María Jesús Delgado Rodríguez

Análisis de las relaciones entre los ciclos económicos internacionales

En anos recientes los estudios sobre ciclos economicos a nivel mundial, han recobrado importancia debido a las sucesivas contracciones y crisis economicas que se han producido en el contexto internacional y que han producido efectos muy diferentes en los paises y regiones del mundo. A esto se une el interes que suscitan la variedad en las tecnicas para extraer el ciclo economico y la disponibilidad de estadisticas que permiten ampliar el numero de paises estudiados. Los trabajos en esta linea se han centrado fundamentalmente en analizar la sincronizacion entre los ciclos con estudios de la Union Europea (EU), para ver si ante medidas de politica estabilizadoras, todos los paises miembros reaccionan igual y sufren las mismas consecuencias; destacando los trabajos de Harding y Pagan (2002), Artis, Marcellino y Proetti (2004), Camacho, Perez-Quiros y Saiz (2005, 2006) y Krolzing y Toro, 2005; o bien, en los paises del G7 mostrando una mayor estabilidad del ciclo economico de estos paises en las ultimas dos decadas (Stock y Watson, 2003), y en la OCDE (Cancelo y Uriz, 2001; Cotis y Copel, 2005). Sin embargo, son pocos los trabajos que tratan de evaluar el ciclo a nivel mundial como el informe del Fondo Monetario Internacional (FMI) de octubre de 2007, que recoge un analisis exhaustivo de los cambios en la dinamica de un ciclo economico global para 133 paises. En este articulo se presentan las principales herramientas para el analisis de los ciclos que permitiran obtener una vision general del ciclo internacional, en terminos del ciclo economico del PIB per capita, siendo el indicador de actividad economica mas utilizado en este tipo de estudios. Para captar el movimiento sincrono de las fluctuaciones ciclicas del producto entre los distintos paises se utiliza un modelo de factores comunes sinteticos (inobservables), basado en el porcentaje de la varianza del producto que puede atribuirse a dichos factores. Eso nos ayudara a entender las relaciones existentes en la economia mundial.

Contribution of economic theory to the cyclical crisis: State of art in historical perspective

The aim of this article is to provide a state of the art of the contribution of economic theory to the understanding of the important economic crises of the 21st century. We this aim, we review models of economic cycle with a historical perspective and highlights the changes that have experienced. This analysis incorporates an overview of how the empirical analysis in the Spanish case has been addressed. This review highlights the economic complexity faced by the countries in the face of new crisis and the relevance of studying their causes. In this article we intend to present the key elements that contribute to the understanding of economic crisis and to contextualize their adjustment mechanisms.

Core-Periphery Business Cycle Synchronization in Europe and the Great Recession

This article investigates the dynamics of business cycle synchronization in Europe. The European core business cycle is estimated by means of a cyclical trend decomposition model, and a testing procedure is proposed to study the stability of the interdependencies between the GDP growth rates of the economies and the cyclical common factor. Results show an extended European business cycle moving toward the synchronization levels enjoyed by core countries. In a second group of periphery economies (mainly economies of the EU enlargements of the 2000s) synchronization has increased since the beginning of the Great Recession.This article investigates the dynamics of business cycle synchronization in Europe. The European core business cycle is estimated by means of a cyclical trend decomposition model, and a testing procedure is proposed to study the stability of the interdependencies between the GDP growth rates of the economies and the cyclical common factor. Results show an extended European business cycle moving toward the synchronization levels enjoyed by core countries. In a second group of periphery economies (mainly economies of the EU enlargements of the 2000s) synchronization has increased since the beginning of the Great Recession.

La ampliación de la UE hacia el Este: análisis del proceso de convergencia con una perspectiva mundial

This article analyzes the economic convergence in the countries of Central and Eastern Europe from a broad perspective, which will provide comparative evidence on the process of convergence for the different world regions. The extensive coverage of the database will make possible to assess the trajectory of the countries of Central and Eastern Europe before and after joining the EU. In this analysis we will apply the methodology of panel data in order to compare the results and expand the available evidence. The evidence shows that the European convergence process is maintained after the entry of the countries of Central and Eastern Europe in the European Union. Furthermore, it appears that this group of countries have managed to intensify the process of convergence in the period studied and this group of countries achieving one of the more favorable results among the world regions.

Speed of Convergence And Economic Policy Instruments.

