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Available evidence taken from the experience of many countries strongly suggests that bad governments and institutions have been serious, if not the most serious, obstacle to economic growth; and all public sectors pursue a mix of both predatory and productive activities—bad governments emphasizing the former, and good governments finding a way of promoting the latter. Depending on your perspective, unfortunately or fortunately, participants in the public-sector policy process generally pay little attention to the advice and counsel of the economics profession. This, in part, is explained by the confusion that emerges from our profession over the role of the public sector. Some would have us believe that the government, or the public sector, is nothing more than a "clearing house" while still others advance frameworks that treat the public sector as a benign pursuer of the public interest.

Available evidence taken from the experience of many countries strongly suggests that bad governments and institutions have been serious, if not the most serious, obstacle to economic growth; and all public sectors pursue a mix of both predatory and productive activities—bad governments emphasizing the former, and good governments finding a way of promoting the latter. Depending on your perspective, unfortunately or fortunately, participants in the public-sector policy process generally pay little attention to the advice and counsel of the economics profession. This, in part, is explained by the confusion that emerges from our profession over the role of the public sector. Some would have us believe that the government, or the public sector, is nothing more than a "clearing house" while still others advance frameworks that treat the public sector as a benign pursuer of the public interest.

This paper is concerned with the "General Possibility Theorem" of Dr. K. J. Arrow. Since the theorem is certainly elegant and probably important, it is proper as well as convenient to refer to it from this point on as Arrow's theorem. The theorem deals with the problem of discovering a rule by which social preferences can be constructed from individual preferences. Such a rule, or social welfare function, gives a social ordering of alternatives of any kind for every possible arrangement of the corresponding individual orderings. Arrow's theorem declares that no social welfare function exists that satisfies those conditions that most of us would consider essential to a satisfactory rule. The outcome is something of a shock to preconceptions.In what follows two aspects of Arrow's theorem are considered. In the early part of the paper the theorem as such is examined. A brief and informal statement of Arrow's argument is followed by a formal statement of the conditions on which the argument depends. A proof of the theorem is offered that seems to be rather more naturally constructed than the original. A set of conditions is proposed (derived from Arrow's proof) that is weaker than the original set, that seems to be at least as plausible, and that leads to the same conclusion by a short and direct route. In the later part of the paper, methods of circumventing the theorem (there seems to be no way of removing it) are explored.

After‐tax income distributions in the UK for a period of 12 years have been used for estimating the coefficient of inequality‐aversion ε implicit in the income distributions, the change in ε during the period, as well as Atkinson's index of inequality corresponding to the different ε. The method used is non‐linear regression analysis.

ABSTRACTIn defining optimum population, economists have used two distinct concepts of the social welfare function: the Millian and the Benthamite. Although analytically the issue of the welfare impact of international migration is closely related to the concept of optimum population, the migration analysis has been based almost exclusively on the Benthamite welfare function. As its point of departure, the present note explores the implications of the alternative Millian welfare function for migration analysis.An interesting aspect of the results derived from the present exercise is that they are in sharp contradiction with the results based on the Benthamite social welfare function. This highlights the sensitivity of the results to the welfare criteria used and the need for greater caution in policy formulation.

Nanak Kakwani and Hyu Hwa Son make use of social welfare functions to derive indicators of development relevant to specific social objectives, such as poverty- and inequality-reduction. Arguing that the measurement of development cannot be value-free, the authors assert that if indicators of development are to have policy relevance, they must be assessed on the basis of the social objectives in question. This study develops indicators that are sensitive to both the level and the distribution of individuals' capabilities. The idea of the social welfare function, defined in income space, is extended to the concept of the social well-being function, defined in capability space. Through empirical analysis from selected developing countries, with a particular focus on Brazil, the authors shape techniques appropriate to the analysis of development in different dimensions. The focus of this evidence-based policy analysis is to evaluate alternative policies affecting the capacities of people to enjoy a better life.

Abstract
The social welfare function (SWF) framework converts the possible outcomes of governmental policy choice into vectors (lists) of interpersonally comparable well-being numbers, measuring the lifetime well-being of each individual in the population of interest. The SWF proper is a rule for ranking these vectors. The utilitarian SWF adds up well-being numbers. A prioritarian SWF adds up well-being numbers plugged into a strictly increasing and strictly concave transformation function. Governmental policies are conceptualized as probability distributions over well-being vectors. A recent literature applies the SWF framework to health policy. This article first provides a brief overview of the SWF framework and then reviews some of the key concepts and findings that have emerged from this literature. One such concept is the "social value of risk reduction" (SVRR): the marginal social value (as calculated by the SWF) per unit of reduction in fatality risk for a given individual. The SVRR is the analogue, within the SWF framework, to the value-of-statistical-life (VSL) concept within benefit–cost analysis. This article explicates the SVRR concept and reports on recent theoretical findings and simulations that illustrate the properties of utilitarian and prioritarian SVRRs and their differences from VSL.