Accounting for Spatial Effects in Economic Models of Land Use: Recent Developments and Challenges Ahead

The marked increase in the availability of spatial data has forced researchers engaged in land use modeling to directly confront the question of space and the theoretical and methodological challenges involved in developing spatial models. Advances have come from multiple disciplines, most notably through the development and application of spatial theory and methods from regional science, geography, urban economics and more recently, theoretical and applied econometrics. The main goal of this paper is to summarize the econometric challenges of spatial data and to highlight spatial models and methods with a particular focus on models of land markets and land use change. We also discuss the data and modeling challenges associated with modeling the underlying spatial economic mechanisms that give rise to land use patterns and the complexities involved in modeling land use as a coupled economic-ecological system.     

Dynamic pricing of electricity in the mid-Atlantic region: econometric results from the Baltimore gas and electric company experiment

The Baltimore Gas and Electric Company (BGE) undertook a dynamic pricing experiment to test customer price responsiveness to different dynamic pricing options. The pilot ran during the summers of 2008 and 2009 and was called the Smart Energy Pricing (SEP) Pilot. In 2008, it tested two types of dynamic pricing tariffs: critical peak pricing (CPP) and peak time rebate (PTR) tariffs. About a thousand customers were randomly placed on these tariffs and some of them were paired with one of two enabling technologies, a device known as the Energy Orb and a switch for cycling central air conditioners. The usage of a randomly chosen control group of customers was also monitored during the same time period. In 2009, BGE repeated the pilot program with the same customers who participated in the 2008 pilot, but this time it only tested the PTR tariff. In this paper, we estimate a constant elasticity of substitution (CES) model on the SEP pilot’s hourly consumption, pricing and weather data. We derive substitution and daily price elasticities and predictive equations for estimating the magnitude of demand response under a variety of dynamic prices. We also test for the persistence of impacts across the two summers. In addition, we report average peak demand reduction for each of the treatment cells in the SEP pilot and compare the findings with those reported from earlier pilots. These results show conclusively that it is possible to incentivize customers to reduce their peak period loads using price signals. More importantly, these reductions do not wear off when the pricing plans are implemented over two consecutive summers. Our analyses reveal that SEP participants reduced their peak usages in the range of 18 to 33% in the first summer of the SEP pilot and continued these reductions in the second summer.     

Estimating the Costs of Protecting Native Species from Invasive Animal Pests in New South Wales,Australia

Invasive animal pests reduce crop and livestock output, require management and control measures, and threaten native plants, animals and their habitat. The agricultural and management costs are often directly measurable. But the costs to protect threatened native plants and animals are harder to assess. The Rural Lands Protection Boards were the government agency in New South Wales that managed invasive animals. An analysis of their decisions provided the opportunity to estimate the costs of protecting native species. The number of native plants and animals threatened by invasive pests was modelled against the expenditure, area, pest abundance, climate and location of 38 Board districts. There was a strong negative relationship between the number of threatened native species and Board expenditure. This relationship was interpreted to estimate the marginal cost of protecting a threatened native species, the downward shift in the supply curve necessary to protect all threatened native species, and the gains from the shift in the form of cost savings in the continued protection of non-threatened native species. These results value some of the costs that invasive animal pests impose on the environment.     

The Effect of Risk Context on the Value of a Statistical Life: a Bayesian Meta-model

This paper presents the first value of statistical life (VSL) meta-analysis that empirically estimates correction factors for ‘out of context’ benefits transfer (BT) purposes. In the field of mortality risk reductions elicited willingness to pay values in one risk context, say road safety, are frequently applied in other risk contexts like air pollution. However, differences in risk perception and the population at risk across contexts are likely to result in diverging VSL estimates. In a meta-analysis of 26 international stated preference studies, a Bayesian model is estimated regressing contingent values for mortality risk reductions, originating from three different risk contexts, on the characteristics of the risk reduction itself and additional variables characterizing the underlying studies. A willingness to pay (WTP) premium for mortality risk reductions in the air pollution and general mortality risk context relative to improving road safety is observed. Evaluated at the mean, road safety VSL estimates should be multiplied by a factor 1.8 before being applicable in the air pollution context. Moreover, in an illustrative BT exercise we find limited overlap in the set of context specific predictive VSL distributions. Consequently, ‘out of context’ BT results in a substantial over- or underestimation of the VSL.     

