ARE DISAGREEMENTS AMONG MALE AND FEMALE ECONOMISTS MARGINAL
AT BEST?: A SURVEY OF AEA MEMBERS AND THEIR VIEWS ON ECONOMICS
AND ECONOMIC POLICY
(forthcoming in Contemporary Economic Policy)
ANN MARI MAY, University of Nebraska-Lincoln
MARY G. MCGARVEY, University of Nebraska-Lincoln
ROBERT WHAPLES,* Wake Forest University
The authors survey economists in the U.S. holding membership in the American
Economic Association (AEA) to determine if there are significant differences in views
between male and female economists on important policy issues. Controlling for place of
current employment (academic institution with graduate program, academic institution undergraduate only, government, for-profit institution) and decade of Ph.D., the authors
find many areas in which economists agree. However, important differences exist in the
views of male and female economists on issues including the minimum wage, views on
labor standards, health insurance, and especially on explanations for the gender wage gap
and issues of equal opportunity in the labor market and the economics profession itself.
These results lend support to the notion that gender diversity in policy-making circles
may be an important aspect in broadening the menu of public policy choices.
* The authors would like to thank Professor Julia McQuillan, Director of the Bureau for Sociological Research,
University of Nebraska-Lincoln for her helpful suggestions on the survey questionnaire, Michael L. May,
Swarthmore College '11 for his research assistance, and the Research Fund of the Department of Economics at the
University of Nebraska-Lincoln for assistance in funding a portion of this research. We also thank three anonymous
referees for their very helpful comments and suggestions.
May: Professor of Economics, University of Nebraska-Lincoln, Lincoln, NE.
Email: [email protected]
McGarvey: Associate Professor of Economics, University of Nebraska-Lincoln, Lincoln,
NE. Email: [email protected]
Whaples: Professor of Economics, Wake Forest University, Winston-Salem, NC.
Email: [email protected]
I. INTRODUCTION
Few changes in the demographics of higher education in the U.S. have been as pronounced as the
increasing percentage of doctoral degrees awarded to women in the past forty years. In 1975 men
received the majority of bachelors, masters, and doctoral degrees; by 2000, the majority of
bachelor’s and master’s degrees were awarded to women. In 2002, for the first time in U.S.
history, more American women than American men received doctoral degrees from U.S.
universities and today more doctorates are awarded to women than to men at U.S. universities.1
Although the proportion of women in economics continues to lag behind that of other
social science disciplines, data from the Survey of Earned Doctorates shows that women
represent 34.5 percent of new doctorates in economics from U.S. universities in 2010, up from
27.0 percent in 2000 (Doctorate Recipients from US Universities 2010: Table 14). This increase
represents a 7.5 percentage point increase over the period as compared with an average 2.9
percentage point increase for all other fields. As a result, increasing numbers of female
economists are actively involved in research and policy-making on a variety of levels including
the Board of Governors of the Federal Reserve Bank to the Council of Economic Advisors. But
does it make any difference if men or women are at the table when economic policies are
debated and alternatives considered? Or, are disagreements between male and female economists
marginal at best?
In this study we survey male and female economists who are members of the American
Economic Association (AEA) and provide what is the first systematic study of the views of male
and female economists on a wide variety of policy issues to determine if there are differences in
1
the views of male and female economists after controlling for place of current employment
(academic institution with graduate program, academic institution - undergraduate only,
government, for-profit institution) and decade of Ph.D.
A Consensus and the Economics Profession
Numerous studies using survey data to examine the degree of consensus among
economists have been published over the past twenty-five years (Kearl et al. 1979; Frey et al.
1984; Alston, Kearl and Vaughn 1992; Fuller and Geide-Stevenson 2003; and Whaples 2006).
While these surveys appeared relatively late in economics as compared with other social science
disciplines, the importance of consensus within the discipline has a long history. In fact, concern
over consensus dates back to the origins of the American Economic Association where the
annual meeting offered a forum for developing consensus in a discipline thought to reflect a
sometimes embarrassingly wide array of views on economic policy questions. Economists, in
particular, had much to gain in the professionalization of higher education and the lack of
consensus on economic questions served as yet one more reminder of the possibly less-thanscientific nature of a discipline aspiring to be scientific (Coats 1993).
Recent studies examine consensus among economists by focusing on underlying
assumptions, methodology, and policy issues. The results of these studies indicate that
economists are less supportive of government intervention in the economy than their
counterparts in other social science disciplines (Klein and Stern 2005 and 2007) and that a fair
degree of consensus exists among economists. Kearl et al. (1979 p. 36) in their study of U.S.
economists in a survey conducted in 1976 report more consensus on microeconomic than
macroeconomic issues, but overall report that the “perceptions of wide-spread disagreement are
simply wrong.” In a follow up study, Alston, Kearl, and Vaughan (1992) find that although 2
opinions of U.S. economists on particular issues had shifted, a similar pattern of consensus
emerged with the caveat that degree vintage and subgroup (AEA membership, government
economists, business economists, teachers of principles of economics courses at four year
institutions, and institutional economists) are also important determinants of consensus on
various questions. Alston, Kearl and Vaughn (1992) find considerable consensus among
economists overall. Yet, as Fuchs et al. (1998) later point out, the seven questions about policy in
Alston, Kearl and Vaughn (1992) show a very high level of disagreement. In their own study
Fuchs et al. (1998) find considerable disagreement between labor and public economists about
policy proposals in their areas of specialization. In an additional study, Fuchs (1996) surveyed
health economists and found considerable disagreement about major issues of health policy.
Other studies have examined the influence of international differences (Frey et al. 1984),
age differences or age upon receipt of degree (Klein and Stern 2005 and Alston, Kearl, and
Vaughn 1992), political party and voting patterns (Klein and Stern 2005 and 2007), school of
thought (Alston and Vaughan 1993), and economic field (Kearl et al. 1979 and Fuller and GeideStevenson 2003) to determine if these factors produce differences in the views of economists.
Yet, absent from these discussions is any examination of gender differences among economists.
In contrast to these previous studies, only a few studies examine gender differences in
opinions of economists.2 Davis (1997), in his study of AEA members, examines economists’ views of methodology, the social value of research, perceptions about the publication of that
research, and perceptions about the influence of race and gender on economic research. He
reports there are significant differences in the views of male and female economists with respect
to whether author recognition among professional economists influences the probability of an
article’s acceptance in refereed economics journals in the U.S., whether there is a “good-old3
boy” network in the economics profession, and whether economists are amenable to interdisciplinary research approaches. Specifically, Davis finds that although the majority of
male and female economists have similar opinions, women typically reach a much stronger
consensus – particularly on issues of equity and fairness in the economics profession.
In her study of AEA economists conducted in 1992, Albelda (1997) examines a variety of
questions concerning gender and the economics profession. According to Albelda, men were
much less interested than women in having more attention paid to topics such as women’s labor force participation, the impact of fiscal and monetary policies on women and the family
structure, wage discrimination, and the economic status of minority women (Albelda 1997, pp.
79-80). Moreover, there was little support for the notion that feminism has impacted the
discipline of economics – nor did economists express much interest in seeing more feminist
economic analysis. Most notable, however, were the large gender gaps in response to questions
about the treatment of women in the economics profession (Albelda 1997, p. 69). As Albelda
reports, almost one-third of male respondents agree with the statement that it is easier for women
to get tenure and promotions than it is for men, while less than 4 percent of women agreed with
the statement (Albelda 1997, p. 81).
Hedengren, Klein and Milton (2010) examine gender differences in policy-oriented
petitions endorsed by economists, finding that men are much more likely to sign “libertyenhancing” petitions, which call for a smaller role for the state, while women economists are
somewhat more likely to endorse petitions calling for greater governmental intervention. Davis
et al. (2011) conduct a survey on a wide range of issues (including favorite economic thinkers,
economics journals, and blogs) and find that women economists are much more likely than men
to be members of the Democratic Party and to favor policies that restrict individual liberty. In
4
addition, Stastny (2010) finds that women economists in the Czech Republic tend to favor much
more government intervention than do male economists.
While these studies offer important insights into gender differences on views of the
economics profession, they ask a fairly narrow range of questions and are not designed to
systematically explore the nuances of differences between male and female economists. Given
the changing demographics of the economics profession over the past thirty years, these
differences, if they exist, may have significant implications for policy-making outcomes.
B. Gender and Economics in the U.S.
Although the “gender gap” in voting and party identification has been a topic of widespread interest since the 1980 election, less attention has been paid to gender differences in
policy preferences. Yet, several studies indicate that gender differences in policy preferences
exist in the U.S. and have increased since the 1970s (Smith 1984; Shapiro and Mahajan 1986;
Inglehart and Norris 2000; Saad 2003; and Pew Research Center 2009). While disagreement
exists as to the cause of these differences in voting patterns, party identification, and public
opinion surveys on policy issues, women and men appear to differ most on matters concerning
violence and force and so-called compassion issues concerning aid to the poor, unemployed,
sick, and others in need, and in their views on regulatory policies (Shapiro and Mahajan 1986, p.
44-45).
While gender differences in the general population are well studied, gender differences in
the views of economists have received little attention. In fact, no systematic study of gender
differences in views of American economists on a wide variety of economic policy issues has yet
5
been undertaken. Our study attempts to remedy this by examining the views of male and female
economists who are members of the AEA in the U.S. Using survey data on core precepts and
approaches in economics, views on market solutions and government intervention, specific
policy issues, and gender equality in economics and society we ask the question, “Do male and female economists share the same views on underlying assumptions, methodological approaches,
policy solutions, perceived problems in economics, and equal opportunity in society and the
economics profession?” Because survey data from non-economists indicates that there are often
significant gender differences in views on policy issues (Saad 2003), we are interested to see if
these differences disappear among economists with shared training and backgrounds.
II. METHODOLOGY
A Data and Descriptive Statistics
Our goal is to estimate the extent of differences in opinions on economic methodology
and policy issues between male and female economists with doctoral degrees who are members
of the AEA. The population from which we sampled is the list of members in the 2007 American
Economic Association Directory who received both their undergraduate and Ph.D. degrees from
United States institutions.3 The selection process yielded 202 randomly selected male members
and 202 randomly-selected female members to whom the survey was mailed in early November
2008. The overall response rate was 35.4 percent which is similar to previous surveys.4
< INSERT TABLE 1 HERE >
Table 1 contains descriptive statistics (overall and disaggregated by sex) for the entire
sample, for the 143 members who returned usable surveys, and for the 261 non-responders.
