Comments on: Panel data analysis—advantages and challenges

Autor: Marc Nerlove
Rok vydání: 2007
Předmět:
Zdroj: TEST. 16:42-46
ISSN: 1863-8260
1133-0686
DOI: 10.1007/s11749-007-0052-z
Popis: In most applications of statistical analysis in the sciences, the process by which the observed data are generated is transparent having usually been determined by the investigator by design. In contrast, in many applications in the social sciences, especially in economics, the mechanism by which the data are generated is opaque. In such circumstances, estimation of the parameters of the statistical model of the process and testing specific hypotheses about it are only half the problem of inference. My own view is that understanding the process by which the observations at hand are generated is of equal importance. Were the data, for example, obtained from a sample of firms selected by stratified random sampling from a census of all firms in the United States in 2000? Were they obtained from regulatory activity? In the case of time series, the data are almost always “fabricated,” in one way or another, by aggregation, interpolation, or extrapolation, or by all three. The nature of the sampling frame or the way in which the data are fabricated must be part of the model specification on which parametric inference or hypothesis testing is based. In his exemplary survey of panel data analysis, Cheng Hsiao focuses primarily on problems of estimation and inference from a parametrically well-specified model of how the observed data were generated. In my commentary, I would like briefly to address some of the issues associated with the other half of the problem. Since such a discussion is data specific, it is possible only to deal with the issues in the context of a specific, although possibly abstract, example. Suppose a longitudinal household survey in which the same households are questioned over time about their actions in, say, a number of consecutive months or years and, initially, about various
Databáze: OpenAIRE
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