Diffusion and adoption of advanced emission abatement technology induced by permit trading

This paper analyzes firm incentives to diffuse and adopt advanced abatement technology for three different regimes of tradeable emission permits (auctioning, benchmarking, and grandfathering). We particularly consider technical change that decreases marginal abatement costs (MACs) only at high emission levels, whereas it increases them at low firm emissions. We establish that the desirability of the different regimes of allocating permits to firms is critically influenced by how MACs are changed by technological improvements.     

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Psycho-social factors impacting credit acquisition and use by college students

This research develops and tests two models using a range of psychological and sociological antecedents of credit card acquisition, spending practices and debt accumulation by college students. Six psycho-social dimensions were investigated: parental involvement, locus of control, compulsivity, impulsivity, debt anxiety and social status. Multivariate regression analysis using two dependent variables was conducted: the number of credit cards and total credit card debt. Although the multivariate model was highly significant, considerable variation emerged that best explained the number of credit cards students owned and the total credit card debt carried. The results offer insights in future research needs and consumer protection issues.     

The value of health interventions: evaluating asthma case management using matching

Despite large public investments in asthma interventions, there are few rigorous assessments of these programmes and little understanding of what comprises an effective intervention. There is a lack of appropriate data, little technical support is provided, and the programs themselves have little incentive to conduct these analyses. In this study, we apply optimal full matching using propensity scores to estimate the impact of an asthma intervention programme across a range of health outcomes. Our participation model is derived using the Deletion, Substitution and Addition (DSA) algorithm, a method used in epidemiology for model selection. We find that the asthma programme in question has no significant effect on participants that distinguishes them from matched nonparticipants, but it is not clear whether this is due to the effectiveness of the programme, heterogeneity of effects or barriers outside the programme's control. Our findings do show how current programmes could be modified to increase their effectiveness and better inform future research.     

Standard Oriented Environmental Policy: Cost-Effectiveness and Incentives for 'Green Technology'

Abstract. In their seminal 1971 paper, W. J. Baumol and W. E. Oates analyzed effluent charges and 'command and control' regarding their ability to attain a given standard of environmental quality at minimum cost. In the subsequent literature,transferable discharge permits (TDPs) have been added to the portfolio of standard oriented environmental policy instruments. We place these instruments in a dynamic context. Here, cost minimization is defined in an intertemporal setting allowing for induced technical change. It turns out that the relative performance of alternative policy instruments regarding their 'dynamic cost-effectiveness' crucially depends on the information available to the involved agents. Under adverse informational conditions,only a TDP system with future markets is dynamically cost-effective.     

Land Invasions,Insecure Property Rights and Production Decisions

This paper investigates empirically the effect of land invasions on farm production decisions. The main hypothesis is that more invasions in a region are associated with lower investment, and in particular a bias towards annual crops as opposed to long‐term crops. We use a county‐level dataset for the state of Paraná, Brazil, from 2003 to 2007, with 1,995 observations. The panel data structure allows us to control for fixed effects, such as the formalisation of land titles and land concentration, which might be correlated with the intensity of invasions. An instrumental variable fixed effects model was estimated to avoid other sources of bias. Our main finding is that land invasions are associated with lower long‐term crop production and a higher percentage of annual crops, which could accelerate land degradation, and undermine environmental sustainability.     

Urbanisation and Food Insecurity Risks: Assessing the Role of Human Development

The phenomenon of rapid urbanisation across the world has become a topic of increased scholarly inquiry. Yet, little attention has been paid to how urban growth affects countries’ food security and whether this association is modified by a country's level of development. The present study aims to fill this lacuna by examining the association between urbanisation and food security applying statistical modelling. The analysis uses country-level data, from the World Development Indicators and the United Nations’ World Urbanization Prospects. Using a Food Insecurity Risk Index (FIRI) as the outcome variable, the results confirm a significant negative impact of urban growth on food security at the country level. It further finds that rapidly urbanising countries with the lowest levels of human development are most at risk of food insecurity.     

Escalating penalties: a supergame approach

The paper provides an economic rationale for punishing repeat offenders with increasing sanctions. We analyze the optimal intertemporal punishment scheme within a supergame framework, in which the legal authority is assumed to minimize the social costs of punishment under the constraint of keeping delinquency at an exogenously given maximal tolerable level.     

Identifying relevant and irrelevant variables in sparse factor models

This paper considers factor estimation from heterogeneous data, where some of the variables—the relevant ones—are informative for estimating the factors, and others—the irrelevant ones—are not. We estimate the factor model within a Bayesian framework, specifying a sparse prior distribution for the factor loadings. Based on identified posterior factor loading estimates, we provide alternative methods to identify relevant and irrelevant variables. Simulations show that both types of variables are identified quite accurately. Empirical estimates for a large multi‐country GDP dataset and a disaggregated inflation dataset for the USA show that a considerable share of variables is irrelevant for factor estimation.