Optimal estimation of a finite population mean under generalized random permutation models

Employing certain generalized random permutation models and a general class of linear estimators of a finite population mean, it is shown that many of the conventional estimators are “optimal” in the sense of minimum average mean square error. Simple proofs are provided by using a well-known theorem on UMV estimation. The results also cover certain simple response error situations.     

Procedures for improving the mle for ordered binomial parameters

The problem is that of estimating the probabilities of m independent binomial random variables when their probabilities are known to be nondecreasing and the loss function is squared error. In the cases where the m.l.e. is inadmissible (essentially when the total number of trials is 7 or more) we present a method for modifying the m.l.e. to get a better estimator. The method requires a series of changes. At each step we alter the action taken by the m.l.e. on each of three, appropriately chosen, points in the sample space.     

A class of Shrunken estimators for normal mean

This paper presents a class of estimators for the mean of a normal population and determines the conditions on characterizing scalars under which the class of estimators uniformly dominates over the conventional sample mean according to the mean-square-error criterion.     

The role of political ties and political uncertainty in corporate innovation

We examine the relationship between firms' political connections and corporate innovation in a European context. We also consider the moderating effect of political connections on the relationship between political uncertainty and firms' innovation. We use two different metrics of innovation: R&D (an input measure), and patent counts (an output measure). We find that firms with former politicians on their board of directors invest less in R&D than their counterpart firms. However, the presence of this type of director on the board is positively associated with the number of a firm's patent applications. It seems that, although political ties reduce the amount of resources devoted to R&D activities, they increase the effectiveness of intellectual rights protection. Results also show that political uncertainty decreases R&D investment but exacerbates the need for legal protection of innovation through patents. According to our results, political connections attenuate the effect of political uncertainty on firm innovation such that the negative (positive) effect of uncertainty on R&D intensity (patents) weakens when the firm is politically connected.     

LABOR‐MARKET HETEROGENEITY,AGGREGATION, AND POLICY (IN)VARIANCE OF DSGE MODEL PARAMETERS

Data from a heterogeneous‐agents economy with incomplete asset markets and indivisible labor supply are simulated under various fiscal policy regimes and an approximating representative‐agent model is estimated. Preference and technology parameter estimates of the representative‐agent model are not invariant to policy changes and the bias in the representative‐agent model’s policy predictions is large compared to predictive intervals that reflect parameter uncertainty. Since it is not always feasible to account for heterogeneity explicitly, it is important to recognize the possibility that the parameters of a highly aggregated model may not be invariant with respect to policy changes.     

FINANCIAL CONSTRAINTS AND INNOVATION: WHY POOR COUNTRIES DON'T CATCH UP

This paper examines micro‐level channels through which financial development can affect such macroeconomic outcomes as level of income. Specifically, we investigate theoretically and empirically how financial constraints affect a firm's innovation activities. Theoretical predictions are tested using unique firm survey data, which provide direct measures for innovations and firm‐specific financial constraints, as well as information on shocks to firms' internal funds that serve as firm‐level instruments for financial constraints. We find unambiguous evidence that financial constraints restrain the ability of domestically owned firms to innovate and hence to catch up to the technological frontier.     

Comparing relative importance of the same component in a series system in two environments

The relative performance of a component of a series system in two different environments is considered. The conditional probability of the failure of the system due to the failure of the specified component given that the system failed before time t is regarded as a measure of relative importance of the component to the system. A U-statistic test for checking the equality of the relative importance of the component to the system in two different environments against the alternative that the relative importance is smaller in one of the environments, is proposed. Some simulation results for estimating the power of the test are reported. The proposed test is applied to one real data set and it is seen that a different aspect of the data is brought out by this comparison than that by the comparisons of the absolute importance functions such as the subsurvival functions, considered in earlier studies.     

Models and methods for pairing data

This paper deals with models and methods for count data derived from observations on pairing phenomena. Pairs formed from “similar” members are excluded. Various models are considered and analyzed. Particular emphasis is on developing methods for testing whether particular pairs are prone to occur more or less often than expected by chance.     

Approximate optimal allocation in repeated sampling from a finite population

Samples of size n are drawn from a finite population on each of two occasions. On the first occasion a variate x is measured, and on the second a variate y. In estimating the population mean of y, the variance of the best linear unbiased combination of means for matched and unmatched samples is itself minimized, with respect to the sampling design on the second occasion, by a certain degree of matching. This optimal allocation depends on the population correlation coefficient, which previous authors have assumed known. We estimate the correlation from an initial matched sample, then an approximately optimal allocation is completed and an estimator formed which, under a bivariate normal superpopulation model, has model expected mean square error equal, apart from an error of order n^-2, to the minimum enjoyed by any linear, unbiased estimator.     

局部环上典型群的非双曲型

引入域上典型群的生成问题所得的成果；对局部环R上典型群生成问题研究，构造度量函数及一平延，为局部环R上典型群向域F上的典型群导入，给出典型群的非双曲型．