Ranking methods are fundamental tools in many areas. Popular methods aggregate the statements of 'experts' in different ways. As such, there are various reasonable ranking methods, each one of them more or less adapted to the environment under consideration. This paper introduces a new method,...

We solve the non-linear income tax program for a rank-dependent social welfare function à la Yaari, expressing the trade-off between size and inequality using the Gini or related families of positional indices. The key idea is that when agents optimize and absent bunching, ranks in the actual...

This paper provides a simple theoretical framework to evaluate the effect of key parameters of ranking algorithms, namely popularity and personalization parameters, on measures of platform engagement, misinformation and polarization. The results show that an increase in the weight assigned to...

This paper illustrates that the generalized propensity score method can easily be applied with multiple continuous endogenous treatment variables. Consistency proofs carry over straightforwardly to this general case, and the approach is shown to work well in finite samples with various...

Making use of restrictions imposed by equilibrium, theoretical progress has been made on the nonparametric and semiparametric estimation and identification of scalar additive hedonic models (Ekeland, Heckman, and Nesheim, 2002) and scalar nonadditive hedonic models (Heckman, Matzkin, and...

Empirical welfare analyses often impose stringent parametric assumptions on individuals' preferences and neglect unobserved preference heterogeneity. In this paper, we develop a framework to conduct individual and social welfare analysis for discrete choice that does not suffer from these...

Commonly used methods of production function estimation assume that a firm's output quantity can be observed as data, but typical datasets contain only revenue, not output quantity. We examine the nonparametric identification of production function from revenue data when a firm faces a general...