RESEARCH

1. Quantifying the Effect of School Lunches on Food Components Consumption and Diet Quality of Children.

(With Ariun Ishdorj) (Under review)

Despite improved National School Lunch Program (NSLP) nutrition standards, participants’ dietary quality remains below the optimal levels. This study examines the relationship between school meal consumption and dietary quality and its components, while accounting for meal cost, and simulating sodium reduction scenarios. Using the National Health and Nutrition Examination Survey and two-group two-period Tobit model, we find that participants, compared to nonparticipants, consume more fruits, vegetables, dairy, whole grains, and less refined grains, and added sugar. Access to free or low-cost meals significantly improves participants’ dietary quality, and sodium reduction can be implemented without compromising overall diet quality.

2. Measuring the Effect of Meal Sources and Prices on Diet Quality.

     (With Ariun Ishdorj)  (In progress)

The dietary quality of US Adults often does not meet recommended nutrition standards, a situation further complicated by the increasing demand for food away from home (FAFH). This study examine how meals from FAFH—through fast-food establishments and full-service dining restaurants—and food at home (FAH) sources along with their prices, has impacted the dietary quality of adults, as measured by the Healthy Eating Index (HEI) and its adequacy and moderation components scores. Using adults’ dietary intake data from the National Health and Nutrition Examination Survey (NHANES) and a copula-based regression model, we find that consuming one fast food meal relative to a home meal, at average meal prices, decreases the HEI by 4.72% and the adequacy components score by  8.71%, while having no significant effect on the moderation components score. Conversely, consuming one full-service dining meal relative to a home meal, at average meal prices, increases the HEI by 8.11% and the adequacy components score by 17.89 %, while also decreasing the moderation components score by 9.83%. Additionally, increase in home meal price above the average amplify the negative impact of fast-food meal and reduces the positive impact of full-service dining meal. Heterogeneity analyses reveals that fast-food meal’s negative effect is strongest for high-income and Hispanic adults, and increase in home meal price above average most adversely affect dietary quality of Hispanic, non-Hispanic black and young and older-age adults.

3. Effects of Information and Communication Technologies on Expanding Agricultural Markets in Developing Countries: A Systematic Review and Meta-Analysis.(USDA Report) 

(with Elizabeth Tabares, Ariun Ishdorj, Siwan Song, Margaret Foster, Thuy Floyd) (In progress.)

4. Evaluating the  impact of Addmilk Program on healthy fluid milk sale.

     (work in Progress, Hunger Solutions Institute)

The Hunger Solutions Institute operates the Addmilk Program in partnership with retailers across more than 15 U.S. states. Under this initiative, SNAP households receive discounts or coupons when purchasing low-fat or skim milk using their SNAP benefits. We analyze milk transaction data to evaluate the program’s impact. In addition, we conduct primary surveys with SNAP households to examine how different SNAP programs and policies could be more effective in improving participants’ health and food security.

5. Evaluating the impact of SNAP Nutrition Incentive Program on Food Security. 

(Work in Progress, Hunger Solutions Institute)

The Double Up Food Bucks Alabama, a SNAP nutrition incentive program, implemented by the HSI under the USDA's GusNIP initiative. In this program, SNAP households receive GusNIP tokens of equal value when they purchase fruits and vegetables using their SNAP benefits. These tokens can be redeemed in subsequent transactions, helping SNAP families stretch their benefits while accessing healthier foods. We analyze the program’s impact on participants’ food security and health status. In addition, we conduct surveys with SNAP households to assess how the program is benefiting them and to identify opportunities for improvement.

Industry research 

1. Estimated the impact of prime fee-hike on the purchase behavior of Amazon prime members using quasi-experimental methods: difference-in-differences, propensity score matching and double machine learning. 

2. Pradhan Mantri MUDRA Yojana - contribution of NBFC-MFIs 

(The Indian Banker (Volume IV Issue 5, December 2016. Page 44. )

3. Rural infrastructure development fund (RIDF)

(Oriental bank of commerce, half yearly magazine. June 2015 )