This paper proposes a new likelihood-based panel cointegration rank test which extends the test of Örsal & Droge (2012) (henceforth Panel SL test) to allow for cross-sectional dependence. The dependence is modelled by unobserved common factors which affect the variables in each cross-section...

We model panel data of crime careers of juveniles from a Dutch Judicial Juvenile Institution. The data are decomposed into a systematic and an individual-specific component, of which the systematic component reflects the general time-varying conditions including the criminological climate....

This chapter presents a unified set of estimation methods for fitting a rich array of models describing dynamic relationships within a longitudinal data setting. The discussion surveys approaches for characterizing the micro dynamics of continuous dependent variables both over time and across...

We model panel data of crime careers of juveniles from a Dutch Judicial Juvenile Institution. The data are decomposed into a systematic and an individual-specific component, of which the systematic component reflects the general time-varying conditions including the criminological climate....

Likelihood based inference for multi-state latent factor intensity models is hindered by the fact that exact closed-form expressions for the implied data density are not available. This is a common and well-known problem for most parameter driven dynamic econometric models. This paper reviews,...

Measuring bias is important as it helps identify flaws in quantitative forecasting methods or judgmental forecasts. It can, therefore, potentially help improve forecasts. Despite this, bias tends to be under represented in the literature: many studies focus solely on measuring accuracy. Methods...

1. Introduction -- 2. Description of Developed Countries’ Climate Policy -- 3. Description of BRICS and Indonesia’s Climate Policy -- 4. Literature Review on Emissions Convergence -- 5. Data and Empirical Strategy -- 6. Econometric Methods -- 7. Empirical Results -- 8. PANIC Results -- 9....

In this paper we focus on estimating the degree of cross-sectional dependence in the error terms of a classical panel data regression model. For this purpose we propose an estimator of the exponent of cross-sectional dependence denoted by α; which is based on the number of non-zero pair-wise...

We develop a finite-sample procedure to test for mean-variance efficiency and spanning without imposing any parametric assumptions on the distribution of model disturbances. In so doing, we provide an exact distribution-free method to test uniform linear restrictions in multivariate linear...

This paper proposes two new panel cointegrating rank tests which are robust to cross-sectional dependency. The dependence in the data generating process is modeled using unobserved common factors. The new tests are based on a metaanalytic approach, in which the p-values of the individual...