Monthly data derived from the Nielsen Homescan Panel for calendar years 1998 through 2003 are used to estimate the effects of a proposed tax on sugar-sweetened beverages (SSBs). Most arguments in describing the ramifications of a tax fail to consider demand interrelationships among various beverages. To circumvent this shortcoming we employ a variation of Quadratic Almost Ideal Demand System (QUAIDS) model. The consumption of isotonics, regular soft drinks and fruit drinks, the set of SSBs, is negatively impacted by the proposed tax, while the consumption of fruit juices, low-fat milk, coffee, and tea is positively affected. Diversion ratios are provided identifying where the volumes of the SSBs are directed as a result of the tax policy. The reduction in the body weight as a result of a 20% tax on SSBs is estimated to be between 1.54 and 2.55 lb per year. However, not considering demand interrelationships would result in higher weight loss. Unequivocally, it is necessary to consider interrelationships among non-alcoholic beverages in assessing the effect of the tax.

Soymilk is one of the fastest growing categories in the U.S dairy alternative functional beverage market. Using household-level purchase data from Nielsen's 2008 Homescan panel and the Tobit econometric procedure, we estimate conditional and unconditional own-price, cross-price, and income elasticities for soymilk, white milk, and flavored milk. Income, age, employment status, education level, race, ethnicity, region, and presence of children in a household are significant drivers of demand for soymilk. White milk and flavored milk are competitors for soymilk, and soymilk is a competitor for white milk. Strategies for pricing and targeted marketing of soymilk are also discussed.

The food environment in the United States is complex. Sixteen socio-economicdemographic variables from various public data sources are studied with a machine learning algorithm to ascertain the causality structure associated with the food environment in the United States. High levels of unemployment and poverty are direct causes of high levels of food insecurity, while low income causes to have high levels of food insecurity via increased levels of poverty. Unemployment is a common cause for both increased levels of food insecurity and poverty. We find that food insecurity and participation in Supplemental Nutrition Assistance Program (SNAP) are related, yet no direct causality is observed. Contrary to past studies which find that SNAP participation decreased the occurrences of poverty, in contemporaneous time, we find that poverty and SNAP participation are related through several back-door paths, via food insecurity, unemployment, race and food taxes. Obesity and SNAP participation are indirectly related via several back-door paths, namely, race income, poverty and food insecurity and unemployment. Also, food insecurity and obesity are related by several back-door paths. Low income, high food taxes, and race (being Black and non-Hispanic) are direct causes of obesity. The complex causality structure in the US food environment reveals that policy variables cannot be treated independently of their rich causal structure. Government agencies responsible for designing policies for food assistance, poverty alleviation, combating food insecurity and obesity need to consider the interrelationships among these variables.