(last update: May 6, 2016 )

Research Interests

· Econometrics

o Main interests: Time Series, Macroeconometrics and Financial Econometrics.

My 7 Most Favourite Refereed Publications from the Past 10 Years (more @ cv)

· "The Empirical Determinants of Credit Default Swap Spreads - a Quantile Regression Approach," forthcoming at European Financial Management (with Pedro Pires and João Pedro Pereira).

We study the empirical determinants of Credit Default Swap (CDS) spreads through quantile regressions. In addition to traditional variables, such as implied volatility, put skew, historical stock return, leverage, profitability, and ratings, the results indicate that CDS premiums are strongly determined by CDS illiquidity costs, measured by absolute bid-ask spreads. The quantile regression approach reveals that high-risk firms are more sensitive to changes in the explanatory variables that low-risk firms. Furthermore, the goodness-of-fit of the model increases with CDS premiums, which is consistent with the credit spread puzzle.

· 2014, "Testing for Persistence Change in Fractionally Integrated Models: An Application to World Inflation Rates", Computational Statistics and Data Analysis, 76, 502-522 (with Paulo M.M. Rodrigues).

A new approach to detect persistence change in fractionally integrated models based on recursive forward and backward estimation of regression-based Lagrange Multiplier tests is proposed. This procedure generalizes approaches for conventional integrated processes to the fractional integration context. Asymptotic results are derived and the performance of the new tests evaluated in a Monte Carlo exercise. In particular, analytical and simulation results are provided for cases where the order of fractional integration is both known and unknown and needs to be estimated. The finite sample size and power performance of the statistics are encouraging and compare favorably to other recently proposed tests in the literature. The test statistics introduced are also applied to several world inflation rates and evidence of persistence change is found in most series.

· 2014, “Linear Instrumental Variables Model Averaging Estimation”, Computational Statistics and Data Analysis, 71, 709-724 (with Vasco J. Gabriel).

Model averaging (MA) estimators in the linear instrumental variables regression framework are considered. The obtaining of weights for averaging across individual estimates by direct smoothing of selection criteria arising from the estimation stage is proposed. This is particularly relevant in applications in which there is a large number of candidate instruments and, therefore, a considerable number of instrument sets arising from different combinations of the available instruments. The asymptotic properties of the estimator are derived under homoskedastic and heteroskedastic errors. A simple Monte Carlo study contrasts the performance of MA procedures with existing instrument selection procedures, showing that MA estimators compare very favorably in many relevant setups. Finally, this method is illustrated with an empirical application to returns to education.

· 2011, “Testing the Stock Price-Dividend Relationship Under Multiple Regime Shifts,” Empirical Economics, 41, 639-662 (with Vasco J. Gabriel)

We examine the properties of several residual-based cointegration tests when long-run parameters are subject to multiple shifts driven by an unobservable Markov process. Unlike earlier study, which considered one-off deterministic breaks, our approach has the advantage of allowing for an unspecified number of stochastic breaks. We illustrate this issue by exploring the possibility of Markov switching cointegration in the stock price-dividend relationship and showing that this case is empirically relevant. Our subsequent Monte Carlo analysis reveals that standard cointegration tests are generally reliable, their performance often being robust for a number of plausible regime shift parameterizations.

· 2010, "The Cost Channel Reconsidered: A Comment Using an Identification-Robust Approach," Journal of Money, Credit and Banking, 42, 1703-1712 (with Vasco J. Gabriel)

We reexamine the empirical relevance of the cost channel of monetary policy (e.g., Ravenna and Walsh 2006), employing recently developed moment-conditions inference methods, including identification-robust procedures. Using U.S. data, our results suggest that the cost channel effect is poorly identified and we are thus unable to corroborate the previous results in the literature.

· 2010, "Time Varying Cointegration," Econometric Theory, 26, 1453-1490 (with Herman J. Bierens) (gauss code) (separate Appendix)

In this paper we propose a time-varying vector error correction model in which the cointegrating relationship varies smoothly over time. The Johansen setup is a special case of our model. A likelihood ratio test for time-invariant cointegration is defined and its asymptotic chi-square distribution is derived. We apply our test to the purchasing power parity hypothesis of international prices and nominal exchange rates, and we find evidence of time-varying cointegration.

Bootstrap tests for time varying cointegration, Forthcoming at Econometric Reviews (gauss code)

This article proposes wild and the independent and identically distibuted (i.i.d.) parametric bootstrap implementations of the time-varying cointegration test of Bierens and Martins (2010). The bootstrap statistics and the original likelihood ratio test share the same first-order asymptotic null distribution. Monte Carlo results suggest that the bootstrap approximation to the finite-sample distribution is very accurate, in particular for the wild bootstrap case. The tests are applied to study the purchasing power parity hypothesis for twelve Organisation for Economic Cooperation and Development (OECD) countries and we only find evidence of a constant long-term equilibrium for the U.S.–U.K. relationship.

· 2004, “On the Forecasting Ability of ARFIMA Models when Infrequent Breaks Occur”, Econometrics Journal, 7, 455-475 (with Vasco J. Gabriel).

Recent research has focused on the links between long memory and structural breaks, stressing the memory properties that may arise in models with parameter changes. In this paper, we question the implications of this result for forecasting. We contribute to this research by comparing the forecasting abilities of long memory and Markov switching models. Two approaches are employed: the Monte Carlo study and an empirical comparison, using the quarterly Consumer Price inflation rate in Portugal in the period 1968–1998. Although long memory models may capture some in-sample features of the data, we find that their forecasting performance is relatively poor when shifts occur in the series, compared to simple linear and Markov switching models

Active Research Projects as Principal Investigator

· PTDC/EGE-ECO/122093/2010, "Robust Inference in Rational Expectation Models", 2011-2014.

Some Ongoing Research

· Structural breaks and its applications;

· GMM and GEL in dynamic stochastic equilibrium models;

· Model selection and evaluation;

· Applications in finance.

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