political influence motives and the choice between tariffs and quotas abstract tariffs and quotas are not symmetric under a variety of circumstances this paper pursues the implications of one such circumstance domestic market power for the political choice of protectionist instrument in the context of a political support maximization model tariffs dominate quotas in the political model in the absence of revenue seeking motives in the presence of revenue seeking ambiguity arises but limits can be placed on the range of tariff or quota levels also some welfare implications emerge

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

a probabilistic choice model for market segmentation and elasticity structure marketing scholars commonly characterize market structure by studying the patterns of substitution implied by brand switching though the approach is useful it typically ignores the destabilizing

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

asymmetric and neighborhood cross price effects some empirical generalizations this paper provides some empirical generalizations regarding how the relative prices of competing brands affect the cross price effects among them particular focus is on the asymmetric price effect and the neighborhood price effect the asymmetric price effect states that a price promotion by a higher priced brand affects the market share of a lower priced brand more so than the reverse the neighborhood price effect states that brands that are closer to each other in price have larger cross price effects than brands that are priced farther apart the main objective of this paper is to test if these two effects are generalizable across product categories and to assess which of these two effects is stronger while the neighborhood price effect has not been rigorously tested in past research the asymmetric price effect has been validated by several researchers however these tests of asymmetric price effect have predominantly used elasticity as the measure of cross price effect the cross price elasticity measures the percentage change in market share or sales of a brand for 1 change in price of a competing brand we show that asymmetries in cross price elasticities tend to favor the higher priced brand simply because of scaling effects due to considering percentage changes furthermore several researchers have used logit models to infer asymmetric patterns we also show that inferring asymmetries from conventional logit models is incorrect to account for potential scaling effects we consider the absolute cross price effect defined as the change in market share percentage points of a target brand when a competing brand s price changes by one percent of the product category price the advantage of this measure is that it is dimensionless hence comparable across categories and it avoids scaling effects we show that in the logit model with arbitrary heterogeneity in brand preferences and price sensitivities the absolute cross price effect is symmetric we develop an econometric model for simultaneously estimating the asymmetric and neighborhood price effects and assess their relative strengths we also estimate two alternate models that address the following questions i if i were managing the ith highest priced brand which brand do i impact the most by discounting and which brand hurts me the most through price discounts ii who hurts whom in national brand vs store brand competition based on a meta analysis of 1 060 cross price effects on 280 brands from 19 different grocery product categories we provide the following empirical generalizations 1 the asymmetric price effect holds with cross price elasticities but tends to disappear with absolute cross price effects 2 the neighborhood price effect holds with both cross price elasticities and absolute cross price effects and is significantly stronger than the asymmetric price effect on both measures of cross price effects 3 a brand is affected the most by discounts of its immediately higher priced brand followed closely by discounts of its immediately lower priced brand 4 national brands impact store brands more so than the reverse when the cross effect is measured in elasticities but the asymmetric effect does not hold with absolute effects store brands hurt and are in turn hurt the most by the lower priced national brands that are adjacent in price to the store brands 5 cross price effects are greater when there are fewer competing brands in the product category and among brands in nonfood household products than among brands in food products the implications of these findings are discussed

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

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

is 75 of the sales promotion bump due to brand switching no only 33 is abstract several researchers have decomposed sales promotion elasticities based on household scanner panel data a key result is that the majority of the sales promotion elasticity approximately 74 on average is attributed to secondary demand effects brand switching and the remainder is attributed to primary demand effects timing acceleration and quantity increases the authors demonstrate that this result does not imply that if a brand gains 100 units in sales during a promotion the other brands in the category lose 74 units the authors offer a complementary decomposition measure based on unit sales the measure shows the ratio of the current cross brand unit sales loss to the current own brand unit sales gain during promotion the authors report empirical results for this measure they also derive analytical expressions that transform the elasticity decomposition into a decomposition of unit sales effects these expressions show the nature of the difference between the two decompositions to ga

a direct utility model for asymmetric complements a symmetric complements refer to goods where one good is more dependent on the other yet consumers receive enhanced utility from consuming both examples include garden hoses and sprinklers chips and dip and routine versus personalized services where the former has a broader base for utility generation and the latter is more dependent on the other s presence measuring asymmetric effects is difficult when all that is observed are the purchase quantities present in a consumer s market basket we propose a direct utility model with a latent decision sequence for measuring asymmetric effects that allows us to capture differential responses to cross category purchases and inventories scanner panel data of milk and cereal purchases are used to investigate the presence of asymmetric complementarity and implications are explored through counterfactual analyses involving cross price elasticities and spillover effects of merchandising variables

