Estimation of hedonic price functions via additive nonparametric regression

We model a hedonic price function for housing as an additive nonparametric regression. Estimation is done via a backfitting procedure in combination with a local polynomial estimator. It avoids the pitfalls of an unrestricted nonparametric estimator, such as slow convergence rates and the curse of dimensionality. Bandwidths are chosen using a novel plug in method that minimizes the asymptotic mean average squared error (AMASE) of the regression. We compare our results to alternative parametric models and find evidence of the superiority of our nonparametric model. From an empirical perspective our study is interesting in that the effects on housing prices of a series of environmental characteristics are modeled in the regression. We find these characteristics to be important in the determination of housing prices.First version received: October 2002/Final version received: October 2003We thank B. Baltagi and two anonymous referees for their comments. The authors retain responsibility for any remaining errors.     

Does Economic Insecurity Cause Weight Gain Among Canadian Labor Force Participants?

The National Population Health Survey (NPHS) suggests that for labor force participants age 25 to 64, the prevalence of self‐reported obesity in Canada has increased from 16 percent in 1998 to 23 percent in 2008. Using six cycles of NPHS data (1998–2009), I explore Canada's obesity dilemma by considering the effect of economic insecurity—measured as the probability of an individual experiencing a severe negative economic shock. As an identification strategy, a fixed effects model is employed to control for unobserved time‐invariant heterogeneity and a set of instruments based on an individual's economic environment are specified in order to isolate causality. Results suggest that for males age 25 to 64, a 1 percent increase in economic insecurity is predicted to increase their body mass index (BMI) by 0.10 points. For females age 25 to 64, the association between economic insecurity and BMI is statistically insignificant at conventional confidence levels.     

Cost effectiveness of rimonabant use in patients at increased cardiometabolic risk: estimates from a Markov model

Summary

Rimonabant, the first selective CB-1 receptor blocker, is expected to reduce cardiometabolic risk substantially. This study assesses the economics of such treatment in patients at elevated cardiometabolic risk.

A Markov model was developed using data from the Rimonabant in Obesity (RIO) trial, published risk equations, and UK cost and utility data. Patients begin either in a diabetic or a non-diabetic state and can transition to cardiovascular disease or to death (based on UK life tables). Transitions to diabetes and subsequent cardiovascular events are also counted. Resource use due to events and long-term management were translated to UK costs (2005 GBP). Tariffs for events and states were applied to age-dependent utilities. Extensive univariate and multivariate probabilistic sensitivity analyses were carried out.

Over 10 years, 8% will suffer a cardiovascular event with a loss of more than 1,000 quality-adjusted life years (QALYs) and a cost of more than £500,000 per 1,000 patients. Projecting risk for a lifetime, 1 year of rimonabant use is estimated to gain >65 QALYs at £8,574/QALY. In probabilistic sensitivity analysis, incremental cost-effectiveness ratios varied from £2,657 to £22,141/QALY.

Based on the metabolic effects seen in clinical trials, rimonabant should reduce cardiovascular risk in obese or overweight people at reasonable cost.     

Non-convex Technologies and Cost Functions: Definitions,Duality and Nonparametric Tests of Convexity

This contribution is the first systematic attempt to develop a series of nonparametric, deterministic technologies and cost functions without maintaining convexity. Specifically, we introduce returns to scale assumptions into an existing non-convex technology and, dual to these technologies, define non-convex cost functions that are never lower than their convex counterparts. Both non-convex technologies and cost functions (total, ray-average and marginal) are characterized by closed form expressions. Furthermore, a local duality result is established between a local cost function and the input distance function. Finally, nonparametric goodness-of-fit tests for convexity are developed as a first step towards making it a statistically testable hypothesis. An erratum to this article is available at .     

工作要求与员工出勤主义行为的关系：工作不安全感和心理资本的作用

基于工作要求-资源理论模型和资源保存理论,通过问卷调查的方式,探讨了在中国背景下企业员工工作要求对出勤主义行为的影响,并提出了一个被调节的中介模型。研究结果表明:工作要求与工作不安全感及出勤主义行为呈显著正相关;工作不安全感在工作要求与出勤主义行为之间起部分中介作用;同时,心理资本能够缓冲工作要求对工作不安全感的消极影响,从而有效消除或限制了企业员工的出勤主义行为。     

消费者不安全感与怀旧产品购买行为研究

本文结合营销学、心理学和社会学等多领域的文献成果,对消费者的不安全感与怀旧产品购买行为之间的关系进行了实证调查。结果发现,当消费者感受到现实世界中的威胁、压力、创伤而处于心理上的不安全感状态时,会试图通过对旧事物的怀念寻找安慰,对那些引起过去经历回忆的怀旧产品激发出强烈的感情和购买倾向,以此来缓解不安全感。因此,不安全感(包括存在不安全感、个人不安全感、社会不安全感和发展不安全感)的增加是促使消费者更多选择怀旧产品的一个重要原因。企业在使用怀旧营销策略以帮助消费者缓解不安全感而促进产品销售时,可以采用设计怀旧的产品样式、采取古老的制作工艺和为产品虚构一个有意义的怀旧故事三种策略,其中,第三种策略效果最佳。     

基于非参数随机前沿面模型的高技术产业效率研究

笔者利用非参数-随机前沿面模型对我国的高技术产业效率进行了实证研究。研究结果表明我国的高技术产业发展过多的是依靠数量扩张,投入产出效率不高,各地区之间的高技术产业效率差异很大,而且在某些地区还存在着高技术产业发展水平和效率水平相背离的现象。     

Estimating bivariate yield distributions and crop insurance premiums using nonparametric methods

Modelling crop yield distribution is crucial in crop insurance premium setting. The correlation between different crop yields due to rotations or systemic risks requires estimation of joint yield distribution for multiple crops. In this article, we apply a nonparametric method to estimate bivariate yield distributions using farm-level yield data of wheat and corn in Shandong Province in China. Then, the simulated yields are used to evaluate the expected indemnity of one traditional and one hypothetical crop insurance programme. Our results reveal that the nonparametric bivariate method is very flexible in shaping the yield probability density functions to estimate local idiosyncrasies and correlation between two crops. It is also feasible to simulate the nonparametric yield distributions at a satisfying level of accuracy. The simulation results show that the hypothetical two-crop insurance contract can be more affordable to farmers than traditional individual crop insurance contracts.     

Is constant returns-to-scale a restrictive assumption for sector-level empirical macroeconomics? The case of Europe

Assuming constant returns-to-scale is commonly agreed for empirical macroeconomic studies when countries are of interest. Recently, an increasing number of works have started to look at sectors building on the same assumption. In this letter, we question the reliability of this assumption for 10 European sectors for the period 1995–2014, for different production factor combinations. We make use of a simple sample-based nonparametric test that does not require any assumptions for any aspect of the production process. Our results suggest that, in general, this assumption is rather acceptable and that the specification with only capital and labour is the best in this case.