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: amay1@unl.edu McGarvey: Associate Professor of Economics, University of Nebraska-Lincoln, Lincoln, NE. Email: mmcgarvey@unl.edu Whaples: Professor of Economics, Wake Forest University, Winston-Salem, NC. Email: whaples@wfu.edu

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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

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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-than-

scientific 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

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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 Geide-

Stevenson 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-old-

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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 “liberty-

enhancing” 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

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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

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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

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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

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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

9

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

10

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, non-

academic, non-government sector, not currently employed or retired.

We base our inference on the estimated coefficient on the binary indicator, female, in the

model,

, 1 2 3 4 5

6 7 8 9 0 ,

1970 1980 1990 2000

,i j j i j i j i j i j i

j i j i j i j i j i j

y female PhD s PhD s PhD s PhD sgraduate government profit undergrad

(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 1j using

only the responders’ observations will produce inconsistent and biased estimates of the gender

11

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,

( 1| ) ( )i i iP s x P Z x , 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 ( *is ) is positive, or if * 0i i is x u , 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 ( 1j ) can be obtained

using only the responders’ information if the error term in equation (1) is uncorrelated with iu ,

the error term in the response equation. We test the hypothesis that these errors have zero

correlation by adding the estimated inverse Mills ratio, ˆ ˆi z i z iIMR = pdf (x α) / CDF (x α) as a

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

12

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.

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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,

, 1 2 3 4 5

6 7 8 9 0 ,

1970 1980 1990 2000

,i j j i j i j i j i j i

j i j i j i j i j i j

y female PhD s PhD s PhD s PhD sgraduate government profit undergrad

(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

14

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

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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,

16

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

17

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

18

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.

19

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

20

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.

21

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.

22

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.

23

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.

24

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.

25

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.”

26

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.

27

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.

28

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

29

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.

30

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).

31

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,

32

indicating that more recently minted Ph.D. economists are more likely to believe the size of

military spending is too large.

33

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N Mean N Mean N Mean N Mean N Mean N Mean N Mean N Mean N Mean

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 0.35Ѐ 64 0.38 78 0.34† 261 0.44 137 0.44 124 0.45

0.49 0.00 0.00 0.48 0.49 0.48 0.50 0.50 0.50

404 0.26 202 0.29 202 0.24 143 0.30 65 0.34 78 0.27 261 0.24 137 0.26 124 0.22

0.44 0.00 0.00 0.46 0.48 0.45 0.43 0.44 0.41

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 0.16

0.35 0.00 0.00 0.33 0.33 0.34 0.35 0.34 0.37

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 0.12

0.32 0.00 0.00 0.33 0.27 0.38 0.31 0.30 0.33

403 0.60 201 0.54*** 202 0.64 143 0.55 65 0.47*** 78 0.60 260 0.62 136 0.58 124 0.67

0.49 0.00 0.00 0.50 0.50 0.49 0.49 0.50 0.47

PhD pre1970 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 0.13

0.28 0.23 0.32 0.27 0.24 0.29 0.29 0.22 0.34

395 0.21 198 0.16** 197 0.25 141 0.16Ѐ 65 0.12 76 0.20 254 0.23 133 0.18** 121 0.29

0.41 0.37 0.44 0.37 0.33 0.40 0.42 0.39 0.46

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 0.32

0.45 0.45 0.46 0.45 0.44 0.46 0.46 0.45 0.47

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 0.15

0.42 0.46 0.38 0.44 0.47 0.41 0.41 0.45 0.36

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 0.11

0.39 0.41 0.36 0.42 0.42 0.41 0.37 0.41 0.31

395 21.63 198 19.02*** 197 24.25 141 19.98ЀЀ 65 18.15*** 76 21.56 254 22.54 133 19.45*** 121 25.94

12.65 12.06 12.73 12.71 11.79 13.33 12.55 12.20 12.09

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).

dŚĞƐLJŵďŽůƐЀЀЀЀЀЀĚĞŶŽƚĞƌĞũĞĐƚŝŽŶĂƚƚŚĞϭϬйϱйϭйƐŝŐŶŝĨŝĐĂŶĐĞůĞǀĞůƐĨŽƌƚĞƐƚƐŽĨĞƋƵĂůŵĞĂŶƐďĞƚǁĞĞŶƌĞƐƉŽŶĚĞƌƐĂŶĚŶŽŶͲƌĞƐƉŽŶĚĞƌƐΖƉŽƉƵůĂƚŝŽŶƐboth overall and for each sex (using responders' and nonresponders' samples).

