Conditional Distribution Specification Testing Based on Data-Dependent Partitions

Miguel A. Delgado and Julius Vainora

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: This article introduces a Pearson-type goodness-of-fit test for the parametric specification of conditional distribution models with continuous responses. Under correct specification, the Rosenblatt transform is uniformly distributed on [0, 1] conditionally on the explanatory variables. The test exploits this characterization by cross-classifying the transformed observations and the explanatory variables according to partitions of [0, 1] and their support, respectively. The resulting Pearson statistic has a chi-squared limiting distribution with known degrees of freedom and detects local alternatives converging to the null at the n−1/2 rate. These results remain valid for the class of data-dependent partitions considered. Monte Carlo simulations indicate accurate size control and favorable power relative to existing bootstrap-based tests, particularly in higher-dimensional settings.

Keywords: Conditional Distribution; Specification Testing; Rosenblatt Transform; Contingency Tables; Pearson Test (search for similar items in EconPapers)
JEL-codes: C12 C52 (search for similar items in EconPapers)
Date: 2026-09-08
Note: jv429
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econ.cam.ac.uk/sites/default/files/pub ... pe-pdfs/cwpe2440.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2440

Access Statistics for this paper

More papers in Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge
Bibliographic data for series maintained by Jake Dyer ().