| In the section | Articles |
| Title of the article | Analysis of Regional Unemployment in Russia and Germany: Spatial-Econometric Approach |
| Pages | 64-85 |
| Author 1 | Elena Vyacheslavovna Semerikova Master of Economics, Post-Graduate Student, Research Assistant of the Center for Market Studies and Spatial Economics National Research University Higher School of Economics 26 Shabolovka Str., Moscow, Russia, 119049 This email address is being protected from spambots. You need JavaScript enabled to view it. |
| Author 2 | Olga Anatolyevna Demidova Ph. D. (Physics and Mathematics), Associate Professor National Research University Higher School of Economics 26 Shabolovka Str., Moscow, Russia, 119049 This email address is being protected from spambots. You need JavaScript enabled to view it. |
| Abstract | The study was supported by the Government of the Russian Federation, grant No.11.G34.31.0059. This paper analyzes the regional unemployment in Russia and Germany in 2005-2010 and addresses issues of choosing the right specification of spatial-econometric models. The analysis based on data of 75 Russian and 370 German regions showed that for Germany the choice of the spatial weighting matrix has a more significant influence on the parameter estimates than for Russia. Presumably this is due to stronger linkages between regional labor markets in Germany compared to Russia. The authors also proposed an algorithm for choosing between spatial matrices and demonstrated the application of this algorithm on simulated Russian data. The authors found that 1) the deviation of the results from the true ones increases when the spatial dependence between regions is higher and 2) the matrix of inverse distances is more preferable than the boundary one for the analysis of regional unemployment in Russia (because of the lower value of the mean squared error). The authors are also planning to apply the proposed algorithm for simulated data of Germany. These results allow accounting the spatial dependence more correctly when modeling regional unemployment which is very important for making proper regional policy. |
| Code | 332.1+332.05+330.43 |
| DOI | 10.14530/se.2015.2.064-085 |
| Keywords | spatial-econometric modelling ♦ spatial weighting matrix ♦ regional unemployment ♦ Russian regions ♦ German regions |
| Download | SE.2015.2.064-085.Semerikova.pdf |
| For citation | Semerikova E.V., Demidova O.A. Analysis of Regional Unemployment in Russia and Germany: Spatial-Econometric Approach. Prostranstvennaya Ekonomika = Spatial Economics, 2015, no. 2, pp. 64-85. DOI: 10.14530/se.2015.2.064-085. (In Russian). |
| References | 1. Aldstadt J., Getis A. Using AMOEBA to Create a Spatial Weights Matrix and Identify Spatial Clusters. Geographical Analysis, 2006, vol. 38, no. 4, pp. 327–343. DOI: 10.1111/j.1538-4632.2006.00689.x 2. Anselin L. Spatial Econometrics: Methods and Models, 1988, 284 p. DOI: 10.1007/978-94-015-7799-1 3. Aragon Y. et al. Explaining the Pattern of Regional Unemployment: The Case of the Midi-Pyrenees Region. Papers in Regional Science, 2003, vol. 82, no. 2, pp. 155–174. DOI: 10.1111/j.1435-5597.2003.tb00009.x 4. Arbia G., Fingleton B. New Spatial Econometric Techniques and Applications in Regional Science. Papers in Regional Science, 2008, vol. 87, no. 3, pp. 311–317. DOI: 10.1111/j.1435-5957.2008.00208.x 5. Beck N., Gleditsch K.S., Beardsley K. Space is More Than Geography: Using Spatial Econometrics in the Study of Political Economy. International Studies Quarterly, 2006, vol. 50, no. 1, pp. 27–44. DOI: 10.1111/j.1468-2478.2006.00391.x 6. Beenstock M., Ben Zeev N., Felsenstein D. Nonparametric Estimation of the Spatial Connectivity Matrix by the Method of Moments Using Spatial Panel Data, 2009, 20 p. 7. Bell K.P., Bockstael N.E. Applying the Generalized-Moments Estimation Approach to Spatial Problems Involving Micro-Level Data. Review of Economics and Statistics, 2000, vol. 82, no. 1, pp. 72–82. DOI: 10.1162/003465300558641 8. Bhattacharjee A., Jensen-Butler C. Estimation of Spatial Weights Matrix in a Spatial Error Model, with an Application to Diffusion in Housing Demand. University of St. Andrews. Centre for Research into Industry, Enterprise, Finance and the Firm. CRIEFF Discussion Papers No. 0519, 2006, 46 р. Available at: (accessed 06 April 2015). 