Abstract: Difficulties with inference in predictive regressions are generally attributed to strong persistence in the predictor series. We show that the major source of the problem is actually the nuisance intercept parameter and propose basing inference on the Restricted Likelihood, which is...

In this paper we explore a new approach to estimation for autoregressive panel data models, based on projecting the unobserved individual effects on the vector of observations on the lagged dependent variable. This approach yields estimators which coincide with known generalised method of...

This paper studies linear time‐series regressions with many regressors. Weak exogeneity is the most used identifying assumption in time series. Weak exogeneity requires the structural error to have zero conditional expectation given present and past regressor values, allowing errors to...

This paper proposes tests for stochastic dominance in mobility based on the empirical likelihood ratio. Two views of mobility are considered, either based on measures of absolute mobility or on transition matrices. First-order and second-order dominance conditions in mobility are first derived,...

Most Difference-in-Difference (DD) papers rely on many years of data and focus on serially correlated outcomes. Yet almost all these papers ignore the bias in the estimated standard errors that serial correlation introduces. This is especially troubling because the independent variable of...

We consider a new class of estimators for volatility functionals in the setting of frequently observed Itô diffusions which are disturbed by i.i.d. noise. These statistics extend the approach of pre-averaging as a general method for the estimation of the integrated volatility in the presence of...

This paper extends the existing literature on linear quadratic adjustment cost (LQAC) models under rational expectations to the inferential issues arising when: (i) agents optimise with respect to a vector of endogenous variables; (ii) the behavioural equations stemming from the agent's...

This paper surveys J. D. Sargan's work on instrumental variable estimation and its connections with the generalized method of moments. I first present the modelling context in which Sargan motivated instrumental variable estimation. Then I review the theory of instrumental variable estimation as...

The problem considered is the estimation of "k" coefficients of interest in a linear regression model when the (k+1)st coefficient is of no interest. It is shown that this problem is equivalent to the problem of estimating the unknown mean of a univariate normal distribution with variance one...

We propose a root-N-consistent estimator for binary response panel data where the individual specific effect may be correlated with the regressors. The estimator is asymptotically normal with a simple variance matrix