QUALITY MANAGEMENT: UNIVERSAL OR CONTEXT DEPENDENT?

Quality management has often been advocated as being universally applicable to organizations. This is in contrast with the manufacturing strategy contingency approach of Operations Management that advocates internal and external consistency between manufacturing strategy choices. This article empirically investigates whether quality management practices are contingent on a plant's manufacturing strategy context, by examining the use of process quality management practices—a critical and distinctive subset of the whole set of quality management practices—across plants representative of different manufacturing strategy contexts. The study strongly suggests that process quality management practices are contingent on a plant's manufacturing strategy, and identifies mechanisms by which this takes place.     

CAN WE INFER HOSPITAL QUALITY FROM MEDICAL GRADUATES’ RESIDENCY CHOICES?

This paper uses a novel approach to infer hospital technical quality from revealed preferences over residency programs. Specifically, we use Spanish medical graduates’ residency choices made from 1995 to 2000. We start by estimating a model of medical graduates preferences that controls for hospital, proximity, specialty, and gender effects. We interpret the coefficients on the hospital dummy variables as measures of medical graduates’ preferences over hospitals. Our results show that graduates do indeed discriminate between hospitals and that their preferences correlate with hospital‐specific covariates arguably related to hospital training quality. We then show that preferences from medical graduates are positively and statistically significantly correlated with risk‐adjusted hospital rankings based on five alternative outcome measures. Finally, we construct reputation scores for each hospital using news story counts in three media outlets and find that medical graduates’ preferences are especially valuable for inference of hospital technical quality of care as they do not simply reflect well known reputation.     

HUMAN CAPITAL IN GROWTH REGRESSIONS: HOW MUCH DIFFERENCE DOES DATA QUALITY MAKE?

We construct estimates of educational attainment for a sample of 21 OECD countries. Our series incorporate previously unexploited information and remove sharp breaks in the data that can only reflect changes in classification criteria. We then construct indicators of the information content of our estimates and a number of previously available data sets and examine their performance in several growth specifications. We find a clear positive correlation between data quality and the size and significance of human capital coefficients in growth regressions. Using an extension of the classical errors in variables model to correct for measurement error bias, we construct a set of meta‐estimates of the coefficient of years of schooling in an aggregate Cobb‐Douglas production function. Our results suggest that the value of this parameter is likely to be above 0.60. (JEL: O40, I20, O30, C19)