price promotions in choice models promotions are used in marketing to increase sales and drive profits by temporarily decreasing the price per unit of a good some price promotions apply to all quantities 20 off some have limits on the number of units that can be purchased at a reduced price and others only offer the discount if the volume purchased is sufficiently high we develop a model of price promotions in the context of a direct utility model where its effects are incorporated through the budget constraint price promotions complicate the estimation and analysis of direct utility models because they induce kinks and points of discontinuity in the budget set we propose a bayesian approach to addressing these irregularities and demonstrate the ability of the direct utility model to be used in counterfactual analyses of price promotions we investigate the stability of utility function estimates for consumers under alternative price promotions and find that the majority of the effect of a price promotion is through the budget s

decomposing promotional effects with a dynamic structural model of flexible consumption abstract in this article the authors offer a methodology to decompose the effects of price promotions into brand switching stockpiling and change in consumption by explicitly allowing for consumer heterogeneity in brand preferences and consumption needs they develop a dynamic structural model of a household that decides when what and how much to buy as well as how much to consume to maximize its expected utility over an infinite horizon by making certain simplifying assumptions the authors reduce the dimensionality of the problem they estimate the proposed model using household purchase data in the canned tuna and paper towels categories the results from the model offer insights into the decomposition of promotional effects into its components this could help managers make inferences about which brand s sales are more responsive to stockpiling or increase in consumption expansion and how temporary price cuts affect future sales contrary to previous literature the authors find that brand swi

empirical strategies for incorporating weak complementarity into consumer demand models abstract this article appraises existing empirical strategies for incorporating weak complementarity into consumer demand models the repackaging integrating back and discontinuity approaches are evaluated in terms of their behavioral implications and potential usefulness for applied research the appraisal suggests that the repackaging approach offers the most flexibility and tractability in the multi good demand system framework but the integrating back approach holds considerable promise in the single good context a multi good empirical comparison suggests that qualitatively similar policy inference arises from different repackaging approaches

demand heterogeneity for index based insurance the case for flexible products abstract a substantial literature has analyzed the challenges around weather index insurance yet an important design issue has been generally overlooked most index insurance products have so far been characterized by a one size fits all payout structure intended for a representative farmer at the cost of ignoring considerable heterogeneity in risk profiles this paper provides unique evidence on the ways in which heterogeneity in farmers risk exposure affects their demand for insurance we analyze a set of flexible insurance products against excess rainfall and exploit the substantial variation in insurance portfolios demanded by farmers we explore the relevance of alternative sources of heterogeneity by extending a simple expected utility decision model and relying on structural estimation to test their significance we find important aspects of farmer heterogeneity directly affecting their demand for insurance we quantify the benefits of a flexible scheme by comparing farmer welfare to that achieved under alternative counterfactual insurance options

structural workshop paper discrete choice models of consumer demand in marketing marketing researchers have used models of consumer demand to forecast future sales to describe and test theories of behavior and to measure the response to marketing interventions the basic framework typically starts from microfoundations of expected utility theory to obtain an econometric system that describes consumers choices over available options and to thus characterize product demand the basic framework has been augmented significantly to account for quantity choices to accommodate purchases of several products on a single purchase occasion multiple discreteness and multicategory purchases and to allow for asymmetric switching between brands across different price tiers these extensions have enabled researchers to bring the analysis to bear on several related marketing phenomena of interest this paper has three main objectives the first objective is to articulate the main goals of demand analysis forecasting measurement and testing and to highlight several considerations associated with these goals our second objective is to describe the main building blocks of individual level demand models we discuss approaches built on direct and indirect utility specifications of demand systems and we review extensions that have appeared in the marketing literature the third objective is to explore a few emerging directions in demand analysis including considering demand side dynamics combining purchase data with primary information and using semiparametric and nonparametric approaches we hope researchers new to this literature will take away a broader perspective on these models and see the potential for new directions in future research

why has u s inflation become harder to forecast we examine whether the u s rate of price inflation has become harder to forecast and to the extent that it has what changes in the inflation process have made it so the main finding is that the univariate inflation process is well described by an unobserved component trend cycle model with stochastic volatility or equivalently an integrated moving average process with time varying parameters this model explains a variety of recent univariate inflation forecasting puzzles and begins to explain some multivariate inflation forecasting puzzles as well

integrating technology traits and producer heterogeneity a mixed multinomial model of genetically modified corn adoption this article proposes a model of technology adoption that integrates demand for individual traits of new technologies with the potential for heterogeneity based on farm and farmer characteristics the model is applied to recent genetically modified corn adoption data from minnesota and wisconsin farmers using a mixed multinomial logit mmnl model to estimate the effects of traits and farm and farmer characteristics on adoption outcomes this approach allows explicit recovery of estimates of farmers shadow prices for individual technology traits results show the importance of producer and regional heterogeneity in preferences for seed traits

please or squeeze brand performance implications of constrained and unconstrained multi item promotions existing research on price promotions typically investigates the effects of single product promotions however brand managers often promote multiple items simultaneously to bolster the performance of a complete brand line this paper investigates the brand performance implications of such multi item promotions we distinguish between two types of multi item promotions traditional unconstrained multi item promotions that grant a discount irrespective of the size or composition of the purchase set and constrained multi item promotions that require consumers to purchase specific quantities self bundling or even predetermined combinations fixed bundling of promoted items using a normative consumer decision model the authors analyze the relative effectiveness of these promotions in terms of unit sales and revenue impact and show that promotion performance is moderated by consumers preference for variety the authors find that unconstrained multi item promotions outperform single item promotions especially in markets without variety seeking in markets with variety seeking unconstrained multi item promotions are not as effective in stealing extra sales from competition because consumers prefer to spread their purchases across all items including competitive ones however in those markets self bundling promotions are particularly effective because they force consumers to adopt larger amounts of the promoted items at the expense of competitors finally in neither type of market does fixed bundling substantially improve promotion performance

invited commentary commentary on structural modeling in marketing review and assessment chintagunta erdem rossi and wedel 2006 cerw discuss many different issues related to the use of structural models in marketing they use examples of structural models that involve both consumer demand and supply side competition to provide a critical assessment of the strengths and weaknesses of structural modeling and its future in marketing while they have done a very nice job the purpose of this commentary is to provide additional discussion of the three issues raised in their paper

