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Empirical economic research. An introduction. - MaRDI portal

Empirical economic research. An introduction. (Q1006539)

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scientific article; zbMATH DE number 5532710
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English
Empirical economic research. An introduction.
scientific article; zbMATH DE number 5532710

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    Empirical economic research. An introduction. (English)
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    25 March 2009
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    During the last two decades there was an increasing interest in developing and applying empirical methods which are capable to isolate and to evaluate the effects of a (policy) measure on a person or a group of persons from what would have happened to them without this measure. And the whole book is written along this guiding principle. In this sense the authors open a fresh view on how empirical research in economics (and related disciplines) could be conducted and how to use methods which allow a distinction between treated and untreated effects to gain reliable information about the effectiveness of various policy measures or other treatments. These most recent techniques in applied (economic) research are completely new as a textbook, and the authors provide a comprehensive overview as well as introduction into these new research methods. The textbook is written for students as well as applied economists and social scientists who are interested in theoretical and empirical problems as well. It should help to understand as well as to judge the results and the methods used in applied economic research. The reader should be familiar with basic mathematical and statistical tools. Nevertheless, in the fist two chapters a comprehensive overview of these tools is given for those who want a quick refreshing. The book is a successful combination of applied statistics and advanced econometric techniques. The genuine part of the book starts at chapter four which gives an introduction into the analysis of causal effects, distinguishing between experimental and non-experimental designs of a study. The next chapter presents the linear regression model followed by issues of model specification in chapter six. The following two chapters are devoted to the problem of heteroskedasticity and the GLS model as well as to the problem of omitted variables and unobserved heterogeneity. This last chapter also contains a subsection where models for panel data are briefly introduced. Exercises are given at the end of each chapter. Furthermore, the authors use the concept of ``key messages'' several times to summarize the most important results discussed in the chapters and which should have been understood by the reader.
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    forecasting
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    linear regression
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    unobserved heteroskedasticity
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    causal analysis
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    identification
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    model evaluation
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    counterfactual situation
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