Análisis de Estructuras Espaciales Persistentes. Desempleo Departamental en Argentina.

Herrera Gómez, Marcos (2013): Análisis de Estructuras Espaciales Persistentes. Desempleo Departamental en Argentina.

Abstract

This paper presents a collection of spatial econometrics tools to detect global and local spatial dependence. These tools are used to analyze the spatial structure of the unemployment rate in Argentina in Census 2001 and 2010. Detailed study enables identification and comparison of persistent spatial structures in the departamental distribution of unemployment.

• Item Type: MPRA Paper
• English Title: Persistent Spatial Structure Analysis. Regional Unemployment in Argentina.
• Language: Spanish
• Keywords: Spatial Autocorrelation, LISA, Getis-Ord Test, Symbolic Entropy, Unemployment
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions; J - Labor and Demographic Economics > J6 - Mobility, Unemployment, Vacancies, and Immigrant Workers > J64 - Unemployment: Models, Duration, Incidence, and Job Search

References

Anselin, L. (1988). Spatial Econometrics: Methods and Models. Dordrecht: Kluwer.

Anselin, L. (1995). “Local Indicators of Spatial association-LISA,” Geographical Analysis, 27, pp. 93-115.

Anselin, L. y A. Bera (1998). “Spatial Dependence in Linear Regression Models with an Introduction to Spatial Econometrics,” en A. Ullah y D. Giles (eds.), Handbook of Applied Economic Statistics. New York: Marcel Dekker.

Bertola G. e I. Ichino (1995). "Wage Inequality and Unemployment: United States versus Europe," NBER Macroeconomics Annual 1995, 10, pp. 13-66. National Bureau of Economic Research, Inc.

Blanchard, O. y L. Katz (1992). “Regional Evolutions,” Brookings Papers on Economic Activity, 1, pp.1-75. [6] Boots, B. (2003). “Developing Local Measures of Spatial Association for Categorical Data,” Journal of Geographical Systems, 5, pp. 139-160.

Carlstein, E. (1986). “The Use of Subseries Methods for Estimating the Variance of a General Statistic from a Stationary Time Series,” The Annals of Statistics, 14, pp. 1171-1179.

Cliff, A. D. y J. K. Ord (1969). “The Problem of Spatial Autocorrelation,” en A. J. Scott (ed.), London Papers in Regional Science 1, Studies in Regional Science. London: Pion.

Cliff, A. D. y J. K. Ord (1973). Spatial Autocorrelation. London: Pion.

Cliff, A. D. y J. K. Ord (1981). Spatial Processes, Models and Applications. London: Pion.

Cressie, N. (1993). Statistics for Spatial Data. Revised edition. New York: Wiley.

Decressin, J. y A. Fatás (1995). “Regional Labor Marker Dynamics in Europe,” European Economic Review, 39, pp. 1627-1655.

Díaz Cafferata, A. y A. Figueras (1996). “Dimensión Espacial de la Desocupación en Argentina. Alternativas de Regionalización,” Documento de Trabajo, AAEP.

Elhorst, P. (2003). “The Mystery of Regional Unemployment Differentials: Theoretical and Empirical Explanations,” Journal of Economic Surveys, 17, pp. 709-748.

Faini, R., Galli, P. y F. Rossi (1997). “An Empirical Puzzle: Falling Migration and Growing Unemployment Differentials Among Italian Regions,” European Economic Review, 41, pp. 571-579.

Galiani, S., Lamarche, C., Porto, C. y W. Sosa Escudero (2004). “Persistence and Regional Disparities in Unemployment (Argentina 1980–1997),” Regional Science and Urban Economics, 35, pp. 375-394.

Geary, R. (1954). “The Contiguity Ratio and Statistical Mapping,” The Incorporated Statistician, 5 (3), pp. 115-145.

Getis, A. (1995). “Spatial Filtering in a Regression Framework: Experiments on Regional Inequality, Government Expenditures, and Urban Crime,” pp. 172-188, en Anselin, L. y R. Florax (eds). New Directions in Spatial Econometrics. Springer, Berlin, Germany

Getis, A. y J. Ord (1992). “The Analysis of Spatial Association by Use of Distance Statistics,” Geographical Analysis, 24, pp. 189-206.

Getis, A. y J. Ord (1996). “Local Spatial Statistics: An Overview,” en Longley, P. y M. Batty (eds), Spatial Analysis: Modelling in a GIS Environment. Cambridge: GeoInformation International.

Griffith, D. (2000). “A Linear Regression Solution to the Spatial Autocorrelation Problem,” Journal of Geographical Systems, 2, pp. 141-156.

Hall, P. (1985). “Resampling a Coverage Pattern,” Stochastic Processes and Their Applications, 20, pp. 231-246.

Herrera, M., Ruiz, M. y J. Mur (2013). “Detecting Dependence between Spatial Processes,” Spatial Economic Analysis, forthcoming.

Jimeno, F. y S Bentolila (1998). “Regional Unemployment Persistence (Spain, 1976-1994),” Labour Economics, 5, pp. 25-51.

Lamarche, C., Porto, A. y W. Sosa Escudero (1998). “Aspectos Regionales del Desempleo en la Argentina”, Documento de Trabajo Nº 8, Depto. de Economía, Facultad de Cs. Es., Universidad Nacional de La Plata.

Lesage, J. y K. Pace (2009). Introduction to Spatial Econometrics. Boca Raton: CRC Press.

Molho, I. (1995). “Spatial Autocorrelation in British Unemployment,” Journal of Regional Science, 35, pp. 641-658.

Moran, P. (1948). “The Interpretation of Statistical Maps,” Journal of the Royal Statistical Society B, 10, pp. 243-251.

Moran, P. (1950). “Notes on Continuous Stochastic Phenomena,” Biometrika, 37 (1), pp. 17-23.

Ord, J. y A. Getis (2001). “Testing for Local Spatial Autocorrelation in the Presence of Global Autocorrelation,” Journal of Regional Science, 41, pp. 411-432.

Overman, H. y D. Puga (2002). “Unemployment Clusters across Europe’s Regions and Countries,” Economic Policy, Abril, pp. 117-147.

Ruiz, M., López, F y A. Páez (2012). “Comparison of Thematic Maps using Symbolic Entropy,” International Journal of Geographical Information, 26(3), pp. 413-439.

Taylor, J. y S. Bradley (1997). “Unemployment in Europe: A Comparative Analysis of Regional Disparities in Germany, Italy and the U.K.,” Kyklos, 50, pp. 221-245.