A Bootstrap Test for Causality with Endogenous Lag Length Choice - theory and application in finance
AbstractGranger causality tests have become among the most popular empirical applications with time series data. 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 a priori. However, in applied research the lag length has to be selected before testing for causality. This paper suggests that in investigating the effectiveness of various Granger causality testing methodologies, including those using bootstrapping, the lag length choice should be endogenized, by which we mean the data-driven preselection of lag length should be taken into account. We provide and accordingly evaluate a Granger-causality bootstrap test which may be used with data that may or may not be integrated, and compare the performance of this test to that for the analogous asymptotic test. The suggested bootstrap test performs well and appears to be also robust to ARCH effects that usually characterize the financial data. This test is applied to testing the causal impact of the US financial market on the market of the United Arab Emirates.
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Bibliographic InfoPaper provided by Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies in its series Working Paper Series in Economics and Institutions of Innovation with number 223.
Length: 21 pages
Date of creation: 10 Apr 2010
Date of revision:
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Causality; VAR Model; Stability; Endogenous Lag; ARCH; Leverages;
Other versions of this item:
- Scott Hacker & Abdulnasser Hatemi-J, 2012. "A bootstrap test for causality with endogenous lag length choice: theory and application in finance," Journal of Economic Studies, Emerald Group Publishing, vol. 39(2), pages 144-160, May.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-04-17 (All new papers)
- NEP-ECM-2010-04-17 (Econometrics)
- NEP-ETS-2010-04-17 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- Selim Yildirim & Bilge Kagan Özdemir & Burhan Dogan, 2013. "Financial Development and Economic Growth Nexus in Emerging European Economies: New Evidence from Asymmetric Causality," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 710-722.
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