Does Disclosure Reduce Pollution? Evidence from India’s Green Rating Project

Public disclosure programs that collect and disseminate information about firms’ environmental performance are increasingly popular in both developed and developing countries. Yet little is known about whether they actually improve environmental performance, particularly in the latter setting. We use detailed plant-level survey data to evaluate the impact of India’s Green Rating Project (GRP) on the environmental performance of the country’s largest pulp and paper plants. We find that the GRP drove significant reductions in pollution loadings among dirty plants but not among cleaner ones. This result comports with statistical and anecdotal evaluations of similar disclosure programs. We also find that plants located in wealthier communities were more responsive to GRP ratings, as were single-plant firms.     

Environmental Policy Theory Given Bounded Rationality and Other-regarding Preferences

Established environmental policy theory is based on the assumption of homo economicus. This means that people are seen as fully rational and acting in a self-regarding manner. In line with this, economics emphasizes efficient policy solutions and the associated advantages of price incentives. Behavioral economics offers alternative, more realistic views on individual behavior. In this paper we investigate opportunities to integrate bounded rationality and other-regarding preferences into environmental policy theory to arrive at recommendations for more effective policies. For this purpose, we will address decisions made under risk and uncertainty, intertemporal choice, decision heuristics, other-regarding preferences, heterogeneity, evolutionary selection of behaviors, and the role of happiness. Three aspects of environmental policy are considered in detail, namely sustainable consumption, environmental valuation and policy design. We pay special attention to the role of non-pecuniary, informative instruments and illustrate the implications for climate policy.     

Abatement and Allocation in the Pilot Phase of the EU ETS

We use historical industrial emissions data to assess the level of abatement and over-allocation that took place across European countries during the pilot phase (2005–2007) of the European Union Emission Trading Scheme. Using a dynamic panel data model, we estimate the counter factual (business-as-usual) emissions scenario for EU member states. Comparing this baseline to allocated and verified emissions, we find that both over-allocation and abatement occurred, along with under-allocation and emissions inflation. Over the three trading years of the pilot phase we find over-allocation of approximately 280 million EUAs and total abatement of 247 Mt CO₂. However, we calculate that emissions inflation of approximately 73 Mt CO₂ also occurred, possibly due to uncertainty about future policy design features.     

A Note on Clean Technology Adoption and its Influence on Tradeable Emission Permits Prices

In this paper, we give an example in which the price of tradable emission permits increases despite firms’ adoption of less polluting technology, a result that is in contrast with Montero (J Environ Econ 44:23–44, 2002) and Parry (J Regul Econ 14:229–254, 1998), among others. If two Cournot players switch to a cleaner technology, the price for permits may increase due to an increase in the net demand for permits and a decrease in the net supply of permits after the clean technology is adopted. This is only the case when output demand is quite elastic.     

The Impact of Land-Use Change on Ecosystem Services,Biodiversity and Returns to Landowners: A Case Study in the State of Minnesota

Land-use change has a significant impact on the world’s ecosystems. Changes in the extent and composition of forests, grasslands, wetlands and other ecosystems have large impacts on the provision of ecosystem services, biodiversity conservation and returns to landowners. While the change in private returns to landowners due to land-use change can often be measured, changes in the supply and value of ecosystem services and the provision of biodiversity conservation have been harder to quantify. In this paper we use a spatially explicit integrated modeling tool (InVEST) to quantify the changes in ecosystem services, habitat for biodiversity, and returns to landowners from land-use change in Minnesota from 1992 to 2001. We evaluate the impact of actual land-use change and a suite of alternative land-use change scenarios. We find a lack of concordance in the ranking of baseline and alternative land-use scenarios in terms of generation of private returns to landowners and net social benefits (private returns plus ecosystem service value). Returns to landowners are highest in a scenario with large-scale agricultural expansion. This scenario, however, generated the lowest net social benefits across all scenarios considered because of large losses in stored carbon and negative impacts on water quality. Further, this scenario resulted in the largest decline in habitat quality for general terrestrial biodiversity and forest songbirds. Our results illustrate the importance of taking ecosystem services into account in land-use and land-management decision-making and linking such decisions to incentives that accurately reflect social returns.