文档介绍：A Bootstrap Test for Causality with Endogenous Lag Length Choice: Theory and Application in Finance
Abdulnasser Hatemi-J
Department of Business and Management Studies, the University of Skovde, Sweden,
and the University of Kurdistan-Hawler, Iraqi Kurdistan
E-mail: -******@
Abstract
Granger causality tests are increasingly applied when time series data is used in empirical research, especially in business, economics and finance. Several new tests have been developed in the literature that can deal with different data generating processes. In all existing theoretical papers it is assumed that the lag length is known. However, in applied research the lag length is chosen before testing for causality. This paper suggests endogenizing the lag length choice. It also provides and evaluates a bootstrap method when the lag length is determined endogenously. The suggested bootstrap test is also robust to ARCH effects that usually characterize the financial data. This test is applied to testing the causal relationship between the US and the UK financial markets. The financial economic implications of the empirical findings are explained in the paper.
Key words: Causality, VAR model, Stability, Endogenous Lag, ARCH, Leverages
JEL classification: C32, C15, G11
Running title: A Bootstrap Test for Causality with Endogenous Lag Length Choice
Introduction
Tests for causality in Granger’s (1969) sense are increasingly conducted in applied research when time series data is used. This is especially the case in empirical studies in the fields of economics and finance. Several new test methods have been put forward in the literature for testing causality that can deal with different data generating processes; see among others Granger (1988), Toda and Yamamoto (1995) and Hacker and Hatemi-J (2006). mon factor in all existing papers is that the lag length is assumed to be known, which might be too restrictive. It is mon practice in the empirical litera