Personnel Economics

Download or read book Personnel Economics written by Peter Kuhn and published by Oxford University Press, USA. This book was released on 2017-11-21 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: The vast majority of economics majors enter the world of work directly after graduation. Unique among the subfields of economics, only personnel economics looks inside the workplace to apply simple economic theory and precise, transparent empirical research to the central issues of employeeselection, motivation and compensation. Students love this subject because it applies basic microeconomic tools to their working lives in a concrete and useful way. Peter Kuhn's conversational and up-to-date treatment of experiments and research about employment issues in Personnel Economics -incorporating the latest findings from behavioral economic research - provides an enormously interesting, instructive, and much needed textbook on these topics.Personnel Economics functions equally well as a stand-alone personnel textbook, or as supplementary material for courses in labor economics, behavioral economics, experimental economics or game theory. Although the book uses some simple economics tools, the author keeps the technical aspects to theminimum level consistent with understanding the key ideas. Aside from thinking graphically about maximizing utility or profits in the presence of a budget set (all of which are all introduced in the book), the only math a student needs is to find the maximum of a function of a single variable.Calculus is offered as an option, but there are other, easy ways to solve the same problems. All of the mathematics are administered with plenty of hand-holding, and optional problem sets - many of which use spreadsheets to provide intuition for the main results - are available to help cement theintuition. On the empirical side, the book includes an intuitive introduction to the two work-horses of empirical research on personnel issues: designing experiments and using regression to study naturally-occurring data.