The Short and Long Run Causality between Agglomeration and Productivity


Department of Economics, Shiraz University


This study is to investigate the short- and long-run causal relationship between agglomeration (localization and urbanization) economies and labor productivity in the manufacturing sector of 28 Iranian provinces over an 11-year period, 2001–2011. Fully Modified Ordinary Least Squares (FMOLS) method was used to estimate our long-run panel data model. The empirical findings suggested that localization and urbanization economies had a positive and statistically significant effect on labor productivity in the long-run equilibrium. Then, the Generalized Method of Moments (GMM) was employed to examine Granger Causality between each pair of variables. The results revealed a bidirectional short-run Granger causality between localization economies and labor productivity. Additionally, a bidirectional short-run causal relationship was found between urbanization economies and labor productivity for all the manufacturing industries. In the long run, however, there seemed to be bidirectional causality between localization economies and productivity and also between urbanization economies and labor productivity in each manufacturing industry.


Azari, M., Kim, H., Kim, J. Y., & Ryu, D. (2016). The Effect of Agglomeration on the Productivity of Urban Manufacturing Sectors in a Leading Emerging Economy. Economic Systems, Retrieved from ? md5 =5c36c363f9a81c956113f54a281808c2&pid=1-s2.0-S0939362516300036-main.pdf.
Brülhart, M., & Mathys, N. A. (2008). Sectoral Agglomeration Economies in a Panel of European Regions. Regional Science and Urban Economics, 38(4), 348-362.‏
Ciccone, A. (2002). Agglomeration Effects in Europe. European Economic Review, 46(2), 213-227.‏
Ciccone, A., & Hall, R. E. (1996). Productivity and the Density of Economic Activity. The American Economic Review, 86, 54-70.
Choi, I. (2001). Unit Root Tests for Panel Data. Journal of International Money and Finance, 20(2), 249-272.
Dehghan Shabani, Z., (2013). Density of Economic Activity and Labor Productivity in Iranian Provinces. Iranian Journal of Economic Research, 55, 93-117.
Combes, P. P., Duranton, G., & Gobillon, L. (2008). Spatial Wage Disparities: Sorting Matters. Journal of Urban Economics, 63(2), 723-742.‏
Graham, D. J., Melo, P. S., Jiwattanakulpaisarn, P., & Noland, R. B. (2010). Testing for Causality between Productivity and Agglomeration Economies. Journal of Regional Science, 50(5), 935-951.‏
Hadri, K. (2000). Testing for Stationarity in Heterogeneous Panel Data. The Econometrics Journal, 3(2), 148-161.‏
Henderson, J. V. (1986). Efficiency of Resource Usage and City Size. Journal of Urban Economics, 19(1), 47-70.
Henderson, J. V. (2003). Marshall's Scale Economies. Journal of Urban Economics, 53(1), 1-28.
Holmes, T. J. (1999). Localization of Industry and Vertical Disintegration. Review of Economics and Statistics, 81(2), 314-325.
Hu, C., Xu, Z., & Yashiro, N. (2015). Agglomeration and Productivity in China: Firm Level Evidence. China Economic Review, 33, 50-66.‏
Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115(1), 53-74.‏
Jacobs, J. (1969). The Economy of Cities. New York: Vintage.
Ke, S. (2010). Agglomeration, Productivity, and Spatial Spillovers across Chinese Cities. The Annals of Regional Science, 45(1), 157-179.
Lall, S. V., Shalizi, Z., & Deichmann, U. (2004). Agglomeration Economies and Productivity in Indian Industry. Journal of Development Economics, 73(2), 643-673.‏
Lee, B. S., Jang, S., & Hong, S. H. (2010). Marshall’s Scale Economies and Jacobs’ Externality in Korea: the Role of Age, size and the Legal form of Organization of Establishments. Urban Studies, 47(14), 3131-3156.‏
Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Journal of Econometrics, 108(1), 1-24.‏
Maddala, G. S., & Wu, S. (1999). A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test. Oxford Bulletin of Economics and Statistics, 61(S1), 631-652.‏
Maré, D. C., Timmons, J., & Economic, M. (2006). Geographic Concentration and Firm Productivity. Motu Working Paper, Retrieved from
Martin, P., Mayer, T., & Mayneris, F. (2011). Spatial Concentration and Plant-Level Productivity in France. Journal of Urban Economics, 69(2), 182-195.‏
Marshall, A. (1920). Principles of Economics. London: Mac-Millan.
Nakamura, R., & Paul, C. J. M. (2009). 16 Measuring Agglomeration. Retrieved from
Pedroni, P. (2004). Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the PPP Hypothesis. Econometric Theory, 20(03), 597-625.‏
---------- (2000). Fully Modified OLS for Heterogeneous Cointegrated Panels. Advanced in Econometrics, 15, 93-130.    
Pesaran, M. H. (2007). A Simple Panel Unit Root Test in the Presence of Cross‐Section Dependence. Journal of Applied Econometrics, 22(2), 265-312.‏
---------- (2004). General Diagnostic Tests for Cross Section Dependence in Panels. Cambridge Working Papers in Economics, Retrieved from
Pesaran, M. H., Shin, Y., & Smith, R. P. (1999). Pooled Mean Group Estimation of Dynamic Heterogeneous Panels. Journal of the American Statistical Association, 94(446), 621-634.‏
Rosenthal, S. S., & Strange, W. C. (2004). Evidence on the Nature and Sources of Agglomeration Economies. Handbook of Regional and Urban Economics, 4, 2119-2171.‏
Westerlund, J. (2005). New Simple Tests for Panel Cointegration. Econometric Reviews, 24(3), 297-316.‏