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.
The paper estimates a dynamic macroeconometric model for the US economy that captures two important features commonly observed in the study of the US business cycle, namely the strong co-movement of key macroeconomic quantities, and the distinction between expansionary and recessionary phases. The model extends the factor-augmented vector autoregressive model of Bernanke et al. (2005) by combining Markov switching with factor augmentation, modeling the Markov switching probabilities endogenously, and adopting a full Bayesian estimation approach which uses shrinkage priors for several parts of the parameter space. Exploiting a large data set for the US economy ranging from 1971:Q1 to 2014:Q2, the model is applied to measure not only the dynamic effects of unconventional monetary policy within distinct stages of the business cycle, but also the dynamic response of the recession probabilities, based on conducting counterfactual simulations. The results obtained provide new insights on the effect of monetary policy under changing business cycle phases, and highlight the importance of discriminating between expansionary and recessionary phases of the business cycle when analyzing the impact of monetary policy on the macroeconomy. (authors' abstract)
This article outlines the general architecture of a knowledge based GISystem that has the potential to intelligently support decision making in a GIS environment. The efficient and effective integration of spatial data, spatial analytic procedures and models, procedural and declarative knowledge is through fuzzy logic, expert systems and neural network technologies. A specific focus of the discussion is on the expert system and neural network components of the system, technologies which had been relatively unknown in the GIS community at the time this chapter was written.
The paper examines the application of the concept of economic efficiency to organizational issues of collective information processing in decision making. Information processing is modeled in the framework of the dynamic parallel-processing model of associative computation with an endogenous set-up cost of the processors. The model is extended to include the specific features of collective information processing in the team of decision makers which could cause an error in data analysis. In such a model, the conditions for efficient organization of information processing are defined and the architecture of the efficient structures is considered. We show that specific features of collective decision making procedures require a broader framework for judging organizational efficiency than has traditionally been adopted. In particular, and contrary to the results presented in economic literature, we show that in human data processing (unlike in computer systems), there is no unique architecture for efficient information processing structures, but a number of various efficient forms can be observed. The results indicate that technological progress resulting in faster data processing (ceteris paribus) will lead to more regular information processing structures. However, if the relative cost of the delay in data analysis increases significantly, less regular structures could be efficient. (authors' abstract)
No abstract is provided for this article.
This paper is one of a pair describing attempts to devise strategies for the effective implementation of continuing professional development for work-oriented communities of practice in Europe. The paper outlines the development of DIADOSYS: an experience-based documentation system for maintenance workers in Germany. The German discussion about experience-guided work has led to the question of how work experience can be used within the process of designing decision support systems for skilled maintenance work. Some considerations about the nature of experience and about the problems skilled workers have in acquiring work competences within computer aided production environments are introduced in order to illustrate the design philosophy of DIADOSYS: a decision support system which stimulates workplace learning by enabling.
Hydrogen is a basic feedstock of chemical technology. For decades it has been used safely on a large scale by the chemical industry where its manufacture, storage, transport and use are essentially routine.
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This chapter provides statistical evidence on the innovation system of Barcelona. The case study region comprises the communities of Barcelones, Maresme, Valles Oriental, Valles Occidental and Baix Llobregat which, from a functional point of view, form the...
No abstract is provided for this article.
In this study interest centers on regional differences in the response of housing prices to monetary policy shocks in the US. We address this issue by analyzing monthly home price data for metropolitan regions using a factor-augmented vector autoregression (FAVAR) model. Bayesian model estimation is based on Gibbs sampling with Normal-Gamma shrinkage priors for the autoregressive coefficients and factor loadings, while monetary policy shocks are identified using high-frequency surprises around policy announcements as external instruments. The empirical results indicate that monetary policy actions typically have sizeable and significant positive effects on regional housing prices, revealing differences in magnitude and duration. The largest effects are observed in regions located in states on both the East and West Coasts, notably California, Arizona and Florida.
No abstract is provided for this article.
This chapter is intended as a convenient resource for regional scientists interested in a statistical view of the neural spatial interaction modelling approach. We view neural spatial interaction models as an example of non-parametric estimation that makes few, if...
