Charles Griffiths

Roads, population pressures, and deforestation in Thailand, 1976-89

Tropical deforestation is considered one of the major environmental disasters of the 20th century, although there have been few careful studies of its causes. This paper examines the causes of deforestation in Thailand between 1976 and 1989, a period when the country lost 28% of its forest cover. This paper takes the perspective that, in the long run, the determinants of deforestation are the determinants of land use change. While logging and fuelwood gathering may remove forest cover, regrowth will occur, at least in moist tropical forests. For an area to remain deforested, it must be profitable to convert the land to another use, and this use is usually agricultural. In Thailand, for example, agricultural land increased between 1961 and 1988; during the same period, forest land decreased. This paper focuses on what, in equilibrium, determines the amount of land cleared for agriculture. The authors emphasize the quantitative impact of two forces--roads and population pressures--that increase the profitability of converting forest land to agriculture. As aerial maps show, development follows road networks. The magnitude of the impact of roads on commercial and subsistence agriculture depends on soil quality along the road. In this case the Thailand government undertook a road-building program in the Northeast section in the 1970s to encourage settlement of that region as a bulwark against Communist encroachment from Laos. Road building very likely spurred deforestation in the Northeast during the 1970s and 1980s, although the magnitude of its impact is not known. Thailand also experienced rapid population growth during this same period, which may have contributed to deforestation in two ways: the growing population demanding more food, increased the demand for agricultural land; and more importantly, in rural areas where other economic opportunities are limited and squatters are permitted on forest lands, a growing population increased the demand for land for subsistence agriculture. The authors conclude that population pressures play less of a role in deforestation than was found in earlier studies on Thailand. Affecting the amount of deforestation are other factors, such as the profitability of converting the land to another use, natural protection for forests like poor soil and steep slopes, and agricultural price variations.

Predicting the Location of Deforestation: The Role of Roads and Protected Areas in North Thailand

Using plot level data, we estimate a bivariate probit model to explain land clearing and the siting of protected areas in North Thailand in 1986. The model suggests that protected areas (national parks and wildlife sanctuaries together) did not reduce the likelihood of forest clearing; however, wildlife sanctuaries may have reduced the probability of deforestation. Road building, by reducing impedance-weighted distance to market, has promoted clearing, especially near the forest fringe. We simulate the impact of further road building to show where road building is likely to have greatest impact and where it is likely to threaten protected areas. (JEL Q23, Q28, R40)

Biofuels Impact on Crop and Food Prices: Using an Interactive Spreadsheet

This paper examines the effect that biofuels production has had on commodity and global food prices. The innovative contribution of this paper is the interactive spreadsheet that allows the reader to choose the assumptions behind the estimates. By allowing the reader to choose the country, time period, supply and demand elasticities, and the size of indirect effects we explicitly illustrate the sensitivity of the estimated effect of biofuels production on prices. Our best estimates suggest that the increase in biofuels production over the past two years has had a sizeable impact on corn, sugar, barley and soybean prices, but a much smaller impact on global food prices. ; Over the past two years (ending June 2008), we estimate that the increase in worldwide biofuels production pushed up corn, soybean and sugar prices by 27, 21 and 12 percentage points respectively. The countries that account for most of the upward pressure on these prices are the United States and Brazil. Our best estimates suggest that the increase in U.S. biofuels production (ethanol and biodiesel) pushed up corn prices by more than 22 percentage points and soybean prices (soybeans and soybean oil) by more than 15 percentage points, while the increase in EU biofuels production pushed corn and soybean prices up around 3 percentage points. Brazils increase in sugar-based ethanol production accounts for the entire rise in the price of sugar. ; Although biofuels had a noticeable impact on individual crop prices, they had a much smaller impact on global food prices. Our best estimate suggests that the increase in worldwide biofuels production over the past two years accounts for just over 12 percent of the rise in the IMFs food price index. The increase in U.S. biofuels production accounts for roughly 60 percent of this effect, while Brazil accounts for 14 percent and the EU accounts for 15 percent. The key take-away point is that nearly 90 percent of the rise in global food prices comes from factors other than biofuels.

