The data envelopment analysis (DEA) model is extensively used to estimate efficiency, but no study has determined the DEA that delivers most precise estimates. To address this issue, we advance Monte Carlo simulation-based generation process proposed by Kohl and Brunner (2020). developed generates an artificial dataset using Translog production function (instead of commonly Cobb Douglas) constr...

Systems that depend on matching often exhibit scale economies, whereby increased participation leads to improved performance for all users. This paper examines the presence of such increasing returns in carpool matching. Data from Scoop, a carpooling app, is used demonstrate this phenomenon across various markets using regression. As number requests certain market rises, share proposed matches ...

Background and Objectives: The goal of current study is to evaluate the performance of hospitals and their departments. This manuscript aimed at estimation of the most productive scale size (MPSS), returns to scale (RTS), and benchmarking for inefficient hospitals and their departments. Methods: The radial and non-radial data envelopment analysis (DEA) ap...

I propose a new measure of common, time-varying tail risk for large cross sections of stock returns. Stock return tails are described by a power law in which the power law exponent is allowed to transition smoothly through time as a function of recent data. It is motivated by asset pricing theory and is estimable via quasi-maximum likelihood. Estimates indicate substantial time variation in sto...

Optimal firm size and patterns of returns to scale among the local exchange companies in the U.S. telecommunications industry are estimated for the years: 1975, 1978, 1981, 1984, 1987 and 1990. The independent companies display increasing returns to scale, while the Baby Bells display constant or decreasing returns to scale. The independent companies operate at a scale smaller than optimal size...