This paper describes some recent advances and contributions to our understanding of economic forecasting. The framework we develop helps explain the findings of forecasting competitions and the prevalence of forecast failure. It constitutes a general theoretical background against which recent...

The ability of Markov-switching (MS) autoregressive models to replicate selected classical business-cycle features found in US post-war consumption, investment and output is compared to that of linear models. Univariate MS models appear to offer more dynamically parsimonious representations, but...

In this paper we exploit the specific structure of the Euler equation and develop two alternative GMM estimators that deal explicitly with measurement error. The first estimator assumes that the measurement error is lognormally distributed. The second estimator drops the distributional...

In a recent paper we have introduced the class of realised kernel estimators of the increments of quadratic variation in the presence of noise. We showed that this estimator is consistent and derived its limit distribution under various assumptions on the kernel weights. In this paper we extend...

For financial assets whose best quotes almost always change by jumping by the market`s price tick size (one cent, five cents, etc.), this paper proposes an estimator of Quadratic Variation which controls for microstructure effects. It measures the prevalence of alternations, where quotes jump...

We analyze the time-series of prices in the Spanish electricity market by means of a time varying-transition-probabilities Markov Switching model. Accounting for demand and supply conditions, we show that the time-series of prices is characterized by two significantly different price levels....

This paper studies the stability of nonlinear autoregressive models with conditionality heteroskedastic errors. We consider a nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a nonlinear first order generalized autoregressive conditional heteroskedasticity...

OLS estimation of an impulse-indicator coefficient is inconsistent, but its variance can be consistently estimated. Although the ratio of the inconsistent estimator to its standard error has a t-distribution, that test is inconsistent: one solution is to form an index of indicators. We provide...

Big Data offer potential benefits for statistical modelling, but confront problems like an excess of false positives, mistaking correlations for causes, ignoring sampling biases, and selecting by inappropriate methods.  We consider the many important requirements when searching for a data-based...

This paper introduces a class of cointegration tests based on estimated low-pass and high-pass regression coefficients from the same wavelet transform of the original time series data.  The procedure can be applied to test the null of cointegration in a n + k multivariate system with n...