Some evidence on the performance of size correction factors in testing consumer demand models

1989 ◽  
Vol 29 (4) ◽  
pp. 311-315 ◽  
Author(s):  
P.M.C. De Boer ◽  
R. Harkema
Author(s):  
Ted C. Schroeder ◽  
Glynn T. Tonsor

Consumer demand for meat is constantly changing and agricultural economists have been prolifically researching this change. The purpose of this article is to give an overview of demand for meat quality attributes and it discusses implications for industry stakeholders and policymakers. Discussion focuses especially on demand for red meat quality attributes by consumers in the United States and Europe. It mentions that properly specified meat demand models require variables capturing changing consumer lifestyles and preferences for specific meat quality attributes if models are to be of value in understanding consumer behavior. It also shows the overall patterns in meat demand. It assesses how consumer demand for meat quality attributes is influencing consumer meat purchasing decisions. Numerous economic experiments and surveys reveal that consumers are willing to pay more for products they perceive possess intrinsic quality attributes they want.


2018 ◽  
Vol 58 (4) ◽  
pp. 730
Author(s):  
R. J. Sadler ◽  
D. B. Purser ◽  
S. K. Baker

Daily food intake is the single most important factor affecting milk production by dairy cows. However, an animal’s choice of food depends not only on the nutritional characteristics of the food in question, but also on the nutritional characteristics of other available foods. Any prediction of intake should be based on the nutritional characteristics of all foods on offer. However, when the initial food-preference experiment possesses a control-specific design (i.e. experiments that include only a limited number of control foods for comparison) it is apparent that the prediction of future food choices must include the same controls as the initial experiment underpinning the prediction model. This requirement is clearly impractical. By drawing an analogy between animal food preference and economic choice, the total and relative dry matter intake of two oaten hays was modelled on their nutritive characteristics by estimating a consumer-demand model (here a generalised additive model representation of a direct bundle good model) from experimental data offering hays to lactating cows (adj-R2 > 80%; where adj-R2 is the value adjusted for the number of predictor terms in the model). To negate the problem of control-specificity, a simplex interpolation was developed to construct and test predictions of hay intake for a second food-preference experiment (adj-R2 > 53%; correlation between predictions and actual intakes = 76%). To improve prediction accuracy and avoid control-specificity, it is recommended that future preference experiments be designed to exclude control-specificity by mimicking fractional factorial designs, supported by a two-stage approach to select a cost-effective number of comparisons. Our approach to predicting food intake may be extended to a choice between more than two foods, and to combinations of foods other than oaten hays.


Author(s):  
Pavel Syrovátka ◽  
Miroslav Navrátil

The paper is focused on the use of the linear constructions for developing of Engel’s demand models in the field of the food-consumer demand. In the theoretical part of the paper, the linear approximations of this demand models are analysed on the bases of the linear interpolation. In the same part of this text, the hyperbolic elasticity function was defined for the linear Engel model. The behaviour of the hyperbolic elasticity function and its properties were consequently investigated too. The behaviour of the determined elasticity function was investigated according to the values of the intercept point and the direction parameter in the original linear Engel model. The obtained theoretical findings were tested using the real data of Czech Statistical Office. The developed linear Engel model was explicitly dynamised, because the achieved database was formed into the time series. With respect to the two variables definitions of the hyperbolic function in the theoretical part of the text, the determined dynamic model of the Engel demand for food was transformed into the form with parametric intercept point:ret* = At + 0.0946 · rmt*,where the values of absolute member are defined as:At = 1773.0973 + 9.3064 · t – 0.3023 · t2; (t = 1, 2, ... 32).The value of At in the parametric linear model of Engel consumer demand for food was during the observed period (1995–2002) always positive. Thus, the hyperbolic elasticity function achieved the elasticity coefficients from the interval:ηt ∈〈+0; +1).Within quantitative analysis of Engel demand for food in the Czech Republic during the given time period, it was founded, that income elasticity of food expenditures of the average Czech household was moved between +0.4080 and +0.4511. The Czech-household demand for food is thus income inelastic with the normal income reactions.


Author(s):  
E. A. Selvanathan ◽  
S. Selvanathan

Author(s):  
Bart Frischknecht ◽  
Katie Whitefoot ◽  
Panos Papalambros

This paper articulates some of the challenges for what has been an implicit goal of design for market systems research: To predict demand for differentiated products so that counterfactual experiments can be performed based on changes to the product design (i.e., attributes). We present a set of methods for examining econometric models of consumer demand for their suitability in product design studies. We use these methods to test the hypothesis that automotive demand models that allow for nonlinear horizontal differentiation perform better than the conventional functional forms, which emphasize vertical differentiation. We estimate these two forms of consumer demand in the new vehicle automotive market, and find that using an ideal-point model of size preference rather than a monotonic model has model fit but different attribute substitution patterns. The generality of the evaluation methods and the range of demand model issues to be explored in future research are highlighted.


1993 ◽  
Vol 32 (60) ◽  
pp. 20-39 ◽  
Author(s):  
RUSSEL J. COOPER ◽  
KEITH R. McLAREN

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