{'fraction_non_alphanumeric': 0.019002375296912115, 'fraction_numerical': 0.0, 'mean_word_length': 5.853658536585366, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Modeling Preference Heterogeneity Within and Across Behavioral Types: Evidence from a Real-world Betting Market

While it is commonly accepted that risk preferences differ across individuals, studies that estimate them typically allow for limited heterogeneity. We develop a methodology that allows for richer representation of heterogeneity both within and across utility types characterized by different behavioral features. This enables us to improve individual- and population-level estimates, and to assess the relative importance of loss aversion and probability weighting, and their prevalence in the population. Applying our model to individual sports-betting choices, we find that utility curvature alone does not explain observed choices and, while two-thirds of individuals exhibit loss aversion, all exhibit probability weighting.