FOOD INSECURITY, RACE and MARKET DEMAND

Abstract

This dissertation includes three essays related to the analysis of the food market from both the consumers’ end and the producers’ end. On the consumption side, I look into the association between food insecurity and liquidity constraint. Further, I investigate this association focusing on black households. On the production side, I estimate the effect of generic advertising on market demand using the Autoregressive Distributive Lag Model. In chapter 1, I investigate the association between food insecurity and financial liquidity constraints. I use a survey data obtained from the Qualtrics panel on the residents of Alabama and estimate the association using Linear Probability Model. In my study, liquidity constrained is defined as the inadequate cash in hand of the respondents. My estimation suggests that adequate cash in hand will act as a cushion for food insecurity. My results underscore that short-term cash on hand can be a solution to smoothen out consumption during a sudden disruption in income to restore food security. To check the robustness of my results, I controlled for the respondents living in the urban areas and incorporated the census tract data obtained from the Food Research Atlas to gauge the association between liquidity constraint and the food insecurity if the households are in the food deserts. We find that our estimates are robust. In addition to this, I find that, the association between financial liquidity constraint and food insecurity varies over race. For example, in the sample as a whole liquidity constraint increases the probability of a household being food insecure by 0.22. For white households the probability increases to 0.26, and for black households it decreases to 0.052. The next chapter focuses on why the correlation between food insecurity and financial liquidity constraint is so much weaker for the black households. In this chapter, the analysis proceeds by focusing on a subset of the original sample identified as black households. For the estimation, I use Linear Probability Model. Surprisingly, I find no significant association between food insecurity and liquidity constraints among the black households. To see whether specification error might explain the result, I explore the influence of different factors that include employment status, ability to obtain money from informal sources, participation of Supplemental Nutrition Assistance Program (SNAP), method of payment for grocery bills, frequency of visits to the grocery stores, distance of grocery stores, time to reach the grocery stores and the choice of visiting the grocery stores. Among these variables the only one to have a significant effect on results was informal sources for obtaining money. In this instance, all else equal the lack of such sources increases the probability of a black household being food insecure by 0.20. The inclusion of the variable caused the liquidity constraint variable to become significant with an estimated coefficient of 0.22. Overall, results suggest black households can mitigate food insecurity and the effect of liquidity constraints on food insecurity if they are able to borrow money from informal sources. The third chapter explores the impact of generic advertising on market demand in the Norwegian whitefish industry using Autoregressive Distributive Lag (ADL) Model. Despite being a “workhorse” for dynamic single-equation regressions the ADL model and attendant methods of testing for cointegration have not been applied in empirical studies of generic advertising. The advantages of the autoregressive distributed lag (ADL) model for estimating the effects of generic advertising on market demand are evaluated by applying the model and attendant methods to data used in a recent study of Norway’s export promotion program for whitefish. The dynamic specification differed greatly depending on model selection criteria (Akaike Information, Hannan-Quin, Schwarz, and Adjusted R2). Despite this there was little to choose between the specifications in terms of the estimated long-run demand elasticities. The estimated short-run elasticities differed among the specifications, with the model selected by the Hannan-Quin criterion indicating a more elastic response to income than the model selected by the Schwarz criterion. The bounds test for cointegration, a special feature of the ADL approach, proved useful in distinguishing between the appropriateness of quantity- and price-dependent specifications of the demand equation. Tests for weak exogeneity of the regressors indicated adjustments in quantity are 5.5 times more important than adjustments in price in resolving dynamic disequilibria caused by random (monthly) shocks to long-run demand.