GMM with Many Moment Conditions

This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimators when the number of moment conditions is allowed to increase with the sample size and the moment conditions may be weak. Examples in which these asymptotics are relevant include instrumental variable (IV) estimation with many (possibly weak or uninformed) instruments and some panel data models that cover moderate time spans and have correspondingly large numbers of instruments. Under certain regularity conditions, the GMM estimators are shown to converge in probability but not necessarily to the true parameter, and conditions for consistent GMM estimation are given. A general framework for the GMM limit distribution theory is developed based on epiconvergence methods. Some illustrations are provided, including consistent GMM estimation of a panel model with time varying individual effects, consistent limited information maximum likelihood estimation as a continuously updated GMM estimator, and consistent IV structural estimation using large numbers of weak or irrelevant instruments. Some simulations are reported.     

典型特点与变异特点--域内闽语与周边闽语之语音比较

研究闽语的语音特点,有必要区分典型特点与变异特点,这样有助于更好地把握闽语的源和流,体现闽语的综合特征和下位特征.以往的研究,较多关注域内闽语的特点,对周边闽语的变异特点注意不够;而周边闽语的语音变异,又有内外因素在起作用.闽语的比较研究要达到一个理想的境地,周边闽语的语料显然是不能忽视的.     

Some rememarks on locally most powerful unbiased tests for the detection of mixtures of poisson or binomial distributions

In t h i s note mixture models are used to represent overdispersion relative to Poisson or binomial distributions. We flnd a sufflclent condition on the mixing distribution underich the detection of mixture departures from the Poisson or binomial adrnits a locally most powerful unbiased test. The conditions specify plynoria: relations between the variance and mean of Le glxing distribution.     

Uncertainty Evaluation of Human Risk Analysis (HRA) of Chemicals by Multiple Exposure Routes

The application of an ISO standard procedure (Guide to the Expression of Uncertainty in Measurement (GUM)) is here discussed to quantify uncertainty in human risk estimation under chronic exposure to hazardous chemical compounds. The procedure was previously applied to a simple model; in this article a much more complex model is used, i.e., multiple compound and multiple exposure pathways. Risk was evaluated using the usual methodologies: the deterministic reasonable maximum exposure (RME) and the statistical Monte Carlo method. In both cases, the procedures to evaluate uncertainty on risk values are detailed. Uncertainties were evaluated by different methodologies to account for the peculiarity of information about the single variable. The GUM procedure enables the ranking of variables by their contribution to uncertainty; it provides a criterion for choosing variables for deeper analysis. The obtained results show that the application of GUM procedure is easy and straightforward to quantify uncertainty and variability of risk estimation. Health risk estimation is based on literature data on a water table contaminated by three volatile organic compounds. Daily intake was considered by either ingestion of water or inhalation during showering. The results indicate one of the substances as the main contaminant, and give a criterion to identify the key component on which the treatment selection may be performed and the treatment process may be designed in order to reduce risk.     

On the Benefit of Inventory‐Based Dynamic Pricing Strategies

We study the optimal pricing and replenishment decisions in an inventory system with a price‐sensitive demand, focusing on the benefit of the inventory‐based dynamic pricing strategy. We find that demand variability impacts the benefit of dynamic pricing not only through the magnitude of the variability but also through its functional form (e.g., whether it is additive, multiplicative, or others). We provide an approach to quantify the profit improvement of dynamic pricing over static pricing without having to solve the dynamic pricing problem. We also demonstrate that dynamic pricing is most effective when it is jointly optimized with inventory replenishment decisions, and that its advantage can be mostly realized by using one or two price changes over a replenishment cycle.     

通用领域流行的方言词的语义功能变异——从地域方言词“大佬”谈起

针对方言词进入通用领域的语言现象,从地域方言词的个案入手,采用调查、统计等方法,考察方言词在通用领域流行的变异情况,证明通用领域中方言词的变异主要表现在语义和功能上。其中语义变异是基础,往往引起功能变异,并在结构、表达、风格等方面表现出来。方言词流行的根本动因是语义功能变化,内涵语义紧缩、外延语义使用域扩大、用法灵活化、表达新颖化。     

Benchmark Dose Estimation Incorporating Multiple Data Sources

With the increased availability of toxicological hazard information arising from multiple experimental sources, risk assessors are often confronted with the challenge of synthesizing all available scientific information into an analysis. This analysis is further complicated because significant between-source heterogeneity/lab-to-lab variability is often evident. We estimate benchmark doses using hierarchical models to account for the observed heterogeneity. These models are used to construct source-specific and population-average estimates of the benchmark dose (BMD). This is illustrated with an analysis of the U.S. EPA Region IX's reference toxicity database on the effects of sodium chloride on reproduction in Ceriodaphnia dubia. Results show that such models may effectively account for the lab-source heterogeneity while producing BMD estimates that more truly reflect the variability of the system under study. Failing to account for such heterogeneity may result in estimates having confidence intervals that are overly narrow.     

Loss of genetic variability in a fragmented continuously distributed population

An individual-based simulation model was used to examine the effect of population subdivision, dispersal distance of offspring, and migration rates between subpopulations on genetic variability(H ₁ H _S andH _T ) in a continuously distributed population. Some difficulties with mathematical models of a continuously distributed population have been pointed out. The individual-based model can avoid these difficulties and can be used to examine genetic variability in a population within which individuals are distributed continuously and in which the dispersal of individuals is disturbed by geographical or artificial barriers. The present simulation showed that the pattern of decrease inH ₁ had three stages. During the first stage,H ₁ decreased at the rates predicted by Wright’s neighborhood size. During the second stage,H ₁ decreased more rapidly when the migration rate decreased, while during the third stage, it decreased less rapidly when the migration rate decreased. Increasing the number of subdivisions increased the rate of decrease after the 200th generation. The pattern of decrease inH _T was classified into 2 stages. During the first stage, the rates of decrease corresponded with those of a randomly mating population. During the second stage, a decrease in the migration rates of the subpopulations slowed the rate of decrease inH _T . A uniform spatial distribution and a reduced total dispersal distance of offspring causedH ₁ H _S , andH _T to decrease more rapidly. Habitat fragmentation in a continuously distributed population usually was detrimental to the genetic variability in the early generations. Other implications of the results for conservation are discussed.