Characteristics of the AEA members include demographic information on sex, year of Ph.D., and
6
current type of employment. This information was obtained from survey responses of those who
returned the surveys and from the AEA directory entries of the non-responders. Additionally,
Table 1 reports whether or not the AEA member chose to list her or his research interests in the
2007 AEA directory. This information was included as an indication not only of the economist’s research activity but also the willingness of the individual to respond to survey questions.
The original, random sample of AEA members was evenly divided between men and
women by design. Approximately 67 percent of those sampled are employed in academic
institutions with 41 percent teaching in graduate programs and 26 percent in undergraduate
programs. Fourteen percent of those sampled work in the for-profit sector and 11 percent are
employed by the government. The remaining eight percent are either retired, not in the formal
labor market, or working in the non-profit sector. Although, in our sample, it is more likely for
women to be employed in academic institutions than men, and more likely for men to work in
the government or for-profit sectors than women, these differences in employment rates are not
statistically significantly different from zero. The economists in the AEA survey earned their
doctoral degrees about 22 years ago with women’s degrees earned about 5 years more recently than men’s and the average difference is statistically significant. It is interesting that, in our random sample of AEA members, male economists are more likely to list their research interests
in the AEA directory than female economists. The ten percentage point difference is also
statistically significant.
A comparison of the responders’ and non-responders’ descriptive statistics shows that
most of the characteristics are similar. Forty-five percent of those responding to the survey are
women whereas 52 percent of the non-responders are women. The distribution of overall
employment across sectors is roughly the same with the exception of employment in an
7
academic institution with a graduate program. Formal statistical tests find evidence that the
overall proportions of economists teaching in graduate institutions differ for the responders and
non-responders (.35 versus .44) and that it is the male responders who are statistically
significantly less likely (by 11 percentage points) to teach in graduate institutions than the male
non-responders. The proportion of economists who list their research interests in the AEA
directory is 55 percent for the responders and 62 percent for the non-responders. On average,
those responding to the survey received their Ph.D.s about two and a half years more recently
than those not responding and this difference is statistically significant. A smaller proportion of
those economists who responded to the survey received their degrees in the 1970s than those
who did not respond.
Most of the statistically significant male and female differences in the original random
sample remain significant in the sample of responders. Male economists are more likely to list
their current research in the AEA directory and received their Ph.D.s earlier than female
economists. In the responders’ sample, male economists are more than twice as likely to be working in the governmental sector as female economists. Although this relative difference in
government employment exists in the original random sample, it is larger and statistically
significant among the responders.
Our statistical analysis of gender differences in economists’ opinions on methodology
and policy issues is based on the responses of those who returned their surveys; we do not know
the opinions of the non-responders. It is possible that estimation using only the observable
survey responses will lead to inconsistent estimates of the gender effect. We address this issue in
the next section by estimating the decision to respond to the survey as a probit model and testing
8
for non-response bias in our estimation of gender differences in the group-level scaled answers
using Heckman’s (1979) procedure. B Scaled Responses to Group Questions and Test for Selection Bias
The survey questions can be classified into five groups, each group designed to ascertain
the respondent’s views about different types of issues. The first group of questions relate to core
principles in economics and economic methodology. The second through fourth groups examine
views on market solutions and government intervention, government spending, taxing, and
redistribution, and the environment. The fifth group of questions asks specifically about equal
opportunity in society and gender equality in the economics profession. The wide variety of
policy-related questions allows us to examine possible gender differences on a host of the most
important and topical issues currently facing economists.
Before examining gender differences in answers to specific questions, we first construct
an overall measure of the economist’s opinion on each of the five group topics. The Appendix describes the construction of each scaled opinion measure and the survey questions upon which
each is based. Tables A1 and A2 provide descriptive statistics of the opinion measures and
correlations of the responses between topics. We find that the Cronbach’s Alpha values are greater than .70 for each of the scaled answers, indicating that each is a reliable measure of the
overall opinion on the group topic.
Our goal is to estimate the mean difference in opinion on economic methodology and
policy issues of male and female Ph.D. economists who received their educational training in the
United States. In order to better isolate the effect of gender on economists’ opinions, we need to control for those variables that are both correlated with the economist’s opinions on policy and 9
methodology and with the economist’s gender. Because female economists received their terminal degrees more recently, on average, than male economists, and opinions might be related
to degree vintage, we include four binary indicators of the decade the Ph.D. was received as one
of our control variables. The omitted category of economists contains those who received their
Ph.D.s prior to 1970. We also include controls for the economist’s place of employment. Although there were no statistically significant differences in the proportions of men and women
employed in graduate or undergraduate-only academic institutions, nor in the for-profit sectors,
there might be differences in types of employment by gender after accounting for degree vintage.
The economists’ opinions on policy issues and methodology might reasonably be related to, or
influenced by, their type of work. For these reasons, we also include the mutually exclusive
employment category variables, graduate, for profit, government, and undergrad as control
variables in the regression. The omitted category includes employment in the non-profit, nonacademic, non-government sector, not currently employed or retired.
We base our inference on the estimated coefficient on the binary indicator, female, in the
model,
yi , j   j1 femalei   j 2 PhD1970si   j 3 PhD1980si   j 4 PhD1990si   j 5 PhD 2000si
  j 6 graduatei   j 7 governmenti   j 8 profiti   j 9undergradi   j 0   i , j ,
(1)
where i denotes the ith economist and j denotes the jth question or group of questions. Because
we cannot observe the survey answers of those economists who did not respond, even if the
regression error is independent of the control variables, it is possible that estimation of  j1 using
only the responders’ observations will produce inconsistent and biased estimates of the gender 10
effect. We test the null hypothesis of no selection bias using the Heckman (1979) two-stage
procedure.
We assume that the decision to respond to the survey follows a probit model,
P( si  1| xi )  P( Z  xi ) , where si = 1 if individual i responds to the survey and si =0, if not.
The (1 x k) vector of variables, xi, that influence the choice to respond to the survey includes the
control variables in equation (1). We also include a binary control for whether or not the
economist lists her or his research interests in the AEA 2007 directory (listed research) and the
interaction of listed research with for profit to allow the effect of listed research on the
probability of response to differ for those working in the for-profit sector.
In this framework, the economist responds to the survey (si = 1) if the unobservable net
benefit from doing so ( si* ) is positive, or if si*  xi  ui  0 , where ui is a standard normal
random variable and is distributed independently of xi. Under these assumptions, consistent
estimation of the gender effect on economists’ opinions on question j (  j1 ) can be obtained
using only the responders’ information if the error term in equation (1) is uncorrelated with ui ,
the error term in the response equation. We test the hypothesis that these errors have zero
ˆ / CDFz (xi α)
ˆ as a
correlation by adding the estimated inverse Mills ratio, IMRi = pdf z (xi α)
regressor in equation (1) and testing that its coefficient equals zero.
< INSERT TABLE 2 HERE >
Table 2 reports the probit estimates of the response equation. The results indicate that the
probability of responding to the survey is lower for female economists relative to males and for
economists employed in two of the included job categories relative to males and those who are
11
retired or employed in non-academic, non-government, or for-profit institutions. Those
economists who earned their Ph.D. in the 2000s are more likely to respond to the survey, relative
to those who earned their degrees prior to 1970. Those economists who list their current research
interest in the AEA directory are less likely to respond; however, those who work in for-profit
institutions and list their current research are more likely to respond.
< INSERT TABLE 3 HERE >
Table 3 presents the ordinary least squares estimation of equation (1) for each of the five
topic groups, with and without the inclusion of the estimated inverse Mills ratio. The dependent
variable is the scaled response to the questions on each topic, standardized to have zero mean
and unit variance, so that the coefficient on female is the average difference in female
economists’ response relative to male economists’ in standard deviation units. The results indicate that male and female U.S. trained, AEA members generally agree on core economic
precepts and methodology and on U.S. environmental policy but differ on issues related to
market solutions and government intervention, government-backed redistribution, and the extent
of gender inequity in the U.S. labor market and within the economics profession.
Tests of the null hypothesis of no selection bias for each topic category provide no
evidence that the selection equation error is correlated with the error in equation (1); moreover,
the inclusion of the inverse Mills ratio in the regressions has little effect on the OLS point
estimates and estimated standard errors. These results support the validity of our using the
sample of responding economists to estimate model (1) and suggest that our inference on gender
differences will not suffer from selection bias.
12
III. GENDER DIFFERENCES IN ECONOMISTS’ VIEWS ON POLICY ISSUES
This section presents Seeming Unrelated Regression (SUR) estimation results based on
the survey response to estimate gender differences in economists’ views on economic methodology and policy issues. The SUR model is relevant when the regression errors are
correlated across equations and have different variances. For convenience, we reproduce our
model of economist i’s response to question j (or topic j) from the previous section,
yi , j   j1 femalei   j 2 PhD1970si   j 3 PhD1980si   j 4 PhD1990si   j 5 PhD 2000si
  j 6 graduatei   j 7 governmenti   j 8 profiti   j 9undergradi   j 0   i , j ,
(1)
where now we treat equation j as part of a SUR system of equations. The error terms represent
those unobservable individual-specific factors that affect opinions but are unrelated to gender,
decade in which the Ph.D. is earned, and type of employment. We allow the variances of the
errors to differ by question, the errors to be correlated across questions, and the error covariance
matrices to differ for males and females. The Generalized Least Squares (GLS) method increases
the precision of our estimates by incorporating the estimated relationship among unobservable
factors that form opinions on related topics.
Our first estimation strategy is to measure gender differences in economists’ views on general issues addressed by the five groups of survey questions. This provides a more precise
measure of opinion on the issue by incorporating repeated observations on the same topic
(averaging an individual’s answers to all questions within the group topic) but limits the sample to individuals who answered all questions within the five groups. Our second strategy is to
estimate the extent of gender differences in average responses to specific questions within a
general topic area. The dependent variable is individual i’s response to question j. Although yi,j is
13
a less precise estimate of individual i’s opinion (it is based on the response to only one question rather than an average of repeated responses on a topic), the sample size increases to the number
of economists who answered all questions in one group rather than all groups.
A Views on General Topic Areas
The first SUR system explains the standardized, scaled answers that measure the
deviations from the average economists’ views on the five topics: core precepts and economic methodology, market solutions and government intervention, government spending, taxing, and
redistribution, U.S. environmental policies, and gender and equal opportunity. The optimal
weighting scheme incorporated in the GLS systems estimation increases the efficiency of the
estimates over the OLS method. The number of observations, however, is smaller for the systems
estimation because it is based on the number of economists that have complete information for
all questions in each of the five groups.
