Water Resources and Economics最新文献

We exploit sudden changes in the marginal tariff scheme to estimate the price elasticity of water demand using households' and firms' data in Tangerang Regency, a part of the Jakarta Greater Metropolitan Area, where water demand management is imperative due to the city's growing population and industrial activities. A monthly water consumption dataset at the consumer level is used in our study. Using the regression discontinuity in time (RDiT) approach, we find the price elasticity of water demand is −0.32 for household consumers and inelastic to changes in price. In contrast, elasticity for industrial and commercial consumers is −1.16, implying a more elastic response. The results raise concerns that firms substitute for a cheaper water source, endangering the water resources sustainability in the area.

The paper examines the response of twelve U.S. agricultural stock returns to El Niño-Southern Oscillation (ENSO) shocks using a recursive VAR model. Baseline results indicate that for seven of the stock returns, an ENSO shock has positive and significant effects. The effects, however, are shortlived, generally becoming statistically indistinguishable from zero three to six months after the shock. Variance decomposition analyses show that ENSO shocks have little explanatory power for fluctuations in U.S. agricultural stock returns. We also provide evidence that historically, movements in the stock returns of U.S. food and agricultural companies have been driven by other shocks, rather than ENSO shocks.

Urban water demand management is key to water supply sustainability in high-density, water-stressed areas throughout the world, and emerging technologies could transform it. In particular, smart metering could allow for conserving water by dynamically changing prices to reflect water scarcity and supply cost variability. Yet, little is known on end-users’ reaction to short-term price changes, an essential determinant of the effectiveness and acceptability of dynamic water pricing. This paper reports on the design and results of an online experiment that measures end-users’ water consumption decisions when confronted with time-varying prices, and investigates the interaction between pricing and water scarcity awareness. We design a series of treatments where players must indicate their shower length given different water prices, price variations, and scarcity scenarios. Beyond corroborating the theory that higher prices lower usage, the experiment finds evidence of a dynamic pricing effect: users respond more strongly to a given price if they have been exposed to a lower price before. This suggests short-term residential price increases could be effective at boosting water conservation.

Where we may be aware that a problem exists, but have only an incomplete description of the drivers and/or possible management solutions, we will be unaware/uncertain about future returns from, and risks to, private and public investments in capital (i.e. social, natural, economic, cultural and political). This paper explores the unawareness/uncertainty problem by coupling Arrow's states of nature approach for dealing with uncertainty with Rothschild and Stiglitz's exploration of inputs and increasing risk. This results in a modified Just-Pope production function equation isolating inputs to i) protect base capital (natural, social or private) and/or ii) generate an output. By exploring water input supply unawareness via alternative states of nature we may identify tipping points where current technology fails, resulting in irreversible losses of private and public capital tied to water inputs. We conclude by discussing the value of quantifying minimum-input requirements and identifying critical tipping-point outcomes in water systems, increased benefits/risks from transformed landscapes chasing higher economic returns, and the need for adaptive public arrangements in response. These insights may help us to understand future risk to natural capital from rising incentives to steal increasingly constrained resources that may trigger revised risk-sharing arrangements, and some limits to analyses relying on perfect foresight requirements by decision-makers.

In this article, we estimate both the economic value of water and own-price and cross-price elasticities of water for the Chilean manufacturing industry using the production function approach. Estimating the production function allows us to estimate the marginal productivity of water which corresponds to its economic value. Our estimations are based on panel data obtained from the National Industrial Survey for the period 1995–2014, accounting for more than 10,000 industrial plants. We use a translog specification for the production function, considering water, capital, labor, energy, and intermediate material as explanatory variables. We find substitution patterns among most inputs, except for energy and water, which are found to be complements. Our results suggest that the manufacturing sector is characterized by an elastic water demand, with an average economic value of water of 8.071 [USD/m³]. Based on our findings, there is room to increase water prices in most sectors without affecting the competitiveness of firms. Knowing the economic value of water and its price elasticity could help policymakers to design water policies that promote more efficient use of this scarce resource.

Cost-benefit analysis (CBA) of flood risk adaptation strategies offers policymakers insight into economically optimal strategies for adapting to sea level rise. However, building-level adaptation measures such as floodproofing or building elevation are often evaluated at aggregated spatial scales, which may result in sub-optimal investment decisions. In this paper, we develop a flood risk model and combine it with a micro-scale CBA at the building level to obtain an optimal mix of adaptation measures per area. We apply this approach to Venice Beach in Los Angeles and Naples in Long Beach. We subsequently compare our results with the conventional, spatially aggregated area-based CBA approach. Our findings show that a mix of 35%–45% dry-floodproofing measures and 55%–65% building elevation measures is optimal. Elevation works best in areas with high inundation depths, while dry-floodproofing is preferable in areas with shallow inundation depths. The optimal mix of measures derived from our micro-scale approach results in an economic efficiency up to 85% higher than that yielded by the commonly applied spatially aggregated approach. We therefore recommend that economic evaluations of building-level adaptation measures are conducted at the smallest possible scale, or that CBAs are performed on disaggregated areas based on inundation depth.

