We introduce an estimation method that applies to a class of multivariate regression problems. The method can estimate parameters that are subject to multiple reduced-rank conditions and other parameter restrictions and the method allows for a general specifications of the covariance matrix. We...

Classical regression analysis uses partial coefficients to measure the influences of some variables (regressors) on another variable (regressand). However, a descriptive point of view shows that these coefficients are very bad measures of influence. Their interpretation as an average change of...

Regressions often use pre-orthogonalized regressors. For example, the exposure of a stock's return to exchange-rate changes is conventionally estimated by regression, and often, the market return is included as an additional regressor. By first orthogonalizing the market return on the exchange...

We offer a new dimension for measuring monthly stock market cycle fluctuations using p-values derived from linear regression analysis. Like any other non-stationary macroeconomic variables, we propose that stock market indices do have their own intrinsic cyclical dynamicity that represents as...

We derive an identity for the determinant of a product involving non-squared matrices. The identity can be used to derive the maximum likelihood estimator in reduced-rank regressions with Gaussian innovations. Furthermore, the identity sheds light on the structure of the estimation problem that...

In this paper we analyze the trend of the gender gap between wives and husbands for Mediterranean countries with a strong family tradition, using data from the European Household Panel (ECHP) of 2001 and the European Survey on Income and Living Conditions (EU-SILC) of 2006. In general, wives and...

We propose an Aitken estimator for Gini regression. The suggested A -Gini estimator is proven to be a U-statistics. Monte Carlo simulations are provided to deal with heteroskedasticity and to make some comparisons between the generalized least squares and the Gini regression. A Gini-White test...

Time series is a collection of observations made at regular time intervals and its analysis refers to problems in correlations among successive observations. Time series analysis is applied in all areas of statistics but some of the most important include macroeconomic and financial time series....