9. Binet M.E., Facchini F. Okun’s Law in the French Regions: A Cross-Regional Comparison // Economics Bulletin, 2013, vol. 33, no. 1, pp. 420–433. 10. Cliff A.D., Ord J.K. Spatial Processes: Models and Applications. London: Pion, 1981, vol. 44, 266 p. 11. Cracolici M.F., Cuffaro M., Nijkamp P. Geographical Distribution of Unemployment: An Analysis of Provincial Differences in Italy. Growth and Change, 2007, vol. 38, no. 4, pp. 649–670. DOI: 10.1111/j.1468-2257.2007.00391.x 12. Elhorst J.P. The Mystery of Regional Unemployment Differentials: Theoretical and Empirical Explanations. Journal of Economic Surveys, 2003, vol. 17, no. 5, pp. 709–748. DOI: 10.1046/j.1467-6419.2003.00211.x 13. Elhorst J.P. Applied Spatial Econometrics: Raising the Bar. Spatial Economic Analysis, 2010, vol. 5, no. 1, pp. 9–28. DOI: 10.1080/17421770903541772 14. Getis A., Aldstadt J. Constructing the Spatial Weights Matrix Using a Local Statistic. Perspectives on Spatial Data Analysis. Edited by L. Anselin, S.J. Rey. Springer-Verlag Berlin Heidelberg, 2010, pp. 147–163. DOI: 10.1007/978-3-642-01976-0 15. Holzer H.J. Structural / Frictional and Demand-Deficient Unemployment in Local Labor Markets. Industrial Relations: A Journal of Economy and Society, 1993, vol. 32, no. 3, pp. 307–328. DOI: 10.1111/j.1468-232X.1993.tb01052.x 16. Kakamu K. Bayesian Estimation of a Distance Functional Weight Matrix Model. Economics Bulletin, 2005, vol. 3, no. 57, pp. 1–6. 17. Kangasharju A., Tavera C., Nijkamp P. Regional Growth and Unemployment: The Validity of Okun’s Law for the Finnish Regions // Spatial Economic Analysis, 2012, vol. 7, no. 3, pp. 381–395. DOI:10.1080/17421772.2012.694141. 18. Lee L.F. Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models. Econometrica, 2004, vol. 72, no. 6, pp. 1899–1925. DOI: 10.1111/j.1468-0262.2004.00558.x 19. LeSage J., Pace R.K. Spatial Econometric Models. Handbook of Applied Spatial Analysis. Edited by M.M. Fischer, A. Getis. Springer-Verlag Berlin Heidelberg, 2010, pp. 355–376. 20. LeSage J.P., Pace R.K. The Biggest Myth in Spatial Econometrics. SSRN, 2010. DOI: 10.2139/ssrn.1725503 21. Lottmann F. Explaining Regional Unemployment Differences in Germany: A Spatial Panel Data Analysis. SFB 649 Discussion Paper 2012-026. Berlin: Humboldt-Universitat, 2012. 56 p. Available at: (accessed 11 April 2015). 22. Martin R. Regional Unemployment Disparities and Their Dynamics. Regional Studies, 1997, vol. 31, no. 3, pp. 237–252. DOI: 10.1080/00343409750134665 23. Meyer B., Tasci M. An Unstable Okun’s Law, Not the Best Rule of Thumb // Economic Commentary, 2012, no. 2012-08, June 7. 24. Molho I. Spatial Autocorrelation in British Unemployment. Journal of Regional Science, 1995, vol. 35, no. 4, pp. 641–658. DOI: 10.1111/j.1467-9787.1995.tb01297.x 25. Mundlak Y. On the Pooling of Time Series and Cross Section Data. Econometrica: Journal of the Econometric Society, 1978, vol. 46, no. 1, pp. 69–85. DOI: 10.2307/1913646 26. Niebuhr A. Spatial Interaction and Regional Unemployment in Europe. European Journal of Spatial Development, 2003, vol. 5, pp. 1–26. 27. Ord K. Estimation Methods for Models of Spatial Interaction. Journal of the American Statistical Association, 1975, vol. 70, no. 349, pp. 120–126. DOI: 10.1080/01621459.1975.10480272 28. Partridge M.D., Rickman D.S. Differences in State Unemployment Rates: The Role of Labor and Product Market Structural Shifts. Southern Economic Journal, 1995, vol. 62, no. 1, pp. 89–106. DOI: 10.2307/1061378 29. Plumper T., Neumayer E. Model Specification in the Analysis of Spatial Dependence. European Journal of Political Research, 2010, vol. 49, no. 3, pp. 418–442. DOI: 10.1111/j.1475-6765.2009.01900.x 30. Stakhovych S., Bijmolt T.H. Specification of Spatial Models: A Simulation Study on Weights Matrices. Papers in Regional Science, 2009, vol. 88, no. 2, pp. 389–408. DOI: 10.1111/j.1435-5957.2008.00213.x |
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