IDENTIFYING CAUSAL RELATIONSHIPS BETWEEN NONSTATIONARY STOCHASTIC PROCESSES: AN EXAMINATION OF ALTERNATIVE APPROACHES IN SMALL SAMPLES

Hector O. Zapata, Michael A. Hudson and Philip Garcia

Western Journal of Agricultural Economics, 1988, vol. 13, issue 2, 14

Abstract: A Monte Carlo investigation is used to examine the performance of two commonly used tests for Granger causality for univariate and bivariate nonstationary ARMA (p,q) processes. Tests are applied to raw data, first differences of the raw data, and detrended versions of the series. The results indicate that for independent series the tests are robust regardless of sample size. With bivariate series and nonstationarity, the tests results are sensitive to the ARMA specification, whether the data are filtered and the type of filter used, and the sample size.

Keywords: Research; Methods/; Statistical; Methods (search for similar items in EconPapers)
Date: 1988
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://ageconsearch.umn.edu/record/32108/files/13020202.pdf (application/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:ags:wjagec:32108

DOI: 10.22004/ag.econ.32108

Access Statistics for this article

More articles in Western Journal of Agricultural Economics from Western Agricultural Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().