Skip to main content
SpringerLink
Log in

Microeconometrics

  • Reference work entry
Encyclopedia of Complexity and Systems Science

Definition of the Subject

Microeconometrics deals with model-based analysis of individual-level or grouped data on the economicbehavior of individuals, households, establishments or firms. Regression methods applied to cross-section or panel (longitudinal) data constitutethe core subject matter. Microeconometric methods are also broadly applicable to social and mathematical sciences that usestatistical modeling. The data used in microeconometric modeling usually come from cross section and panel surveys, censuses, or socialexperiments. A major goal of microeconometric analysis is to inform matters of public policy. The methods of microeconometrics have also proveduseful in providing model-based data summaries and prediction of hypothetical outcomes.

Introduction

Microeconometrics takes as its subject matter the regression-based modeling of economic relationships using data at the levels of individuals,households, and firms. A distinctive feature microeconometrics derives from the low...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Abbreviations

Cowles commission approach:

An approach to structural econometric modeling identified with the pioneering work of the Cowles Foundation during the 1940s and 1950s.

Endogenous variable:

A variable whose value is determined within a specified model.

Exogenous:

A variable that is assumed given for the purposes of analysis because its value is determined outside the model of interest.

Reduced form models:

A stochastic model with relationships between endogenous variables on the one hand and all exogenous variables on the other.

Structural model:

A stochastic model with interdependent endogenous and exogenous variables.

Treatment effects:

An effect attributed to a change in the value of some policy variable analogous to a treatment in a clinical trial.

Bibliography

Primary Literature

  1. Albert JH, Chib S (1993) Bayesian Analysis of Binary and Polychotomous Response Data. J Am Stat Assoc 88:669–679

    MathSciNet  MATH  Google Scholar 

  2. Allen RGD, Bowley AL (1935) Family Expenditure. PS King and Son, London

    Google Scholar 

  3. Amemiya T (1985) Advanced Econometrics. Harvard University Press, Cambridge (Mass)

    Google Scholar 

  4. Andrews DWK (2005) Cross-section Regression with Common Shocks. Econometrica 73:1551–1585

    MathSciNet  MATH  Google Scholar 

  5. Angrist JD, Krueger AB (2000) Empirical Strategies in Labor Economics. In: Ashenfelter OC, Card DE (eds) Handbook of Labor Economics, vol 3A. North-Holland, Amsterdam, pp 1277–1397

    Google Scholar 

  6. Angrist JD, Imbens G, Rubin D (1996) Identification of Causal Effects Using Instrumental Variables. J Am Stat Assoc 91:444–455

    MATH  Google Scholar 

  7. Anselin L (2001) Spatial Econometrics. In: Baltagi BH (ed) A Companion to Theoretical Econometrics. Blackwell, Oxford, pp 310–330

    Google Scholar 

  8. Baker M, Melino A (2000) Duration Dependence and Nonparametric Heterogeneity: A Monte Carlo Study. J Econ 96:357–393

    MATH  Google Scholar 

  9. Blundell RW, Powell JL (2001) Endogeneity in Semiparametric Binary Response Models. Rev Econ Stud 71:581–913

    MathSciNet  Google Scholar 

  10. Blundell RW, Smith RJ (1989) Estimation in a Class of Limited Dependent Variable Models. Rev Econ Stud 56:37–58

    MathSciNet  MATH  Google Scholar 

  11. Bunch D (1991) Estimability in the Multinomial Probit Model. Transp Res Methodol 25B(1):1–12

    MathSciNet  Google Scholar 

  12. Cameron AC, Trivedi PK (1998) Regression Analysis for Count Data. Econometric Society Monograph No. 30, Cambridge University Press, Cambridge

