Speaker lecturing.

The Research Network On The Determinants Of Life Course Capabilities And Outcomes

Bringing Together Scholars In Economics, Genetics, Psychology, Sociology, And Statistics To Produce New Knowledge About The Determinants, Development, And Measurement Of Capabilities Across The Life Cycle, As Well As Life Course Inequalities

The Research Network On The Determinants Of Life Course Capabilities And Outcomes initiative, an NIH-funded project lead by the CEHD from 2014-2023, produced new work on development across the life cycle and on life course inequalities. Scholars from the fields of economics, genetics, psychology, sociology, and statistics worked together to develop a comprehensive framework with which to analyze inequality in capabilities, with a focus on mid-life and late-life outcomes. The project convened conferences across disciplines, presenting a range of perspectives on the research topics and identifying and charting areas of commonalities and differences. Workshops hosted by the initiative brought together graduate students and emerging scholars to help foster cross-disciplinary training, creating a forum for new measurement and development approaches. The project also supported a pilot grant program, which facilitated multidisciplinary projects and trained emerging scholars.

Leadership

Principal Investigators
James Heckman, University of Chicago

Angela Duckworth, University of Pennsylvania

Planning Committee Members
Steven Durlauf, University of Wisconsin-Madison
Sara Jaffee,University of Pennsylvania
Brent Roberts, University of Illinois at Urbana-Champaign
Gene Robinson, University of Illinois at Urbana-Champaign
Burton Singer, University of Florida

Themes

Broad, Overlapping Themes

1. Methodological Research on Measurement, Causality, and Mechanisms

Our objective is to produce evidence-based models of life course inequality, using psychometric, econometric, and statistical tools.

2. Linking Social Science and Genetics

The network focuses on developing an integration of social science and genetics, with psychological, economic, and social traits and outcomes. Specifically, we wish to combine biologically-appropriate models of genes into the formal models of individual choices and outcomes. Using these models, we will reexamine long-standing questions on the relationship between nature and nurture.

3. Understanding the Evolution of Capabilities Across the Life Course

The network links the methodological and gene/environment work with the primary focus on life course inequalities. To accomplish this, we model inequalities from the perspective of capabilities.

4. Developmental Origins of Health

Physical health not only represents an essential component of overall capabilities but is highly dependent on other capabilities. We strive for a full understanding of the dynamics of health, which influence a range of socioeconomic outcomes.

Conferences and Workshops

The study of life course inequalities requires new science. Work from the fields of psychology, economics, genetics, sociology, and statistics must be integrated and built upon, involving both methodological and substantive research directions. The initiative held conferences and workshops to facilitate communication between psychologists, economists, geneticists, and others on frontier research topics. Alternative perspectives on the same research question were presented; areas of commonality and differences were identified and charted.

Events

October 20, 2014, University of Chicago:
The Effects of Socioeconomic Status on Identity and Personality

October 1-2, 2015, University of Chicago:
Measuring and Assessing Skills

November 17–18, 2016, University of Chicago:
Workshop on the Maternal Environment

December 8-9, 2016 University of Southern California's Leonard D. Schaeffer Center for Health Policy & Economics::
Conference on Genetics and Social Science

March 3-4, 2017, University of Chicago:
Conference on Measuring and Assessing Skills 2017

May 8-9, 2017, University of Pennsylvania:
Conference on Making Behavior Change Stick

February 9-10, 2018, the University of Chicago:
Measuring and Assessing Skills: Real-Time Measurement of Cognition, Personality, and Behavior

September 26, 2018, the University of Chicago:
Epigenetic Correlates of Adolescent Depression

September 27, 2018, the University of Chicago:
Child Endowments and Parental Investments: Does Inequality Start at Home?

November 2-3, 2018, New York City, New York:
Next Generation Data Sets for Measuring Child Development

November 30 - December 1, 2018, Los Angeles, California:
Polygenic Prediction and its Application in the Social Sciences

December 7-8, 2018, Los Angeles, California:
Measuring and Improving Health Equity

December 13-14, 2018, Austin, Texas:
Genes, Schools, and Interventions That Address Educational Inequality

February 4-6, 2019, Winnipeg, Manitoba:
Breastfeeding and the Origins of Health: Interdisciplinary Perspectives and Priorities

February 19, 2019, Chicago:
Prosociality: Hard to build but easy to destroy

June 6, 2019, Philadelphia:
Conference on Making Behavior Change Stick 2019

November 18-19, 2021, Madison:
Frontiers in Genetics and Economics

March 10-11, 2023, Chicago:
Frontiers in Economic Analysis with Genetic Data

Training Workshops

Training the Next Generation of Scholars

Workshops for graduate students and new professionals provided mechanisms for creating a long-run research program across disciplines. New approaches for both measurement and development were assessed and disseminated through these workshops. This work fostered a new generation of scholars not limited by traditional field boundaries.

