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|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|12266||2012||12 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Regional Science and Urban Economics, Volume 42, Issue 4, July 2012, Pages 595–606
We compute aggregate productivity of three categories of regions, classified by the level of urbanization and density of economic activity in the Netherlands, from firm-specific total factor productivity (TFP) measures. TFP measures are estimated by a semi-parametric algorithm, within 2-digit industries, covering agriculture, manufacturing, construction, trade and services, using AMADEUS data over the period 1997–2006. We analyse the productivity differentials across urbanization categories by decomposing them into industry productivity effect and industry composition effect. Our analysis indicates that there is non-linear net effect of agglomeration on productivity growth but in levels agglomeration is associated with higher productivity.
Agglomeration and thus, the geographic concentration of economic activity in urbanized regions can result in a snowball effect, where firms tend to agglomerate to benefit from higher diversity and specialization in production processes. There are also benefits to firms from co-locating in close proximity to other firms in the same industry (Marshall, 1920, Henderson, 1974 and Henderson, 2003). Both urbanization and localization economies can be considered centripetal (agglomeration) forces leading to concentration of economic activity. Theoretical models (e.g., Glaeser et al., 1992 and Ciccone and Hall, 1996) and empirical studies (e.g., Carlino and Voith, 1992, Ciccone, 2002, Combes et al., 2009, Combes et al., 2010 and Graham, 2009) show that agglomeration associated with high density of economic activity positively affects productivity. Agglomeration can affect productivity in several ways. If technologies have constant returns themselves, but the transportation of products from one stage of production to the next involves costs that rise with distance, then the technology for the production of all goods within a particular geographical area will have increasing returns – the ratio of output to input will rise with density. If there are positive externalities associated with the physical proximity of production, then density will contribute to productivity for this reason as well. A third source of density effects is the higher degree of beneficial specialization possible in areas of dense economic activity.
نتیجه گیری انگلیسی
The focus of the paper is on evaluating the net impact of agglomeration on productivity (TFP) in the Dutch regions classified by level of urbanization. We build a structural model of the unobservable productivity incorporating land price (and wage) information to proxy for the effects of agglomeration and adapt the semi-parametric estimation approach proposed in Olley and Pakes (1996) to estimate the parameters of production functions using firm data, within 2-digit industries, for the period 1997–2006. We use information on land prices available at 4-digit postcodes and allow market structure to differ at disaggregate municipality (gemeente) level. We model the unobservable productivity as a second-order Markov process which enhances our ability to obtain unbiased and consistent estimates of the production function parameters and thus, back out unbiased and consistent firm-specific TFP measures.