Systematic Effects of Capital Service Price Definition on Perceptions of Input Substitution

Earlier attempts at reconciling disparate substitution elasticity estimates examined differences in separability hypotheses, data bases, and estimation techniques, as well as methods employed to construct capital service prices. Although these studies showed that differences in elasticity estimates between two or three studies may be attributable to the aforementioned features of the econometric models, they have been unable to demonstrate this link statistically and establish the existence of systematic relationships between features of the econometric models and the perception of production technologies generated by those models. Using sectoral data covering the entire production side of the U.S. economy, we estimate 34 production models for alternative definitions of the capital service price. We employ substitution elasticities calculated from these models as dependent variables in the statistical search for systematic relationships between features of the econometric models and perceptions of the sectoral technology as characterized by the elasticities. Statistically significant systematic effects are found between the monotonicity and concavity properties of the cost functions and service price–technical change specifications as well as between substitution elasticities.     

粮食主产区农村居民食物消费行为的计量分析

“民以食为天”,食物消费是人类生存和发展首要的物质基础。农村居民的食物消费水平是决定农村居民身体健康的物质基础,是农村居民生活水平的重要标志。研究和掌握食物消费结构特征,有利于农业产业结构调整和制定正确的农业产业政策,从而促进农民增收,实现农业的可持续发展。粮食主产区的粮食产量占全国粮食总产量的60%以上,对中国的粮食供给和安全具有举足轻重的作用,增加主产区农民收入有利于提高农民种粮食积极性,保证中国的粮食供给和粮食安全。为此,借助几乎理想的需求系统模型(Almost Ideal Demand System,简称AIDS),建立联立方程…     

The Bias in Price Elasticity Estimates Under Homothetic Separability: Implications for Analysis of Peak-Load Electricity Pricing

This article demonstrates that the assumption of a homothetically separable utility function places a priori restrictions on the parameters of the demand system. If these restrictions are unwarranted, an open question if they are not explicitly tested, they will lead to biased price elasticity estimates. In particular, we show that the uncompensated own-price elasticities must be smaller than the negative of the expenditure shares; that is, the price elasticity of peak electricity demand must be less than the negative of the share of expenditure devoted to peak electricity. This finding is probably not new to economists familiar with consumer demand analysis. Nevertheless, many recent studies of consumer demand for electricity under time-of-day rates explicitly impose this restriction. The resulting price elasticity estimates are usually quite large in absolute value (.5 to .8); but they are the product of restrictive a priori assumptions as well as information embodied in the sample data. The results of two analyses of time-of-day experiments, where the researchers imposed the untested assumption of homothetic separability, are examined more closely. We find that the reported price elasticities are strongly influenced by that a priori assumption. A Monte Carlo experiment demonstrates that using this model will lead to the reported price elasticities even if the consumption data are perfectly random with respect to price.     

Energy Use in Institutional Buildings: Estimates From State Energy-Audit Surveys

This article examines the determinants of energy demand for nearly 9,000 institutional buildings in the United States. The data were collected, as part of the federal Institutional Conservation Program, by state energy offices using mail surveys. The article presents energy demand estimates adjusted for differences in state surveys as well as for nonresponse bias, as functions of energy prices, building characteristics, and fuel-type variables for approximations of the installed heating ventilation and air-conditioning equipment. Energy price elasticities are found to vary from ?.28 for schools to ?1.05 for hospitals.     

The Effects of Price Aggregation Bias in Systems of Demand Equations

This article illustrates the importance of maintaining consistent levels of aggregation between prices and quantities when estimating consumer demand functions. The impact of violating this condition is quantified by using summary performance measures and estimates of demand elasticity biases. Results derived from an application of 1972–1973 Consumer Expenditure Survey data and supported with a quasi-Monte Carlo experiment consistently indicate that the point estimates of demand elasticities are significantly biased. Thus the study indicates the importance of developing and maintaining price indexes disaggregated to the same level as the expenditure data in consumer expenditure and budget surveys.     

Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care

Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member’s injury to induce variation in an individual’s own price. Across the conditional deciles of the expenditure distribution, I find elasticities that vary from ?0.76 to ?1.49, which are an order of magnitude larger than previous estimates. Supplementary materials for this article are available online.     