< INSERT TABLE 4 HERE >
Table 4 contains the GLS estimates of the coefficients in equation (1) for j= 1,2,...,5,
corresponding to the five group topics. The dependent variables are the scaled responses,
standardized to have zero mean and unit variance, so the coefficient on a binary control variable
(female, employment category, or decade of Ph.D.) is the average difference (in standard
deviation units) in the response of economists who fall into the respective category relative to
those in the omitted category, given the other controls. The GLS system results confirm the
conclusions based on the OLS and Heckit estimates of Table 3. Male and female members of the
AEA with doctoral degrees from U.S. institutions appear to agree on core precepts and economic
methodology whereas female economists tend to favor government-backed redistribution
14
policies more than males, view gender inequality as a problem in the U.S. labor market and
economics profession more than males, and favor government intervention over market solutions
more than their male counterparts. The mean gender differences in opinions on these topics are
relatively large. The mean views of women economists on government spending, taxing, and
redistribution and on gender inequality are both approximately one standard deviation away from
the mean opinion of male economists. Although the divergence in magnitudes of the GLS and
OLS estimated gender difference in opinion on U.S. environmental policies is not large, the GLS
estimate is statistically significant. The mean response of female economists is about .45
standard deviation greater than the mean male response, indicating that women tend to favor an
increase in U.S. environmental protection more than men.
Generally speaking, the demographic controls contribute little to explaining views on the
five group topics once one controls for the economist’s gender.5 The economists’ place of employment appears to have no effect on opinion once gender and degree vintage are
considered. The results indicate a statistically significant and relatively large difference in
opinion between those who earned their degrees prior to 1970 and those who earned their
degrees more recently. Those who graduated in the 1970s or 1980s are less likely to agree with
core precepts and economic methodology than economists who earned their degrees before 1970.
The results also indicate that economists with degrees from the 1980s are more likely to favor
government interventions over market solutions than economists with degrees prior to 1970.
Interestingly, the only characteristic that matters for the scaled answer to the Gender and Equal
Opportunity questions is whether or not the economist is female.
The results from system GLS estimation of economists’ mean responses to the five groups of questions on economic methodology, the role of government (in allocating resources,
15
redistributing wealth, protecting the environment), and equal opportunity provide strong
evidence of gender differences. Female economists’ average responses differ from male economists’ by a statistically significant margin in four of the five topic areas after controlling
for type of employment and degree vintage. Mean differences in views on government-backed
redistribution and on gender and equal opportunity also differ by a substantial margin - about one
full standard deviation.
B Views on Core Precepts and Economic Methodology
We include several questions designed to address core economic precepts – one to
examine the question of individuals as rational utility-maximizers and another to examine the
assumption that human wants are unlimited. Also included in this group are questions concerning
economic methodology that attempt to ascertain views on mathematics in economic modeling,
deductive versus empirical approaches to the study of economics, and two questions that
examine potential differences in views on modeling of household decision-making and
measuring aggregate economic output. GLS estimation of a SUR system for responses to the
Group 1 questions indicate no difference in mean opinions by gender after controlling for degree
vintage and place of employment.6
Economists’ mean responses indicate agreement with the notions that individuals are utility-maximizers and that human wants are unlimited. Likewise, when examining
methodological questions in the economics profession there appears to be no significant
difference in beliefs. On average, economists agree that mathematical modeling should be an
important part of economics and that research on households should include intra-household
decision-making. Economists’ mean response to question 23 indicates a neutral view on GDP
16
being an insufficient measure of overall economic performance. The GLS estimation results for
the response to question 39 indicate that, although there is no difference in opinion based solely
on gender, those economists who work in the for-profit sector are more likely to believe that the
profession relies too much on empirical analysis and not enough on deduction.
It would appear that on several core concepts in economics and methodology, the beliefs
of male and female economists are very similar. Male and female economists that are members
of the AEA appear to start from the same assumptions about how people behave and how to
approach the study of economics.
C Views on Market Solutions and Government Intervention
Previous studies such as Klein and Stern (2005) confirm that economists are less
supportive of government intervention in the economy than their counterparts in other social
science disciplines. Indeed, it is perhaps the penchant for free market solutions that is the
hallmark of the discipline (Fourcade 2009). Yet, when we examine the question of support for
market solutions versus government intervention, interesting differences between male and
female economists begin to emerge.
< INSERT TABLE 5 HERE >
Despite the similarities in views on core principles and methodological approaches to
economics, our study shows differences in the views of male and female economists in their
support of market solutions versus government regulation. The GLS estimation results indicate
that the mean responses of women economists are significantly lower than those of male
economists, suggesting women economists are less supportive of market solutions over
government interventions than male economists. The only exception is on the issue of whether
17
the government should tax unhealthy foods where both men and women appear approximately
equal in their opposition.
Table 5 presents GLS estimates of male and female economists’ expected response to
each proposition for which the estimated female mean difference exceeds one half a point on the
Likert-type scale. For those questions, the probability of responding “disagree” or “strongly disagree” to the proposition conditional on gender, degree vintage, and place of employment is
estimated by a linear probability model.7 The table reports the estimated probabilities of
disagreeing with the proposition at the sample mean values of the Ph.D. and place of
employment dummy variables for both male and female economists. After controlling for Ph.D.
vintage and type of employment, we find that women are more likely to disagree that either the
European Union or the United States has excessive government regulations by about 20
percentage points. Female economists are 27 percentage points more likely to disagree that
parents should be given educational vouchers and 14 percentage points more likely to disagree
that Wal-Mart generates positive net benefits. In other words, evidence suggests that male
economists are more likely to prefer market solutions to economic problems.8 Although the SUR
estimated mean difference in opinion on whether the U.S. should drill for oil in the Arctic
National Wildlife Refuge indicates a lower level of agreement for women, the 12 percentage
point difference in the probability of disagreement is not statistically significant. According to
the SUR results, the largest difference in the mean response is due to degree vintage. Those
economists who earned their degrees in the 1980s or 1990s, regardless of their gender or place of
employment, are much more likely to oppose drilling in the Arctic National Wildlife Refuge than
economists whose Ph.D.s were granted prior to 1970.
18
It is interesting to us that there appears to be little disagreement between male and female
economists about the question of whether the U.S. should impose taxes on unhealthy foods –
what many in the popular press have dubbed an example of the so-called “nanny state.” Both male and female economists show little support for the imposition of a tax on unhealthy foods.
D Views on Government Spending, Taxing, and Redistribution
Differences in views between male and female economists not only reflect variations in
preferences for market solutions versus government intervention but also appear to reflect values
differences – some of which correspond to what have been called “compassion issues.” These differences may not emerge when we consider overall levels of government spending or taxation,
but may emerge more clearly when we ask specific questions about the nature of government
spending, income distribution, revenue financing options, as well as evaluating the impact of
various government programs. The estimation results indicate statistically significant gender
differences in opinions on each of the nine propositions; however, Table 6 reports only those
with mean differences greater than one half.
< INSERT TABLE 6 HERE >
When asked their opinions about the size of the government, the average male
economist’s response is closest to the “too large” choice whereas the average female economist’s response is closest to the “about right” response. Examination of the probability estimates shows that women are 24 percentage points more likely than men to believe the size of the government
is either “too small” or “much too small.” There are also statistically significant differences in mean responses between men and women economists in their views of the composition of
government spending and other questions about redistribution. For example, the mean response
19
to question 30 of a female economist is almost 2.0, indicating that current levels of military
spending are “too large” while the average male economist’s response is about 2.4, closer to the “about right” choice.9 Conversely, when asked whether employers should be required to provide
health insurance for their employees, the mean gender gap is almost one full point on the opinion
scale with the average male response at 2.4 closer to the “disagree” category. The estimated
proportion of female economists is .23 greater than the proportion of male economists who agree
or strongly agree with the proposition.
Several questions asked about the distribution of income and the tax structure as it relates
to income distribution. The estimated mean response of male economists indicates a belief that
the tax structure should remain at its current level of progressivity whereas the mean response of
female economists falls closer to a belief that taxes should be more progressive. In fact, women
are 41 percentage points more likely than men to favor a more progressive tax structure. A
comparison of economists’ mean responses to the issue of whether the U.S. income distribution should be more equal shows that the average male indicates disagreement while females’ average response is closer to a neutral opinion. The linear probability model estimates that
women are 32 percentage points more likely to agree or strongly agree with making the U.S.
income distribution more equal than men. Along the same lines, there is disagreement on
whether the U.S. should implement a tax on consumption and rely less on income taxes for
revenue. The average male economist is closer to being neutral with a tax on consumption while
the average female economist is closer to disagreeing. According to the point estimates, 54
percent of female economists either disagree or strongly disagree compared to 31 percent of male
economists. This result may not be surprising given the difference between male and female
economists on the question of making the tax structure more progressive.
20
We see the same gender differences in so-called “compassion issues” in questions about international trade and labor standards and the impact of the minimum wage. When asked if the
U.S. should link import openness to the labor standards of its export partners, the average male
economist’s response is closer to disagreement whereas the average female economist’s response is closer to neutral. Female economists are 30 percentage points more likely to agree or strongly
agree with linking openness to labor standards than male economists. The average female
economists’ opinion on the proposition that increasing the minimum wage leads to increased unemployment among unskilled workers is neutral whereas the average male indicates
agreement.
E Views on Environmental Policy Issues
On environmental issues, we ask questions about energy taxes in general, taxes on
emissions of greenhouse gases in particular, as well as ethanol subsidies to gauge the degree to
which male and female economists agree on the use of taxes and subsidies to discourage or shape
desired activities that may affect the environment. On this issue of taxes and subsidies, there
appears to be no significant difference in the opinions of male and female economists. On the
question of “nudging” environmental policy through various taxes, the average responses of both male and female economists indicate agreement that energy taxes should be increased along with
taxes on emissions of greenhouse gases. Men and women also show no divergence in average
opinions on U.S. policies favoring the environment over economic growth. Neither male nor
female economists indicate support for an increase in ethanol taxes.
21
F Views on Gender and Equal Opportunities
Although previous studies have not examined gender differences in views of economists
on policy issues, studies by Davis (1997) and Albelda (1997) both show differences in the views
of male and female economists concerning equity and equal opportunity in the economics
profession. In this section we examine survey results on a variety of questions related to notions
of equal opportunity and affirmative action policies in the U.S. as well as questions of gender
equality in the economics profession. These questions allow us to examine in more detail the
views of male and female economists on issues of equal opportunity.
< INSERT TABLE 7 HERE>
The results of our survey of male and female economists show that the area of largest
disagreement between men and women lies in views on equal opportunity. These differences
reveal themselves not only in views of gender equality in the economics profession but in society
in general.
