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In twenty-three original essays this book reviews the course of labor economics over the more than two centuries since the publication of Adam Smith's Wealth of Nations. It fully examines the contending theories, changing environmental contexts, evolving issues, and varied policies affecting labor's participation in the economy. While the intellectual framework of the book looks partly to the past--explaining the labor factor in classical and neoclassical systems--its emphasis is on contemporary problems that will figure prominently in future developments, such as the operation of internal labor markets, dispute resolution, concession bargaining, equal employment opportunity, and individual labor contracting.
Access to relevant external knowledge is crucial for a firms' competitiveness in innovation-driven industries. This thesis focuses on how different forms of proximity affect a firm's ability to access such knowledge. We consider the influence of being co-located in space, of being embedded in a network, and of being active in similar knowledge domains. By integrating these three proximity perspectives, we contribute to various disciplines such as economic geography, organizational sociology and innovation studies. Further, we investigate the make, buy or ally strategies that pharmaceutical firms employ to maximize the probability of innovation (finding new drugs). Our findings suggest that firms employ multiple governance structures simultaneously, even when targeting similar innovations. These insights contribute to our understanding of the boundaries of the firm.
Believing in a single model may be dangerous, and addressing model uncertainty by averaging different models in making forecasts may be very beneficial. In this thesis we focus on forecasting financial time series using model averaging schemes as a way to produce optimal forecasts. We derive and discuss in simulation exercises and empirical applications model averaging techniques that can reproduce stylized facts of financial time series, such as low predictability and time-varying patterns. We emphasize that model averaging is not a "magic" methodology which solves a priori problems of poorly forecasting. Averaging techniques have an essential requirement: individual models have to fit data. In the first section we provide a general outline of the thesis and its contributions to previ ous research. In Chapter 2 we focus on the use of time varying model weight combinations. In Chapter 3, we extend the analysis in the previous chapter to a new Bayesian averaging scheme that models structural instability carefully. In Chapter 4 we focus on forecasting the term structure of U.S. interest rates. In Chapter 5 we attempt to shed more light on forecasting performance of stochastic day-ahead price models. We examine six stochastic price models to forecast day-ahead prices of the two most active power exchanges in the world: the Nordic Power Exchange and the Amsterdam Power Exchange. Three of these forecasting models include weather forecasts. To sum up, the research finds an increase of forecasting power of financial time series when parameter uncertainty, model uncertainty and optimal decision making are included.
In most decisions we have to choose between options that involve some uncertainty about their outcomes and their effect on our well-being. Casual observation and carefully controlled studies suggest that, in making these decisions, we often deviate from the benchmark of expected income maximization. This should not come as a surprise. Our well-being is affected by many factors, and the outside observer does not know the importance of various dimensions of the outcome to the decision maker. Even if goals are well defined, it is far from obvious that we succeed in choosing what is best for us. The psychological literature has shown deviations from optimal behavior in simple decision tasks, and we may expect similar deviations to occur in more complex real life problems. In real life situations, however, experience and market interaction will help to restrain suboptimal behavior. This thesis examines deviations from expected income maximization in situations involving uncertainty. We focus on deviations generated by social factors.
This publication is the first from the Leverhulme program of study, which focused on the major strategic options likely to be available to higher education institutions and policy-making bodies in the 1980s and 1990s. It resulted from a specialist seminar on higher education and the labor market. The chapters are: "Employers' Perceptions of Demand" (Laurence C. Hunter); "Technological Manpower" (Derek L. Bosworth); "Response to Change in the United States" (Richard B. Freeman); "Higher Education Policy" (Maurice Peston); and "The Challenge of Market Imperatives" (Robert M. Lindley). Lindley notes that the British higher education system has never come to grips with the role it might play in economic development and examines some areas of need and improvement: the search for more students; the need to get the labor market more involved in the environment of higher education and to get education to respond to market need with qualified persons; the role of higher education in the screening and credentialism process; to encourage industry's role in funding and organizing higher education; and stabilizing the labor market environment. It is concluded that labor market issues have to be handled at a more sophisticated level than the debate about manpower alone. (LC)
In the six years since the appearance of the first edition of Stephen Smith's book, labour economics has become a more firmly entrenched subject on the curriculum. Previously regarded as a subsection within industrial economics, there are now very few universities that do not devote a course to it in its own right. The focus of topics covered withi