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In 2012 the Swedish Environmental Protection Agency was provided with 100,000 ha of productive forest land. The Agency swapped the land to obtain conservation-worthy forests, and these were turned into natural reserves. Conservation without reference to both benefits and cost typically results in inefficient solutions. In this paper we discuss how to select the forest stands to preserve in a cost-effective manner. We also discuss how to design a cost-benefit analysis of the swapping program. We provide several new results regarding the economics of preservation, when land swaps is a viable instrument.

In this note, we consider a case when a forestry property may lose its market value through "political risk", illustrated here by it being classified as containing a key biotope. If a key biotope is found on a forest property in Sweden, the wood is almost impossible to sell. We show how the Faustmann formula is modified in this case and identify a "balance sheet" effect and a shortened rotation period. The theory seems to have some empirical support, given observed changes in bank lending contracts and alleged changes in forester's behavior to reduce the "political risk".

If the survival function of a random variable X lies to the right of the survival function of a random variable Y, then X is said to stochastically dominate Y. Inferring stochastic dominance is particularly complicated because comparing survival functions raises four possible hypotheses: identical survival functions, dominance of X over Y, dominance of Y over X, or crossing survival functions. In this paper, we suggest four-decision tests for stochastic dominance suitable for paired samples. The tests are permutation-based and do not rely on distributional assumptions. One-sided Cramér–von Mises and Kolmogorov–Smirnov statistics are employed but the general idea may be utilized with other test statistics. The power to detect dominance and the different types of wrong decisions are investigated in an extensive simulation study. The proposed tests are applied to data from an experiment concerning the individual’s willingness to pay for a given environmental improvement.

While support schemes to renewable energy are ubiquitous around the world today, there are few systematic welfare evaluations of their social benefits and costs in an economy-wide setting. We develop a general equilibrium cost–benefit rule to assess changes in quantity based subsidy schemes, “green” certificates, that support renewable electricity generation. An advantage to large-scale numerical models of the same issue is that we can go “into the black box” and uncover key economic mechanisms. We study a second-best economy with distorting taxes and pollution, so that a perturbation of the certificate scheme causes both benefits and costs; these items can be uncovered and estimated using our framework. To this end, we provide a user-friendly approximation for empirical implementation, which means that data requirement is modest relative to a typical computable general equilibrium model. We apply the theory to a currently existing scheme in Sweden taking into account “trickle-down” effects, including e.g. a loss of value-added tax income in the rest of the economy and environmental costs (i.e. externalities from electricity generation not currently internalized). We first present an ex post estimate, i.e. the welfare consequences of having scrapped the existing system 2003–2017 and then an ex ante analysis of extending the system to 2045. The latter includes a systematic sensitivity analysis based on Monte-Carlo simulation. Overall, we find net present value gains from removing the subsidy scheme, taking into account externalities, “trickle-down” and public finance repercussions.

Using data from a survey of households in 11 OECD countries, this paper investigates the determinants of preferences for a completely green residential electricity system. Three important questions are addressed: (i) how much are households willing to pay to use only renewable energy? (ii) does willingness-to-pay (WTP) vary significantly across household groups and countries? and (iii) what drives the decision to enter the (hypothetical) market for green energy and, given entry, what drives the level of WTP? The analysis here differs from previous studies on green energy in two ways: first, data and analyses are comparable across countries and second, a comprehensive attempt is made to understand 0 WTP, and to accommodate-using a censored quantile regression (CQR) framework-unobserved heterogeneity. The survey data indicate a low WTP, at 11-12 % of current electric bill. This study also addresses a key question: how important is income for understanding WTP, relative to more "attitudinal" determinants? The effect of income overall appears ambiguous, with Tobit-like models indicating that income is not significant while the CQR indicates that income exerts a significant effect near the center of the distribution of WTP. Across all frameworks used, a key determinant of WTP appears to be environmental attitudes, particularly membership in an environmental organization.

