Estimation Of Demand Systems Research Articles

Do Consumers Respond to Country-of-Origin Labelling?

Seafood was the first class of foods to fall under the 2002 US regulatory requirements for mandatory country-of-origin labelling (COOL). If this regulation created benefits for consumers, filling an information void by demanding information that the market did not, then there should have been an observable response in the demand for seafood. To gauge the impact, we examined markets most likely to respond. We estimated retail demand for shrimp, seafood that in the USA is largely sourced from Southeast Asia and has a history of raising food safety concerns. Our estimated demand systems included standard variables consistent with economic theory—price and expenditure changes, ongoing trends, and seasonality in consumption patterns. The demand systems also accounted for regulations that required country-of-origin labels for some, but not all, foods prior to COOL. Data came from a nationally representative panel of households that record retail food purchases, allowing us to construct relatively high-frequency market data suitable for testing for the presence of even short-lived impacts. Household demographic information allowed us to separately estimate demands by consumers most likely to respond to label information. The demand systems yielded reasonable price and expenditure elasticity estimates, but none of the variables related to COOL revealed evidence of an impact.

Estimating a Demand System with Seasonally Differenced Data

Several recent papers have used annual changes and monthly data to estimate demand systems. Such use of overlapping data introduces a moving average error term. This paper shows how to obtain consistent and asymptotically efficient estimates of a demand system using seasonally differenced data. Monte Carlo simulations and an empirical application to the estimation of the U.S. meat demand are used to compare the proposed estimator with alternative estimators. Once the correct estimator is used, there is no advantage to using overlapping data in estimating a demand system.

Semiparametric estimation of consumer demand systems in real expenditure

AbstractMicrodata concerning consumer demand typically show considerable variation in real expenditures, but very little variation in prices. We propose a semiparametric strategy for the consumer demand problem in which expenditure share equations are estimated nonparametrically in the real expenditure direction and estimated parametrically (with fixed or varying coefficients) in price directions. In our model, Engel curves are unrestricted: demands may have any rank. Because the demand model is derived from a cost function, it may be restricted to satisfy integrability and used for consumer surplus calculations. Since real expenditure is unobserved, but rather estimated under the model, we face a semiparametric model with a nonparametrically generated regressor. We show efficient convergence rates for parametric and nonparametric components. We illustrate the feasibility of our proposed strategy using Canadian expenditure and price data: Engel curves display curvature which cannot be encompassed by standard parametric models. We also find that the rationality restriction of Slutsky symmetry is rejected in the fixed‐coefficients model, but not in the varying‐coefficients model. Copyright © 2009 John Wiley & Sons, Ltd.

Incomplete Demand Systems, Corner Solutions, and Welfare Measurement

This paper demonstrates how corner solutions raise difficulties for the specification, estimation, and use of incomplete demand systems for welfare measurement with disaggregate consumption data, as is common in the outdoor recreation literature. A simple analytical model of consumer behavior is used to elucidate the potential biases for welfare measurement arising from modeling the demand for M goods as a function of M + N prices (N > 1) and income when individuals do not consume all goods in strictly positive quantities. Results from a Monte Carlo experiment suggest that these biases can be substantial for large-scale policy shocks when prices are highly correlated.

Testing and imposing Slutsky symmetry in nonparametric demand systems

Maximization of utility implies that consumer demand systems have a Slutsky matrix which is everywhere symmetric. However, previous non- and semi-parametric approaches to the estimation of consumer demand systems do not give estimators that are restricted to satisfy this condition, nor do they offer powerful tests of this restriction. We use nonparametric modeling to test and impose Slutsky symmetry in a system of expenditure share equations over prices and expenditure. In this context, Slutsky symmetry is a set of nonlinear cross-equation restrictions on levels and derivatives of consumer demand equations. The key insight is that due to the differing convergence rates of levels and derivatives and due to the fact that the symmetry restrictions are linear in derivatives, both the test and the symmetry restricted estimator behave asymptotically as if these restrictions were (locally) linear. We establish large and finite sample properties of our methods, and show that our test has advantages over the only other comparable test. All methods we propose are implemented with Canadian micro-data. We find that our nonparametric analysis yields statistically significantly and qualitatively different results from traditional parametric estimators and tests.

