Search results

The first Research in Labor Economics (RLE) volume was published in 1977. Its founding editor, Ronald Ehrenberg, saw the need for high quality substantive research papers in the labor/human resource area. Each volume was to contain “original contributions comparable (or exceeding) those found in leading journals.” The articles were of three genres: (1) results from ongoing or completed important research endeavors, (2) critical survey articles, and (3) symposia on policy related topics (RLE, Vol. 1, p. vii). In 1995, Solomon Polachek took over as series editor. Beginning in 2007 RLE affiliated with the Institute for the Study of Labor (IZA), an international network of about 1,100 labor economists spanning more than 40 countries. Konstantinos Tatsiramos became the IZA coeditor in 2008 after taking over from Olivier Bargain. Finally in 2011 RLE established an editorial board consisting of Orley C. Ashenfelter, Francine D. Blau, Richard Blundell, David Card, Ronald G. Ehrenberg, Richard B. Freeman, Daniel S. Hamermesh, James J. Heckman, Alan B. Krueger, Edward P. Lazear, Christopher A. Pissarides, and Klaus F. Zimmermann. Two are Nobel Laureates and all are top labor economists.

Around the world, people are confronted by a variety of complex and pervasive environmental, social and economic challenges. In many cases, including anthropogenic climate change, resource depletion, financial system disruption and poverty, there has been an increasing recognition that ‘wicked problems’ require entirely new ways of thinking, and that the solutions are unlikely to be found by governments, businesses or civil society actors operating in isolation. In parallel with these developments, many observers have commented on a growing interest in various forms of social entrepreneurship and in new models of enterprise that seek alternative ways of delivering products and services, while also securing the ‘triple bottom line’ of social, environmental and economic sustainability. This volume draws together a selection of contemporary entrepreneurship research studies that explore different aspects of this phenomenon. Our original call for papers was based around the themes addressed in one of ISBE's longstanding annual conference tracks. It attracted some strong submissions from within and beyond the ISBE research community. The editors reviewed papers relating to social and sustainable entrepreneurship, the environmental impacts of enterprise, and ethics and social responsibility in enterprise.

Sarah Underwood is the Director of Student Education for Enterprise and a Lecturer in Enterprise at the Leeds Enterprise Centre, University of Leeds, UK. Her research interests cover social enterprise and social innovation, with particular focus on the pedagogical development and inclusion of these topics in HEI curricula. Sarah has published several academic papers and was the founding Chair of the Institute for Small Business and Enterprise special interest group, the ‘Social and Sustainable Enterprise Network’ 2010–2012.

The field of entrepreneurship is continuously expanding, and new perspectives on existing theories continue to emerge, challenging established norms and generating exciting avenues of inquiry. The aim of the ISBE-Emerald Book Series is to facilitate such inquiry by providing a platform for leading edge research that reflects the themes of interest to contemporary entrepreneurship scholars. Each volume in the series is designed around a specific theme that is both relevant to the ISBE Conference and of importance to the entrepreneurship and small business community. While volumes will seek to explore and develop theory and practice in the field of entrepreneurship and small business, the emphasis of the research will be on quality, currency and relevance.

This chapter reviews developments to improve on the poor performance of the standard GMM estimator for highly autoregressive panel series. It considers the use of the ‘system’ GMM estimator that relies on relatively mild restrictions on the initial condition process. This system GMM estimator encompasses the GMM estimator based on the non-linear moment conditions available in the dynamic error components model and has substantial asymptotic efficiency gains. Simulations, that include weakly exogenous covariates, find large finite sample biases and very low precision for the standard first differenced estimator. The use of the system GMM estimator not only greatly improves the precision but also greatly reduces the finite sample bias. An application to panel production function data for the U.S. is provided and confirms these theoretical and experimental findings.