Econometric policy evaluation: A critique

Here, we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a ‘three degrees of influence’ property, and we review statistical approaches we have used to characterize interpersonal influence with respect to phenomena as diverse as obesity, smoking, cooperation, and happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations. Copyright © 2012 John Wiley & Sons, Ltd.

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Social contagion theory: examining dynamic social networks and human behavior

This chapter summarizes the recent literature on peer effects in student outcomes at the elementary, secondary, and post-secondary levels. Linear-in-means models find modest sized and statistically significant peer effects in test scores. But the linear-in-means model masks considerable heterogeneity in the effects experienced by different types of students. Using nonlinear models, one prevalent finding is larger peer effects in which high ability students benefit from the presence of other high ability students. Studies that stratify students by race and ability often find that students are affected both by the racial composition of their peers and by the achievement of their same-race peers. At the university level, several studies find modest sized effects from dormmate and roommate background on own academic performance. For both university and high school students, the measured peer effects on “social” outcomes such as drinking are larger than the effects on academic outcomes. Many authors find substantial peer effects in drinking, drug use, and criminal behavior. This chapter suggest areas for future investigation and data collection.

Peer Effects in Education: How Might They Work, How Big Are They and How Much Do We Know Thus Far?

Psychological and socio-psychological factors are now more commonly discussed as possible explanations for gender differences in labor market outcomes. We first describe the (mainly) laboratory-based evidence regarding gender differences in risk preferences, in attitudes towards competition, in the strength of other-regarding preferences, and in attitudes towards negotiation. We then review the research that has tried to quantify the relevance of these factors in explaining gender differences in labor market outcomes outside of the laboratory setting. We also describe recent research on the relationship between social and gender identity norms and women’s labor market choices and outcomes, as well as on the role of child-rearing practices in explaining gender identity norms. Finally, we report on some recent work documenting puzzling trends in women’s well-being and discuss possible explanations for these trends, including identity considerations. We conclude with suggestions for future research.

New Perspectives on Gender

Summary Much has been written in the past two decades about women in academic science careers, but this literature is contradictory. Many analyses have revealed a level playing field, with men and women faring equally, whereas other analyses have suggested numerous areas in which the playing field is not level. The only widely-agreed-upon conclusion is that women are underrepresented in college majors, graduate school programs, and the professoriate in those fields that are the most mathematically intensive, such as geoscience, engineering, economics, mathematics/ computer science, and the physical sciences. In other scientific fields (psychology, life science, social science), women are found in much higher percentages. In this monograph, we undertake extensive life-course analyses comparing the trajectories of women and men in math-intensive fields with those of their counterparts in non-math-intensive fields in which women are close to parity with or even exceed the number of men. We begin by examining early-childhood differences in spatial processing and follow this through quantitative performance in middle childhood and adolescence, including high school coursework. We then focus on the transition of the sexes from high school to college major, then to graduate school, and, finally, to careers in academic science. The results of our myriad analyses reveal that early sex differences in spatial and mathematical reasoning need not stem from biological bases, that the gap between average female and male math ability is narrowing (suggesting strong environmental influences), and that sex differences in math ability at the right tail show variation over time and across nationalities, ethnicities, and other factors, indicating that the ratio of males to females at the right tail can and does change. We find that gender differences in attitudes toward and expectations about math careers and ability (controlling for actual ability) are evident by kindergarten and increase thereafter, leading to lower female propensities to major in math-intensive subjects in college but higher female propensities to major in non-math-intensive sciences, with overall science, technology, engineering, and mathematics (STEM) majors at 50% female for more than a decade. Post-college, although men with majors in math-intensive subjects have historically chosen and completed PhDs in these fields more often than women, the gap has recently narrowed by two thirds; among non-math-intensive STEM majors, women are more likely than men to go into health and other people-related occupations instead of pursuing PhDs. Importantly, of those who obtain doctorates in math-intensive fields, men and women entering the professoriate have equivalent access to tenure-track academic jobs in science, and they persist and are remunerated at comparable rates—with some caveats that we discuss. The transition from graduate programs to assistant professorships shows more pipeline leakage in the fields in which women are already very prevalent (psychology, life science, social science) than in the math-intensive fields in which they are underrepresented but in which the number of females holding assistant professorships is at least commensurate with (if not greater than) that of males. That is, invitations to interview for tenure-track positions in math-intensive fields—as well as actual employment offers—reveal that female PhD applicants fare at least as well as their male counterparts in math-intensive fields.

