicit public-interest rationales but ;:I the aggregate
represented a marked drain on the Treasury. Late in that decade a cruder
(but, in the event, effective) rule was imposed on the SOEs in the form of
external financing limits, which restricted the gaps between the enterprises
revenues and the sum of their current and investment outlays. What began
as an effort to define the public interest arrived at nothing more than a
restriction on the SOEs ability to increase the government deficit [Vickers
and Yarrow (1988, pp. 133-134)].
When the Thatcher government was first elected in May 1979, public
corporations accounted for 10.5 percent of gross domestic product, employed
8.1 percent of the workforce and 17.2 percent of the net capital stock? The
policy of privatizating SOEs began unobtrusively with the sale of part of the
governments shares in British Petrcleum. It continued through the early
1980s with the privatization of firms in the aerospace, telecommunications
operation, petroleum, radio-chemicals, automobiles (Jaguar), banking
services, and highway freight transportation, and the sale of government
shareholdings in the sugar-refining and electronics industries. It then proceeded into the traditional public-utilities sector with seaports, long-distance
bus transportation, ferries, telecommunications, natural-gas distribution, airlines, major airports, and . The
Thatcher government has committed itseif to privatize British Steel, electricity, and water supply. The coal industry and the railways remain on the
horizon.
ivatization, li~rali~tio~ and economic performance
The privatization policy arose from a generalized faith in market incentives
and not from any explicit consideration of agency and motivation problems
4Prykes (1981) influential study is representative. Redwood and Hatch (1982) stressed the
unsystematic and ad hoc nature of most ministerial interventions into SOEs behavior.
This approach came to the fore in the White Paper issued in 1967, Nationalised Industries: A
Review oj- Econamic and Financial Objectives, Cmnd. 3437 (1967).
6Calculations from public data reported by Vickers and Yarrow (1988, p. 140).
A <vstematic summary was provided by Vickers and Yarrow ( 1988, pp. 160-169).
148 R.E. Caves, L,essons from privatization in Britain
in SOEs. There was no public debate framed in terms of privatization versus
the status quo. However, a patchwork debate did occur over the policy
payouts of privatization versus liberalization [Kay and Silberston (1984);
Sharpe (1984); Thompson (1988)]. Because British SOEs have commonly
been protected by statute from the entry of private-sector competitors,*
liberalizing the rules for would-be competitors was presented variously as an
alternative and a complement to privatization. The question is reviewed here
for two reasons. First, the payouts of privatization and liberalization pose a
problem of the standard policy assignment form, although that context was
not recognized. Second, and more relevant to the balance of this paper, the
payouts to application of these policies to a particular SOE depend on the
public firms actual allocative choices and thus its motivation.
Changes in the efficient use of economic resources in a market following a
shift of policy can take two forms – changes in allocative eflciency (alignment
of prices to marginal costs) and in technical or productive eflciency (minimization of the cost of the output prodused). A SOEs performance might
warrant a policy change if it displays nonoptimal performance in either or
both dimensions. The prospective effectiveness of privatization and liberalization depends on both the extent (and direction, in the case of allocative
inefficiency) of the two performance deficiencies and the efficacy of the two
policies for correcting them.g
Liberalization has the potential of unleashing private-sector competitors
who in the best case could preclude a public enterprise from either charging
a price above its actual marginal costs or incurring costs above the minimal
level. The ideal target for liberalization is a public-sector monopoly astride
an industry whose underlying structure is consistent with a purely competitive organization of the market. Theoretically, a sufficient number of entrants
arrive to enforce competitive prices, and it their levels of technical efficiency
match the SOEs, they preclude it from covering its costs unless those co&
are minimized. l0 Liberalization is insufficient to assure allocative efficiency if
the public enterprise enjoys an uncontestable natural monopoly [Sharkey
(1982)] or one of the many first-mover advantages identified in recent
economic research on strategic entry deterrence [Gilbert (1986)]. Finally,
liberalization cannot force allocative efficiency on a SOE that can and does
*The exact degree of statutory and effective protection from competitors varies in ways that
will not be developed here. Relatively complete protection is (or was) accorded in telecommunications, postal service (first-class mail), gas distribution, electricity generation and distribution,
scheduled air service, and intercity bus and rail service. At the opposite pole, no statutory
protection was enjoyed by public enterprises in automobiles and steel. Still other enterprises
were in intermediate situations, facing competition from substitute goods and services (ferries) or
from rivals located in other countries (aircraft manufacture, international airline service). Details
can be found in surveys such as Vickers and Yatrow (1988) and Pryke (1981).
Anot her app-0 1 ,ach to these issues is provided by Jones, Tandon and Vogelsang (forthcoming).
Proving that competition assures productive efftciency in the face of principal-agent
problems has turned out to be a tricky matter. See Wart (1983) and Scharfstein (1988).
R.E. Cwes, Lessons from privatization in Britain 149
charge too low a price (relatively to its marginal cost) and consequmtly
produces more than an eflicient, competitive output.
Similarly, liberalization suffices to assure technical efficiency only when the
SOE operates in an industry with the structural potential for enforcing
competitive pricing. If competition (actual or potential) is insufficient to drive
price down to its minimized marginal cost, the SOE is still able to cover its
costs even if these are not held down to a minimum level. Likewise,
competitive entry fails to squeeze out all excessive costs if it enjoys some
first-mover advantage, either a firm-specific rent or an asset valuable for
deterring entry. The SOEs costs then lie below the lowest attainable costs of
rival entrants and the equilibrium competitive price, which sets a ceiling on
the viable SOEs actual costs. Liberalization, however, could exert a
negative effect on productive efficiency via a different channel: where
important scale economies exist, the total cost of obtaining a given output
increases with the number of producers.
Privatization is also incompletely effective for achieving allocative and
technical efficiency. It could compel technical efficiency in ideal circumstances: a perfectly functioning market for corporate control in the private
sector and/or efficient executive-compensation contracts that suflice to align
the incentives of the managers fully with the shareholders interest in
maximized profits (through minimized costs). If, as we expect, these devices
are less than completely effective,12 privatization may still improve technicai
efficiency if the monitoring of private-enterprise managers by their shareholders is superior to the monitoring of managers of SOEs by the govemment or by the taxpaying public (as the implicit shareholders in a SOE).13
This test is likely to be met if the government develops no po!icy toward the
efficiency (or other performance dimensions) of the SOE or proves ineffectual
at monitoring the enterprises managers. The likelihood of passive governmental supervision is reinforced by the publics free-rider problem: the
taxpayers collective interest in the WEs efficiency is unlikely to induce
It was assumed in this paragraph that the SOE and private-sector competitor face the sac;li:
input prices. That assumption could fail for many reasons. The enterprise may obtain i;lputs
(especially capital) on favorable terms or be exempted from taxes that enter into the costs of
private enterprises. On the other hand, public enterprises are sometimes saddled witl. excess
costs that convey rents to suppliers of their inputs. A notable case in Britain, is the Central
Electricity Generating Boards requirement to purchase British Coal at prices that have been
estimated to exceed those on the world market by 8 to 36 percent. See Molyneux and
Thompson ( 1987), 7%~ Economist, March 25, 1989, 1619.
Grossman and Hart (1980) and Holmstrom (1979).
13The taxpaying p ublic are implicit shareholders in a public enterprise because of the
consequences of any profit or loss run by the enterprise for the public finances. If the enterprise
runs a loss, the government budget run:; into deficit by that amount, and the public make up the
loss in the proportions that they pay higher taxes or lose benefits from the reduction of
government expenditures. If the enterprise runs a profit, they benelit from lower taxes or
increased benefits. These net-benefit shares thus function as implicit shareholdings in the public
enterprise. See Peltzman (197!).
150 R.E. Caves, Lessof~s jirom prwatization in Britain
individuals or any coherent group to make the political investment in
lobbying and campaigning needed to bring about a change of policy. On the
other hand, a welfare-maximizing government could choose to steer the SOE
to-ward policies inconsistent with minimizing its private costs, but appropriate for repairing some gap between private and social values.14 If it does, the
enterprise serves as an instrument of public policy, and no case is made for
privatization.
Privatization can advance allocative efIiciency only to the extent that
shifting the enterprises objectives toward maximizing its profits increases its
allocativ7 efliciency. However, the adoption of a profit goal by an enterprise
can certainly have the opposite effect. In the absence of public regulation, a
privatized enterprise is expected to pursue any monopoly profits that its
public-management staff may have foregone, impairing allocative efliciency.
Allocative efficiency can be improved by the quest for higher profits only if
