Deciding upon the optimal sample size in advance is a difficult problem in general. Often, the investigator regrets not having drawn a larger sample; in many cases additional observations are done. This implies that the actual sample size is no longer deterministic; hence, even if all sample...

Many common statistical models can be specified as linear models with restrictions imposed on the parameters. A large amount of these models impose restrictions which do not allow for the analytical construction of the probability density function (pdf) of the parameters given the restrictions....

This paper considers estimation and inference in panel vector autoregressions with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood estimator based on a transformed likelihood function is proposed and shown to be...

It is argued that size distortions and power properties of likelihood based tests for cointegration are so poor in many small sample situstions that alternative are necessary for analysing typical macroeconomic relationships.