Graduate

Table 1: Characteristics of AEA Survey Sample

Variable

AEA Survey Sample Responders to Survey Non-Responders

Total Female Male Total Female Male Total Female Male

Female

PhD1990s

PhD2000s

YearsPh.D.

Undergraduate

For Profit

Government

Listed Research

PhD1970s

PhD1980s

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.

Table 2 : Probit Estimation of Probability of

Response to AEA survey, N = 391

PhD2000s

Constant

For Profit

Listed Research

For Profit x Listed Research

PhD1970s

PhD1980s

PhD1990s

X variables

Female

Graduate

Undergrad

Government

OLS Heckit OLS Heckit OLS Heckit OLS Heckit OLS Heckit

Female -0.196

(0.197)

-0.219

(0.232)-0.506***

(0.180)

-0.613***

(0.216)-1.056***

(0.174)

-0.979***

(0.213)0.300

(0.198)

0.400*

(0.239)

0.938***

(0.173)

0.806***

(0.214)

PhD1970s -0.851*

(0.473)

-0.842*

(0.480)-0.415

(0.409)

-0.467

(0.413)-0.415

(0.409)

-0.461

(0.451)0.812

(0.494)

0.935*

(0.514)

0.095

(0.433)

-0.010

(0.447)

PhD1980s -0.882*

(0.463)

-0.859*

(0.467)-0.919**

(0.400)

-0.847**

(0.410)-0.919*

(0.400)

-0.822*

(0.443)0.913*

(0.476)

0.901*

(0.478)

0.043

(0.420)

0.103

(0.425)

PhD1990s -0.903*

(0.459)

-0.919*

(0.504)-0.716*

(0.397)

-0.494

(0.452)-0.716

(0.397)

-0.587

(0.481)0.814*

(0.478)

0.659

(0.509)

0.032

(0.409)

0.224

(0.450)

PhD2000s -0.596

(0.488)

-0.559

(0.568)-0.423

(0.426)

-0.163

(0.510)-0.423

(0.426)

-0.688

(0.531)0.620

(0.501)

0.433

(0.554)

-0.089

(0.438)

0.191

(0.513)

Graduate 0.889**

(0.361)

0.875*

(0.472)0.118

(0.318)

-0.107

(0.394)0.118

(0.318)

0.123

(0.373)-0.357

(0.378)

-0.173

(0.437)

-0.067

(0.326)

-0.305

(0.398)

Government 0.608

(0.422)

0.591

(0.462)-0.224

(0.368)

-0.345

(0.391)-0.224

(0.368)

-0.162

(0.376)-0.015

(0.416)

0.073

(0.432)

0.126

(0.367)

0.011

(0.384)

For Profit 0.972**

(0.418)

0.965**

(0.466)-0.025

(0.370)

-0.213

(0.416)-0.025

(0.370)

0.068

(0.406)-0.254

(0.442)

-0.095

(0.480)

0.101

(0.412)

-0.046

(0.436)

Undergrad 0.829**

(0.381)

0.770*

(0.417)0.108

(0.342)

-0.010

(0.373)0.108

(0.342)

0.384

(0.370)-0.311

(0.400)

-0.227

(0.420)

-0.130

(0.345)

-0.258

(0.367)

Inverse Mills

Ratio

0.015

(0.908)

0.740

(0.744)

-0.389

(0.748)

-0.727

(0.845)

0.849

(0.805)

Constant 0.122

(0.367)

0.117

(0.846)0.764**

(0.320)

0.109

(0.730)0.764**

(0.320)

1.296**

(0.771)-0.628*

(0.374)

-0.008

(0.809)

-0.403

(0.321)

-1.147

(0.775)

R-squared 0.099 0.106 0.155 0.160 0.306 0.306 0.067 0.072 0.218 0.214

N 113 112 123 122 114 113 117 116 120 119

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.

