Patricio Aroca

Growth Dynamics and Space in Brazil

The authors bring together two strands of the empirical literature and analyze the geography of the regional economic performance of the states of the Brazilian Federation from 1939 to 1998. Using tools from spatial statistics, they examine the spatial dependence of regional per capita income in Brazil during the past six decades. They also examine the role of geography in explaining economic growth patterns using intradistribution dynamic tools based on Markov transition matrices and stochastic kernels in a discrete and a continuous framework. The analyses reveal the existence of two spatial clusters in Brazil, a low-income cluster in the northeast and a high-income cluster in the southeast. Moreover, the spatial pattern of economic growth in Brazilian states cannot be viewed without accounting for spatial spillovers. The authors show that states with relatively rich neighbors have a greater chance of being prosperous.

La conmutación regional en Chile y su impacto en la Región de Antofagasta

La distancia creciente entre el lugar de residencia y el de trabajo ha dado lugar a flujos de conmutacion entre regiones cuyo impacto en las economias locales ha sido poco estudiado hasta ahora. En este articulo se analiza la magnitud de este fenomeno en Chile y se estima su impacto en el bienestar de la economia de Antofagasta, una region chilena caracterizada por recibir una gran cantidad de trabajadores que viven en otras regiones. Los resultados, obtenidos a partir de un modelo insumo-producto extendido, muestran que los efectos indirectos de este tipo de conmutacion en la demanda regional tienen una incidencia negativa y significativa en la generacion de ingresos y la creacion de empleo en las regiones que solo son atractivas para trabajar. Con ello se pone de manifiesto la relevancia que tienen las estrategias de desarrollo local orientadas a crear lugares atractivos para vivir.

Are vertical linkages promoting the creation of a mining cluster in Chile? An analysis of the SMEs' practices along the supply chain

In regions whose industrial structure is organized around one or more large firm corporations, the best practices of small and medium enterprises depend on where firms are located in the supply chain. This paper studies 351 small and medium enterprises in the Antofagasta Region in Chile between 2007 and 2008, where multinational and public mining companies are the drivers of the local economy and the government is promoting the formation of a mining cluster. Structural equation model is used to show that first-tier small and medium enterprise mining suppliers, directly related to large corporations, follow business practices that promote international certification, quality control, and investment in innovation, while in contrast second-tier small and medium enterprises are more focused on avoiding insolvency and client orientation. These results cast doubt on the formation of a mining cluster in the region and suggest the need for differentiated policies in these two groups of small and medium enterprises, especially those related to knowledge transfer.

Regional Growth and Convergence in Chile 1960–1998: The Role of Public and Foreign Direct Investment

The purpose of this chapter is to re-examine the convergence process in Chile, utilizing more recent data and focusing on the role of public (domestic) and foreign direct investment in shaping the welfare levels across regions. There have been many prior studies focusing on the problem of regional convergence in Chile. Morande et al. (1996) argue that some evidence is found to support regional GDP/pc absolute convergence in Barro-style estimations for the period 1960–1992. Here, they estimated that convergence occurred at an annual rate of 1.2%. However, the same authors find that using time series analysis results raises doubts about the convergence properties derived from their equation system. Fuentes (1996) obtains similar results postulating an annual convergence rate of 1.3%; in addition, he also estimated convergence rates with income per capita data, and found this to be much higher, of the order of 7.4% per annum.

Escalas de producción en economías mineras: El caso de Chile en su dimensión regional

An important share of Chilean copper production is located in two regions: Antofagasta and Atacama. In recent years there has been a rise in the price of copper, and the incomes of the inhabitants of these regions have varied differently as a response to the variations in the price of copper. This article analyzes these differences between the evolution of regional income based on the size or scale of production in the mining sector. Using an input-output model disaggregated by the scale of production (large versus small and medium-sized scales) of the mining sector for each region, linkages and multipliers have been calculated and a sensitivity analysis carried out in order to test the strength of the estimations. This strategy allowed for identifying and calculating the impact of each scale on local income and production, showing the heterogeneous impact of the mining sector on local economies, which is very relevant for evaluating the current Chilean mining policy.

ECONOMÍAS AISLADAS, PEQUEÑAS Y DEPENDIENTES DE COMMODITIES: EL CASO DEL PETRÓLEO Y METANOL EN LA COMUNA DE PUNTA ARENAS, CHILE.

