About

Senarath Dharmasena, Ph.D., is an instructional associate professor in the Department of Agricultural Economics at Texas A&M University. He also serves as an associate in the Agribusiness, Food and Consumer Economics Research Center (AFCERC) and is an associate editor for the Journal of Agribusiness in Developing and Emerging Economies (JADEE). His educational background includes a B.S. in Agriculture from the University of Peradeniya, and both an M.S. and Ph.D. in Agricultural Economics from Texas A&M University. His areas of expertise encompass consumer economics, applied demand analysis, agribusiness and food market analysis and forecasting, health and nutrition economics, economics of food security, food environments and obesity, causality modeling and causal inference, artificial intelligence and machine learning, data science, market integration and price discovery, U.S. energy demand analysis, macroeconomics of agriculture, simulation, and risk modeling. Dr. Dharmasena's research contributions include analyzing demand interrelationships of food products, policy implications of energy demand systems, complex food environments, seasonal demand system modeling, and the economic impacts of health-related taxes. His work is characterized by a focus on applying economic analysis to food markets, health, and energy systems, contributing to the understanding of complex economic systems within agriculture and food sectors.

Research topics

• Food science
• Economics
• Mathematics
• Business
• Marketing
• Agricultural economics
• Forestry
• Geography
• Biology
• Microeconomics
• Econometrics
• Engineering

Selected publications

• Economics of the Agricultural Aviation Industry in the United States: Determination of Profit Under Varying Agricultural Aircraft and Risk

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• How much is the Agricultural Aerial Application Industry in the United States Worth? A Counterfactual Study

  SSRN Electronic Journal · 2024-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Value of the Agricultural Aerial Application Industry in the United States Delineated by Crops Grown and by State: A Counterfactual Study

  SSRN Electronic Journal · 2024-01-01

  preprintOpen access
  PublisherDOI

• Food Price Inflation in the United States as a Complex Dynamic Economic System

  Journal of Agricultural & Food Industrial Organization · 2024-05-21 · 3 citations

  articleOpen accessSenior authorCorresponding

  Abstract The issue of volatile food prices is a consistent problem for American consumers, as rising prices make it challenging to afford nutritious food that meets dietary standards. Various complex factors influence this price volatility, including economic conditions, weather patterns, global trade, energy prices, and more. Notably, the impact of food price increases is not equal for everyone. Low-income individuals and those in rural areas are disproportionately affected. A comprehensive understanding of the driving factors is essential to tackle this issue effectively. We employ advanced time-series techniques such as Vector Error Correction Models (VECM) and modern causal inference methods such as probabilistic graphical models implemented via machine learning and artificial intelligence approaches on monthly data from 2000 to 2021 to investigate the U.S. food price inflation issue. These methods help unravel the intricate dynamics among key variables driving food price inflation. The study aims to achieve several objectives. It intends to (1) clarify how factors influencing food price inflation in the U.S. change over time using VECM models, (2) establish causal relationships among interconnected variables to develop probabilistic graphical models using innovative search algorithms, and (3) create and validate forecasts related to U.S. food price inflation. The end goal is to provide actionable insights for policy design. Results show that food price inflation is heavily tied to commodity pricing and pricing for medical services. Additionally, historical decompositions for COVID-19 show ties between food price inflation and energy inflation.

  PublisherDOI

• A household-level demand system analysis of nuts in the United States

  Agricultural and Resource Economics Review · 2022 · 10 citations

  Senior authorCorresponding
  • Economics
  • Agricultural economics
  • Econometrics

  Abstract An Exact Affine Stone Index demand model is estimated to analyze the household-level demand for nine nut products (peanuts, pecans, almonds, cashews, walnuts, pistachios, mixed nuts, macadamia nuts, and other nuts) in the United States using Nielsen Homescan panel data from 2009 through 2015. The demands for all nuts are elastic. All nut products are necessities and substitutes for each other. Household sociodemographic characteristics are statistically significant drivers of the demand for nut products. Finally, the effects of changes in the magnitude of selected promotion expenditure elasticities for nuts are simulated to determine their impacts on prices and quantities demanded.

  PublisherOA PDFDOI

• Demand analysis of peanuts and tree nuts in the United States: a micro-perspective

  The International Food and Agribusiness Management Review · 2021 · 8 citations

  Senior authorCorresponding
  • Marketing
  • Economics
  • Agricultural economics

  This paper examines household purchases of peanuts and tree nuts in the United States using the Nielsen Homescan Panel for calendar year 2015. Households located in different regions and from different races and ethnicities along with seasonality were important factors affecting the propensities to purchase and actual quantities purchased. The demand for pecans, almonds, and walnuts was sensitive to price changes. The reverse was true regarding the demands for cashews, macadamia nuts, pistachios, mixed nuts, and peanuts. All nuts were identified as necessities. Findings of this research provide insights for stakeholders in the nut industry, in terms of target marketing, product positioning, and pricing strategies. Moreover, we contribute to the literature by providing a micro-perspective investigation concerning the demand for nut products in the United States. In addition, we provide a more up-to-date analysis concerning factors affecting not only the likelihood of purchasing nuts but also the quantities purchased.

