Technology shocks and aggregate fluctuations in an estimated hybrid RBC model

This paper contributes to the on-going empirical debate regarding the role of the RBC model and in particular of technology shocks in explaining aggregate fluctuations. To this end we estimate the model’s posterior density using Markov-Chain Monte-Carlo (MCMC) methods. Within this framework we extend Ireland’s (2001, 2004) hybrid estimation approach to allow for a vector autoregressive moving average (VARMA) process to describe the movements and co-movements of the model’s errors not explained by the basic RBC model. The results of marginal likelihood ratio tests reveal that the more general model of the errors significantly improves the model’s fit relative to the VAR and AR alternatives. Moreover, despite setting the RBC model a more difficult task under the VARMA specification, our analysis, based on forecast error and spectral decompositions, suggests that the RBC model is still capable of explaining a significant fraction of the observed variation in macroeconomic aggregates in the post-war U.S. economy.

The Inventor Balance and the Functional Specialization in Global Inventive Activities

We study the functional specialization whereby some countries contribute relatively more inventors vs. organizations in the production of inventions at a global scale. We propose a conceptual framework to explain this type of functional specialization, which posits the presence of feedbacks between two distinct sub-systems, each one providing inventors and organizations. We quantify the phenomenon by means of a new metric, the “inventor balance”, which we compute using patent data. We show that the observed imbalances, which are often conspicuous, are determined by several factors: the innovativeness of a country relative to its level of economic development, relative factor endowments, the degree of technological specialization and, last, cultural traits. We argue that the “inventor balance” is a useful indicator for policy makers, and its routine analysis could lead to better informed innovation policies.