The Network sponsored an ongoing student training lecture series called "The Lifecycle Working Group", which was open to the campus research community and ran for the duration of this project. The Lifecycle Working Group, organized by James Heckman, Juanna S. Joensen, and Jin Zhou, invited faculty, researchers and graduate students to present work that applied the comprehensive lifecycle approach to the study of human flourishing.

Published Papers

Research Products

Cunha, Flavio and James J. Heckman. (2016). "Decomposing Trends in Inequality in Earnings into Forecastable and Uncertain Components." Forthcoming, Journal of Labor Economics.

Abstract
A substantial empirical literature documents the rise in wage inequality in the American economy. It is silent on whether the increase in inequality is due to components of earnings that are predictable by agents or whether it is due to greater uncertainty facing them. These two sources of variability have different consequences for both aggregate and individual welfare. Using data on two cohorts of American males, we find that a large component of the rise in inequality for less skilled workers is due to uncertainty. For skilled workers, the rise is less pronounced.

Duckworth, Angela L., Johannes C. Eichstaedt, and Lyle H. Ungar. (2015). "The Mechanics of Human Achievement," Social and Personality Psychology Compass, 9(7): 359-369.

Abstract
Countless studies have addressed why some individuals achieve more than others. Nevertheless, the psychology of achievement lacks a unifying conceptual framework for synthesizing these empirical insights. We propose organizing achievement-related traits by two possible mechanisms of action: Traits that determine the rate at which an individual learns a skill are talent variables and can be distinguished conceptually from traits that determine the effort an individual puts forth. This approach takes inspiration from Newtonian mechanics: achievement is akin to distance traveled, effort to time, skill to speed, and talent to acceleration. A novel prediction from this model is that individual differences in effort (but not talent) influence achievement (but not skill) more substantially over longer (rather than shorter) time intervals. Conceptualizing skill as the multiplicative product of talent and effort, and achievement as the multiplicative product of skill and effort, advances similar, but less formal, propositions by several important earlier thinkers.

Duckworth, Angela L., Tamar Szabó Gendler, and James J. Gross. (2016). "Situational Strategies for Self-Control," Perspectives on Psychological Science. 11: 35-55.

Abstract
Exercising self-control is often difficult, whether declining a drink in order to drive home safely, passing on the chocolate cake to stay on a diet, or ignoring text messages to finish reading an important paper. But enacting self-control is not always difficult, particularly when it takes the form of proactively choosing or changing situations in ways that weaken undesirable impulses or potentiate desirable ones. Examples of situational self-control include the partygoer who chooses a seat far from where drinks are being poured, the dieter who asks the waiter not to bring around the dessert cart, and the student who goes to the library without a cell phone. Using the process model of self-control, we argue that the full range of self-control strategies can be organized by considering the timeline of the developing tempting impulse. Because impulses tend to grow stronger over time, situational self-control strategies—which can nip a tempting impulse in the bud—may be especially effective in preventing undesirable action. Ironically, we may underappreciate situational self-control for the same reason it is so effective—namely, that by manipulating our circumstances to advantage, we are often able to minimize the in-the-moment experience of intrapsychic struggle typically associated with exercising self-control.

Duckworth, Angela L., Elizabeth P. Shulman, Andrew J. Mastronarde, Sarah D. Patrick, Jinghui Zhang, and Jeremy Druckman. (2015). "Will not want: Self-control rather than motivation explains the female advantage in report card grades," Learning and Individual Differences, 39: 13-23.

Abstract
Girls earn better grades than boys, but the mechanism explaining this gender difference is not well understood. We examined the relative importance of self-control and motivation in explaining the female advantage in grades. In Study 1, we surveyed middle school teachers and found that they judged girls to be higher in both school motivation and self-control. In Studies 2 and 3—using self-reported motivation and teacher- and/or parent-reported self-control, and quarterly and final grades obtained from school records—we find that self-control, but not school motivation, helps to explain the gender gap in academic performance. In these studies, girls appeared to be more self-controlled than boys, but—contrary to teacher judgments in Study 1—did not appear to be more motivated to do well in school.

Duckworth, Angela L., R. E. White, A. J. Matteucci, and J. J. Gross. (in press). "A stitch in time: Strategic self-control in high school and college students," Forthcoming in Journal of Educational Psychology.

Abstract

Duckworth, Angela L. and David Scott Yeager. (2015). "Measurement Matters: Assessing Personal Qualities Other Than Cognitive Ability for Educational Purposes," Educational Researcher, 44: 237-251.