  PublisherOA PDFDOI

• U.S. Consumers’ Intake of Food at Home (FAH) and Food Away from Home (FAFH) As a Complex Economic System

  AgEcon Search (University of Minnesota, USA) · 2021-01-01 · 2 citations

  articleOpen access

  Americans spend billions of dollars in personal consumption expenditures each year. The percentage of FAH expenditures in the United States has been dwindling, while the percentage of FAFH expenditures has increased. Many factors might be causing this trend. Complex interactions of such factors determining the U.S. consumer’s intake of FAH and FAFH expenditures were studied using machine learning and Directed Acyclic Graphical approaches. Employment and education status are common causes of both FAH and FAFH expenditures. Body mass index, marital status, race and sex have mixed effects. Findings will be useful for policy makers to implement social support programs.

  PublisherOA PDFDOI

• U.S. Consumer Demand for Plant-Based Milk Alternative Beverages: Hedonic Metric Augmented Barten’s Synthetic Model

  Foods · 2021 · 24 citations

  Senior authorCorresponding
  • Food science
  • Mathematics
  • Marketing

  Consumers in the U.S. increasingly prefer plant-based milk alternative beverages (abbreviated "plant milk") to conventional milk. This study is motivated by the need to take into consideration varied nutritional and qualitative attributes in plant milk to examine consumers' purchasing behavior and estimate demand elasticities which are achieved by a new approach combing hedonic pricing model with Barten's synthetic demand system. The method of estimation is enlightened from the common practice of companies differentiating their products in multidimensions in terms of attributes. A research dataset was uniquely created by associating the products' purchase data from Nielsen Homescan dataset with exclusive first-hand nutritional data. Estimations began with creating a multidimensional hedonic attribute space based on the qualitative information of different types of plant milk and conventional milk available to consumers and then calculating the hedonic distances by Euclidean distance measurement to reparametrize Barten's synthetic demand system. Estimation results showed that the highest own-price elasticity pertained to soy milk which was -0.25. Three plant milk types had inelastic demand. Soy milk exerted substituting effects on all types of conventional milk products and vice versa. Soy milk, rice milk and almond milk entertained complementary relationships between each other and four types of conventional milk were strong substitutes within the group.

  PublisherOA PDFDOI

• Consumers preferences on nutritional attributes of dairy‐alternative beverages: hedonic pricing models

  Food Science & Nutrition · 2020 · 27 citations

  Senior authorCorresponding
  • Business
  • Marketing
  • Food science

  Dairy products, especially milk play a crucial role in assuring dietary quality for U.S. households. However, due to taste, nutrition, health and environmental concerns, households increasingly prefer to consume dairy alternative beverages instead of conventional milk in the U.S. This work is motivated by the need to take into consideration of intrinsic characteristics and differences of such characteristics when analyzing the changes of consumers' purchasing behavior of and willingness to pay for dairy alternative beverages and conventional milk products. After aggregating and organizing the purchase data of Nielsen Homescan and first-hand nutrition data, this study estimates both linear and semi-log hedonic pricing models. The results show that consumers exert the highest weights and assign highest evaluation on such qualitative characteristic as nutritional attributes which include calories, protein, fat, vitamin A and vitamin D in which protein is the most valued attribute and other characteristics such as package size, multi pack and brand. The hedonic pricing order and value of these qualitative characteristic are indicative of consumers' purchasing behavior and thus provide essential information for manufacturers to better differentiated their products and develop products catering to consumer's preferred attributes.

  PublisherOA PDFDOI

• Empirical Assessment of Endogeneity and Instrumental Variables in a Complex Economic System using Graph Theoretic Approach: An Application to the U.S. Food Environment

  2019-01-01 · 1 citations

  preprintOpen access1st authorCorresponding

  Agricultural and Food Policy, Research Methods/Statistical Methods

  PublisherDOI

Frequent coauthors

• Oral Capps

  Texas A&M University

  101 shared

• David A. Bessler

  36 shared

• Mark C. Senia

  College Station Medical Center

  23 shared

• Alicia Copeland

  8 shared

• Tingyi Yang

  Shaanxi Normal University

  6 shared

• Victoria Salin

  Texas A&M University

  6 shared

• Michelle Paukett

  Mitchell Institute

  6 shared

• Andrés Silva

  San Sebastián University

  6 shared

Education

• Ph.D., Agricultural Economics

  Texas A&M University

  2000

• M.S., Agricultural Economics

  Texas A&M University

  1996

• B.S., Agricultural Economics

  University of Peradeniya

  1992

Awards & honors

• Tyrus R. Timm Honor Registry