Abstract
‘Longitudinal data’ (or ‘panel data’) refers to data-sets that contain time series observations of a number of individuals. In other words, it provides multiple observations for each individual in the sample. Compared with cross-sectional data, in which observations for a number of individuals are available only for a given time, or time-series data, in which a single entity is observed over time, panel data have the obvious advantages of more degrees of freedom and less collinearity among explanatory variables, and so provide the possibility of obtaining more accurate parameter estimates. More importantly, by blending inter-individual differences with intra-individual dynamics, panel data allow the investigation of more complicated behavioural hypotheses than those that can be addressed using cross-sectional or time-series data.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Bibliography
Ahn, S.C. and Schmidt, P. 1995. Efficient estimation of models for dynamic panel data. Journal of Econometrics 68, 5–27.
Anderson, T.W. and Hsiao, C. 1981. Estimation of dynamic models with error components. Journal of the American Statistical Association 76, 598–606.
Anderson, T.W. and Hsiao, C. 1982. Formulation and estimation of dynamic models using panel data. Journal of Econometrics 18, 47–82.
Anselin, L. 1988. Spatial Econometrics: Methods and Models. Boston: Kluwer.
Anselin, L. and Griffith, D.A. 1988. Do spatial effects really matter in regression analysis? Papers of the Regional Science Association 65, 11–34.
Anselin, L., Le Gallo, J. and Jayet, H. 2006. Spatial panel econometrics. In The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice. 3rd edn, ed. L. Matyas and P. Sevestre. Dordrecht: Kluwer.
Arellano, M. 2001. Discrete choice with panel data. Working Paper No. 0101. Madrid: CEMFI.
Arellano, M. 2003. Panel Data Econometrics. Oxford: Oxford University Press.
Arellano, M. and Bond, S.R. 1991. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies 58, 277–97.
Arellano, M. and Bover, O. 1995. Another look at the instrumental variable estimation of error-components models. Journal of Econometrics 68, 29–51.
Bai, J. and Ng, S. 2002. Determining the number of factors in approximate factor models. Econometrica 70, 91–121.
Balestra, P. and Nerlove, M. 1966. Pooling cross-section and time series data in the estimation of a dynamic model: the demand for natural gas. Econometrica 34, 585–612.
Baltagi, B.H. 2001. Econometric Analysis of Panel Data. 2nd edn. New York: Wiley.
Baltagi, B.H. and Kao, C. 2000. Nonstationary panels, cointegration in panels and dynamic panel: a survey. In Nonstationary Panels Panel Cointegration, and Dynamic Panels, ed. B. Baltagi. Amsterdam: JAI Press.
Ben-Porath, Y. 1973. Labor force participation rates and the supply of labor. Journal of Political Economy 81, 697–704.
Bhargava, A. and Sargan, J.D. 1983. Estimating dynamic random effects models from panel data covering short time periods. Econometrica 51, 1635–59.
Binder, M., Hsiao, C. and Pesaran, M.H. 2005. Estimation and inference in short panel vector autoregressions with unit roots and cointegration. Econometric Theory 21, 795–837.
Breitung, J. and Pesaran, M.H. 2006. Unit roots and cointegration in panels. In The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice. 3rd edn, ed. L. Matyas and P. Sevestre. Dordrecht: Kluwer.
Butler, J.S. and Moffitt, R. 1982. A computationally efficient quadrature procedure for the one factor multinomial probit model. Econometrica 50, 761–1.
Carro, J.M. 2006. Estimating dynamic panel data discrete choice models with fixed effects. Journal of Econometrics (forthcoming).
Chamberlain, G. 1980. Analysis of covariance with qualitative data. Review of Economic Studies 47, 225–38.
Chamberlain, G. 1984. Panel data. In Handbook of Econometrics, vol. 2, ed. Z. Griliches and M. Intriligato. Amsterdam: North-Holland.
Chamberlain, G. 1993. Feedback in panel data models. Mimeo, Department of Economics, Harvard University.
Chang, Y. 2002. Nonlinear IV unit root tests in panels with cross-sectional dependency. Journal of Econometrics 110, 261–92.
Choi, I. 2001. Unit root tests for panel data. Journal of International Money and Finance 20, 249–72.
Choi, I. 2006. Nonstationary panels. In Palgrave Handbooks of Econometrics, vol. 1, ed. T.C. Mills and K.D. Patterson. Basingstoke: Palgrave Macmillan.
Cox, D.R. and Reid, N. 1987. Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society, B 49, 1–39.
Dickey, D.A. and Fuller, W.A. 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74, 427–31.
Granger, C.W.J. 1990. Aggregation of time-series variables: a survey. In Disaggregation in Econometric Modeling, ed. T. Barker and M.H. Pesaran. London: Routledge.
Griliches, Z. 1967. Distributed lags: a survey. Econometrica 35, 16–19.
Griliches, Z. and Hausman, J.A. 1986. Errors-in-variables in panel data. Journal of Econometrics 31, 93–118.