trend of subjects published in economics journals 1969 2007 i introduction a fundamental question for any academic discipline is what subjects are people researching this question can be asked in several ways which subjects are economists publishing which subjects are economists reading which subjects have the most impact on the literature which subjects are represented in well respected general subject journals how many specialty journals are dedicated to each subject answers to these questions are useful for strategic planning publication strategy and curriculum design through the identification of shifting focus within the economics discipline for instance the research record of an economist who publishes in a widely published subject field that is little published in leading general subject journals should be evaluated differently from an economist whose fields have the opposite properties a liberal arts college that desires to make more of an impact on the literature may find that the subjects that need to be taught at the undergraduate level are in conflict with the subjects that are being published in top journals a subject area with a small percentage of articles published that has had a strong impact when adjusted for citations may be fertile ground for research although the study of economic research has a long history subject area focus has been little studied morin 1966 examined the sales of chamberlin s theory of monopolistic competition schumpeter s theory of economic development samuelson s foundations of economic analysis friedman s essays in positive economics and becket s economics of discrimination to examine the changes in economics from 1933 to 1964 figuring that most copies of these books were being read by researchers he posited that the changes in the sales of these books indicate shifts in interests within economics fusfeld 1956 examined the departments and types of institutions which were represented by papers at the 1950 1954 american economic association meetings he did not rank these departments but viewed the narrow group of represented schools as a flaw in the program selection niemi 1975 created rankings of the top 100 economics departments and the top southern economics departments according to the number of publications and the number of pages published in a group of 24 journals smith and gold 1976 adjusted niemi for the number of faculty members in each department graves marchand and thompson 1982 built on the work by niemi as well as smith and gold by updating their statistics and providing a trend analysis to examine rankings through time scott and mitias 1996 provided updated rankings by pages published using two different sets of economics journals and created a list of the top 50 economists by pages published davis and papanek 1984 first proposed using citations for ranking economics departments laband 1986 ranked departments based upon the productivity of the graduates of the program using both pages published and citations bodenhorn 1997 ranked liberal arts colleges by citations medoff 1989 ranked individual economists based upon citations and ranks schools based upon the number of top economists employed there although these analyses provide important insights into the productivity of economists and provide a benchmark for hiring and promotion to tenure few have discussed the distribution of subject areas within journals harden liano and chan 2006 calculated the percentage of real estate economics articles published mccain 1991 used article subjects in her cocitation analysis durden and ellis 1991 listed the most oft cited articles in the aer broken down by subject area kim morse and zingales 2006 examined all the articles from 1970 to 2005 that received more than 500 citations they used the econlit database to identify the journal of economic literature jel codes associated with each article

accounting for primary and secondary demand effects with aggregate data discrete choice models of aggregate demand such as the random coefficients logit can handle large differentiated products categories parsimoniously while still providing flexible substitution patterns however the discrete choice assumption may not be appropriate for many categories in which we expect consumers may purchase more than one unit of the selected item we derive the aggregate demand system corresponding to a discrete continuous household level model of demand we also propose a method of simulated moments procedure that provides consistent estimates of the structural parameters when only aggregate data are available the procedure also enables the researcher to control both for the potential endogeneity of marketing variables as well as potential heterogeneity in consumer tastes using our aggregate estimates we can measure the decomposition of price elasticities into incidence brand choice and purchase quantity components we also propose several empirical tests to assess the validity of the discrete continuous demand system versus that of the logit model in several simulation experiments we demonstrate the robustness of this model across datasets in which quantity choices may or may not be important our empirical calibration to store level data in the refrigerated orange juice category indicates a considerable improvement in fit of the observed aggregate sales using the discrete continuous model

structural modeling and policy simulation a primary goal of research in marketing is to evaluate and recommend optimal policies for marketing actions or instruments in the terminology of franses 2005 in this respect marketing is a very policy oriented field and it is ironic that so much published research skirts the issue of policy evaluation franses s article draws much needed attention to the question of what sort of model is usable for policy simulation and evaluation our perspective on what constitutes a valid model for policy evaluation differs from franses s view but we believe our view complements his in many important respects we also strongly believe that marketing has much to contribute to the literature on structural modeling we outline some of what we believe are the advantages for marketing scholars of using structural modeling for policy evaluations and some of the challenges presented by marketing problems franses focuses on a reduced form sales response model in which the outcome variable yt is modeled conditional on marketing variables xt if customers anticipate future marketing actions and take these into account in responding to the environment at time t an additional equation is appended to the system to describe the evolution of the xt variables in franses s view this system can be used for policy simulation if both the y and x equations have timeinvariant parameters that is the lucas critique which implies that parameters of reduced form models change if the policy regime changes does not apply according to franses a model must pass standard diagnostics possess good predictive properties and exhibit parameter stability to be useful for policy simulation we applaud the attention franses is bringing to model diagnostics we believe that structural work in both marketing and economics should pay close attention to the central features of the data increased use of model diagnostics will help ensure that structural models are capable of capturing these features however we do not believe that all the criteria proposed by franses such as out of sample validity and parameter stability are either necessary or sufficient to render a model useful for policy simulation reduced form models can pass all diagnostics including out of sample validation and still provide misleading predictions about the effects of policy changes reduced form

are professional macroeconomic forecasters able to do better than forecasting trends this paper investigates whether survey forecasters are able to make more accurate forecasts than simply supposing that the future values of the variable will move monotonically to the long run expectation we consider the forecasts individually and the consensus forecasts consensus survey forecasts are able to do so to varying degrees depending on the variable but this ability is largely limited to forecasts of the current quarter

forecasting efficiency concepts and applications this article introduces the concept of forecast efficiency in which the forecast contains all information available at the time of the forecast empirical tests investigate weak efficiency where the information set is all past forecasts and where all forecast revisions and errors should be uncorrelated with past forecast revisions tests of macroeconomic energy consumption and oil price forecasts find a significant autocorrelation of forecast revisions with fifty of fifty one tests showing positive correlation of forecast revisions as opposed to zero correlation consistent with forecast efficiency copyright 1987 by mit press

a discrete continuous model for multicategory purchase behavior of households abstract this article provides an integrated utility maximizing framework for households multicategory purchase incidence brand choice and purchase quantity decisions on a store visit households maximize utility across several categories subject to an overall budget constraint then they choose to purchase a subset of categories in which they select a specific brand and an associated quantity level under their assumptions for the stochastic terms in the specification the authors obtain closed form expressions for the household demands the marginal and joint purchase incidence and the brand choice probabilities along with conditional purchase quantities the authors show that the modeling framework accounts for both coincidence and complementarity substitutability across categories in addition it accounts for unobserved heterogeneity in the estimation thus the three key features of multicategory models proposed in the literature are all reflected in the framework the authors provide an empi

predictability of output growth and inflation a multi horizon survey approach we develop an unobserved components approach to study surveys of forecasts containing multiple forecast horizons under the assumption that forecasters optimally update their beliefs about past current and future state variables as new information arrives we use our model to extract information on the degree of predictability of the state variable and the importance of measurement errors in the observables empirical estimates of the model are obtained using survey forecasts of annual gdp growth and inflation in the united states with forecast horizons ranging from 1 to 24 months and the model is found to closely match the joint realization of forecast errors at different horizons our empirical results suggest that professional forecasters face severe measurement error problems for gdp growth in real time while this is much less of a problem for inflation moreover inflation exhibits greater persistence and thus is predictable at longer horizons than gdp growth and the persistent component of bot

