Product Differentiation and Mergers in the Carbonated Soft Drink Industry

I simulate the competitive impact of several soft drink mergers from the 1980s on equilibrium prices and quantities. An unusual feature of soft drink demand is that, at the individual purchase level, households regularly select a variety of soft drink products. Specifically, on a given trip households may select multiple soft drink products and multiple units of each. A concern is that using a standard discrete choice model that assumes single unit purchases may understate the price elasticity of demand. To model the sophisticated choice behavior generating this multiple discreteness , I use a household-level scanner data set. Market demand is then computed by aggregating the household estimates. Combining the aggregate demand estimates with a model of static oligopoly, I then run the merger simulations. Despite moderate price increases, I find substantial welfare losses from the proposed merger between Coca-Cola and Dr. Pepper. I also find large price increases and corresponding welfare losses from the proposed merger between Pepsi and 7 UP and, more notably, between Coca-Cola and Pepsi.     

Studying the association between air pollution and lung cancer incidence in a large metropolitan area using a kernel density function

In the absence of patient-specific data, composite level data are often used in epidemiological studies. However, since individual exposure levels cannot accurately be inferred from aggregate data, such an approach may lead to erroneous estimates of health effects of potential environmental risk factors. In the present study, we attempt to address this information-loss problem by using the “kernel density function”, which estimates the intensity of events across a surface, by calculating the overall number of cases situated within a given search radius from a target point. The present paper illustrates the use of this analytical technique for a study of association between the geographical distributions of lung cancer cases and SO₂ air pollution estimates in the Greater Haifa Metropolitan Area (GHMA). In the analysis, the results obtained by kernel smoothing are contrasted with those obtained by areal aggregation techniques more commonly used in empirical studies.     

Repeat Purchase amid Rapid Quality Improvement: Structural Estimation of Demand for Personal Computers

This paper estimates a structural model of demand for the personal computer (PC) by repeat purchasers. Taking advantage of a large data set on household-level PC purchases, the econometric model uses variation in PC holdings among PC owners to identify households' marginal values of quality improvements. The analysis only requires data on a cross-section of households along with observed PC offerings over time, and accounts for stock effects, forward-looking behavior, and large amounts of household heterogeneity. The estimates allow us to measure sensitivity to long-term and short-term price and technology changes, as well as consumer welfare changes from technological improvements. The results show a large variation in marginal values for PC quality across households, and that failing to account for forward-looking behavior results in biased estimates and a poorer fit to the data. Incorporating stock effects proves especially important because, for the data used here, the model's parameters are not only biased but also virtually impossible to pin down without them. The results also show that price elasticity is approximately 25% higher in the short term compared to the long term, and technology elasticity is approximately 35% higher in the short term compared to the long term. Furthermore, welfare measurements are significantly underestimated when using a model that does not account for forward-looking behavior. Finally, the model is extended to include first-time purchasers. The results show similar patterns, but should be interpreted with much caution owing to the likely presence of significant unobserved heterogeneity between new purchasers and repeat purchasers.     

Air pollution-mortality models: A demonstration of the effects of random measurement error

Errors of measurement have long been recognized as a chronic problem in statistical analysis. Although there is a vast statistical literature of multiple regression models estimating the air pollution-mortality relationship, this problem has been largely ignored. It is well known that pollution measures contain error, but the consequences of this error for regression estimates is not known. We use Lave and Seskin's air pollution model to demonstrate the consequences of random measurement error. We assume a range of 0% to 50% of the variance of the pollution measures is due to error. We find large differences in the estimated effects on mortality of the pollution variables as well as the other explanatory variables once this measurement error is taken into account. These results cast doubt on the usual regression estimates of the mortality effects of air pollution. More generally our results demonstrate the consequences of random measurement error in the explanatory variable of a multiple regression analysis and the misleading conclusions that may result in policy research if this error is ignored.     