the effects of cross ruff coupons on sales and profits cross ruff coupons are obtained at the time of purchase of a carrier brand and may be redeemed at a later date on a target brand these coupons therefore have the ability to link consumer purchases across different brands as well as shopping trips we model the effects of cross ruff coupons on consumer choice behavior and derive the conditions under which cross ruff coupons can lead to higher sales and profits than other types of package coupons the model also provides insights into the selection of appropriate carrier and target brands and on how the choice of an appropriate carrier or a target brand is affected when the categories that these brands belong to are demand complements or substitutes we conduct an empirical analysis using data from 195 different cross ruff coupon campaigns observed in grocery stores in a major u s city over a three month period the data are consistent with the key insights provided by the model

consumers price sensitivities across complementary categories in this paper we examine the pattern of correlation among consumer price sensitivities for customer purchase incidence decisions across complementary product categories we use a hierarchical bayesian multivariate probit model to uncover this pattern we estimated this model using purchase incidence data for six categories involving three pairs of complementary products our results show a new and interesting pattern of correlation among price parameters of complementary products for example we find that the correlation of own price sensitivities of complementary products is negative these results are consistent across the three complementary pairs of products we also investigate the reason for this counterintuitive result finally we present some managerial implications of our model we show how our model can be used for cross category targeting decisions by retailers we find that compared to nontargeted discounting the average profitability gain from customized discounting across the three category pairs is only 1 29 when complementarity is ignored but this gain improves to 8 26 when full complementarity is taken into account we also investigate whether ignoring the complex pattern of correlation has implications for managerial actions regarding targeting and optimal discounting we find that retailers can make misleading inferences about the impact of targeted discounts when they ignore cross category effects in modeling

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 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

bureaucratic discretion or congressional control regulatory policymaking by the federal trade commission this paper extends stigler and peltzman s approach to regulation by incorporating a legislature the model yields comparative statics results and hence testable implications the paper then tests between two opposing approaches about regulatory agency behavior the first assumes agencies operate independently of the legislature and hence exercise discretion the second assumes that congress controls agency decisions the recent behavior of the federal trade commission provides the empirical setting substantial evidence is found for the specific predictions of the model including the hypothesis of systematic congressional influence over ftc decisions

a multicategory model of consumers purchase incidence quantity and brand choice decisions methodological issues and implications on promotional decisions abstract the authors propose a multicategory model of consumers purchase incidence quantity and brand choice decisions the model specification allows for cross category promotion effects in both components of the primary demand incidence and quantity decisions and uses a flexible functional form of consumer s utility to accurately measure those cross category effects to demonstrate the importance of the methodology the authors investigate two issues of relevance to retailers namely how retailers should 1 allocate promotional expenditures across brands in a category and 2 coordinate timing of promotions of brands across categories the authors estimate the proposed model using consumers purchases in pasta sauce and pasta categories the results reveal that using restrictive functional forms of utilities or ignoring cross category effects in incidence and quantity decisions leads to incorrect assessments on relative allocation of promotional expenditures across brands furthermore retailers

domestic politics foreign interests and international trade policy reply this paper incorporates the foreign interest in the determination of a country s international trade policy into a model of political competition between candidates contesting elective office we envisage foreign and domestic producer interests as expressing political support for a candidate via campaign contributions and candidates as making trade policy pronouncements to maximize political support from producer interests tariffs are divisive but vers are consistent with conciliatory policy positions yielding mutual gain to foreign and domestic interests no candidate has an interest in formulating a trade policy position using a tariff if a ver is a policy option protection in the developed countries has in recent years often taken the form of bilaterally negotiated voluntary export restraints vers rather than the more traditional unilaterally imposed import restrictions the use of voluntary export restraints has been paralleled by interest in the theoretical literature the effects of vers have been compared with tariffs and quotas and vers have been examined in a political economy framework with a view to identifying the gainers and losers from this form of restric

demand forecasting with high dimensional data the case of sku retail sales forecasting with intra and inter category promotional information in marketing analytics applications in or the modeler often faces the problem of selecting key variables from a large number of possibilities for example sku level retail store sales are affected by inter and intra category effects which potentially need to be considered when deciding on promotional strategy and producing operational forecasts but no research has yet put this well accepted concept into forecasting practice an obvious obstacle is the ultra high dimensionality of the variable space this paper develops a four steps methodological framework to overcome the problem it is illustrated by investigating the value of both intra and inter category sku level promotional information in improving forecast accuracy the method consists of the identification of potentially influential categories the building of the explanatory variable space variable selection and model estimation by a multistage lasso regression and the use of a rolling scheme to generate forecasts the success of this new method for dealing with high dimensionality is demonstrated by improvements in forecasting accuracy compared to alternative methods of simplifying the variable space the empirical results show that models integrating more information perform significantly better than the baseline model when using the proposed methodology framework in general we can improve the forecasting accuracy by 12 6 percent over the model using only the sku s own predictors but of the improvements achieved 95 percent of it comes from the intra category information and only 5 percent from the inter category information the substantive marketing results also have implications for promotional category management