the public enterprise had supplied its market with an excessive output
(relative to the competitive norm). In pursuit of any available monopoly
profits the privatized firm is still expected to contract output. However, if
competition limits the gains from output restriction, privatization could
improve allocative efficiency by leaving output closer to the competitive ideal
than before. A privatized enterprise might choose a different pattern of price
discrimination than its public counterpart (see below), but it is not clear that
the private pattern would be normatively superior.
Apart from identifying the possible effects and limitations of the two
policies, this analysis shows that they may interact subtly, so that the simple
and obvious choice – privatize for productive efliciency and liberalize for
allocative eflicicncy – is unlikely to be optimal. If the markets structure
keeps iiberalization from assuring allocative eficiency, and SOEs produce no
less than a zero-profit output (inferred from their actual costs), then an
internal policy optimum could exist: privatizing would not be pursued to the
maximum, 5 some productive-efficiency gains would be foregone in order to
limit losses of allocative el?iciency, and marginal e&cts on allocative and
productive efficiency would be equated. Similarly, should liberalization
Repairing discrepancies has not been a conspicuous function assigned to British public
corporations, but two examples can be noted. The water authorities !,~ve as one of their
responsibilities flood control and drainage, which are effectively public goods because of the
technical dificulty of denying their benefits to individually nonpaying beneficiaries; the
performance of these functions is accordingly to be left with a public authority when the
functions of providing household water and sewerage services are privatized [Vickers and
Yarrow (1988, p. 399)]. Vickers and Yarrow (1988, p. 323) argued that privatizing of the British
Fiiational Oil Company might have been a mistake because of its value for disimpacting
information for the public on the rents captured by North Sea oil producers and potentially
subject to capture through taxation in the national interest.
Assume for this argument that privatization can be thought of as a continuous variable,
such as the fraction of shares in the enterprise not held by the government. The empirical
aptness of this assumption can be defended by the results of Eckel and Vermaelen (1986).
R.E. Caves, Lessmu &km privatization in Britain 151
impair productive efficiency (by fostering inefficient-scale production), privatization might optimally be curtailed in order to reduce the enterprises
propensity toward output restriction and allocative inefficiency. More
detailed ccnsideration of these normative issues does not prove helpful for
interpreting Britains actual experience, but they yield the important implication that an internal optimum combination of policies may exist, and its
existence and nature depend on the behavioral properties of the SOE in
question.
3. Behavior of public enterprises and implications for privatization
Although these conclusions identify the aspects of privatization and related
policjr changes that have important normative consequences, a positive
vantage point is also needed to explain why SOEs behavior could yield
suboptimal market performance and hence icvite privatization. The preceding section showed that a simple policy of privatization, to be fottnd optimal,
requires more than the assumption that private investor-owned enterprises
maximize productive eficiency. One needs some basis for understanding
what choices SOE managers were making, and why, in order to foretell and
evaluate the changes that privatization will bring.
Aspects of the privatization process allow casual tests of any theory of
SOEs behavior, using the evidence of pre-privatization outcomes flushed out
by the privatization process as well as the changes in the behavior of
enterprises in transit into the private sector. One promising theoretical
approach to SOEs conduct is selected in the subsection that follows, then
-____ – used to anaiyze various features of privdzation and the operation of SOEs
relevant in light of the normative framework presented in section 2.
3.1. Behavior of SOEs
The approach suggested here for interpreting the behavior of SOEs
employs the same procedure normally used to study the principal-agent
relationship in private investor-owned corporations. Two ingredients are
needed: a hypothesis about the objective pursued by the public enterprises
managers, and a stipulation of the effectiveness and preferred objective of the
government or the tax-paying public as its external monitors. Research on
public enterprise has not given rise to either a widely accepted model of
either the agents or the principals behavior; what seems a fruitful approach
will be advanced merely as a working hypothesis.
We can think of the SOBs objectives either as imposed by its chief
executive and directors or as emerging from a complex organizational
coalition. Both approaches prove fruitful, and either is consistent with the
same substantive hypothesis about the firms objective: that the SOE
152 R.E. Caves, Lessons from privatization in Britain
maximizes political support. l6 The pursuit of political support is a plausible
consequence of utility maximization by the SOEs managers, who are
assumed to value the independence from outside interference and ample
scope for deploying resources that political support can assure. This hypothesis yields specific, testable predictions about the allocative and technical
efficiency levels that the SOE will achieve. If management pursues political
support, the SOE will tend to earn no excess profit. This result follows if any
losses that require subventions from the Treasury are expected to bring
outside interference from the governmental monitor, and are therefore
avoided. Potential excess profits, however, can be traded for political
support, for example, by charging lower prices to customer groups who are
politically powerful or generally regarded as deserving favor.
Another way for the SOEs managers to buy political support is to transfer
pecuniary rents or perquisites to members of the enterprises coalition – its
employees and contractual affiliates, who may then lobby vigorously to
oppose outside intervention. The enterprise then may appear to earn no
excess profit, although both its price and costs exceed the efficient competitive level. This corollary of the political-support hypothesis shades into an
alternative way to derive the assumed objective of the SOE – namely, as
arising from the overall coalition of stakeholders in the enterprise and not
just from its managers preferences and opportunities. This alternative grows
from the Carnegie model of the firm as a nexus of lateral contracts among
functional specialists, * a view that becomes relevant for its very neglect of
the equity owners control of the firm and the vertical structure of contracts
within it. That model reaches two relevant conclusions. First, it predicts that
the goals pursued by the firm reflect the policy preferences of the various
participants in the organizational coalition; one of these goals could be
independence from externally imposed constraints and objectives. Second, the
r6Analytical foundations for this hypothesis were provided by Peltzman (1971) and Baldwin
(1975, Part II). Other approaches to public-enterprise behavior can be found in the literature.
For example, managers can be assumed to pursue efficient allocation of resources but experience
disutility in getting costs down to a minimized level (that is, tolerate technical inefficiency); this
approach was developed by Vickers and Yarrow (1988, pp. 35-39, 135-139). Or the objective of
the enterprise can be taken as a weighted average of the goals pursued by its managers and its
organized employees [ Rees ( 1984)J
That is all parties who may lay explicit or implicit claims on the ex post cash flow of the
enterprise ind are not guaranteed (restricted to) a predetermined compensation.
% that model the firm is taken to comprise a team of fuflctional specialists. -When the team
is formed, each specialists expected benefit must at least equal his reservation price. That
reservation price can be met not only by pecuniary rewards but also by policy side-payments,
because each specialist is assumed to have a taste for bending the firms policies toward subgoals
congenial to his specialty (the production department wants a steady output rate over time, the
finance department strong balance sheets, and so forth). The firms actual policies therefore
represent a bargained outcome, bearing the imprint of each specialist to a degree reflecting the
specialtys structural position in the firm and its bargaining finesse. (Further consequences are
goted in the text below.) For a concise account, see Syert and March (1963).
R.E. Caves, Lessons from privatization in Britain 153
slack of the enterprise is absorbed by the organizations members through
exercise of the same bargaining process that generates the firms overall
objectives. Symmetrically, a shortfall of actual from anticipated cash flows
forces the disgorging of slack (subject to the constraint that the coalition
remain viable). The usual objection to the Carnegie model, that the manager
imposes the goal of profit maximization on the enterprises participants,
applies with much less force to the SOE, which may well lack an externally
mandated goal.
The organizational model of the enterprise, allied with the hypothesis that
its managers seek to maximize political support and the independence that
such support provides and preserves, represents an attractive characterization
of the SOE. Strong predictions are generated about both its allocative and
productive efficiency. If production is efficient, the quest for political support
induces it to set a price that just covers its costs. If the enterprise operates in
the range of constant average costs, its price is then set equal to its average
and long-run marginal costs, with its output corresponding to the desirable
level that an unregulated competitive industry with the same costs would
select 2o This conclusion depends, however, on the SOBs economic costs
coinciding with the costs that its governmental monitor expects it to cover.
The model implies that in general costs will not be minimized due to rents
