{'fraction_non_alphanumeric': 0.0273224043715847, 'fraction_numerical': 0.0, 'mean_word_length': 4.9728260869565215, '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}}
A Better Calculus for Regulators: From Cost-Benefit Analysis to the Social Welfare Function

The “social welfare function” (SWF) is a powerful tool that originates in theoretical welfare economics and has wide application in economic scholarship, for example in optimal tax theory and environmental economics. This Article provides a comprehensive introduction to the SWF framework. It then shows how the SWF framework can be used as the basis for regulatory policy analysis, and why it improves upon cost-benefit analysis (CBA). 
Two types of SWFs are especially plausible: the utilitarian SWF, which sums individual well-being numbers, and the prioritarian SWF, which gives extra weight to the well-being of the worse off. Either one of these is an improvement over CBA, which uses a monetary metric to quantify well-being and is thereby distorted by the declining marginal utility of money. The Article employs a simulation model based on the U.S. population survival curve and income distribution to illustrate, in detail, how the two SWFs differ from CBA in selecting risk-regulation policies.