“Regional and International Market Integration of a Small Open Economy”, with F. Lorenzo and C.M. Rodríguez. Journal of Applied Economics, Vol X, No. 1 (May 2007), 77-98.

“Dating U.S. Business Cycles with Macro Factors”.

Abstract - I propose a framework for the assessment of current business conditions using a factor-augmented autoregressive probit model where the dependent variable is the state of the economy as defined by the NBER. Results show that latent common factors estimated by principal components analysis from a large number of macroeconomic series have important predictive power for NBER recession dates. The models generate in-sample recession probabilities that almost perfectly reproduce NBER dates. A pseudo out-of-sample forecasting exercise, designed to approximate real time conditions, shows that predicted recession probabilities consistently rise during subsequently declared NBER recession dates. With the appropriate classification rule, the models exhibit good performance as real time dating algorithms. The latent variable in the probit model can be interpreted as an index of business conditions which is used to assess the strength of an expansion or the depth of a recession.

“Unit Root Testing with Stationary Covariates and a Structural Break in the Trend Function”, submitted.

Abstract - I consider the issue of testing for a unit root allowing for a structural break in the trend function. The focus is on the construction of more powerful tests using the information in relevant multivariate data sets. The proposed test adopts the GLS detrending approach and uses correlated stationary covariates to improve power. As it is standard in the literature, the break date is treated as unknown. I derive the asymptotic distributions of the test and a set of asymptotic and finite sample critical values are tabulated. Asymptotic local power functions show that power gains can be large. Finite sample results show that the test exhibits small size distortions and power that can be far beyond what is achievable by univariate tests.

“Covariate Unit Root Tests with Good Size and Power”, submitted.

Abstract - I consider the selection of the truncation lag using information criteria for covariate unit root tests. Simulation results show that standard information criteria such as the BIC or the AIC can result in tests with large size distortions. In the case of the test proposed by Elliott and Jansson (2003), a modified information criterion for cointegration tests introduced by Qu and Perron (2007) yields big size improvements and powerful tests. The selection rule suggested by Pesavento (2006) yields tests with small size distortions only for a certain class of models. A simple modification yields tests with improved power.

“Break Fraction Estimation in Covariate Unit Root Tests with a Structural Break” (manuscript in progress).

“Forecasting U.S. Recessions with Macro Factors” (in progress).