Bayesian Inference for Multidimensional Welfare Comparisons
Using both single-index measures and stochastic dominance concepts, we show how Bayesian inference can be used to make multivariate welfare comparisons. A four-dimensional distribution for the well-being attributes income, mental health, education, and happiness are estimated via Bayesian Markov chain Monte Carlo using unit-record data taken from the Household, Income and Labour Dynamics in Australia survey. Marginal distributions of beta and gamma mixtures and discrete ordinal distributions are combined using a copula. Improvements in both well-being generally and poverty magnitude are assessed using posterior means of single-index measures and posterior probabilities of stochastic dominance. The conditions for stochastic dominance depend on the class of utility functions that is assumed to define a social welfare function and the number of attributes in the utility function. Three classes of utility functions are considered, and posterior probabilities of dominance are computed for one, two, and four-attribute utility functions for three time intervals within the period 2001 to 2019.
Code (0)
등록된 구현이 없습니다.
Tasks
AttributeBayesian InferenceSimilar Papers 제목 키워드 기반
Generalized Social Marginal Welfare Weights Imply Inconsistent Comparisons of Tax Policies
This paper concerns Saez and Stantcheva's (2016) generalized social marginal welfare weights, which aggregate losses and gains due to tax policies, while incorporating non-utilitarian ethical considerations. The approach…
Learning Social Welfare Functions
Is it possible to understand or imitate a policy maker's rationale by looking at past decisions they made? We formalize this question as the problem of learning social welfare functions belonging to the well-studied fami…
Keeping up with "The Joneses": reference dependent choice with social comparisons
Keeping up with "The Joneses" matters. This paper examines a model of reference dependent choice where reference points are determined by social comparisons. An increase in the strength of social comparisons, even by onl…
No-Regret Learning in Bayesian Games
Recent price-of-anarchy analyses of games of complete information suggest that coarse correlated equilibria, which characterize outcomes resulting from no-regret learning dynamics, have near-optimal welfare. This work pr…
On the Welfare (Ir)Relevance of Two-Stage Models
In a two-stage model of choice a decision maker first shortlists a given menu and then applies her preferences. We show that a sizeable class of these models run into significant issues in terms of identification of pref…