This article presents an innovative methodology to empirically evaluate the response of the rate of convergence in the neoclassical growth model to changes in the conditional factors. We apply this method to test the sensitivity of the speed of convergence in the EU-15 during the period 1980-2002 to increases in human and public capital. INTRODUCTION The relation between private productivity and policy instruments has been a topic of considerable interest in the literature on economic development. A key aspect in the literature on convergence has been the determination of the speed of convergence towards the stationary state. This is determined by its own structural characteristics, among which technology, public policies and the population growth rate are included. Recently, in the debate on convergence, the role played by these conditioning factors has gained prominence – primarily public policy instruments – with the objective of establishing whether part of the observed convergence (if any) can be attributed to these instruments. In the context of the EU, development and cohesion policies have primarily supported public investment in infrastructures and in education, in addition to support policies for the private sector during the last 20 years. The analyses carried out suggest that these efforts have contributed positively to the process of convergence in productivity in the EU (Salinas et al., 2006). However, recent difficulties encountered in relation to the reduction of disparities in the EU have led to questioning to what extent the speed of convergence could be altered by means of public policies in the European Union. In spite of a clear interest in this matter, few papers have analyzed the sensitivity of the speed of convergence and the majority are theoretical research papers (Turnovsky, 2002, Gokan, 2003, Klump et al., 2008). Unlike these works, in this article a methodological proposal is put forth to estimate the response of the speed of convergence in the EU to changes in economic policy instruments. The analysis proposes two scenarios of convergence: the first one will make it possible to estimate the effect on the speed of convergence arising from changes in the instruments in the EU as a whole; and a second scenario where the effect on the speed of convergence resulting from changes in each one of the countries is considered separately. In this way an attempt will be made to identify not only the potential of various public policies to influence European convergence, but also the role they may play in each country toward achieving convergence in the EU. The proposal develops various scenarios with Matlab that will make it possible to evaluate the sensitivity of the parameter of convergence in the face of variations in the analyzed determining factors, while the other factors remain ceteris paribus. The article is structured as follows: in the next section, the proposal for empirically evaluating the sensibility of the speed of convergence in the face of changes in the conditioning factors is presented. Section 3 describes the data and presents the findings. Finally, in Section 4, the primary conclusions are presented. CONDITIONAL CONVERGENCE AND SENSITIVITY ANALYSIS As of the research carried out by Mankiw et al. (1992) and Barro y Sala-i-Martin (1995), the neoclassical growth model is commonly used in order to contrast Proceedings 23rd European Conference on Modelling and Simulation ©ECMS Javier Otamendi, Andrzej Bargiela, Jose Luis Montes, Luis Miguel Doncel Pedrera (Editors) ISBN: 978-0-9553018-8-9 / ISBN: 978-0-9553018-9-6 (CD) conditional convergence. The metodology proposed to examine the response of the rate of convergence consists of the estimation of the convergence equation, recovery of the structural parameters and evaluate the sensibility of the parameter of convergence under specific assumptions about changes in the model. In addition, we simulate those changes In the estimation of the model we used the routine programming in Matlab available in http://www.spatialeconometrics.com/. The simulations programming in Matlab for this work are available on requestby introducing an extension in the neoclassical growth model. To do so, the fixed effects model provides the basis -. The estimation method is determined by the Matlab programming used to perform the sensitivity analysis. Since GMM approach is suitable to deal with growth models in empirical work, we have also estimated the model with this method and we have reached similar results -, where it is assumed that each explanatory variable has a single coefficient; that is, it has the same effect on the dependent variable, while each individual variable has a different constant which represents the individual effect. Formally, the model to be estimated is the following: , , 1 , , , 1 ln ln( ) ln( ) i t i t i t i i t i t y y x u y                    ;(1) where it y is the annual GDP per employee of 1, ,   i N countries (N=15) and for an annual period of 1, ,   t T (T=22 from 1980 until 2002); , i t x is a vector of 1  k explanatory variables; i  is the individual effect; and , i t u is a disturbance term. In this case, the concept of conditioned convergence is analyzed by introducing heterogeneity in the model by means of the introduction of fixed effects and/or the effect of other variables, , i t x , assuming that the fixed effects i  are correlated with them. The estimation of the model (1) is carried out in deviations with respect to the mean using Ordinary Least Squares (OLS), making it possible to consistently estimate the parameters of the model associated with convergence-β and with the explanatory variables since its consistency will not depend on the specification of fixed effects i  which have been eliminated with the transformation. This estimation is also equivalent to estimating with the OLS model (1) or the model with the variables transformed by orthogonal deviations, a transformation proposed by Arellano (1988) Given the model , , , i t i t i i t y x u      he defines the transformation in orthogonal deviations as: , , ,( 1) , ( 1) 1 ( ) ( 1) i t i t i t i T T t y y y y T t T t                   -. The extension of the estimated model (1) takes place through the introduction of changes (simulated increases) in exogenous variables of interest. The simulated increases are based on the minimum of the selected variable and they continue increasing with a fixed value, inc , until reaching a maximum value that, in this case, has been fixed at 100%, since the variables are taken as the percentage of GVA; but both the minimum value as well as the maximum value could be modified with absolute flexibility. The variations generated with Matlab are then placed in rows, until they complete a column, and they continue being placed in the first row of the next column until it has been completed as has been mentioned above and the same process continues likewise until a maximum value of 100% is reached. Therefore, the number of columns will depend on the increase inc selected, which in our paper is 5%. Furthermore, the analysis of the variations has been approached in two ways: a. Evaluating variations of all of the countries at the same time: 1,1 2,1 1, ,1 1, 1,2 1,1 2,2 2,1 ,2 ,1 1 1, 1 2, 2, 1 , min( ) ( ) 100% t T S S T S S t T S T T T T S T X inc inc inc inc inc X inc inc 