Estimation of an exponential quantile under pitman's measure of closeness

We consider the problem of estimating a quantile of an exponential distribution with unknown location and scale parameters under Pitman's measure of closeness (PMC). The loss function is required to satisfy some mild conditions but is otherwise arbitrary. An optimal estimator is obtained in the class of location-scale-equivariant estimators, and its admissibility in the sense of PMC is investigated.     

Robust scale estimation in the error-components model using the empirical characteristic function

Robust estimators of the scale parameters in the error-components model are described. The new estimators are based on the empirical characteristic functions of appropriate sets of residuals and are affine equivariant, consistent and asymptotically normal. The robustness of the new estimators is investigated via influence-function calculations. The results of Monte Carlo experiments and an example based on real data illustrate the usefulness of the estimators.     

Resolving conflicting demands on evaluation: A test demonstration of videotex for farmers

Evaluating an innovation for federal, state, and local policymakers and program managers alike entails conflicting demands on the evaluation study. Policymakers at federal, state, and local levels are best assisted by impact evaluations, whereas state and local program managers are best assisted by process evaluations. In-house evaluators often have an advantage in conducting process evaluations; external evaluators generally have an advantage in conducting impact evaluations. A cost-effective approach may be to combine in-house process evaluation and external impact evaluation. This dual approach was found to reduce conflicting demands on the evaluation of an experimental videotex system for agricultural producers.     

Inference about permutation parameter in large samples

The estimation problem of a permutation parameter on the basis of a random sample of increasing size is considered. A necessary and sufficient condition for the existence of an estimator, asymptotically fully efficient for two different distributions families, is derived. We also study the application of this result to cyclic groups of order two and three.     

Sequential procedures based on M-estimators with discontinuous score functions

Bounded-width sequential confidence intervals and sequential tests for regression parameter based on M-estimators are extended to the case where the score-functions generating the M-estimators have jump-discontinuities. In the context of the asymptotic normality of the stopping variable, for the confidence interval problem, it is observed that the jump-discontinuities induce a slower rate of convergence. The proofs of the main theorems rest on the weak convergence of some related processes and this is also studied.     

On regressing regression coefficients

This paper considers a regression model in which coefficients obtained from a previous regression are themselves the object of analysis. It is shown that the parameters of interest can be obtained in two ways: pooling across observations and subsamples, or a two-stage process of first estimating the coefficients within each subsample, and then using these coefficients as dependent variables in a second stage regression. The relative properties of these estimators are analyzed, and the conditions under which the two estimators are equivalent are derived.     

On the ABLUE of the normal mean from a censored sample

The asymptotically best linear unbiased estimate (ABLUE) of the normal mean is discussed. The estimate is based on k selected order statistics chosen from a singly or doubly censored large sample of size n(>k). The coefficients, the asymptotic relative efficiency of the estimate, and the optimum spacing of k real numbers between 0 and 1 which determines the optimum ranks of order statistics, are provided. A comparison between the ABLUE and the iterated maximum likelihood estimate is made.     

Minimax subset selection for the multinomial distribution

Let (X₁,…,X_k) be a multinomial vector with unknown cell probabilities (p₁,?,p_k). A subset of the cells is to be selected in a way so that the cell associated with the smallest cell probability is included in the selected subset with a preassigned probability, P¹. Suppose the loss is measured by the size of the selected subset, S. Using linear programming techniques, selection rules can be constructed which are minimax with respect to S in the class of rules which satisfy the P¹-condition. In some situations, the rule constructed by this method is the rule proposed by Nagel (1970). Similar techniques also work for selection in terms of the largest cell probability.     

Immigration,Growth, and Unemployment: Panel VAR Evidence from OECD Countries

This paper examines empirically the interaction between immigration and host country economic conditions. We employ panel vector autoregression (VAR) techniques for a large annual data set on 22 OECD countries over the period 1987–2009. The VAR approach addresses the endogeneity problem by allowing for endogenous interactions between the variables in the system. Our results provide evidence of migration contribution to host economic prosperity (positive impact on GDP per capita and negative impact on aggregate unemployment, native‐ and foreign‐born unemployment rates). We also find that migration is influenced by host economic conditions (migration responds positively to host GDP per capita and negatively to host total unemployment rate).     

融资融券能促进标的证券的定价效率吗?——基于上证50ETF的实证研究

通过分析ETF作为融资融券标的前后折溢价率水平变化及其影响因素,发现融资融券推出和交易费用减免都显著提高了ETF的定价效率。具体而言,融资融券推出与交易费用减免都是通过影响ETF的套利成本来提高其定价效率的。交易费用减免一方面直接降低了套利显性成本,另一方面通过提高市场流动性降低了套利隐形成本;而融资融券推出为ETF交易提供了额外的套利渠道,降低了市场非流动性对原有的跨市场套利的影响,从而提高其定价效率。