GREEN PAYMENT PROGRAMS FOR NONPOINT SOURCE POLLUTION CONTROL: HOW IMPORTANT IS TARGETING FOR COST-EFFECTIVENESS?

Mechanism design theory is used to examine the case of a cost-minimizing regulator who uses input-reduction subsidies to meet an exogenously imposed ambient standard for nonpoint source pollution. A general result claimed for a welfare-maximizing equilibrium. Numerical results suggest the ability to directly target contracts reduces costs significantly for the regulator. But in the absence of this ability, indirect targeting reduces costs only slightly.Environmental Economics and Policy,

Some Simulation Results for a Green Insurance Mechanism

This analysis extends previous work on green insurance by proposing a mechanism that offers a stronger adoption incentive and is applicable to heterogeneous populations and non-binary adoption decisions. Endogenous learning about the new technology is incorporated, and empirically calibrated simulation results are presented for the case of reduced-phosphorus dairy diets. Results show that the mechanism has a significant impact on behavior and may incur no net cost for the regulator when an insurance premium is charged. Conditions under which a green payment mechanism may be preferable to green insurance also are discussed.conservation technology adoption, dairy farming, endogenous learning, green insurance, phosphorus, risk preferences, voluntary programs, Environmental Economics and Policy,

Simulating the Effects of a Green Payment Program on the Diffusion Rate of a Conservation Technology

The decision to adopt a potentially profitable but unfamiliar conservation technology is cast in a multi-period Bayesian framework. Specifically, dairy farmers who are both risk-averse and susceptible to peer group influence progressively learn about the true impact of adopting reduced phosphorus dairy diets on their income distributions as they repeatedly experiment with this new technology. Empirically calibrated simulations are used to examine the effects of a voluntary green payment program on the rate of technological diffusion. Results suggest that (a) green payments can accelerate learning and produce significant, permanent changes in behavior relatively quickly and for a reasonable cost; (b) shorter contracts offering larger incentives may be more cost-effective when learning plays an important role in behavioral change; and (c) unknown prior beliefs can reduce the efficacy of a green payment program, implying efforts to verify these priors or to ensure against them by increasing the payment level may be worthwhile.Environmental Economics and Policy,

Ground Water Quantity and Quality Management: Agricultural Production and Aquifer Salinization over Long Time Scales

An economic model of ground water salinization is developed. Starting from a full, high-quality aquifer, there is an initial extraction period, an intermediate waste disposal period, and a final drainage period. Drainage management is initially source control and reuse, but eventually culminates in evaporation basins and a system steady-state. This process occurs over long time scales but is consistent with historical observation. Efficiency is qualitatively similar to common property though quantitative magnitudes differ substantially. Regulatory pricing instruments are developed to support the efficient allocation. The system is not sustainable in that net returns generally decline through time until the steady-state.common property, dynamic programming, efficiency, ground water, irrigation, salinity, sustainability, Resource /Energy Economics and Policy,

STATIC MODELING OF DYNAMIC RECREATION BEHAVIOR: IMPLICATIONS FOR PREDICTION AND WELFARE ESTIMATION

This paper examines the consequences of using a static model of recreation trip-taking behavior when the underlying decision problem is dynamic. In particular, we examine the implications for trip forecasting and welfare estimation using a panel dataset of Lake Michigan salmon anglers for the 1996 and 1997 fishing seasons. We derive and estimate both a structural dynamic model using Bellman's equation, and a reduced-form static model with trip probability expressions closely mimicking those of the dynamic model. We illustrate an inherent identification problem in the reduced-form model that creates biased welfare estimates, and we discuss the general implications of this for the interpretation of preference parameters in static models. We then use both models to simulate trip taking behavior and show that although their in-sample trip forecasts are similar, their welfare estimates and out-of-sample forecasts are quite different.Research Methods/ Statistical Methods,

A Stochastic-Dynamic Model of Costly Reversible Technology Adoption

We develop a stochastic-dynamic model of technology adoption that imposes fewer restrictions on behavior than do previous studies of similar decision problems. Like these previous studies, our model is forward-looking and can be used to demonstrate the additional "hurdle rate" that must be met before adoption will take place when the future state of the world is uncertain. Unlike these previous studies, our approach does not impose the untenable assumptions that investment in a new technology is irreversible or that technologies have unlimited useful lifetimes. Rather, we address the more reasonable situation of costly reversibility and limited lifetimes. Our solution method utilizes Bellman's equation and standard dynamic programming techniques. Similar methods have been used previously to examine irreversible investment and adoption problems, but to our knowledge no application to costly reversible adoption has yet to appear in the literature. Our behavioral simulations, calibrated for irrigated cotton farming in California's San Joaquin Valley, demonstrate that the more restrictive approach can produce significant model prediction errors and can overlook important features of the adoption problem when decisions are reversible and technologies eventually become obsolete. Policy implications are discussed.dynamic optimization, irrigation, reversible, technology adoption, water, Research and Development/Tech Change/Emerging Technologies,

Effects of Nutrient Restrictions on Confined Animal Facilities: Insights from a Structural Model

Nutrient emissions from animal feeding operations continue to degrade water and air quality. New regulations will limit the amounts of nutrients that can be locally applied to land. In this article, a structural-dynamic model of a livestock-crop operation is calibrated with data from a representative farm and is used to predict the effects of nitrogen regulations. Policy simulations clarify the importance of dynamic elements and demonstrate three main results: (1) cost estimates are relatively high; (2) cross-media pollution effects are potentially large; and (3) improved input management appears most promising for reducing both emissions and waste management costs. Implications for policy and future research are discussed.Ammonia, animal feeding operation, cross-media pollution, dairy, dynamic optimization, groundwater, nitrate, nitrogen, nutrient management plan, Livestock Production/Industries,

Simulating the Effects of a Green Payment Program on the Diffusion Rate of a Conservation Technology

The decision to adopt a potentially profitable but unfamiliar conservation technology is cast in a multi-period Bayesian framework. Specifically, dairy farmers who are both risk-averse and susceptible to peer group influence progressively learn about the true impact of adopting reduced phosphorus dairy diets on their income distributions as they repeatedly experiment with this new technology. Empirically calibrated simulations are used to examine the effects of a voluntary green payment program on the rate of technological diffusion. Results suggest that (a) green payments can accelerate learning and produce significant, permanent changes in behavior relatively quickly and for a reasonable cost; (b) shorter contracts offering larger incentives may be more cost-effective when learning plays an important role in behavioral change; and (c) unknown prior beliefs can reduce the efficacy of a green payment program, implying efforts to verify these priors or to ensure against them by increasing the payment level may be worthwhile

GREEN PAYMENT PROGRAMS FOR NONPOINT SOURCE POLLUTION CONTROL: HOW IMPORTANT IS TARGETING FOR COST-EFFECTIVENESS?

Mechanism design theory is used to examine the case of a cost-minimizing regulator who uses input-reduction subsidies to meet an exogenously imposed ambient standard for nonpoint source pollution. A general result claimed for a welfare-maximizing equilibrium. Numerical results suggest the ability to directly target contracts reduces costs significantly for the regulator. But in the absence of this ability, indirect targeting reduces costs only slightly