nep-geo New Economics Papers
on Economic Geography
Issue of 2015‒05‒02
ten papers chosen by
Andreas Koch
Institut für Angewandte Wirtschaftsforschung

  1. Does Labour Mobility Foster Innovation? Evidence from Sweden By Braunerhjelm, Pontus; Ding, Ding; Thulin, Per
  2. The Effect of State Taxes on the Geographical Location of Top Earners: Evidence from Star Scientists By Enrico Moretti; Daniel Wilson
  3. Determinants of City Growth in Brazil By Daniel da Mata; Uwe Deichmann; J. Vernon Henderson; Somik V. Lall; Hyoung G. Wang
  4. Does Migration Lead to Regional Convergence in Russia? By Elena Vakulenko
  5. Urban Spatial Structure in OECD Cities: is Urban Population Decentralising or Clustering? By Paolo Veneri
  6. Spatial Dynamics of Labor Markets in Brazil By Kenneth M. Chomitz; Daniel da Mata; Alexandre Carvalho; João Carlos Magalhães
  7. Fertility, Regional Demographics, and Economic Integration By Hiroshi Goto; Keiya Minamimura
  8. Estimation of Multiequation Cross-section Models in the Presence of Spatial Autocorrelation By Alexandre Carvalho; Daniel da Mata; Kenneth M. Chomitz
  9. The problem of the inclusion of spatial dependence within the TOPSIS method By Michal Bernard Pietrzak
  10. Space-varying Regression Models: Specifications and Simulation By Dani Gamerman; Ajax R. B. Moreira; Havard Rue

  1. By: Braunerhjelm, Pontus (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology); Ding, Ding (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology); Thulin, Per (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology)
    Abstract: By utilising a Swedish unique, matched employer-employee dataset that has been pooled with firm-level patent application data, we provide new evidence that knowledge workers’ mobility has a positive and strongly significant impact on firm innovation output, as measured by firm patent applications. The effect is particularly strong for knowledge workers that have previously worked in a patenting firm (the learning-by-hiring effect), but firms losing a knowledge worker are also shown to benefit (the diaspora effect), albeit more weakly. Finally, the effect is more pronounced when the joining worker originates in another region.
    Keywords: Labour mobility; knowledge diffusion; innovation; social networks
    JEL: J24 O31 R23
    Date: 2015–04–24
  2. By: Enrico Moretti; Daniel Wilson
    Abstract: Using data on the universe of U.S. patents filed between 1976 and 2010, we quantify how sensitive is migration by star scientist to changes in personal and business tax differentials across states. We uncover large, stable, and precisely estimated effects of personal and corporate taxes on star scientists’ migration patterns. The long run elasticity of mobility relative to taxes is 1.6 for personal income taxes, 2.3 for state corporate income tax and -2.6 for the investment tax credit. The effect on mobility is small in the short run, and tends to grow over time. We find no evidence of pre-trends: Changes in mobility follow changes in taxes and do not to precede them. Consistent with their high income, star scientists migratory flows are sensitive to changes in the 99th percentile marginal tax rate, but are insensitive to changes in taxes for the median income. As expected, the effect of corporate income taxes is concentrated among private sector inventors: no effect is found on academic and government researchers. Moreover, corporate taxes only matter in states where the wage bill enters the state’s formula for apportioning multi-state income. No effect is found in states that apportion income based only on sales (in which case labor’s location has little or no effect on the tax bill). We also find no evidence that changes in state taxes are correlated with changes in the fortunes of local firms in the innovation sector in the years leading up to the tax change. Overall, we conclude that state taxes have significant effect of the geographical location of star scientists and possibly other highly skilled workers. While there are many other factors that drive when innovative individual and innovative companies decide to locate, there are enough firms and workers on the margin that relative taxes matter.