(slack) captured by those parties who hold bargaining power within the
firms coalition. Bargaining power is related to participants ability to
generate or withhold political support outside the enterprise. The exact
combination of shirking, overpayment, and policy diversion that results
cannot be predicted without providing more structure to the theoretical
problem. 21 Technical inefficiency, combined with pricing to cover nominal
costs, implies that the SOEs output will be less than a competitive industry
would provide.
Because the U.K. government and the SOE managers have acted as
independent decision-makers in the round of privatizations, we must address
the behavior of the public-sector monitor as well. The taxpaying public hold
implicit shares in the residual income of the SOE. Because these shares are
implicit and nontransferable as well as widely dispersed, members of the
public or organizations outside the government have minimal incentives to
That is, excess of potential revenue over minimized costs, which can be absorbed either as
pecuniary re-3 l t s c: as polky side-payments to members of the qanizational coalition.
This conclusion does not hold if the public enterprise sells to distinct submarkets and
manipulates their price-cost margins in pursuit of political support. See Peltzman (1971).
2Brittan (1984) found implications in these properties for a public enterprises tea&ion to
entry and small-numbers rivalry. With the Treasury ready to make up losses, he proposed that
newcomers would be unlikely to enter and compete with a public-enterpiise incumbent. Perhaps,
but other factors are relevant, such as a degree to which the enterprises internally generated
preferences favor indepenckxuze from competition. Also, the govemmeatal monitors attitude
should certainly affect the feasibility of running short-run losses to deter a would-be entrant and
thus the credibility of deterrence.
154 R.E. Caves, Lessons from privatization in Britain
monitor the SOE. However, the government itself potentially serves as a fully
centralized monitor, with the monitoring done chiefly by the sponsoring
ministry and any others that come to regard the SOE as a tool useful for
effecting policies that they prefer. 22 Rather than proposing an a priori
treatment of the governments monitoring actions, we simply adopt a
characterization widely agreed upon in the U.K. literature: the governmental
monitors are effective but inconstant, their periodic interventions forcing
policy responses by the enterprise but not necessarily any enduring shift of
objectives. 23 British SOEs seem to follow many policies that they deem to
serve the public interest, but much more from internal initiative (thai is, the
pursuit of political support) than in response to general instructions from the
govemment.24
This view of the SOEs monitors does not much modify the preceding
conclusions about its allocative and technical eficiency. Except when the
enterprise serves explicitly as an engine of taxation, the monitors are unlikely
to dislodge its propensity toward average-cost pricing or the allocation of
resources to obtain political support. Nor are they likely to retrieve the flow
of slack absorbed within the SOE.
3.2. Implications for the privatization process
Key features of Britains experience with privatization will be considered
against this background. We advance a series of propositions that connect
the preceding conceptual framework to empirical evidence on the behavior
and performance of the SOEs.
3.2.1. Allocative qfficiency of SOEs
The wave of privatizations has led to intensified research on the allocative
and technical efficiency of SOEs in Britain and elsewhere. Evidence on
allocative efficiency is taken from reported profits or margins, which of
course reflect the relation of revenues to costs actually incurred and not
necessarily to minimized costs. The data indicate that during the 1970s U.K.
public enterprises in the aggregate were running losses or earning substan-
See Robson (1962) and Curwen (1986, ch. 2) on the governance structures of ptb:ic
corporations. SOEs are sometimes pressed to pursue goals other than those in the nominal
responsibility of the sponsoring ministry when these are assigned high priorities by the Prime
Minister. In Britains case these have typically been macroeconomic goals of avoiding
unempioyment or restraining inflation. See Redwood and Hatch (1982, p. 5).
Yarrow (1986, p. 331). The theory of public-sector monitoring was discussed by Mayer
(1987). The reasons why ministerial power to appoint boards of directors for public enterprises
fails to attain effective monitoring were discussed by Redwood and Hatch (1982, pp. 42-44).
24As an interesting case, Newbery showed that the effective effort of British Gas to beat down
the price of natural gas purchased from suppliers was probabiy not consistent with optimai
resource conservation for the country as a whole, yet governmental monitors by no means
discouraged it. See Newbery (1986) and Vickers and Yarrow (1988, p. 256).
R.E. Caves, Lessons from privatization in Britain 155
tially less than a market rate of return on their invested capital.2s Can these
losses be squared with the normal profit prediction of the model proposed
r%h
avvv rir~3 4. AZ dEma!ive answer seems appropriate, because the government
never registered any vigorous unwillingness to supply the funds absorbed by
the SOEs until the gradual introduction of external financing limits, beginning in 1975/76, constituted a threatening and committed intervention
[Redwood and Hatch (1982, pp. 81-103)].
As another putative form of allocative inefficiel;cy, policies of crosssubsidizing selected markets were in widespread use, similar in pattern to
counterpart industries that have operated under intensive regulation in the
United States. These include charges for rail, postal, and telephone service
favoring rural customers and those in remote locations and telephone
charges favoring residential over business customers and local over intercity
calls.26 Such price discrimination tends to imply that some submarkets were
undersupplied, others oversupplied. These patterns of discrimination are
consistent with the political-support hypothesis: household customers are the
ones with the votes, rural residents are chronic candidates for discrimination
—
as fair treatment, and so forth. In the coal industry the Nationai Coal Board
has used net revenues from its profitable activities (notably surface mines) to
keep unprofitable underground mines in operation, in order to maintain the
support (or at least acquiescence) of the mineworkers [Pryke (1981, pp.
M-60)].
3.2.2. Productive efficiency of SOEs
The framework implies that the productive efficiency of SOEs should not
be superior to that of private enterprises carrying out the same activiiies. The
privatization campaign bolstered the previous stock of research on this topic,
and the hypothesis was generally confirmed. The productive eficiency of a
SOE is hard to assess from the direct analysis of its accounts. The attractive
strategy of a yardstick comparison to ;d similar private-sector firm is difficult
to implement, at least partly because suitable yardsticks are seldom available
for enterprises enjoying some element of naturd-monopdy status.27 The
findings of Pryke (1981, 1982) yielded a sharply negative appraisal of the
25Brittan (1984, p. 128) estimated that their returns on invested capital (earnings before tax
and interest) ranged between -0.4 percent and 1.1 percent during 1972-1982. This is less than
the 5 percent reai return that the Treasury has required of state enterprises investment plans
since 1978, which in turn is below comparable discount rates used by the private sector. Also see
The Economist, August !, 1987, pp. 49-50, and Vickers and Yarrow (1988, p. 143). Vickers and
Yarrow emphasized the enterprises lack of knowledge of their marginal costs.
26For descriptio n s of these patterns, see Vickers and Yarrow (1988, pp. 223426) on
telecommunications prices and their post-privatization changes and Pryke (1981, p. 160) on
discrimination by the postal services in favor of rural customers and against first-class mail
users.
27The diCficulties researchers have faced in making these comparisons illustrate the point. See
Pryke (1981, 1982); Foreman-Peck and Manning (1988).
156 R.E. Caves, Lessons from privatization in Britain
cost-efficiency of several public-enterprise activities for which private-sector
comparisons were feasible. 28 Prykes own explanation for the change (1981,
pp. 257-266) emphasized not the behavior of the SOEs themselves but rather
the British governments willingness to provide subsidies under loosely
specified but generous terms. A number of investigations by the Monopolies
and Mergers Commission into SOEs performancetg provide evidence of
various specific forms of inefficient management structures and ineffective
policy, especially in the use of manpower. The most compelling evidence of
technical efficiency is found in the eficiency gains that some SOEs attained
once they were clearly destined for privatization. Between 1980/81 and 1986/
87 British Steel halved its workforce and concentrated its production in five
major integrated facilities with little reduction in its output, while British
Airways reduced its employees by 36 percent between 1980 and 1985.j The
significance of these improvements occurring before privatization is discussed
below.
3.2.3. Organization and performance of the SOEs
A good deal of evidence supports the Carnegie-style characterization of
SOEs as lateral coalitions with considerable internal diffusion of power. Aat
intensive study of postal and telecommunications services [Batstone, Ferner
and Terry (1984)] is particularly enlightening. Employees in such complex
network activities acquire locally specific knowledge that conveys considerable bargaining power within the organizational coalition. Also, the
managers find it difficult to combat the absorption of slack within the
eilterprise when no clear policy gaals are imposed from the outside. When
the political monitors intrude only sporadically and with constantly changing
demands, management lacks a strong hand for imposing coherent objectives
within the organization. At least for such labor-intensive SOEs, the evidence
seems to support the prediction that organizational patterns have not been
conducive to technical eff;.ciency.31
The definition of goals internally within the enterprise and the exercise of