Punta Arenas es una comuna ubicada en el extremo sur de Chile, cuya economia se basa en la produccion de dos materias primas ( commodities ): petroleo y metanol. En este contexto, el objetivo principal de este articulo es estimar el impacto de estas materias primas sobre la produccion, el ingreso y el empleo de la comuna, en donde la importancia relativa de la produccion de estas materias primas ha estado cambiando del petroleo al metanol. Usando una matriz input-ouput, demostramos que, los encadenamientos de estas materias primas, en economias que son pequenas y aisladas generan un bajo impacto en la produccion e ingreso. Adicionalmente, se detecta que mientras los encadenamientos de empleo son grandes, se observa que el nivel del mismo en estas industrias es muy bajo respecto al total de empleados de Punta Arenas.

Tourism statistics: Correcting data inadequacy

Tourism statistics are key sources of information for economic planners, tourism researchers, and operators. Still, several cases of data inadequacy and inaccuracy are reported in literature. The aim of this article is to propose a methodology useful to improve tourism statistics: a modified version of the Coarsened Exact Matching. The methodological steps herein proposed provide tourism statisticians and authorities with a tool to improve the reliability of available sample surveys. Data from a Chilean region are used to illustrate the method. This study contributes to the realm of tourism statistics literature in that it offers a new methodological approach to the creation of accurate and adequate tourism data.

Applying weights to correct distortions in a non-random sample: an application to Chilean tourism time series data.

Statistics that accurately represent the evolution of tourism activity are needed for tourism research and planning. Monthly accommodation statistics provided by the Chilean Statistical Institute show a negative trend despite considerable growth in the number of foreign visitors. This paper proposes a methodology to create sample weights to overcome statistics inaccuracy caused, as in the case of Chilean tourism statistics, by the use of a non-random sample with serious attrition bias. The benefits of the methodology are discussed, highlighting their relevance to a broader range of applications where tourism statistics are questionable or demonstrably inaccurate.

Desarrollo de una base de datos integrada de Censo y encuesta mediante el uso de elementos de inteligencia de negocios y SIG

In this paper, we propose a solution development of Business Intelligence and Geographic Information Systems (SIG) to an integrated management of information generated from Census of population, households and dwellings, and the Survey of Economic and Social Classification (CASEN). This, as an alternative to current methods in small area estimation (SAE) that are used to obtain disaggregated welfare indicators and estimate, for example, the income from the household attributes, ignoring the geographical location of the observations in the Survey. In this paper, we propose a change in the traditional implicit logic in these methods, to estimate the average income in small areas, georeferencing the survey observations using the matching method known as Matching Estimator and then extrapolating data using the Kriging prediction technique. The proposal suggests the use of an integrated database of both sources allowing to obtain data from the survey of economic characterization at levels of disaggregation not originally provided and are transferred by pairing with census data. Using spatial location codes incorporated into a SIG, cartographic visualization tools are added, which facilitates the observation and analysis of spatial relationships among geographic units, as well as observation and analysis of particularities in small areas. As an application, we describe the per capita spatial disaggregation income of households in Regions XIII, VI and VII of Chile

Matching espacial para georreferenciar datos de encuestas de hogar

Spanish Abstract: Este trabajo desarrolla una metodologia de inteligencia de negocios (data warehouse) y herramientas OLAP (Online Analytical Processing) para parear individuos de una encuesta de hogares con los del censo. Para georreferenciar los datos de los hogares, el metodo aprovecha la informacion geografica del censo. Usando la Encuesta de Hogares de 2003 y el Censo de Poblacion y Vivienda de Chile 2002, se estima el ingreso promedio familiar en niveles intramunicipales y los resultados se comparan con la metodologia Elbers et al. (2003). Los resultados muestran que la metodologia propuesta permite tener en cuenta la heterogeneidad intramunicipal y mostrar el impacto y la interaccion espacial entre las unidades espaciales. English Abstract: This paper develops a methodology using business intelligence (data warehouse) and OLAP tools (Online Analytical Processing) to match individuals from a household survey data to a census one. In order to geo-reference the household data, the method takes advantage of the geographical information of the census. Using the 2003 Household Survey and the 2002 Chilean Census of Population and Housing, the average household income is projected to intra-municipality levels and the results are compared to Elbers et al. (2003) methodology. The results show that the proposed methodology allows for taking into account and display the impact of intra-municipality heterogeneity and the spatial interaction among the spatial units.