This paper presents a theoretical growth model that accounts for technological interdependence among regions in a Mankiw-Romer-Weil world. The reasoning behind the theoretical work is that technological ideas cannot be fully appropriated by investors and these ideas may diffuse and increase the productivity of other firms. We link the diffusion of ideas to spatial proximity and allow for ideas to flow to nearby regional economies. Through the magic of solving for the reduced form of the theoretical model and the magic of spatial autoregressive processes, the simple dependence on a small number of neighbouring regions leads to a reduced form theoretical model and an associated empirical model where changes in a single region can potentially impact all other regions. This implies that conventional regression interpretations of the parameter estimates would be wrong. The proper way to interpret the model has to rely on matrices of partial derivatives of the dependent variable with respect to changes in the Mankiw-Romer-Weil variables, using scalar summary measures for reporting the estimates of the marginal impacts from the model. The summary impact measure estimates indicate that technological interdependence among European regions works through physical rather than human capital externalities.

According to AK and R&D models, permanent rise in investment rates and the growing number or researchers should have permanent effects on growth rate. Charles Jones (1995a) used the lack of long-term movements in GDP and productivity growth to challenge the validity of these models. The aim of this paper is to empirically re-test these models of endogenous growth. The author follows the methods proposed by Ch. Jones (1995a) and extends the analysis for variables that could offset the movements in growth rates. The results show no support for the tested models.

Esta tesis se ocupa de los problemas de la estimación econométrica con muestras pequeñas, en los contextos del los VARs monetarios y de la investigación empírica del crecimiento. Primero, demuestra cómo mejorar el análisis con VAR estructural en presencia de muestra pequeña. El primer capítulo adapta la especificación con prior intercambiable (exchangeable prior) al contexto del VAR y obtiene nuevos resultados sobre la transmisión monetaria en nuevos miembros de la Unión Europea. El segundo capítulo propone un prior sobre las tasas de crecimiento iniciales de las variables modeladas. Este prior resulta en la corrección del sesgo clásico de la muestra pequeña en series temporales y reconcilia puntos de vista Bayesiano y clásico sobre la estimación de modelos de series temporales. El tercer capítulo estudia el efecto del error de medición de la renta nacional sobre resultados empíricos de crecimiento económico, y demuestra que los procedimientos econométricos robustos a incertidumbre acerca del modelo son muy sensibles al error de medición en los datos. / This thesis deals with the problems of econometric estimation with small samples, in the contexts of monetary VARs and growth empirics. First, it shows how to improve structural VAR analysis on short datasets. The first chapter adapts the exchangeable prior specification to the VAR context, and obtains new findings about monetary transmission in New Member States. The second chapter proposes a prior on initial growth rates of modeled variables, which tackles the Classical small-sample bias in time series, and reconciles Bayesian and Classical points of view on time series estimation. The third chapter studies the effect of measurement error in income data on growth empirics, and shows that econometric procedures which are robust to model uncertainty are very sensitive to measurement error of the plausible size and properties.