The paper studies the effects of credible disinflation in the presence of real wage rigidity, comparing the Calvo and Rotemberg price setting mechanisms (the two popular variants of the New-Keynesian model). In both types of models, a credible, gradual disinflation is shown to lead to a delayed...

This paper presents results concerning the nonlinear analysis of the mean annual value temperature time series corresponding to the Earth’s global climate for the time period of 713 – 2004. The nonlinear analysis consists of the application of several filtering methods, the estimation of...

We investigated causal factors driving German hog-price dynamics with an innovative ‘diagnostic’ modeling approach. Hog-price cycles are conventionally attributed to randomly-generated behavior best modeled stochastically—most recently as randomly-shifting sinusoidal oscillations....

We devise a decision tool to help economic researchers select a causal detection method compatible with real-world dynamics of an economic system under investigation. We apply it to test for dynamic causality between promotions and sales of a case-study beer brand in England. We find evidence...

We investigate the eects of government spending on U.S. output with a threshold structural vector autoregressive model. We consider Bayesian model comparison and generalized impulse response analysis to test for nonlinearities in the responses of output to government spending. Our empirical...

This paper presents a model inspired by the Unified Growth Theory, where reductions in adult mortality together with improvements in technological progress are the deep causes of the transition from a Traditional (Malthusian) Regime to a Pre-Modern Regime, characterized by the accumulation of...

This paper presents a framework to undertake likelihood-based inference in nonlinear dynamic equilibrium economies. The authors develop a sequential Monte Carlo algorithm that delivers an estimate of the likelihood function of the model using simulation methods. This likelihood can be used for...

We propose a new class of non-linear diffusion processes for modeling financial markets data. Our non-linear diffusions are obtained as transformations of affine processes. We show that asset-pricing and estimation is possible and likelihood estimation is straightforward. We estimate a...

This paper introduces dynamics in the R&D-to-innovation and innovation-to-productivity relationships, which have mostly been estimated on cross-sectional data. It considers four nonlinear dynamic simultaneous equations models that include individual effects and idiosyncratic errors correlated...