金融素养、金融资产配置与投资组合有效性

基于动态最优控制理论模型，运用中国家庭微观调查数据，系统研究了金融素养在家庭金融资产配置中的作用及对投资组合有效性的影响。理论分析表明，在一定条件下，金融素养能够显著提升家庭资产中风险性资产的配置比重，有助于实现消费效用最大化。考虑了内生性的实证分析结果表明：金融素养对于风险性资产与金融资产具有显著的正向影响，但无法作用于国债这类无风险资产；金融素养的提升有助于增加股票与基金的配置概率，有助于实施积极的投资策略，但对消极投资策略不显著；金融素养的提升能够显著增加家庭投资组合有效性，促使家庭获得更多的超额回报。     

Are CEOs expected utility maximizers?

Are individuals expected utility maximizers? This question represents much more than academic curiosity. In a normative sense, at stake are the fundamental underpinnings of the bulk of the last half-century’s models of choice under uncertainty. From a positive perspective, the ubiquitous use of benefit-cost analysis across government agencies renders the expected utility maximization paradigm literally the only game in town. In this study, we advance the literature by exploring CEO’s preferences over small probability, high loss lotteries. Using undergraduate students as our experimental control group, we find that both our CEO and student subject pools exhibit frequent and large departures from expected utility theory. In addition, as the extreme payoffs become more likely CEOs exhibit greater aversion to risk. Our results suggest that use of the expected utility paradigm in decision making substantially underestimates society’s willingness to pay to reduce risk in small probability, high loss events.     

Decision making under risk in Deal or No Deal

We analyse the choices of 399 contestants in the Australian version of the television game show Deal or No Deal. We calculate risk aversion bounds for each contestant, revealing considerable heterogeneity. We then estimate a structural stochastic choice model that captures the dynamic decision problem faced by contestants. To address individual heterogeneity, we nest the dynamic problem within the settings of both a random effects and a random coefficients probit model. Our structural model produces plausible estimates of risk aversion, confirms the role of individual heterogeneity and suggests that a model of stochastic choice is indeed appropriate. We find mixed evidence of greater risk aversion by females. We also examine generalizations to expected utility theory, finding that the rank‐dependent utility model adds non‐negligible explanatory power and indicates optimism in probability weighting. Finally, we test, but are unable to confirm, the existence of an endowment effect for lotteries. Copyright © 2009 John Wiley & Sons, Ltd.     

Equity, Price Elasticity, and Household Income Under Increasing Block Rates for Water

Abstract . For an examination of the relationships between household income levels and residential water use, individual household survey data from Tucson, Arizona the combined with monthly water use data for these same households. The objectives were to examine individual response to the existing block rate pricing structure and to provide policy conclusions on potential improvements in this rate structure. A simultaneous equation model of demand is estimated for households within each income group to determine the price elasticity of demand for each income group. The demand models show that under the existing increasing block rate pricing schedules, higher income households not only use more water, but have lower elasticities of demand. Thus a uniform proportional rate increase will cause a larger percentage drop in water use among low income households than among high income households. Given the assumption of declining marginal utility of water use, this result leads to a policy recommendation for substantially steeper block rates to improve interpersonal equity in water pricing.     

Spectral analysis of public utility returns

This study tests the practicality of using the capital asset pricing model to evaluate public utility returns. To this end, utilities are grouped into portfolios, in accordance with their industry classification and their prime regulatory authority. Then their relationship to a market index of unregulated securities is analyzed vis-à-vis the relationship between this index and several control securities believed, a priori, to be of commensurate risk. These relationships are analyzed in two steps: the first step investigates the real trend movements over time; the second, the association of the wide-sense stationary components of these return processes. Bivariate spectral analysis is used in the second phase of this investigation. This enables us to analyze the time lags between return processes, and to break up our estimates by duration of cyclical movement and compare the long-term and short-term estimates.We conclude that ordinary least squares estimates of utility β's lack value to either investors or regulators. This is due to the highly unstable relationship between utility returns and the market index and to the existence of a lag between these processes. One explanation for this finding is regulatory lag and the uncertainty (as well as the actual content) surrounding regulatory authority decisions.     

Credit rationing, race, and the mortgage market

This study applies microdata from the 1983 Survey of Consumer Finances to evaluate the effects of borrower race and default risk in mortgage lending. The empirical analysis is based on a probit model of whether borrowers obtain FHA or conventional mortgages; the former are fully insured and are characterized by easier downpayment constraints, but are typically more expensive. Hence, households borrowing through the FHA will tend to be credit constrained in the conventional market. Results of the analysis indicate that variables which proxy lender concerns about default risk and cost have an important effect on the type of loan borrowers obtain. Empirical estimates also suggest that minority households are significantly less likely to obtain conventional financing than whites, even after controlling for various proxies of default risk. These results suggest that race effects in mortgage lending may persist for reasons unrelated to borrower default risk.     

