Incorporating Time Costs into SNAP Allotment Calculation: A Home Food Production Time Use Analysis
Wen You and
No 235903, 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts from Agricultural and Applied Economics Association
The Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp Program, is the largest domestic food assistance program for low-income individuals and, according to the Congressional Research Service, accounts for almost 80% of the USDA mandatory budget. In 2014, the program served about 47 million people with a total program cost of about $74 billion. The average monthly benefits in 2014 were around $125 per person and $256 per household (FNS, 2015a). Thorough evaluations of the SNAP program effectiveness at achieving its goals (i.e., achieving food security and healthier diets) are wanted given the sizable program costs and are essential for utilizing the vast coverage of SNAP program to achieve the largest public health impact. It has been shown in the literature that ignoring food production time (i.e., labor cost) in the home food production can lead to an overly optimistic evaluation of the effectiveness of SNAP. Focusing on single-headed households, Davis and You (2011) found out the households spent on average 40% less than enough to meet the Thrift Food Plan (TFP) threshold (as compared to 35% more than enough when labor time is ignored) and only 15% households spend enough to reach the TFP threshold (as compared to 65% when labor is not considered). It shows that time constraint is a significant barrier to reach nutrition goal. This line of research has caught political and policy attentions with the leading example that the Institute of Medicine (IOM) report in 2013 calls for research that seeks tractable manner to incorporate time cost into SNAP benefit calculation in order to improve the SNAP program effectiveness at reaching nutrition targets. The purpose of this paper is three fold. First is to answer the recent call from the IOM to incorporate time dimension into the SNAP benefit formula in a tractable manner for both single-headed households and dual-headed households. The first recommendation coming out of the IOM indicates that “USDA-FNS should examine the impact of accounting for cost-time trade-offs, for example, by: applying a time adjustment multiplier to the cost of the TFP…” (Caswell and Yatkine 2013 p.6-5). We demonstrate the appropriate form this multiplier needs to take to be consistent with the basic compensation principle known as the cost difference approach. Second is to demonstrate how to estimate this multiplier for both single headed and dual headed households. For dual headed households we present an algorithm that utilizes the food production role identification information that is available in the Eating and Health Module supplement to the ATUS to predict the missing spousal home food production time for the dual-headed households. This algorithm is a contribution in its own right as a similar procedure could be used to look at other important time allocation duties, such as child care, but where time use information collection may be limited. Third is to determine whether or not the dual nature of the household makes a difference in the proposed SNAP benefit adjustment and compare the adjusted benefits with other food plans (i.e., Low Cost Food Plan and Moderate Cost Food Plan). This study utilizes American Time Use Survey (ATUS) data to get information on actual time spent in food production. For single-headed households, the respondent time use data can be treated as the total household time spent in food production if the respondent is the main food producer which we utilize information provided by Eating and Health Module (EHM) supplement to ATUS to identify. For dual-headed households, the missing spousal time use information requires imputation which we propose an algorithm for that. We restrict the sample to those with one or two adults to avoid predicting other adults’ time use since we do not have any further information on other adults of the households. We further limit the sample to those households indicating that their household income is less than or equal to 185% of the poverty threshold since the focus of scaling the SNAP benefits is to help low-income households. We further drop households with respondent indicating that he/she is sharing the food production roles with other adults in the household since there is no information available to assume the percentage split of the responsibility. Two-part models are utilized to predict spousal time use and other days of the week time use based on food production role differences and the scaling factor k is calculated for the following four categories of households: single-headed households with children, single-headed households without children, dual-headed households with children, dual-headed household without children. To account for the uncertainty in the opportunity cost of time and the estimation noises in the actual time use, we conduct parametric bootstrapping to map out the empirical distribution for the estimated multiplier for the SNAP benefits. We find that ignoring spousal contribution to household food production underestimates household home food production time by about 3 hours per week. Without considering the spousal contribution to food production time, we are likely to overestimate the labor adjusted full TFP cost deficit by about $50 per week. On average, the suggested multiplier, k, is less than 0.5. Furthermore, we compare the adjusted TFP amount with the Low-Cost Food Plan (LCFP) amount and Moderate-Cost Food Plan (MCFP) amount. The adjusted TFP amount has much higher median than both LCFP and MCFP for single-headed households with and without children. Results also show that dual-headed households have the flexibility of spousal time substitution therefore their time constraints are not as tight as the single-headed households and require smaller time-cost adjustment to meet the threshold.
Keywords: Consumer/Household Economics; Food Consumption/Nutrition/Food Safety; Food Security and Poverty; Health Economics and Policy (search for similar items in EconPapers)
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