Exports and growth: Granger causality analysis on OECD countries with a panel data approach

Kónya, László

doi:10.1016/j.econmod.2006.04.008

Cited by 656 publications

(926 citation statements)

References 5 publications

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“…The estimation follows the bootstrap panel Granger causality proposed by Kónya (2006). This approach has two important advantages.…”

Section: Empirical Framework Data and Methodologymentioning

confidence: 99%

“…Regarding the countryspecific heterogeneity assumption, the slope homogeneity tests ( Δ andΔ − adj ) of Pesaran and Yamagata (2008) are used (Appendix 3 provides more information about these tests). The Kónya's (2006) approach considers both issues, based on SUR systems estimation and identification of Wald tests with country-specific bootstrap critical values. This procedure allows us to consider all variables in their levels and perform causality output for each country:…”

Section: Empirical Framework Data and Methodologymentioning

confidence: 99%

“…Due to the existence of these structural breaks, we should incorporate these breaks into our testing model; otherwise, the results will be biased. Since Kónya (2006) cannot allow different break dates into the testing model, we follow the procedure adopted by Tsong and Lee (2011) and Bahmani-Oskooee et al (2014) to adjust the data as follows:…”

Section: Empirical Framework Data and Methodologymentioning

confidence: 99%

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Saving and investment causality: implications for financial integration in transition countries of Eastern Europe

Irandoust

2017

Int Econ Econ Policy

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Numerous studies have been devoted to the Feldstein-Horioka puzzle. However, no consensus has been reached in the literature. This paper examines the causal relationship between domestic saving and investment rates in six transition economies (Estonia, Latvia, Lithuania, Ukraine, Belarus, and Russian Federation). Theoretically, the presence of any type of causal structure between these two series in a country implies that national capital markets are not open; hence capital flows are impeded. Therefore, the paper employs the bootstrap panel Granger causality approach that accounts for both cross-sectional dependence and slope heterogeneity across countries to determine the causal structure. The findings show that there is a causality between the series, thereby implying that capital is not perfectly mobile internationally in any of the countries under review, but it is more mobile in Estonia, Russian Federation, and Latvia than Lithuania, Belarus, and Ukraine. The underdevelopment of financial markets in these countries as well as the demand for foreign capital to finance domestic investment projects and the lack of adequate economic and financial reforms might have driven these results.

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“…The estimation follows the bootstrap panel Granger causality proposed by Kónya (2006). This approach has two important advantages.…”

Section: Empirical Framework Data and Methodologymentioning

confidence: 99%

Section: Empirical Framework Data and Methodologymentioning

confidence: 99%

Section: Empirical Framework Data and Methodologymentioning

confidence: 99%

See 1 more Smart Citation

Saving and investment causality: implications for financial integration in transition countries of Eastern Europe

Irandoust

2017

Int Econ Econ Policy

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“…To investigate the existence of cross-section dependence we carried out four different tests (LM, CD lm ,CD, LM adj ). Secondly, as indicated by Kónya (2006), the selection of optimal lag structure is of importance because the causality test results may depend critically on the lag structure. In determining lag structure we follow Kónya (2006)'s approach that maximal lags are allowed to differ across variables, but to be same across equations.…”

Section: Empirical Findingsmentioning

confidence: 99%

“…Secondly, as indicated by Kónya (2006), the selection of optimal lag structure is of importance because the causality test results may depend critically on the lag structure. In determining lag structure we follow Kónya (2006)'s approach that maximal lags are allowed to differ across variables, but to be same across equations. We estimate the system for each possible pair of ly 1 , lx 1 , ly 2 and lx 2 respectively by assuming from 1 to 4 lags and then choose the combinations which minimize the Schwarz Bayesian Criterion.…”

Section: Empirical Findingsmentioning

confidence: 99%

The causal relationship between house prices and growth in the nine provinces of South Africa: evidence from panel - Granger causality tests

Chang

Simo-Kengne

Gupta

2014

IJSE

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This paper analyses the causal relationship between housing activity and growth in nine provinces of South Africa for the period 1995-2011, using panel causality analysis, which accounts for cross-section dependency and heterogeneity across provinces. Our empirical results support unidirectional causality running from housing activity to economic growth for most of the provinces studied; bi-directional causality between housing activity and economic growth for Gauteng; and no causality in any direction between housing activity to economic growth in Eastern Cape and KwaZulu-Natal. Our findings provide important insights for housing policies and strategies for South Africa. Specifically, housing sector might be an efficient growth-led instrument for all the provinces except Eastern Cape and KwaZulu-Natal.

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Does International Trade Cause Economic Growth? A Survey

Singh¹

2011

The World Economy

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Exports and growth: Granger causality analysis on OECD countries with a panel data approach

Cited by 656 publications

References 5 publications

Saving and investment causality: implications for financial integration in transition countries of Eastern Europe

Saving and investment causality: implications for financial integration in transition countries of Eastern Europe

The causal relationship between house prices and growth in the nine provinces of South Africa: evidence from panel - Granger causality tests

Does International Trade Cause Economic Growth? A Survey

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