Mike Palazzolo

Mike Palazzolo is an Associate Professor of Marketing at the University of California, Davis' Graduate School of Management. His research examines intertemporal trade-offs in consumer behavior at the intersection of marketing and policy, with recent emphasis on nutrition-related decision-making and causal inference methodologies.

His academic credentials include:

• Ph.D. in Marketing from University of Michigan’s Ross School of Business (2016)
• MBA from UC Davis Graduate School of Management
• B.S. in Management Science from UC San Diego

Palazzolo's research focuses on how consumers make trade-offs between immediate and future benefits, particularly in food selection and financial decisions. His work demonstrates how policy interventions like school nutrition mandates and minimum wage increases directly affect household consumption patterns, with special attention to low-income and time-constrained families. He employs rigorous causal inference techniques to isolate policy effects from confounding factors, establishing robust links between economic policies and nutritional outcomes.

Analysis of his 2018-2025 publications reveals consistent thematic progression: early work established foundational insights into frugality constraints, while recent research examines real-world policy impacts on nutrition through school meal programs and wage policies. His studies increasingly incorporate behavioral economics frameworks to explain why households respond to nutritional mandates, with growing emphasis on vulnerable populations.

Key recognition:

• 2019 Paul Green Award for "Frugality is Hard to Afford" - the Journal of Marketing Research's top honor recognizing exceptional contribution to marketing theory and practice

Palazzolo teaches MBA courses in causal inference and marketing analytics at UC Davis. His research collaborations span institutions including Georgia Institute of Technology and Dartmouth College, though specific grant funding details aren't disclosed in source materials. No dedicated research labs or teams are mentioned in available documentation.