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AbstractThe second edition of this acclaimed graduate text provides a unified treatment of the analysis of two kinds of data structures used in contemporary econometric research: cross section data and panel data. The book covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particularly methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models, multinomial and ordered choice models, Tobit models and two-part extensions, models for count data, various censored and missing data schemes, causal (or treatment) effect estimation, and duration analysis. Control function and correlated random effects approaches are expanded to allow estimation of complicated models in the presence of endogeneity and heterogeneity. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster sampling problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage of inverse probability weighting; a more complete framework for estimating treatment effects with assumptions concerning the intervention and different data structures, including panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain “obvious” procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights. Suggested CitationHandle: RePEc:mtp:titles:0262232588 Download full text from publisherTo our knowledge, this item is not available for download. To find whether it is available, there are three options: Other versions of this item:
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Provided here are the datasets that were used to produce the output in the book Econometric Analysis of Cross Section and Panel Data by Jeffrey Wooldridge. You can download the datasets from within Stata using the net command. At the Stata prompt, type . net from http://www.stata.com/data/jwooldridge/
. net describe eacsap
. net get eacsap
This will download all files associated with the book to your current directory. If you do not have an Internet connection from within Stata, you can download one of the following files: We suggest you create a new directory and copy the materials there. The book sometimes refers to filenames using capital letters. Due to differences across operating systems, the filenames stored here are all lowercase. In addition to the methods above of obtaining all files associated with the book at once, it is possible to use any individual file from within Stata. Simply click on a file in the list of datasets below to download it to a local folder on your machine, or from within Stata, type . use http://www.stata.com/data/jwooldridge/eacsap/filename where filename is the name of the dataset in the book, typed as all lowercase without the extension. For example, on page 59, the file MROZ.RAW is discussed. For ease of use, we have made this data available in Stata format as mroz.dta. To load the dataset into Stata, type . use http://www.stata.com/data/jwooldridge/eacsap/mroz Many users find it convenient to define a macro to the path so that files can be obtained with less typing: . global JW http://www.stata.com/data/jwooldridge/eacsap
. use $JW/mroz
Here is a list of the datasets:
ReferencesBlackburn, M. and D. Neumark. 1992.Unobserved ability, efficiency wages, and interindustry wage differentials. Quarterly Journal of Economics 107: 1421–1436.Card, D. 1995.Using geographic variation in college proximity to estimate the return to schooling. In Aspects of Labour Market Behavior: Essays in Honour of John Vanderkamp, ed. L. N. Christophides, E. K. Grant, and R. Swidinsky, 201–222. Toronto: University of Toronto Press.Chung, C.-F., P. Schmidt, and A. D. Witte. 1991.Survival analysis: A survey. Journal of Quantitative Criminology 7: 59–98.Cornwell, C. and D. Trumball. 1994.Estimating the economic model of crime with panel data. Review of Economics and Statistics 76: 360–366.Grogger, J. 1991.Certainty vs. severity of punishment. Economic Inquiry 29: 297–309.Holzer, H., R. Block, M. Cheatham, and J. Knott. 1993.Are training subsidies effective? The Michigan experience. Industrial and Labor Review 46:625–636.Keane, M. P. and K. I. Wolpin. 1997.The career decisions of young men. Journal of Political Economy 105: 473–522.Kiel, K. A. and K. T. McClain. 1995.House prices during siting decision stages: The case of an incinerator from rumor through operation. Journal of Environmental Economics and Management 28: 241–255.Levitt, S. D. 1996.The effect of prison population size on crime rates: evidence from prison overcrowding legislation. Quarterly Journal of Economics 111: 319–351.Meyer, B. D., W. K. Viscusi, and D. L. Durbin. 1995.Workers' compensation and injury duration: evidence from a natural experiment. American Economic Review 85: 322–340.Mroz, T. A. 1987.The sensitivity of an empirical model of married women's hours to work economic and statistical assumptions. Econometrica 55: 765–799.Papke, L. E. 1994.Tax policy and urban development: Evidence from the Indiana enterprise zone program. Journal of Public Economics 54: 37-49.——. 1998.How are participants directing their participant-directed individual account pension plans? American Economic Review 88: 212–216.Romer, D. 1993.Openness and inflation: Theory and evidence. Quarterly Journal of Economics 108: 869–903.Vella, F. and M. Verbeek. 1998.Whose wages do unions raise? A dynamic model of unionism and wage rate determination for young men. Journal of Applied Econometrics 13: 163–183. What is cross section data in econometrics?Cross-sectional data, or a cross section of a study population, in statistics and econometrics, is a type of data collected by observing many subjects (such as individuals, firms, countries, or regions) at the one point or period of time. The analysis might also have no regard to differences in time.
What is cross section and panel data?Cross sectional data means that we have data from many units, at one point in time. Time series data means that we have data from one unit, over many points in time. Panel data (or time series cross section) means that we have data from many units, over many points in time.
What is panel data econometrics?Panel data consist of repeated observations over time on the same set of cross-sectional units. These units can be individuals, firms, schools,cities, or any collection of units one can follow over time.
How do you analyze panel data?Panel (data) analysis is a statistical method, widely used in social science, epidemiology, and econometrics to analyze two-dimensional (typically cross sectional and longitudinal) panel data. The data are usually collected over time and over the same individuals and then a regression is run over these two dimensions.
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Wooldridge econometric analysis of cross section and panel data
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