Carmen Ramos Carvajal

Core/periphery structure models: An alternative methodological proposal

Abstract The idea of a structure made up of a core and periphery is a common, classic paradigm in many fields of science. Following this line, in 1999, researchers Stephen Borgatti and Martin Everett developed a model of structural analysis based on the delimitation of a core formed by a group of densely connected actors, in contrast to a class of actors, more loosely connected and forming the periphery of the system. The original approach of these authors is modified, employing measures that, in our opinion, show a larger degree of coherence and accuracy in the proposed objectives.

The impact of immigration on interregional migrations: an input–output analysis with an application for Spain

Developed countries in general, Spain in particular, have experienced a dramatic rise in the reception of foreign workers in the last decade. Among all the economic and social effects originated by the arrivals of immigrants, the literature has paid some attention to the potential effect that this immigration can produce on the internal migration patterns (the so-called “displacement effect”). This paper proposes the use of a multi-region input–output model of migrations for measuring how the reception of immigrants in one region displaces population among all the regions included in the model. From some basic assumptions, the input–output methodology proposed describes how the arrival of one immigrant in one region i, by the dissemination of internal population from i, generates indirect effects on other region j. To illustrate the methodology proposed in the paper, an empirical application for Spain is also included.

Adjustment of Input–Output Tables from Two Initial Matrices

The compilation of the information required to construct survey-based input–output (I–O) tables consumes resources and time to statistical agencies. Consequently, a number of non-survey techniques have been developed in the last decades to estimate I–O tables. These techniques usually depart from observable information on the row and column margins, and then the cells of the matrix are adjusted using as a priori information a matrix from a past period (updating) or an I–O table from the same time period (regionalization). This paper proposes the use of a composite cross-entropy approach that allows for introducing both types of a priori information. The suggested methodology is suitable to be applied only to matrices with semi-positive interior cells and margins. Numerical simulations and an empirical application are carried out, where an I–O table for the Euro Area is estimated with this method and the result is compared with the traditional projection techniques.