Provides a comprehensive approach to productivity and efficiency analysis using economic and econometric theory.

Measuring Economic Growth and Productivity: Foundations, KLEMS Production Models, and Extensions presents new insights into the causes, mechanisms and results of growth in national and regional accounts. It demonstrates the versatility and usefulness of the KLEMS databases, which generate internationally comparable industry-level data on outputs, inputs and productivity. By rethinking economic development beyond existing measurements, the book's contributors align the measurement of growth and productivity to contemporary global challenges, addressing the need for measurements as well as the Gross Domestic Product. All contributors in this foundational volume are recognized experts in their fields, all inspired by the path-breaking research of Dale W. Jorgenson. Demonstrates how an approach based on sources of economic growth (KLEMS – capital, labor, energy, materials and services) can be used to analyze economic growth and productivity Includes examples covering the G7, E7, EU, Latin America, Norway, China, Taiwan, Japan, Korea, India and other South Asian countries Examines the effects of digital, information, communication and integrated technologies on national and regional economies

How do the benefits of higher education compare with its costs, and how does this comparison vary across individuals and institutions? These questions are fundamental to quantifying the productivity of the education sector. The studies in Productivity in Higher Education use rich and novel administrative data, modern econometric methods, and careful institutional analysis to explore productivity issues. The authors examine the returns to undergraduate education, differences in costs by major, the productivity of for-profit schools, the productivity of various types of faculty and of outcomes, the effects of online education on the higher education market, and the ways in which the productivity of different institutions responds to market forces. The analyses recognize five key challenges to assessing productivity in higher education: the potential for multiple student outcomes in terms of skills, earnings, invention, and employment; the fact that colleges and universities are “multiproduct” firms that conduct varied activities across many domains; the fact that students select which school to attend based in part on their aptitude; the difficulty of attributing outcomes to individual institutions when students attend more than one; and the possibility that some of the benefits of higher education may arise from the system as a whole rather than from a single institution. The findings and the approaches illustrated can facilitate decision-making processes in higher education.

Get the most out of this foundational reference and improve the productivity of your software teams. This open access book collects the wisdom of the 2017 "Dagstuhl" seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity. The results of their work, Rethinking Productivity in Software Engineering, includes chapters covering definitions and core concepts related to productivity, guidelines for measuring productivity in specific contexts, best practices and pitfalls, and theories and open questions on productivity. You'll benefit from the many short chapters, each offering a focused discussion on one aspect of productivity in software engineering. Readers in many fields and industries will benefit from their collected work. Developers wanting to improve their personal productivity, will learn effective strategies for overcoming common issues that interfere with progress. Organizations thinking about building internal programs for measuring productivity of programmers and teams will learn best practices from industry and researchers in measuring productivity. And researchers can leverage the conceptual frameworks and rich body of literature in the book to effectively pursue new research directions. What You'll LearnReview the definitions and dimensions of software productivity See how time management is having the opposite of the intended effect Develop valuable dashboards Understand the impact of sensors on productivity Avoid software development waste Work with human-centered methods to measure productivity Look at the intersection of neuroscience and productivity Manage interruptions and context-switching Who Book Is For Industry developers and those responsible for seminar-style courses that include a segment on software developer productivity. Chapters are written for a generalist audience, without excessive use of technical terminology.

This manual presents the theoretical foundations to productivity measurement, and discusses implementation and measurement issues.

Survey and 5 case studies on the measurement of productivity in the federal public services of USA. Research methods.

This book develops the theory of productivity measurement using the empirical index number approach. The theory uses multiplicative indices and additive indicators as measurement tools, instead of relying on the usual neo-classical assumptions, such as the existence of a production function characterized by constant returns to scale, optimizing behavior of the economic agents, and perfect foresight. The theory can be applied to all the common levels of aggregation (micro, meso, and macro), and half of the book is devoted to accounting for the links existing between the various levels. Basic insights from National Accounts are thereby used. The final chapter is devoted to the decomposition of productivity change into the contributions of efficiency change, technological change, scale effects, and input or output mix effects. Applications on real-life data demonstrate the empirical feasibility of the theory. The book is directed to a variety of overlapping audiences: statisticians involved in measuring productivity change; economists interested in growth accounting; researchers relating macro-economic productivity change to its industrial sources; enterprise micro-data researchers; and business analysts interested in performance measurement.