    Google Scholar 

  13. Cameron AC, Trivedi PK (2005) Microeconometrics: Methods and Applications. Cambridge University Press, Cambridge

    Google Scholar 

  14. Chesher A (2005) Nonparametric identification under discrete variation. Econometrica 73(5):1525–1550

    MathSciNet  MATH  Google Scholar 

  15. Cosslett SR (1981) Maximum Likelihood Estimator for Choice-Based Samples. Econometrica 49:1289–1316

    MathSciNet  MATH  Google Scholar 

  16. Deb P, Trivedi PK (1997) Demand for Medical Care by the Elderly: A Finite Mixture Approach. J Appl Econ 12:313–326

    Google Scholar 

  17. Deb P, Trivedi PK (2002) The Structure of Demand for Health Care: Latent Class versus Two-part Models. J Health Econ 21:601–625

    Google Scholar 

  18. Deb P, Trivedi PK (2006) Specification and Simulated Likelihood Estimation of a Non-normal Treatment-Outcome Model with Selection: Application to Health Care Utilization. Econ J 9:307–331

    MathSciNet  MATH  Google Scholar 

  19. Diggle PJ, Heagerty P, Liang KY, Zeger SL (1994, 2002) Analysis of Longitudinal Data, 1st and 2nd editions. Oxford University Press, Oxford

    Google Scholar 

  20. Dubin J, McFadden D (1984) An Econometric Analysis of Residential Electric Appliance Holdings and Consumption. Econometrica 55:345–362

    Google Scholar 

  21. Durlauf S, Cohen-Cole E (2004) Social Interactions Models. In: Lempf-Leonard K (ed) Encyclopedia of Social Measurement. Academic Press, New York

    Google Scholar 

  22. Eckstein Z, Wolpin K (1989) The Specification and Estimation of of Dynamic Stochastic Discrete Choice Models: A Survey. J Hum Resour 24:562–598

    Google Scholar 

  23. Engel E (1857) Die Produktions- und Consumptionsverhältnisse des Königreichs Sachsen, Zeitschrift des Statistischen Bureaus des Königlich Sächsischen Ministerium des Innern, 22 November 1857. Reprinted in 1895 as appendix to E. Engel, Die Lebenskosten belgischer Arbeiter-Familien früher und jetzt. Bull Inst Int Stat 9:1–124

    Google Scholar 

  24. Frühwirth-Schnatter S (2006) Finite Mixture and Markov Switching Models. Springer, New York

    Google Scholar 

  25. Geweke J (1992) Evaluating the Accuracy of Sampling-based Approaches to the Calculation of Posterior Moments (with discussion). In: Bernardo J, Berger J, Dawid AP, Smith AFM, (eds) Bayesian Statistics, vol 4. Oxford University Press, Oxford, pp 169–193

    Google Scholar 

  26. Greene WH (2004) The Behavior of the Fixed Effects Estimator in Nonlinear Models. Econ J 7(1):98–119

    MATH  Google Scholar 

  27. Greene WH (2004) Fixed Effects and the Incidental Parameters Problem in the Tobit Model. Econ Rev 23(2):125–148

    MathSciNet  MATH  Google Scholar 

  28. Gouriéroux C, Monfort A (1996) Simulation Based Econometrics Methods. Oxford University Press, New York

    Google Scholar 

  29. Hajivassiliou V, McFadden D, Ruud P (1996) Simulation of multivariate normal rectangle probabilities and their derivatives: Theoretical and computational results. J Econ 72:85–134

    MathSciNet  MATH  Google Scholar 

  30. Heckman JJ (1974) Shadow Prices, Market wages, and Labor Supply. Econometrica 42:679–94

    MATH  Google Scholar 

  31. Heckman JJ (1976) The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for such Models. Ann Econ Soc Meas 5:475–492

    Google Scholar 

  32. Heckman JJ (1978) Dummy Endogenous Variables in a Simultaneous Equations System. Econometrica 46:931–960

    MathSciNet  MATH  Google Scholar 

  33. Heckman JJ (1979) Sample Selection as a Specification Error. Econometrica 47:153–61

    MathSciNet  MATH  Google Scholar 

  34. Heckman JJ (2000) Causal Parameters and Policy Analysis in Economics: A Twentieth Century Perspective. Quart J Econ 115:45–98

