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Dr. Maarten van Kampen


Room 7
+49 231 755 - 3869
Fakultät Statistik
Technische Universität Dortmund
44221 Dortmund

Research interests

Econometrics, Time Series Analysis, Copulas


Working Papers

  • Van Kampen, M. (2013), "The nonparametric IV regression model with an Archimedean dependence structure", working paper
  • Van Kampen, M. and Wied, D. (2013), "A nonparametric constancy test for copulas under mixing conditions", SFB 823 Discussion Paper 36/2010, Fakultät Statistik, Universität Dortmund, Version (2013).


  • Wied, D., Dehling, H., van Kampen, M. and Vogel, D. (forthcoming), "A fluctuation test for constant Spearman's rho", Computational Statistics and Data Analysis, link. [SFB 823 Discussion Paper 16/2011, pdf].

Abstract: We propose a CUSUM type test for constant correlation that goes beyond a previously suggested correlation constancy test by considering Spearman's rho in arbitrary dimensions. By using copula-based expressions, we simultaneously extend a previously suggested copula constancy test. We calculate the asymptotic null distribution using an invariance principle for the sequential empirical copula process. The limit distribution is free of nuisance parameters and critical values can be obtained without bootstrap techniques. We give a local power result and analyze the test's behavior in small samples.

  • Bücker, M., van Kampen, M. and Krämer, W. (2013), Reject inference in consumer credit scoring with nonignorable missing data, Journal of Banking and Finance 37, 1040-1045, link. [SFB 823 Discussion Paper 01/2011, pdf].

Abstract: We generalize an empirical likelihood approach to deal with missing data to a model of consumer credit scoring. An application to recent consumer credit data shows that our procedure yields parameter estimates which are significantly different (both statistically and economically) from the case where customers who were refused credit are ignored. This has obvious implications for commercial banks as it shows that refused customers should not be ignored when developing scorecards for the retail business. We also show that forecasts of defaults derived from the method proposed in this paper improve upon the standard ones when refused customers do not enter the estimation data set.

  • Krämer, W. and van Kampen, M. (2011), A simple nonparametric test for structural change in joint tail probabilities, Economics Letters 110, 245 - 247, link. [SFB 823 Discussion Paper 04/2009].

Abstract: We propose a new test against a change in the probability of multivariate tail events. The test is based on partial sums of a suitably defined indicator function and detects multiple changes in joint tail probabilities better than a previously suggested competitor.



  • Lineare Modelle (SS 2013, TUD)
  • Lineare Modelle (SS 2012, TUD)
  • Tutorial Ökonometrie (WS 2011/2012, TUD)
  • Tutorial Econometrics I (WS 2009/2010, RGS Econ)