Table 3 : Regression Tests of No Selection Bias using 2-Step Heckman Procedure (Heckit)

Dependent Variable: Standardized Scaled Answer to Group Question

Variables

Group 1:Core

Precepts/Economic

Group2: Market

Solutions & Gov.

Group 3: Gov.

Spending, Taxing and

Group 4: The

Environment

Group5: Gender and

Equal Opportunity

-0.27 -1.20** -0.86* -0.84 -0.60 0.86 0.26 0.84 0.35 0.35

(0.23) (0.54) (0.51) (0.51) (0.55) (0.41) (0.47) (0.47) (0.44) (0.43)

-0.65*** -0.77 -1.010** -0.872* -0.67 0.35 -0.23 0.18 0.07 0.91**

(0.23) (0.52) (0.49) (0.49) (0.53) (0.39) (0.46) (0.46) (0.43) (0.41)

-0.91*** -0.78 -0.831* -0.63 -0.73 0.26 -0.19 0.10 0.29 0.88**

(0.22) (0.51) (0.48) (0.48) (0.52) (0.38) (0.45) (0.45) (0.42) (0.40)

0.43* 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)

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 PhD1970s PhD1980s PhD1990s PhD2000s

population coefficient equals zero.

Graduate Govt For Profit Undergrad Constant

Group 1:Core Precepts/

Economic Methology (6

ques; Cronbach alpha=.71)

Group2: Market Solutions

& Gov. Interventions (8

ques; Cronbach alpha=.78)

Group 3: Government

Spending, Taxing, &

Redistribution (9 ques;

Cronbach alpha=.92)

Group 4: The Environment

(4 ques; Cronbach

alpha=.73)

Group 5: Gender and

Equal Opportunity (6

ques; Cronbach alpha=.93)

Standard errors are in parentheses beneath coefficient point estimates. *, **, *** denote 10%, 5%, 1% significance levels from the null hypothesis that the

Gender ɴІ R* ɲІ

female 3.11***

(0.15)

-0.54***

(0.19)

0.33***

(0.06)

0.19**

(0.08)

male 3.65***

(0.12)

0.14***

(0.04)

female 2.38***

(0.14)

-0.55***

(0.21)

0.62***

(0.06)

0.21**

(0.09)

male 2.93***

(0.14)

0.41***

(0.06)

female 2.21***

(0.18)

-0.54**

(0.27)

0.64***

(0.06)

0.12

(0.09)

male 2.75***

(0.20)

0.52***

(0.06)

female 2.99***

(0.18)

-0.77***

(0.24)

0.40***

(0.06)

0.27**

*

male 3.75***

(0.16)

0.13***

(0.05)

female 3.30***

(0.14)

-0.77***

(0.20)

0.22***

(0.05)

0.14**

(0.06)

male 4.07***

(0.13)

0.08**

(0.03)

*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.

A Wal-Mart store typically generates more benefits to society than

costs 1 or 2

The United States has an excessive amount of government

regulation of economic activity 1 or 2

The US should drill for oil in the Arctic National Wildlife Refuge

1 or 2

Parents should be given educational vouchers which can be used

at government-run or privately-run schools 1 or 2

The European Union has an excessive amount of government

regulation of economic activity 1 or 2

Table 5. Gender Differences in Opinions on Market Solutions & Government Interventions

Linear Probability Model: P(opinion| female, X) = ɲІ female + X ɲЇMean Response Model: E(R| female, X) = ɴІнyɴЇ

X = decade of Ph.D. (1970s, 1980s,1990s,2000s), type of employment

Group 2 Proposition: Mkt Solutions & Gov Interventions

N = 122P(R | X)E(R | X)

Gender β₁ R* α₁

female3.86***(0.16)

0.72***(0.23)

0.73***(0.06)

0.32***(0.09)

male 3.14***(0.16)

0.41***(0.06)

female2.91***(0.17)

-0.94***(0.21)

0.38***(0.07)

0.26***(0.08)

male 3.85***(0.12)

0.12***(0.04)

female3.34***(0.17)

0.94***(0.23)

0.52***(0.07)

0.30***(0.09)

male 2.41***(0.14)