policy preferences are often evident at the managerial level. For example,
troubles of the Central Electricity Generatim Beard have &en trmvd in n-t* -v–v_ -_ ..p ___ w–wY *a. yam c
to its willingness in the 1960s to plan its expansions of capacity on demand
forecasts that were markedly more optimistic than the consensus among
outsiders (as well as in comparison to actual subsequent rates of demand
28This conclusion ran contrary to the judgment of his investigation a decade earlier (Pryke,
1971). Also see Shepherd ( 1968, 1976, ch. 6).
Summarized by Utton (1986, pp. 178487).
Aylen ( 1988); Wall Street Journal, August 8, 1988, p. 10.
3Sporadic governmental intervention apparently had a particularly negative effect on labor
reiations, because of recurrent attempts to apply wage-restraint policies with particular vigor to
the state enterprises. These led to real-wage declines followed by increasing labor conflict that
was finally resolved by large pay awards [Winchester (1983, pp. M-178)].
R.E. Caves, Lessons from privatization in Britain 157
growth). Another source was policies toward its equipment suppliers (including Buy British) that served interests other than maximum efficiency and
reliability of the system [Pryke (1981, pp. 22-32)].
The organizational interpretation may seem all too obvious for nationalized sectors with strong and militant unions. British Rail in the 1970s
provides an instructive example of interacting quests for slack by both
workers and management. Manning requirements in union agreements,
among other factors, contributed to excessive employment that Pryke (1981,
pp. 81-87) estimated at 25 percent in 1978. Furthermore, the difficulties that
management expected to face in reducing employment discouraged
productivity-raising investments that would otherwise have had high
payouts. But British Rails difficulties went beyond a lack of incentives for
managers to press for efficient use of labor. Its managers embraced the
objective of maintaining an uneconomically large rail network and tended to
view their chief problem as simply how to regularize the needed flow of
subsidy from the Treasury. Favorable turns in the availability of subsidy
were promptly absorbed as slack within the organization.32
3.2.4. Organizational response to prospect of privatization
Yarrows (1986, p. 337) careful examination of the limited evidence on
price-cost performance of privatized enterprises suggests that gains in
technical efficiency have occurred, but they apparently preceded privatization
rather than followed it. Brittan (1984, p. 120) similarly noted that the greatest
reductions in manning levels since 1978-80 occurred in SOEs facing some
prospect of full or partial private ownership.33 The organizational model of
the SOE implies that the prospect of privatization might at least set in train
the squeezing out of slack.
The Carnegie model of the firm presumes that many of its members
contemplate a long-term association with the firm or incur large switching
costs of changing employment. The prospect of either privatization or
liberalization then signals to all participants that slack will be squeezed by
outside invaders (competitors, or monitors with new and compelling
demands). Reputation effectsJ4 and the credible threat of retrospective
A particularly striking example of slack absorption is provided by British Gas, which in
effect obtained an enormous increase in productivity in the 1970s when natural gas from North
Sea fields replaced manufactured gas. During a period when employment in British Gas was
reduced by 18 percent, staff costs per employee rose twice as fast as in British manufacturing as
a whoie. See Pryke (1981, pp. 16, 18).
j3Later evidence continues to confirm this: Chambers (1988) on Jaguar; The Ecurromist, June
Li, 1986, p. 59, on water authorities; March 15, 1986, p. 16, on British Airways; Nov. 8, 1986, p.
66, on British Gas; March 25, 1989, on British Coal. The rapid productivity gains experienced
by British Sttzl form a particularly dramatic example, but they also raise the question whether
the cause was the prospect of privatdation or simply a change in priorities of the Thatcher
governments monitors [Aylen ( 1988) J.
j4These effects refer to the role of the managerial labor market in supplying incentives for
managers to run their enterprises eficiently [Fama (198O)J.
158 RX. Caves, Lessons from privatization in Britain
punishment may explain why participants enjoying rents are willing to
disgorge before the SOE is actually cast into the private sector and the
external market pressures become actual. Indeed the top managers of a SOE
may be able to capture large gains from seizing the opportunity to break
vertical contracts within the firm and curtail shirking that they previously
could tolerate costlessly. Batstone, Femer and Terry (1984) found that the
threat of liberalization, coupled with the opportunity of privatization, led
management to take a much more active stance in labor relations than
before; the change was less evident in the postal service than in telecommunications, where both privatization and liberalization were more severe
threats.35
3.2.5. Libetalization and managetial tents
Managers of a SOE destined for privatization have access to large gains
(in compensation and status) if they can iimit the associated liberalization.
These gains can be realized because privatization allows the imposition of a
coherent goal of cost minimization at the same time it removes some
inhibitions against value-maximizing use of natural-monopoly elements in
the enterprises market position, Liberalization and regulation are the main
threats to these gains, and so managers have a strong interest in resisting
their intrusion. Furthermore, skills is %luencing the details of public policy
toward the enterprise are presumably well-honed in such managers may and
Thompson ( 1986)]. A particularly useful source of leverage for some chief
executives was their role in convincing the financial community about the
rosy cash-flow prospects of the privatizled firms. The government, concerned
with maximizing the proceeds from sale of the public firms (see section 4),
faced credible threats by the managers that their public shows of enthusiasm
and confidence would wilt if they had to cope simultaneously with liberalization and competition, Researchers have concluded that British Telecoms
success in minimizing the potential competition in long-distance services and
British Airways resistance to the Civil Aviation Authoritys proposal to
make its routes more competitive resulted from their managers bargaining
power.36
The conclusions o&red here have been assembled from scattered and
selective evidence on a diverse group of SOEs. Nonetheless, they suggest that
3SOne argument made for privatization in Britain was that participants in the SOEs could
generate slack by encroaching on the firms cash flows, and the government could not credibly
refuse to make up the resulting losses [Heald (1984)]. Paradoxically, it appears (after the event)
that the external funds limitations imposed on the public enterprises by the Thatcher
government were important among the factors causing the pre-privatization increase in their
technical efficiency [Redwood and Hatch (1982, pp. 81-103)J.
36Kay (1984); Kay, Mayer and Thompson (1986, p. 17); Newman (1986, pp. 12-13, 155-164).
Unions have also been actively opposed to liberalization, but the specific concessions that they
obtained had to do with pension funding vhomas (1984, p. 66)].
R.E. Caves, kssons from privatization in Britain 159
the chosen theoretical approach to the behavior of these enterprises has some
predictive value. The extent and forms of allocative and technical inefficiency
that the SOEs displayed seem consistent with the model. More pointedly, the
behavior of SOE executives and employees, both prior to and in the face of
privatization, fails to reject the hypothesis that investor ownership promises
rents for increasing the level of productive efliciency.
4 Public policy choices and monitoring by equity stmrehb
The remaining group of findings about privatization relate to the intersection between public choice and corporate governance. The U.K. government
stated its commitment to goals of competition and efficiency that were
generally consistent with economic definitions of allocative and technical
efficiency. Other policy objectives were also pursued, however, notably
maximizing the revenue obtained from selling the SOEs and encouraging
the widespread dispersion of share ownership among the British public
[Grout (1987)]. These policies altered the potential changes in allocative and
productive efficiency that could be expected from privatization – chiefly by
affecting the amount of liberalization that took place and the efficiency with
which the new investor-owners could be expected to monitor the privatized
enterprises.
4.1. Sequence of privatization
Privatization has followed a sequence in which the first SOEs ejected into
the private sector were those operating in markets relatively untainted by
natural monopoly. Enterprises subject to natural monopoly or other
problems of market failure came later, or are still in the queue. Observers
who noted this pattern suggest that postponing the difficult cases had some
logic [e.g. Moore (1986)]. The economic logic is not articulated, however,
and indeed is far from obvious. When ailr i;&nsry commercial enterprise
wound up in the public sector to stave off some disaster that threatened
bankruptcy, there is little downside social risk in returning it to private
status if its cash flows have regained a positive pr esent value. For enterprises
with activities subject to serious market failures, however, any gains in
technical efficiency from privatization have to be set against the cost of
exacerbating the market failure. The question is not whether the tough cases
should wait but whether they are appropriate candidates for privatization at
all. The only economic justification for putting them at the back of the
privatization queue arises if the firms first undergoing changes in status are
expected to supply useful ex post evidence on the efficiency gains from
This was discussed extensively by Kay, Mayer and Thompson (1986, chs. 3, 4).
160 R.E. Caves, Lessons from privatization in Britain
privatization. However, it is not obvious that the U.K. government was
collecting this information and feeding it into the assessment process.
