Using eye-tracking to model attribute non-attendance in choice experiments

We investigate revealed attribute attendance in discrete choice experiments using eye-tracking. A simple theoretical framework is proposed in which choices are a function of visual attention. Consistent with the existing literature, the assumption that participants use all the available information to make their decisions does not hold. The results also illustrate that model fit and predictive power are greatly increased by using visual attendance measures as regressors. The use of eye-tracking technology has value for measuring revealed attention and to benchmark with existing choice models.     

Network effects and the choice of mobile phone operator

This paper explores the role of network effects in the consumer’s choice of mobile phone operators in the UK. It contributes to the existing literature by taking a new approach to testing for direct network effects and by using individual-level data, which allows to analyse the impact that the immediate social network has on consumer choice in network markets. For our empirical analysis we use two sources of data: market-level data from the British telecommunications regulator OFCOM and micro-level data on consumers’ usage of mobile telephones from the survey, Home OnLine. We estimate two classes of models which illustrate the role of network effects. The first is an aggregate model of the comparative volume of on-net and off-net calls. This finds that the proportion of off-net calls falls as mobile operators charge a premium for off-net calls, but even in the absence of any price differential between on-net and off-net, there is still a form of pure network effect, where a disproportionate number of calls are on-net. The second is a model of the individual consumer’s choice of operator. This finds that individual choice shows considerable inertia, as expected, but is heavily influenced by the choices of others in the same household. There is some evidence that individual choice of operator is influenced by the total number of subscribers for each operator, but a much stronger effect is the operator choice of other household members.     

A micro-analytic threshold model for the timing of first purchases of durable goods

A micro-analytic threshold model to describe the timing of household purchases of consumer durable goods is developed and tested. The model incorporates unobserved heterogeneity via a generalized gamma distribution and accounts for time varying covariates. Further, we employ estimation methods applicable or purchase data observed at periodic intervals of time. The model outperforms other competing models for predicting the timing of purchase of durable goods in terms of fit and predictive ability. In particular, this model outperforms the logit model and the diffusion model. The generalized gamma timing model predicts well the time to purchase the durable good; we show how it can be employed for micro-segmentation of households. Several research directions and applications are described.     

Consumer valuation of energy-saving features of residential air conditioners with hedonic and choice models

The promotion of energy-efficient appliances is necessary to reduce the energetic and environmental burden of the household sector. However, many studies have reported that a typical consumer underestimates the benefits of energy-saving investment on the purchase of household electric appliances. To analyze this energy-efficiency-gap problem, many scholars have estimated implicit discount rates that consumers use for energy-consuming durables. Although both hedonic and choice models have been used in previous studies, a comparison between the two models has not yet been made. This study uses point-of-sale data about Japanese residential air conditioners and estimates implicit discount rates with both hedonic and choice models. Both models demonstrate that a typical consumer underinvests in energy efficiency. Although choice models generally estimate a lower implicit discount rate than hedonic models, the latter models estimate the values of other product characteristics more consistently than choice models.     

Consumer choice and television

A consumer choice model which described 48 television programmes in terms of 48 specially constructed orthogonal characteristics was employed to predict how frequently adult US males would watch each of eight shows chosen for testing purposes. The first half of the random sample of 789 was used to construct estimates of the relevant structures and parameters including parameters of viewer utility functions. The second half was used for testing purposes. The predictive error was significantly less - 28 per cent less- than a naive alternative. This 28 per cent was apparently a significantly greater reduction than a comparable percentage found by BOWMAN and FARLEY (1972) using other techniques and the same data.     

Modelling preference heterogeneity for theatre tickets: a discrete choice modelling approach on Royal Danish Theatre booking data

This article analyses the behavioural choice for theatre tickets using a rich data set for 2010–2013 from the sale system of the Royal Danish National Theatre. A consumer who decides to attend a theatre production faces multiple sources of price variation that involves a choice by the consumer among different ticket alternatives. Three modelling approaches are proposed in order to model ticket purchases: conditional logit with socio-demographic characteristics, nested logit and latent class. These models allow us explicitly to take into account consumers’ preference heterogeneity with respect to the attributes associated with each ticket alternative (quality of the seat and day of the performance). In addition, the willingness to pay of choice attributes is estimated. Final results suggest that customers’ characteristics in terms of age and frequency of theatre attendance characterize different patterns of behaviour in the choice of theatre ticket.     

Analysis of product efficiency in the Korean automobile market from a consumer’s perspective

In this study we develop and describe a conceptual and methodological framework to measure technical and allocative efficiency at the product level considering consumer choice, which encompasses overall efficiency. Empirically, we combined data envelopment analysis and a discrete choice model in order to measure efficiency levels. The suggested framework is applied to the Korean automobile market. The relationship between the level of efficiency and market performance is discussed in terms of market share.     