Large disparities in average responses between male and female economists emerge in
response to the statement, “Job opportunities for men and women in the U.S. are currently approximately equal.” The estimation results show the mean response of female economists is one point (a full standard deviation) lower than that of male economists after controlling for
degree vintage and employment type. The average response of males is closer to “agree” with the statement while the average response of females is closer to “neutral.” The linear probability model, however, indicates that 58 percent of female economists with the average characteristics
of the sample either “disagree” or “strongly disagree” that job opportunities are equal. Women are 42 percentage points more likely to display this opinion than men.
22
As our previous results indicate, male economists appear more likely to prefer market
solutions to economic problems than do women. We are interested to learn if male economists
are also more likely to see differences in outcomes, such as variations in wages between men and
women in the U.S., as an outcome of choice or the free market versus other institutional factors.
When we ask if respondents agree with the statement that the gender wage gap is largely
explained by differences in human capital and voluntary occupational choices, the results of our
survey indicate a significant difference between male and female economists on this issue. When
comparing economists with the same employment status, who received their Ph.D. in the United
States in the same decade, we find that the mean response of males is more than a full standard
deviation higher than that of females. On average, women disagree that the gender wage gap is
due to choices and productivity difference; the average man is more likely to agree. The
probability of disagreeing or strongly disagreeing with the statement is 51 percentage points
higher for female economists than for male economists. Rent seeking, male preferences for
market solutions, and women’s views on gender equity may be reflected in the gender gap in
responses.
Because one of the most visible and controversial solutions to the problem of
discrimination and equal opportunity has been affirmative action, we ask two questions about
affirmative action. Question 26 asks whether affirmative action programs for women are a good
idea and Question 27 asks whether affirmative action programs for African-Americans are a
good idea. Women’s average responses to both questions are statistically significantly more favorable to the use of Affirmative Action than men’s;; however, the magnitudes of the gender differences in opinions are only about one third of a standard deviation.
23
Finally, we examine views on equal opportunity in the economics profession and
examine perceptions of equal opportunity for women as graduate students and as faculty. The
question about graduate education asks respondents if they believe that opportunities for women
graduate students in economics in the U.S. currently favor men or women. After controlling for
degree vintage and type of employment, we find that the mean response of female economists is
closer to the “favors men a bit more” choice and the mean response of male economists is closer to the “is approximately equal for men and women” choice. According to the point estimates, 52
percent of women and 15 percent of men believe graduate education favors men either a bit more
or a lot more.
On the issue of gender equality as it relates to women faculty in economics we ask
respondents if they believe that opportunities for economics faculty in the U.S. currently favor
men or women or neither sex. We find that the average female economist believes opportunities
favor men more than women and this view reflects a full standard deviation difference in opinion
from the average male economist. The average male response indicates a belief that current
opportunities for economics faculty in the U.S. are equal, favoring neither men nor women.
Women are 55 percentage points more likely to believe that opportunities for economics faculty
favor men a bit or a lot more than women.
On four of the five questions concerning gender equality, male and female members of
the AEA have reached the opposite conclusion, with statistically significant and large differences
of opinion. More than 50 percent of female economists believe that opportunities in the
economics profession or in the job market in general favor men whereas more than 75 percent of
male economists believe they are either equal or favor women.
24
IV. CONCLUSION
Our survey of AEA economists provides a snapshot picture of the views of economists on
some of the core precepts and approaches to the study of economics and a variety of important
and topical policy issues facing policy-makers today. To isolate the difference in views on
overall topics and specific policy issues, our statistical analysis controls for degree vintage and
type of employment. We estimate the mean gender gap in opinions using system GLS methods
that incorporate the estimated relationship among unobservable factors that form opinions on
related topics.
It is important to note that on the core precepts and methodological approaches to
economics we found no significant difference in average opinion between male and female
economists after controlling for the decade the Ph.D. was granted and type of employment.
Statistical tests based on GLS systems composed of individual responses support the conclusion
that male and female economists share the view that individuals are utility-maximizers, human
wants are unlimited, and that mathematical modeling should be an important part of economic
modeling. Moreover, male and female economists also embrace the notion that research on
household decision-making should include analysis of intra-household decision-making. In other
words, male and female economists appear to start with the same assumptions about how people
are expected to behave and how to approach the study of economics.
Despite their similar academic training and shared views about core precepts and
methodology in economics, our study reveals differences in the views of male and female
economists in their support of market solutions versus government intervention, in their
interpretation of economic outcomes, and their views toward so-called “compassion issues.” 25
These results show a greater willingness among male AEA members to rely on markets and see
problems from interfering with market processes – views that emerge when questions are put in
general terms and more clearly when they are put in terms of specific policy issues.
Although male and female economists agree that market solutions are most efficient, on
the issue of government regulation in general, male AEA economists, on average, see
government regulation in both the EU and the U.S. as more excessive than do female
economists. Moreover, male economists express greater support than women economists for
reducing tariffs and express greater opposition to linking trade openness to partners’ labor policies and greater opposition to mandating that employers provide health insurance. Male
economists report greater support for the use of vouchers in education and greater agreement that
the competition provided by a Wal-Mart store benefits society and are far more likely to support
drilling in the Arctic National Wildlife Refuge. Not surprisingly, male economists are more
likely to see the costs associated with government intervention. For example, male economists
are more likely to see a loss of employment from raising the minimum wage.
Another area where we find some consensus is on the environment. Here the average
response of both male and female AEA economists indicates support for increases in energy
taxes and taxes on greenhouse emissions and recommend that ethanol subsidies be eliminated. It
is important to recognize that value differences associated with environmental issues do emerge
when we consider other areas of market solutions versus governmental solutions. Although the
mean responses of both male and female AEA economists suggest that policies in the U.S.
currently do too much to favor economic growth at the expense of environmental quality, the
average female AEA economist disagrees more with drilling for oil in the Arctic National
Wildlife Refuge than the average male.
26
Our estimation results indicate the largest gender gap in views among AEA economists
occur around the issue of gender equality in society and in the economics profession – not
surprising since this area goes to the heart of the efficiency of market solutions and may also be
influenced by self-interest of both men and women. After controlling for degree vintage and type
of employment, the system GLS results show that the average male AEA economist is neutral in
his belief that job opportunities for men and women in the U.S. are currently approximately
equal, whereas the average female economist disagrees with this view. Likewise, the average
male response suggests agreement that the gender wage gap is explained by differences in human
capital and voluntary occupational choices while the average female AEA economist disagrees
with this view. While both male and female economists disagree that affirmative action for
women or for African-Americans is a good idea, women, on average, disagree less strongly than
men.
A large difference in views between male and female economists emerges on gender
equality in the economics professions itself. The GLS system results show that women
economists are more likely to believe that opportunities for economics faculty in the U.S.
currently favor men more than women. Approximately 75 percent of female economists share
this view whereas only 21 percent of male economists hold this opinion.
The gender gaps in
views on economic policy that we have detected among economists who study markets in their
professional capacity, suggest that many of the differences found between men and women in the
wider population hold for economists as well. Our findings of significant and large gender gaps
in economists’ views on the role of government intervention, the desirability of government’s role to promote equality, and the lack of gender equality in labor market opportunities and
outcomes are important for a variety of reasons.
27
First, these results suggest that it is crucial to include both women and men economists at
the table when forming policy to ensure that a variety of professional perspectives are included
in the discussion. If demographic differences such as sex shape our views of policy related
questions, it may be important that women be included on boards and in policy making circles at
all levels of decision-making. While including women in policy-making circles does not prevent
the selection of only those individuals with shared beliefs, it nonetheless may increase the
possibility that diverse viewpoints will be represented.
Second, the gender gap in economists’ views may provide a possible explanation why women are underrepresented in economics as faculty in the leading research institutions. If
women hold views that shape their perspectives on research issues and inform their thinking on
policy conclusions that are at odds with the perspectives of their male counterparts in areas that
are at the heart of a discipline, this may affect hiring and promotion decisions in ways that
disadvantage women. In the nuanced process of hiring and promoting of colleagues at research
institutions, these differences may result in fewer women on dissertation committees, fewer
courses related to subjects on gender differences in economics, and fewer women engaging in
research that shapes both theory and policy in the discipline.
Finally, differences in views on economic policy between similarly trained men and
women may also influence classroom materials and discussion and ultimately the worldview of
students in these classes. If these differences in views on policy contribute to the crowding out of
women from research institutions and crowding in of women into undergraduate institutions, one
would expect that they would have increased influence on undergraduate students – especially
those unwilling or uninterested in pursuing graduate training. Diversity of faculty in higher
education in general has resulted in a change in what constitutes knowledge in the various
28
disciplines and will no doubt continue to influence students as future citizens by at least
providing a more complete menu of perspectives about important aspects of economic policy.
29
Footnotes
1
“Earned Degrees Conferred: 1870-2000,” Postsecondary Education Opportunity, Number 116, February 2002 available at
http://www.eric.ed.gov/ERICWebPortal/custom/portlets/recordDetails/detailmini.jsp?_nfpb=true
&_&ERICExtSearch_SearchValue_0=ED473779&ERICExtSearch_SearchType_0=no&accno=
ED473779 and accessed December 6, 2009.
2
Some studies on gender differences in economic policy on single issues offer similarly
interesting results. See, for example, Brian A. Burgoon and Michael J. Niscox, “The Gender Divide over International Trade: Why Do Men and Women Have Different Views about
Openness to the World Economy,” working paper available at http://www.people.fas.harvard.edu/~hiscox/Gender.pdf, accessed June 27, 2012.
3
The 2007 AEA membership directory has 1116 pages of members. To create a sample of
approximately 200 male and 200 female members we randomly picked a starting page between 1
and 5 and then selected the first male and the first female to meet the selection criteria. (Many
members do not list information regarding their degrees and had to be skipped.) The search
procedure was repeated by fifth/sixth page thereafter. This yielded 202 males and 202
females (in one instance there was a stretch of six pages over which no female met the
criteria). Sex was usually obvious from the individual's first name, but an internet search of
individuals was conducted in cases of ambiguity.
4
Response rates among AEA member in recent surveys include 34.4% in Alston, Kearl and
Vaughan (1992), 30.8% in Fuller and Geide-Stevenson (2003), 36.3% in Whaples and
Heckelman (2005), and 26.6% in Klein and Stern (2005) and 40.0% in Whaples (2006).
30
5
The joint null hypotheses that the coefficients on PhD1970s, PhD1980s, PhD1990s, PhD2000s,
Graduate, Government, Forprofit, and Undergrad equal zero cannot be rejected for each of the
five equations in the system.
6
The results of the full GLS estimation of equation (1) for each of the five groups is available
from the authors upon request.