Coexistence of surplus labor and the Lewis turning point in China: a unitary household decision-making model study

This paper discusses the underlying relationship between surplus labor and the Lewis turning point in the duration of rapid economic growth in China. An agent-based model was proposed for studying the Lewis turning point and labor resource allocation, in which the decision-making interactions were made among the members of a household. This model differs from traditional development economics theory in which only an individual’s behavior is considered. How peasant households allocate their human capital to maximize the utility of a household unit was investigated on the basis of the unitary principle under the assumption of risk aversion. The roles of living expenses, subsidies and income adjustment factors were also considered. Our results revealed the paradoxical phenomenon that rural surplus labor and the Lewis turning point coexist.     

货币供应量变动对家庭风险资产持有比例的影响研究——基于利率渠道视角

构建跨期投资决策模型,运用CHFS微观数据和相关的宏观数据,基于利率渠道研究了货币供应量变动对家庭金融参与及风险资产持有比例的影响。理论分析表明,货币供应量增加导致货币市场利率降低时,各类风险偏好家庭的金融参与及风险资产持有比例均会提高。实证结果表明：货币供应量变动对货币市场利率的影响较弱,利率渠道可能存在堵塞;货币供应量变动通过利率渠道对风险喜好家庭的金融参与及风险资产持有比例有部分中介效应,但对风险规避家庭有完全中介效应。     

Demand for education, and its estimation

Since education produces major externalities and has important merit want characteristics, the estimation of a demand schedule is extremely difficult. Demand estimation for higher education is made somewhat easier because of the great importance of the associated costs and the relevant private substitutes, i.e. private colleges and universities. Therefore higher education is a good candidate for the application of the individual (economic) preference approach, which is based on the assumption that individuals are aware of their need for education about as they are aware of their needs for products provided by the open market.

The estimation of demand for primary and secondary education can rely only to a minor extent on the individual (economic) preference approach. The voter's behavior approach analysis is likely to be more directly applicable. Study of the behavior of voters and the behavior of legislators and members of school boards can shed light on the demand for education. Analytic insight can be gained also by the “voting with one's feet”, and the “calculus of consent” methods.

Finally, benefit-cost analysis can be applied in situations where education gives an extremely weak demand signal. In education we often are less interested in overall benefit-cost estimates than in the benefit-cost positions in which different important interest groups find themselves with regard to education. Such analysis requires the identification of significant interest groups, bargaining strategies, and bargaining patterns, as well as of ways in which education decision makers respond to group pressures.     

What drives equity market non-participation?

This paper produces endogenous equity market non-participation in an economy with uninsurable labor income risk and heterogeneous skill levels. Prudence and impatience generate stationary household wealth levels that depend on income. Skill, and therefore labor income, heterogeneity leads to wealth heterogeneity, with high skill households accumulating high wealth and low skill households accumulating low wealth. A HARA class utility with subsistence consumption requirement generates decreasing RRA with respect to household wealth. Consequently, low skill households also have significantly higher local RRA. In addition low skill households have less human capital and therefore have lower diversification demand for stocks. Low wealth, high RRA and low diversification demand predicts that low skill households do not hold stocks in the face of a moderate ownership cost. In addition, the model predicts a humped lifecycle wealth accumulation pattern and a humped lifecycle stock allocation pattern. I also find that stockholders exhibit a greater aggregate willingness to supply risky capital during the expansion phase of a business cycle, despite the lower conditional equity premium.     

Differences in Opportunities? Wage,Employment and House‐Price Effects on Migration*

Most empirical studies of individual migration choice analyse factors associated with out‐migration from an origin location. In contrast, we model the migration decision within the context of potential destinations, combining British panel data over the period 1992–2008 with other data sources. Contrary to earlier micro studies, we show that differences in house prices levels (but not growth) are important determinants of household migration for homeowners. Unemployed individuals respond to regional differences in expected individual wages, whereas the employed are more sensitive to employment opportunities. Our evidence is consistent with partners of heads of households being tied migrants.     