Estimating demand systems and measuring consumer preferences

Estimating demand systems and measuring consumer preferences

Demand-System Estimation: Update

The nlsur command is better suited to demand-system estimation than the suite of ado-files provided in Poi (2002, Stata Journal 2: 403–410) because it is faster and requires only one ancillary ado-file. This article replicates the results presented in Poi (2002) by using nlsur instead of ml.

Tobacco and Alcohol: Complements or Substitutes? A Structural Model Approach

The question of whether two drugs - namely alcohol and tobacco - are used as complements or substitutes is of crucial interest if side-effects of anti-smoking policies are considered. Numerous papers have empirically addressed this issue by estimating demand systems for alcohol and tobacco and subsequently calculating cross-price effects. However, this traditional approach often is seriously hampered by insufficient price-variation observed in survey data. We therefore suggest an alternative instrumental variables approach that statistically mimics an experimental study and does not rely on prices as explanatory variables. This approach is applied to German survey data. Our estimation results suggest that a reduction in tobacco consumption results in a moderate reduction in alcohol consumption. It is shown theoretically that this implies that alcohol and tobacco are complements. Hence, we conclude that successful anti-smoking policies will not result in the unintended side-effect of an increased (ab)use of alcohol.

A neural network demand system with heteroskedastic errors

Abstract In this paper we consider estimation of demand systems with flexible functional forms, allowing an error term with a general conditional heteroskedasticity function that depends on observed covariates, such as demographic variables. We propose a general model that can be estimated either by quasi-maximum likelihood (in the case of exogenous regressors) or generalized method of moments (GMM) if the covariates are endogenous. The specification proposed in the paper nests several demand functions in the literature and the results can be applied to the recently proposed Exact Affine Stone Index (EASI) demand system of [Lewbel, A., Pendakur, K., 2008. Tricks with Hicks: The EASI implicit Marshallian demand system for unobserved heterogeneity and flexible Engel curves. American Economic Review (in press)]. Furthermore, flexible nonlinear expenditure elasticities can be estimated.

Estimating demand systems when outcomes are correlated counts

Abstract We describe and employ a Bayesian posterior simulator for fitting a high-dimensional system of ordinal or count outcome equations. The model is then applied to describe the multiple site recreation demands of individual agents, and we argue that our approach provides advantages relative to existing methods commonly applied in this area. In particular, our model flexibly adjusts to match observed frequencies in trip outcomes, permits a flexible correlation pattern among the sites visited by individuals, and the posterior simulator for fitting this model is relatively easy to implement in practice. We also describe how the posterior simulations produced from the model can be used to conduct a variety of counterfactual experiments, including predicting behavioral changes and describing welfare implications resulting from shifts in exogenous demographic and site characteristics. We illustrate our method using data from the Iowa Lakes Project by modeling the visitation patterns of individuals to a set of twenty-nine large Iowa lakes. Consistent with previous findings in the literature, we see strong evidence that own and cross-price effects on trip demand are negative and positive, respectively, that higher income increases the likelihood of visiting most sites, and that a commonly used indicator of water quality, Secchi transparency, is positively correlated with the number of trips taken. In addition, the correlation structure among the errors reveals a complex pattern in which unobserved factors affecting trip demand are generally (though not strictly) positively correlated across sites. The flexibility and richness with which we are able to characterize the demand system provides a solid platform for counterfactual analysis, where we find significant behavioral and welfare effects from changes in site availability, water quality, and travel costs.

Estimating high-dimensional demand systems in the presence of many binding non-negativity constraints

Abstract Two econometric issues arise in the structural estimation of consumer or producer demand systems in the presence of many binding non-negativity constraints. Firstly, most existing methods entail the evaluation of multivariate probability integrals. Secondly, the issue of statistical coherency must be addressed. We circumvent both of these issues using Gibbs’ Sampling, along with data augmentation and rejection sampling. We illustrate our method using several simulated data sets.

Maintaining parameter invariance in seemingly unrelated regressions estimation

Seemingly unrelated regressions (SUR) is an important estimation methodology in demand analysis. While possessing qualities that make it attractive to applied demand analysts, the SUR estimation technique poses several difficulties, including the lack of parameter invariance in some instances e.g. estimation of consumer demand systems with micro-level data. When data includes zero consumption, corrections used to account for censoring may result in different parameter estimates when different share equations are dropped for estimation. This article proposes an alternative estimation objective which results in invariant parameter estimates when imposing adding-up by dropping equations.

