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Consumer Demand Analysis When Zero Consumption Occurs: the Case of Cigarettes (TB-1792)

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Consumer Demand Analysis When Zero Consumption Occurs: the Case of Cigarettes (TB-1792) United States Department of WJ Agriculture Consumer Demand Analysis When Zero Technical Bulletin Number 1792 Consumption Occurs The Case of Cigarettes James R. Blaylock William N. Blisard yjfèè It's Easy To Order Another Copy! Just dial 1-800-999-6779. Toll free in the United States and Canada. Other areas, please call 1-301-725-7937. Ask for Consumer Demand Analysis When Zero Consumption Occurs: The Case of Cigarettes (TB-1792). The cost is $8.00 per copy. For non-U.S. addresses (includes Canada), add 25 percent. Charge your purchase to your VISA or MasterCard, or we can bill you. Or send a check or purchase order (made payable to ERS-NASS) to: ERS-NASS P.O. Box 1608 Rockville, MD 20849-1608. We'll fill your order by first-class mail. Consumer Demand Analysis When Zero Consumption Occurs: The Case of Cigarettes. By James R. Blaylock and William N. Blisard. Commodity Economics Division, Economic Research Service, U.S. Department of Agriculture. Technical Bulletin No. 1792. Abstract Analysts use household survey information when attempting to model the demand for certain commodities. However, many individuals do not purchase or use specific agricultural commodities during a survey period. This presents a problem for analysts because it is unclear what the zero purchase implies. It could mean that the individual never uses the product or that the survey period was too short. Or perhaps the individual would use the product if the price were lower. By focusing on a specific commodity with well-known characteristics and patterns of use, cigarettes, we are able to examine methods of treating zero observations. Our results generally support the conclusions that analysts should thoroughly understand the characteristics of the commodity to be studied, should apply appropriate econometric techniques, and should make full and creative use of all survey information. Survey designers should structure survey questions to permit separation of the sample into users, never-users, and potential users. Keywords: Zero consumption, cigarettes, Cragg model, double-hurdle model 1301 New York Ave., NW Washington, DC 20005-4788 September 1991 III Contents Page Summary v Introduction 1 Theoretical Foundations 3 Statistical Models 5 Descriptive Statistics and Model Specification 8 Some Statistical Notes 11 Empirical Findings 11 Summary of Empirical Findings 20 References 21 IV Summary Analysts use household survey information when attempting to model the demand for certain commodities. However, many individuals do not purchase or use specific agricultural commodities during a survey period. This presents a problem for analysts because it is unclear what the zero purchase implies. It could mean that the individual never uses the product or that the survey period was too short. Or perhaps the individual would use the product if the price were lower. By focusing on a specific commodity with well-known characteristics and patterns of use, cigarettes, we are able to examine methods of treating zero observations. Our results generally support the conclusions that analysts should thoroughly understand the characteristics of the commodity to be studied, should apply appropriate econometric techniques, and should make full and creative use of all survey information. Survey designers should structure survey questions to permit separation of the sample into users, never-users, and potential users. Zero consumption can have several different meanings. One is that all individuals are potential users of the good. This implies that households can be induced to use a product if they could change their socioeconomic characteristics, income level, or the relative prices. For some agricultural products, this assumption may be invalid, resulting in biased estimates of income elasticities and the relationship drawn between demographic characteristics and consumption behavior. For example, a person may not eat certain foods because of medical conditions, religious faith, special diet, or palatability reasons. In many cases it is impossible from survey data to distinguish whether the individual is a nonuser or simply did not purchase the product during the survey period. For example, if individuals do not consume meat because they are vegetarians, then they have no influence on the demand curve for beef. On the other hand, if individuals did not eat beef during the survey period because their income was low, then they provide valuable input into the Engel curve for beef. In general, households can be separated into three groups: (1) those that never use the product, (2) infrequent users such as households that use the product but the survey period was too short to record their use, and (3) potential users who might use the product if certain economic or other factors changed, such as a lower price or increased income. Survey designers need to ask questions which may identify infrequent users, nonusers, and potential users so that researchers can formulate more effective modeling strategies. For example, if a survey question identifies members in the household as vegetarians, then this information can be used in modeling the demand for meat. Information about an individual's religious and ethnic background is valuable for treating zero observations on pork consumption. Questions probing whether or not individuals ever use or how frequently they use certain major commodities can be incorporated into econometric demand analysis. Consumer Demand Analysis When Zero Consumption Occurs The Case of Cigarettes James R. Blaylock William N. Blisard Introduction Agricultural economists often rely on household survey data to quantify the relationships between consumption of a commodity and various household socioeconomic characteristics. Many households will not, however, record purchasing or using given products during a survey period. In general, these households can belong to at least one of three groups: those that never use the product in question; infrequent users, that is, those that use the product but the survey period was too short to record it; and those that would use the product if certain economic or other factors changed, such as a lower relative commodity price or increased income. Our research objectives are to examine the use of various types of econometric models for use in more rigorous modeling of the zeros present in household survey data. We focus on using survey information that is often not available, or not used if it is, to help in our modeling efforts. The approaches we use also help explain how and why researchers should clearly understand the characteristics of the commodity to be analyzed and to exploit any special or unusual characteristics in their models. In situations in which some individuals report no purchase of a particular good, the method of Tobit estimation for demand analysis is often used. One underlying assumption embodied in this statistical technique is that all individuals are potential users of the good or, alternatively, that all zero observations represent standard corner solutions. The assumption is consequently implicit that households can be induced to use a product if they could change their socioeconomic characteristics, income level, or the relative prices. For some agricultural products, this assumption may be plausible. However, for other products this assumption may be invalid, resulting in inefficient estimates of income elasticities and the empirical measures of the association between demographic characteristics and consumption behavior. For example, a person may not eat certain foods because of medical conditions, religious faith, special diet, or palatabiiity reasons. In many cases it is impossible to distinguish from survey data whether the individual is a nonuser or is a consumer who did not consume or purchase the product during the survey period. For example, if a person simply does not consume meat, such as a vegetarian, then this individual has no influence on the demand curve for beef. On the other hand, if a person did not eat beef during the survey period because of low income, then this individual provides valuable input into the demand curve for beef. Based on input from researchers, survey designers sometimes include questions that are useful for determining whether or not a person uses a product and/or how often the person uses it. For example, the recently released individual intake part of the U.S. Department of Agriculture's (USDA) Nationwide Food Consumption Survey includes extensive questions on the use of alcoholic beverages, as well as questions on the frequency of use of other products. As this trend is likely 1 to continue, it is important for analysts to become familiar with statistical and econometric techniques that allow all available information to be used in estimating demand relationships. In this study, we examine methods of treating zero observations by focusing on the smoking behavior of women participating in the 1985-86 USDA Continuing Survey of Food Intakes by Individuals, Low-Income Women Ages 19-50. We chose to analyze smoking behavior for several reasons. First, tobacco is a product that has well-known characteristics: it is an addictive and frequently used product. Cigarette use represents not only a consumption decision but is also a form of social behavior. This suggests that the decision to start smoking and the decision of how much to smoke may be influenced in different ways by the same factor. This highlights another shortcoming of the Tobit model. This model restricts the coefficients of the starting and consumption equations to have the same sign and magnitude. There is no a priori reason why this should be the case. An alternative is to model the decisions to consume and how much to consume separately. This technique is known as the double-hurdle approach in the economics literature and the well-known Cragg model is an example (5).^ Second, our data contain additional information that permits separation of the sample's nonsmokers into two groups: those who have never smoked and ex-smokers. We will specify several different theoretical models and their statistical counterparts each treating the nonsmokers differently.
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