A Bayesian Multiple Comparison Procedure for Order-Restricted Mixed Models

A Bayesian hierarchical mixed model is developed for multiple comparisons under a simple order restriction. The model facilitates inferences on the successive differences of the population means, for which we choose independent prior distributions that are mixtures of an exponential distribution and a discrete distribution with its entire mass at zero. We employ Markov Chain Monte Carlo (MCMC) techniques to obtain parameter estimates and estimates of the posterior probabilities that any two of the means are equal. The latter estimates allow one both to determine if any two means are significantly different and to test the homogeneity of all of the means. We investigate the performance of the model-based inferences with simulated data sets, focusing on parameter estimation and successive-mean comparisons using posterior probabilities. We then illustrate the utility of the model in an application based on data from a study designed to reduce lead blood concentrations in children with elevated levels. Our results show that the proposed hierarchical model can effectively unify parameter estimation, tests of hypotheses and multiple comparisons in one setting.     

Endogenous household interaction

Most econometric models of intrahousehold behavior assume that household decision making is efficient, i.e., utility realizations lie on the Pareto frontier. In this paper, we investigate this claim by adding a number of participation constraints to the household allocation problem. Short-run constraints ensure that each spouse obtains a utility level at least equal to what they would realize under (inefficient) Nash equilibrium. Long-run constraints ensure that each spouse obtains a utility level at least equal to what they would realize by cheating on the efficient allocation and receiving Nash equilibrium payoffs in all successive periods. Given household characteristics and the (common) discount factor of the spouses, not all households may be able to attain payoffs on the Pareto frontier. We estimate these models using a Method of Simulated Moments estimator and data from one wave of the Panel Study of Income Dynamics. We find that both short- and long-run constraints are binding for sizable proportions of households in the sample. We conclude that it is important to carefully model the constraint sets household members face when modeling household allocation decisions, and to allow for the possibility that efficient outcomes may not be implementable for some households.     

Disclosure‐protected Inference Using Generalised Linear Models

Vast amounts of data that could be used in the development and evaluation of policy for the benefit of society are collected by statistical agencies. It is therefore no surprise that there is very strong demand from analysts, within business, government, universities and other organisations, to access such data. When allowing access to micro‐data, a statistical agency is obliged, often legally, to ensure that it is unlikely to result in the disclosure of information about a particular person or organisation. Managing the risk of disclosure is referred to as statistical disclosure control (SDC). This paper describes an approach to SDC for output from analysis using generalised linear models, including estimates of regression parameters and their variances, diagnostic statistics and plots. The Australian Bureau of Statistics has implemented the approach in a remote analysis system, which returns analysis output from remotely submitted queries. A framework for measuring disclosure risk associated with a remote server is proposed. The disclosure risk and utility of approach are measured in two real‐life case studies and in simulation.     

‘Stochastically more risk averse:’ A contextual theory of stochastic discrete choice under risk

Microeconometric treatments of discrete choice under risk are typically homoscedastic latent variable models. Specifically, choice probabilities are given by preference functional differences (given by expected utility, rank-dependent utility, etc.) embedded in cumulative distribution functions. This approach has a problem: Estimated utility function parameters meant to represent agents’ degree of risk aversion in the sense of Pratt (1964) do not imply a suggested “stochastically more risk averse” relation within such models. A new heteroscedastic model called “contextual utility” remedies this, and estimates in one data set suggest it explains (and especially predicts) as well as or better than other stochastic models.     

The economic returns to schooling for Italian men. An evaluation based on instrumental variables

We study the relationship between (log) hourly earnings and schooling for male household heads in Italy, using cross-sectional data from the 1993 and 1995 waves of the Bank of Italy (BI) survey on the income and wealth of Italian households. In line with international evidence, we find that OLS under-estimate the return to schooling. When the endogeneity of schooling is taken into account, the return to an additional year in school increases from 4.8% to 5.6%. This estimate is lower than the estimates tabulated by Card [Card, D., 1994. Earnings, Schooling and Ability Revisited. NBER Working Paper no. 4832.] for the United States. We also find evidence that this return increases with higher levels of educational attainment.