structural estimation of the effect of out of stocks we develop a structural demand model that endogenously captures the effect of out of stocks on customer choice by simulating a time varying set of available alternatives our estimation method uses store level data on sales and partial information on product availability our model allows for flexible substitution patterns which are based on utility maximization principles and can accommodate categorical and continuous product characteristics the methodology can be applied to data from multiple markets and in categories with a relatively large number of alternatives slow moving products and frequent out of stocks unlike many existing approaches in addition we illustrate how the model can be used to assist the decisions of a store manager in two ways first we show how to quantify the lost sales induced by out of stock products second we provide insights on the financial consequences of out of stocks and suggest price promotion policies that can be used to help mitigate their negative economic impact which run counter to simple commonly used heuristics

implications of rational inattention abstract a constraint that actions can depend on observations only through a communication channel with finite shannon capacity is shown to be able to play a role very similar to that of a signal extraction problem or an adjustment cost in standard control problems the resulting theory looks enough like familiar dynamic rational expectations theories to suggest that it might be useful and practical while the implications for policy are different enough to be interesting

modeling consumer demand for variety consumers are often observed to purchase more than one variety of a product on a given shopping trip the simultaneous demand for varieties is observed not only for packaged goods such as yogurt or soft drinks but in many other product categories such as movies music compact disks and apparel multinomial mn choice models cannot be applied to data exhibiting the simultaneous choice of more than one variety the random utility interpretation of either the mn logit or probit model uses a linear utility specification that cannot accommodate interior solutions with more than one variety alternative chosen to analyze data with multiple varieties chosen requires a nonstandard utility specification standard demand models in the economics literature exhibit only interior solutions we propose a demand model based on a translated additive utility structure the model nests the linear utility structure while allowing for the possibility of a mixture of corner and interior solutions where more than one but not all varieties are selected we use a random utility specification in which the unobservable portion of marginal utility follows a log normal distribution the distribution of quantity demanded the basis of the likelihood function is derived from these log normal random utility errors the likelihood function for this class of models with mixtures of corner and interior solutions is a mixed distribution with both a continuous density portion and probability mass points for the corners the probability mass points must be calculated by integrals of the log normal errors over rectangular regions we evaluate these high dimensional integrals using the ghk approximation we employ a bayesian hierarchical model allowing household specific utility parameters our utility specification related to the approach of wales and woodland 1983 who employ a translated quadratic utility function wales and woodland were only able to study at the most three varieties because there was no practical way to evaluate the utility function at that time in addition the quadratic utility specification is not a globally valid utility function making welfare computations and policy experiments questionable hendel 1999 and dube 1999 present an alternative approach in the utility function which is constructed by summing up over unobservable consumption occasions while only one variety is consumed on each occasion the marginal utilities of varieties change over the consumption occasions giving rise to a simultaneous purchase of multiple varieties our bayesian inference approach allows us to obtain individual household estimates of utility parameters household utility estimates are used to compute the value of each variety we compute a compensating value for the removal of each flavor that is we compute the monetary equivalent of the household s loss in utility from removal of a flavor these calculations show that households highly value popular flavors and would incur substantial utility losses from removal of these flavors from the yogurt assortment next we consider the implications of our model for retailer assortment and pricing policies given limited shelf space only a subset of the possible varieties can be displayed for purchase at any one time if consumers value variety then a retailer with lower variety must compensate the consumers in some way such as a lower price level we see this trade off between price and variety across different retailing formats discount or warehouse format retailers often have both lower variety and lower prices to measure this trade off we explore the utility loss from reduction in variety and find the reductions in price that will compensate for this utility loss these price reduction calculations must be based on a valid utility structure heterogeneity in tastes is critical in these utility computations and policy experiments we find that a relatively small fraction of households with extreme preferences dominate the compensating value computations that is some households are observed to purchase mostly or exclusively one variety these households must be heavily compensated for the removal of this variety from the assortment in some retailing contexts customization of the assortment is possible at the customer level we show that such customization virtually eliminates any utility loss from reduction in variety

evaluating real time var forecasts with an informative democratic prior this paper proposes bayesian forecasting in a vector autoregression using a democratic prior this prior is chosen to match the predictions of survey respondents in particular the unconditional mean for each series in the vector autoregression is centered around long horizon survey forecasts heavy shrinkage toward the democratic prior is found to give good real time predictions of a range of macroeconomic variables as these survey projections are good at quickly capturing endpoint shifts

a hierarchical bayes model of primary and secondary demand product design pricing policies and promotional activities influence the primary and secondary demand for goods and services brand managers need to develop an understanding of the relationships between marketing mix decisions and consumer decisions of whether to purchase in the product category which brand to buy and how much to consume knowledge about factors most effective in influencing primary and secondary demand of a product allows firms to grow by enhancing their market share as well their market size the purpose of this paper is to develop an individual level model that allows an investigation of both the primary and secondary aspects of consumer demand unlike models of only primary demand or only secondary demand this more comprehensive model offers the opportunity to identify changes in product features that will result in the greatest increase in demand it also offers the opportunity to differentially target consumer segments depending upon whether consumers are most likely to enter the market increase their consumption level or switch brands in the proposed hierarchical bayes model an integrative framework that jointly models the discrete choice and continuous quantity components of consumer decision is employed instead of treating the two as independent the model includes parameters that capture individual specific reservation value attribute preference and expenditure sensitivity the model development is based upon the microeconomic theory of utility maximization heterogeneity in model parameters across the sample is captured by using a random effects specification guided by the underlying microeconomic model this requires that some of the effects are strictly positive this is accommodated through the use of a gamma distribution of heterogeneity for some of the parameters a normal distribution of heterogeneity is used for the remaining parameters gibbs sampling is used to estimate the model the key methodological contribution of this paper is that we show how to specify a hierarchical bayes continuous random effects model that integrates consumer choice and quantity decisions such that individual level parameters can be estimated individual level estimates are desirable because insights into primary demand involve nonlinear functions of model parameters for example consumers not in the market are those whose utilities for the choice alternatives fall below some reservation value the proposed methodology yields individual specific estimates of reservation values and expenditure sensitivity which allow assessment of the origins of demand other than the switch ing behavior of consumers the methodology can also be used to help identify changes in product features most likely to bring new customers into a market our work differs from previous research in this area as we lay the framework needed to obtain individual level parameter estimates in a continuous random effects model that integrates choice and quantity the methodology is demonstrated with survey data collected about consumer preferences and consumption for a food item for the data available a large response heterogeneity was observed across all model parameters in spite of limited data available at the individual level a majority of the individual level estimates were found to be significant predictive tests demonstrated the superiority of the proposed model over existing latent class and aggregate models particularly significant gains in predictive accuracy were observed for the no buy behavior of the respondents these gains demonstrate that by structurally linking the choice and quantity models results in a more accurate characterization of the market than existing finite mixture approaches that model choice and quantity independently we show that our joint model makes more efficient use of the available data and results in better parameter estimates than those that assume independence finally the individual level demand analysis is illustrated through a simple example involving a 1 00 price cut we demonstrate practical usefulness of the model for targeting by developing the demographic attitudinal and behavioral profiles of consumer groups most likely to increase consumption enter the market or switch brands because of a price cut decision

