Theoretical and research considerations of burnout

As in any new area of investigation, the study of the phenomenon of burnout contains much potential benefit, especially to workers in helping/service professions; and it contains sources of error which may delay or distort understandings that are sorely needed. This paper identifies and explains many pitfalls and sources of error in developing theory and research about burnout. After discussing the limitations of the current definitions of burnout, the authors explore the ramifications of the most well supported definition. Specific suggestions are made for further investigation, especially in the area of individual characteristics and their interaction with the burnout phenomenon. Finally, methodologies most likely to yield solid, usable information for practitioners are discussed.     

Interest rate policies and inflation in interdependent economies: Recent policy dilemmas

This paper examines Federal Reserve Board policies that are premised on a negative short-run association of interest rate movements and the rate of inflation. In particular, econometric evidence is provided, supporting the view that tighter monetary policy appears to raise inflation rates in the short run. Conversely, it is demonstrated that easier monetary policy does not necessarily raise inflation rates in the short run. In the case of uncoordinated monetary restrictiveness, interest rate competition among major countries can produce higher inflation and lower growth than was originally intended.     

A Recursive Formula for the Probability of Occurrence of at Least m out of N Events

A recursive same-sign relation is derived that reduces the probability of occurrence of at least m out of N independent events to the probability of occurrence of at least m out of N ? 1 of these N events.     

Robust location estimation with missing data

In a missing data setting, we have a sample in which a vector of explanatory variables ${\bf x}_i$ is observed for every subject i, while scalar responses $y_i$ are missing by happenstance on some individuals. In this work we propose robust estimators of the distribution of the responses assuming missing at random (MAR) data, under a semiparametric regression model. Our approach allows the consistent estimation of any weakly continuous functional of the response's distribution. In particular, strongly consistent estimators of any continuous location functional, such as the median, L‐functionals and M‐functionals, are proposed. A robust fit for the regression model combined with the robust properties of the location functional gives rise to a robust recipe for estimating the location parameter. Robustness is quantified through the breakdown point of the proposed procedure. The asymptotic distribution of the location estimators is also derived. The proofs of the theorems are presented in Supplementary Material available online. The Canadian Journal of Statistics 41: 111–132; 2013 © 2012 Statistical Society of Canada     

Path dependent societal transformation: Stratification in hybrid mixed economies

Theory and Society -     

Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models

This paper proposes a new nested algorithm (NPL) for the estimation of a class of discrete Markov decision models and studies its statistical and computational properties. Our method is based on a representation of the solution of the dynamic programming problem in the space of conditional choice probabilities. When the NPL algorithm is initialized with consistent nonparametric estimates of conditional choice probabilities, successive iterations return a sequence of estimators of the structural parameters which we call K–stage policy iteration estimators. We show that the sequence includes as extreme cases a Hotz–Miller estimator (for K=1) and Rust's nested fixed point estimator (in the limit when K→∞). Furthermore, the asymptotic distribution of all the estimators in the sequence is the same and equal to that of the maximum likelihood estimator. We illustrate the performance of our method with several examples based on Rust's bus replacement model. Monte Carlo experiments reveal a trade–off between finite sample precision and computational cost in the sequence of policy iteration estimators.