Demand forecasting for multigenerational products combining discrete choice and dynamics of diffusion under technological trajectories

The discrete choice model generally captures consumers' valuation of the product's quality within the framework of a cross-sectional analysis, while the diffusion model captures the dynamics of demand within the framework of a time-series analysis. We propose an adjusted discrete choice model that incorporates the choice behavior of the consumer into the dynamics of product diffusion. In addition, a new estimation structure is proposed, within the framework of the time-series analysis, which enables the estimation of the discrete choice model on market-level data to be performed in such a way as to avoid the problem of price endogeneity and to obtain greater flexibility in forecasting demand. As an empirical application, the suggested model is applied to the case of the worldwide DRAM (dynamic random access memory) market. In forecasting future demand of DRAM generations, we integrate Moore's law and learning by doing to reflect the future technological trajectories of DRAM innovations, as well as consumers' consumption trends to reflect the dynamics of demand environments. As a result, the suggested model shows better performance in explaining the diffusion of new-generation product with limited number of data observations.     

Environmental Risk and Averting Behavior: Predictive Validity of Jointly Estimated Revealed and Stated Behavior Data

We conduct predictive validity tests using revealed and stated behavior data from a panel survey of North Carolina coastal households. The application is to hurricane evacuation behavior. Data was initially collected after Hurricane Bonnie led to hurricane evacuations in North Carolina in 1998. Respondents were asked for their behavioral intentions if a hurricane threatened the North Carolina coast during the 1999 hurricane season. Following Hurricanes Dennis and Floyd in 1999, a follow-up survey was conducted to see if respondents behaved as they intended. A jointly estimated revealed and stated behavior model indicates that the hypothetical and real evacuation behavior is based on the same choice process. Using predictions from this model with a hypothetical bias correction, we find that it predicts actual evacuation behavior with a small forecast error. These results suggest that stated behavior data has some degree of predictive validity.     

The Exchange Rate and Inflation in the UK

The United Kingdom is a highly open economy, and has a monetary policy strategy of targeting inflation in consumer prices. In this paper, we look at the evidence from the UK on inflation behaviour, and examine the propositions from several theoretical models about inflation dynamics in an open economy, focusing in particular on the hypothesized connections between the exchange rate and consumer price inflation. Theoretical open‐economy macroeconomic models ‘cover the waterfront’ on this issue, ranging from ‘exchange rate disconnect’ to a rigid link between nominal exchange rate changes and inflation. We estimate on UK data the open‐economy Phillips curves implied by the alternative explanations. We argue that, of the alternatives considered, only a model where imports are modelled as an intermediate good, as in McCallum and Nelson (1999) , provides a reasonable match with the data. Unlike the standard model, in which imports are treated as a final consumer good, the intermediate‐goods specification provides support for a policy of CPI inflation targeting.     

Forecasting demand for a newly introduced product using reservation price data and Bayesian updating

Forecasting demand during the early stages of a product's life cycle is a difficult but essential task for the purposes of marketing and policymaking. This paper introduces a procedure to derive accurate forecasts for newly introduced products for which limited data are available. We begin with the assumption that the consumer reservation price is related to the timing with which the consumer adopts the product. The model is estimated using reservation price data derived through a consumer survey, and the forecast is updated with sales data as they become available using Bayes's rule. The proposed model's forecasting performance is compared with that of benchmark models (i.e., Bass model, logistic growth model, and a Bayesian model based on analogy) using 23 quarters' worth of data on South Korea's broadband Internet services market. The proposed model outperforms all benchmark models in both prelaunch and postlaunch forecasting tests, supporting the thesis that consumer reservation price can be used to forecast demand for a new product before or shortly after product launch.     

石油合同对国际油气合作博弈影响分析

本文建立了国际油气合作中的资源国与消费国之间的合作博弈模型,分析了不同的油气合同模式对资源消费国效用水平的影响.研究表明,合同模式在油气合作博弈中扮演着重要角色.从投资者的角度看,为获得效用最大化,投资者不但应注意投资区块的选择,还要对资源国的合同模式进行深入分析和利弊权衡.通过对几种石油合同模式的比较,发现在总收益相同的条件下,从风险大小的角度考虑,纯服务合同带来的效用大于产品分成合同和矿税制合同；从收益的角度考虑,产品分成合同和矿税制合同使资源消费国保留了油价上涨时获取高额利润的权利,带来的效用大于技术服务合同.     