If the candidates for privatization had to be taken up in sequence, because
of some limited political or bureaucratic capacity, the sectors expected to
yield the largest total net benefits should have come first. That is consistent
with taking first the SOEs whose privatization portends no incidental cost of
allocative inefficiency or other market failures, but it also suggests the
relevance of other criteria for determining the optimal sequence, such as
taking larger sectors first. 38 It has also been charged that privatizations
yielding large gross revenues for the Treasury got into the queue ahead of
those with large net economic benefits, reflecting an overt governmental
interest in reducing short-term budget deficits.3g
4.2. Monitoring considerations and methods of privatization
The theory of principal-agent relationships between firms owners and
managers hold implications for the way in which shares are sold when the
SOE is privatized. Because of free-riding by small shareholders, the market
for corporate control is more likely to enforce productive efficiency on the
privatized enterprise in the presence of blocks of shares that are less than a
majority, but large enough to be expanded to majority status without being
frustrated by this externality [Shleifer and Vishny (198611. A government that
raognizes this value might privatize an enterprise so as to encourage some
agglomeration in large blocks, or might itself retain a substantial minority
holding.
Whi!e not always inconsistent with this consideration, the 1J.K. govemments diverse methods of privatizing shares have not been motivated by it
directly [Steel (1984)]. The chief objective pursued by the government has
been to widen the base of household shareholding by offering concessional
terms for purchases of small blocks of shares. The stated rationale for this
policy was to promote peoples capitalism, but no doubt it was also intended
to deter a future renationalization. Although the policy does not maximize
expected productive efficiency, an argument can be made for its contributions
to allocative efliciency from shareholder unanimity models [Grossman and
Stiglitz (ISSO)]. Consider an investor-owned monopoly that provides a
widely consumed service, such as telecommunications. If shareholdings are
small and widely dispersed through the population, the typical shareholders
interest in maximum (monopo!y) profits is tempered somewhat by the
38Beesley and Littkchild (1983). Some British SOEs (coal?) may not have positive present
values in the absence of some dedicated subsidy commitment or reorganization of uncertain
feasibility. Privatization would require some form of subsidy wntract, which has its own
incentive problems,
39Gas, telecommunications, and electricity ahead of coal, steel, and automobiles (T/114
Economist, July 18, 1987, pp. 1446).
R.E. Caves, Lessons from privatization in Britain 161
negative effect of monopoly prices on his welfare from consuming the output
[compare Brittan (1984, p. 123)].
Observers have noted that many small shareholders resold their newly
purchased shares and took the capital gains when prices rose at the start of
trading [Yarrow (1986, p. 357)]. Indeed, there is no market-based reason
why the initial distribution of shareholdings upon privatization and the
ultimate equilibrium distribution should be closely related.40 Nonetheless, the
policy that succeeded in at least doubling the number of households owning
shares certainly did not promote effective monitoring, especially considering
that the absolute size of such enterprises as British Telecom tends to put
them out of the reach of the market for corporate contro1.41
Where the U.K. government chose to retain a minority holding in
privatized enterprises, other objectives were once again present. The main
consideration was that minority shareholdings might prove effective vehicles
for influencing policies of privatized firms that occasionally invite some
public intervention. Thus, shares were retained in military-goods producers
(British Aerospace and the Royal Ordnance factories), in a firm that does a
good deal of business with foreign governments (Cable & Wireless), and in
British Telecom [Pickering (1984); Steel (1984)]. A comparable policy was
announced for the privatization of British Steel, in order to allow the
government to veto any takeovers.42
4.3. Public decisions on liberalization
It was demonstrated in section 2 that the best normative outcome for a
SOE is likely to require an optimal combination of pGvatization and
liberalization. Their respective roles in the U.K. governme& policies hence
hold considerable interest. Although some liberalization has occurred,
observers on balance have found it inadequate.43
Instances of liberalization include the removai of monopoly privileges for
the National Bus Company, limited trunk-line competition for British
For the United States there is some evidence that the concentration of companies*
shareholdings is related to the expected payout to monitoring of the management by
shareholders; see Demsetz and Lehn (1983, whose evidence is consistent &sh the model of
Shleifer and Vishny (1986).
41Kay, Mayer and Thompson (1986, pp. 1 l-13). The goal of bringing joy to small
shareholders has probably conflicted with the governments other objective of obtaining the
maximum sale revenue, because underpricing raised the probability of large immediate
appreciations which Indeed occurred in many cases when the shares began to trade. The
questions whether the government avoidably underpriced shares sold to the public, and whether
it has been too risk-averse about overpricing, have been extensiveiy but inconclusively debated
in Britain. An interesting contrarv consideration is that the promotion of widespread shareholding could have raised the publics reservation price, by precommitting the government not
to renationalize, tax, or otherwise invade shareholders gains [Grout (1987, p. 68)].
42 Wall Street Journal, July 7, 1988, p. 19.
43For example, Kay and Silberston (1984) and Kay, Mayer and Thompson (1986, p 16).
162 R.E. Caves, Lessons from privatization in Britain
Telecom, as well as several minor liberalizations for enterprises still in the
public sector (e.g., ending the Post Ofices monopoly of parcels and allowing
the F-:!$ic electrical distribution network to purchase privately generated
power)? In some cases the liberalizations (because they preceded the
privatizations) had marked and distinguishable effwts on the pricing and
performance of the SOEs? However, two factors may have deterred further
use of liberalization. First, the government was concerned with its short-term
deficit (Public Sector Borrowing Requirement) and hence sought maximum
sale revenue (subject to the constraint of promoting shareholdings by
employees and small shareholders). 46 It was widely recognized that a SOE
would fetch a lower price on the stock market, the more competition it was
expected to face. Second, the government was evidently sensitive to pressures
from both managers and unions of the SOEs that the firms should pass
intact and healthy into the private sector. Specific proposals for liberalization
were considered and rejected under pressure from the affected enterprise.47
British Gas provides a telling example. The distribution network could have
been divided into twelve regional suppliers, restoring the organization that
prevailed before 1972. This division would have insured competition for
natural-gas supplies, upset the existing pattern of regional cross-subsidies,
and provided yardstick comparisons of efficiency for the newly created
regulatory office (Ofgas). However, management opposition, the consideration of maximizing sale revenue, and haste to complete the transaction
before an election all counted against this solution pickers and Yarrow
( 1988, pp. 268-27 l)].
Thus, the effective joint use of liberalization and privatization seems to
have been frustrated to a significant degree by extraneous considerations of
?Ietails can be found in the extensive case studies contained in ViCkGS and Yarrow (1988).
45British Teiecom faced a competing long-distance carrier (Mercury) and various forms of
indirect rivalry before privatization, and its pricing and efficiency were clearly a&c&d pewman
(1986, p. S)]. Deregulation of longdistance bus transportation quickly generated entry and
competition that depressed the fares of National Express to one-half to two-thirds of their
fqrmer levels, even though National Express ultimately succeeded in repelling its major
competitors. See Jaffer and Thompson (1986), Muiiey and Wright (1986), and Thompson (1988).
46Nonetheiess, the government was apparently risk-averse about the pricing of its initial
offerings, on the evidence of discounts from the prices that prevailed after short periods of
trading on the market (normalized by the experience of private-sector placements in similar
market conditions). That is, gains were taken by those who took up the tendered shares that
could have gone to the general public. See Mayer and Meadowcroft (1986).
47!5ee Brittan (1984, p. 119); Utton (1986, p. 202-213); Kay and Thompson (1986, pp. 29-31).
Vickers and Yarrow (1985, ch. 3) covered the case of telecommunications in detail. Ashworth
and Forsyth (1986) discussed skeptically the case for competitive dismantling of British Airwa:fs
in the course of privatization. On the decision not to divide Londons airports into separate
private firms, see Starkie and Thompson (1985). On the prospective separation of electric-power
stations see Helm (1988). Brittan (1984) proposed that shares in the SOEs simply be given to ail
British citizens, partly to relieve the governments inhibitions on the degree of liberalization
(although also to maximize the barrier to renationalization).
R.E. Caves, Lessons from privatization in Britain 163
the effect on public-sector borrowing4* and the political influence of
members of the SOE coalitions who would be the losers. The time of
privatization probably was the last chance for liberalization, in that liberalizing after the public had paid for a share of expected monopoly rents would
seem patently unfair.
Employee shareholding, promoted in the course of many privatizations,
holds particular interest for its incentive effects. One SOE (National Freight
Corporation) was sold entirely to its employees, and the operating subsidiaries of National Bus were placed mostly through management buyouts. In
