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This chapter provides an overview of the methodological and practical issues that arise when estimating causal relationships that are of interest to labor economists. The subject matter includes identification, data collection, and measurement problems. Four identification strategies are discussed, and five empirical examples - the effects of schooling, unions, immigration, military
service, and class size - illustrate the methodological points. In discussing each example, we adopt an experimentalist perspective that emphasizes the distinction between variables that have causal effects, control variables, and outcome variables. The chapter also discusses secondary datasets, primary data collection strategies, and administrative data. The section on measurement issues
focuses on recent empirical examples, presents a summary of empirical findings on the reliability of key labor market data, and briefly reviews the role of survey sampling weights and the allocation of missing values in empirical research.
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