Towards Sustainable Consumption: Economics and Ethical Concerns for the Environment in Consumer Choices

The article examines individual action informed by ethical concerns for the environment as a strategy for moving toward more sustainable consumption. The article first employs a model of rational choice to analyze independent consumer choices among the usually assumed self- and welfare-centered consumers and then expands the model to analyze the implications of other than self- and welfare-centered motivations for consumer choice. The article next analyzes interdependent consumer choices informed by self- and welfare-centered values with the help of a simple game-theoretic model and then moves on to examine the implications of nonutilitarian environmental concerns for interdependent consumer choice in the same game-theoretic framework. The article concludes that although a strategy based on individual action may have limited promise when environmental concerns are widely shared, the case for collective action remains strong because of both efficiency and equity reasons.     

ON THE SOURCES OF UNCERTAINTY IN EXCHANGE RATE PREDICTABILITY

In a unified framework, we examine four sources of uncertainty in exchange rate forecasting models: (i) random variations in the data, (ii) estimation uncertainty, (iii) uncertainty about the degree of time variation in coefficients, and (iv) uncertainty regarding the choice of the predictor. We find that models that embed a high degree of coefficient variability yield forecast improvements at horizons beyond one month. At the one‐month horizon, and apart from the standard variance implied by unpredictable fluctuations in the data, the second and third sources of uncertainty listed above are key obstructions to predictive ability. The uncertainty regarding the choice of the predictors is negligible.     

Model uncertainty and asset return predictability: an application of Bayesian model averaging

We investigate model uncertainty associated with predictive regressions employed in asset return forecasting research. We use simple combination and Bayesian model averaging (BMA) techniques to compare the performance of these forecasting approaches in short-vs. long-run horizons of S&P500 monthly excess returns. Simple averaging involves an equally-weighted averaging of the forecasts from alternative combinations of factors used in the predictive regressions, whereas BMA involves computing the predictive probability that each model is the true model and uses these predictive probabilities as weights in combing the forecasts from different models. From a given set of multiple factors, we evaluate all possible pricing models to the extent, which they describe the data as dictated by the posterior model probabilities. We find that, while simple averaging compares quite favorably to forecasts derived from a random walk model with drift (using a 10-year out-of-sample iterative period), BMA outperforms simple averaging in longer compared to shorter forecast horizons. Moreover, we find further evidence of the latter when the predictive Bayesian model includes shorter, rather than longer lags of the predictive factors. An interesting outcome of this study tends to illustrate the power of BMA in suppressing model uncertainty through model as well as parameter shrinkage, especially when applied to longer predictive horizons.     

The impact of restructuring and deregulation on gas rates

This article evaluates the impact of consumer choice programs, price caps, and sliding scale plans on consumer prices of gas using a custom survey of public service commissions and data from the Department of Energy. A seemingly unrelated regressions model estimates residential, commercial and industrial prices jointly, controlling for potentially endogenous demand. Consumer choice programs are estimated to lower residential and commercial prices significantly, by bringing competition to markets with smaller consumers. Prices fall even before deregulation as utilities build consumer loyalty and fight competition. Sliding scale plans are estimated to lower prices of small consumers while raising industrial prices. Price caps lead to overall higher prices, with unclear ranking across consumer classes.      

Supermarket Choice and Supermarket Competition in Market Equilibrium

Multi-store firms are common in the retailing industry. Theory suggests that cross-elasticities between stores of the same firm enhance market power. To evaluate the importance of this effect in the U.K. supermarket industry, we estimate a model of consumer choice and expenditure using three data sources: profit margins for each chain, a survey of consumer choices and a data-set of store characteristics. To permit plausible substitution patterns, the utility model interacts consumer and store characteristics. We measure market power by calculating the effect of merger and demerger on Nash equilibrium prices. Demerger reduces the prices of the largest firms by between 2 and  3.8%  depending on local concentration; mergers between the largest firms lead to price increases up to  7.4%  .     

A Bayesian Approach to Double Bounded Contingent Valuation

In this paper we propose a Bayesian approach to model double bounded contingent valuation data. The double bounded elicitation method is interpreted as a two tier iterated process in which the subject is allowed to have a second thought about his/her valuation for the environmental good. Prior information is modelled from the answers to the first dichotomous choice question. The model is Quasi-Bayesian (Q-B) in that the prior distribution refers to mean willingness to pay while the likelihood function refers to the proportions of a multinomial distribution. This model is applied to empirical data from a contingent valuation survey involving the valuation expressed by European tourists for access to natural areas in the Canary Islands. Results show that point estimate of consumer surplus computed with the Q-B model does not differ substantially from single bounded model estimation. In addition, double bounded seems to be quite robust to the choice of the prior model of willingness to pay responses. Comparison with open ended suggests that the Q-B model might be useful to control for strategic response and starting point biases.