Intertemporal Emission Permits Trading Under Uncertainty and Irreversibility

This paper analyzes the effect of emission permit banking on clean technology investment and abatement under conditions where the stringency of the future cap is uncertain. We examine the problem of heterogeneous firms minimizing the cost of intertemporal emission control in the presence of stochastic future pollution standards and emission permits that are tradable across firms and through time. A firm can invest in clean capital (an improved pollution abatement technology) to reduce its abatement cost. We consider two possibilities: that investment is reversible or irreversible. Uncertainty is captured within a two period model: only the current period cap is known. We show that if banking is positive and marginal abatement costs are sufficiently convex, there will be more abatement and investment in clean technology under uncertainty than there would be under certainty and no banking. These results are at odds with the common belief that uncertainty on future environmental policy is a barrier to investment in clean capital. Moreover, under uncertainty and irreversibility, we find that there are cases where banking enables firms to invest more in clean capital.     

Shaping the Relationship Between Economic Development and Carbon Dioxide Emissions at the Local Level: Evidence from Spatial Econometric Models

The debate over the correlation between economic growth and environmental pollution has attracted a great deal of attention from academic researchers and policy makers in recent years. There has been excessive use of spatial econometric models and too much emphasis on statistical procedures in empirical studies. In this study, we contribute to the existing literature by conducting a more rigorous analysis of the relationship between economic growth and \(\hbox {CO}_{2}\) emissions in Chinese cities using spatial Durbin models. Our results show that \(\hbox {CO}_{2}\) emissions increase monotonically in relation to economic growth at the city level and that the driving effects of economic growth are slightly smaller in central China than in eastern and western China. In addition to economic growth, industry’s share of the economy is a major driver of \(\hbox {CO}_{2}\) emissions, while technological improvement, measured by energy intensity per unit of gross domestic product (GDP), and the effectiveness of environmental governance flatten the shape of the environmental Kuznets curve. We provide evidence of local spillover effects of explanatory variables on \(\hbox {CO}_{2}\) emissions. Economic competition as well as technological diffusion are found to exist in Chinese cities in relation to \(\hbox {CO}_{2}\) emissions. We also find carbon leakage between cities only if the per capita GDP of a given city is less than $493 (in 2010 constant dollars). Results hold when robustness checks are performed. Policy makers should carefully consider regional differences and the inherent spatial interactions between factors when formulating carbon reduction policies.     

Information Exchange and Transnational Environmental Problems

This paper analyzes information exchange in a model of transnational pollution control in which countries use private information in independently determining their domestic environmental policies. We show that countries may not always have an incentive to exchange their private information. However, for a sufficiently high degree of predictability of domestic environmental policy processes, the expected welfare from sharing information is greater than the expected welfare from keeping it private. The minimum degree of policy predictability for which information sharing occurs increases with the level of environmental risk. Intuitively, information exchange can help mitigate the perception of global uncertainty (both political and scientific) that surrounds transnational environmental problems and potentially improve welfare if policymaking processes are sufficiently aligned with evidence-based approaches (predictable).     

Taking Time for the Environment: On Timing and the Role of Delays in Environmental and Resource Economics

Ecosystem transformation and climate change evolve over long time scales. The effects of the economic decisions on the natural environment are also of a long-run character because they relate to investment decisions and capital stocks. At the same time, the economy is short-sighted and subject to different kinds of market failures. The time it takes to notice the changes and adequately address the associated problems affects the dynamics and inertia of the process. We discuss some recent contributions and new research questions that deal with time and timing in environmental and resource economics.     

Non-market Value of Winter Outdoor Recreation in the Swiss Alps: The Case of Val Bedretto

A longstanding interest from environmental economists on winter outdoor recreation has overlooked activities practiced outside the boundaries of winter resorts—e.g. ski mountaineering. This paper implements the Travel Cost Method to estimate consumer surplus per season derived from ski mountaineering and snowshoeing in Val Bedretto—a valley located in the Swiss Alps. In addition, the Contingent Behavior Method is used to estimate the changes in welfare associated with the construction of an alpine center that would provide services aiming to reduce the risk of injury and death associated with winter outdoor recreation. The data is analyzed by means of latent class panel on-site count models. The latent class approach allows us to identify subpopulations that benefit from the alpine center. The results show that 33% of visitors would experience an increase in their consumer surplus per season equivalent to €31 per visitor.     