several other privatizations employees of the SOE received special encouragements to purchase its shares. The arrangements involved concessions that
tended to assure a gain from purchase and prompt resale. Nonetheless, the
large proportions of employees who took up the share-purchase options
[Pirie (1985); Grout (1987, p. 63)] may shed some light on the problem of
organizational behavior in public enterprises.
Two factors might induce employees to take up shares in the initial
offering. First, employees have information superior to that of the general
public on the amount of inefficiency that might be squeezed out following
privatization. If the less-informed public underestimates this improvement,
the capital gains to employee; from their initial share purchases will be
enlarged (on the assumption that the issue price is controlled at the margin
by the general publics expectaions). Second, one constraint on the efficiency
of a SOE is the difficulty oi rewarding participants in the coalition for
contributions to the firms long-run value.4g This constraint gives employees
a manifest collectiue interest in shareholding by members of the team,
because improvement in the incentives of any member of the team tends to
raise the productivity of the team as a whole. Although this interest does not
tianslate automatically into a prlvQCti ;-rn*n -4~ llluCn W for . e&t err?ployee to take up
shares, the free-riding problem seems more easily overcome when all
employees make the choice at the same time, and some horizontal monitoring may become habituated.
48This issue itself has been discussed extensively in Britain. Over a long time horizon, the sale
of shares in a public enterprise has on certain assumptions no effect on the governments net
financial position if the capitalization rate for income from the shares is the same as the rate of
interest on government borrowirgs. Selling shares denies the Treasury a certain stream of future
revenue: an er,ual borrowing commits the Treasury to make future payments in the same
amount. Obviously, a short time-horizon is implied for governmental decision-makers. See
Mayer and Meadowcroft (1986).
49That is, public enterprises and other firms without marketed equity (cooperatives, partnerships) lack the possibility of motivating employees by compensation tied to the enterprises
market value [Jensen and Meckling (1979)].
164 R.E. Caves, Lessons from privatization in Britain
4.5. Warding off allocative inefficiency
In order to avert losses in allocative efficiency following privatization, the
British government had to consider restricting any welfare-impairing pokier
that would be attractive to a profit-seeking privatized enterprise. What
theop,f and evidence have confirmed in this paper was assumed in practice:
that SOEs had not generally chosen to set prices at monopolistic levels
relative to their realized costs. In considering its options, the government
recognized that U.S.-style regulation faces its own problems of disincentives
and limited effectiveness. 5o There was no enthusiasm for embracing it as a
broad alternative to SOE status.
The issue first presented itself urgently with the privatization of British
Telecom (BT). The Office of Telecommunications (Oftel) was created as a
regulatory body, with one of its responsibilities being regulation of BTs
prices. This regulation would be accomplished by application of a formula
widely referred to as RPI-X. BT would be allowed to raise a weighted
average of its prices by an amount equal to the increase of the retail price
index (WI) less an adjustment for the relative productivity growth that BT
was expected to achieve (X). The terms of the formula were initially set for
,,,,, five years, over which period BT could keep any profits (or suffer any ~USSCS~
associated with productivity gains greater than (less than) expected? The
hope was to utilize regulatory lag to mitigate the disincentive for efficiency
that is associated with cost-plus regulation, and indeed the five-year interval
prior to review of the RPI-X formula was consciously chosen to optimize
between this incentive for technical efficiency and the possible interim loss in
allocative efficiency.
Unlike. regulation in comparable U.S. industries, the formula did not
address the question whether BTs price-cost margin was appropriate at the
outset, only how much it might increase. Nonetheless, it was recognized that
the level question central to U.S.-style rate-of-return regulation could not be
avoided when the time for reconsidering X came around.
In addition, an element of franchise regulation was involved. BTs license
committed the privatized firm to maintain some of the preferences that the
SOE had devised. It also prohibited a long list of anticompetitive practices
[Vickers and Yarrow (1988, pp. 21 l-212)].
The arrangements devised for BT were expected to serve as a template for
natural-monop o!y enterprises yet to be privatized. Ts also was one of the
cases (mentioned above) in which minority shareholdings were retained by
the government for the purpose of tacit control, although the exact
Swarm (1988) developed extensively the lessons of U.S. regulatory experience for British
policy-makers.
U . K. Ofice Telecommunications (1986); The Economist, Sept. 5, 1987, p. 51. In its
application to other privatized firms, the formula was extended to allow the pass-through of
changes in the prices of major inputs,
R.E. Caves, Lessons from privatization in Britain 165
mechanism by which a minority shareholding induces internalization of an
externality by a profit-seeking management is not obvious.52
5 Conclusions
The sectors privatized in Britain are largely congruent with those that
have been deregulated in the United States. This congruence confirms what
can be predicted from the prevalence of common elements in their market
structures – scale economies, network externalities, heavy sunk costs for
producers and switching costs for customers. These sectors have been and
remain prone to deficient market performance, yet the public-control devices
in the standard repertory have been judged on balance largely unsatisfactory.
The general importance of this dilemma warrants a close review of the
lessons yielded so far by the privatization process in Britain.
Many of those lessons revolve around organizational behavior (the
conduct of public enterprises) and corporate governance (alternative ways to
privatize and their subsequent consequences for managerial behavior and
economic performance). Much of the evidence on SOEs conduct flushed out
in the privatization process fails to reject an organizational interpretation
that possesses two main strands. First, insofar as a singie generai objective
seems to explain the SOEs behavior, the choice of policies that maximize
political support and independence predicts various behavior patterns for the
SOEs that agree with the facts. Second, the absence of a coherent principal
implies the primacy of lateral contracts and policy side-payments within the
[email protected] – aisc! consistent with assorted bits of evidence that have surfaced
in the privatization process. No claim is made that these hypotheses about
SOEs conduct ha.ve been systematically tested or alternative models considered and rejected – only that a promising stock of evidence has surfaced
for performing such tests.
Other findings bear on corporate governance and principal-agent relationships. Given the implication of organizational slack within SO& the
The electricity and water-supply sectors, scheduled for privatization, pose difftcult problems
of regulation. The electricity distribution network is a classic natural monopoly, and discussion
has focused on how to inject sorite timpetition in the decentralized generation of electricity
while somehow recognizing the natural-monopoly status of the national energy grid. See Sykes
and RoE:irson (1987); The Economist, Oct. 24, 1987, pp. 66-67; Helm (1988). The solution chosen
entails substantial (but not complete) vertical dis-integration of generation and distribution,
regional monopolies in distribution, and duopoly (with some gateways for entry) in generation
(The Economist, Apr. 15, 1989, p. 63). The regional boards that supply water and :ewerage
services also are responsible for river management, with strong public-good status. The
chairman of the Thames Water authority chose his cliche aptly in declaring that .without
regulation of river management, privatization of the water authorities would be throwing the
baby out with the bathwater (Wall Street Journal, June 8, 1987, p. 17). Also see Vickers and
Yarrow ( 1988, pp. 399-423).
166 R.E. Caves. Lessons from privatization in Britain
prospect of privatization implies that large rents may be available for those
who can squeeze out the slack, and factors such as large pre-privatization
gGns in efficiency are consistent with this. Privatization substitutes the
market for corporate control for the central government as the monitoring
principal. Some choices made by the British government (retaining minority
b!ocks of shares in governmental hands; encouraging employee s areholding)
are consistent with effective monitoring, while others (promotion of smallscale shareholding) arguably are not.
These positive conclusions about economic behavior and public choice
relate to the normative problem faced by the British government of how to
proceed with privatization in such a way that net welfare gains were
obtained in productive eflicier,cy and allocative efficiency taken together. Ihe
behavior of SOEs, on the interpretation offered here, is consistent with the
conclusion that privatization should Irnqra LiaVQ -.. aQil accompanied (as it was) by
some liberalization of the opportunities for other firms to compete with the
newly privatized enterprises. The theoretical problem (as reviewed in this
paper) seems rather more subtle than the choice process followed by British
policy makers, but the general principles were gotten more or less right.
Furthermore, various interesting choices were made with regard to substituting regulation for public ownership in ways that pursued an effective
compromise between its (potentially favorable) effects on allocative efficiency
aad its (potentially unfavorable) effects on productive efIiciency.
This evaluation of Britains experience with privatization has been selective. For example, students of regulation and economic performance may
