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The Scientific Contributions of James Heckman and Daniel McFadden


  • Committee, Nobel Prize

    (Nobel Prize Committee)


Advanced Information. Microeconometric research is concerned with empirical analysis of the economic behavior of individuals and households, such as decisions on labor supply, consumption, migration or occupational choice. Microeconometric methods are equally relevant in studies of individual firms, for example their production and employment decisions. Over the last several decades, significant breakthroughs in empirical microeconomic research have been triggered by innovations in microeconometric methods and by greater availability of new types of data. The raw material in microeconometric research is microdata, where the units of observation are individuals, households or firms. Microdata appear as cross-section data and, to an increasing degree, as longitudinal (panel) data.

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  • Committee, Nobel Prize, 2000. "The Scientific Contributions of James Heckman and Daniel McFadden," Nobel Prize in Economics documents 2000-2, Nobel Prize Committee.
  • Handle: RePEc:ris:nobelp:2000_002

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    References listed on IDEAS

    1. Willis, Robert J & Rosen, Sherwin, 1979. "Education and Self-Selection," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages 7-36, October.
    2. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
    3. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
    4. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    5. Newey, Whitney K & Powell, James L & Walker, James R, 1990. "Semiparametric Estimation of Selection Models: Some Empirical Results," American Economic Review, American Economic Association, vol. 80(2), pages 324-328, May.
    6. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 487-535.
    7. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
    8. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
    9. Gronau, Reuben, 1974. "Wage Comparisons-A Selectivity Bias," Journal of Political Economy, University of Chicago Press, vol. 82(6), pages 1119-1143, Nov.-Dec..
    10. James J. Heckman & Christopher R. Taber, 1994. "Econometric Mixture Models and More General Models for Unobservables in Duration Analysis," NBER Technical Working Papers 0157, National Bureau of Economic Research, Inc.
    11. Lee, Lung-fei, 1994. "Semiparametric two-stage estimation of sample selection models subject to Tobit-type selection rules," Journal of Econometrics, Elsevier, vol. 61(2), pages 305-344, April.
    12. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    13. McFadden, Daniel, 1987. "Regression-based specification tests for the multinomial logit model," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 63-82.
    14. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    15. Hausman, Jerry A. & Leonard, Gregory K. & McFadden, Daniel, 1995. "A utility-consistent, combined discrete choice and count data model Assessing recreational use losses due to natural resource damage," Journal of Public Economics, Elsevier, vol. 56(1), pages 1-30, January.
    16. Ahn, H. & Powell, J.L., 1990. "Semiparametric Estimation Of Censored Selection Models With A Nonparametric Selection Mechanism," Working papers 90-33, Wisconsin Madison - Social Systems.
    17. Theil, Henri, 1969. "A Multinomial Extension of the Linear Logit Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(3), pages 251-259, October.
    18. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
    19. Lee, Lung-Fei, 1994. "Semiparametric instrumental variable estimation of simultaneous equation sample selection models," Journal of Econometrics, Elsevier, vol. 63(2), pages 341-388, August.
    20. A. D. Roy, 1951. "Some Thoughts On The Distribution Of Earnings," Oxford Economic Papers, Oxford University Press, vol. 3(2), pages 135-146.
    21. Lewis, H Gregg, 1974. "Comments on Selectivity Biases in Wage Comparisons," Journal of Political Economy, University of Chicago Press, vol. 82(6), pages 1145-1155, Nov.-Dec..
    22. Manski, Charles F & Lerman, Steven R, 1977. "The Estimation of Choice Probabilities from Choice Based Samples," Econometrica, Econometric Society, vol. 45(8), pages 1977-1988, November.
    23. Heckman, James J & Sedlacek, Guilherme, 1985. "Heterogeneity, Aggregation, and Market Wage Functions: An Empirical Model of Self-selection in the Labor Market," Journal of Political Economy, University of Chicago Press, vol. 93(6), pages 1077-1125, December.
    24. Heckman, James J, 1991. "Identifying the Hand of the Past: Distinguishing State Dependence from Heterogeneity," American Economic Review, American Economic Association, vol. 81(2), pages 75-79, May.
    25. Diamond, P. A. & McFadden, D. L., 1974. "Some uses of the expenditure function in public finance," Journal of Public Economics, Elsevier, vol. 3(1), pages 3-21, February.
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    Cited by:

    1. Atish R. Ghosh & Juan Zalduendo & Manuela Goretti & Bikas Joshi & Alun H. Thomas, 2007. "Modeling Aggregate Use of Fund Resources—Analytical Approaches and Medium-Term Projections," IMF Working Papers 07/70, International Monetary Fund.

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    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models


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