In the standard linear instrumental variables regression model, it must be assumed that the instruments are correlated with the endogenous variables in order to ensure the consistency and asymptotic normality of the usual instrumental variables estimator. Indeed, if the instruments are only...

This paper analyzes autoregressive time series models where the errors are assumed to be martingale difference sequences that satisfy an additional symmetry condition on their fourth order moments. Under these conditions Quasi Maximum Likelihood estimators of the autoregressive parameters are no...

In this paper a new class of Instrumental Variables estimator for linear processes and in particular ARMA models is developed. Previously, IV estimators based on lagged observations as instruments have been used to account for unmodelled MA(q) errors in the estimation of the AR parameters. Here...

This paper develops a new instrumental-variable (IV) approach to estimate the effects of different exchange rate regimes on bilateral outcomes. The basic idea is that the characteristics of the exchange rate regime between two countries (exchange rate variability, fixed or float, autonomous or...

We discuss statistical inference problems associated with identification and testability in econometrics. We consider inference in non-parametric models and weakly identified structural models (weak instruments). We point out that many ill-defined statistical problems, such as non-testable...

This paper deals with two alternatives to the so-called Hausman test for the exogeneity of instruments, in the context of a model where one or more explanatory variables are possibly correlated with the structural error. These two alternatives are at least as good or better than the Hausman test...

This paper studies the ordinary least-squares (OLS) and instrumental variable (IV) estimates of the returns to schooling for male workers in Spain. OLS estimates are often biased due to the endogeneity of schooling, measurement errors or omitted variables. Proper IV estimates correct this bias....