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

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

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

rules or politics an empirical analysis of itc anti dumping decisions this research analyzes the international trade commission s anti dumping decisions from 1980 to 1986 the results suggest that commissioners use criteria consistent with the instructions set forth in u s legislation the analysis also indicates that political variables help predict commissioner decisions petitions involving senate oversight committee members constituencies may be systematically favored in the process evidence of possible bias toward less developed country exports is presented as well the methodology also yields estimates of commissioner specific fixed effects

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

the congressional bureaucratic system a principal agent perspective with applications to the sec this paper provides the theoretical perspective and empirical support for congressional dominance of agency decisions my thesis is twofold first because much of the previous evidence on this question is not evidence at all many scholars intuition and conclusions are based on a logically flawed foundation second i have provided here and in previous work a look at a variety of different agencies and in each case have shown how the events can plausibly be interpreted as involving congress agency problems within the congressional bureaucratic system are real and substantial just as they are within corporations however as in the latter institutional forms develop within the congressional system to partially if not wholly mitigate these problems the logical perspective together with the evidence provide a strong case against the agency dominance hypothesis as typified by the early sections of niskanen 1971 and wilson 1980

cumulation and itc decision making the sum of the parts is greater than the whole in 1984 congress amended the antidumping and countervailing duty laws man dating that the international trade commission itc cumulate imports across countries when determining injury we estimate that cumulation increases the probability of an affirmative injury determination by 20 to 30 percent and has changed the itc s decision from negative to affirmative for about one third of cumulated cases we also show that the protective effect of cumulation increases as the number of countries involved increases holding import market share constant that is cumulated imports have a super additive effect on itc decision making

endogenous protection foreign direct investment and protection building trade abstract we introduce the possibility of foreign direct investment fdi in a strategic oligopolistic setting with endogenous protection and find that a number of unique subgame perfect equilibria may arise including a new result we call protection building trade this phenomenon occurs in our model when foreign firms locating production in the home country try to increase protectionist pressures in the home country through increased exports to provide larger barriers against other foreign competitors in future periods we discuss how the foreign firm behavior surrounding significant u s protectionist actions including the vers on japanese automobiles may be consistent with protection building trade behavior

examining demand elasticities in hanemann s framework a theoretical and empirical analysis this paper examines demand elasticities using an integrated framework proposed by hanemann hanemann m w 1984 discrete continuous models of consumer demand econometrica52 3 541 561 which models the incidence brand choice and quantity decisions of a consumer as an outcome of her utility maximization subject to budget constraints although the hanemann framework has been the mainstay of earlier efforts to examine these decisions jointly empirical researchers who have used the it to study purchase behavior have often found that the quantity elasticities are around 1 regardless of the brand or category we attempt to uncover the underlying reasons for this finding and propose approaches to get as close to the true quantity elasticities as possible we do this by i analytically demonstrating how assumptions on the distribution of the brand specific econometrician s errors imply certain restrictions that in turn force quantity elasticities to 1 ii discussing how these restrictions can be alleviated by considering a suitable specification of unobserved parameter heterogeneity and iii using scanner data to empirically illustrate the impact of the restrictions on quantity elasticities and the relative efficacy of multiple specifications of unobserved heterogeneity in easing those restrictions we find that the specification of unobserved heterogeneity crucially influences estimates of quantity elasticities and that the mixture normal specification outperforms the alternatives

the long term effects of price promotions on category incidence brand choice and purchase quantity abstract to what extent do price promotions have a long term effect on the components of brand sales namely category incidence brand choice and purchase quantity the authors answer this question by using persistence modeling on weekly sales data of a perishable and a storable product derived from a scanner panel their analysis reveals first that permanent promotion effects are virtually absent for each sales component next the authors develop and apply an impulse response approach to estimate the promotional adjustment period and the total dynamic effects of a price promotion specifically they calculate the long term equivalent of gupta s 1988 14 84 2 breakdown of promotional effects because of positive adjustment effects for incidence but negative adjustment effects for choice the authors find a reversal of the importance of category incidence and brand choice 66 11 23 for the storable product and 58 39 3 for the perishable product the authors discuss the implications of the findings an