modeling indivisible demand disaggregate demand in the marketplace exists on a grid determined by the package sizes offered by manufacturers and retailers although consumers may want to purchase a continuous valued amount of a product realized purchases are constrained by available packages this constraint might not be problematic for high volume demand but it is potentially troubling when demand is small despite the prevalence of packaging constraints on choice economic models of choice have been slow to deal with their effects on parameter estimates and policy implications in this paper we propose a general framework for dealing with indivisible demand in economic models of choice and we show how to estimate model parameters using bayesian methods analyses of simulated data and a scanner panel data set of yogurt purchases indicate that ignoring packaging constraints can bias parameter estimates and measures of model fit which results in the inaccurate measures of metrics such as price elasticity and compensating value we also show that a portion of nonpurchase in the data e g 2 27 for yoplait original reflects the restriction of indivisibility not the lack of preference the importance of demand indivisibility is also highlighted by the counterfactual study where the removal of the smallest package size i e 4 oz mainly results in nonpurchase in the yogurt category instead of switching to larger package sizes

income and wealth effects on private label demand evidence from the great recession we measure the causal effects of income and wealth on the demand for private label products prior research suggests that these effects are large and in particular that private label demand rises during recessions our empirical analysis is based on a comprehensive household level transactions database matched with price information from store level scanner data and wealth data based on local house value indices the great recession provides a key source of the variation in our data showing a large and geographically diverse impact on household incomes over time we estimate income and wealth effects using within variation of income at the household level and wealth at the zip code level our estimates can be interpreted as income and wealth effects consistent with a consumer demand model based on utility maximization we establish a precisely measured negative effect of income on private label shares the effect of wealth is negative but not precisely measured however the estimated effect sizes

why do forecasters disagree lessons from the term structure of cross sectional dispersion abstract key sources of disagreement among economic forecasters are identified by using data on cross sectional dispersion in forecasters long and short run predictions of macroeconomic variables dispersion among forecasters is highest at long horizons where private information is of limited value and lower at short forecast horizons moreover differences in views persist through time such differences in opinion cannot be explained by differences in information sets our results indicate they stem from heterogeneity in priors or models differences in opinion move countercyclically with heterogeneity being strongest during recessions where forecasters appear to place greater weight on their prior beliefs

measuring market power in the ready to eat cereal industry the ready to eat cereal industry is characterized by high concentration high price cost margins large advertising to sales ratios and numerous introductions of new products previous researchers have concluded that the ready to eat cereal industry is a classic example of an industry with nearly collusive pricing behavior and intense nonprice competition this paper empirically examines this conclusion in particular i estimate price cost margins but more importantly i am able empirically to separate these margins into three sources i that which is due to product differentiation ii that which is due to multi product firm pricing and iii that due to potential price collusion the results suggest that given the demand for different brands of cereal the first two effects explain most of the observed price cost margins i conclude that prices in the industry are consistent with noncollusive pricing behavior despite the high price cost margins leading firms are able to maintain a portfolio of differentiated products and influence the perceived product quality it is these two factors that lead to high price cost margins

variety pass through an examination of the ready to eat breakfast cereal market abstract we examine variety pass through effects that occur when multiproduct retailers adjust the length of their product lines in response to changes in wholesale prices studying variety pass through is essential to understanding how wholesale price changes transmit into retail prices when variety is endogenous using data from the ready to eat breakfast cereal category we find that retailers jointly adjust retail prices and the length of their product lines in response to changes in wholesale prices we show the importance of controlling for the endogeneity of retailers product line decisions when calculating price pass through rates

multi category competition and market power a model of supermarket pricing in many competitive settings consumers buy multiple product categories and some prefer to use a single firm generating complementary cross category price effects to study pricing in supermarkets an organizational form where these effects are internalized we develop a multi category multi seller demand model and estimate it using uk consumer data this class of model is used widely in theoretical analysis of retail pricing we quantify crosscategory pricing effects and find that internalizing them substantially reduces market power we find that consumers inclined to one stop rather than multi stop shopping have a greater pro competitive impact because they generate relatively large cross category effects

what can survey forecasts tell us about information rigidities a lot we derive common and conflicting predictions from models in which agents face information constraints and then assess their validity using surveys of consumers firms central bankers and professional forecasters we document that mean forecasts fail to completely adjust on impact to shocks leading to statistically and economically significant deviations from the null of full information the dynamics of forecast errors after shocks are consistent with the predictions of models with information rigidities the conditional responses of forecast errors and disagreement among agents can also be used to differentiate between some of the most prominent models of information rigidities

the shopping basket a model for multicategory purchase incidence decisions consumers make multicategory decisions in a variety of contexts such as choice of multiple categories during a shopping trip or mail order purchasing the choice of one category may affect the selection of another category due to the complementary nature e g cake mix and cake frosting of the two categories alternatively two categories may co occur in a shopping basket not because they are complementary but because of similar purchase cycles e g beer and diapers or because of a host of other unobserved factors while complementarity gives managers some control over consumers buying behavior e g a change in the price of cake mix could change the purchase probability of cake frosting co occurrence or co incidence is less controllable other factors that may affect multi category choice may be unobserved household preferences or observed household demographics we also argue that not accounting for these three factors simultaneously could lead to erroneous inferences we then develop a conceptual framework that incorporates complementarity co incidence and heterogeneity both observed and unobserved as the factors that could lead to multi category choice we then translate this framework into a model of multi category choice our model is based on random utility theory and allows for simultaneous interdependent choice of many items this model the multivariate probit model is implemented in a hierarchical bayes framework the hierarchy consists of three levels the first level captures the choice of items for the shopping basket during a shopping trip the second level captures differences across households and the third level specifies the priors for the unknown parameters we generalize some recent advances in markov chain monte carlo methods in order to estimate the model specifically we use a substitution sampler which incorporates techniques such as the metropolis hit and run algorithm and the gibbs sampler the model is estimated on four categories cake mix cake frosting fabric detergent and fabric softener using multicategory panel data the results disentangle the complementarity and co incidence effects the complementarity results show that pricing and promotional changes in one category affect purchase incidence in related product categories in general the cross price and cross promotion effects are smaller than the own price and own promotions effects the cross effects are also asymmetric across pairs of categories i e related category pairs may be characterized as having a primary and a secondary category thus these results provide a more complete description of the effects of promotional changes by examining them both within and across categories the co incidence results show the extent of the relationship between categories that arises from uncontrollable and unobserved factors these results are useful since they provide insights into a general structure of dependence relationships across categories the heterogeneity results show that observed demographic factors such as family size influence the intrinsic category preference of households larger family sizes also tend to make households more price sensitive for both the primary and secondary categories we find that price sensitivities across categories are not highly correlated at the household level we also find some evidence that intrinsic preferences for cake mix and cake frosting are more closely related than preferences for fabric detergent and fabric softener we compare our model with a series of null models using both estimation and holdout samples we show that both complementarity and co incidence play a significant role inpredicting multicategory choice we also show how many single category models used in conjunction may not be good predictors of joint choice our results are likely to be of interest to retailers and manufacturers trying to optimize pricing and promotion strategies across many categories as well as in designing micromarketing strategies we illustrate some of these benefits by carrying out an analysis which shows that the true impact of complementarity and co incidence on profitability is significant in a retail setting our model can also be applied to other domains the combination of item interdependence and individual household level estimates may be of particular interest to database marketers in building customized cross selling strategies in the direct mail and financial service industries

