The Estimation of Long-run Relationship between Serbian and German Economic Growth
Abstract
Germany has always had an essential influence on Serbia's economic development. Today, Germany is Europe’s economic and political superstar so this is even more pronounced. Hence, the aim of this paper is to explore the fundamental causal relationship between German and Serbian economy. In doing so, after the introductory part, where we emphasized interconnection in terms of investment, foreign trade, employment, new technologies etc., we are extending our study using quarterly 2004q1-2015q2 GDP data of both Serbia and Germany to estimate the Vector Error Correction model (VECM). The results suggest that there is co-integration between Serbia's and Germany's economic growth. The statistically significant negative coefficient on indicates that Serbian GDP responds to a temporary disequilibrium between the Germany and Serbia. On the other hand, Germany does not appear to respond to a disequilibrium between the two economies; the t-ratio on is statistically insignificant. These results support the idea that economic conditions in Serbia depend on those in Germany incomparably more than conditions in Germany depend on Serbia. Despite a solid long-term impact, there is not short run causality running from GerGDP to SrbGDP.
References
Davidson, J.E.H., Hendry, D.F., Srba, F., Yeo, J.S. (1978). Econometric modeling of the aggregate time--series relationship between consumers' expenditure and income in the United Kingdom. Economic Journal, 661-692
Dungey, M., Vehbi, T. (2011). Modelling East Asia economics in a small open economy VECM: The inferences of international and domestic shocks, Manuscript Australian National University, University of Cambridge and University of Tasmania
Engle, R.F., & Granger, C.W.J.(1987). Co-integration and error correction: Representation, estimation, and testing, Econometrica, 55: 251–276.
Hamilton, J.D. (1994). Time Series Analysis, Princeton University Press, Princeton, NJ
Lee C., Adkins and R. Carter Hill (2011). Using Stata for Principles of Econometrics, Fourth Edition, Stata Press, 407-412.
Liu Zhuang (2011). Time Series Analysis of China and Africa's GDP: A Case of Sudan, Proceedings of The 2011 International Symposium ——Technical Innovation of Industrial Transformation and Structural Adjustment
Nielsen, B. (2001). Order determination in general vector autoregressions, Working paper, Department of Economics, University of Oxford and Nuffield College
Paulsen, J. (1984), Order determination of multivariate autoregressive time series with unit roots, Journal of Time Series Analysis 5: 115–127.
Tsay, R. S. (1984). Order selection in nonstationary autoregressive models, Annals of Statistics 12: 1425–1433.
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