    JEL: H71 J01 J08 J18 J23 R0
    Date: 2015–04
  3. By: Daniel da Mata; Uwe Deichmann; J. Vernon Henderson; Somik V. Lall; Hyoung G. Wang
    Abstract: TIn this paper, we examine the determinants of Brazilian city growth between 1970 and 2000. We consider a model of a city, which combines aspects of standard urban economics and the new economic geography literatures. For the empirical analysis, we constructed a dataset of 123 Brazilian agglomerations, and estimate aspects of the demand and supply side as well as a reduced form specification that describes city sizes and their growth. Our main findings are that increases in rural population supply, improvements in inter-regional transport connectivity and education attainment of the labor force have strong impacts on city growth. We also find that local crime and violence, measured by homicide rates impinge on growth. In contrast, a higher share of private sector industrial capital in the local economy stimulates growth. Using the residuals from the growth estimation, we also find that cities who better administer local land use and zoning laws have higher growth. Finally, our policy simulations show that diverting transport investments from large cities towards secondary cities do not provide significant gains in terms of national urban performance. O presente trabalho examina os determinantes do crescimento das cidades brasileiras entre 1970 e 2000. Nós consideramos um modelo de cidades que combina tanto aspectos da tradicional economia urbana quanto da literatura da nova geografia econômica. Para a análise empírica, nós construímos um banco de dados para 123 aglomerações urbanas no Brasil, e estimamos especificações de demanda e oferta, assim como uma forma reduzida que descreve o tamanho das cidades e seu crescimento. Os principais resultados do estudo são que acréscimos na oferta da população rural, melhorias na conexão de transporte inter-regional e aumento na educação da força de trabalho têm impactos positivos no crescimento das cidades. Averiguou-se também que crime e violência, mensurados pela taxa de mortalidade, são negativos ao crescimento das cidades. Por outro lado, uma maior parcela do setor privado no capital industrial na economia local estimula tal crescimento. Utilizando os resíduos das estimativas das equações de crescimento, nós verificamos que cidades melhores administradas em termos de regulação fundiária e leis de zoneamento apresentam um crescimento mais acentuado. Por fim, nossas estimativas de políticas públicas mostram que investimentos em transporte de cidades grandes em direção a cidades médias não fornecem ganhos significativos para a performance urbana nacional.
    Date: 2015–01
  4. By: Elena Vakulenko (-)
    Abstract: We analyze the impact of migration on wage, income and the unemployment rate. Using the official Russian statistical database from 1995 to 2010, we calculate a dynamic panel data model with spatial effects. There is a positive spatial effect for wage, income and unemployment rate. There is no significant impact of migration on the unemployment rate. We find a negative relationship between net internal migration and both wages and income, which is explained by the positive effect of emigration and negative effect of immigration for income. However, the migration benefits are not big enough to make a difference on the Gini index across regions. We conclude that migration does not affect the regional -convergence of economic indicators.
    Keywords: convergence, migration, wage, income, unemployment rate, spatial dynamic panel data models
    JEL: R23 C23
    Date: 2015–03–06
  5. By: Paolo Veneri
    Abstract: This paper presents an analysis of urban spatial structure and its trends in the OECD between 2001 and 2011. It does so by using a standardised definition of urban areas in 29 OECD countries as composed of high density cores and their respective commuting zones. While urban population is growing everywhere, the way in which populations locate throughout the urban space differs across OECD cities and countries. The prevalent trend is an increasing dispersion of the population, with growth taking place outside existing centres. However, in specific countries, there are cities experiencing a higher growth in their central cores, while others are strengthening their polycentric structures. Overall, the population has grown more in relatively low-density locations close to the main centre, but outside it. Closeness to sub-centres also proves to be a strong advantage for growth and suggests the emergence of new centralities shaping urban spatial structures.
    Keywords: polycentricity, Urban spatial structure, suburbanization, sprawl
    JEL: R10 R12 R14
    Date: 2015–04–03
  6. By: Kenneth M. Chomitz; Daniel da Mata; Alexandre Carvalho; João Carlos Magalhães
    Abstract: There was substantial spatial variation in labor market outcomes in Brazil over the 1990’s. In 2000, about one fifth of workers lived in apparently economically stagnant municipios where real wages declined but employment increased faster than the national population growth rate. More than one third lived in apparently dynamic municipios experiencing both real wage growth and faster-than-average employment growth; these areas absorbed more than half of net employment growth over the period. To elucidate this spatial variation, we estimated spatial labor supply and demand equations describing wage and employment changes of Brazilian municípios. We used Conley’s spatial GMM technique to allow for instrumental variable estimation in the presence of spatially autocorrelated errors. Chief findings include: a very strong influence of initial workforce educational levels on subsequent wage growth (controlling for possibly confounding variables such as remoteness and climate); evidence of positive spillover effects of own-municipio growth onto neighbors’ wage and employment levels; an exodus from farming areas; relatively elastic response of wages to an increase in labor supply; and evidence of a local multiplier effect from government transfers. O mercado de trabalho brasileiro apresentou uma dinâmica espacial diversa durante a década de 1990. Em 2000, aproximadamente um quinto dos trabalhadores vivia em municípios aparentemente estagnados em termos econômicos, em que os salários reais caíam, mas em que o emprego crescia acima da taxa de crescimento populacional do Brasil. Por outro lado, mais de um terço dos trabalhadores vivia em municípios dinâmicos, com crescimento dos salários reais e crescimento do emprego acima do crescimento populacional brasileiro: essas áreas absorveram mais da metade do crescimento líquido do emprego durante o período. A fim de elucidar essa dinâmica, o presente artigo estimou um modelo espacial de demanda e oferta por trabalho no qual descreve as mudanças no nível de salários e empregos dos municípios. Foi utilizado o método GMM espacial desenvolvido por Conley (1999), que permite o uso de variáveis instrumentais na presença de autocorrelação espacial. Os principais resultados incluem: a influência muito forte do nível educacional inicial da força de trabalho na taxa de crescimento subseqüente dos salários (mesmo após controlar por diversas variáveis, tais como distância e clima); presença de efeitos de transbordamento positivos do crescimento do município sobre os níveis de salário e emprego de seus vizinhos; queda no emprego em atividades rurais; elasticidade na resposta dos salários a um aumento na oferta de trabalho; e presença de efeitos multiplicadores das transferências governamentais.
