Autores: Ana Maria Bonomi Barufi, Eduardo A. Haddad, Peter Nijkamp
Abstract. The tendency towards urbanization in the emerging world accompanied by the constant pursuit for higher productivity prompts an urge for studies aiming at understanding agglomeration economies. In the context of Brazil, a country with extremely high regional disparities, exploring this issue is important not only for private stakeholders, but also for public policy practitioners. In the framework of static agglomeration effects, we investigate the industrial scope of agglomeration economies in Brazil. On the basis of identified registration data covering the whole formal labor market in three distinct years (2004, 2008 and 2012), we estimate separate models for the logarithm of the hourly individual wage for five broad economic sectors (S1 – Manufacturing low-tech, S2 – Manufacturing medium-tech, S3 – Manufacturing high-tech, S4 – Services less-knowledge, and S5 – Services high-knowledge). Different estimation strategies are considered in a two-stage mode: with and without individual fixed effects in the first stage, and with and without instrumental variables for population density in the second stage. The main results indicate that there is not a unique optimal local industrial mix to foster productivity in different technological sectors. Comparing possible theoretical approaches (MAR, Jacobs, Porter) related to combinations of diversity, specialization and competition, we find that for S5 only diversity is significant (and positive), suggesting that a Jacobs’ perspective is rather adequate. For S1, S2 and S4, the MAR framework seems more adequate to explain the underlying patterns. In the case of S3, there are elements from both Marshall’s and Jacobs’ perspectives. These results seem to be robust to different specifications and estimation strategies. Finally, the urbanization economies coefficient appears to be positive and significant for all sectors, ranging from 0.0511 to 0.0940 in different specifications, under the simplest estimation (OLS in the first and the second stages). Ordering these effects between the sectors from the highest to the lowest, we find the following sequence: S3, S1, S5, S4 and S2. This can be considered as evidence that high-tech and low-tech manufacturing sectors benefit more from the urban or metropolitan scale in Brazil, followed by services associated with higher knowledge intensity.
Clique aqui para fazer o download