Difícilmente pueden entenderse muchos de los impactos que infringimos al medio ambiente, así como sus soluciones, sin comprender la relación entre economía y medio ambiente. Cómo usamos y cómo podríamos utilizar mejor los recursos, sean estos renovables o no renovables. En cuánto valoramos las personas la protección de determinados espacios naturales o hasta cuánto estamos dispuestos a invertir para gozar de agua de mejor calidad. Cuándo vale la pena construir una carretera a pesar de sus impactos ambientales o cuándo renunciar a ella. Qué consecuencias tiene el que unos países adopten leyes ambientales más estrictas y otros más laxas. En cuánto deberíamos penalizar a aquellas industrias que dañan nuestro entorno. Cómo podemos lograr que se emitan menos gases de efecto invernadero en todo el mundo sin que nos cueste demasiado. Estas son algunas cuestiones que nos pueden preocupar y a las que este manual de economía ambiental y de los recursos naturales puede ayudar a dar respuesta. Los autores, todos ellos doctores de economía y profesores de universidad especialistas en economía del medio ambiente, han trasladado a este libro su experiencia docente y de investigación para que los lectores puedan introducirse a la economía ambiental y de los recursos naturales sin requerir de conocimientos específi cos previos. El libro se dirige no sólo a economistas o estudiantes de economía interesados en el medio ambiente, sino también, y especialmente, a otros estudiantes, profesionales y personas con preocupación ambiental y deseo de conocer lo que la economía puede aportar.

This paper makes a contribution towards the statistical analysis of data sets containing intervals, that naturally arises in survey contexts. The suggested approach is sufficiently general to cover most cases where interval data are used. Interval data appear in many contexts, such as in reliability studies and survival analysis, in medicine and economics, in opinion elicit surveys, etc. There are several reasons for the extensive use of interval data, perhaps, the most common being one of necessity; exact values of the underlying observations are censored. The nature of the intervals analyzed here is somewhat unusual. The self-selected intervals (SeSeI) are (freely) chosen by the subjects. A generalization of the influential approach has been suggested to the statistical analysis of general censoring introduced by B. W. Turnbull. A key independence assumption in Turnbull's analysis has been explained and generalized. A sampling stopping rule based on the coverage probability has been suggested and the properties of a two-step estimator, based on the idea of asking two questions, where the second involves a way of fine-graining the information, has been discussed. This paper provides several informatics methods for SeSeI, targeting the problem of partial nonparametric identification. The properties of the suggested statistical models are stated, including a recursion for easy numerical calculations. An extensive simulation study, displaying, inter alia, the usefulness of the proposed resampling methods for the situation under study, completes the paper.

When the agent making an investment decision is different from the one bearing the costs of the decision, the outcome (energy usage, here) is socially sub-optimal, a scenario known in the energy efficient technology case as "split incentive" effect. Using a sample of households (from a survey conducted in 2011) from 11 OECD countries, this paper investigates the magnitude of the "split incentive" effect between home occupants who are owners and those who are renters. A wide variety of energy-related "technologies" are considered: appliances, energy efficient bulbs, insulation, heat thermostat, solar panels, ground source heat pumps and wind turbines. Mean difference in patterns of access to these technologies are consistent with the "split incentives" hypothesis. Regression results suggest that, even after controlling for the sizeable differences in observed characteristics, owners are substantially more likely to have access to energy efficient appliances and to better insulation as well as to heat thermostats. For relatively immobile investments such as wind turbines and ground source heat pumps, we find no differences between owners and renters.

This paper is devoted to some important welfare economic issues related to natural disasters, in particular those connected with floods and storms. Our analysis of the social cost of a natural disaster is different from (most) existing analyses, in that we focus sharply on the welfare effects of a disaster. We derive a simple dynamic general equilibrium cost-benefit rule, which captures loss in production of private and public goods, as well as the value of (statistical) lives lost; it also clarifies the role played by changes in stocks and flows, respectively. Standard analysis of losses typically only includes damages to market-priced stocks and flows, thus our model paints a different picture of social cost. This difference is particularly striking for disaster that results in many deaths, but has relatively low (reported) costs. We take our model to the data by using EM-DAT, one of the several prominent databases in this literature, focusing on water-related disasters in the US.

This paper uses the interval data model to explore the determinants of uncertainty in two-way payment ladder and in multiple-bounded uncertainty choice surveys. It estimates the uncertainty function that relates the size of the willingness-to-pay range to explanatory variables, where one of them is a proxy of the actual willingness-to-pay. The combination of the interval data model and the inclusion of the proxy variable present some advantages over the ordinary least square estimations currently used in the literature. In particular, it reduces the risk of the omitted variable bias and it takes into account that the dependent variable is not fully observed.