Impatience versus Incentives

This paper studies the dynamics of long‐term contracts in repeated principal–agent relationships with an impatient agent. Despite the absence of exogenous uncertainty, Pareto‐optimal dynamic contracts generically oscillate between favoring the principal and favoring the agent.     

财政分权和环境规制促进了中国绿色技术创新吗？

基于我国2003-2017年省级面板数据测算财政分权水平和财政分权效率,结合两阶段关联网络DEA测算绿色创新效率、绿色技术研发效率、绿色技术成果转化效率。结合理论模型与实证模型,分析了财政分权、环境规制对我国绿色技术创新的影响。结果表明：从整体上看,财政分权水平、财政分权效率和环境规制都是推动我国绿色创新发展的积极因素,财政分权还通过影响环境规制对绿色技术创新产生积极间接影响;但也导致了地方政府不注重绿色研发的短视行为。从不同时段看,财政分权和环境规制对绿色创新影响发生了变化,一是国际金融危机以后,财政分权加大了经济刺激政策对绿色创新发展的挤出效应,但这在新时代以后得到缓解;二是2013年以后地方环境规制水平提升过快,在一定程度上反而不利于绿色创新。从发展处于不同分位的地区看,财政分权对高、低分位地区绿色创新发展支持都稍显不足,但提高财政分权效率则能显著带动高分位地区发展;环境规制只在高分位地区促进了绿色创新发展,但对绿色创新效率较低的地区而言,过高的环境规制并没有实际意义。     

Model averaging inconcentration–QT analyses

This article describes how a frequentist model averaging approach can be used for concentration–QT analyses in the context of thorough QTc studies. Based on simulations, we have concluded that starting from three candidate model families (linear, exponential, and Emax) the model averaging approach leads to treatment effect estimates that are quite robust with respect to the control of the type I error in nearly all simulated scenarios; in particular, with the model averaging approach, the type I error appears less sensitive to model misspecification than the widely used linear model. We noticed also few differences in terms of performance between the model averaging approach and the more classical model selection approach, but we believe that, despite both can be recommended in practice, the model averaging approach can be more appealing because of some deficiencies of model selection approach pointed out in the literature. We think that a model averaging or model selection approach should be systematically considered for conducting concentration–QT analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Estimating Abundance from Presence–Absence Maps via a Paired Negative‐Binomial Model

The estimation of abundance from presence–absence data is an intriguing problem in applied statistics. The classical Poisson model makes strong independence and homogeneity assumptions and in practice generally underestimates the true abundance. A controversial ad hoc method based on negative‐binomial counts (Am. Nat.) has been empirically successful but lacks theoretical justification. We first present an alternative estimator of abundance based on a paired negative binomial model that is consistent and asymptotically normally distributed. A quadruple negative binomial extension is also developed, which yields the previous ad hoc approach and resolves the controversy in the literature. We examine the performance of the estimators in a simulation study and estimate the abundance of 44 tree species in a permanent forest plot.     

On the Flexibility of Metropolis–Hastings Acceptance Probabilities in Auxiliary Variable Proposal Generation

Abstract. Use of auxiliary variables for generating proposal variables within a Metropolis–Hastings setting has been suggested in many different settings. This has in particular been of interest for simulation from complex distributions such as multimodal distributions or in transdimensional approaches. For many of these approaches, the acceptance probabilities that are used turn up somewhat magic and different proofs for their validity have been given in each case. In this article, we will present a general framework for construction of acceptance probabilities in auxiliary variable proposal generation. In addition to showing the similarities between many of the proposed algorithms in the literature, the framework also demonstrates that there is a great flexibility in how to construct acceptance probabilities. With this flexibility, alternative acceptance probabilities are suggested. Some numerical experiments are also reported.     

Motherhood Penalties and Living Arrangements in China

Past research on the “motherhood wage penalty” has been based on data from nuclear families, leaving open the possibility that the motherhood wage penalty may be lower or even absent in multigenerational families. In this article, the wage gap between mothers and nonmothers is examined in nuclear and multigenerational families in the context of contemporary China, which has a long tradition of patriarchal families. Using 1993 to 2006 China Health and Nutrition Survey data, the magnitude and variation of motherhood penalty is explored with fixed effects models among 1,058 women. The results show that each additional child lowers hourly wages by about 12%. In addition, the motherhood penalty is largest for women living with their husbands' parents, smaller for women not living with parents, and nil for women living with their own parents.     

Separating Spheres? Diverging Trends in Youth's Gender Attitudes About Work and Family

The authors investigated whether trends in attitudes about gender were consistent with the gender stall primarily occurring in the family domain and examined potential mechanisms associated with changing gender norms. Using data from Monitoring the Future surveys (1976–2015), the authors assessed three components of trends in youth's beliefs about gender: the marketplace, the family, and mothers' employment. Findings showed continued increases in egalitarianism from 1976 through the mid‐1990s across all three dimensions. Thereafter, support for egalitarianism in the public sphere plateaued at high levels, rising support for mothers' employment persisted at a slower pace, and conventional ideology about gender in families returned. The changing demographic composition of American high school students did not account for the gender attitude trends. Youth's mothers' employment and increased education were related to increased egalitarianism. Changes in population averages of mothers' employment and educational attainment were only weakly associated with increases in egalitarian attitudes.     

A robust multivariate measurement error model with skew-normal/independent distributions and Bayesian MCMC implementation

Skew-normal/independent distributions are a class of asymmetric thick-tailed distributions that include the skew-normal distribution as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in multivariate measurement errors models. We propose the use of skew-normal/independent distributions to model the unobserved value of the covariates (latent variable) and symmetric normal/independent distributions for the random errors term, providing an appealing robust alternative to the usual symmetric process in multivariate measurement errors models. Among the distributions that belong to this class of distributions, we examine univariate and multivariate versions of the skew-normal, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.     

Geometric Anisotropic Spatial Point Pattern Analysis and Cox Processes

We consider spatial point processes with a pair correlation function, which depends only on the lag vector between a pair of points. Our interest is in statistical models with a special kind of ‘structured’ anisotropy: the pair correlation function is geometric anisotropic if it is elliptical but not spherical. In particular, we study Cox process models with an elliptical pair correlation function, including shot noise Cox processes and log Gaussian Cox processes, and we develop estimation procedures using summary statistics and Bayesian methods. Our methodology is illustrated on real and synthetic datasets of spatial point patterns.