We propose in this paper a likelihood-based framework for cointegration analysis in panels of a fixed number of vector error correction models. Maximum likelihood estimators of the cointegrating vectors are constructed using iterated Generalized Method of Moments estimators. Using these...

We show that three convenient statistical properties that are known to hold forthe linear model with normal distributed errors that: (i.) when the variance is known, the likelihood based test statistics, Wald, Likelihood Ratio andScore or Lagrange Multiplier, coincide, (ii.) when the variance is...

We propose in this paper a likelihood-based framework forcointegration analysis in panels of a fixed number of vector errorcorrection models. Maximum likelihood estimators of thecointegrating vectors are constructed using iterated GeneralizedMethod of Moments estimators. Using these estimators...

We construct a novel statistic to test hypothezes on subsets of the structural parameters in an Instrumental Variables (IV) regression model. We derive the chi squared limiting distribution of the statistic and show that it has a degrees of freedom parameter that is equal to the number of...

We show that three convenient statistical properties that are known to hold for the linear model with normal distributed errors that: (i.) when the variance is known, the likelihood based test statistics, Wald, Likelihood Ratio and Score or Lagrange Multiplier, coincide, (ii.) when the variance...

Root cancellation in Auto Regressive Moving Average (ARMA) models leads to local non-identification of parameters. When we use diffuse or normal priors on the parameters of the ARMA model, posteriors in Bayesian analyzes show an a posteriori favor for this local non-identification. We show that...

Root cancellation in Auto Regressive Moving Average (ARMA) models leads tolocal non-identification of parameters. When we use diffuse or normal priorson the parameters of the ARMA model, posteriors in Bayesian analyzes show ana posteriori favor for this local non-identification. We show that the...

We construct a novel statistic to test hypothezes on subsets of the structural parameters in anInstrumental Variables (IV) regression model. We derive the chi squared limiting distribution of thestatistic and show that it has a degrees of freedom parameter that is equal to the number...

We show that the Anderson-Rubin (AR) statistic is the sum of two independent piv-otal statistics. One statistic is a score statistic that tests location and the other statistictests misspecification. The chi-squared distribution of the location statistic has a degreesof freedom parameter that is...

We propose a generalized method of moments (GMM) Lagrange multiplier statistic, i.e. the <I>K</I> statistic, that uses a Jacobian estimator based on the continuous updating estimator that is asymptotically uncorrelated with the sample average of the moments. Its asymptotic (...)<P>This discussion paper...</p></i>