** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** THIS PROJECT GENERATES NEW KNOWLEDGE REGARDING FARMERS' MARKETSTRUCTURE AND PERFORMANCE, CONSUMER CHOICES, AND FOOD POLICY THROUGH BIG MOBILE LOCATION DATA AND ADVANCED MACHINE LEARNING (ML) METHODS. DIRECT MARKETING BENEFITS PRODUCERS, CONSUMERS, AND THE LOCAL COMMUNITY AND IS A KEY COMPONENT OF FOOD-BASED POLICIES. PREVIOUS WORK ON FARMERS' MARKETS HASRELIED ON CASE STUDIES AND SURVEY DATA, WHICH WERE GENERALLY LOCALIZED WITH SMALL SAMPLE SIZES, QUESTIONING THEIR EXTERNAL VALIDITY AND MERIT FOR CAUSAL INFERENCE. WE PROPOSE TO ADDRESS THESE LIMITATIONS BY EXPLOITING A UNIQUE DATASET OF MOBILE LOCATION DATA FOR 125 MILLION CELLPHONE USERS THROUGHOUT THE UNITED STATES. THIS NOVEL DATASET ALLOWS US TO ANSWER CRITICAL QUESTIONS OF INTEREST TO PRODUCERS, POLICYMAKERS, AND MARKET MANAGERS. OUR RESEARCH PROVIDES FOUR PRIMARY CONTRIBUTIONS. FIRST, WE WILL GENERATE NEW INSIGHTS REGARDING CONSUMER DECISIONS SURROUNDING FARMERS' MARKETS. SECOND, WE CAN IDENTIFY THE SPILLOVER EFFECTSOF FARMERS' MARKETSON NEARBY BUSINESSES. THIRD, AS POLICYMAKERS USE FARMERS' MARKETSTO ADDRESS FOOD INSECURITY IN LOW-INCOME NEIGHBORHOODS, WE WILL MEASURE THE DEGREE TO WHICH TARGETED CUSTOMERS ATTEND THESE MARKETS. FOURTH, GIVEN INCREASING CONCERNS ABOUT THESATURATION OF FARMERS' MARKETS, WE WILL ASSESS THE COMPETITIVE LANDSCAPE AND HOW THAT IMPACTS ATTENDANCE AND COMPLEMENTARY BEHAVIOR. THE PANEL NATURE OF OUR DATA ALSO ALLOWS US TO IDENTIFY COVID-19 IMPACTS USING CAUSAL INFERENCE METHODS AND REVEALED CONSUMER CHOICE DATA FROM 2019-2022. THIS INNOVATIVE AND INTERDISCIPLINARY RESEARCH WILL PROVIDE ESSENTIAL KNOWLEDGE OF THE FUNCTIONING OF AGRICULTURAL MARKETS. IT WILL PAVE PATHWAYS FOR NOVEL RESEARCH INTO CONSUMER CHOICES THROUGH MULTIDISCIPLINARY COLLABORATION AND TRAINING, BIG ECONOMIC DATA, AND ADVANCED ML METHODS.