7
We estimated the probability of disagreement using a linear probability model rather than a
logit or probit model in order to incorporate the error correlation across responses using
individual-clustered standard errors. Because the explanatory variables are binary indicators, the
linear probability model estimated probabilities are bounded between zero and one.
8
Also included in the original survey was a question about the newly enacted bailout of
financial institutions. At the time that this question was asked, the bailout was very new and
opinion quite fluid. Not surprisingly perhaps, most economists in our sample – male and female
– indicated their support for the law and no gender differences were apparent at that time.
Likewise, our question about the best way to deal with Social Security’s long term funding gap elicited a rather high number of “none of the above” answers. As a result, we have concluded that this question reveals little about the issue and have chosen to leave the discussion of it out of
our narrative. Along these same lines, our questions about the impact of undocumented workers
on American-born workers in various income groups and on returning to the gold standard
produced no differences in opinion between male and female economists.
9
The difference in opinion on military spending attributable to degree vintage is much larger.
Given gender and type of employment, the mean response of economists receiving their Ph.D.s
in the 1980s, 1990s, or 2000s is a full point lower than those who graduated prior to 1980,
31
indicating that more recently minted Ph.D. economists are more likely to believe the size of
military spending is too large.
32
REFERENCES
Albelda, Randy. 1997. Economics and Feminism: Disturbances in the Field. New York:
Twayne Publishers.
Alston, Richard M., J.R. Kearl, and Michael B. Vaughan. 1992. “Is There a Consensus
Among Economists in the 1990s?” The American Economic Review, 82(2): 203-9.
Alston, Richard M. and Michael B. Vaughan. 1993. “Institutionalists: A United Front or
Divergent Voices of Dissent?” Journal of Economic Issues, 27(2): 351-61.
Burgoon, Brian A. and Michael J. Niscox. “The Gender Divide over International Trade:
Why Do Men and Women Have Different Views about Openness to the World
Economy,” working paper available at http://www.people.fas.harvard.edu/~hiscox/Gender.pdf accessed December 6, 2009.
Coats, A.W. Bob. 1993. The Sociology and Professionalization of Economics: British &
American Economic Essays, Volume II. London and New York: Routledge.
Davis, William L. 1997. “Economists’ Perceptions of Their Own Research: A Survey of
the Profession,” The American Journal of Economics and Sociology, 56(2): 159-72.
Davis, William L., Bob Figgins, David Hedengren, and Daniel B. Klein. 2011. “Economics
Professors’ Favorite Economic Thinkers, Journals, and Blogs (along with Party and Policy
Views).” Econ Journal Watch 8 (2): 126-46.
Fourcade, Marion. 2009. Economists and Societies: Discipline and Profession in the
United States, Britain, & France, 1890s to 1990s. Princeton, New Jersey: Princeton
University Press.
Frey, Bruno S., Werner W. Pommerehne, Friedrich Schneider, and Guy Gilbert. 1984.
“Consensus and Dissension among Economists: An Empirical Inquiry,” The American
33
Economic Review 74(5): 986-94.
Fuchs, Victor R. 1996. “Economics, Values, and Health Care Reform,” The American
Economic Review 86(1): 1-24.
Fuchs, Victor R., Alan B. Krueger, and James Poterba.1998. “Economists’ Views about
Parameters, Values and Policies: Survey Results in Labor and Public Economics,” Journal of Economic Literature 36 (3):1387-1425.
Fuller, Dan and Doris Geide-Stevenson. 2003. “Consensus among Economists:
Revisited,” The Journal of Economic Education 34(4): 369-87.
Heckman, James. 1979. “Sample Selection Bias as a Specification Error.” Econometrica
47(1): 153-61.
Hedengren, David, Daniel B. Klein, and Carrie Milton. 2010. “Economist Petitions: Ideology
Revealed.” Econ Journal Watch 7 (3): 288-319.
Ingelhart, Ronald and Pippa Norris. 2000. "The Development Theory of the Gender Gap:
Women's and Men's Voting Behavior in Global Perspective," International Political Science
Review/ Revue internationale de science politique 21 (4): 441-63.
Kearl, J.R., Clayne L. Pope, Gordon C. Whiting, and Larry T. Wimmer. 1979. “A
Confusion of Economists?” The American Economic Review 69(2): 28-37.
Klein, Daniel B. and Charlotta Stern. 2005. “Professors and Their Politics: The Policy
Views of Social Scientists,” Critical Review 17(3-4): 257-303.
Klein, Daniel B. and Charlotta Stern. 2007. “Is There a Free-Market Economist in the
House?” The American Journal of Economics and Sociology 66(2): 209-34.
34
National Science Foundation, “Doctorate Recipients from US Universities: 2010 Arlington, VA (NSF 12-305) December 2011 http://www.nsf.gov/statistics/sed/pdf/tab14.pdf accessed
June 5, 2012.
Pew Research Center. 2009. “Trends in Political Values and Core Attitudes: 1987-2009:
Independents Take Center Stage in the Obama Era.”
Saad, Lydia. 2003. “Women Skeptical of Society Fairness to Their Gender.” Gallup
http://gallup.com/poll/9433/Women-Skeptical-Societal-Fairness-Their-Gender.aspx.
Shapiro, Robert Y. and Harpreet Mahajan. 1986. “Gender Differences in Policy Preferences: A
Summary of Trends From the 1960s to the 1980s.” Public Opinion Quarterly 50 (1): 42-61.
Smith, Tom W. "The Polls: Gender Attitudes toward Violence," Public Opinion Quarterly 48
(1B): 384-96.
Stastny, Daniel. 2010. “Czech Economists on Economic Policy: A Survey.” Econ Journal Watch
7(3): 275-87.
Whaples, Robert. 2006. “Do Economists Agree on Anything? Yes!” Economists Voice
3(9):1-6.
Whaples, Robert and Jac C. Heckelman. 2005. “Public Choice Economics: Where Is There Consensus?” American Economist 49 (1): 66-78.
35
Table 1: Characteristics of AEA Survey Sample
AEA Survey Sample
Total
Female
Responders to Survey
Male
Total
Variable
Female
Female
Non-Responders
Male
Total
Female
N
Mean
N
Mean
N
Mean
N
Mean
N
Mean
N Mean
N
Mean
N
Mean
N
404 0.50
143 0.45
261 0.52
0.50
0.50
0.50
403 0.41
201 0.42
202 0.41
142 0.35
64 0.38
78 0.34† 261 0.44
137 0.44
124
Graduate
0.49
0.00
0.00
0.48
0.49
0.48
0.50
0.50
202 0.29
202 0.24
143 0.30
65 0.34
78 0.27
261 0.24
137 0.26
124
Undergraduate 404 0.26
0.44
0.00
0.00
0.46
0.48
0.45
0.43
0.44
403 0.14
201 0.13
202 0.15
143 0.13
65 0.12
78 0.13
260 0.15
136 0.13
124
For Profit
0.35
0.00
0.00
0.33
0.33
0.34
0.35
0.34
403 0.11
201 0.09
202 0.14
143 0.13
65 0.07***
78 0.17
260 0.11
136 0.10
124
Government
0.32
0.00
0.00
0.33
0.27
0.38
0.31
0.30
201 0.54***
202 0.64
143 0.55
65 0.47***
78 0.60
260 0.62
136 0.58
124
Listed Research 403 0.60
0.49
0.00
0.00
0.50
0.50
0.49
0.49
0.50
395 0.09
198 0.06**
197 0.12
141 0.08
65 0.06
76 0.09
254 0.09
133 0.05**
121
PhD pre1970
0.28
0.23
0.32
0.27
0.24
0.29
0.29
0.22
395 0.21
198 0.16**
197 0.25
141 0.16
65 0.12
76 0.20
254 0.23
133 0.18**
121
PhD1970s
0.41
0.37
0.44
0.37
0.33
0.40
0.42
0.39
395 0.29
198 0.27
197 0.31
141 0.28
65 0.26
76 0.29
254 0.30
133 0.28
121
PhD1980s
0.45
0.45
0.46
0.45
0.44
0.46
0.46
0.45
395 0.23
198 0.29***
197 0.17
141 0.26
65 0.32
76 0.21
254 0.22
133 0.28**
121
PhD1990s
0.42
0.46
0.38
0.44
0.47
0.41
0.41
0.45
395 0.18
198 0.22*
197 0.15
141 0.22
65 0.23
76 0.21† 254 0.16
133 0.21**
121
PhD2000s
0.39
0.41
0.36
0.42
0.42
0.41
0.37
0.41
395 21.63 198 19.02***
197 24.25 141 19.98
65 18.15***
76 21.56 254 22.54 133 19.45***
121
YearsPh.D.
12.65
12.06
12.73
12.71
11.79
13.33
12.55
12.20
Standard deviations are beneath sample means. The symbols *, **, *** denote rejection at the 10%, 5%, 1% significance levels of female-male
equal means tests within AEA members population (using AEA survey sample), within AEA responders' population (using responders' sample), and within the
non-responders' population (using non-responders sample).
both overall and for each sex (using responders' and nonresponders' samples).
Male
Mean
0.45
0.50
0.22
0.41
0.16
0.37
0.12
0.33
0.67
0.47
0.13
0.34
0.29
0.46
0.32
0.47
0.15
0.36
0.11
0.31
25.94
12.09
Table 2 : Probit Estimation of Probability of
Response to AEA survey, N = 391
X variables
Female
Graduate
Undergrad
Government
For Profit
Listed Research
For Profit x Listed Research
PhD1970s
PhD1980s
PhD1990s
PhD2000s
Constant
Coefficients
-0.245*
(.136)
-.684**
(.292)
-0.471
(.308)
-0.528
(.340)
-1.101***
(.399)
-0.263*
(0.149)
0.828**
(.388)
0.075
(.293)
0.253
(.289)
0.444
(.300)
0.566*
(.314)
0.166
(.0305)
Standard errors are in parentheses beneath coefficient point estimates.
*, **, *** denote 10%, 5%, 1% significance levels from testing the
null hypothesis that the coefficient equals zero.
Variables
Female
PhD1970s
PhD1980s
PhD1990s
PhD2000s
Graduate
Government
For Profit
Undergrad
Table 3 : Regression Tests of No Selection Bias using 2-Step Heckman Procedure (Heckit)
Dependent Variable: Standardized Scaled Answer to Group Question
Group 1:Core
Group2: Market
Group 3: Gov.