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Women in Academic Science: A Changing Landscape

We estimate peer effects in college achievement using a data set in which individuals are exogenously assigned to peer groups of about 30 students with whom they are required to spend the majority of their time interacting. This feature enables us to estimate peer effects that are more comparable to changing the entire cohort of peers. Using this broad peer group, we measure academic peer effects of much larger magnitude than found in previous studies. The effects persist at a diminished rate into follow‐on years, and we find evidence of nonlinearities in the magnitude of the effects across student academic ability.

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Does Your Cohort Matter? Measuring Peer Effects in College Achievement

We take cohorts of entering freshmen at the United States Air Force Academy and assign half to peer groups designed to maximize the academic performance of the lowest ability students. Our assignment algorithm uses nonlinear peer effects estimates from the historical pre-treatment data, in which students were randomly assigned to peer groups. We find a negative and significant treatment effect for the students we intended to help. We provide evidence that within our �optimally� designed peer groups, students avoided the peers with whom we intended them to interact and instead formed more homogeneous subgroups. These results illustrate how policies that manipulate peer groups for a desired social outcome can be confounded by changes in the endogenous patterns of social interactions within the group.

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From Natural Variation to Optimal Policy? The Importance of Endogenous Peer Group Formation

Why aren't there more women in science? Female college students are currently 37 percent less likely than males to obtain a bachelor's degree in science, technology, engineering, and math (STEM), and comprise only 25 percent of the STEM workforce This paper begins to shed light on this issue by exploiting a unique dataset of college students who have been randomly assigned to professors over a wide variety of mandatory standardized courses We focus on the role of professor gender Our results suggest that while professor gender has little impact on male students, it has a powerful effect on female students' performance in math and science classes, their likelihood of taking future math and science courses, and their likelihood of graduating with a STEM degree The estimates are largest for female students with very strong math skills, who are arguably the students who are most suited to careers in science Indeed, the gender gap in course grades and STEM majors is eradicated when high performing female students' introductory math and science classes are taught by female professors In contrast, the gender of humanities professors has only minimal impact on student outcomes We believe that these results are indicative of important environmental influences at work

Sex and Science: How Professor Gender Perpetuates the Gender Gap

NBER WORKING PAPER SERIESSEX AND SCIENCE:HOW PROFESSOR GENDER PERPETUATES THE GENDER GAPScott E. CarrellMarianne E. PageJames E. WestWorking Paper 14959http://www.nber.org/papers/w14959NATIONAL BUREAU OF ECONOMIC RESEARCH1050 Massachusetts AvenueCambridge, MA 02138May 2009Thanks go to USAFA personnel: J. Putnam, D. Stockburger, R. Schreiner, K. Carson and P. Eglestonfor assistance in obtaining the data, and to Deb West for data entry. Thanks also go to Charlie Brown,Charles Clotfelter, Caroline Hoxby, Deborah Niemeier, Kim Shauman, Catherine Weinberger andseminar participants at NBER Higher Education Working Group, PPIC, SDSU, UC Davis, UC Irvine,and UC Santa Cruz for their helpful comments and suggestions. The views expressed in this articleare those of the authors and do not necessarily reflect the official policy or position of the USAF, DoD,the U.S. Government, or the National Bureau of Economic Research.© 2009 by Scott E. Carrell, Marianne E. Page, and James E. West. All rights reserved. Short sectionsof text, not to exceed two paragraphs, may be quoted without explicit permission provided that fullcredit, including © notice, is given to the source.

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In primary and secondary education, measures of teacher quality are often based on contemporaneous student performance on standardized achievement tests. In the postsecondary environment, scores on student evaluations of professors are typically used to measure teaching quality. We possess unique data that allow us to measure relative student performance in mandatory follow‐on classes. We compare metrics that capture these three different notions of instructional quality and present evidence that professors who excel at promoting contemporaneous student achievement teach in ways that improve their student evaluations but harm the follow‐on achievement of their students in more advanced classes.

http://faculty.econ.ucdavis.edu/faculty/scarrell/profqual2.pdf

James E. West

Papers

Does Your Cohort Matter? Measuring Peer Effects in College Achievement

From Natural Variation to Optimal Policy? The Importance of Endogenous Peer Group Formation

Sex and Science: How Professor Gender Perpetuates the Gender Gap

Sex and Science: How Professor Gender Perpetuates the Gender Gap

Does Professor Quality Matter? Evidence from Random Assignment of Students to Professors