This dissertation consists of two essays dealing with the trends in industrial agglomeration and changes in the influence of micro-determinants of agglomeration due to globalization in the U.S. manufacturing agglomeration and the second essay discusses the impact of globalization on the micro-determinants of agglomeration. The first essay explores recent agglomeration trends in the U.S. manufacturing industries between 1988 and 2003 using employment and employment-based agglomeration measures such as Ellison-Glaeser Index and Gini index, and using Herfindahl index as a measure of industrial concentration due to scale economies. Between 1988 and 2003, forty two states lost and eight states gained manufacturing employment with a net loss of more than 5.13 million jobs nationwide. Middle Atlantic, New England, and South Atlantic are the three divisions with highest drops in manufacturing employment with Middle Atlantic division’s loss of 45 percent jobs, New England division’s loss of 44 percent and South Atlantic division’s loss of 28 percent of jobs in the manufacturing industries. Three states that experienced the most decrease in manufacturing jobs in 2003 measured in percent of their 1988 employment are New Jersey (51 percent), New York (51 percent), and Connecticut (48 percent). Textile and apparel industries, metal related industries and leather and leather goods industries etc. are among the industries that experienced relatively higher attrition in manufacturing jobs in 2003. Three trends are apparent. First, employment has declined across regions, years and industries. Second, the industries that were among the most agglomerated industries in 1988 have generally displayed decrease in agglomeration indices (both in terms of EGI and Gini measures) in later years including 2003. This trend may imply that for these industries, attrition of manufacturing employment in later years mainly occurred from the counties with relatively higher share of employment in the concerned industries in 1988. Third, industries that are found to be least agglomerated in 1988 have often displayed increase in agglomeration in later years including 2003. This trend may imply that for these industries, attrition of manufacturing employment in 2003. This trend may imply that for these industries, attrition of manufacturing employment in 2003 mainly occurred from the counties with lower employment share of the concerned industries in 1988. Similar trends are observed for the Herfindahl indices. Changes in the Herfindahl indices may be due to changes in traditional scale economies caused by advancements in the ICTs. The second essay explores the differential impacts of technological advancements and trade liberalization on the three Marshallian determinants of industrial agglomeration for U.S. manufacturing industries. These three micro-determinants of agglomeration are goods pooling (input sharing), labor pooling (availability of labor), and idea pooling (knowledge spillover). The impact of decrease in employment on industrial agglomeration is ambiguous, and warrants empirical investigation. An index of agglomeration is regressed on proxies for three micro-determinants of agglomeration, after controlling for transportation costs, natural advantage and other state level economic variables, and after inclusion of interaction variables for technological advancement and trade liberalization. The regression results for both the OLS and FE specifications are consistent with the hypothesis that there was a structural change in the effect of the micro-determinants of industrial agglomeration in the U.S. manufacturing industries beginning in 1995. In the second essay, we decompose the impact of globalization on three micro-determinants of agglomeration into two separate segments: impact of technological advancements and impact of trade liberalization. The findings are partially consistent with the hypothesis that globalization has attenuated the effect of micro-determinants of agglomeration as the influence of two out of three micro-determinants of agglomeration diminished in the post-1995 years relative to their pre-1995 levels. For example, in the post 1995 period in our base line model, influence of labor pooling is diminished by about 4 percent and influence of idea pooling has attenuated by about 1 percent from their pre-1995 levels. Contrary to our hypothesis, we find that the influence of goods pooling has increased as a micro-determinant of agglomeration in the post-1995 years relative to its pre-1995 levels. The attenuation in influence for labor pooling and increase in influence of goods pooling in the post-1995 period are statistically significant when attenuation of influence of idea pooling is not statistically significant. Also, when we decompose the total effect of globalization, we find the impact of technology to be greater than that of international trade. The key findings are robust to alternative specifications of the econometric model, particularly to changes in the proxies used for LP.

