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SPATIAL ISSUES RELATED TO MY RESEARCH: Agglomeration, migrations and the role of human capital. An analysis for the Span

19th Advanced Summer School in Regional Science GIS and Spatial Econometrics University of Groningen 4-12 July 2006. SPATIAL ISSUES RELATED TO MY RESEARCH: Agglomeration, migrations and the role of human capital. An analysis for the Spanish Provinces. Rosa Sanchis-Guarner Herrero.

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SPATIAL ISSUES RELATED TO MY RESEARCH: Agglomeration, migrations and the role of human capital. An analysis for the Span

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  1. 19th Advanced Summer School in Regional Science GIS and Spatial Econometrics University of Groningen 4-12 July 2006 SPATIAL ISSUES RELATED TO MY RESEARCH:Agglomeration, migrations and the role of human capital.An analysis for the Spanish Provinces. Rosa Sanchis-Guarner Herrero Grup d’Anàlisi Quantitativa Regional Institut d’Economia Aplicada Regional i Pública

  2. 1. MY RESEARCH: What? • In my research I try to analyse • MIGRATORY INTER-PROVINCIAL MOVEMENTS • Under a NEG framework (forward linkage) • Considering the role played by HUMAN CAPITAL • I do it for the Spanish provinces in the period 1988-2002 • NEG predicts the formation of agglomerations through two mechanisms (Krugman 91, 92): Backward linkage: predicts movements of firms. Forward linkage: predicts movements –migrations- of workers towards economic agglomerations attracted by higher real wages → I focus in this mechanism.

  3. 1. MY RESEARCH: Why? • There exists little literature on NEG empirics and even less focused on the verification of the forward linkage: Crozet(2004), Poncet (2006) and Tirado et al (WP 2006). • Besides this, the migration literature has highlighted the importance of human capital on the migratory decision. • I follow the theoretical model of Crozet (2004), extending it to take into account the effect of human capital endowments of the regions. Crozet (2004) derives a migration equation that relates migrants to market potentials combining a migration model (migratory decision) and a standard NEG model (price indexes).

  4. 2. THE THEORETICAL EQUATIONS: Model with human capital • R regions; 3 sectors (traditional, manufactures and services); 2 factors of production (mobile and immobile workers) • The migration decision given by the maximization of: • The new reduced equation including human capital is: • The migrations proxy is explained by: • The manufactures and services price indexes (NEG elements) • Expected nominal wage, migratory cost (distance & borders) and hk endowments

  5. 3. THE EMPIRICAL APPLICATION: Data and gravity estimable equations • We will estimate several linear gravity equations that include a proxy for agglomerations (MP) and for human capitalendowments: • General model with human capital • Our dependent variable is the share of migrants from j to i in t : we construct it from the flows of migrants from j to i in t for the 47 Spanish peninsular provinces. • Our proxy for human capital endowments is the average years of education for the employed workers (IVIE) • We use DATA from INE and IVIE.

  6. 3. THE EMPIRICAL APPLICATION: Estimation issues and general results • As our dependent variable is in logs and we have several flows that are 0 we reformulate the model as a SAMPLE SELECTION MODEL • We use the Heckman two-step estimator to obtain the coefficients. • To quantitatively assess the effects we calculate the conditional marginal effects (on the selected sample) • Despite some data problems (autocorrelations), in some of the specifications used we find evidence that support our model.

  7. 4. SOME SPATIAL ISSUES: The spatial issues in variables • We can have problems of spatial dependence and/or spatialheterogeneity in: • The dependent variable: share of migrants from j to i in t • For instance we can have different behaviour on specific groups of regions (coast or the south) • The regressors, specially on: • wages and employment probability • employed workers spatial dependence

  8. 4. SOME SPATIAL ISSUES: The spatial issues in variables Averaged share 2001 Human capital endowment 2000

  9. 4. SOME SPATIAL ISSUES: The spatial issues in variables Employment rates in 2000 Nominal wages in 2000

  10. 4. SOME SPATIAL ISSUES: Panel structure of the dataset • I analyse migration for a panel of: • 47 provinces • 15 years (1988-2002) • Is the spatial dependence structure stable during the entire period of analysis? • For a short period this could hold, but we can’t be sure for a long period of analysis

  11. 4. SOME SPATIAL ISSUES : Migration variable constructed from flows • My dependent variable share of migrants is constructed from migration flows: • We can have spatial dependence on: • Host regions (i): from a specific province j migrants move to provinces i which are close in the space • Home regions (j): from a group of provinces j that are close in the space migrants move to a specific province i • More complicated relationships: from a group of provinces j that are close in the space migrants move to provinces i which are close in the space flows from i (home region) to j (host region)

  12. 19th Advanced Summer School in Regional Science GIS and Spatial Econometrics University of Groningen 4-12 July 2006 THANK YOU FOR YOUR ATTENTIONAgglomeration, migrations and the role of human capital.An analysis for the Spanish Provinces. Rosa Sanchis-Guarner Herrero Grup d’Anàlisi Quantitativa Regional Institut d’Economia Aplicada Regional i Pública

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