According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

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Modern Applied Statistics With S

Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

http://d1c25a6gwz7q5e.cloudfront.net/papers/67.pdf

Efficiency of financial institutions: International survey and directions for future research

Estimation and inference in two-stage, semi-parametric models of production processes

Data envelopment analysis (DEA) and free disposal hull (FDH) estimators are widely used to estimate efficiencies of production units In applications, both efficiency scores for individual units as well as average efficiency scores are typically reported While several bootstrap methods have been developed for making inference about the efficiencies of individual units, until now no methods have existed for making inference about mean efficiency levels This paper shows that standard central limit theorems do not apply in the case of means of DEA or FDH efficiency scores due to the bias of the individual scores, which is of larger order than either the variance or covariances among individual scores The main difficulty comes from the fact that such statistics depend on efficiency estimators evaluated at random points Here, new central limit theorems are developed for means of DEA and FDH scores, and their efficacy for inference about mean efficiency levels is examined via Monte Carlo experiments

/pdf/when-bias-kills-the-variance-central-limit-theorems-for-dea-29b4qgyv4p.pdf

When Bias Kills the Variance: Central Limit Theorems for DEA and FDH Efficiency Scores

Annual data on U.S. hospitals from 1985–1988 are evaluated by ownership type—profit, nonprofit, state and local government, and U.S. Department of Veterans Affairs (VA)—for changes in hospital productivity over time. Distance functions are used to measure Malmquist indices of productivity change, which are then decomposed into indices of efficiency change and technology change. In contrast to previous studies using this approach, we allow for variable returns to scale and use both input and output orientations. We find that changes in technology dominate changes in inefficiency in determining changes in productivity.

Decomposing hospital productivity changes, 1985–1988: A nonparametric Malmquist approach

Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations

This article uses a new nonparametric, unconditional, hyperbolic order-αquantile estimator to construct a hyperbolic version of the Malmquist index. Unlike traditional nonparametric efficiency estimators, the new estimator is both robust to data outliers and has a root-n convergence rate. We use this estimator to examine changes in the efficiency and productivity of U.S. banks between 1985 and 2004. We find that larger banks experienced larger efficiency and productivity gains than small banks, consistent with the presumption that recent changes in regulation and information technology have favored larger banks.

/pdf/robust-nonparametric-quantile-estimation-of-efficiency-and-2e8cf86hoi.pdf

Paul W. Wilson

Papers

When Bias Kills the Variance: Central Limit Theorems for DEA and FDH Efficiency Scores

Decomposing hospital productivity changes, 1985–1988: A nonparametric Malmquist approach

Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations

Robust Nonparametric Quantile Estimation of Efficiency and Productivity Change in U.S. Commercial Banking, 1985–2004

Consolidation in US banking: Which banks engage in mergers?