valuing new goods in a model with complementarity online newspapers many important economic questions hinge on the extent to which new goods either crowd out or complement consumption of existing products recent methods for studying new goods rule out complementarity by assumption so their applicability to these questions has been limited i develop a new model that relaxes this restriction and use it to study competition between print and online newspapers using new micro data from washington dc i estimate the relationship between the print and online papers in demand the welfare impact of the online paper s introduction and the expected impact of charging positive online prices

a flexible yet globally regular multigood demand system a vexing challenge when using the utility maximization framework to estimate consumers decisions on which set of goods to purchase and how much quantity to buy is obtaining a functional form of the utility that satisfies three criteria tractability flexibility and global regularity flexibility refers to the ability of a utility function to impose minimal prior restrictions on demand elasticities global regularity refers to the ability of a utility function to satisfy regularity properties required by economic theory in the entire feasible space of variables the tractable utility functions used so far are either inflexible which could yield inaccurate estimates of underlying elasticities or do not satisfy global regularity which can result in invalid expressions of likelihood and invalid policy simulations i tackle this problem by deriving necessary and sufficient conditions for global regularity of basic translog utility using simulated and scanner data i show that the proposed demand system

estimating multiple discrete choice models an application to computerization returns buyers in many markets face multiple discrete choices they can purchase multiple units as well as multiple brands at the same time this paper presents a multiple discrete choice model for the analysis of differentiated products demand users maximize profits by choosing the number of units of each brand they purchase i estimate the model using micro level data on the demand for personal computers i use the estimated demand structure to assess the welfare gains from computerization and technological innovation in peripherals the estimated return on investment in personal computers is 92 moreover a 10 increase in the performance to price ratio of microprocessors leads to a 2 2 gain in the estimated user surplus the personal computer pc market is of interest to industrial organization economists because of its size the continual technological change and above all because of the farreaching implications of pcs on the economy as a whole several distinct features make pc demand difficult to model pcs are a differentiated durable good in constant technological evolution moreover buyers make multiple discrete choices firms according to our data spread their purchases of pcs over different brands at the same time they buy pcs in blocks several units of each brand that they have chosen the aim of the paper is to present a model that captures these features and to use this model to estimate the welfare gains from computerization classical discrete choice models allow one choice among mutually exclusive alternatives in contrast the proposed framework allows users to demand multiple units and multiple brands the model can be applied to other cases of multiple discrete choices e g the composition of airline fleets car holdings per household the fields of the faculty in economics departments household cereals consumption or any other good consumed in more than one variety during a relevant time period although pervasive multiple discrete choice problems have received little attention because of their complexity a central issue regarding the pc market is the current controversy in the economics literature about the computerization puzzle this puzzle stems from the empirical finding that computerization has had no effect on firm productivity griliches and siegel 1991 and morrison and berndt 1990 contrary to those results hendel 1994 and lichtenberg 1995 using more disaggregate data than most previous studies report excess returns to computerization this indicates that data aggregation may have created the computerization puzzle in this paper i present a model consistent with the basic

a dynamic analysis of market structure based on panel data internal market structure analysis infers brand positions in an attribute space from preference and choice data given a market in which consumers have heterogeneous tastes for attributes previous market structure models have adopted a static framework e g elrod 1988 chintagunta 1994 elrod and keane 1995 furthermore they assumed that consumer perceptions of brand attributes do not vary across consumers yet these approaches may render inaccurate representations of market structure if there is state dependence in consumer choice behavior this paper attempts to incorporate consumer choice dynamics into market structure models by specifying the source of choice dynamics explicitly in particular the process by which past purchases affect current choices is modeled in a framework which captures both consumer habit persistence and variety seeking behavior more specifically consumer preferences for brand attributes are modeled to depend on the attributes of brands bought on the previous purchase occasion furthermore the modeling approach adopted incorporates heterogeneity in both consumer preferences and perceptions of brand attributes the audience of this paper includes practitioners and academics interested in understanding consumer choice processes and inferring market structure from consumer choice data the proposed models are estimated on nielsen scanner panel data for margarine peanut butter yogurt and liquid detergent using simulated maximum likelihood techniques the empirical results suggest that accounting for choice dynamics improves both in sample and out of sample fit the results indicate that the average consumer is habit persistent in all the product categories studied this result is consistent with the findings of kannan and sanchez 1994 who conducted an aggregate analysis of consumer variety seeking behavior across product categories however the results obtained in this paper suggest that consumers are heterogeneous with respect to the processes by which past purchases affect current purchases these results provide strong evidence for habit persistence and variety seeking in brand attributes to be the behavioral source of consumer choice dynamics in food categories thus consumer tastes utility weights seem to be affected by the attributes of the brands consumed in the past given the empirical result that a large proportion of consumers are habit persistent this suggests that tastes are reinforced by the brand attributes consumed in the past the empirical results also show that not accounting for state dependence in market structure models for panel data may produce misleading results that is depending on consumer behavior patterns models that do not account for state dependence may distort the true nature of competition among brands more specifically the results confirm the expectation that if there is habit persistence that is if consumer tastes are reinforced by attributes of brands consumed in the past models that do not capture this choice dynamics will overestimate the distance between similar brands furthermore the policy experiments conducted suggest that 1 static models overestimate the short run impact of a price cut on the sales of the brand on promotion 2 price cuts hurt the sales of the more similar brands more and 3 free samples affect relatively less similar brands the most finally this paper studies variety seeking and habit persistence across brands over purchase occasions however variety seeking behavior may also involve the purchase of a portfolio of brands or items at a purchase occasion consumers may buy multiple items knowing that prior to the next trip they may want to consume different items simanson 1990 walsh 1995 this type of behavior can be modeled within the context of dynamic expected utility maximization with forward looking consumers the development and estimation of market structure models that include forward looking consumers who maximize expected utility over a planning horizon incorporating their future tastes and needs and shopping for an inventory of brands remain an important future research issue

estimating a continuous hedonic choice model with an application to demand for soft drinks using micro level scanner data i study empirically the consumer demand for soft drinks which is characterized by multiple product multiple unit purchasing behavior i develop a continuous hedonic choice model to investigate how consumers choose the best basket of products to satisfy various needs my model s embedded characteristics approach both helps to reduce the dimensionality problem in model estimation and generates flexible substitution patterns hence the model is useful in application to data with many product choices that are correlated with each other at the individual level the estimation results show that interesting substitutability and even a form of complementarity exist among soft drinks