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

an analysis of factors influencing the anti dumping behaviour in india the use of anti dumping measures as a trade protection tool has increased phenomenally during the last decade one significant aspect of this new trend is the increasing involvement of developing countries india is one such country which has emerged as a very frequent user of anti dumping measures surpassing even the traditional users it had initiated more than 300 anti dumping cases by the end of 2002 03 many of these cases are against developing countries most of the cases are concentrated in narrow range product groups like chemicals and petrochemicals iron and steel pharmaceuticals and textiles this study examines india s experience with anti dumping measures the main objective of the study is to identify the factors which might have influenced the anti dumping behaviour in india discussion of these factors shows that imports have increased considerably this is particularly true for a number of developing countries facing dumping charges in india at the same time many of the domestic producers of the like products have performed poorly during the last decade such trends may instigate the import competing industries to seek anti dumping protection and may also influence the authority to provide that however the results of our statistical exercise show that although imports and performance of the domestic industry might have influenced the initiation of anti dumping cases these factors did not seem to significantly influence the final decision of the authority the results rather indicated a tendency on the part of the authority to provide anti dumping protection to industries which are characterised by a large number of firms

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

measuring cross category price effects with aggregate store data our objective is to understand the cross category effects of marketing activities using aggregate store level scanner data for this we provide a framework derived from household utility maximizing behavior which assumes that a household chooses the bundle of products with the highest utility we use a second order taylor series approximation to an arbitrary utility function to represent bundle utility aggregate sales or shares in each category are derived under the assumption that households are heterogeneous in their preferences and in their sensitivities to marketing activities our estimation accounts for potential price endogeneity in demand using store level scanner data on four product categories liquid laundry detergents powdered laundry detergents liquid fabric softeners and sheet fabric softeners we find evidence for a complementary relationship between liquid softeners and both forms of detergents we also find that the magnitude of cross category elasticities are brand specific i e different brands in a category have a different price impact on the demand for a brand in another category the results have implications for retailers in terms of the potential need for cross category management as well as for manufacturers such as procter gamble that participate in all four categories we compare our model with a log log regression specification on three criteria estimated elasticities hold out sample predictions and retailer cross category pricing we find that the proposed model produces more reasonable estimates relative to the log log model it predicts better and is more useful for pricing purposes further in a simulation study we show that our proposed model can recover the elasticities from a data generating process that simulates household level joint outcomes across categories even after these data have been aggregated to brand level shares within each category by contrast the log log regression model is unable to do so

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

buchanan economics and politics author affiliation paul h rubin samuel candler dobbs professor of economics emory university department of economics 312e rich building 1602 fishburne drive atlanta ga 30322 2240 usa e mail prubin emory edu1 introductionmy work has been greatly influenced by jim buchanan much of my early work was in public choice see e g kau and rubin 1979 2002 of course this field would not exist without the calculus of consent buchanan and tullock 1962 more recently my research has gone in different directions but it still bears jim s influence i take as my text today a statement from jim buchanan s great presidential address to the southern economic association in 1963 economics is the study of the whole system of exchange relationships politics is the study of the whole system of coercive or potentially coercive relationships buchanan 1964 p 220 i agree with this statement but in this tribute i want to extend this analysis a little bit i want to point out some additional differences between thinking about economics and thinking about politics some of this analysis is based on my work on the biology of politics rubin 2002 2003 based on that work i have come to the conclusion that in some sense political thinking is more basic to our minds than is economic thinking that is when faced with an interpersonal issue that does not involve family or sex an individual untrained in economics is more likely to treat it as a political issue than as an economic issue indeed one of our tasks as economists is or should be to educate our students and the public about the distinction between economics and politics pinker 2003 not an economist argues that economics is one area where human intuitions are lacking and that it is important to teach economics for this reason 2 characteristics of political versus economic thinkinghere are some of the relevant characteristics of political thinking as contrasted with economic thinking i politics is about competition for resources while economics is about cooperation to generate surpluses ii political thinking tends to be zero sum division of a fixed pie economics allows for positive sum interactions iii politics is an us versus them conflict we are a tribal species with tribal competition economics is universal trade with anyone is beneficial iv perhaps because of its us versus them nature politics is dichotomous win or lose good or bad economics is continuous more or less how much v political processes are controlled by specific active agents the chief the king the general these agents may be heroes or villains but they are purposeful agents economics deals with processes as the market process or the invisible hand vi politics focuses on motives economics focuses on net outputs i now discuss each of these issues in turn competitionthe most important error in economic thinking is associated with one of the most fundamental concepts of economics competition as buchanan argues in his address the fundamental unit of economics is the transaction and transactions are cooperative competition is important but it is a tool to improve cooperation buchanan among others points out that in the purely competitive model there is no competition but we do not fully understand or analyze the implications even in nonperfectly competitive environments the degree of competition is overestimated firms in this environment do compete with each other but they are competing for the right to cooperate with consumers and suppliers including workers a monopolist is a firm with an exclusive ability or right to cooperate with consumers in some market we focus on competition rather than cooperation because of our political bias toward looking at markets through the lens of politics competition is between firms which are actively striving to accomplish some goal

