London School of Economics and Political Science

About: London School of Economics and Political Science is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Politics. The organization has 8759 authors who have published 35017 publications receiving 1436302 citations.

An Introduction to the Wage Curve

Abstract: En conomists and policymakers are interested in understanding the forces that determine the level of unemployment and the level of wages. This paper describes an empirical discovery-made with the help of international microeconometric evidence covering more than a dozen nations-about a link between these two variables. The connection can be portrayed on a graph with the level of unemployment on the horizontal axis and the level of wages on the vertical axis. Then the "wage curve," as shown in Figure 1, is a downwardsloping locus. This relationship tells us that (holding others things constant) if a region has a rise in unemployment in a particular year, those who live there will have a fall in their wages in that year. What does this curve mean? How, in a field where fully controlled experiments are almost impossible, could there be any convincing scientific basis for this wage curve? What is the relationship between the wage curve and a Phillips curve, other than that the curve of Figure 1 looks like a Phillips curve with the vertical axis mislabeled? How does the wage curve fit into existing economic knowledge, and is the empirical finding consistent with competitive theory? This paper sketches answers to these kinds of questions. The discussion draws on our book, The Wage Curve (Blanchflower and Oswald, 1994), where the points raised here are investigated more fully. It also rests upon work done by other economists whose work is listed in the paper and the bibliography.

Price Stability in Open Economies

Abstract: This paper studies the conditions under which price stability is the optimal policy in a two-country open-economy model with imperfect competition and price stickiness. Special conditions on the levels of country-specific distortionary taxation and the intratemporal and intertemporal elasticities of substitution need to be satisfied. These restrictions apply to both cooperative and non-cooperative settings. Most importantly, we show that cooperative and non-cooperative solutions do not coincide despite market completeness and producer currency pricing. In this framework, our analysis suggests a role for international policy coordination.

Confidence, uncertainty and decision-support relevance in climate predictions.

Abstract: Over the last 20 years, climate models have been developed to an impressive level of complexity. They are core tools in the study of the interactions of many climatic processes and justifiably provide an additional strand in the argument that anthropogenic climate change is a critical global problem. Over a similar period, there has been growing interest in the interpretation and probabilistic analysis of the output of computer models; particularly, models of natural systems. The results of these areas of research are being sought and utilized in the development of policy, in other academic disciplines, and more generally in societal decision making. Here, our focus is solely on complex climate models as predictive tools on decadal and longer time scales. We argue for a reassessment of the role of such models when used for this purpose and a reconsideration of strategies for model development and experimental design. Building on more generic work, we categorize sources of uncertainty as they relate to this specific problem and discuss experimental strategies available for their quantification. Complex climate models, as predictive tools for many variables and scales, cannot be meaningfully calibrated because they are simulating a never before experienced state of the system; the problem is one of extrapolation. It is therefore inappropriate to apply any of the currently available generic techniques which utilize observations to calibrate or weight models to produce forecast probabilities for the real world. To do so is misleading to the users of climate science in wider society. In this context, we discuss where we derive confidence in climate forecasts and present some concepts to aid discussion and communicate the state-of-the-art. Effective communication of the underlying assumptions and sources of forecast uncertainty is critical in the interaction between climate science, the impacts communities and society in general.

The significance of context in information systems and organizational change

Abstract: . This paper argues that it is of crucial importance that information systems (IS) research and practice associates technology innovation with the context within which it is embedded. It identifies three principles to be followed in order to address the contextual processes involved in IS implementation: first, technology innovation should be considered in relation to socio-organizational change; second, analysis should consider not only the local organizational, but also the national and international context; and third, analysis should consider both the technical/rational decisions and actions involved in the innovation process and the cultural, social and cognitive forces of such a process. These principles are demonstrated with the analysis of a case study of organizational reform in Cyprus.

Dynamic Mean-Variance Asset Allocation

Abstract: Mean-variance criteria remain prevalent in multi-period problems, and yet not much is known about their dynamically optimal policies. We provide a fully analytical characterization of the optimal dynamic mean-variance portfolios within a general incomplete-market economy, and recover a simple structure that also inherits several conventional properties of static models. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates much tractability in the explicit computation of portfolios. We solve the problem by explicitly recognizing the time-inconsistency of the mean-variance criterion and deriving a recursive representation for it, which makes dynamic programming applicable. We further show that our time-consistent solution is generically different from the pre-commitment solutions in the extant literature, which maximize the mean-variance criterion at an initial date and which the investor commits to follow despite incentives to deviate. We illustrate the usefulness of our analysis by explicitly computing dynamic mean-variance portfolios under various stochastic investment opportunities in a straightforward way, which does not involve solving a Hamilton-Jacobi-Bellman differential equation. A calibration exercise shows that the mean-variance hedging demands may comprise a significant fraction of the investor's total risky asset demand.