Abstract
There has been perennial interest in personal qualities other than cognitive ability that determine success, including self-control, grit, growth mind-set, and many others. Attempts to measure such qualities for the purposes of educational policy and practice, however, are more recent. In this article, we identify serious challenges to doing so. We first address confusion over terminology, including the descriptor noncognitive. We conclude that debate over the optimal name for this broad category of personal qualities obscures substantial agreement about the specific attributes worth measuring. Next, we discuss advantages and limitations of different measures. In particular, we compare self-report questionnaires, teacher-report questionnaires, and performance tasks, using self-control as an illustrative case study to make the general point that each approach is imperfect in its own way. Finally, we discuss how each measure’s imperfections can affect its suitability for program evaluation, accountability, individual diagnosis, and practice improvement. For example, we do not believe any available measure is suitable for between-school accountability judgments. In addition to urging caution among policymakers and practitioners, we highlight medium-term innovations that may make measures of these personal qualities more suitable for educational purposes.

Duckworth, Angela L. and David Scott Yeager. (2015). "Measurement Matters: Assessing Personal Qualities Other Than Cognitive Ability for Educational Purposes," Educational Researcher, 44: 237-251.

Abstract
There has been perennial interest in personal qualities other than cognitive ability that determine success, including self-control, grit, growth mind-set, and many others. Attempts to measure such qualities for the purposes of educational policy and practice, however, are more recent. In this article, we identify serious challenges to doing so. We first address confusion over terminology, including the descriptor noncognitive. We conclude that debate over the optimal name for this broad category of personal qualities obscures substantial agreement about the specific attributes worth measuring. Next, we discuss advantages and limitations of different measures. In particular, we compare self-report questionnaires, teacher-report questionnaires, and performance tasks, using self-control as an illustrative case study to make the general point that each approach is imperfect in its own way. Finally, we discuss how each measure’s imperfections can affect its suitability for program evaluation, accountability, individual diagnosis, and practice improvement. For example, we do not believe any available measure is suitable for between-school accountability judgments. In addition to urging caution among policymakers and practitioners, we highlight medium-term innovations that may make measures of these personal qualities more suitable for educational purposes.

Elango, Sneha, Jorge Luis Garcia, James J. Heckman, and Andres Hojman. (2016). "Early Childhood Education," Forthcoming in Means-Tested Transfer Programs in the United States II. Moffitt R, editor. Chicago, IL: University of Chicago Press.

Abstract
This paper organizes and synthesizes the literature on early childhood education and childcare. In it, we go beyond meta-analysis and reanalyze primary data sources in a common framework. We consider the evidence from means-tested demonstration programs, large-scale means-tested programs and universal programs without means testing. We discuss which programs are beneficial and whether they are cost-effective for certain populations. The evidence from high-quality demonstration programs targeted toward disadvantaged children shows beneficial effects. Returns exceed costs, even accounting for the deadweight loss of collecting taxes. When proper policy counterfactuals are constructed, Head Start has beneficial effects on disadvantaged children compared to home alternatives. Universal programs benefit disadvantaged children.

Heckman, James J., John Eric Humphries, and Gregory Veramendi. (2016). "Dynamic Treatment Effects." Journal of Econometrics, 191(2): 276-292.

Abstract
This paper develops robust models for estimating and interpreting treatment effects arising from both ordered and unordered multistage decision problems. Identification is secured through instrumental variables and/or conditional independence (matching) assumptions. We decompose treatment effects into direct effects and continuation values associated with moving to the next stage of a decision problem. Using our framework, we decompose the IV estimator, showing that IV generally does not estimate economically interpretable or policy relevant parameters in prototypical dynamic discrete choice models, unless policy variables are instruments. Continuation values are an empirically important component of estimated total treatment effects of education. We use our analysis to estimate the components of what LATE estimates in a dynamic discrete choice model.

Heckman, James J. (2015). "Gary Becker: Model Economic Scientist." American Economic Review. 105(5):74-79.

Abstract
Gary Becker transformed economics by broadening the range of problems considered by economists and by creating new analytical frameworks. He founded flourishing fields of economics and public policy. It can be said of Gary Becker that his ideas launched hundreds of datasets and thousands of empirical and theoretical studies. This paper discusses Becker as a model economic scientist whose creativity, curiosity, tenacity, openness to ideas, and research methodology combined to produce a body of research that expanded the boundaries of economics and addressed fundamental questions of public policy.

Pilot Grant Program

Support for Research Projects from Graduate Students or Emerging Scholars

Our grant program was designed to support research projects from graduate students and emerging scholars which represent the interdisciplinary syntheses of the network’s aims. It encouraged both new collaborations and innovative ideas that transcended a scholarly environment that can be limited by discipline-specific training.

The pilot project awardee received a grant of up to $10,000 to support an existing or new research project that contributed to the understanding of the mechanisms by which inequality is created by synthesizing and extending discipline-specific approaches. In particular, how do genetics, family and social life experiences, and markets combine to produce observed inequality in health, income, and wealth? The awardee took a novel approach to this question under the auspices of a mentorship team of two senior scholars from differing disciplines. In addition, the program’s awardee was invited to forthcoming training workshops that paralleled the themes of this research network.