The Nobel Prize

James J. Heckman (b. 1944)



James Heckman was born in Chicago, Illinois, USA in 1944. He spent most of his childhood in Chicago but the family lived in Kentucky and Oklahoma for a few years before settling in Denver, Colorado, where Heckman went to high school. His time in the South, coupled with a later visit in the company of a Nigerian friend, exposed him to the last spasms of institutionalised racial discrimination practised there. This left a lasting impression and kindled a determination to do something to confront the implications of such social degeneration: ‘The separate water fountains, park benches, bathrooms and restaurants of the Jim Crow South startled me. These experiences motivated my lifelong study of the status of African Americans, and the sources of improvement in that status’ (Nobel Foundation, 2004).

In high school, Heckman was taught by Frank Oppenheimer, whose brother Robert had been leader of the team that developed the first atomic bomb. Frank Oppenheimer was also a physicist but, according to Heckman, he lost his university post because of his membership of the Communist Party. This happened in the early 1950s, a period associated with ‘McCarthyism’ in the United States, when many Americans suffered professionally because of alleged or sincerely held political beliefs. Eventually Oppenheimer returned to teaching and Heckman won a place in his class. This was an important stage in Heckman’s intellectual development. He recollects:

Under his [Oppenheimer’s] guidance I learned the beauty of experimental science and the pleasure of matching theory to evidence. Although I later abandoned physics for economics, my enthusiasm for scientific empirical work guided by theory was born in his classroom. (Nobel Foundation, 2004)

Heckman attended Colorado College, obtaining a BA in mathematics in 1965. After spending a short time at the University of Chicago, he transferred to Princeton University largely because of the presence there of Arthur Lewis. Heckman had first read Lewis at Colorado College and wanted to learn more about his work on economic development (see entry on Lewis – a joint Laureate in 1979 – in this volume). Heckman was awarded an MA in economics by Princeton in 1968. Although he had been drawn to Princeton by the opportunity to study development, Heckman found his interests stimulated by labour economics and econometrics, and a ‘lifetime intellectual passion’ to bring together theory and evidence in economics was born. He received his PhD from Princeton in 1971 for work on household labour supply and the demand for market goods.

Heckman’s first academic post was at Columbia University, where he was assistant professor from 1970 to 1973 and associate professor from 1973 to 1974. In 1972 he was also adjunct professor at New York University. Apart from a very brief period in the mid-1980s, Heckman has enjoyed a long association with the National Bureau of Economic Research where he has been a research associate (1971– 85 and 1987–date) and a research fellow (1972–73). In 1973 Heckman moved to the University of Chicago as associate professor before becoming Professor of Economics in 1977 and, in 1985, Henry Schultz Professor. In 1988 he was appointed A. Whitney Griswold Professor of Economics at Yale University before becoming, briefly, Professor of Statistics at Yale in 1990. He returned to the University of Chicago in 1990 as Henry Schultz Professor and also accepted a joint position at the Irving Harris School of Public Policy, also at Chicago. In 1991 Heckman became director of the university’s newly founded Center for Evaluation of Social Programs. Since 1995 he has been Henry Schultz Distinguished Service Professor at Chicago.

Heckman’s professional activities have included service as a member of: the Social Science Research Council Committee on Research Methods for Longitudinal Data (1976–79 and 1981–82); the National Science Foundation Evaluation Panel in Economics (1977–79); the National Academy of Sciences Panel on Statistical Assessments as Evidence in the Courts (1982–85); and the National Academy of Sciences Panel on the Status of Black Americans (1985–88).

Heckman’s offices and honours include a fellowship at the Center for Advanced Study in the Behavioural Sciences at Stanford University in 1978–79 and, for the same period, a John Simon Guggenheim Memorial Fellowship. He became a fellow of the Econometric Society in 1980 and was awarded the John Bates Clark Medal by the American Economic Association in 1983. In the Fall of 1984, Heckman was Irving Fisher Visiting Professor at Yale University and in 1985 he received the first annual Louis T. Benezet Distinguished Alumnus Award from Colorado College. Also in 1985 he became an elected fellow of the American Academy of Arts and Sciences. Since 1991 he has been a senior research fellow at the American Bar Foundation. Heckman was president of the Midwest Economics Association in 1998 and a fellow of the American Statistical Association in 2001. He became an elected member of the National Academy of Sciences in 1992 and he holds honorary degrees and professorships from a number of universities around the world. In 2000 Heckman was awarded the Nobel Memorial Prize in Economics ‘for his development of theory and methods for analysing selective samples’ (Nobel Foundation, 2004).

Heckman’s most notable contribution to the field of microeconometrics – the theoretically informed study of individual behaviour using individual data – is methodological. In an enormously influential paper in Econometrica, he proposed a means of dealing with the problem of ‘selection bias’ in statistically-based economic research (Heckman, 1979). This paper was highlighted in Heckman’s Nobel award. The selection bias problem arises because the samples investigators work with may not be representative of the populations from which they are drawn. One way in which this can happen is through individuals ‘self-selecting’ into a sample. Heckman’s Nobel citation provides an illustration. An investigation of the effect of education on wages must necessarily focus on a sample whose members have chosen to work: the sample is selective and not representative of the true population that contains both those in work and the unemployed. To address selection bias Heckman proposed a two-stage selection model – what has become known as the Heckman two-step estimator or ‘Heckit’ estimator. The first step is to estimate the probability of selection into the sample; the second is to use these probabilities as an independent variable in a leastsquares model. The problem of selection bias is, of course, not unique to economics and Heckman’s innovations have been taken up in other social science disciplines; indeed, it has been suggested that Heckman’s (1979) Econometrica paper is the most widely read outside economics ever to have been published in that journal (Heinrich and Wenger, 2002).