    MATH  Google Scholar 

  35. Heckman JJ (2001) Micro Data, Heterogeneity, and the Evaluation of Public Policy: Nobel Lecture. J Political Econ 109(4):673–748

    MathSciNet  Google Scholar 

  36. Heckman JJ, Robb R (1985) Alternative Methods for Evaluating the Impact of Interventions. In: Heckman JJ, Singer B (eds) Longitudinal Analysis of Labor Market Data. Cambridge University Press, Cambridge, UK

    Google Scholar 

  37. Heckman JJ, Singer B (1984) A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models of Duration Data. Econometrica, 52:271–320

    MathSciNet  MATH  Google Scholar 

  38. Heckman JJ, Vytlacil E (2001) Local instrumental variables. In: Hsiao C, Morimue K, Powell JL (eds) Nonlinear Statistical Modeling. In: Proceedings of the Thirteenth International Symposium in Economic Theory and Econometrics: Essays in the Honor of Takeshi Amemiya. Cambridge University Press, New York, pp 1–46

    Google Scholar 

  39. Heckman JJ, Vytlacil E (2005) Structural Equations, Treatment Effects, and Econometric Policy Evaluation. Econometrica 73(3):669–738

    MathSciNet  MATH  Google Scholar 

  40. Holland PW (1986) Statistics of Causal Inference. J Am Stat Assoc 81:945–60

    MathSciNet  MATH  Google Scholar 

  41. Horowitz J (1998) Semiparametric Methods in Econometrics. Springer, New York

    MATH  Google Scholar 

  42. Hotz V, Miller R (1993) Conditional Choice Probabilities and the Estimation of Dynamic Models. Rev Econ Stud 60:497–529

    MathSciNet  MATH  Google Scholar 

  43. Houthakker HS (1957) An International Comparison of Household Expenditure Patterns. Econometrica 25:532–552

    Google Scholar 

  44. Hsiao C (1986, 2003) Analysis of Panel Data, 1st and 2nd edn. Cambridge University Press, Cambridge

    Google Scholar 

  45. Imbens GW, Angrist J (1994) Identification and Estimation of Local Average Treatment Effect. Econometrica 62:467–475

    MATH  Google Scholar 

  46. Imbens GW, Lancaster T (1996) Efficient Estimation and Stratified Sampling. J Econ 74:289–318

    MathSciNet  MATH  Google Scholar 

  47. Keane MP (1992) A Note on Identification in the Multinomial Probit Model. J Bus Econ Stat 10:193–200

    MathSciNet  Google Scholar 

  48. Keane MP (1994) A Computationally Practical Simulation Estimator for Panel Data. Econometrica 62:95–116

    MATH  Google Scholar 

  49. Keane MP (2006) Structural vs. Atheoretical Approaches to Econometrics. Unpublished paper

    Google Scholar 

  50. Keane M, Wolpin K (1994) The Solutions and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpretation: Monte Carlo Evidence. Rev Econ Stat 76:648–672

    Google Scholar 

  51. Koenker R (2005) Quantile Regression. Cambridge University Press, New York

    MATH  Google Scholar 

  52. Koenker R, Bassett G (1978) Regression Quantiles. Econometrica 46:33–50

    MathSciNet  MATH  Google Scholar 

  53. Koop G, Poirier D, Tobias JL (2007) Bayesian Econometric Methods. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  54. Lancaster T (2000) The Incidental Parameter Problem since 1948. J Econ 95:391–413

    MathSciNet  MATH  Google Scholar 

  55. Lancaster T, Imbens GW (1996) Case-Control with Contaminated Controls. J Econ 71:145–160

    MathSciNet  MATH  Google Scholar 

  56. Lee LF (2001) Self-selection. In: Baltagi B (ed) A Companion to Theoretical Econometrics. Blackwell Publishers, Oxford, pp 381–409

