Using intersection matrices to identify graphical structure

Intersection matrices help identify the common graphical structure of two or more objects. They arise naturally in a variety of settings. Several examples of their use in a computer algebra environment are given. These include: simplifying an expression involving array products, automating cumulant calculations, determining the behaviour of an expected value operator and identifying model hierarchy in a factorial experiment. The emphasis is placed on the graphical structure, and the symmetry of arrays help reduce the complexity of the graphical problem.     

Analysis of incomplete durations with application to contraceptive use

Models for analysing incomplete durations obtained from cross-sectional surveys are presented. The aim of the paper is to develop a framework for analysing the incomplete duration of episodes in progress at the time of the survey by formulating generalized linear models and fitting and assessing them by using standard statistical packages. The maximum quasi-likelihood method is used for model fitting. The choice of the distribution and the diagnostic procedures are discussed. Simulated data from two distributions (the Weibull and log-logistic distributions) are used to evaluate the methodology developed and to assess model misspecifications. A data set on the current use of the contraceptive pill from a cross-sectional survey in Egypt is analysed.     

略论邓小平关于坚持中国共产党宗旨的思想

本文论述了邓小平关于坚持党的全心全意为人民服务的根本宗旨的思想 ,阐明了党是人民完成特定历史任务的工具 ;党必须要同人民群众建立起血肉联系 ,贯彻党的群众路线 ;党必须把人民是否拥护作为判定各项方针政策的出发点     

如何把旅游业培育成为新的经济增长点——常德市旅游业发展个案分析

现代旅游业具有不衰老性、广泛的关联性和无限资源性。西部大开发战略的实施和全球经济一体化进程的加快 ,给旅游业带来了前所未有的机遇和挑战。如何面对这种机遇和挑战 ,把旅游业培育成为新的经济增长点 ,对处于中部地区的常德的社会经济发展有着十分重要的意义     

Correcting the Errors: Volatility Forecast Evaluation Using High‐Frequency Data and Realized Volatilities

We develop general model‐free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit recent nonparametric asymptotic distributional results, are both easy‐to‐implement and highly accurate in empirically realistic situations. We also illustrate that properly accounting for the measurement errors in the volatility forecast evaluations reported in the existing literature can result in markedly higher estimates for the true degree of return volatility predictability.     

Nonparametric Identification under Discrete Variation

This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function that depends on a discrete endogenous variable and is nonseparable in latent variates. The function delivers values of a discrete or continuous outcome and instruments may be discrete valued. Application of the analog principle leads to quantile regression based interval estimators of values and partial differences of structural functions. The results are used to investigate the nonparametric identifying power of the quarter‐of‐birth instruments used in Angrist and Krueger's 1991 study of the returns to schooling.     

Structural Equations,Treatment Effects,and Econometric Policy Evaluation1

This paper uses the marginal treatment effect (MTE) to unify the nonparametric literature on treatment effects with the econometric literature on structural estimation using a nonparametric analog of a policy invariant parameter; to generate a variety of treatment effects from a common semiparametric functional form; to organize the literature on alternative estimators; and to explore what policy questions commonly used estimators in the treatment effect literature answer. A fundamental asymmetry intrinsic to the method of instrumental variables (IV) is noted. Recent advances in IV estimation allow for heterogeneity in responses but not in choices, and the method breaks down when both choice and response equations are heterogeneous in a general way.     

Estimation of smooth regression functions in monotone response models

We consider the estimation of smooth regression functions in a class of conditionally parametric co-variate-response models. Independent and identically distributed observations are available from the distribution of (Z,X)$(Z,X)$, where Z is a real-valued co-variate with some unknown distribution, and the response X conditional on Z   is distributed according to the density p(·,ψ(Z))$p(·,\psi (Z))$, where p(·,θ)$p(·,\theta )$ is a one-parameter exponential family. The function ψ$\psi$ is a smooth monotone function. Under this formulation, the regression function E(X|Z)$E(X|Z)$ is monotone in the co-variate Z   (and can be expressed as a one–one function of ψ$\psi$); hence the term “monotone response model”. Using a penalized least squares approach that incorporates both monotonicity and smoothness, we develop a scheme for producing smooth monotone estimates of the regression function and also the function ψ$\psi$ across this entire class of models. Point-wise asymptotic normality of this estimator is established, with the rate of convergence depending on the smoothing parameter. This enables construction of Wald-type (point-wise) as well as pivotal confidence sets for ψ$\psi$ and also the regression function. The methodology is extended to the general heteroscedastic model, and its asymptotic properties are discussed.     

Assessing non-tariff barriers in Syria

International trade in Syria is highly regulated through a combination of tariffs and non-tariff barriers. At 8% of the value of imports on average, effective tariffs are relatively low. However, non-tariff barriers to trade actually make Syria's trade restrictiveness very high. Comparing world and domestic prices of imports indeed suggests that non-tariff barriers increase the domestic price of imported goods by 17% on average, notably the result of significant quantitative restrictions. Using a computable general equilibrium model, the costs of NTBs on the Syrian economy are assessed. Simulations suggest that reallocation gains resulting from a complete removal of NTBs could be substantial. Accordingly, the key message from the analysis is that trade reform if it focuses only on tariff reduction will have limited growth benefits. On the contrary, if the Government abolishes the widespread non-tariff barriers to trade, including the elimination of quantitative trade restrictions, trade policy can become the central instrument to redress Syria's growth prospects.     

Dummy Endogenous Variables in Weakly Separable Models

In this paper, we consider the nonparametric identification and estimation of the average effect of a dummy endogenous regressor in models where the regressors are weakly but not additively separable from the error term. The model is not required to be strictly increasing in the error term, and the class of models considered includes limited dependent variable models such as discrete choice models. Conditions are established conditions under which it is possible to identify the average effect of the dummy endogenous regressor in a weakly separable model without relying on parametric functional form or distributional assumptions and without the use of large support conditions.