Carlo Fezzi

Bringing Ecosystem Services into Economic Decision-Making: Land Use in the United Kingdom

Monitoring Land Use Land-use decisions are based largely on agricultural market values. However, such decisions can lead to losses of ecosystem services, such as the provision of wildlife habitat or recreational space, the magnitude of which may overwhelm any market agricultural benefits. In a research project forming part of the UK National Ecosystem Assessment, Bateman et al. (p. 45) estimate the value of these net losses. Policies that recognize the diversity and complexity of the natural environment can target changes to different areas so as to radically improve land use in terms of agriculture and greenhouse gas emissions, recreation, and wild species habitat and diversity. The value of using land for recreation and wildlife, not just for agriculture, can usefully factor into planning decisions. Landscapes generate a wide range of valuable ecosystem services, yet land-use decisions often ignore the value of these services. Using the example of the United Kingdom, we show the significance of land-use change not only for agricultural production but also for emissions and sequestration of greenhouse gases, open-access recreational visits, urban green space, and wild-species diversity. We use spatially explicit models in conjunction with valuation methods to estimate comparable economic values for these services, taking account of climate change impacts. We show that, although decisions that focus solely on agriculture reduce overall ecosystem service values, highly significant value increases can be obtained from targeted planning by incorporating all potential services and their values and that this approach also conserves wild-species diversity.

Bringing ecosystem services into economic decision-making

Monitoring Land Use Land-use decisions are based largely on agricultural market values. However, such decisions can lead to losses of ecosystem services, such as the provision of wildlife habitat or recreational space, the magnitude of which may overwhelm any market agricultural benefits. In a research project forming part of the UK National Ecosystem Assessment, Bateman et al. (p. 45) estimate the value of these net losses. Policies that recognize the diversity and complexity of the natural environment can target changes to different areas so as to radically improve land use in terms of agriculture and greenhouse gas emissions, recreation, and wild species habitat and diversity. The value of using land for recreation and wildlife, not just for agriculture, can usefully factor into planning decisions. Landscapes generate a wide range of valuable ecosystem services, yet land-use decisions often ignore the value of these services. Using the example of the United Kingdom, we show the significance of land-use change not only for agricultural production but also for emissions and sequestration of greenhouse gases, open-access recreational visits, urban green space, and wild-species diversity. We use spatially explicit models in conjunction with valuation methods to estimate comparable economic values for these services, taking account of climate change impacts. We show that, although decisions that focus solely on agriculture reduce overall ecosystem service values, highly significant value increases can be obtained from targeted planning by incorporating all potential services and their values and that this approach also conserves wild-species diversity.

Interaction of European Carbon Trading and Energy Prices

This paper addresses the economic impact of the EU Emission Trading Scheme for carbon on wholesale electricity and gas prices. Specifically, we analyse the mutual relationships between electricity, gas and carbon prices in the daily spot markets in the United Kingdom. Using a structural co-integrated VAR model, we show how the prices of carbon and gas jointly influence the equilibrium price of electricity. Furthermore, we derive the dynamic pass-trough of carbon into electricity price and the response of electricity and carbon prices to shocks in the gas price.

The Effects of Weather and Climate Change on Dengue

Background There is much uncertainty about the future impact of climate change on vector-borne diseases. Such uncertainty reflects the difficulties in modelling the complex interactions between disease, climatic and socioeconomic determinants. We used a comprehensive panel dataset from Mexico covering 23 years of province-specific dengue reports across nine climatic regions to estimate the impact of weather on dengue, accounting for the effects of non-climatic factors. Methods and Findings Using a Generalized Additive Model, we estimated statistically significant effects of weather and access to piped water on dengue. The effects of weather were highly nonlinear. Minimum temperature (Tmin) had almost no effect on dengue incidence below 5°C, but Tmin values above 18°C showed a rapidly increasing effect. Maximum temperature above 20°C also showed an increasing effect on dengue incidence with a peak around 32°C, after which the effect declined. There is also an increasing effect of precipitation as it rose to about 550 mm, beyond which such effect declines. Rising access to piped water was related to increasing dengue incidence. We used our model estimations to project the potential impact of climate change on dengue incidence under three emission scenarios by 2030, 2050, and 2080. An increase of up to 40% in dengue incidence by 2080 was estimated under climate change while holding the other driving factors constant. Conclusions Our results indicate that weather significantly influences dengue incidence in Mexico and that such relationships are highly nonlinear. These findings highlight the importance of using flexible model specifications when analysing weather–health interactions. Climate change may contribute to an increase in dengue incidence. Rising access to piped water may aggravate dengue incidence if it leads to increased domestic water storage. Climate change may therefore influence the success or failure of future efforts against dengue.

