Policy makers view public sector-sponsored employment and training programs and other active labor market policies as tools for integrating the unemployed and economically disadvantaged into the work force. Few public sector programs have received such intensive scrutiny, and been subjected to so many different evaluation strategies. This chapter examines the impacts of active labor market policies, such as job training, job search assistance, and job subsidies, and the methods used to evaluate their effectiveness. Previous evaluations of policies in OECD countries indicate that these programs usually have at best a modest impact on participants’ labor market prospects. But at the same time, they also indicate that there is considerable heterogeneity in the impact of these programs. For some groups, a compelling case can be made that these policies generate high rates of return, while for other groups these policies have had no impact and may have been harmful. Our discussion of the methods used to evaluate these policies has more general interest. We believe that the same issues arise generally in the social sciences and are no easier to address elsewhere. As a result, a major focus of this chapter is on the methodological lessons learned from evaluating these programs. One of the most important of these lessons is that there is no inherent method of choice for conducting program evaluations. The choice between experimental and non-experimental methods or among alternative econometric estimators should be guided by the underlying economic models, the available data, and the questions being addressed. Too much emphasis has been placed on formulating alternative econometric methods for correcting for selection bias and too little given to the quality of the underlying data. Although it is expensive, obtaining better data is the only way to solve the evaluation problem in a convincing way. However, better data are not synonymous with social experiments. © 1999 Elsevier Science B.V. All rights reserved.

The Economics and Econometrics of Active Labor Market Programs

As digital platforms are transforming almost every industry today, they are slowly finding their way into the mainstream information systems (ISs) literature. Digital platforms are a challenging research object because of their distributed nature and intertwinement with institutions, markets and technologies. New research challenges arise as a result of the exponentially growing scale of platform innovation, the increasing complexity of platform architectures and the spread of digital platforms to many different industries. This paper develops a research agenda for digital platforms research in IS. We recommend researchers seek to (1) advance conceptual clarity by providing clear definitions that specify the unit of analysis, degree of digitality and the sociotechnical nature of digital platforms; (2) define the proper scoping of digital platform concepts by studying platforms on different architectural levels and in different industry settings; and (3) advance methodological rigour by employing embedded case studies, longitudinal studies, design research, data-driven modelling and visualisation techniques. Considering current developments in the business domain, we suggest six questions for further research: (1) Are platforms here to stay? (2) How should platforms be designed? (3) How do digital platforms transform industries? (4) How can data-driven approaches inform digital platforms research? (5) How should researchers develop theory for digital platforms? and (6) How do digital platforms affect everyday life?

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The digital platform: a research agenda

With a global market share of about 90%, crystalline silicon is by far the most important photovoltaic technology today. This article reviews the dynamic field of crystalline silicon photovoltaics from a device-engineering perspective. First, it discusses key factors responsible for the success of the classic dopant-diffused silicon homojunction solar cell. Next it analyzes two archetypal high-efficiency device architectures – the interdigitated back-contact silicon cell and the silicon heterojunction cell – both of which have demonstrated power conversion efficiencies greater than 25%. Last, it gives an up-to-date summary of promising recent pathways for further efficiency improvements and cost reduction employing novel carrier-selective passivating contact schemes, as well as tandem multi-junction architectures, in particular those that combine silicon absorbers with organic–inorganic perovskite materials.

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High-efficiency crystalline silicon solar cells: status and perspectives

Public policies, pressure groups, and dead weight costs

This paper presents an exploratory analysis of the emergent reporting practices used by social entrepreneurs in terms of their institutional settings and strategic objectives. These reporting practices not only account for financial performance but also disclose more nuanced and contingent social and environmental impacts and outcomes. Furthermore, they act as symbolic objects expressing the market orientation of many socially entrepreneurial organizations in that they aim to provide more complete and transparent disclosure of a variety of performance impacts. Conceptually, this paper draws upon approaches developed within the sociology of accounting as institutional practice and uses three theoretical interpretations to conceptualize the function and effects of reporting, disclosure, and audit in social entrepreneurship: positivist; critical theorist; and interpretative. A discussion of five case studies leads to the development of a new theoretical construct - 'Blended Value Accounting' - that constitutes a spectrum of disclosure logics used by social entrepreneurs to access resources and realize organizational mission objectives with key stakeholders. Conclusions consider some further questions around socially entrepreneurial reporting practices and strategies and suggest some new lines of research going forward.