Group 4: The
Group5: Gender and
Solutions & Gov. Spending, Taxing and
Equal Opportunity
Precepts/Economic
Environment
OLS
Heckit
OLS
Heckit
OLS
Heckit
OLS
Heckit
OLS
Heckit
-0.196
(0.197)
-0.851*
(0.473)
-0.882*
(0.463)
-0.903*
(0.459)
-0.596
(0.488)
0.889**
(0.361)
0.608
(0.422)
0.972**
(0.418)
0.829**
(0.381)
Inverse Mills
Ratio
0.122
Constant
R-squared
N
(0.367)
0.099
113
-0.219
(0.232)
-0.842*
(0.480)
-0.859*
(0.467)
-0.919*
(0.504)
-0.559
(0.568)
0.875*
(0.472)
0.591
(0.462)
0.965**
(0.466)
0.770*
(0.417)
0.015
(0.908)
0.117
(0.846)
0.106
112
-0.506***
(0.180)
-0.415
(0.409)
-0.919**
(0.400)
-0.716*
(0.397)
-0.423
(0.426)
0.118
(0.318)
-0.224
(0.368)
-0.025
(0.370)
0.108
(0.342)
0.764**
(0.320)
0.155
123
-0.613***
(0.216)
-0.467
(0.413)
-0.847**
(0.410)
-0.494
(0.452)
-0.163
(0.510)
-0.107
(0.394)
-0.345
(0.391)
-0.213
(0.416)
-0.010
(0.373)
0.740
(0.744)
0.109
(0.730)
0.160
122
-1.056***
(0.174)
-0.415
(0.409)
-0.919*
(0.400)
-0.716
(0.397)
-0.423
(0.426)
0.118
(0.318)
-0.224
(0.368)
-0.025
(0.370)
0.108
(0.342)
0.764**
(0.320)
0.306
114
-0.979***
(0.213)
-0.461
(0.451)
-0.822*
(0.443)
-0.587
(0.481)
-0.688
(0.531)
0.123
(0.373)
-0.162
(0.376)
0.068
(0.406)
0.384
(0.370)
-0.389
(0.748)
1.296**
(0.771)
0.306
113
0.300
(0.198)
0.812
(0.494)
0.913*
(0.476)
0.814*
(0.478)
0.620
(0.501)
-0.357
(0.378)
-0.015
(0.416)
-0.254
(0.442)
-0.311
(0.400)
-0.628*
(0.374)
0.067
117
0.400*
(0.239)
0.935*
(0.514)
0.901*
(0.478)
0.659
(0.509)
0.433
(0.554)
-0.173
(0.437)
0.073
(0.432)
-0.095
(0.480)
-0.227
(0.420)
-0.727
(0.845)
-0.008
(0.809)
0.072
116
Standard errors are in parentheses beneath coefficient point estimes. *, **, *** denote 10%, 5%, 1% significance levels from
testing the null hypothesis that the population coefficient equals zero.
0.938***
(0.173)
0.095
(0.433)
0.043
(0.420)
0.032
(0.409)
-0.089
(0.438)
-0.067
(0.326)
0.126
(0.367)
0.101
(0.412)
-0.130
(0.345)
-0.403
(0.321)
0.218
120
0.806***
(0.214)
-0.010
(0.447)
0.103
(0.425)
0.224
(0.450)
0.191
(0.513)
-0.305
(0.398)
0.011
(0.384)
-0.046
(0.436)
-0.258
(0.367)
0.849
(0.805)
-1.147
(0.775)
0.214
119
Table 4: GLS System Estimation of Responses to Survey Questions
Standardized (Mean = 0, Standard Deviation = 1) Scaled Answers to Group Questions
N = 83
Question Group
Female
Group 1:Core Precepts/
-0.27
Economic Methology (6
ques; Cronbach alpha=.71)
(0.23)
Group2: Market Solutions
-0.65***
& Gov. Interventions (8
ques; Cronbach alpha=.78)
(0.23)
Group 3: Government
-0.91***
Spending, Taxing, &
Redistribution (9 ques;
(0.22)
Cronbach alpha=.92)
Group 4: The Environment
0.43*
(4 ques; Cronbach
alpha=.73)
Group 5: Gender and
Equal Opportunity
(6
ques; Cronbach alpha=.93)
PhD1970s
PhD1980s
PhD1990s
PhD2000s Graduate
Govt
For Profit
Undergrad
-1.20**
-0.86*
-0.84
-0.60
0.86
0.26
0.84
0.35
0.35
(0.54)
(0.51)
(0.51)
(0.55)
(0.41)
(0.47)
(0.47)
(0.44)
(0.43)
-0.77
-1.010**
-0.872*
-0.67
0.35
-0.23
0.18
0.07
0.91**
(0.52)
(0.49)
(0.49)
(0.53)
(0.39)
(0.46)
(0.46)
(0.43)
(0.41)
-0.78
-0.831*
-0.63
-0.73
0.26
-0.19
0.10
0.29
0.88**
(0.51)
(0.48)
(0.48)
(0.52)
(0.38)
(0.45)
(0.45)
(0.42)
(0.40)
1.025*
0.79
0.874*
0.80
-0.46
0.07
-0.36
-0.49
-0.63
(0.24)
(0.55)
(0.52)
(0.52)
(0.57)
(0.42)
(0.49)
(0.49)
(0.45)
(0.44)
1.08***
0.60
0.39
0.28
0.66
0.02
0.54
0.47
0.22
-1.02***
(0.21)
(0.48)
(0.45)
(0.45)
(0.49)
(0.36)
(0.42)
(0.42)
(0.39)
(0.38)
Standard errors are in parentheses beneath coefficient point estimates. *, **, *** denote 10%, 5%, 1% significance levels from the null hypothesis that the
population coefficient equals zero.
Constant
Table 5. Gender Differences in Opinions on Market Solutions & Government Interventions
Linear Probability Model: P(opinion| female, X) = female + X
Mean Response Model: E(R| female, X) =
X = decade of Ph.D. (1970s, 1980s,1990s,2000s), type of employment
Group 2 Proposition: Mkt Solutions & Gov Interventions
N = 122
The European Union has an excessive amount of government
regulation of economic activity
Gender
female 3.11***
male
The United States has an excessive amount of government
regulation of economic activity
female
male
The US should drill for oil in the Arctic National Wildlife Refuge
female
male
Parents should be given educational vouchers which can be used
at government-run or privately-run schools
E(R | X)
female
male
A Wal-Mart store typically generates more benefits to society than female
costs
male
(0.15)
3.65***
(0.12)
2.38***
(0.14)
2.93***
(0.14)
2.21***
(0.18)
2.75***
(0.20)
2.99***
(0.18)
3.75***
(0.16)
3.30***
(0.14)
4.07***
(0.13)
R*
-0.54***
(0.19)
-0.55***
(0.21)
-0.54**
(0.27)
-0.77***
(0.24)
-0.77***
(0.20)
1 or 2
1 or 2
1 or 2
1 or 2
1 or 2
*Unless otherwise noted, 1 = strongly disagree; 2 = disagree; 3 = neutral; 4 = agree; 5 = strongly agree.
Mean parameters were estimated by SUR methods with different covariance matrices for males and females.
Linear probability model parameters were estimated by OLS with clustered standard errors.
*, **, *** denote 10%, 5%, 1% significance levels from testing the null hypothesis that the coefficient equals zero.
P(R | X)
0.33***
(0.06)
0.14***
(0.04)
0.62***
(0.06)
0.41***
(0.06)
0.64***
(0.06)
0.52***
(0.06)
0.40***
(0.06)
0.13***
(0.05)
0.22***
(0.05)
0.08**
(0.03)
0.19**
(0.08)
0.21**
(0.09)
0.12
(0.09)
0.27**
*
0.14**
(0.06)
Table 6. Gov. Spending, Taxing, & Redistribution
Linear Probability Model: P(opinion| female, X) = α₁ female + X α₂
Mean Response Model: E(R| female, X) = β₁ + Xβ₂
X = decade of Ph.D. (1970s, 1980s,1990s,2000s), type of employment
Group 3 Proposition: Gov Spending, Taxing, &
β₁
R*
Gender E(R | X)
Redistribution N = 115
3.86***
The distribution of income in the U.S. should be made more equal
female (0.16)
male
Increases in the minimum wage will increase unemployment
among unskilled workers
female
male
The U.S. should link import openness to the labor standards of its
female
export partners
male
Employers in the U.S. should be required to provide health
insurance to their full-time employees
female
male
The U.S. should implement a tax on consumption and rely less on
female
income taxes for revenue
male
The size of government in the U.S. is: 1=much too large, 2=too
large, 3=about right, 4=too small, 5=much too small
female
male
The U.S. tax structure should be: 1=made less progressive, 2=kept
female
at its current level of progressivity, 3=made more progressive
male
3.14***
(0.16)
2.91***
(0.17)
3.85***
(0.12)
3.34***
(0.17)
2.41***
(0.14)
3.31***
(0.17)
2.39***
(0.14)
2.51***
(0.16)
3.31***
(0.16)
2.80***
(0.11)
2.34***
(0.12)
2.81***
(0.08)
2.11***
(0.11)
0.72***
(0.23)
-0.94***
(0.21)
0.94***
(0.23)
0.92***
(0.23)
-0.80***
(0.23)
0.46***
(0.17)
4 or 5
1 or 2
4 or 5
4 or 5
1 or 2
3,4 or
5
0.70***
(0.14)
3
*Unless otherwise noted, 1 = strongly disagree; 2 = disagree; 3 = neutral; 4 = agree; 5 = strongly agree.
Mean parameters were estimated by SUR methods with different covariance matrices for males and females.
Linear probability model parameters were estimated by OLS with clustered standard errors.
*, **, *** denote 10%, 5%, 1% significance levels from testing the null hypothesis that the coefficient equals zero.