    Date: 2015–01
  7. By: Hiroshi Goto (Research Institute for Economics & Business Administration (RIEB), Kobe University, Japan); Keiya Minamimura (Graduate School of Economics, Kobe University)
    Abstract: To explain the links between population distribution and economic integration, we construct a spatial economics model with endogenous fertility. A higher population concentration increases real wages and child-raising costs, thus lowering the fertility rate. However, people migrate to more populated regions to obtain higher real wages. We show that mobility across regions results in more people flowing into highly populated regions, but lowers fertility rates there. The population growth path resembles a logistic curve in the early phase, but population decreases in the last phase. Additionally, economic integration leads to population concentration and decreases population size in the whole economy.
    Keywords: Population change, Migration, Agglomeration, Trade freeness
    JEL: F15 J13 R12 R23
    Date: 2015–04
  8. By: Alexandre Carvalho; Daniel da Mata; Kenneth M. Chomitz
    Abstract: We describe econometric techniques to treat spatial autocorrelation in multiequation cross-section models. The cross-section approaches discussed here are heavily based on the spatial GMM procedure, proposed by Conley (1999). An extension for fullinformation instrumental variable models is presented. Monte Carlo simulations are employed in order to verify some asymptotic properties of the Spatial GMM approach. The simulations suggest that, even in the presence of spatial nonstationarity, the spatial GMM still delivers valid standard errors. Besides, usual t-statistics appear to have a standard normal distribution. An application for estimating labor and wage equations to study regional growth and development of the Brazilian municipalities, between 1991 and 2000, is presented. Neste artigo, nós descrevemos técnicas econométricas para tratar autocorrelação espacial em modelos multiequacionais, com dados em cross-section. Os procedimentos abordados aqui se baseiam no método de momentos generalizados espacial (GMM espacial) proposto em Conley (1999). Uma extensão para estimação com variáveis instrumentais com informação plena é apresentada. Nós empregamos simulações de Monte Carlo para verificar as propriedades assintóticas dos estimadores descritos. As simulações sugerem que, mesmo na presença de heterogeneidade espacial, o GMM espacial apresenta erros padrões apropriados. Além disso, estatísticas t usuais parecem seguir a distribuição normal padronizada. Finalmente, nós apresentamos uma aplicação, em que são estimadas equações de salário para estudar crescimento e desenvolvimento regional nos municípios brasileiros, entre 1991 e 2000.
    Date: 2015–01
  9. By: Michal Bernard Pietrzak (Nicolaus Copernicus University)
    Abstract: According to Tobler’s first law of geography, one of the key issues in doing the regional research is considering spatial location. Therefore, the article presents a proposal for modifying the TOPSIS method, which allows the spatial dependence to be considered in the research. The composite index calculated by means of the modified TOPSIS method allows to determine the trend in the level of the development of the phenomenon under study, assuming the impact of the spatial mechanisms. The TOPSIS method defined in that way has been applied in the spatial analysis of the situation on the labour market in Poland.
    Keywords: regional research, spatial econometrics, spatial dependence, TOPSIS method
    JEL: C21 E24 J01
    Date: 2015–04
  10. By: Dani Gamerman; Ajax R. B. Moreira; Havard Rue
    Abstract: Space-varying regression models are generalizations of standard linear models where the regression coefficients are allowed to change in space. The spatial structure is specified by a multivariate extension of pairwise difference pri- ors thus enabling incorporation of neighboring structures and easy sampling schemes. Different sampling schemes are available and may be used in an MCMC algorithm. These schemes are compared in terms of chain autocor- relation and resulting inference. We also discuss different prior specifications that accommodate the spatial structure. Results are illustrated with simulated data and applied to a real dataset. Os modelos de regressão com parâmetros variando no espaço são uma generalização dos modelos lineares em que é permitido aos coeficientes da regressão mudarem ao longo do espaço. A estrutura espacial é especificada por uma extensão multivariada de uma distribuição a priori que considera as diferenças entre os coeficientes de regiões vizinhas. Isso permite a incorporação da informação da vizinhança espacial. Para estimar o modelo utilizamos a abordagem bayesiana e o algoritmo do MCMC considerando diferentes esquemas de amostragem. Esses esquemas foram comparados em termos da autocorrelação da cadeia de Markov, e em termos dos resultados obtidos. Foram discutidas diferentes especificações a priori que admitem estruturas espaciais semelhantes. Os resultados são ilustrados com dados simulados e com um conjunto real de informações.
    Date: 2015–01

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