Density estimation in the uniform deconvolution model

We consider the problem of estimating a probability density function based on data that are corrupted by noise from a uniform distribution. The (nonparametric) maximum likelihood estimator for the corresponding distribution function is well defined. For the density function this is not the case. We study two nonparametric estimators for this density. The first is a type of kernel density estimate based on the empirical distribution function of the observable data. The second is a kernel density estimate based on the MLE of the distribution function of the unobservable (uncorrupted) data.     

On Testing for the Nullity of Some Skewness Coefficients

Three tests for the skewness of an unknown distribution are derived for iid data. They are based on suitable normalization of estimators of some usual skewness coefficients. Their asymptotic null distributions are derived. The tests are next shown to be consistent and their power under some sequences of local alternatives is investigated. Their finite sample properties are also studied through a simulation experiment, and compared to those of the √ b ₂-test.     

The Robustness of the APT to Alternative Estimators

We test the robustness of the APT to two alternative estimation procedures: the Fama and MacBeth (1973) two-step methodology; and the one-step procedure due to Burmeister and McElroy (1988). We find that the APT is indeed sensitive to the chosen estimator and assumptions about the factor structure of stock returns. We believe that our findings have implications for the estimation of asset pricing models in general.     

On efficiency of the ratio estimator

Summary The exact mean square error for the ratio estimator of a finite population total based on simple random sampling without replacement is shown to have an expected value less than that of the variance of the ratio estimator based on Midzuno’s scheme, under a usual super-population model.     

Asymptotic behaviour of regression pre-test estimators with minimal Bayes risk

Pre-test estimators (PTE) are considered which are optimal under a Bayes risk among PTE with general measurable sets as “regions of significance” for the test statistic t associated with the estimate of a given regression coefficient. Asymptotic and some finite sample results are stated and numerical experiments are commented on.     

Some properties of the length of the shortest half

This paper discusses some properties of the length of the shortest half proposed by Rousseeuw and Leroy (1988) as a robust scale estimator.     

MSE-improvement of the least squares estimator by dropping variables

It is well known that dropping variables in regression analysis decreases the variance of the least squares (LS) estimator of the remaining parameters. However, after elimination estimates of these parameters are biased, if the full model is correct. In his recent paper, Boscher (1991) showed that the LS-estimator in the special case of a mean shift model (cf. Cook and Weisberg, 1982) which assumes no “outliers” can be considered in the framework of a linear regression model where some variables are deleted. He derived conditions under which this estimator outperforms the LS-estimator of the full model in terms of the mean squared error (MSE)-matrix criterion. We demonstrate that this approach can be extended to the general set-up of dropping variables. Necessary and sufficient conditions for the MSE-matrix superiority of the LS-estimator in the reduced model over that in the full model are derived. We also provide a uniformly most powerful F-statistic for testing the MSE-improvement.     

Output Gap Estimation and Monetary Policy in China

Using the Bayesian multivariate Beveridge-Nelson decomposition method, this paper estimates China's output gap based on a multivariate dynamic model featuring distinct interactions among real output, inflation, money, and the exchange rate in China during the period 1980-2010. The authors compare the statistical nature and potential forecasting effects of the resulting multivariate gap measure on monetary policy with those of the output gap measures based on univariate models. The empirical results show that only the measure based on the multivariate system significantly predicts monetary policy, which indicates that the output gap estimated by the multivariate system contains more information than the traditional measures for macroeconomic policy adjustments do.     

Risk-Taking Behavior and Capital Adequacy in a Mixed Banking System: New Evidence from Malaysia Using Dynamic OLS and Two-Step Dynamic System GMM Estimators

This study is the first attempt to investigate the relationship between the level of risky assets and capital level in a mixed Malaysian banking system covering 83 months starting December 2006. The results of dynamic ordinary least squares indicate positive relationship between capital ratio (CAR) and risk-weighted asset ratio (RWA) in the long run. Furthermore, the causality analysis based on panel vector error correction model (VECM) and two-step dynamic system generalized method of moments indicates unidirectional causality from CAR to RWA. Our results further suggest that higher capital growth and capital buffer provide an extra cushion for the Malaysian banks to pursue relatively riskier financial activities, and the nature of risk-taking behavior of Islamic banks follows that of the conventional banks.     

Tax Rebate and Dividend Payout in Bangladesh

The purpose of this paper is to examine the effects of the introduction of 20% tax rebate in 2002 for certain firms on the dividend policy of firms potentially qualifying for this rebate in Bangladesh. A balanced panel data set of 63 non-financial firms of Bangladesh for 14 （1998-2011） years from the Dhaka stock exchange is used for this purpose Newey-West estimator is used to estimate a logit model and the specified model uses binary values of 0 and 1 to identify if it met the tax rebate threshold. The explanatory variables are finn size, log of market value to face value ratio and profitability. A dummy variable was used to separate the pre-rebate period （2003 and before） from post-rebate period （after 2003）. The dummy variable turned out to be insignificant indicating that introduction of the tax rebate had no impact on dividend policy of qualifying firms.