research note a cross category model of households incidence and quantity decisions this paper advances the literature on multicategory demand models by simultaneously handling more than one purchase decision of the household we propose a two stage bivariate logit model of incidence and quantity outcomes in multiple categories our results show that cross category promotional spillovers are asymmetric between the two product categories of bacon and eggs the total retail profit responds more to bacon price than to egg price promoting bacon is found to have a bigger impact on egg profit than the impact of egg promotion on bacon profit we decompose 1 the total retail profits as well as 2 the cross category profit impact of a price promotion into its two components and find that 1 23 67 of the total retail profit impact of a promotion on bacon eggs arises on account of quantity effects and 2 40 33 of the increase in egg bacon profit from promoting bacon eggs is on account of quantity effects

the decomposition of promotional response an empirical generalization price promotions are used extensively in marketing for one simple reason consumers respond the sales increase for a brand on promotion could be due to consumers accelerating their purchases i e buying earlier than usual and or buying more than usual and or consumers switching their choice from other brands purchase acceleration and brand switching relate to the primary demand and secondary demand effects of a promotion gupta 1988 captures these effects in a single model and decomposes a brand s total price elasticity into these components he reports for the coffee product category that the main impact of a price promotion is on brand choice 84 and that there is a smaller impact on purchase incidence 14 and stockpiling 2 in other words the majority of the effect of a promotion is at the secondary level 84 and there is a relatively small primary demand effect 16 this paper reports the decomposition of total price elasticity for 173 brands across 13 different product categories on average we find that 25 of the elasticity is due to primary demand expansion i e purchase acceleration and 75 to secondary demand effects or brand switching thus while gupta s finding that the majority of promotional response stems from brand switching is supported the average magnitude of the effect appears to be smaller than first thought more important there is ample evidence that promotions have a significant primary demand effect the relative emphasis on purchase acceleration and brand switching varies systematically across categories and the second goal of the paper is to explain this variation as a function of exogeneous covariates in doing this we recognize that promotional response is the consumer s reaction to a price promotion and therefore develop a framework for understanding variability in promotional response that is based on the consumer s perspective of the benefits from a price promotion these benefits are posited to be a function of i category specific factors ii brand specific factors and iii consumer characteristics the framework is formalized as a generalized least squares meta analysis in which the brand s price elasticity is the dependent variable several interesting results emerge from this analysis category specific factors brand specific factors and consumer demographics explain a significant amount of the variance in promotional response for a brand at both the primary and secondary demand levels category specific factors have greater influence on variability in promotional response and its decomposition than do brand specific factors there are several instances where exogenous variables do not affect total elasticities yet significantly affect individual components of total elasticity in fact the lack of a significant relationship between the variables and total elasticity is often due to offsetting effects within two or more of the three behavioral components of elasticity this is particularly true for brand specific factors which typically have no effect on total elasticity yet have important effects on the individual behaviors there is some evidence to suggest that not all promotion related increases in primary demand are due to forward buying in some cases promotions appear to increase consumption we use these results to illustrate how category and brand specific factors work to drive primary and secondary demand elasticities in different directions in short this paper offers an empirical generalization of a key finding on promotional response how elasticities decompose across brand choice purchase incidence and stockpiling and new insights into factors that explain variance in promotional response these findings are likely to be of interest to researchers who are concerned with theory development and the generalizability of marketing phenomena and to managers who plan promotion campaigns

tariffs subsidies and welfare with endogenous policy abstract it is a well established proposition of trade theory that in the absence of directly trade related distortions or policy goals subsidies are superior to tariffs for achieving any economic or non economic objective this paper shows that once the endogeneity of the distortion or non economic objective is allowed for the welfare ranking of various policies can be reversed the particular model analyzed is one where the level of non economic objectives that have to be fulfilled itself depends on the policy tools considered to fulfill them with this arises from the public good nature of tariffs compared to subsidies

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

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