'We do good things, don't we?': 'Blended Value Accounting' in social entrepreneurship

The compensating variation was defined by J. R. Hicks (1942) as the amount one would have to deduct from a person's income to make him just as well off after a change in prices and income as he had been in the initial situation. If the compensating variation is positive, the individual is better off under the new situation. Since the compensating variation furnishes a uniquely defined numerical (cardinal) indicator of welfare improvement, it provides an implicit ranking of alternative prospective situations not only relative to the initial situation, but also relative to each other. In practice this appears to be how this and other tools of cost-benefit analysis are actually used: one is interested in knowing not only whether a particular bridge, or a particular excise tax, will lead to an improvement in welfare, but which out of a set of alternative bridges or alternative tax systems will improve welfare the most.1 In this paper we analyze conditions under which the compensating variation can be validly used in this generalized sense; these turn out to be precisely the same as conditions previously derived (see our 1976 paper) for the valid use of consumer' s surplus as a welfare measure. In our final section we analyze the problem of deriving the generalized equivalent and compensating variations (either exactly or approximately) from observable demand functions, by means of generalizations of, or alternatives to, consumer's surplus.

Compensating Variation, Consumer's Surplus, and Welfare

The new welfare economics 1939-1974*

While most real-life decisions are of necessity made with less than perfect information, there is usually some opportunity to acquire additional information regarding the problem at hand before a final decision is made. It is, of course, the recognition of this fact which has led to the importance now attached to the field of Decision Support Systems. On the other hand, the formal analysis of the sort of decision problem for which Decision Support Systems can be useful appears to have lagged behind the developments in applications. In this paper we develop a model of decision-making in which there is available a variety of informational sources (experiments) which can reduce (though generally not eliminate) the uncertainty associated with the final decisions. Since the informational sources are available only at some cost (either monetarily or in terms of time, or both), the decision-maker must solve two conceptually distinct problems: (1) developing an optimal information-gathering strategy, and (2) developing an optimal final decision strategy, conditional upon the information obtained during the information-gathering process. A theoretical framework is developed here for the analysis of this general problem, and fairly complete solutions are obtained for some interesting special cases; most notably the computer file search problem.

A model of decision-making with sequential information-acquisition (part 1)

While most real-life decision are of necessity made with less than perfect information, there is usually some opportunity to acquire additional information regarding the problem at hand before a final decision is made. It is, of course, the recognition of this fact which has led to the importance now attached to the field of Decision Support Systems. On the other hand, the formal analysis of the sort of decision problem for which Decision Support Systems can be useful appears to have lagged behind the developments in applications. In this paper we develope a model of decision-making in which there is available a variety of informational sources (experiments) which can reduce (though generally not eliminate) the uncertainty associated with the final decision. Since the informational sources are available only at some cost (either monetarily or in terms of time, or both), the decision-maker must solve two conceptually distinct problems: (1) developing an optimal information-gathering strategy, and (2) developing an optimal final decision strategy, conditional upon the information obtained during the information-gathering process. A theoretical framework is developed here for the analysis of this general problem, and fairly complete solutions are obtained for some interesting special cases; most notably the computer file search problem.

James C. Moore

Papers

Compensating Variation, Consumer's Surplus, and Welfare

The new welfare economics 1939-1974*

A model of decision-making with sequential information-acquisition (part 1)

A model of decision-making with sequential information-acquisition (part 2)

Social utility and the gains from trade