Economias de aglomeração nos municípios brasileiros: uma abordagem utilizando nascimento de firmas, mobilidade dos trabalhadores e equações de salários

• Autor(a) principal: Amarante, Patrícia Araújo
• Data de Publicação: 2017
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFPB
• Texto Completo: https://repositorio.ufpb.br/jspui/handle/123456789/12522
• topic: Economias de aglomeração; Densidade do emprego; Produtividade; Agglomeration economies; Density of employment; Productivity; CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA

This thesis aimed to verify, through three essays, how the economies of agglomeration affect the decisions of location of the companies, the mobility of workers and the salaries in the Brazilian municipalities. The first essay analyzes, based on the birth of firms in the Transformation Industry, how the agglomeration mechanisms proposed by Marshall (1920) act as underlying causes of the economies of location and urbanization. We use a two-step procedure was performed: i) estimation of regression models for Poisson and Negative Binomial counts, which identified, for each industrial sector, which type of agglomeration economy contributes to the location of the new companies; and ii) using the coefficients obtained in the first stage, it was verified which characteristics of the industries related to the mechanisms of agglomeration of Marshall (1920) can contribute to the differences of intensities of these economies. Based on the results obtained, economies of location and urbanization could be considered as important determinants of firms' localization decisions. Localization economies are more intense in industries employing workers with industryspecific skills, thus being able to share a common pooling of skilled workers. In the same way, knowledge spillovers act in a way that boosts the economies of location, providing an environment conducive to the transmission of knowledge and new ideas. However, location economies are less intense in industries that have a greater dependence on manufactured inputs and the primary sectors and on energy supply in their production processes. In addition, they tend to decline in more technologically intensive industries and to rise the larger the size of the company in terms of the number of workers. Urbanization economies are negatively related, such as labor market pooling and knowledge spillovers, indicating that firms in sectors that employ workers with industry-specific skills and have high proportions of skilled workers tend to have low urbanization economies. On the other hand, the effects of input sharing and dependence on primary input and energy sectors on urbanization economies are positive and statistically significant, suggesting the presence of high urbanization economies in industries that use manufactured inputs and the primary and energy supply sectors more intensely. In addition, the evidence indicates that urbanization economies are larger in technologically intensive industries and smaller in terms of number of workers. The second essay aimed to investigate how the spatial density of employment affects the inter-firm mobility of workers in the Brazilian labor market. For this, we produced evidence using Probit models with random effects and dynamic Probit applied to an employer-employee data panel that captures regional differences, as well as characteristics related to workers and companies, built through the identified RAIS. The results indicate that individuals working in denser regions are more likely to inter-firm mobility. In general, employment density affects inter-firm mobility with greater intensity if workers are in the age group between 18 and 29 years of age and are more skilled. In addition, the results obtained for the dynamic models using the Heckman (1981) and Stewart (2006) estimators indicate that the temporally lagged interphase mobility is statistically significant; suggesting that the inter-firm mobility in period t depends potentially on the inter-firm mobility in the period t-1. However, this relationship is negative, indicating that individuals who have moved from one job to another in period t-1 are less likely to make another change in period t. Finally, the purpose of the third essay is to verify, through wage equations associated with the Urban Economy and the New Economic Geography, how the relation between agglomeration economies and productivity behaves. The theoretical framework was based on Fingleton and Longhi (2013), and the empirical strategy considers the different levels of aggregation of data, as well as the possible evidence of spatial autocorrelation in the regional data, through the spatial hierarchical approach with formulation based on Morenoff (2003). The results suggest that individual wages tend to be larger as the higher employment density and the lower the distance to the municipal economic center (the greater the market potential). In addition, the inclusion of the spatial lags of these variables suggests that the density of employment and the market potential of neighboring municipalities may also influence average wages.