P(R | X)
α₁
0.73***
(0.06)
0.41***
(0.06)
0.38***
(0.07)
0.12***
(0.04)
0.52***
(0.07)
0.22***
(0.05)
0.47***
(0.07)
0.16***
(0.04)
.54***
(0.07)
0.31***
(0.06)
0.74***
(0.06)
0.50***
(0.06)
0.83***
(0.05)
0.41***
(0.06)
0.32***
(0.09)
0.26***
(0.08)
0.30***
(0.09)
0.31***
(0.08)
0.23**
(0.09)
0.24***
(0.09)
0.41***
(0.08)
Table 7. Gender Differences in Opinions on Gender & Equal Opportunity
Linear Probability Model: P(opinion| female, X) = female + X
Mean Response Model: E(R| female, X) =
X = decade of Ph.D. (1970s, 1980s,1990s,2000s), type of employment
Group 5 Proposition: Gender & Equal Opportunity
N=
P(R | X)
R*
Gender E(R | X)
122
2.55***
-1.07***
0.58***
Job opportunities for men and women in the U.S. are currently
(0.17)
(0.23)
(0.07)
female
approximately equal
1 or 2
male
The gender wage gap is largely explained by difference in human
capital and voluntary occupational choices
female
male
Opportunities for economics faculty in the U.S. currently: 1. favor
men a lot more than women; 2. favor men a bit more than
women; 3. are approximately equal for men and women; 4. favor
women a bit more than men; 5. favor women a lot more than men
Graduate education in economics in the U.S. currently: 1. favors
men a lot more than women; 2. favors men a bit more than
women; 3. is approximately equal for men and women; 4. favors
women a bit more than men; 5. favors women a lot more than
3.62***
(0.14)
2.22***
(0.14)
3.46***
(0.15)
2.04***
female (0.12)
male
-1.24***
(0.21)
-1.09***
(0.18)
0.16***
(0.05)
0.74***
(0.06)
1 or 2
0.23***
(0.05)
0.76***
1 or 2 (0.06)
3.13***
(0.13)
2.29***
female (0.12)
0.51***
(0.08)
0.55***
(0.08)
0.21***
(0.05)
-0.58***
(0.14)
0.52***
(0.06)
1 or 2
0.15***
(0.04)
2.88***
(0.08)
*Unless otherwise noted, 1 = strongly disagree; 2 = disagree; 3 = neutral; 4 = agree; 5 = strongly agree. Mean
response parameters were estimated by SUR methods with different covariance matrices for males and females.
Linear probability model parameters were estimated by OLS with clustered standard errors.
*, **, *** denote 10%, 5%, 1% significance levels from testing the null hypothesis that the coefficient equals zero.
male
0.42***
(0.08)
0.55***
(0.08)
Appendix
The appendix summarizes the survey results by percentage frequency distributions and describes
the scaled measures of economist’s views on (1) Core Precepts and Economic Methodology, (2) Market Solutions and Government Interventions, (3) Government Spending, Taxing, and
Redistribution, (4) the Environment, and (5) Gender and Equal Opportunity.
43
Group 1. Core Precepts and Economic Methodology
Distribution of Responses by Gender*
Proposition
Response
4
5
fema l e
3.2 15.9 17.5 55.6
7.9
ma l e
2.7 20.3 12.2 48.6 16.2
fema l e
1.6 21.9
6.3 48.4 21.9
ma l e
2.6 17.1
7.9 44.7 27.6
Res ea rch on hous ehol d deci s i on-ma ki ng s houl d i ncl ude a na l ys i s of
i ntra hous ehol d deci s i on-ma ki ng
fema l e
0.0
1.6 17.7 48.4 32.3
ma l e
0.0
1.6 29.7 46.9 21.9
Ma thema ti ca l model i ng s houl d be a n i mporta nt pa rt of economi c
model i ng
fema l e
0.0
7.8 21.9 50.0 20.3
ma l e
0.0
6.7 21.3 50.7 21.3
fema l e
1.7 11.7 20.0 50.0 16.7
Indi vi dua l s a re ra ti ona l uti l i ty ma xi mi zers
Huma n wa nts a re unl i mi ted
GDP i s a n i ns uffi ci ent mea s ure of overa l l economi c performa nce
1
2
3
ma l e
2.6 19.7 19.7 42.1 15.8
The economi cs profes s i on i n the US currentl y: 1. rel i es too much on
deducti ve model i ng a nd not enough on empi ri ca l a na l ys i s ; 2. ha s
fema l e
45.9 45.9 8.2 a bout the ri ght mi x of empi ri ca l a na l ys i s a nd deducti ve model i ng; 3.
ma
l
e
41.3
48.0
10.7
rel i es too much on empi ri ca l a na l ys i s a nd not enough on deducti ve
model i ng
*Unl es s otherwi s e noted, 1 = s trongl y di s a gree; 2 = di s a gree; 3 = neutra l ; 4 = a gree; 5 = s trongl y a gree
44
Group 2. Market Solutions and Government Interventions
Distribution of Responses by Gender*
Proposition
Response
1
2
3
4
5
Ma rket s ol uti ons a re the mos t effi ci ent wa y to a l l oca te res ources
under mos t ci rcums ta nces
fema l e
1.6
7.8 10.9 56.3 23.4
ma l e
0.0
2.6
The Europea n Uni on ha s a n exces s i ve a mount of government
regul a ti on of economi c a cti vi ty
fema l e
6.7 26.7 20.0 41.7
ma l e
1.4 13.7 26.0 39.7 19.2
The Uni ted Sta tes ha s a n exces s i ve a mount of government regul a ti on fema l e
of economi c a cti vi ty
ma l e
The US s houl d reduce ta ri ffs a nd other ba rri ers to tra de
fema l e
ma l e
The US s houl d dri l l for oi l i n the Arcti c Na ti ona l Wi l dl i fe Refuge
The US s houl d i mpos e ta xes on unhea l thy foods .
Pa rents s houl d be gi ven educa ti ona l vouchers whi ch ca n be us ed a t
government-run or pri va tel y-run s chool s
A Wa l -Ma rt s tore typi ca l l y genera tes more benefi ts to s oci ety tha n
cos ts
9.0 46.2 42.3
17.5 47.6 20.6 12.7
5.0
1.6
7.7 33.3 26.9 21.8 10.3
0.0
8.1
9.7 61.3 21.0
0.0
1.3
7.8 44.2 46.8
fema l e
39.7 27.0 14.3 14.3
ma l e
27.6 25.0 11.8 17.1 18.4
fema l e
27.4 32.3 19.4 17.7
3.2
ma l e
32.0 30.7 13.3 17.3
6.7
fema l e
16.1 24.2 22.6 22.6 14.5
ma l e
6.5
fema l e
5.0 16.7 28.3 41.7
4.8
7.8 24.7 28.6 32.5
8.3
ma l e
1.4 8.1 12.2 41.9 36.5
*Unl es s otherwi s e noted, 1 = s trongl y di s a gree; 2 = di s a gree; 3 = neutra l ; 4 = a gree; 5 = s trongl y a gree
45
Group 3. Government Spending, Taxing, and Redistribution
Distribution of Responses by Gender*
Proposition
Response
The di s tri buti on of i ncome i n the U.S. s houl d be ma de more equa l
1
2
3
4
5
fema l e
6.2 15.4 15.4 36.9 26.2
ma l e
9.2 19.7 26.3 30.3 14.5
Increa s es i n the mi ni mum wa ge wi l l i ncrea s e unempl oyment a mong
uns ki l l ed workers
fema l e
7.9 25.4 22.2 38.1
ma l e
1.3 13.2 15.8 47.4 22.4
The U.S. s houl d l i nk i mport opennes s to the l a bor s ta nda rds of i ts
export pa rtners
fema l e
6.7 26.7 18.3 38.3 10.0
ma l e
Empl oyers i n the U.S. s houl d be requi red to provi de hea l th i ns ura nce fema l e
to thei r ful l -ti me empl oyees
ma l e
21.9 38.4 16.4 20.5
6.3
2.7
6.5 30.6 22.6 25.8 14.5
24.7 26.0 28.6 14.3
6.5
0.0
The U.S. s houl d i mpl ement a ta x on cons umpti on a nd rel y l es s on
i ncome ta xes for revenue
fema l e
15.0 33.3 21.7 30.0
ma l e
10.4 27.3 20.8 23.4 18.2
The s i ze of government i n the U.S. i s : 1=much too l a rge, 2=too l a rge,
3=a bout ri ght, 4=too s ma l l , 5=much too s ma l l
fema l e
Current l evel s of U.S. mi l i ta ry s pendi ng a re: 1=much too l a rge, 2=too
l a rge, 3=a bout ri ght, 4=too s ma l l , 5=much too s ma l l
The U.S. ta x s tructure s houl d be: 1=ma de l es s progres s i ve, 2=kept a t
i ts current l evel of progres s i vi ty, 3=ma de more progres s i ve
fema l e
The effect of modera te a mounts of i nfl a ti on (< 5 %) on the economy
a re: 1=very ha rmful , 2=s omewha t ha rmful , 3=mi ni ma l , 4=s omewha t
hel pful , 5=very hel pful
8.8
0.0
ma l e
24.7 23.4 40.3 11.7
0.0
fema l e
33.9 47.5 13.6
5.1
0.0
ma l e
14.5 50.0 26.3
7.9
1.3
4.8 17.7 77.4
-
-
28.6 28.6 42.9
-
-
ma l e
7.0 28.1 56.1
fema l e
0.0 26.7 53.3 20.0
0.0
ma l e
6.5 35.1 45.5 13.0
0.0
*Unl es s otherwi s e noted, 1 = s trongl y di s a gree; 2 = di s a gree; 3 = neutra l ; 4 = a gree; 5 = s trongl y a gree
46
Group 4. The Environment
Distribution of Responses by Gender*
Proposition
Response
The U.S. s houl d i ncrea s e energy ta xes
The U.S s houl d i mpos e a ta x on emi s s i ons of greenhous e ga s es
Pol i ci es i n the U.S. currentl y: 1. do too much to fa vor envi ronment
qua l i ty a t the expens e of economi c growth; 2. s tri ke a pproxi ma tel y
the ri ght ba l a nce between envi ronmenta l qua l i ty a nd economi c
growth; 3. do too much to fa vor economi c growth a t the expens e of
Etha nol s ubs i di es i n the U.S. s houl d be: 1=el i mi na ted, 2=reduced,
3=kept a t the current l evel , 4=i ncrea s ed
1
2
3
fema l e
3.3
8.3
5
ma l e
9.1 10.4 11.7 31.2 37.7
fema l e
4.8
3.2
ma l e
9.3
1.3 13.3 40.0 36.0
fema l e
6.9 20.7 72.4
-
-
ma l e
12.2 31.1 56.8
-
-
fema l e
70.4 16.7
9.3
3.7
-
ma l e
76.3 18.4
2.6
2.6
-
6.7 48.3 33.3
4.8 50.0 37.1
*Unl es s otherwi s e noted, 1 = s trongl y di s a gree; 2 = di s a gree; 3 = neutra l ; 4 = a gree; 5 = s trongl y a gree
47
4
Group 5. Gender and Equal Opportunity
Distribution of Responses by Gender*
Proposition
Response
Job opportuni ti es for men a nd women i n the U.S. a re currentl y
a pproxi ma tel y equa l
fema l e
The gender wa ge ga p i s l a rgel y expl a i ned by di fference i n huma n
ca pi ta l a nd vol unta ry occupa ti ona l choi ces
fema l e
Affi rma ti ve a cti on progra ms for women a re a good i dea
Affi rma ti ve a cti ons progra ms for Afri ca n-Ameri ca ns a re a good i dea
Opportuni ti es for economi cs fa cul ty i n the U.S. currentl y: 1. fa vor men
a l ot more tha n women; 2. fa vor men a bi t more tha n women; 3. a re
a pproxi ma tel y equa l for men a nd women; 4. fa vor women a bi t more
tha n men; 5. fa vor women a l ot more tha n men
ma l e
ma l e
1
2
3
4
5
18.8 37.5 10.9 29.7
3.1
4.1 15.1 19.2 45.2 16.4
16.1 53.2 16.1 12.9
6.8 20.3 18.9 39.2 14.9
fema l e
12.7 36.5 23.8 20.6
6.3
ma l e
25.0 30.3 25.0 19.7
0.0
9.5 28.6 23.8 30.2
7.9
ma l e
20.8 29.9 18.2 28.6
2.6
fema l e
22.0 54.2 16.9
6.8
0.0
7.0 12.7 46.5 23.9
9.9
fema l e
ma l e
Gra dua te educa ti on i n economi cs i n the U.S. currentl y: 1. fa vors men
fema l e
a l ot more tha n women; 2. fa vors men a bi t more tha n women; 3. i s
a pproxi ma tel y equa l for men a nd women; 4. fa vors women a bi t more
ma l e
tha n men; 5. fa vors women a l ot more tha n men
18.3 35.0 43.3
5.6
9.7 77.8
*Unl es s otherwi s e noted, 1 = s trongl y di s a gree; 2 = di s a gree; 3 = neutra l ; 4 = a gree; 5 = s trongl y a gree
48
1.6
3.3
0.0
5.6
1.4
Group 1: Core Precepts and Economic Methodology
The Adhere to Core Precepts and Economic Methodology variable is constructed from the
responses to the following questions:
1.
