My work implies a lot of econometrics, and I had a good formation about it. Nevertheless, I am regularly faced with some semi or non parametric techniques (for instance I had to use quantile regressions, partial estimation, or nonparametric estimation of whole distribution estimations), and I had no courses about it, neither in statistics or econometrics.

So my question is which book would you recommend for someone to have both a good overview and a logical presentation of this domain ? I would like to have a good background for these techniques. I precise that I have a graduate level in econometrics and applied statistics, so some maths are fine, but with some intuition is very good too !

Thanks in advance


I would recommend two books if you are interested in smoothing techniques, especially in density estimation and regression (rather than in tests that don’t require classical normality assumptions, which are often based on ranks rather than the raw data):

  1. Nonparametric and Semiparametric Models by Härdle, Müller, Sperlich, and Werwatz
  2. Li and Racine's Nonparametric Econometrics: Theory and Practice

The first is much slimmer, a bit more introductory, with lots of examples and illustrations. It covers histograms, nonparametric density estimation, nonparametric regression, semiparametric and generalized regression models, single index models, generalized partial linear models, additive models and their marginal effects and generalized additive models.

The second tome covers nonparametric kernel methods, semiparametric methods, consistent model specification tests, nonparametric nearest neighbor and series methods, and some time series, simultaneous equations, and panel data models at the end. There is not too much about QR in this book. Koenker's QR would make a nice supplement.

It is also worth mentioning some other books. While comprehensive and worth reading later, I found Pagan and Ullah to be a difficult first introductions to this material. I have heard good things about Yatchew's Semiparametric Regression book, but I have not read it myself.


There is a recent title by Henderson/Parmeter: Applied Nonparametric Econometrics. As the name suggests, its focus is more applied than that of Li and Racine, although it does devote quite some attention to theoretical underpinnings, too.

Compared to the titles mentioned by @Dimitriy, it (unsurprisingly given its more recent date) surveys many of the recent developments in for example the area of nonparametric instrumental variables or panel data estimation.

What I additionally like a lot (probably in line with many CVers) is its usage of R as well as...cross-validation ;-).


The online StatSoft textbook is a good place to start.

  • $\begingroup$ Welcome to the site. Please don't sign your posts. Your username & a link to your userpage are automatically added to all your posts. Since you are new here, you may want to take our tour, which contains information for new users. (I'm not the downvoter, btw.) $\endgroup$ – gung - Reinstate Monica Sep 11 '14 at 13:34
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    $\begingroup$ Welcome to CrossValidated! It does look like a useful resource, but could you add a few sentences summarizing the contents or explaining why you like it. $\endgroup$ – Matt Krause Sep 11 '14 at 13:36

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