This study aims to understand the economic and bio-physical conditions under which mussel farming is a cost-effective mitigation measure to improve water quality related to excess nitrogen in fjords and coastal areas. We set-up a mixed-integer optimization model including every farm in three agricultural catchments surrounding Limfjorden, the largest fjord in Denmark. We include a number of relevant nitrogen abatement measures, including agricultural land-use measures and mussel farming in the sea. The aim is to model the least costly combination of mitigation measures to improve water quality when agricultural, environmental and market conditions vary. We run three scenarios varying environmental conditions for mussel productivity and market opportunities for mussel-based products as organic animal feed. We analyze the resulting marginal abatement costs and draw insights about the potential scale of mussel farming for the different catchments. We show that mussel farming is a cost-effective option for 2 of the 3 catchments, but that decreasing mussel productivity over time may make the measure ineffective for one of the catchments, if a market for feed is not available. The possibility of a market for mussel-based organic feed significantly increases the share of nitrogen reduction done by mussels and decreases overall costs by up to 65%. Ultimately, the results indicate that, for catchments where environmental conditions are adequate, mussel farming can be a cost-effective nutrient reduction measure. Therefore, mussel farming can potentially increase the cost-effectiveness of incentive schemes aimed at reducing eutrophication in fjords and coastal waters.

Allocation trade is an instrument that has been widely used to recover water for the environment during periods of scarcity (droughts). This paper proposes a water bank operating within a monopsony-monopoly setting with the dual purpose of reallocating water among farmers and acquiring water for the environment during drought periods. The proposed water bank would be managed by a public agency seeking to maximize economic efficiency generated in purchases and sales of water for agriculture and the efficiency generated by the recovery of water allocations for the environment. An additional, innovative feature of the analysis performed is that it considers the inefficiencies in the economy as a whole caused by public spending on water allocation purchases, measured through the marginal cost of public funds. The potential performance of the proposed water bank is simulated by mathematical programming techniques, taking the Guadalquivir River Basin (Southern Spain) as an empirical case study. The results provide evidence that, in terms of economic efficiency, the proposed institutional arrangement outperforms the instruments currently in place to purchase water allocations.

This research explores the relationship between episodes of contaminated drinking water and health care expenditures in the United States. The analysis relies on panel data from the 48 contiguous states from 2000 to 2011. We use the population served by public water systems that violate health-based standards of the Safe Drinking Water Act as a proxy for contaminated drinking water. We estimate spatial and non-spatial models and control for factors that may affect per capita health care expenditures including variables that reflect air quality violations along with ability to pay plus demand for and supply of health care services. The results from a Spatial Durbin Model indicate that a 1% decrease in the annual percentage of population exposed to drinking water quality violations is associated with reductions in in-state and regional effects equal to 0.005% and 0.035% of per capita health care expenditures, respectively. While relatively small on a per capita basis, drinking water violations have a larger impact on health care expenditures than air quality violations (whose effects are not statistically different from zero). However, compared to other factors, such as Medicare enrollment and income, the impact of these violations on health care expenditures is small. We find that the cumulative regional health care expenditure impacts from drinking water violations are substantially greater than in-state impacts. Thus, a regional approach is recommended to addressing drinking water quality improvements.

Benefit Transfer (BT) is often applied when a primary valuation study is considered too costly or time consuming to conduct. It is commonly assumed that BT performance improves with increasing similarity between study and policy sites. However, no common criteria for defining similarity exist, making it difficult to operationalise the concept of similarity in a practical BT context. We propose a structured framework for distinguishing between different degrees of similarity. In particular, we differentiate between three dimensions: physical, population and attribute similarity. While the first two are often used in the literature, attribute similarity is not. To investigate the impact attribute descriptions have on BT, we define it as whether or not the same ecosystem service categories are emphasised in the valuation studies. Using value estimates for water quality improvements obtained from 17 Choice Experiments conducted in Europe, we empirically test unit value transfer performance along a similarity gradient. The results confirm that increasing physical similarities across commodities and sites generally lead to lower transfer errors. However, when using income adjusted value transfer, we surprisingly find the opposite. Finally, we demonstrate that increasing attribute similarity may offset dissimilarities in terms of the site characteristics.