Data Envelopment Analysis of different climate policy scenarios

Recent developments in the political, scientific and economic debate on climate change suggest that it is of critical importance to develop new approaches able to compare policy scenarios for their environmental effectiveness, their distributive effects, their enforceability, their costs and many other dimensions. This paper discusses a quantitative methodology to assess the relative performance of different climate policy scenarios when accounting for their long-term economic, social and environmental impacts. The proposed procedure is based on Data Envelopment Analysis, here employed in evaluating the relative efficiency of eleven global climate policy scenarios. The methodology provides a promising comparison framework; it can be seen as a way of setting some basic guidelines to frame further debates and negotiations and can be flexibly adopted and modified by decision makers to obtain relevant information for policy design. Three major findings emerge from this analysis: (i) stringent climate policies can outperform less ambitious proposals if all sustainability dimensions are taken into account; (ii) a carefully chosen burden-sharing rule is able to bring together climate stabilisation and equity considerations; and (iii) the most inefficient strategy results from the failure to negotiate a post-2012 global climate agreement.     

The Model of a Gender-Segregated Low-Income Economy Reconsidered: Evidence from Uganda

This paper examines Darity's model of gender-segregated low-income agrarian society in light of evidence from Uganda. It identifies three important features of the interactions between men and women which are likely to have economic effects but which are subsumed within Darity's schematic presentation. It suggests a reformulation of the Darity model in terms of a bargaining framework. This facilitates greater insights into gendered economic processes that otherwise are ignored, and investigation of a wider range of macro outcomes.     

Getting Shut Out of the International Capital Markets: It Doesn't Take Much*

We use a simple model of international lending to show that an emerging market borrower who might default can be shut out of international capital markets without warning. A modest haircut on obligations, for example, can shut down lending.     

Are property rights enough?Re‐evaluating a big‐bang claim1

We investigate the claim made by proponents of the big‐bang strategy that the establishment of property rights in an economy in transition creates its own demand for the enforcement of laws to protect those rights. Our model contains a government engaging in activities to accomplish objectives that depend on public support for the enforcement of the rule of law and agents who interpret the level of activities of the government as indications of the government's intent to enforce the rule of law. Agents, using the level of government activities as an input to their decisions, choose whether to support the government's objectives. We establish conditions under which the level of activities chosen by the government maximizes its benefits, and simultaneously induces the constituency to support enforcement of the rule of law. These conditions provide a basis for the argument for the implementation of the big‐bang policy. When these conditions do not hold, however, we show that the level of activities that maximizes the government's benefits may have only a minor impact on support for the enforcement of the rule of law. Two characteristics play an important role in these conditions: the initial level of crime and the types of activities the government chooses to undertake. We present examples showing that the initial level of crime has the more dramatic effect on subsequent support for the rule of law.     

The long-term effects of job search requirements: Evidence from the UK JSA reform

This paper investigates long-term returns from unemployment compensation, exploiting variation from the UK JSA reform of 1996, which implied a major increase in job search requirements for eligibility and in the related administrative hurdle. Search theory predicts that such changes should raise the proportion of nonclaimant nonemployed, with consequences on search effort and labor market attachment, and lower the reservation wage of the unemployed, with negative effects on post-unemployment wages. I test these ideas on longitudinal data from social security records (LLMDB). Using a difference in differences approach, I find that individuals who start an unemployment spell soon after JSA introduction, as opposed to 6 months earlier, are 2.5–3% more likely to move from unemployment into Incapacity Benefits spells, and 4–5% less likely to have positive earnings in the following year. This latter employment effect only vanishes 4 years after the initial unemployment shock. Also, annual earnings for the treated individuals are lower than for the non-treated. These results suggest that while tighter search requirements were successful in moving individuals off unemployment benefits, they were not successful in moving them onto stable or better jobs, with fairly long-lasting unintended consequences on a number of labor market outcomes.     

Trade Credit Management and the Decision to Use Factoring: An Empirical Study

This paper examines the firm's decision to use factoring amongst a cross-sectional sample of 655 manufacturing companies using a rich firm-level database. The paper develops and tests hypotheses that explain this particular choice of credit and financial management policy. We find strong evidence of a 'financing demand' explanation for the use of factoring, and also some support for theories which relate the decision to use a factor to the firm's product characteristics, to market characteristics and to the preferences of the factor (supply constraints). The motivation to use factoring, however, appears to be related more to a demand for asset-based finance from small companies than to firm-level choices about organisational structure.     

A medium-N approach to macroeconomic forecasting

This paper considers methods for forecasting macroeconomic time series in a framework where the number of predictors, N, is too large to apply traditional regression models but not sufficiently large to resort to statistical inference based on double asymptotics. Our interest is motivated by a body of empirical research suggesting that popular data-rich prediction methods perform best when N ranges from 20 to 40. In order to accomplish our goal, we resort to partial least squares and principal component regression to consistently estimate a stable dynamic regression model with many predictors as only the number of observations, T, diverges. We show both by simulations and empirical applications that the considered methods, especially partial least squares, compare well to models that are widely used in macroeconomic forecasting.