0.22***(0.05)

female3.31***(0.17)

0.92***(0.23)

0.47***(0.07)

0.31***(0.08)

male 2.39***(0.14)

0.16***(0.04)

female2.51***(0.16)

-0.80***(0.23)

.54*** (0.07)

0.23** (0.09)

male 3.31***(0.16)

0.31*** (0.06)

female2.80***(0.11)

0.46***(0.17)

0.74***(0.06)

0.24***(0.09)

male 2.34***(0.12)

0.50***(0.06)

female2.81***(0.08)

0.70***(0.14)

0.83***(0.05)

0.41***(0.08)

male 2.11***(0.11)

0.41***(0.06)

*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.

Table 6. Gov. Spending, Taxing, & RedistributionLinear Probability Model: P(opinion| female, X) = α₁ female + X α₂

Mean Response Model: E(R| female, X) = β₁ + Xβ₂X = decade of Ph.D. (1970s, 1980s,1990s,2000s), type of employment

Increases in the minimum wage will increase unemployment among unskilled workers 1 or 2

Group 3 Proposition: Gov Spending, Taxing, & Redistribution N = 115

The distribution of income in the U.S. should be made more equal

4 or 5

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 3,4 or

5

The U.S. tax structure should be: 1=made less progressive, 2=kept at its current level of progressivity, 3=made more progressive 3

The U.S. should link import openness to the labor standards of its export partners 4 or 5

Employers in the U.S. should be required to provide health insurance to their full-time employees 4 or 5

The U.S. should implement a tax on consumption and rely less on income taxes for revenue 1 or 2

P(R | X)E(R | X)

Gender ɴІ R* ɲІ

female

2.55***

(0.17)

-1.07***

(0.23)

0.58***

(0.07)

0.42***

(0.08)

male

3.62***

(0.14)

0.16***

(0.05)

female

2.22***

(0.14)

-1.24***

(0.21)

0.74***

(0.06)

0.51***

(0.08)

male

3.46***

(0.15)

0.23***

(0.05)

female

2.04***

(0.12)

-1.09***

(0.18)

0.76***

(0.06)

0.55***

(0.08)

male

3.13***

(0.13)

0.21***

(0.05)

female

2.29***

(0.12)

-0.58***

(0.14)

0.52***

(0.06)

0.55***

(0.08)

male

2.88***

(0.08)

0.15***

(0.04)

*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.

The gender wage gap is largely explained by difference in human

capital and voluntary occupational choices 1 or 2

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

1 or 2

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

1 or 2

Job opportunities for men and women in the U.S. are currently

approximately equal 1 or 2

Table 7. Gender Differences in Opinions on Gender & Equal Opportunity

Linear Probability Model: P(opinion| female, X) = ɲІ female + X ɲЇMean Response Model: E(R| female, X) = ɴІнyɴЇ

X = decade of Ph.D. (1970s, 1980s,1990s,2000s), type of employment

Group 5 Proposition: Gender & Equal Opportunity N =

122P(R | X)E(R | X)

43

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.

44

Response 1 2 3 4 5female 3.2 15.9 17.5 55.6 7.9

male 2.7 20.3 12.2 48.6 16.2

female 1.6 21.9 6.3 48.4 21.9

male 2.6 17.1 7.9 44.7 27.6

female 0.0 1.6 17.7 48.4 32.3

male 0.0 1.6 29.7 46.9 21.9

female 0.0 7.8 21.9 50.0 20.3

male 0.0 6.7 21.3 50.7 21.3

female 1.7 11.7 20.0 50.0 16.7

male 2.6 19.7 19.7 42.1 15.8

female 45.9 45.9 8.2 - -

male 41.3 48.0 10.7 - -

Research on household decis ion-making should include analys is of intrahousehold decis ion-making

Group 1. Core Precepts and Economic Methodology Distribution of Responses by Gender*

PropositionIndividuals are rational uti l i ty maximizers

Human wants are unl imited

Mathematica l model ing should be an important part of economic model ing

GDP is an insufficient measure of overa l l economic performance

The economics profess ion in the US currently: 1. rel ies too much on deductive model ing and not enough on empirica l analys is ; 2. has about the right mix of empirica l analys is and deductive model ing; 3. rel ies too much on empirica l analys is and not enough on deductive model ing*Unless otherwise noted, 1 = s trongly disagree; 2 = disagree; 3 = neutra l ; 4 = agree; 5 = s trongly agree