find interest in several features of the British situation that were neglected
here. Changes in pricing structures are occurring in privatized sectors that
reflect – in degrees to be determined – the effects of privatization and
liberalization. 53 Problems intrinsic to the regulatory process are demanding
attention as the incomple teness of the RPI-X formula makes itself felt and
problems arise for the new regulatory of&es to assert their authority and
gain adequate access to information from the firms that they regulate.54
Markets such as airlines and intercity bus transportation, for which the
threat of competitive entry (contestability) held out hope for enforcing both
allocative and technical efficiency, are proving as dismayingly advantageous
to first-moving occupants as their U.S. counterparts? Indeed, experience
with all aspects of performance since privatization and liberalization
continues to accumulate and calls out for analyses such as comparisons
between the performance of Britains privatized sectors and their counterS3Examples include the ending of British Telecoms price discrimination in favor of basic
household services and against long-distance calls [Vickers and Yarrow (1988, pp. 224-2231.
5?he case of natural gas is particularly interesting [Vickers and Yarrow (1988, pp. 2%268)J.
s5 Wall Street Journal, Aug. 8, 1988, p. 10, on British Airways; Jaffer and Thompson (1986) on
intercity bus service.
R.E. Caves, Lessons from privatization in Britain 167
parts in other countries. 56 Moreover, the contracting out of public-sector
functions – not discussed in this paper – is yielding an interesting body of
data. Useful lessons from the British experience will not stop with those of
the privatization process itself.
56For example, Foreman-Peck and Manning (I988) on teiecommunications.
References
Ashworth, Mark and Peter Forsyth, 1986, British Airways: Privatization and airline regulatory
procedure, in: John Kay, Colin Mayer and David Thompson, eds., Privatisation and
regulation: The U.K. experience (Clarendon Press, Oxford) ch. 8.
Aylen, Jonathan, 1988, The privatization of the British Steel Corporation, Fiscal Studies 9(3),
l-25.
Baldwin. John R., 1975, The regulatory agency and the public corporation: The Canadian air
transport industry (Ballinger, Cambridge).
Batstone, Eric, Anthony Femer and Michael Terry, 1984, Consent and efIiciency: Labour
relations and management strategy in the state enterprises (Basil Blackwell, OXrord).
Beesley, Michael and Stephen Littlechild, 1983, Privatization: Principles, problems and priorities,
Lloyds Bank Review, July, l-20.
B&tan, Samuel, 1984, The politics and economics of privatization, Political Quarterly 55,
109-128.
Chambers, David, 1988, Managing operations and the relevance of privatization, in: V.V.
Ramanadham, ed., Privatization in the UK (Routledge, London) 140-152.
Curwen, Peter J., 1986, Public enterprise: A modem approach (St. Martins Press, New York!.
Cyert, Richard M. and James G. March, 1963, The theory of the lirm (Prentice-Hall, New
York).
Demsetz, Harold and Kenneth Lehn, 1985, The structure of corporate ownership: Causes and
consequences, Journal of Political E;=onomy 93, 1155-l 177.
Eckel, Catherine C. and Theo Vermaeien, 1986, Inizrnal iqulation: The effects of government
ownership on the value of the firm, Journal of Law and Economics 29, 381-403.
Fama, Eugene F., 1980, Agency problems and the theory of the firm, Journal of Political
Economy 88, 288-307.
Foreman-Peck, James and Dorothy Manning, 1988, How well is BT performing? An intemational comparison of telecommunications total factor productivity, Fiscal Studies 9(3), 54-67.
Gilbert, Richard J., 1986, Pre-emptive competition, in: Joseph E. Stiglitz and G. Frank
Mathewson, eds., New developments in the analysis of market structure (MIT Press,
Cambridge) 9&l 23.
Grossman, Sanford J. and Oliver D. Hart, 1980, Takeover bids, the free-rider problem. and the
theory of the corporation, Bell Journal of Economics 11, 4264.
Grossman, Sanford 9. and Joseph E. Stiglitz, 1980, Stockholder unanimity in making production
and linance decisions, Quarterly Journal of Economics 94, 543-566.
Grout, Paul, 1987, The wider share ownership programme, Fiscal Studies 8(3), 5974.
Hart, Oliver D., 1983, The market mechanism as an incentive scheme, Rand Journal of
Economics 14, 366382.
Heald, David, 1984, Privatization and public money, in: David Steel and David Heaid, eds.,
Privatizing public enterprises: Options and dilemmas (Royal Institute of Public Administration, London) ch. 2.
Helm, Dieter, 1988, Regulating the electricity supply industry, Fiscal Studies 9(3), 86105.
Holmstrom, Ben& 1979, Mci;i?li hazard and observability, Bell Journal of Economics 14 74-91.
Jaffer, Sue and David Thompson, 1986, Deregulating express coaches: A reassessment, Fiscal
Studies 7(4), 45-68.
Jensen, Michael C. and William H. Meckling, 1979, Property rights and production functions:
An application to labor-managed firms and codetermination, Journal of Business 52, 469.
168 R.E. Caves, Lessons from privatization in Britain
Jones, Leroy, Pankaj Tandon and Ingo Vogelsang, forthcoming, Selling public enterprises: The
economics of privatization (MIT Press, Cambridge).
Kay, John, Colin Mayer and David Thompson, eds., 1986, Privatization and regulation: The
U.K. experience (Clarendon Press, Oxford).
Kay, John and 2. Aubrey Silberston, 1984, The new industrial policy – privatization and
competition, Midland Bank Review, Spring, 8-16.
Kay, J.A. and D.J. Thompson, 1986, Privatisation: A policy in search of a rationale, Economic
Journal 96, 18-32.
Mayer, Cohn, 1987, Public ownership: Concepts and applications, Discussion paper no. 182
(Centre for Economic Policy Research, London).
Mayer, Cohn, and Shirley Meadowcroft, 1986, Selling public assets: Techniques and financial
implications, in: John Kay, Cohn Mayer and David Thompson, eds., Privatisation and
regulation: The U.K. experience (Clarendon Press, Oxford) ch. 17.
Millward, Robert, 1982, The comparative performance of public and private ownership, in: Lord
Roll of Ipsden, ed., The mixed economy (Macmillan, London) 58-93.
Molyneux, R. and D. Thompson, 1987, National&d industry performance: Still third-rate?
Fiscal Studies 8(l), 48-82.
Moore, John, 1986, The success of privatisation, in: John Kay, Cohn Mayer and David
Thompson, eds., Privatisation and regulation: The U.K. experience (Clarendon Press,
Oxford).
Mulley, Corinne and Mike Wright, 1986, Buy-outs and the privatisation of National Bus, Fiscal
Studies 7(3), 1-24.
Newbery, David M., 1986, The privatisation of British Gas and possible consequences for the
European us market, Discussion paper no. 101 (Centre for Economic Pohcy Research,
London).
Newman, Karin, 1986, The selling of British Telecom (St. Martins Press, New York).
Peltzman, Sam, 1971, Pricing in public and private enterprises: Electric utilities in the United
States, Journal of Law and Economics 14, 109-147.
Pickering, Craig, 1984, The mechanics of disposal, in: David Steel agd David Heald, eds.,
Privatising public enterprises: Options and dilemmas (Royal Institute of Public Administration, London) ch. 3.
Pirie, Madsen, 1985, Privatization in theory and practice (AS1 Research, London).
Pryke, Richard, 1971, Public enterprise in practice: The British experience of nationalization
over two decades (MacGibbon and Kee, London).
Pryke, Richard, 1981, The nationalised industries: Policies and performance since 1968 (Martin
Robertson, Oxford).
Pryke, Richard, 1982, The comparative performance of public and private enterprise, Fiscal
Studies 3(2), 68-81.
Redwood, John and John Hatch, 1982, Controlling public industries (Basil Blackwell, Oxford).
Rees, Roy, 1984, A positive theory of public enterprise, in: Maurice Marchand, Pierrre Pestieau,
and Henry Tuikens, eds., The performance of public cntcrp&s: Concepts and measurements
(North=Hoti*mA sLU..Y, , A .msterdam) !?9-19!.
Robson, William A., 1962, Nationalized industry and public ownership, 2nd ed. (Allen and
Unwin, London).
Scharfstein, David, 1988, Product-market competition and managerial slack, Rand Journal of
Economics 19, 147- 155.
Sharkey, William W., 1982, The theory of natural monopoly (Cambridge University Press,
Cambridge).
Sharpe, Tom, 1984, Privatization, regulation and competition, Fiscal Studies 5(!), 47-60.
Shepherd. William G., 1968, Alternatives for public expenditure, in: Richard E. Caves, ed.,
Britains economic prospects (Brookings Institution, Washington) 38 l-447.
Shepherd, William G., 1976, Public enterprise: Economic analysis of theory and practice
(Lexington Books, Lexington, MA).
Shleifer, Andre and Robert W. Vishny, 1986, Large shareholders and corporate control, Journal
of Political Economy 94, 461-488.
Starkie, David and David Thompson, 1985, Privatising Londons airports (Institute for Fiscal
Studies, London).
R.E. Caves, Lessons from privatization in Britain 169
Steel, David, 1984, Government and the new hybrids, in: David Steel and David Heald, eds.,
Privatixing public enterprises: Options and dilemmas (Royal Institute of Public Administration, London) ch. 7.
Swann, Dennis, 1988, The retreat of the state: Deregulation and privatisation in the UK and US
(WheatsheaL Sussex).
Sykes, A. and C. Robinson, 1987, Current choices – good ways and bad to privatise electricity
(Centre for Economic Policy Research, London).
Thomas, David, 1984, The union response to denationalization, in: D&d Stee! and D&d
Heald, eds., Privatizing public enterprises: Options and dilemmas (Royal Institute of Public
Administration, London), ch. 7.
Thompson, David, 1988, Privatisation: Introducing competition, opportunities and constraints,
in: V.,. Ramanadham, ed., Privatisation in the UK (Routledge, London) 39-58.
U.K. Office of Telecommunications, 1986, Review of British Telecoms tariff charges.
U.S. Presidents Commission on Privatization, 1988, Privatization: Toward more effective
government (Government Printing Office, Washington).
Utton, M.A., 1986, The economics of regulating industry (Basil Blackwell, Oxford).
Vickers, John and George Yarrow, 1985, Privatization and the natural monopolies (Public
Policy Centre, London).
Vickers, John and George Yarrow, 1988, Privatization: An economic analysis (MIT Press,
Cam bridge).
Winchester, David, 1983, Industrial relations in the public sector, in: George Sayers Bain, ed.,
Industrial relations in Britain (Basil Biackwell, Oxford) 155-l 78.
Yarrow, George, 1986, Privatization in theory and practice, Economic Policy 2, 323-364.

