Conclusions

Two estimators were considered, Full Information Maximum Likelihood and Iterative Seemingly Unrelated Regression. The first estimator did not produce as many significant differences in consumption as the second. Dummy variables were used for comparing significant differences in meat consumption by ethnic groups with respect to Hispanics.

Under the same starting values generated by SUR, and same convergence criteria, FIML produced almost the same magnitudes in the parameters and elasticities compared with those generated by ITSUR, albeit the standard errors were bigger. Interpretations of parameters and elasticities were accomplished from the estimates produced by ITSUR.

The inclusion of demographic variables in the demand system required more computing power as the number of bvariables increased in the models. It was observed that the inclusion of household size in Amsterdam scale produced elasticities more consistent with economic theory, by producing more substitute relationships among the meat items that were analyzed. The number of substitute relationships increased as the sample increased. The same took place with own price elasticities; more elasticities were produced with negative signs.

The decision to purchase was modeled in order to correct for selectivity bias, although many combinations of variables and transformations were considered; the procedures of Lanfranco were followed, since the deletion or inclusion of variables produced slight va riations in the classification tables, Likelihood Ratio tests for the parameters included in the probit regressions were the same, and no single mean probability was significantly different from the estimates produced by the complete set of variables in the demand system compared with the estimates generated with household size and logarithm of income as the independent variables for explaining the probability of positive expenditures. More research needs to be done for

addressing the functional form of the variables that must be used in the Probit regression, since its estimates are used to calculate the standard and normal cumulative functions that eliminate selectivity bias that comes from zero values in the dependent variables in the demand system.

More significant marginal effects of household size were found compared to marginal effects of income, across all ethnic groups. Hispanic households were less likely to be influenced by income in their purchase decisions when compared to White, African American and households of other minorities. Hispanic households were influenced more by household size than income in their decisions to purchase meat products; when they were compared with other ethnic groups.

It is widely known that as sample size increases the number of significant parameters increase. This was the case of censored LinQuad demand systems, not only did the number of significant parameters increase but also the number of significant elasticities that were estimated under high levels of censoring.

Hispanic households consume more beef products, pork products and chicken with respect to other ethnic groups. Hispanics consume less ground beef compared to White and African American households, and they consume significantly more with respect to other minorities at the 10% level of significance. White households consume less beef products compared to Hispanics, significant differences were found in beef steak at the 5% level of significance. Consumption of pork products by White households was in general lower when compared to Hispanics, with the exception of bacon. At the 5% level of significance, White households consume significantly less chicken and seafood products compared to Hispanic households.

Positive and significant differences in consumptio n of meats between Hispanics and African Americans were found only on ground beef, bacon, and chicken, using a 10% level of significance. Households of other minorities in general allocated less expenditures for meat products compared to Hispanics; negative and statistically significant differences were found in beef steak and ham and ground beef; positive and significant differences were found in other pork and seafood products. The responsiveness to changes in demand due to changes in own prices, cross prices, income, and household size was presented for each ethnic group. In each set of results, a demand system for all households was performed; by doing so, not only can comparisons among ethnic groups that represent U.S. society be made but also comparisons with the results of the market as a whole.

If the interest of the researcher is to find the effects of prices on demand for goods under high levels of censoring, it is questionable whether or not one should make interpretations from demand systems that include demographic variables since most of the effects of demographic variables were insignificant across ethnic groups and also the inclusion of demographic variables produced inconsistent own price elasticities, and the estimated parameters and elastic ities are sensitive to the number of variables used in the first step of the Probit regressions as well. As a result, the use of disaggregated data that keeps the linkage between prices, quantities of the goods consumed, and socioeconomic characteristics of the consumer is recommended.

Given that on average Hispanics consume more meat products, although there are differences in income, the higher rate of their population will make it even more attractive for the food industry to target this group of consumers. The food industry must understand the food preferences for meats of Hispanics in order to harness the potential market opportunities that this segment of the population is likely to create in the U.S. marketplace. Researchers, corporations,

agribusinesses, governmental agencies and businesses in general may benefit from the results that this study produces.

Louisiana farmers, the U.S. food industry, and in particular the meat industry may endeavor to develop marketing strategies and competitive advantages by determining the food needs of Hispanics and fulfilling them by providing healthier products for consumers. In the end, those endeavors will bring more revenue to American farmers and food corporations, and a greater well-being to the served markets.