beyond the endogeneity bias the effect of unmeasured brand characteristics on household level brand choice models we investigate the role of potential weekly brand specific characteristics that influence consumer choices but are unobserved or unmeasurable by the researcher we use an empirical approach based on the estimation methods used for standard random coefficients logit models to account for the presence of such unobserved attributes using household scanner panel data we find evidence that ignoring such time varying latent to the researcher characteristics can lead to two types of problems first consistent with previous literature we find that these unobserved characteristics may lead to biased estimates of the mean price response parameters this argument is based on a form of price endogeneity if marketing managers set prices based on consumer willingness to pay then the observed prices will likely be correlated with the latent to the researcher brand characteristics we resolve this problem by using an instrumental variables procedure our findings suggest that simply ignoring these attributes may also lead to larger estimates of the variance in the heterogeneity distribution of preferences and price sensitivities across households this could overstate the benefits from marketing activities such as household level targeting we resolve the problem by using weekly brand intercepts embedded in a random coefficients brand choice model to control for weekly brand specific characteristics while accounting for household heterogeneity overall our results extend the finding on the endogeneity bias from the mean of the heterogeneity distribution i e the price effect to include the variance of that distribution

testing the rationality of price forecasts new evidence from panel data this paper tests the rationality of individual price forecasts in a panel of professional forecasters here unlike in most previous studies rationality is not rejected the results here differ because 1 using individual forecasts avoids aggregation bias 2 comparison of forecasts to initial data avoids bias due to data revision 3 the professional forecasters have economic incentives to state their expectations accurately and 4 a new covariance matrix estimator consistent when forecast errors are correlated across individuals is used copyright 1990 by american economic association

logit demand estimation under competitive pricing behavior an equilibrium framework discrete choice models of demand have typically been estimated assuming that prices are exogenous since unobservable to the researcher product attributes such as coupon availability may impact consumer utility as well as price setting by firms we treat prices as endogenous specifically prices are assumed to be the equilibrium outcomes of nash competition among manufacturers and retailers to empirically validate the assumptions we estimate logit demand systems jointly with equilibrium pricing equations for two product categories using retail scanner data and cost data on factor prices in each category we find statistical evidence of price endogeneity we also find that the estimates of the price response parameter and the brand specific constants are generally biased downward when the endogeneity of prices is ignored our framework provides explicit estimates of the value created by a brand i e the difference between consumers willingness to pay for a brand and its cost of production we develop theoretical propositions about the relationship between value creation and competitive advantage for logit demand systems and use our empirical results to illustrate how firms use alternative value creation strategies to accomplish competitive advantage

household electricity and gas consumption for heating homes energy consumption has been drastically changed because of energy source depletion price fluctuations development and penetration of alternative energy sources and government policies household energy sources are interrelated and energy price and household characteristics such as income level and dwelling size affect the usage to supply energy consistently and achieve a balance between production and consumption stakeholders must understand consumer energy consumption behavior therefore this study identifies household heating energy usage patterns and the substitutive and or complementary relationships between electricity and gas based on a multiple discrete continuous extreme value model household utility structure is identified from data on gas heating usage results show greater utility and the smallest satiation values for gas boilers than for electric heaters and electric heating beds the effects of consumer socioeconomic and environmental characteristics on the choice of heating energy sources were analyzed also for further comparison the respondents were split into high and low categories for income heating degree days dwelling size and gas usage gas was found to be the most economical heating choice for households

investigating consumers purchase incidence and brand choice decisions across multiple product categories a theoretical and empirical analysis we propose a framework to investigate consumers brand choice and purchase incidence decisions across multiple categories where both decisions are modeled as an outcome of a consumer s basket utility maximization we build the model from first principles by theoretically explicating a general model of basket utility maximization and then examining the reasonable restrictions that can be placed to make the solution tractable without sacrificing its flexibility comparing with prior models we show why prior multicategory purchase incidence models overemphasize the role of the cross effects of a market mix of brands in other categories on the purchase incidence decision of a given category additionally we show that prior single category models are a special case of the proposed model when further restrictions are placed on the basket utility structure we estimate the model on household basket data for the laundry family of categories we show i why prior single category and multicategory models would systematically bias the estimates of the own and cross price promotional purchase incidence elasticities and ii how the market mix of each brand in each category affects the purchases across all categories which can help retailers make promotional decisions across a portfolio of products

estimating the impact of consumer expectations of coupons on purchase behavior a dynamic structural model we examine the basic premise that consumers may anticipate future promotions and adjust their purchase behavior accordingly we develop a structural model of households who make purchase decisions to minimize their expenditure over a finite period the model allows for future expectations of promotions to enter the purchase decision households with adequate inventory of the product may face a trade off of buying in the current period with a coupon or defer the purchase until next period given their expectations of future promotions thus we provide a framework for examining the impact of consumer expectations on choice behavior the target audiences for our paper are a empirical researchers who intend to make structural models part of their applied research agenda and b managers who value and seek to understand the impact of consumers coupon expectations on current purchase behavior our research objective is to provide an empirical framework to examine whether and to what extent consumers anticipate future coupon promotions and adjust purchase behavior the central premise of our approach is that a rational consumer minimizes the present discounted value of the cost of a purchase where cost in a single period consists of purchase price inventory holding cost gains from coupons and potential stockout cost we aim to test whether our hypotheses regarding the various elements of the cost structure are supported and that whether consumers take into account future discounted cost when making current purchase decisions the research methodology we adopt is relatively new in econometrics and known as the estimable stochastic structural dynamic programming method the methodology amounts to incorporating a maximum likelihood routine embedded in a dynamic programming problem the dynamic programming problem is solved several times within a maximum likelihood iteration for each value of the state space elements and for each value of the parameters in the parameter set the state space in our model consists of purchase and nonpurchase alternatives in each time period coupon availability and no coupon availability in each time period level of inventory in each time period for each household and consumption rate of each household we use scanner panel data on purchases in the disposable diaper product category and promotions we estimate the inventory holding and stockout costs brand specific value of coupons and consumers expectations of future coupons the key insights and lessons learned can be summarized as follows 1 our results are consistent with the notion that consumers hold beliefs about future coupons and that such beliefs affect the purchase decision we find that the dynamic optimization model performs significantly better than a single period optimization model and a naive benchmark model 2 we find a high and significant stockout cost consistent with the essential nature of the product category our estimate of the holding cost yields a reasonable annualized percentage value when converted to the cost of capital we find that consumer valuation of coupons differ markedly across brands 3 our empirical evidence supports the notion that consumers hold beliefs about future coupon availability we also find that the expectations about future coupons estimated endogenously differ depending upon whether or not a coupon was available in the current period thus the proposed model structure yields rich managerial insights and facilitates several what if scenarios a possible limitation of our model and estimable structural models in general is the computational cost while it is possible to conceptually extend the state space to accommodate variations across households and add a richer parameter structure each addition multiplies the size of the state space and the computation time for this reason we have kept the state space as tight as possible and refrained from additions that would otherwise enable us to incorporate heterogeneity in consumer decisions for example we assumed that consumers are similar other than reflected by their purchase behavior we built a category purchase incidence model rather than a brand choice model we refrained from including unobserved heterogeneity in the parameters we chose to opt out of modeling autocorrelation and other time dependent error term patterns in the likelihood function thus we have made an effort to build a structural model that reasonably reflects consumer purchase behavior without requiring expensive computation currently there are developments in econometrics to approximate the computation of the valuation functions without sacrificing much accuracy when these methods are well developed we expect that structural models will become more commonplace in marketing