Karlstads kommun har en målsättning om att kommunen år 2020 skall vara 100 000 invånare till antalet. För att detta mål skall nås inom en rimlig tid så har kommunen tre hållbarhetsstrategier som skall ligga till grund för kommunens arbete de kommande åren. De tre hållbarhetsstrategierna är folkhälsostrategin, tillväxtstrategin och miljö- och klimatstrategin, som skall se till att kommunen skall kunna växa på ett socialt, ekonomiskt och miljömässigt hållbart sätt.    Den här uppsatsen undersöker Karlstads kommuns tillväxtstrategi och hur bra den och dess mål och delmål passar in på ekonomiprofessorn Richard Floridas teorier om den kreativa klassen och på ekonomiprofessorn Edward Glaesers teorier om humankapital och stadstillväxt. / Karlstad Municipality has a vision that the municipality shall have 100 000 inhabitants by the year 2020. For this goal to be reached within a reasonable time, the municipality has made three sustainability strategies that will be the basis for the municipality’s work for the coming years. The three sustainability strategies are: the public health strategy, the economic growth strategy and the environment and climate strategy. The idea behind these strategies is to ensure that the municipality will grow in a socially, economic and environmentally sustainable manner.    This thesis examines Karlstad Municipality’s economic growth strategy and how well it and its goals and objectives can be applied on the economics professor Richard Florida and his theories about the Creative Class and on the economics professor Edward Glaeser and his theories about human capital and urban economics.

Submitted by Israel Vieira Neto (israel.vieiraneto@ufpe.br) on 2015-03-06T14:14:22Z No. of bitstreams: 2 DISSERTAÇÃO Francisco de Lima Cavalcanti.pdf: 3061717 bytes, checksum: 8e9d69f54e4cf9d9f5b26bd5990cb3ea (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-06T14:14:22Z (GMT). No. of bitstreams: 2 DISSERTAÇÃO Francisco de Lima Cavalcanti.pdf: 3061717 bytes, checksum: 8e9d69f54e4cf9d9f5b26bd5990cb3ea (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2013-03-05 / O presente trabalho caracteriza a distribuição espacial da classe criativa e do capital humano no Brasil, identificando clusters espaciais, e analisa a associação entre o dinamismo urbano entre e a presença da classe criativa e do capital humano entre os municípios brasileiros no período de 1991 e 2010. Faz-se também uma investigação comparativa entre medidas de mensuração de capital humano por níveis educacionais e composições ocupacionais. Como metodologia de análise de dependência espacial utilizou-se Índice de Moran e Índice Local de Autocorrelação Espacial – LISA, e para correlações entre dinamismo urbano, classe criativa e capital humano utilizou-se regressões com mínimos quadrados ordinários, regressões espaciais Durbin e dados em painel com efeitos fixos. Os resultados apontaram a discrepância espacial dos indicadores de capital humano e indicadores de classe criativa na composição ocupacional dos municípios brasileiros e evidência de associações positivas com dinamismo urbano.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-09-05T19:09:38Z No. of bitstreams: 1 JeanCarlosDosSantos_DISSERT.pdf: 2384951 bytes, checksum: a3bee8a2bc3dab828b39b947957ad74c (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-09-12T22:53:18Z (GMT) No. of bitstreams: 1 JeanCarlosDosSantos_DISSERT.pdf: 2384951 bytes, checksum: a3bee8a2bc3dab828b39b947957ad74c (MD5) / Made available in DSpace on 2017-09-12T22:53:18Z (GMT). No. of bitstreams: 1 JeanCarlosDosSantos_DISSERT.pdf: 2384951 bytes, checksum: a3bee8a2bc3dab828b39b947957ad74c (MD5) Previous issue date: 2017-06-02 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / A concentra??o industrial ? capaz de influenciar as caracter?sticas de determinadas regi?es, algumas vezes de forma construtiva e outras destrutiva. ? importante observar que dependendo da localidade, algumas caracter?sticas se tornam predominantes na atra??o de ind?strias, tais como, tradi??es produtivas, formas de trabalho e o perfil dos consumidores. A Teoria da Nova Geografia Econ?mica, tendo como principais autores Krugman (1991), Fujita (1989), Venables (1996) e Thisse (1996), aborda os efeitos da localiza??o no mercado e, consequentemente, das aglomera??es industriais. O estudo desses autores ? feito a partir da Trindade Marshalliana (transbordamento de conhecimento, fornecedores de insumo e especializa??o do trabalhador) e do Modelo de Concorr?ncia Monopol?stica de Dixit-Stiglitz, que examina como economias de escala, retornos crescentes e custos de transporte podem