Corradi, Valentina and Swanson, Norman R. (2007) Nonparametric bootstrap procedures for predictive inference based on recursive estimation schemes. International Economic Review, Vol.48 (No.1). pp. 67-109. doi:10.1111/j.1468-2354.2007.00418.x ISSN 0020-6598.

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Abstract

We introduce block bootstrap techniques that are (first order) valid in recursive estimation frameworks. Thereafter, we present two examples where predictive accuracy tests are made operational using our new bootstrap procedures. In one application, we outline a consistent test for out-of-sample nonlinear Granger causality, and in the other we outline a test for selecting among multiple alternative forecasting models, all of which are possibly misspecified. In a Monte Carlo investigation, we compare the finite sample properties of our block bootstrap procedures with the parametric bootstrap due to Kilian (Journal of Applied Econometrics 14 (1999), 491-510), within the context of encompassing and predictive accuracy tests. In the empirical illustration, it is found that unemployment has nonlinear marginal predictive content for inflation.

Item Type:	Journal Article
Subjects:	H Social Sciences > HC Economic History and Conditions
Divisions:	Faculty of Social Sciences > Economics
Journal or Publication Title:	International Economic Review
Publisher:	Wiley-Blackwell Publishing, Inc.
ISSN:	0020-6598
Official Date:	February 2007
Dates:	Date Event February 2007 Published
Volume:	Vol.48
Number:	No.1
Number of Pages:	43
Page Range:	pp. 67-109
DOI:	10.1111/j.1468-2354.2007.00418.x
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access

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