45

Response 1 2 3 4 5female 1.6 7.8 10.9 56.3 23.4

male 0.0 2.6 9.0 46.2 42.3

female 6.7 26.7 20.0 41.7 5.0

male 1.4 13.7 26.0 39.7 19.2

female 17.5 47.6 20.6 12.7 1.6

male 7.7 33.3 26.9 21.8 10.3

female 0.0 8.1 9.7 61.3 21.0

male 0.0 1.3 7.8 44.2 46.8

female 39.7 27.0 14.3 14.3 4.8

male 27.6 25.0 11.8 17.1 18.4

female 27.4 32.3 19.4 17.7 3.2

male 32.0 30.7 13.3 17.3 6.7

female 16.1 24.2 22.6 22.6 14.5

male 6.5 7.8 24.7 28.6 32.5

female 5.0 16.7 28.3 41.7 8.3

male 1.4 8.1 12.2 41.9 36.5

The US should dri l l for oi l in the Arctic National Wi ldl i fe Refuge

Group 2. Market Solutions and Government Interventions Distribution of Responses by Gender*

Proposition

Market solutions are the most efficient way to a l locate resources under most ci rcumstances

The European Union has an excess ive amount of government regulation of economic activi ty

The United States has an excess ive amount of government regulation of economic activi tyThe US should reduce tari ffs and other barriers to trade

The US should impose taxes on unhealthy foods .

Parents should be given educational vouchers which can be used at government-run or privately-run schoolsA Wal-Mart s tore typica l ly generates more benefi ts to society than costs

*Unless otherwise noted, 1 = s trongly disagree; 2 = disagree; 3 = neutra l ; 4 = agree; 5 = s trongly agree

46

Response 1 2 3 4 5female 6.2 15.4 15.4 36.9 26.2

male 9.2 19.7 26.3 30.3 14.5

female 7.9 25.4 22.2 38.1 6.3

male 1.3 13.2 15.8 47.4 22.4

female 6.7 26.7 18.3 38.3 10.0

male 21.9 38.4 16.4 20.5 2.7

female 6.5 30.6 22.6 25.8 14.5

male 24.7 26.0 28.6 14.3 6.5

female 15.0 33.3 21.7 30.0 0.0

male 10.4 27.3 20.8 23.4 18.2

female 7.0 28.1 56.1 8.8 0.0

male 24.7 23.4 40.3 11.7 0.0

female 33.9 47.5 13.6 5.1 0.0

male 14.5 50.0 26.3 7.9 1.3

female 4.8 17.7 77.4 - -

male 28.6 28.6 42.9 - -

female 0.0 26.7 53.3 20.0 0.0

male 6.5 35.1 45.5 13.0 0.0

The U.S. should implement a tax on consumption and rely less on income taxes for revenue

Group 3. Government Spending, Taxing, and Redistribution Distribution of Responses by Gender*

PropositionThe dis tribution of income in the U.S. should be made more equal

Increases in the minimum wage wi l l increase unemployment among unski l led workers

The U.S. should l ink import openness to the labor s tandards of i ts export partners

Employers in the U.S. should be required to provide health insurance to their ful l -time employees

The s ize of government in the U.S. i s : 1=much too large, 2=too large, 3=about right, 4=too smal l , 5=much too smal l

Current levels of U.S. mi l i tary spending are: 1=much too large, 2=too large, 3=about right, 4=too smal l , 5=much too smal l

The U.S. tax s tructure should be: 1=made less progress ive, 2=kept at i ts current level of progress ivi ty, 3=made more progress ive

The effect of moderate amounts of inflation (< 5 %) on the economy are: 1=very harmful , 2=somewhat harmful , 3=minimal , 4=somewhat helpful , 5=very helpful*Unless otherwise noted, 1 = s trongly disagree; 2 = disagree; 3 = neutra l ; 4 = agree; 5 = s trongly agree

