Agglomeration economies are externalities that impact on prices in the economy. The interactions that occur in agglomerations are relevant for the understanding of the benefits generated by proximity. These benefits directly affect workers' wage, real estate prices, etc. Many papers have focused on non-market interaction in aggregated labor markets, but intra-urban labor markets have received less attention. Seeking to fulfill such lack, 1 km² areas of the Metropolitan Area of São Paulo (MASP) are taken as the scope of analysis of this study. The central objectives of this dissertation are twofold. First, in chapter 3, I identified and characterized the most relevant areas in terms of job agglomeration in the MASP, named subcentral business districts (SBD). For this purpose, the geocoded matched employer-employee database of the Ministry of Labor (RAIS-TEM) was used. I developed a new empirical approach to identify the SBD, using Geographicaly Weight Regression and cutoff rules of identification. The results identified three SBD in the years of 2002 and 2008, and only two in 2014. Considering the two initial periods, the SBD are located in the municipalities of Barueri (SBD-BAR), São Paulo (SBD-SAO) and São Caetano do Sul (SBD-SCS). In the last year, the SBD are located in Barueri and São Paulo municipality only. The employment located in the central areas of São Paulo shows a relatively higher amount of employee than in the other SBD areas. SBD-BAR and SBD-SCS lost not only in terms of employment, but also in terms of area. In 2002, these last two SBD occupied areas of 5 and 7 km² respectively. In 2014, the SBD-BAR occupied 1 km², while the SBD-SCS is not ranked at all. In São Paulo, the area ranges from 79 km² to 90 km². The results stemmed from the first paper suggest a high spatial concentration of employment in the MASP. In the second paper (chapter 4), the objectives are to identify the impact of agglomeration on workers' wages and test the agglomeration spatial attenuation hypothesis (SAH). For that, I use employer-employee RAIS database and consider a specification with multiple fixed effects and spatial lags of the employment agglomeration as a strategy to SAH identification. Even in the face of a more restrictive specification, the results suggest a positive effect of agglomeration, which is attenuated as the spatial distance increases. In other words, agglomeration affects positively workers' wage in the workplace area. Estimates without solving for endogeneity between wage and agglomeration indicate a direct effect of 0.039% (in the area itself), a first-order indirect effect of-0.11% (in the contiguous areas), and a second-order effect of-0.23% (in the ring around the contiguous areas), normalized by 100,000. When considering instrumental variables, the estimated direct effect on wages becomes 1.78%, the first-order effect changes to-2.12%, and the second order effect is not statistically significant.
Resumo Um dos méritos da abordagem de preços hedô-nicos é poder estimar preços implícitos de carac- AbstractOne of the merits of hedonic prices treatment is its capacity to estimate implicit prices of characteristics that have not a specifi c market. For example, it is possible to estimate implicit characteristics of complex housing markets. The fi rst part of this paper is concerned with the microfoundations of AMM and AMM with amenity models. Using hedonic prices jointly with spatial econometrics estimation I intend to estimate the willingness of consumers to pay for house characteristics and amenities in the São Paulo housing market taking into account consumer profi le.
ResumoMuitos trabalhos estudaram fatores que determinam o preço de imóveis. Todavia, pouco esforço foi atribuído para estudar o spillover espacial entre distritos, atentando para as hierarquias dos objetos de análise. Nesse contexto, utilizando o Método Hierárquico Linear Espacial, o presente artigo busca analisar os efeitos implícito, vizinhança e adjacência no município de São Paulo, isto é, quais os fatores afetam o preço intra e entre imóveis e quais fatores atuam sobre os preços intra e entre distritos. Os resultados apontam que 96,89% do preço do imóvel é explicado pelas características intrínsecas e de localização, enquanto 3,11% (efeito vizinhança e adjacência) é explicado pelas características dos distritos e o spillover espacial entre estes. Em relação à primeira decomposição, 90,13% pode ser entendido como efeito implícito (intra imóvel) e 6,76% como efeito adjacência (efeito entre imóveis). Palavras-ChaveEconomia urbana. Mercado imobiliário. Preços hedônicos. Modelo Hierárquico Linear Espacial. AbstractMany articles have studied factors that determine housing prices. However, few are concerned with the spatial spillover among districts, also taking into account the hierarchies. The Spatial Hierarchical Linear Model is thus applied to analyze neighborhood effects and adjacency effects within the city of Sao Paulo. In other words, we focus on the factors that affect housing price within and between districts. The results indicate that 96.88 percent of the housing prices can be explained by houses' intrinsic characteristics and their location, while 3.11 percent by the characteristics of the districts and their spatial spillover.
Theoretical models concerned with multiple centers were brought into the debate on sprawling urban employment. However, empirical methods that identify central places are not a specific aspect in the specialized literature. Then, the purpose of this paper is to identify and characterize the urban employment subcenters (Small Business Districts, SBD) in the Municipality of São Paulo by using a new methodology approach. We propose a two-step methodology: 1) Exploratory Spatial Data Analysis and 2) Spatial Hedonic Prices Model. As a result, we found seven regions that can be considered SBD. These regions are able to impact housing prices as predicted by polycentric theoretical models.
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