Convergence of Sectoral Productivity in Turkish Provinces: A Markov Chains Model
Abstractthis study examines the role that sectors play in aggregate convergence of provincial labor productivity across the 67 provinces of turkey during the 1975-1990 period. a markov chain model is applied to characterize the long-run tendencies of productivity both at the aggregate and sectoral levels. in order to determine the likely sources of aggregate fluctuations, sectoral time-invariant distributions are compared with the aggregate distribution, and those sectors that exhibit similar distribution patterns as that of the aggregate distribution are characterized as dominant sectors. evidence strongly suggests that the aggregate time-invariant distribution is determined mainly by the agricultural, industrial and transportation sectors. specifically, the pattern of polarization of productivity levels in these three sectors is very similar to the pattern prevailing at the aggregate level. the results suggest that, in the long run, two convergence clubs are likely to emerge - one for the agricultural and another for the highly industrialized provinces. an exception is the service sector, which exhibits global convergence.
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Bibliographic InfoArticle provided by Euro-American Association of Economic Development in its journal International Journal of Applied Econometrics and Quantitative Studies .
Volume (Year): 2 (2005)
Issue (Month): 2 ()
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Find related papers by JEL classification:
- O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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