    Google Scholar 

  57. Lee LF (2004) Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Econometric Models. Econometrica 72:1899–1926

    MathSciNet  MATH  Google Scholar 

  58. Lee MJ (2002) Micro-Econometrics for Policy, Program and Treatment Effects. Oxford University Press, Oxford

    Google Scholar 

  59. Luce D (1959) Individual Choice Behavior. Wiley, New York

    MATH  Google Scholar 

  60. Ma L, Koenker R (2006) Quantile regression methods for recursive structural equation models. J Econ 134:471–506

    MathSciNet  Google Scholar 

  61. Manski CF (1975) Maximum Score Estimation of the Stochastic Utility Model of Choice. J Econ 3:205–228

    MathSciNet  MATH  Google Scholar 

  62. Manski CF (1995) Identification Problems in the Social Sciences. Harvard University Press, Cambridge

    Google Scholar 

  63. Manski CF (2003) Partial Identification of Probability Distributions. Springer, New York

    MATH  Google Scholar 

  64. Manski CF, Lerman SR (1977) The Estimation of Choice Probabilities from Choice-Based Samples. Econometrica 45:1977–1988

    MathSciNet  MATH  Google Scholar 

  65. Manski CF, McFadden D (1981) Alternative Estimators and Sample Design for Discrete Choice Analysis. In: Manski CF, McFadden D (eds) Structural Analysis of Discrete Data with Econometric Applications. MIT Press, Cambridge, pp 2–50

    Google Scholar 

  66. Manski CF, McFadden D (eds) (1981) Structural Analysis of Discrete Data with Econometric Applications. MIT Press, Cambridge

    MATH  Google Scholar 

  67. McCulloch R, Rossi P (2000) Bayesian analysis of the multinomial probit model. In: Mariano R, Schuermann T, Weeks M (eds) Simulation-Based Inference in Econometrics. Cambridge University Press, New York

    Google Scholar 

  68. McFadden D (1973) Conditional Logit Analysis of Qualitative Choice Behavior. In: Zarembka P (ed) Frontiers of Econometrics. Academic Press, New York

    Google Scholar 

  69. McFadden D (1976) Quantal Choice Analysis: A Survey. Ann Econ Soc Meas 5(4):363–390

    Google Scholar 

  70. McFadden D (1978) Modelling the Choice of Residential Location. In: Karlquist A et al (eds) Spatial Interaction Theory and Residential Location. North Holland, Amsterdam, New York

    Google Scholar 

  71. McFadden D (1981) Econometric Models of Probabilistic Choice. In: Manski CF, McFadden D (eds) Structural Analysis of Discrete Data with Economic Applications. MIT Press, Cambridge, pp 198–272

    Google Scholar 

  72. McFadden D (1984) Econometric Analysis of Qualitative Response Models. In: Griliches Z, Intriligator M (eds) Handbook of Econometrics, vol 2. North Holland, Amsterdam

    Google Scholar 

  73. McFadden D (2001) Economic Choices. Am Econ Rev 91(3):351–78

    Google Scholar 

  74. McFadden D, Ruud PA (1994) Estimation by Simulation. Rev Econ Stat 76:591–608

    Google Scholar 

  75. McFadden D, Train K (2000) Mixed MNL Models of Discrete Response. J Appl Econ 15:447–470

    Google Scholar 

  76. Maddala GS (1983) Limited Dependent and Qualitative Variables in Economterics. Cambridge University Press, Cambridge

    Google Scholar 

  77. Marschak J, Andrews WH (1944) Random Simultaneous Equations and the Theory of Production. Econometrica 12:143–205

    MathSciNet  MATH  Google Scholar 

  78. Miller R (1997) Estimating Models of Dynamic Optimization with Microeconomic Data. In: Pesaran HH, Schmidt P (eds) Handbook of Applied Econometrics, vol II. Blackwell Publishers, Oxford