incentivar ou justificar a concentra??o das firmas em determinadas localidades. No caso brasileiro, Lautert e Ara?jo (2007), Silva e Bacha (2014) e Resende (2015) tratam quest?es que envolvem as aglomera??es industriais. Neste sentido, este trabalho ter? como objetivo principal promover uma an?lise que investigue quais os fatores que influenciaram a concentra??o industrial entre as Unidades Federativas do Brasil no per?odo de 2003 a 2014. Para execu??o desse objetivo, ser? utilizado o ?ndice de Concentra??o Ellison e Glaeser para medir a concentra??o industrial. As vari?veis utilizadas na observa??o dos impactos da concentra??o s?o as proxies, da influ?ncia do governo sobre a concentra??o industrial (al?quota do ICMS), o transbordamento de conhecimento (anos de estudo), externalidades (participa??o regional das firmas, competitividade das firmas) e custo de neg?cio (custos de transporte). Os dados ser?o organizados em forma de painel e ser? elaborado um modelo econom?trico de Vetores Autorregressivos em Painel ? PVAR, que permitir? estudar as rela??es din?micas e mecanismos de ajustes entre as vari?veis analisadas. Como fonte de dados, majoritariamente, utilizam-se dados encontrados na Rela??o Anual de Informa??es Sociais (RAIS), Censo Demogr?fico do IBGE e Banco Central do Brasil. Este estudo contribui com a literatura ao utilizar um ?ndice pouco explorado a n?vel nacional e ferramentas econom?tricas in?ditas para o estudo da concentra??o industrial. Os resultados da an?lise em painel indicam que dentre as vari?veis utilizadas, as que apresentaram maior signific?ncia sobre a concentra??o industrial est?o relacionados ? influ?ncia do governo e as externalidades. Verificou-se que choques relacionados ao transbordamento de conhecimento impactam positivamente na concentra??o industrial. Podemos concluir, portanto, que as externalidades e educa??o formal s?o fatores importantes para atra??o de ind?strias em uma regi?o. / The industrial concentration is capable of influencing the characteristics of certain regions, sometimes constructive and sometimes destructive. It is important to notice that depending on the locality, some characteristics become predominant in attracting industries, such as productive traditions, ways of working and the profile of the consumers. The New Economic Geography Theory, whose main authors are Krugman (1991), Fujita (1989), Venables (1996) and Thisse (1996), approaches the effects of market location and, consequently, industrial agglomerations. The study of these authors is based on the Marshallian Trinity (knowledge overflow, input suppliers and worker specialization) and the Dixit-Stiglitz Monopolistic Competition Model, which examines how economies of scale, increasing returns and transport costs can encourage or sometimes justify the concentration of firms in certain localities. In the Brazilian case, Lautert and Ara?jo (2007), Silva and Bacha (2014) and Resende (2015) deal with issues involving industrial agglomerations. In this sense, this work will promote an analysis that investigates the factors that influenced the industrial concentration between the states of Brazil in the period that goes from 2003 to 2014. In order to achieve this goal, we will use the Ellison and Glaeser Concentration Index to measure the industrial concentration. The variables used to check the impacts of the concentration are the proxies, the influence of the government on the industrial concentration (ICMS rate), the knowledge overflow (years of study), externalities (firms' regional participation and firm competitiveness) and business cost (Transport costs). The data will be organized in panel form and an econometric model of Autorregressive Panel Vectors - PVAR will be elaborated, which will allow to study the dynamic relations and mechanisms of adjustments among the analyzed variables. As a data source, we used the data found in the Annual Social Information Ratio (RAIS), Demographic Census of the IBGE and Central Bank of Brazil. This study contributes to the literature by using an index that has not been explored at a national level and some new econometric tools for the study of industrial concentration. The results of the panel analysis indicate that among the variables used, those that presented the highest significance on industrial concentration are related to government influence and externalities. It was also verified that shocks related to knowledge overflow cause a positive impact on industrial concentration. We can therefore conclude that externalities and formal education are important factors when it comes to attracting industries in a region.