Network Games
For long time my research has focused on Game Theory. At present, I'm working on social network models from the point of view of GT. This is an active area of research in the last years. A complete review of this literature can be found in the work by S. Goyal, Connections: An Introducction to the Economics of Networks (Princeton University Press, New Jersey, 2007) and in the work by M. O. Jackson, Social and Economic Networks (Princeton University Press, New Jersey, 2008).
Integration
The advance of globalization has received a great deal of attention for some years now. However, to date, no consensus has been reached on the level of globalization attained and how far we are from completing it. A recent state of the art revision of the economic globalization indicators undertaken by the OECD, 2005 clearly shows that the current indicators do not reflect the new reality. Its conclusion is that there is no connection between the importance that globalization has acquired and the improvements in the available indicators, which are inordinately based on the old concept of market openness (Measuring globalisation. OECD handbook on economic globalisation indicators. Statistics. Paris: OECD Publishing)
Measuring globalization requires a Standard of International Integration as a benchmark that a single world space would reach under conditions of geographic neutrality. We consider an extension of Iapadre's concept of geographic neutrality: where the flow from one region to another depends only on their relative sizes ((Regional integration agreements and the geography of world trade: Measurement problems and empirical evidence. In P. De Lombaerde (Ed.), Assessment and measurement of regional integration (pp. 65-85). London: Routledge). We present indicators for openness, connectedness and integration, for each specific economy, and for the world economy; and we apply these indexes to international trade and finantial flows.
Valuating residential real state
Mass appraisal, or the automatic valuation of a large number of real estate assets, has attracted the attention of many researchers, who have mainly approached this issue employing traditional econometric models such as Ordinary Least Squares (OLS). However, this method does not consider the hierarchical structure of the data and therefore assumes the unrealistic hypothesis of the independence of the individuals in the sample. This paper proposes the use of the Hierarchical Linear Model (HLM) to overcome this limitation. The HLM also gives valuable information on the percentage of the variance error caused by each level in the hierarchical model. We applying HLM to a large dataset of apartments, which included different variables belonging to three hierarchical levels: apartment, neighborhood and city.