    Google Scholar 

  79. Prais SJ, Houthakker HS (1955) Analysis of Family Budgets. Cambridge University Press, Cambridge

    Google Scholar 

  80. Pudney S (1989) Modeling Individual Choice: The Econometrics of Corners. Basil, Kinks and Holes. Blackwell, New York

    Google Scholar 

  81. Rust J (1987) Optimal replacement of gmc bus engines: An empirical model of Harold Zurcher. Econometrica 55:993–1033

    Google Scholar 

  82. Rust J (1994) Estimation of dynamic structural models, problems and prospects: Discrete decision processes. In: Sims C (ed) Advances in Econometrics: Sixth World Congress, vol II. Cambridge University Press, New York, pp 5–33

    Google Scholar 

  83. Rust J (1994) Structural Estimation of Markov Decision Processes. In: Engle RF, McFadden D (eds) Handbook of Econometrics, vol 4. North-Holland, Amsterdam, pp 3081–3143

    Google Scholar 

  84. Rust J (1997) Using Randomization to Break the Curse of Dimensionality. Econometrica 65:487–516

    MathSciNet  MATH  Google Scholar 

  85. Rust J, Phelan C (1997) How Social Security and Medicare Affect Treatment Behavior in a World of Incomplete Markets. Econometrica 65(4):781–842

    MATH  Google Scholar 

  86. Stone R (1953) The Measurement of Consumers’ Expenditure and Behavior in the United Kingdom, vol 1. Cambridge University Press, Cambridge, pp 1920–1938

    Google Scholar 

  87. Thurstone L (1927) A Law of Comparative Judgment. Psychol Rev 34:273–286

    Google Scholar 

  88. Tobin J (1958) Estimation of Relationships for Limited Dependent Variables. Econometrica 26:24–36

    MathSciNet  MATH  Google Scholar 

  89. Train KE (2003) Discrete Choice Methods with Simulation. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  90. Walker J, Ben-Akiva M (2002) Generalized random utility model. Math Soc Sci 43:303–343

    MathSciNet  MATH  Google Scholar 

Books and Reviews

  1. Arellano M (2003) Panel Data Econometrics. Oxford University Press, Oxord, UK

    MATH  Google Scholar 

  2. Blundell R, Powell JL (2003) Endogeneity in Nonparametric and Semiparametric Regression Models. In: Dewatripont M, Hansen LP, Turnovsky SJ (eds) Advances in Economics and Econonometrics: Theory and Applications, Eighth World Congress, vol II. Cambridge University Press, Cambridge

    Google Scholar 

  3. Deaton A (1997) The Analysis of Household Surveys: A Microeconometric Approach to Development Policy. Johns Hopkins, Baltimore

    Google Scholar 

  4. Greene WH (2007) Econometric Analysis, 6th edn. Macmillan, New York

    Google Scholar 

  5. Hensher DA, Rose J, Greene W (2005) Applied Choice Analysis: A Primer. Cambridge University Press, New York

    MATH  Google Scholar 

  6. Lancaster T (1990) The Econometric Analysis of Transitional Data. Cambridge University Press, New York

    Google Scholar 

  7. Lee MJ (2002) Panel Data Econometrics: Methods-of-Moments and Limited Dependent Variables. Academic Press, San Diego

    Google Scholar 

  8. Louviere J, Hensher D, Swait J (2000) Stated Choice Methods: Analysis and Applications. Cambridge University Press, New York

    MATH  Google Scholar 

  9. Wooldridge JM (2002) Econometric Analysis of Cross Section and Panel Data. MIT Press, Cambridge

    MATH  Google Scholar 

  10. Yatchew A (2003) Semiparametric Regression for the Applied Econometrician. Cambridge University Press, Cambridge

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Economics, Indiana University, Bloomington, USA

    Pravin K. Trivedi

Authors
  1. Pravin K. Trivedi
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag

About this entry

Cite this entry

Trivedi, P.K. (2009). Microeconometrics. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_330

Download citation

Publish with us

Policies and ethics

Search

Navigation