Search

The simultaneous estimation of Cronbachs alpha coefficients from q populations under the compound symmetry assumption is considered. In a multi-sample scenario, it is suspected that all the Cronbac...

In this article, we have developed asymptotic theory for the simultaneous estimation of the k means of arbitrary populations under the common mean hypothesis and further assuming that corresponding population variances are unknown and unequal. The unrestricted estimator, the Graybill-Deal-type restricted estimator, the preliminary test, and the Stein-type shrinkage estimators are suggested. A large sample test statistic is also proposed as a pretest for testing the common mean hypothesis. Under the sequence of local alternatives and squared error loss, we have compared the asymptotic properties of the estimators by means of asymptotic distributional quadratic bias and risk. Comprehensive Monte-Carlo simulation experiments were conducted to study the relative risk performance of the estimators with reference to the unrestricted estimator in finite samples. Two real-data examples are also furnished to illustrate the application of the suggested estimation strategies.

This article addresses the problem of parameter estimation of the logistic regression model under subspace information via linear shrinkage, pretest, and shrinkage pretest estimators along with the traditional unrestricted maximum likelihood estimator and restricted estimator. We developed an asymptotic theory for the linear shrinkage and pretest estimators and compared their relative performance using the notion of asymptotic distributional bias and asymptotic quadratic risk. The analytical results demonstrated that the proposed estimation strategies outperformed the classical estimation strategies in a meaningful parameter space. Detailed Monte-Carlo simulation studies were conducted for different combinations and the performance of each estimation method was evaluated in terms of simulated relative efficiency. The results of the simulation study were in strong agreement with the asymptotic analytical findings. Two real-data examples are also given to appraise the performance of the estimators.

Excessive exchange rate volatility has a deleterious effect on international financial flows, external trade, investment and output. Among others, these economic costs prompt the central bank in emerging countries to contain excessive exchange rate volatility through intervention in the foreign exchange market. This article investigates the effectiveness of State Bank of Pakistan's (SBP) daily foreign exchange intervention starting from 3 July 2000 to 31 December 2005 (1593 trading day observations). The method of Generalized Autoregressive Conditional Heteroscedasticity, with exogenous variables (GARCH-X), used in this article, shows that SBP's intervention operation is very effective as it not only affects the exchange rate levels but also reduces the exchange rate volatility. It is also found that the short-term interest rate and the size of the foreign exchange reserves held by SBP also affect the exchange rate level and its volatility. Increase in short-term interest rate and higher foreign exchange ...