47

Response 1 2 3 4 5female 3.3 8.3 6.7 48.3 33.3

male 9.1 10.4 11.7 31.2 37.7

female 4.8 3.2 4.8 50.0 37.1

male 9.3 1.3 13.3 40.0 36.0

female 6.9 20.7 72.4 - -

male 12.2 31.1 56.8 - -

female 70.4 16.7 9.3 3.7 -

male 76.3 18.4 2.6 2.6 -

Ethanol subs idies in the U.S. should be: 1=el iminated, 2=reduced, 3=kept at the current level , 4=increased

Group 4. The EnvironmentDistribution of Responses by Gender*

PropositionThe U.S. should increase energy taxes

The U.S should impose a tax on emiss ions of greenhouse gases

Pol icies in the U.S. currently: 1. do too much to favor environment qual i ty at the expense of economic growth; 2. s trike approximately the right ba lance between environmental qual i ty and economic growth; 3. do too much to favor economic growth at the expense of

*Unless otherwise noted, 1 = s trongly disagree; 2 = disagree; 3 = neutra l ; 4 = agree; 5 = s trongly agree

48

Response 1 2 3 4 5female 18.8 37.5 10.9 29.7 3.1

male 4.1 15.1 19.2 45.2 16.4

female 16.1 53.2 16.1 12.9 1.6

male 6.8 20.3 18.9 39.2 14.9

female 12.7 36.5 23.8 20.6 6.3

male 25.0 30.3 25.0 19.7 0.0

female 9.5 28.6 23.8 30.2 7.9

male 20.8 29.9 18.2 28.6 2.6

female 22.0 54.2 16.9 6.8 0.0

male 7.0 12.7 46.5 23.9 9.9

female 18.3 35.0 43.3 3.3 0.0

male 5.6 9.7 77.8 5.6 1.4

*Unless otherwise noted, 1 = s trongly disagree; 2 = disagree; 3 = neutra l ; 4 = agree; 5 = s trongly agree

Group 5. Gender and Equal OpportunityDistribution of Responses by Gender*

Proposition

Job opportunities for men and women in the U.S. are currently approximately equal

The gender wage gap is largely expla ined by di fference in human capita l and voluntary occupational choices

Affi rmative action programs for women are a good idea

Affi rmative actions programs for African-Americans are a good idea

Opportunities for economics faculty in the U.S. currently: 1. favor men a lot more than women; 2. favor men a bi t more than women; 3. are approximately equal for men and women; 4. favor women a bi t 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 bi t more than women; 3. i s approximately equal for men and women; 4. favors women a bi t more than men; 5. favors women a lot more than men

49

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.

50

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.

51

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

52

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 Government-

backed 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.

53

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.

54

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.

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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.

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All Females Males

N 115 53 62Mean 3.01 2.97 3.05Stdev 0.49 0.52 0.46Min 1.33 1.33 2.00Max 4.00 3.83 4.00N 125 54 71Mean 2.70 2.57 2.81Stdev 0.44 0.41 0.45Min 1.75 1.75 1.75Max 3.63 3.50 3.63N 115 46 69Mean 2.98 2.57 3.25Stdev 0.68 0.51 0.65Min 1.67 1.67 2.00Max 4.67 4.00 4.67N 119 48 71Mean 3.21 3.31 3.14Stdev 0.67 0.64 0.69Min 1.25 1.25 1.25Max 4.50 4.50 4.50N 122 56 66Mean 3.04 3.44 2.69Stdev 0.82 0.73 0.74Min 1.17 2.00 1.17Max 4.83 4.83 4.50

Favor Increased Environmental

Protection

Labor Market Opportunities

Unequal

Table A1: Descriptive Statistics of Group Questions' Scaled Answers by AEA Member Sample

Value of 3.0 denotes "Neutral"Variable

Adhere to Core Precepts and

Economic Methology

Favor Market Solutions over Government Interventions

Favor Limiting Government-back

Redistribution

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Groups1 12 0.36 13 0.41 0.68 14 -0.41 -0.52 -0.67 15 -0.29 -0.46 -0.63 0.43 1

Groups 1 2 3 4 5

CorrelationTable A2: Pairwise Correlations of Scale Group Answers