中国城镇居民肉类需求的单位价值弹性估计偏差研究

当前,对中国居民肉类需求的价格弹性估计多是利用汇总数据和用单位价值替代市场价格进行估计,而产品质量变化会导致用单位价值估计的价格弹性有偏。鉴此,利用全国984个样本汇总数据,估计城镇居民对猪牛羊禽肉的各种弹性,并且对利用单位价值估计的单位价值弹性和真实的价格弹性之间的偏差进行估计。结论显示:通过单位价值估计的价格弹性(单位价值弹性)高估了真实的价格弹性;随着收入水平的提高城镇居民对肉类质量水平需求会不断提高,通过单位价值高估的价格弹性程度将更强,因此对单位价值弹性偏差的衡量越发重要。     

Non-stationary structural model with time-varying demand elasticities

The paper considers local linear regression of a time series model with non-stationary regressors and errors. Asymptotic property of the local linear estimator is derived under a new dependence measure of non-stationary time series. We apply the local linear regression method to estimate the “time-varying” coefficients of an economic-causal model for the industrial sector of the U.S. economy. Nonparametric bootstrap test on the time-varying coefficients strongly suggests that the price/income elasticities of the U.S. durable goods demand are time-varying.     

Reduced-Form Versus Structural Models of Water Demand Under Nonlinear Prices

Increasing-block prices are common in markets for water, cellular phone service, and retail electricity. This study estimates demand models under block prices and conducts a Monte Carlo experiment to test the small-sample bias of structural and instrumental variables (IV) estimators. We estimate the price and income elasticity of water demand under increasing-block prices using a structural discrete/continuous choice (DCC) model, as well as random effects and IV. Elasticity estimates are sensitive to the modeling framework. The Monte Carlo experiment suggests that IV and DCC models estimate both price and income elasticity with bias, with no clear best choice among estimators.     

Search With Dirichlet Priors: Estimation and Implications for Consumer Demand

This article is an empirical application of the search model with an unknown distribution, as introduced by Rothschild in 1974. For searchers who hold Dirichlet priors, we develop a novel characterization of optimal search behavior. Our solution delivers easily computable formulas for the ex-ante purchase probabilities as outcomes of search, as required by discrete-choice-based estimation. Using our method, we investigate the consequences of consumer learning on the properties of search-generated demand. Holding search costs constant, the search model from a known distribution predicts larger price elasticities, mainly for the lower-priced products. We estimate a search model with Dirichlet priors, on a dataset of prices and market shares of S&P 500 mutual funds. We find that the assumption of no uncertainty in consumer priors leads to substantial biases in search cost estimates.     

Money-Demand Variability: A Demand-Systems Approach

This article tests the Fourier flexible form on quarterly U.S. monetary data. The data have been prescreened for consistency with the general axiom of revealed preference, and subindexes are formed using the Divisia approach. In this article, the global Fourier model fits well, although there is a potential problem of overfitting and certain data points exhibit behavior inconsistent with the model. The elasticities are variable over time, particularly around business-cycle troughs. It appears that financial asset demand surfaces are highly nonlinear and the many unsuccessful existing attempts to estimate money demand may not have worked well for this reason.     

Estimating class-specific parametric models using finite mixtures: an application to a hedonic model of wine prices

Hedonic price models are commonly used in the study of markets for various goods, most notably those for wine, art, and jewelry. These models were developed to estimate implicit prices of product attributes within a given product class, where in the case of some goods, such as wine, substantial product differentiation exists. To address this issue, recent research on wine prices employs local polynomial regression clustering (LPRC) for estimating regression models under class uncertainty. This study demonstrates that a superior empirical approach – estimation of a mixture model – is applicable to a hedonic model of wine prices, provided only that the dependent variable in the model is rescaled. The present study also catalogues several of the advantages over LPRC modeling of estimating mixture models.     

A Note on the Stochastic Approach to Index Numbers

In a recent article, Clements and Izan (1987) used the stochastic approach to index-number theory to estimate the rate of inflation and its standard error. Selvanathan (1988) extended their approach to the prices of groups of goods and to prices within groups. In this note, I apply the within-group results to the U.K. alcohol data. Simulation results show that the estimates are unbiased, but the asymptotic standard errors understate the true sampling variability of the estimates. To overcome this problem, I applied the bootstrap technique to obtain alternate standard errors.     

Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter

In this paper Bayesian methods are applied to a stochastic volatility model using both the prices of the asset and the prices of options written on the asset. Posterior densities for all model parameters, latent volatilities and the market price of volatility risk are produced via a Markov Chain Monte Carlo (MCMC) sampling algorithm. Candidate draws for the unobserved volatilities are obtained in blocks by applying the Kalman filter and simulation smoother to a linearization of a nonlinear state space representation of the model. Crucially, information from both the spot and option prices affects the draws via the specification of a bivariate measurement equation, with implied Black–Scholes volatilities used to proxy observed option prices in the candidate model. Alternative models nested within the Heston (1993) framework are ranked via posterior odds ratios, as well as via fit, predictive and hedging performance. The method is illustrated using Australian News Corporation spot and option price data.     

Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter

In this paper Bayesian methods are applied to a stochastic volatility model using both the prices of the asset and the prices of options written on the asset. Posterior densities for all model parameters, latent volatilities and the market price of volatility risk are produced via a Markov Chain Monte Carlo (MCMC) sampling algorithm. Candidate draws for the unobserved volatilities are obtained in blocks by applying the Kalman filter and simulation smoother to a linearization of a nonlinear state space representation of the model. Crucially, information from both the spot and option prices affects the draws via the specification of a bivariate measurement equation, with implied Black-Scholes volatilities used to proxy observed option prices in the candidate model. Alternative models nested within the Heston (1993) framework are ranked via posterior odds ratios, as well as via fit, predictive and hedging performance. The method is illustrated using Australian News Corporation spot and option price data.     

非线性定价有效吗

非线性定价存在于日常生活的方方面面,如阶梯电、水、气价格以及累进税率、通话套餐等。然而,价格信号的复杂性,使得消费者常常并未基于边际价格做出经济决策,关于非线性定价对于需求是否存在抑制的争论亦是此起彼伏。有鉴于此,本文基于Ito（2014）所提模型,利用广东省2010-2013年间各城市阶梯水价在时间维度和横截面维度的变异性以及微观住户月度用水消费数据,对消费者认知价格进行了甄别,并指出既往研究存在的识别问题。实证结果显示,住户当月消费基本是对上月平均价格而非边际价格或者期望边际价格做出反应,弹性约为-0.24。这说明,阶梯水价并未如设计初衷那样,通过跳跃性的价格激励机制降低住户用水需求,而是通过提高平均价格实现了对于住户用水的抑制。本文对于税率设计以及其他能源价格、通信套餐定价也有一定启发意义。     

住房价格、土地价格与地方政府行为

本文基于中国35个大中城市2005至2015年的面板数据,通过构建具有“空间依赖”性质的房价地价空间面板联立方程模型,深入研究房价与地价关系、地方政府行为对房价和地价的作用机制以及城际间的相互作用。研究表明,临近城市间的房价相互“模仿”并一同推动地价上涨,房价对地价的影响呈现“模仿促进”的作用特征;各城市通过尽可能抬高本地地价来拉大与临近城市地价水平的差距,进而推高房价,实现“以地生财”。此外,研究还证实地方政府通过“价格途径”和“政策途径”均能对房价进行有效调控,且“价格途径”具有一定的传染性;而“数量途径”和“结构途径”作为地方政府控制地价的有效手段,具有较强的溢出效应。     

Nonparametric Estimation of Search Costs for Differentiated Products: Evidence from Medigap

Abstract

This article develops a method to estimate search frictions as well as preference parameters in differentiated product markets. Search costs are nonparametrically identified, which means our method can be used to estimate search costs in differentiated product markets that lack a suitable search cost shifter. We apply our model to the U.S. Medigap insurance market. We find that search costs are substantial: the estimated median cost of searching for an insurer is $30. Using the estimated parameters we find that eliminating search costs could result in price decreases of as much as $71 (or 4.7%), along with increases in average consumer welfare of up to $374.     

EM Algorithm Estimation of Simultaneous Equation Model with Limited Variables: An Example of Cigarette Consumption

The two-part model and Heckman's sample selection model are often used in economic studies which involve analyzing the demand for limited variables. This study proposed a simultaneous equation model (SEM) and used the expectation-maximization algorithm to obtain the maximum likelihood estimate. We then constructed a simulation to compare the performance of estimates of price elasticity using SEM with those estimates from the two-part model and the sample selection model. The simulation shows that the estimates of price elasticity by SEM are more precise than those by the sample selection model and the two-part model when the model includes limited independent variables. Finally, we analyzed a real example of cigarette consumption as an application. We found an increase in cigarette price associated with a decrease in both the propensity to consume cigarettes and the amount actually consumed.     

Nonparametric Panel Estimation of Labor Supply

In this article, we estimate structural labor supply with piecewise-linear budgets and nonseparable endogenous unobserved heterogeneity. We propose a two-stage method to address the endogeneity issue that comes from the correlation between the covariates and unobserved heterogeneity. In the first stage, Evdokimov’s nonparametric de-convolution method serves to identify the conditional distribution of unobserved heterogeneity from the quasi-reduced model that uses panel data. In the second stage, the conditional distribution is plugged into the original structural model to estimate labor supply. We apply this methodology to estimate the labor supply of U.S. married men in 2004 and 2005. Our empirical work demonstrates that ignoring the correlation between the covariates and unobserved heterogeneity will bias the estimates of wage elasticities upward. The labor elasticity estimated from a fixed effects model is less than half of that obtained from a random effects model.