Testing for causality between FDI and economic growth using heterogeneous panel data

Autor: Chris Stewart, Melisa Chanegriha, Christopher Tsoukis
Jazyk: angličtina
Rok vydání: 2020
Předmět:
ISSN: 1469-9559
0963-8199
Popis: The causal relationship between FDI inflows and growth is of great policy interest, yet the state of concrete knowledge on the issue is rather poor. Our contribution is to investigate the causal relationship between the ratio of FDI to GDP (FDIG) and economic growth (GDPG) using a battery of cutting-edge methods and an extensive data set. We employ the heterogeneous-panel tests of the Granger non-causality hypothesis based on the works of Hurlin, C. 2004a. Testing Granger Causality in Heterogeneous Panel Data Models with Fixed Coefficients. Mimeo: University of Orléans, (Fisher, R. A. 1932. Statistical Methods for Research Workers. Edinburgh: Oliver & Boyd., Fisher, R. A. 1948. ‘Combining Independent Tests of Significance.’ American Statistician 2 (5): 30–31) and Hanck, C. 2013. ‘An intersection test for panel unit roots.’ Econometric Reviews 32 (2): 183–203. Our panel data set is compiled from 136 developed and developing countries over the 1970-2006 period. According to the Hurlin and Fisher tests, FDIG unambiguously Granger-causes GDPG for at least one country. However, the results from these tests are ambiguous regarding whether GDPG Granger-causes FDIG for at least one country. Using a test based upon Hanck, C. 2013. ‘An intersection test for panel unit roots.’ Econometric Reviews 32 (2): 183–203, both with and without one structural break in the vector autoregression, we are able to determine whether and for which countries there is Granger-causality. This test suggests that at most there are six countries (Estonia, Guyana, Poland, Switzerland, Tajikistan and Yemen) where FDIG Granger-causes GDPG and at most four countries (Dominican Republic, Gabon, Madagascar and Poland) where GDPG Granger-causes FDIG.
Databáze: OpenAIRE
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