Real Reviews from our Customers

Academic Writing Service of a Professional Level

Any academic writer who wishes to join our team of professional writers must possess all the following qualities:

To write an exemplary academic paper, you must have good critical thinking skills, possess the proper knowledge of the discipline, and be knowledgeable about applying an academic writing style.

Our Mission

Get professional help from our brilliant, skilled, and experienced essay writers

Academic Writing Help From Professionals

Expert Assignment Help for College/University Students

Proceed to order page

Online Academic Help With Different Subjects

Literature

Finance

Computer science

Psychology

Engineering

Nursing

Sociology

Business

Statistics

Law

Affordable prices

HIGH SCHOOL

from

$10 page

COLLEGE

from

$13 page

UNIVERSITY

from

$14 page

Calculate price

Cheap essay writing service

Proceed to order page

Cheap paper writing service provides high-quality essays for affordable prices

Affordable essay writing service: get custom papers created by academic experts

Plagiarism-free affordable papers

Money-back guarantee

On-time Delivery

24/7 support

Proceed to order page

Continue to order Get a quote

Journal of Economic Behavior and Organization

Real Reviews from our Customers

Academic Writing Service of a Professional Level

Our Mission

Get professional help from our brilliant, skilled, and experienced essay writers

Academic Writing Help From Professionals

Expert Assignment Help for College/University Students

Online Academic Help With Different Subjects

Literature

Finance

Computer science

Psychology

Engineering

Nursing

Sociology

Business

Statistics

Law

Affordable prices

Cheap essay writing service

Cheap paper writing service provides high-quality essays for affordable prices

Affordable essay writing service: get custom papers created by academic experts

Plagiarism-free affordable papers

Money-back guarantee

On-time Delivery

24/7 support

Journal of Economic Behavior and Organization

Real Reviews from our Customers

Academic Writing Service of a Professional Level

Our Mission

Get professional help from our brilliant, skilled, and experienced essay writers

Academic Writing Help From Professionals

Expert Assignment Help for College/University Students

Online Academic Help With Different Subjects

Literature

Finance

Computer science

Psychology

Engineering

Nursing

Sociology

Business

Statistics

Law

Affordable prices

Cheap essay writing service

Cheap paper writing service provides high-quality essays for affordable prices

Affordable essay writing service: get custom papers created by academic experts

Plagiarism-free affordable papers

Money-back guarantee

On-time Delivery

24/7 support

Calculate the price of your order

Our guarantees

Money-back guarantee

Zero-plagiarism guarantee

Free-revision policy

Privacy policy

Fair-cooperation guarantee