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About sense and nonsense of non- and semiparametric analysis in applied econometrics


  • Sperlich, Stefan


The discussion about the use of semiparametric analysis in empirical research in economics is as old as the methods are. This article can certainly not be more than a small contribution to the polemic question how useful is non- or semiparametric statistics for applied econometrics. The goal is twofold: to illustrate that the use of these methods have their justification in economics, and to highlight what might be reasons for the lack of its application in empirical research. We do not give a survey of available methods and procedures. Since we discuss the question of the use of non- or semiparametric methods (in economics) in general, we believe that it is fair enough to stick to kernel smoothing methods. It might be that we will face some deficiencies that are more typical in the context of kernel smoothing than it is for other methods. However, the different smoothing methods share mainly the same advantages and disadvantages we will discuss. Even though many points of this discussion hold also true for other research fields, all our examples are either based on economic data sets or concentrate on models that are typically motivated from economic or econometric theory.

Suggested Citation

  • Sperlich, Stefan, 2003. "About sense and nonsense of non- and semiparametric analysis in applied econometrics," SFB 373 Discussion Papers 2003,36, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  • Handle: RePEc:zbw:sfb373:200336

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