We suggest the use of an Internet job-search indicator (the Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample forecasting comparison analyzing many models that adopt both our preferred leading indicator (GI), the more standard...

Human-generated greenhouse gases depend on the level of economic activity. Therefore, most climate change studies are based on models and scenarios of economic growth. Economic growth itself, however, is likely to be affected by climate change impacts. These impacts affect the economy in...

This paper uses a dynamic CGE model to assess the intertemporal and spatial dimension of technology spillovers embodied in international trade within a climate and trade policy framework. Three are the main contributions of the study. First, to include endogenous factor-biased technical change...

The present research proposes a macroeconomic assessment of the role of waste incineration with energy recovery (WtE) and controlled landfill biogas to electricity generation and their potential contribution to a CO2 emission reduction policy, within a recursive-dynamic computable general...

We develop a structural econometric model to study the impacts of El Niño Southern Oscillation (ENSO) on Colombian coffee production, exports and price. Our empirical specification is consistent with an economic model of the coffee market that, in the short-run, is characterized by a...

This paper presents a micro-econometric model testing for changes in firms' product and pricing decisions in two American industries where leading companies have sharply increased their financial leverage. According to the latest econometric theory, the empirical analysis is carried out through...

Increased population pressure and political decisions have led to more intensive agricultural practices in China. As in other regions of the world, these practices can damage natural capital. We use the Kalman filter and Chinese panel data to estimate an index of environmental productivity...

This paper estimates the dynamic conditional correlations in the returns on WTI oil one-month forward prices, and one-, three-, six-, and twelve-month futures prices, using recently developed multivariate conditional volatility models. The dynamic correlations enable a determination of whether...

The identification of the forces that drive stock returns and the dynamics of their associated volatilities is a major concern in empirical economics and finance. This analysis is particularly relevant for determining optimal hedging strategies based on whether shocks to the volatilities of...

The identification of the forces that drive oil stock prices is extremely important given the size of the Oil&Gas industry and its links with the energy sector and the environment. In the next decade oil companies will have to deal with international policies to contrast climate change. This...