a new utility consistent econometric approach to multivariate count data modeling summary in the current paper we propose a new utility consistent modeling framework to explicitly link a count data model with an event type multinomial choice model the proposed framework uses a multinomial probit kernel for the event type choice model and introduces unobserved heterogeneity in both the count and discrete choice components additionally this paper establishes important new results regarding the distribution of the maximum of multivariate normally distributed variables which form the basis to embed the multinomial probit model within a joint modeling system for multivariate count data the model is applied to analyzing out of home non work episodes pursued by workers using data from the national household travel survey copyright 2014 john wiley sons ltd

a simultaneous approach to the whether what and how much to buy questions consumer s purchase decisions of whether to buy what to buy and how much to buy are examined simultaneously based on a consumer utility maximization problem an unobservable threshold price about which a consumer pivots from nonpurchase to purchase can be deduced with any model specification the interrelationships between purchase decisions can be explicitly derived the model is applied to coffee purchasing data in addition by suppressing the nonpurchase options the model is compared with an alternative approach appearing in the marketing literature

rivalry in price and variety among supermarket retailers recent theoretical models of retail competition suggest that product heterogeneity is critical to retail price and variety strategies this article provides empirical evidence on supermarket retailers price and variety strategies using a nested constant elasticity of substitution nces modeling framework the model is estimated using chain level scanner data for four major grocery chains in a large urban west coast market the results show that retailers compete for market share using both price and variety while they all tend to follow moderately cooperative pricing strategies the extent to which they follow cooperative strategies in variety is less homogeneous

taking the pulse of the economy measuring gdp national income and product accounts best known by one of their principle aggregates gross domestic product gdp are produced by virtually every nation in the world simon kuznets and richard stone both later to become nobel prize winners led the creation of the national accounts for the united states and the united kingdom respectively so what exactly does gdp measure how is it constructed why do the gdp and other national accounts estimates sometimes present a different picture of the economy than other economic indicators this article is intended to help answer these questions by providing a broad overview of the measurement techniques used in estimating gdp and the national accounts in the united states in the united states the gdp and the national accounts estimates are fundamentally based on detailed economic census data and other information that is available only once every five years the challenge lies in developing a framework and methods that take these economic census data and combine them using a mosaic of monthly quarterly and annual economic indicators to produce quarterly and annual gdp estimates for example one problem is that the other economic indicators that are used to extrapolate gdp in between the five year economic census data such as retail sales housing starts and manufacturers shipments of capital goods are often collected for purposes other than estimating gdp and

flexibility in consumer purchasing for uncertain future tastes consumers often simultaneously purchase multiple units in the same product category whether they are best off purchasing an assortment of alternatives or an equal number of one alternative is addressed in this paper models of an expected utility maximizing consumer are developed and it is shown that an assortment may have greater expected utility than an equal number of any one alternative the rationale is that the assortment allows the consumer to choose from inventory the alternative most appropriate for a consumption occasion using preference information not available at the purchase occasion it is also shown that when consuming alternatives from inventory the consumer may forego the alternative offering the most utility in the expectation that it will yield even more utility in the future

investigating purchase incidence brand choice and purchase quantity decisions of households we develop a comprehensive utility maximizing framework to study the impact of marketing variables on the category purchase brand choice and purchase quantity decisions of households for frequently purchased packaged goods the model allows for dependence among the three decisions while ensuring that these decisions provide in combination the greatest possible utility to the household by accounting for variations in reservation prices and intrinsic brand preferences across households the modeling framework explicitly captures the effects of unobserved heterogeneity on all three purchase decisions the principal empirical finding from analyzing the a c nielsen data for the yogurt product category is that the substantive implications for the effects of marketing variables are sensitive to whether these effects are determined conditional or unconditional on a product category purchase our results show that reservation prices and intrinsic brand preferences vary across households and not accounting for these variations in the estimation could lead to biased estimates for the coefficients of the marketing variables a comparison of our results to those obtained from a nested logit model of purchase incidence and brand choice reveals that our proposed model performs better using both a formal statistical test as well as the criterion of predictive validity in a holdout sample of panelists further the purchase quantity model compares favorably with two alternative models of quantity choice in the validation sample

similarities in choice behavior across product categories differences between consumers in sensitivity to marketing mix variables have been extensively documented in the scanner panel data all studies of consumer heterogeneity focus on a specific category of products and ignore the fact that the purchase behavior of panel households is often observed simultaneously in multiple categories if sensitivity to marketing mix variables is a common consumer trait then one should expect to see similarities in sensitivity across multiple categories the goal in this paper is to measure the covariance of both observed linked to measured characteristics of households and unobserved heterogeneity in marketing mix sensitivity across multiple categories measurement of correlation in sensitivities across categories will serve to guide the interpretation of the literature on household heterogeneity if there is a large correlation one can be more confident that sensitivity to marketing variables is a fundamental household pr operty and not simply a category specific anomaly detection of correlation in sensitivities across categories requires an appropriate methodology that can handle the high dimensional covariance structures and properly account for uncertainty in estimatio n for example a simple approach might be to fit a brand choice model to each of the available categories in turn ignoring the data in the other categories for each category household parameter estimates could be obtained for the parameters corresponding to price display and feature sensitivity these parameter estimates could be viewed as data and the correlations across categories could be computed such a procedure could induce a downward bias in the estimation of correlation dueto the independent sampling errors which are present in each parameter estimate we develop a hierarchical model structure that introduces an explicit correlation structure across categories and utilizes the data in multiple categories at the same time to reduce the size of the covariance matrix we use a variance components approach we introduce household specific demographic variables to decompose the correlation across categories into that which can be ascribed to observable and unobservable sources shopping behavior variables such as shopping frequency and market basket size as well as intensity of shopping in a category are also included in the model using data on five categories we find substantial and statistically important correlations ranging from 32 for price sensitivities to 58 for feature sensitivity these correlations are much larger than the correlations obtained with the state of the art techniques available prior to our work we attribute our ability to detect substantial correlations to our method which involves the joint use of multiple category data in a parsimonious and efficient manner unlike previous studies with panel data household demographic variables are found to be strongly related to price sensitivity higher income households are less price sensitive and large families are more price sensitive shopping behavior variables are also important in explaining price sensitivity households that visit the store often are more price sensitive households with larger market baskets are less price sensitive confirming the view of bell and lattin 1998 heavy user households tend to be both less price sensitive and less display sensitive the evidence presented here of substantial correlations validates in part the notion that sensitivity to marketing mix variables is a consumer trait and is not unique to specific product categories it also opens the possibility of using information across categories in making inferences about consumer brand preference and marketing mix sensitivity providing a richer source of information for target marketing