Tobacco and Alcohol: Complements or Substitutes? A Structural Model Approach

The question of whether two drugs – namely alcohol and tobacco – are used as complements or substitutes is of crucial interest if side-effects of anti-smoking policies are considered. Numerous papers have empirically addressed this issue by estimating demand systems for alcohol and tobacco and subsequently calculating cross-price effects. However, this traditional approach often is seriously hampered by insufficient price-variation observed in survey data. We therefore suggest an alternative instrumental variables approach that statistically mimics an experimental study and does not rely on prices as explanatory variables. This approach is applied to German survey data. Our estimation results suggest that a reduction in tobacco consumption results in a moderate reduction in alcohol consumption. It is shown theoretically that this implies that alcohol and tobacco are complements. Hence, we conclude that successful anti-smoking policies will not result in the unintended side-effect of an increased (ab)use of alcohol.

The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions

Many consumer choice situations are characterized by the simultaneous demand for multiple alternatives that are imperfect substitutes for one another. A simple and parsimonious multiple discrete-continuous extreme value (MDCEV) econometric approach to handle such multiple discreteness was formulated by Bhat (2005) [Bhat, C.R., 2005. A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions. Transportation Research Part B 39(8), 679–707]. within the broader Kuhn–Tucker (KT) multiple discrete-continuous economic consumer demand model of Wales and Woodland (1983) [Wales, T.J., and Woodland, A.D., 1983. Estimation of consumer demand systems with binding non-negativity constraints. Journal of Econometrics 21(3), 263–85]. This paper examines several issues associated with the MDCEV model and other extant KT multiple discrete-continuous models. Specifically, the paper proposes a new utility function form that enables clarity in the role of each parameter in the utility specification, presents identification considerations associated with both the utility functional form as well as the stochastic nature of the utility specification, extends the MDCEV model to the case of price variation across goods and to general error covariance structures, discusses the relationship between earlier KT-based multiple discrete-continuous models, and illustrates the many technical nuances and identification considerations of the multiple discrete-continuous model structure through empirical examples. The paper also highlights the technical problems associated with the stochastic specification used in the KT-based multiple discrete-continuous models formulated in recent Environmental Economics papers.

The Use of Conditional Cost Functions to Generate Estimable Mixed Demand Systems

Mixed demand systems have been virtually ignored in empirical work solely because derivation of these systems requires closed forms for both direct and indirect utility functions. This article proposes the alternative of using a conditional cost function to generate empirical mixed demand models. This approach allows the estimation of mixed demand systems, which are explicit in an unobservable variable (utility), but may lack a closed form representation in terms of observable variables such as prices, quantities and expenditure. Results indicate that this approach is operationally feasible, which opens up a wider range of mixed demand specifications in static analyses.

Socio-economic characteristics and the effect of taxation as a health policy instrument

This paper analyses the quantitative effects of using economic instruments in health policy on the basis of price elasticities calculated from estimated demand systems. The nutritional effects of various taxation schemes are compared for households in different age groups and social classes. Focusing on the consumption of saturated fats, fibre and sugar; it is generally found that the impact of price instruments is stronger for lower social classes than in other groups of the population. With regard to age groups, it is mostly the youngest that decrease their demand for saturated fat in response to price changes, while it is mostly the middle-aged who exhibit price responsiveness in their demand for sugar. These groups are however not considered as key target groups for dietary regulation; thus tax instruments may be effective in improving diets on average, but the design of the instruments and the targeting of vulnerable groups with special needs should be done with care. It should be noted that a tax on a single nutrient or food may have undesired effects on the demand for other food components, though this may be avoided by introducing taxes/subsidies on several food products simultaneously.