Individuals are rational utility-maximizers.
2.
Human wants are unlimited.
7.
Research on household decision-making should include analysis of intra-household
decision-making.
8.
Mathematical modeling should be an important part of economic modeling.
23.
GDP is an insufficient measure of overall economic performance.
39.
The economics profession in the US currently
a. relies too much on deductive modeling and not enough on empirical analysis
b. has about the right mix of empirical analysis and deductive modeling
c. relies too much on empirical analysis and not enough on deductive modeling.
We let the response “Strongly Disagree” equal 1, “Disagree” equal 2, “Neutral” equal 3, “Agree” equal 4, or “Strongly Agree” equal 5 for questions 1, 2, 8, and we let the reverse assignment hold for the response to questions 7, 23. For question 39, we let the response “a” equal 2, “b” equal 3, and “c” equal 4. The value of the variable, Adhere to Core Precepts and Economic
Methodology, is the average of the values assigned to the question responses. The standardized
answer to Group 1 questions has zero mean and unit variance. A higher value reflects that the
economist more strongly agrees with traditional economic assumptions and methodology. The
standardized Cronbach’s alpha value is .71 indicating a reliable measure.
49
Group 2: Market Solutions and Government Intervention
The Favor Market Solutions over Government Intervention variable is constructed from the
responses to the following questions:
3.
Market solutions are the most efficient way to allocate resources under most
circumstances.
5.
The European Union has an excessive amount of government regulation of economic
activity.
6.
The United States has an excessive amount of government regulation of economic
activity.
10.
The US should reduce tariffs and other barriers to trade.
13.
The US should drill for oil in the Arctic National Wildlife Refuge.
16.
The US should impose taxes on unhealthy foods.
18.
Parents should be given educational vouchers which can be used at government-run or
privately-run schools.
21.
A Wal-Mart store typically generates more benefits to society than costs.
We let the response “Strongly Disagree” equal 1, “Disagree” equal 2, “Neutral” equal 3, “Agree” equal 4, or “Strongly Agree” equal 5 for questions 3, 5, 6, 10, 13, 18, 21, and we let the reverse assignment hold for the response to question 16. The variable, Favor Market Solutions over
Government Intervention, is the average of the values assigned to the question responses. The
standardized answer to Group 2 questions has zero mean and unit variance. A higher value
reflects that the economist more strongly agrees with the policy conclusions predicted by
traditional economic assumptions and methodology. The standardized Cronbach’s alpha value is .78 indicating a reliable measure.
50
Group 3: Government Spending, Taxing, and Redistribution
The Favor Limiting Government-backed Redistribution variable is constructed from the
responses to the following questions:
4.
The distribution of income in the U.S. should be made more equal.
9.
Increases in the minimum wage will increase unemployment among unskilled workers.
11.
The U.S. should link import openness to the labor standards of its export partners.
15.
Employers in the U.S. should be required to provide health insurance to their full-time
employees.
17.
The U.S. should implement a tax on consumption and rely less on income taxes for
revenue.
29.
The size of government in the U.S. is
a. much too large
b. too large
c. about right
d. too small
e. much too small
30.
Current levels of U.S. military spending are
a. much too large
b. too large
c. about right
d. too small
e. much too small
51
31.
The U.S. tax structure should be
a. made less progressive
b. kept at its current level of progressivity
c. made more progressive
36.
The effect of moderate amounts of inflation (< 5 percent per year) on the economy are:
a. very harmful
b. somewhat harmful
c. minimal
d. somewhat helpful
e. very helpful
We let the response “Strongly Disagree” equal 1, “Disagree” equal 2, “Neutral” equal 3, “Agree” equal 4, or “Strongly Agree” equal 5 for questions 9, 17, and we let the reverse assignment hold for the response to questions 4, 11, 15. For questions 29, 36, we let the response “a” equal 5, “b” equal 4, and “c” equal 3, “d” equal 2, and “e” equal 1. For question 30, we let the response “a” equal 1, “b” equal 2, and “c” equal 3, “d” equal 4, and “e” equal 5. For question 31, we let the response “a” equal 4, “b” equal 3, and “c” equal 2. The variable, Favor Limiting Governmentbacked Redistribution, is the average of the values assigned to the question responses. The
standardized answer to Group 3 questions has zero mean and unit variance. A higher value
reflects that the economist more strongly agrees that government’s role should be limited to public good provision and promotion of free market outcomes rather than redistribution. The
standardized Cronbach’s alpha value is .71 indicating a reliable measure.
52
Group 4: The Environment
The Favor Increased Environmental Protection variable is constructed from the responses to the
following questions:
12.
The U.S. should increase energy taxes.
14.
The U.S should impose a tax on emissions of greenhouse gases.
35.
Policies in the U.S. currently
a. do too much to favor environment quality at the expense of economic growth
b. strike approximately the right balance between environmental quality and economic
growth.
c. do too much to favor economic growth at the expense of environmental quality
41.
Ethanol subsidies in the U.S. should be:
a. eliminated
b. reduced
c. kept at the current level
d. increased
We let the response “Strongly Disagree” equal 1, “Disagree” equal 2, “Neutral” equal 3, “Agree” equal 4, or “Strongly Agree” equal 5 for questions 1, 2, and we let the response “a” equal 1, “b” equal 2, and “c” equal 3, and “d” equal 4 for question 41. For question 35, we let the response “a” equal 4, “b” equal 3, and “c” equal 2. The variable, Favor Increased Environmental
Protection, is the average of the values assigned to the question responses. The standardized
answer to Group 4 questions has zero mean and unit variance. A higher value reflects that the
economist more strongly agrees that government policies should protect the environment. The
standardized Cronbach’s alpha value is .73 indicating a reliable measure.
53
Group 5: Gender and Equal Opportunities
The Labor Market Opportunities Unequal variable is constructed from the responses to the
following questions:
25.
Job opportunities for men and women in the U.S. are currently approximately equal.
24.
The gender wage gap is largely explained by difference in human capital and voluntary
occupational choices.
26.
Affirmative action programs for women are a good idea.
27.
Affirmative actions programs for African-Americans are a good idea.
37.
Opportunities for economics faculty in the U.S. currently
a. favor men a lot more than women
b. favor men a bit more than women
c. are approximately equal for men and women
d. favor women a bit more than men
e. favor women a lot more than men.
38.
Graduate education in economics in the U.S. currently
a. favors men a lot more than women
b. favors men a bit more than women
c. favors neither men nor women
d. favors women a bit more than men
e. favors women a lot more than men.
54
We let the response “Strongly Disagree” equal 1, “Disagree” equal 2, “Neutral” equal 3, “Agree” equal 4, or “Strongly Agree” equal 5 for questions 26, 27, and we let the reverse assignment hold for the response to questions 24, 25. For questions 37, 38, we let the response “a” equal 5, “b” equal 4, and “c” equal 3, “d” equal 2, and “e” equal 1. The variable, Labor Market
Opportunities Unequal, is the average of the values assigned to the question responses. The
standardized answer to Group 5 questions has zero mean and unit variance. A higher value
reflects that the economist more strongly agrees that men and women do not have equal job
opportunities, affirmative action programs are desirable, and graduate education and the
academic job market for economists tend to favor men over women. The standardized
Cronbach’s alpha value is .93 indicating a reliable measure. Tables A1 and A2 contain descriptive statistics and correlations of the scaled answers to
the five groups of questions.
55
Table A1: Descriptive Statistics of Group Questions' Scaled
Answers by AEA Member Sample
Value of 3.0 denotes "Neutral"
Variable
All
Females Males
Adhere to Core
N
115
53
62
Precepts and
Mean
3.01
2.97
3.05
Economic
Stdev
0.49
0.52
0.46
Methology
Min
1.33
1.33
2.00
Max
4.00
3.83
4.00
Favor Market
N
125
54
71
Solutions over
Mean
2.70
2.57
2.81
Government
Stdev
0.44
0.41
0.45
Interventions
Min
1.75
1.75
1.75
Max
3.63
3.50
3.63
Favor Limiting
N
115
46
69
Government-back Mean
2.98
2.57
3.25
Redistribution
Stdev
0.68
0.51
0.65
Min
1.67
1.67
2.00
Max
4.67
4.00
4.67
Favor Increased N
119
48
71
Environmental
Mean
3.21
3.31
3.14
Protection
Stdev
0.67
0.64
0.69
Min
1.25
1.25
1.25
Max
4.50
4.50
4.50
Labor Market
N
122
56
66
Opportunities
Mean
3.04
3.44
2.69
Unequal
Stdev
0.82
0.73
0.74
Min
1.17
2.00
1.17
Max
4.83
4.83
4.50
56
Groups
1
2
3
4
5
Groups
Table A2: Pairwise Correlations of Scale Group Answers
Correlation
1
0.36
1
0.41
0.68
1
-0.41
-0.52
-0.67
1
-0.29
-0.46
-0.63
0.43
1
2
3
4
57
1
5