This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymptotically normal. We also derive the asymptotic distribution of average impact coefficients...

In the standard generalized method of moments estimation of dynamic panel data models, the constant term is usually omitted from instrument sets. As a result, adding a constant to the dependent variable affects the estimates for models without full period dummies. Omitting the constant term from...

This paper proposes to include the spatial time lag in empirical applications using spatial panel data models, and also explains why the coefficient of that term can be negative. We provide simple theoretical frameworks to justify the relevance of the spatial time lag to empirical...

We complement existing inferential theory for panel factor models by deriving the asymptotics for the first differences of the estimated factors and common components obtained from a non-stationary panel factor model. As an application, we propose an estimator for the long run variance of the...

By employing the threshold regression method, we estimate the average tariff equivalent of fixed costs for the use of a free trade agreement (FTA) among all existing FTAs in the world. It is estimated to be around 3%.

A panel data approach is used to investigate both the steady-state and the transitional impact of trade liberalisation on export performance within a sample of selected OECD countries. The results find trade policy to be a largely insignificant determinant of export performance. Domestic...

This paper considers a factor-augmented regression model in the presence of structural change. We propose a two-step procedure to estimate the coefficients of explanatory variables. We show that when the number of units (N) and the number of periods (T) are large and comparable, the proposed...

We estimate the long rate and its volatility within the Svensson framework. The procedure that best extrapolates the longest observable rate and its volatility is a 2-dimensional grid search conditioned on the ridge regression suggested by Annaert et al. (2013).

We propose to apply the group fused Lasso to estimate time series models with endogenous regressors and an unknown number of breaks. It can correctly determine the number of breaks and estimate the break dates asymptotically. Simulations and applications are given.

This paper extends the classical work of bipower variation by allowing the return process to be autocorrelated. We propose a method of estimating the return volatility when the price process is described by a fractal Brownian motion with jumps.