Decoupling of industrial energy consumption and CO 2-emissions in energy-intensive industries in Scandinavia

As methodology the ex-post analysis deserves more attention as a device to calibrate energy sector models. This paper studies the impact of energy prices and taxes on energy efficiency and carbon emissions of ten industrial sectors in the three Scandinavian countries. A database with sector-specific energy prices and taxes has been established, which allows the analysis to take various price reductions and tax exemptions better into account. A translog factor demand system estimation for a cross industry pooled model is explored and fixed effects across industries and time is estimated. The findings here confirm recent analyses which indicate higher long-term elasicities for industries than normally assumed in Scandinavian energy-sector models. With the observations on differences in energy-intensities among sectors and countries the findings allow for some optimism as to the opportunities for further decoupling between trends in gross value added, carbon emissions and energy consumption.

The Impact of Advertising on Consumer Price Sensitivity in Experience Goods Markets

In this paper we use Nielsen scanner panel data on four categories of consumer goods to examine how TV and other marketing activities affect the demand curve facing a brand. Advertising can affect consumer demand in many different ways. Becker and Murphy (1993) have argued that the presumptive should be that works by raising marginal consumers' willingness to pay for a brand. This has the effect of flattening the demand curve, thus increasing the equilibrium elasticity of demand and the lowering the equilibrium price. Thus, advertising is profitable not because it lowers the elasticity of demand for the advertised good, but because it raises the level of demand. Our empirical results support this conjecture on how shifts the demand curve for 17 of the 18 brands we examine. There have been many prior studies of how affects two equilibrium quantities: the elasticity of demand and/or the level. Our work is differentiated from previous work primarily by our focus on how shifts demand curves as a whole. As Becker and Murphy pointed out, a focus on equilibrium prices or elasticities alone can be quite misleading. Indeed, in many instances, the observation that causes prices to fall and/or demand elasticities to increase, has misled authors into concluding that consumer price must have increased, meaning the number of consumers' willing to pay any particular for a brand was reduced - perhaps because makes consumers more aware of substitutes. But, in fact, a decrease in the equilibrium is perfectly consistent with a scenario where actually raises each individual consumer's willingness to pay for a brand. Thus, we argue that to understand how affects consumer sensitivity one needs to estimate how it shifts the whole distribution of willingness to pay in the population. This means estimating how it shifts the shape of the demand curve as a whole, which in turn means estimating a complete demand system for all brands in a category - as we do here. We estimate demand systems for toothpaste, toothbrushes, detergent and ketchup. Across these categories, we find one important exception to conjecture that should primarily increase the willingness to pay of marginal consumers. The exception is the case of Heinz ketchup. Heinz has a greater positive effect on the WTP of infra-marginal consumers. This is not surprising, because Heinz focuses on differentiating the brand on the thickness dimension. This is a horizontal dimension that may be highly valued by some consumers and not others. The consumers who most value this dimension have the highest WTP for Heinz, and, by focusing on this dimension; Heinz raises the WTP of these inframarginal consumers further. In such a case, is profitable because it reduces the market share loss that the brand would suffer from any given increase. In contrast, in the other categories we examine, tends to focus more on vertical attributes.

Tobacco and Alcohol: Complements Or Substitutes? - A Statistical Guinea Pig Approach

The question of whether two drugs - namely alcohol and tobacco - are used as complements or substitutes is of crucial interest if side-effects of anti-drug policies are considered. Numerous papers have empirically addressed this issue by estimating demand systems for alcohol and tobacco and subsequently calculating cross-price effects. However, this traditional approach often is seriously hampered by insufficient price-variation observed in survey data. We, therefore, suggest an alternative instrumental variables approach that statistically mimics an experimental study and does not rely on prices as explanatory variables. This approach is applied to German survey data. Our estimation results suggest that a reduction in tobacco consumption results in a reduction in alcohol consumption, too. It is shown theoretically that this implies that alcohol and tobacco are complements. Hence, we conclude that successful antismoking policies will not result in the unintended side-effect of an increased (ab)use of alcohol.

Demand systems for agricultural products in OECD countries

This study concerned with the estimation of demand systems for agricultural products in OECD countries. Three representatives demand systems with their extensions, namely the Rotterdam Model, An Almost Ideal Demand System (AIDS), and CBS model are used. These models are estimated by Seemingly Unrelated Regression (SUR) method. The procedures to estimate demand systems suggest significant empirical regularities for agricultural products in OECD countries. The study also applies a procedure for model selection. This procedure implies the superiority of AIDS and CBS models over the Rotterdam model. The main contribution of this study is to model demand for agricultural products over a wide array of items and across large number of countries.