Nonparametric estimation of finite measures

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract. The aim of this paper is to provide simple nonparametric methods to estimate finitemixture models from data with repeated measurements. Three measurements suffice for the mixture to be fully identified and so our approach can be used even with very short panel data. We provide distribution theory for estimators of the mixing proportions and the mixture distributions, and various functionals thereof. We also discuss inference on the number of components. These estimators are found to perform well in a series of Monte Carlo exercises. We apply our techniques to document heterogeneity in log annual earnings using PSID data spanning the period 1969-1998. Terms of use: Documents in EconStor may

Partial identification of finite mixtures in econometric models

“…Finally, one could combine our exclusion restriction with others to achieve tighter identification. The repeated measurement literature is a case in point: the results of Bonhomme, Jochmans, and Robin (2012), for instance, can be integrated with ours.…”

“…Kasahara and Shimotsu (2009) built on similar ideas to identify finite mixtures of persistent types in dynamic discrete choice models. Bonhomme, Jochmans, and Robin (2012) showed point identification when T ≥ 3 under a rank condition and they proposed a convenient estimation method. Molinari (2008) gave general partial identification results for the distribution of a misclassified categorical variable.…”

Economics at the FTC: Fraud, Mergers and Exclusion

“…19 In statistics, see Hall and Zhou (2003), Hall et al (2005), and Allman et al (2009). In economics, see Adams (2015), Bonhomme et al (2014), and Kasahara and Shimotsu (2014). 20 This assumption rules out autocorrelation in refund rates conditional on type.…”

Theoretical grounding for estimation in conditional independence multivariate finite mixture models

“…Here, we assume m is known. For recent work that addresses the esti-mation of m, along with a different approach to the estimation of the model parameters than the one outlined here, see Bonhomme et al (2014) and Kasahara and Shimotsu (2014).…”