the value of purchase history data in target marketing an important aspect of marketing practice is the targeting of consumer segments for differential promotional activity the premise of this activity is that there exist distinct segments of homogeneous consumers who can be identified by readily available demographic information the increased availability of individual consumer panel data open the possibility of direct targeting of individual households the goal of this paper is to assess the information content of various information sets available for direct marketing purposes information on the consumer is obtained from the current and past purchase history as well as demographic characteristics we consider the situation in which the marketer may have access to a reasonably long purchase history which includes both the products purchased and information on the causal environment short of this complete purchase history we also consider more limited information sets which consist of only the current purchase occasion or only information on past product choice without causal variables proper evaluation of this information requires a flexible model of heterogeneity which can accommodate observable and unobservable heterogeneity as well as produce household level inferences for targeting purposes we develop new econometric methods to implement a random coefficient choice model in which the heterogeneity distribution is related to observable demographics we couple this approach to modeling heterogeneity with a target couponing problem in which coupons are customized to specific households on the basis of various information sets the couponing problem allows us to place a monetary value on the information sets our results indicate there exists a tremendous potential for improving the profitability of direct marketing efforts by more fully utilizing household purchase histories even rather short purchase histories can produce a net gain in revenue from target couponing which is 2 5 times the gain from blanket couponing the most popular current electronic couponing trigger strategy uses only one observation to customize the delivery of coupons surprisingly even the information contained in observing one purchase occasion boasts net couponing revenue by 50 more than that which would be gained by the blanket strategy this result coupled with increased competitive pressures will force targeted marketing strategies to become much more prevalent in the future than they are today

blue chip rationality tests this paper tests the rationality of forecasts made by individuals who contribute to the blue chip consensus forecasting service and tries by means of a questionnaire on forecasting methods to establish why some forecasters appear more rational than others tests based on consensus forecasts prove unreliable as guides to the number of individuals who produce rational forecasts individual forecasts are more likely to be rational if they are based on a mainstream economic theory and incorporate a substantial element of judgment copyright 1991 by ohio state university press

price competition in markets with consumer variety seeking we investigate price competition between firms in markets characterized by consumer variety seeking while previous research has addressed the effect of consumer inertia on prices there exists no research on the effects of variety seeking on price competition our study fills this gap in the literature using a two period duopoly framework as in klemperer s analysis of inertial markets we show that the noncooperative pricing equilibrium in a market with consumer variety seeking may be the same as the collusive outcome in an otherwise identical market without variety seeking specifically our variety seeking model implies tacit collusion between firms in both periods unlike the inertia model of klemperer that implies tacit collusion between firms only in the second period but implies fierce price competition in the first period when consumers are assumed to have rational expectations about future prices the implied first period prices increase further which is consistent with what klemperer finds in an inertial market to summarize while our variety seeking analyses support two key results pertaining to second period prices and rational expectations previously derived for inertial markets by klemperer they depart from one key result pertaining to first period prices

a choice model for packaged goods dealing with discrete quantities and quantity discounts utility maximizing solutions to economic models of choice for goods with either discrete quantities or non linear prices cannot always be obtained using standard first order conditions such as kuhn tucker and roy s identity when quantities are discrete there is no guarantee that derivatives of the utility function are equal to derivatives of the budget constraint moreover when prices are nonlinear as in the case of quantity discounts first order conditions can be associated with the minimum rather than the maximum value of utility in these cases the utility function must be directly evaluated to determine its maximum this evaluation can be computationally challenging when there exist many offerings and when stochastic elements are introduced into the utility function in this paper we provide an economic model of demand for substitute brands that is flexible parsimonious and easy to implement the methodology is demonstrated with a scanner panel data set of light beer purchases the model is used to explore the effects of price promotions on primary and secondary demand and the utility of product assortment

does uncertainty matter consumer behavior under three part tariffs in communication information and other industries three part tariffs are increasingly popular a three part tariff is defined by an access price an allowance and a marginal price for any usage in excess of the allowance empirical nonlinear pricing studies have focused on consumer choice under two part tariffs we show that consumer behavior differs under three part tariffs and assess how consumer demand uncertainty impacts tariff choice we develop a discrete continuous model of choice among three part tariffs and estimate it using consumer level data on internet usage our model extends prior work in accommodating consumer switching to competitors thereby capturing behavior in competitive industries more accurately our empirical work shows that demand uncertainty is a key driver of choice among three part tariffs consumers expected bill increases with the variation in their usage steering them toward tariffs with high allowances consequently demand uncertainty decreases consumer surplus and increases provider revenue a further analysis of consumers responsiveness to the different elements of a three part tariff under the provider s current pricing structure reveals that prices affect a consumer s tariff choice more than her usage quantity and that the allowance plays a strong role in consumer tariff choice based on our results we derive implications for pricing with three part tariffs

benefit based conjoint analysis firms develop products by manipulating the attributes of offerings and consumers derive utility from the benefits that the attributes afford while the field of marketing has long been aware of the distinction between attributes and benefits it has not developed methods for understanding how attributes and benefits are related this paper develops a benefit based model for conjoint analysis that assumes consumers satiate on attributes that are perceived to provide the same benefit a latent variable model is proposed that estimates the map between attributes and benefits and is applied to data from two conjoint studies involving a durable product and a household consumable the model is shown to fit the data better provide improved predictions and lead to different product design implications than the standard conjoint model data as supplemental material are available at http dx doi org 10 1287 mksc 2016 1003

capturing consumption flexibility in assortment choice from scanner panel data this study develops and estimates a model to empirically identify two behavioral effects namely consumption flexibility and state dependence that may underlie temporal and horizontal assortment choice using scanner panel data where consumption information is unavailable the proposed approach permits a consumer s consumption utility to be dependent on previous consumptions thus capturing state dependence both across purchase occasions and within horizontal assortments moreover consumers purchase and consumption decisions are modeled at two distinctive and sequentially related stages which allows for incorporating the effect of consumption flexibility the model is estimated on scanner panel data of yogurt purchase it is found that the two captured effects provide strong empirical support with face validity for the temporal and horizontal assortment choice patterns observed in the data the behavioral insights derived from estimating the proposed model can also be translated into significant managerial implications

multiple discreteness and product differentiation demand for carbonated soft drinks for several of the largest supermarket product categories such as carbonated soft drinks canned soups ready to eat cereals and cookies consumers regularly purchase assortments of products within the category consumers often purchase multiple products and multiple units of each alternative selected on a given trip this multiple discreteness violates the single unit purchase assumption of multinomial logit and probit models the misspecification of such demand models in categories exhibiting multiple discreteness would produce incorrect measures of consumer response to marketing mix variables in studying product strategy these models would lead to misleading managerial conclusions we use an alternative microeconomic model of demand for categories that exhibit the multiple discreteness problem recognizing the separation between the time of purchase and the time of consumption we model consumers purchasing bundles of goods in anticipation of a stream of consumption occasions before the next trip we apply the model to a panel of household purchases for carbonated soft drinks