We develop a theory linking “misallocation,” i.e., dispersion in marginal products of capital (MPK), to macroeconomic risk. Dispersion MPK depends on (i) heterogeneity firm-level risk and (ii) the magnitude premia. Stock market-based measures imply that considerations explain about 25% among US firms rationalize large persistent component MPK, consistent with micro-level data. Time-varying prem...

Covariate-adjusted regression was recently proposed for situations where both predictors and response in a regression model are not directly observed, but are observed after being contaminated by unknown functions of a common observable covariate. The method has been appealing because of its flexibility in targeting the regression coefficients under different forms of distortion. We extend this...

Two frequently used parametric statistics of person-fit with the dichotomous Rasch model (RM) are adjusted and compared to each other and to their original counterparts in terms of power to detect aberrant response patterns in short tests (10, 20, and 30 items). Specifically, the cube root transformation of the mean square for the unweighted person-fit statistic, t, and the standardized likelih...

We propose and axiomatize probability adjusted rank-discounted critical-level generalized utilitarianism (PARDCLU). We thus generalize rank-discounted utilitarianism (RDU) to variable population and uncertainty and thereby take important steps towards preparing RDU for practical use, e.g. for evaluation of climate policies and other policy issues with long-run consequences. We illustrate how PA...

A simple adjustment to parametric failure-time distributions, which allows for much greater flexibility in the shape of the hazard-rate function, is considered. Closed-form expressions for the distributions of the power-law adjusted Weibull, gamma, log-gamma, generalized gamma, lognormal and Pareto distributions are given. Most of these allow for bathtub shaped and other multi-modal forms of th...

We propose covariate adjustment methodology for a situation where one wishes to study the dependency of a generalized response on predictors while both predictors and response are distorted by an observable covariate. The distorting covariate is thought of as a size measurement that affects predictors in a multiplicative fashion. The generalized response is modeled by means of a random threshol...

We investigate the possible bias due to an erroneous missing at random assumption if adjusted odds ratios are estimated from incomplete covariate data using the maximum likelihood principle. A relation between complete case estimates and maximum likelihood estimates allows us to identify situations where the bias vanishes. Numerical computations demonstrate that the bias is most serious if the ...

Ascertainment-adjusted parameter estimates from a genetic analysis are typically assumed to reflect the parameter values in the original population from which the ascertained data were collected. Burton et al. (2000) recently showed that, given unmodeled parameter heterogeneity, the standard ascertainment adjustment leads to biased parameter estimates of the population-based values. This findin...