Hausman, J.A. 1978. Specification tests in econometrics. Econometrica 46, 1251–71.
Heckman, J.J. 1981. Statistical models for discrete panel data. In Structural Analysis of Discrete Data with Econometric Applications, éd. CF. Manski and D. McFadden. Cambridge, MA: MIT Press.
Honoré, B. 1992. Trimmed LAD and least squares estimation of truncated and censored regression models with fixed effects. Econometrica 60, 533–67.
Honoré, B. and Kyriazidou, E. 2000. Panel data discrete choice models with lagged dependent variables. Econometrica 68, 839–74.
Horowitz, J.L. 1992. A smoothed maximum score estimator for the binary response model. Econometrica 60, 505–31.
Hsiao, C. 1996. Random coefficient models. In The Econometrics of Panel Data. 2nd edn, ed. L. Matyas and P. Sevestre. Dordrecht: Kluwer.
Hsiao, C. 2003. Analysis of Panel Data, 2nd edn. Cambridge: Cambridge University Press.
Hsiao, C. and Pesaran, M.H. 2006. Random coefficients models. In The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice. 3rd edn, ed. L. Matyas and P. Sevestre. Dordrecht: Kluwer.
Hsiao, C, Pesaran, M.H. and Tahmiscioglu, A.K. 2002. Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods. Journal of Econometrics 109, 107–50.
Hsiao, C, Shen, Y. and Fujiki, H. 2005. Aggregate vs disaggregate data analysis — a paradox in the estimation of money demand function of Japan under the low interest rate policy. Journal of Applied Econometrics 20, 579–601.
Hsiao, C, Shen, Y., Wang, B. and Weeks, G. 2005. Evaluating the effectiveness of Washington State repeated job search services on the employment rate of prime-age female welfare recipients. Mimeo, University of Southern California.
Hsiao, C. and Tahmiscioglu, A.K. 2005. Estimation of dynamic panel data models with both individual and time specific effects. Mimeo.
Im, K., Pesaran, M.H. and Shin, Y 2003. Testing for unit roots in heterogeneous panels. Journal of Econometrics 115, 53–74.
Kao, C. 1999. Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics 90, 1–44.
Kyriazidou, E. 1997. Estimation of a panel data sample selection model. Econometrica 65, 1335–64.
Lee, M.J. 1999. A root-N-consistent semiparametric estimator for related effects binary response panel data. Econometrica 67, 427–33.
Levin, A., Lin, C. and Chu, J. 2002. Unit root tests in panel data: asymptotic and finite sample properties. Journal of Econometrics 108, 21–24.
Lewbel, A. 1994. Aggregation and simple dynamics. American Economic Review 84, 905–18.
MaCurdy, T.E. 1981. An empirical model of labor supply in a life cycle setting. Journal of Political Economy 89, 1059–85.
Manski, CF. 1987. Semiparametric analysis of random effects linear models from binary panel data. Econometrica 55, 357–62.
Moon, H.R. and Perron, B. 2004. Testing for a unit root in panels with dynamic factors. Journal of Econometrics 122, 81–126.
Neyman, J. and Scott, E.L. 1948. Consistent estimates based on partially consistent observations. Econometrica 16, 1–32.
Nickeil, S. 1981. Biases in dynamic models with fixed effects. Econometrica 49, 1399–416.
Pakes, A. and Griliches, Z. 1984. Estimating distributed lags in short panels with an application to the specification of depreciation patterns and capital stock constructs. Review of Economic Studies 51, 243–62.
Pesaran, M.H. 2005. A simple panel unit root test in the presence of cross-section dependence. DAE Working Paper No. 0346, Cambridge University.
Pesaran, M.H. 2006. Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 967–1012.
Phillips, P.C. 1986. Understanding spurious regressions in econometrics. Journal of Econometrics 33, 311–10.
Phillips, P.C. and Moon, H.R 1999. Linear regression limit theory for nonstationary panel data. Econometrica 67, 1057–111.
Rao, CR. 1973. Linear Statistical Inference and Its Applications, 2nd edn. NewYork: Wiley.
Wansbeek, T.J. and Koning, R.H. 1989. Measurement error and panel data. Statistica Neerlandica 45, 85–92.
Zilak, J.P. 1997. Efficient estimation with panel data when instruments are predetermined: an empirical comparison of moment-condition estimators. Journal of Business and Economic Statistics 15, 419–31.
Editor information
Editors and Affiliations
Copyright information
© 2010 Palgrave Macmillan, a division of Macmillan Publishers Limited
About this chapter
Cite this chapter
Hsiao, C. (2010). Longitudinal Data Analysis. In: Durlauf, S.N., Blume, L.E. (eds) Microeconometrics. The New Palgrave Economics Collection. Palgrave Macmillan, London. https://doi.org/10.1057/9780230280816_14
Download citation
DOI: https://doi.org/10.1057/9780230280816_14
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-0-230-23881-7
Online ISBN: 978-0-230-28081-6
eBook Packages: Palgrave Media & Culture CollectionLiterature, Cultural and Media Studies (R0)