Strong and Weak Cross-Section Dependence in Non-Stationary Spatial Panel Data
- 575 Downloads
We begin by recalling that dependence in nonstationary panel data may by weak or strong, and statistical tests to distinguish between weak and strong dependence are presented. In Chaps. 7, 8, and 9 dependence is assumed to be weak or spatial. This chapter is concerned with deciding whether dependence is weak, strong or both.
We describe the econometric theory of common factor models, which induce strong dependence in stationary and nonstationary spatial panel data. We report critical values for panel cointegration tests from the literature in the presence of common factors when the data are nonstationary. In the first empirical illustration time series data for the stock of foreign direct investment is hypothesized as a common factor in the determination of capital deepening, measured by regional capital-labor ratios in Israel. Another common factor is time series for national capital-labor ratios. Common factor models in which panel dependence is assumed to be strong are compared with spatial models in which panel dependence is assumed to be weak.
In a second empirical illustration the residuals for the spatial general equilibrium model in Chap. 8 and the SpVECM in Chap. 9 are tested for weak versus strong panel dependence. The residuals from Chap. 8 are not weakly dependent, but the residuals from Chap. 9 are weakly dependent. The former suggests that common factors should be specified in Chap. 8. However, strong cross-section dependence still remains indicating a need for ‘mixed dependence’ models incorporating both spatial and common factors.
- Armstrong H, Taylor J (2000) Regional economics and policy, 3rd edn. Blackwell, OxfordGoogle Scholar
- Ascani A, Gagliardi L (2015) Inward FDI and local innovative performance. An empirical investigation on Italian provinces. Rev Reg Res 35(1):29–47Google Scholar
- Beenstock M (1986) The World Bank’s contribution to economic development. In: Recovery in the developing world. The World Bank, Washington, DC, pp 34–46Google Scholar
- Bornschier V, Chase-Dunn C (1985) Transnational corporations and underdevelopment. Praeger, New YorkGoogle Scholar
- Casi L, Resmini L (2010) Evidence on the determinants of foreign direct investment: the case of EU regions. East J Eur Stud 1(2):93–118Google Scholar
- Dall’Erba S, de Gallo J (2007) The impact of EU regional support on growth and employment. Czech J Econ Financ 57(7–8):325–350Google Scholar
- Elhorst JP (2014) From spatial cross-section data to spatial panel data. Springer, BerlinGoogle Scholar
- EU (2011) Estimating the capital stock for the NUTS 2 regions of the EU-27. Working Papers no01/2011, DG Regional Policy, European Union, BrusselsGoogle Scholar
- Navon G, Frisch R (2009) The effect of Israel’s encouragement of capital investments in industry law on product, employment, and investment: an empirical analysis of micro data. Discussion Paper Series, 2009.12, Research Department, Bank of Israel, Jerusalem (Hebrew)Google Scholar