Roger Koenker

Bruce D. Smith

Mark Huggett

Joseph T. Mahoney

Chung-Ming Kuan

Stephen P. D'Arcy

Chamu Sundaramurthy

Chao-Shin Liu

George Edward Monahan

Gillian Yeo Hian Heng

Herbert L. Baer

Joseph Francis Allen Porac

Luis C. Nunes

Miles B. Gietzmann

Rhonda K. Reger

Timothy L. Smunt

The Relevance of Opportunity Costs in the Management of Congested Stochastic Production Systems

Absorption Versus Direct Costing

Hans Brems

Japan's East Asia Market, 1870-1940

The Dynamics of the Intra-Asian Market Economy and Japanese Industrialization

James A. Gentry

Bhaskar Chakravorti

Kent G. Becker

Stefan Krasa

David M. Gardner

Case Sprenkle

George E. Monahan

H. Peter Holzer

Hei Wai Lee

Richard Arnould

Riyaz Sikora

Halbert White

A Cash Flow Components Approach

An Empirical Study of the Corporate Choice Among Equity, Convertible Bonds and Straight Debt

Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. The author has devoted more than 25 years of research to this topic. The methods in the analysis are illustrated with a variety of applications from economics, biology, ecology and finance. The treatment will find its core audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above.

Quantile Regression

Roger Koenker

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