This paper analyzes the effect of environmental policies on the direction of energy innovation across countries over the period 1990-2012. Our novelty is to use threshold regression models to allow for discontinuities in policy effectiveness depending on a country's relative competencies in...

We study nonparametric estimation of regression function with nonstationary (integrated or nearly integrated) covariates and the error series of the regressor process following a fractional ARIMA model. A local linear estimation method is developed to estimate the unknown regression function....

This paper investigates the relationship between exchange rate pass-through and exchange rate appreciations/depreciations and inflation by estimating nonlinear time series models. Motivated by theoretical and empirical results in the literature, the paper proposes new econometric models that can...

We develop a set of necessary and sufficient conditions for equilibria to be determinate in a class of forward-looking Markov-switching rational expectations models, and we develop an algorithm to check these conditions in practice. We use three examples, based on the new Keynesian model of...

This paper proposes a new panel model of cross-sectional dependence. The model has a number of potential structural interpretations that relate to economic phenomena such as herding in financial markets. On an econometric level it provides a flexible approach to the modelling of interactions...

Relying on data for a panel of 90 economies over 1970-2015 and System-GMM estimates, we extend the standard Kuznets-curve empirical framework to investigate how financial development, globalisation and technology affect income inequality. Our findings reveal the presence of significant...

Markov-switching DSGE (MSDSGE) modeling has become a growing body of literature on economic and policy issues related to structural shifts. This paper develops a general perturbation methodology for constructing high-order approximations to the solutions of MSDSGE models. Our new method, called...

We propose an Adaptive Dynamic Nelson-Siegel (ADNS) model to adaptively forecast the yield curve. The model has a simple yet flexible structure and can be safely applied to both stationary and nonstationary situations with different sources of change. For the 3- to 12-months ahead out-of-sample...