Structural Agricultural Land Use Modeling for Spatial Agro-Environmental Policy Analysis

This paper develops a spatially disaggregated, structural econometric model of agricultural land use and production based on the joint multi-output technology representation introduced by Chambers and Just (1989) . Starting from a flexible specification of the farm profit function, we derive land use allocation, input application, crop yield, and livestock intensity equations in a joint and theoretically consistent framework. To account for the presence of censored observations in micro-level data, the model is estimated as a system of two-limit Tobit equations via quasi-maximum likelihood. We present an empirical application using fine-scale spatial data covering the entirety of England and Wales and including the main economic, policy, and environmental drivers of land use change in the past forty years. A simulation of the effects of diffuse pollution reduction measures illustrates how our approach can be applied for agro-environmental policy appraisal. Copyright 2011, Oxford University Press.

Predicting microbial pollution concentrations in UK rivers in response to land use change

The Water Framework Directive has caused a paradigm shift towards the integrated management of recreational water quality through the development of drainage basin-wide programmes of measures. This has increased the need for a cost-effective diagnostic tool capable of accurately predicting riverine faecal indicator organism (FIO) concentrations. This paper outlines the application of models developed to fulfil this need, which represent the first transferrable generic FIO models to be developed for the UK to incorporate direct measures of key FIO sources (namely human and livestock population data) as predictor variables. We apply a recently developed transfer methodology, which enables the quantification of geometric mean presumptive faecal coliforms and presumptive intestinal enterococci concentrations for base- and high-flow during the summer bathing season in unmonitored UK watercourses, to predict FIO concentrations in the Humber river basin district. Because the FIO models incorporate explanatory variables which allow the effects of policy measures which influence livestock stocking rates to be assessed, we carry out empirical analysis of the differential effects of seven land use management and policy instruments (fiscal constraint, production constraint, cost intervention, area intervention, demand-side constraint, input constraint, and micro-level land use management) all of which can be used to reduce riverine FIO concentrations. This research provides insights into FIO source apportionment, explores a selection of pollution remediation strategies and the spatial differentiation of land use policies which could be implemented to deliver river quality improvements. All of the policy tools we model reduce FIO concentrations in rivers but our research suggests that the installation of streamside fencing in intensive milk producing areas may be the single most effective land management strategy to reduce riverine microbial pollution.

Cost-Effective Mitigation of Diffuse Pollution: Setting Criteria for River Basin Management at Multiple Locations

A case study of the Yorkshire Derwent (UK) catchment is used to illustrate an integrated approach for assessing the viability of policy options for reducing diffuse nitrate losses to waterbodies. For a range of options, modeling methods for simulating river nitrate levels are combined with techniques for estimating the economic costs to agriculture of modifying those levels. By incorporating spatially explicit data and information on catchment residence times (which may span many decades particularly in areas of groundwater discharge) a method is developed for efficient spatial targeting of measures, for example, to the most at-risk freshwater environments. Combining hydrological and economic findings, the analysis reveals that, in terms of cost-effectiveness, the ranking of options is highly sensitive to both (i) whether or not specific stretches of river within a catchment are regarded as a priority for protection, and (ii) the criterion of nitrate concentration deemed most appropriate as an indicator of the health of the environment. Therefore, given the focus under European legislation upon ecological status of freshwaters, these conclusions highlight the need to improve understanding of mechanistic linkages between the chemical and biological dynamics of aquatic systems.

The Impact of Climate Change on Agriculture: Nonlinear Effects and Aggregation Bias in Ricardian Models of Farmland Values

Ricardian (hedonic) analyses of the impact of climate change on farmland values typically assume additively separable effects of temperature and precipitation with model estimation being implemented on data aggregated across counties or large regions. We use a large panel of farm-level data to investigate the potential bias induced by such approaches. Consistent with the literature on plant physiology, we observe significant nonlinear interaction effects, with more abundant precipitation acting as a mitigating factor for increased heat stress. This interaction disappears when the same data are aggregated in the conventional manner, leading to predictions of climate change impacts that are significantly distorted.

Structural Analysis of Electricity Demand and Supply Interactions

We specify a structural asymmetric vector error-correction model to identify and estimate the demand and supply functions in hourly day-ahead wholesale electricity markets. In doing so, we provide, inter alia, new insights into a well-established but unresolved issue concerning the extent of the demand elasticity to price in these markets. We show that whilst demand appears to be inelastic in the short-run, the quantity traded on the market is significantly influenced by the price level and responds to previous disequilibria in the supply curve through an asymmetric error-correction mechanism, reacting to a positive disequilibrium but not to a negative one.

Structural Analysis of High Frequency Electricity Demand and Supply Interactions

A dynamic, structural asymmetric vector-error correction model is used to identify and estimate the demand and the supply functions for hourly, day-ahead electricity wholesale markets. The analysis provides new insights on a well-established but unresolved aspect concerning the extent of demand elasticity to price. We argue that the conventional meanreverting,stationarity assumption for electricity prices raises subtle issues of specification and must be carefully evaluated. We present evidence for adopting a non-stationary specification in the short-window, high-frequency context, and thereby estimate a cointegrating system. This allows us to distinguish between long run and short run effects, and to estimate an error-correction term embedded in a simultaneous equation model. We show that, whilst demand appears to be inelastic in the short run, the quantity traded on the market reacts significantly to previous disequilibria in the supply curve through an asymmetric error-correction mechanism, and does in fact adjust to positive changes in the price level, but not to negative ones.