Heckman has applied his insights into selection bias to some important economic and social questions. For example, in work with Thomas Lyons and Petra Todd, he has produced a view of the economic progress made by black males in the United States since the Second World War that is, after allowing for selection bias, less sanguine than the norm (Heckman et al., 2000; see also Heckman and Payner, 1989). As he reports in his Nobel lecture, the median American black–white male wage ratio increased between 1940 and 1980 from less than 0.5 to a little above 0.7; after 1980 the ratio stabilised (Heckman, 2001). The problem is that over the whole period, blacks were withdrawing from the labour force at a much faster rate than whites, and this means that they were also withdrawing from the statistics used to measure wages. He finds that

Correcting for the selective withdrawal of low-wage black workers from employment reduces and virtually eliminates black male economic progress compared to that of whites and challenges optimistic assessments of African-American economic progress. (ibid., p. 699)

Heckman’s early work in microeconometrics was also characteristically pioneering. The wealth of new microeconomic data that became available to researchers from the 1950s posed significant analytical challenges. As Heckman points out, ‘The R2 (measure of explained fit) of any micro relationship is typically low, so the unobservables account for a lot of … variability’ (ibid, p. 684). This is testament to what he calls the ‘pervasiveness of heterogeneity and diversity in economic life’ (ibid., p. 674). The challenge was to make scientific and economic sense of data that describes such diversity. This is something Heckman began to do in a series of important papers beginning in the first half of the 1970s. For example, in a widely cited article in Econometrica, Heckman modelled labour supply in such a way that the decision to work reflected interrelated choices over hours of work, the reservation wage and constraints on labour force participation (Heckman 1974b; and see Blundell, 2001; Heinrich and Wenger, 2002). He applied this model to consider the effects of the Nixon administration’s programmes of childcare support on women’s work effort (Heckman, 1974a). Heckman (1976) has also extended his analytical framework to consider the life cycle of labour supply. In the 1980s, with Richard Robb, Heckman produced highly influential methodological advances in the evaluation of training programmes (Heckman and Robb, 1985; 1986), and has since built up a whole body of evaluation work in collaboration with a number of researchers (see, for example, Heckman and Smith, 1997; Cameron and Heckman, 1998a; Heckman et al., 1998b).

Heckman’s output is prodigious. His CV lists over 200 journal articles and there is no doubt that, in the words of the Royal Swedish Academy of Sciences, ‘His work has had a decisive influence both on subsequent methodological development and on applied research in microeconometrics’ (Nobel Foundation, 2004).

Main Published Works
(1974a), ‘Effects of Child Care Programs on Women’s Work Effort’, Journal of Political Economy, 82, March/April, pp. S136–S143; reprinted in T.W. Schultz (ed.), Economics of the Family: Marriage, Children and Human Capital, Chicago: University of Chicago Press (for NBER).
(1974b), ‘Shadow Prices, Market Wages and Labor Supply’, Econometrica, 42, July, pp. 679– 94.
(1976), ‘A Life-Cycle Model of Earnings, Learning and Consumption’, Journal of Political Economy, 84, August, pp. S11–S44.
(1979), ‘Sample Selection Bias as Specification Error’, Econometrica, 47, January, pp. 47–74.
(1985), ‘Alternative Methods for Estimating the Impact of Interventions’ (with R. Robb), in J. Heckman and B. Singer (eds), Longitudinal Analysis of Labour Market Data, New York: Wiley, pp. 156–256.
(1986), ‘Alternative Identifying Assumptions in Econometric Models of Selection Bias’ (with R. Robb), in D.J. Slottje (ed.), Advances in Econometrics, vol. 5, Greenwich, CT: JAI Press.
(1989), ‘Determining the Impact of Federal Anti-Discrimination Policy on the Economic Status of Blacks: A Study of South Carolina’ (with B.S. Payner), American Economic Review, 79, March, pp. 138–77.
(1997), ‘Making the Most out of Program Evaluations and Social Experiments: Accounting for Heterogeneity in Programme Impacts’ (with J. Smith), Review of Economic Studies, 64, October, pp. 487–535.
(1998a), ‘Life Cycle Schooling and Educational Selectivity: Models and Choice’ (with S. Cameron), Journal of Political Economy, 106, April, pp. 262–333.
(1998b), ‘General-Equilibrium Treatment Effects: A Study of Tuition Policy’ (with L. Lochner and C. Taber), American Economic Review, 88, May, pp. 381–6.
(2000), ‘Understanding Black–White Wage Differentials, 1960–1990’ (with T.M. Lyons and P.E. Todd), American Economic Review, 90, May, pp. 344–9.
(2001), ‘Microdata, Heterogeneity and the Evaluation of Public Policy’, Journal of Political Economy, 109, August, pp. 673–784.

Secondary Literature
Blundell, R. (2001), ‘James Heckman’s Contributions to Economics and Econometrics’, Scandinavian Journal of Economics, 103 (2), pp. 191–203.
Heinrich, C.J. and J.B. Wenger (2002), ‘The Economic Contributions of James J. Heckman and Daniel L. McFadden’, Review of Political Economy, 14, January, pp. 69–89.
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