Fractional Integration Versus Structural Change: Testing the Convergence of $$\hbox {CO}_{2}$$ Emissions

This paper assesses the stochastic convergence of relative \(\hbox {CO}_{2}\) emissions within 28 OECD countries over the period 1950–2013. Using the local Whittle estimator and some of its variants we assess whether relative per capita \(\hbox {CO}_{2}\) emissions are long memory processes which, although highly persistent, may revert to their mean/trend in the long run thereby indicating evidence of stochastic convergence. Furthermore, we test whether (possibly) slow convergence or the complete lack of it may be the result of structural changes to the deterministics of each of the relative per-capita emissions series by means of the tests of Berkes et al. (Ann Stat 1140–1165, 2006) and Mayoral (Oxford Bull Econ Stat 74(2):278–305, 2012). Our results show relatively weak support for stochastic convergence of \(\hbox {CO}_2\) emissions, indicating that only between 30 and 40% of the countries converge to the OECD average in a stochastic sense. This weak evidence disappears if we enlarge the sample to include 4 out of the 5 BRICS, indicating that our results are not robust to the inclusion of countries which are experiencing rates of growth which are far larger than those of the OECD members. Our results also decisively indicate that a slow or lack of convergence is not the results of a structural break in the relative \(\hbox {CO}_{2}\) emissions series.     

How are Scope and Adding up Relevant for Benefits Transfer?

In this paper, we explore ways in which the theoretical constructs of scope and adding up can inform and improve the practice of benefit transfer. Specifically, we examine how the stated preference literature on scope and adding up can inform three critical steps in benefits transfer: study site selection, including studies to select for use in a meta-regression; calibrating benefit functions; and assessing transfer validity.     

Understanding Error Structures and Exploiting Panel Data in Meta-analytic Benefit Transfers

A regression meta-analysis is a statistical summary of results from a set of empirical studies. While, a meta-analysis is typically used to drawn inferences regarding the collective insights from an empirical literature, a regression meta-analysis can also be used to predict outcomes as a substitute for the conduct of a new study. Within the nonmarket-valuation literature benefit transfers are a special case of prediction where value estimates collected for one purpose are used as a basis for predicting value for unstudied applications. Balancing against the prediction opportunities provided by a regression meta-analysis is the potential prediction error. This paper considers some of these issues in the estimation of a regression meta-analysis to support prediction of nonmarket values for applications where an original study does not exist. We do not purport to address all elements of the error structure and prediction issues, but to present a more coherent focus to enhance future research on the validity and reliability of benefit-function transfers, and ultimately assist in enhancing the credibility of benefit transfers to support policy analyses.     

Seeking External Evidence to Assess Benefit Transfers for Environmental Policy

The cost and time required to produce original benefit estimates makes benefit transfers a highly valuable component of the process of assessing the benefits and costs of environmental improvements. Because of the great variety of benefit estimates, conducted at different times with different data sources and different techniques, there is concerted effort to understand the validity of transfers. The research in this paper approaches the validity issue of benefit transfers by asking whether there is indirect evidence of the benefits. The premise of the paper is that policies that give significant benefits should induce expected and unexpected behavioral changes. We look for evidence of potential indirect evidence by by estimating the effect of differences air pollutants on activities such as outdoor recreation and work, as found in the American Time Use Survey.     

The pyramid of Okun’s coefficient for Italy

Our aim is to propose a pyramid of Okun’s coefficient by age and gender in the Italian labour force using a varying-coefficient model. The unemployment rate by age and gender—useful information for estimating Okun’s relationship—is not available for Italy from official statistics. Therefore, we provide an estimation of the indicator using microdata for the 2005–2014 period from ISTAT, the Italian labour force survey. Okun’s law is investigated using two measures of the unemployment rate: a traditional measure based on a labour force with and without work experience, and a new measure restricted to the labour force with experience. When Okun’s relationship is estimated using the unemployment rate restricted to the labour force with experience, the young population is less sensitive to business cycles. As the workforce ages, this gap in sensitivity tends to shrink. We also found that there are no significant differences by gender in the magnitude of Okun’s coefficient among the youngest population when considering the unemployment rate restricted to the labour force with experience.