The two-stage least squares simultaneous equation estimation procedure is shown to be identical to the modified two stage least squares estimator obtained by a) replacing the right-hand side endogenous variable in a single structural equation by their reduced form regression estimates; and b)...

This paper examines practical procedures for obtaining generalized ridge-type estimators of a standard linear regression model. The analysis is specialized to the single 'k' model and this is compared to a procedure recently proposed by McDonald and Galarneau (1975).

Maximum likelihood estimation of equation systems with first-order autocorrelation should, in principle, take into account the first observation and associated stationarity condition. In the general case, this leads to computational difficulties compared with conventional procedures, which...

Changes in demographic composition and industrial structure have been used to explain rising "natural" unemployment rates in Canada. We find the change in industry mix accommodated concurrent changes in labour force structure, but the substitution within industries, rather than changes in the...

This paper proposes a methodology for analyzing spell duration of unemployment in terms of duration shares. One can examine directly the shares of total unemployment accounted for by short and long spells. The approach extends recent theoretical work on statistical inference with distributional...

This paper advances a new method for analyzing short-run cyclical changes in income concentration in the size distribution of income. Rather than focussing on Gini coefficients or variance, this approach involves analyzing fluctuations in individual quantile income levels for each of seven age...

This paper empirically examines entire distributions of unemployment spells according to a novel duration-share approach based on decile shares and Lorenz curves of unemployment. The approach is applied to Canadian micro-data. The approach reveals distinctive patterns of unemployment spell...

This paper develops a technique for estimating linear models with second-order autoregressive errors, which utilizes the full set of observations, and explicitly constrains the estimates of the error process to satisfy a priori stationarity conditions. A nonlinear solution technique which is new...