U.S. Environmental Protection Agency Valuation of Surface Water Quality Improvements

Since 1982, the U.S. Environmental Protection Agency has used benefit-cost analysis to evaluate many of its surface water quality regulations. Early regulations were aimed at controlling conventional and toxic pollutants that were directly linked to highly visible water quality problems. More recent regulations have focused on “unconventional” water quality stressors or more subtle distinctions in water quality. While a number of national-scale water quality models have been used over the years, there has been less exploration of economic models to estimate benefits. This article addresses three issues that have been particularly challenging in estimating the benefits from water quality improvement: defining standardized measures of water quality improvement, measuring benefits arising from ecological protection and restoration, and measuring nonuse benefits.

The Use of Voluntary Approaches for Environmental Policymaking in the U.S.

The use of voluntary approaches to achieve environmental improvements has grown dramatically in the United States (U.S.) since they were first introduced thirteen years ago. As of 2004, there are over 50 voluntary programs in the U.S. at the federal level alone. These programs take a variety of forms, from large, cross-industry efforts to reduce global climate impacts to smaller, “boutique” efforts aimed at specific industrial sectors. Other voluntary approaches used in the U.S. include negotiated agreements, industry-initiated unilateral commitments, and state and regional voluntary initiatives, but these tend to be used less regularly.

A comparison of the monetized impact of IQ decrements from mercury emissions.

Objective The U.S. Environmental Protection Agency (EPA) reports that the upper bound of benefits from removing mercury emissions by U.S. power plants after implementing its Clean Air Interstate Rule (CAIR) is

Risk assessment for benefits analysis: framework for analysis of a thyroid-disrupting chemical.

210 million per year. In contrast, Trasande et al. [Environ Health Perspect 113:590–596 (2005)] estimated that American power plants impose an economic cost of

Incremental CH4 and N2O mitigation benefits consistent with the US Government's SC-CO2 estimates

1.3 billion due to mercury emissions. It is impossible to directly compare these two estimates for a number of reasons, but we are able to compare the assumptions used and how they affect the results. Data Sources and Data Extraction We use Trasande’s linear model with a cord/maternal blood ratio of 1.7 and calculate health effects to children whose mothers had blood mercury levels ≥ 4.84 μg/L. Data Synthesis We introduce the assumptions that the U.S. EPA used in its Clean Air Mercury Rule (CAMR) analysis and discuss the implications. Using this approach, it is possible to illustrate why the U.S. EPA assumptions produce a lower estimate. Conclusions The introduction of all the U.S. EPA assumptions, except for those related to discounting, decreases the estimated monetized impact of global anthropogenic mercury emissions in the Trasande model by 81%. These assumptions also decrease the estimated impact of U.S. sources (including power plants) by almost 97%. When discounting is included, the U.S. EPA assumptions decrease Trasande’s monetized estimate of global impacts by 88% and the impact of U.S. power plants by 98%.

Linking Economics and Risk Assessment

Benefit-cost analysis is of growing importance in developing policies to reduce exposures to environmental contaminants. To quantify health benefits of reduced exposures, economists generally rely on dose-response relationships estimated by risk assessors. Further, to be useful for benefits analysis, the endpoints that are quantified must be expressed as changes in incidence of illnesses or symptoms that are readily understood by and perceptible to the layperson. For most noncancer health effects and for nonlinear carcinogens, risk assessments generally do not provide the dose-response functions necessary for economic benefits analysis. This article presents the framework for a case study that addresses these issues through a combination of toxicology, epidemiology, statistics, and economics. The case study assesses a chemical that disrupts proper functioning of the thyroid gland, and considers the benefits of reducing exposures in terms of both noncancer health effects (hypothyroidism) and thyroid cancers. The effects are presumed to be due to a mode of action involving interference with thyroid–pituitary functioning that would lead to nonlinear dose response. The framework integrates data from animal testing, statistical modeling, human data from the medical and epidemiological literature, and economic methodologies and valuation studies. This interdisciplinary collaboration differs from the more typical approach in which risk assessments and economic analyses are prepared independently of one another. This framework illustrates particular approaches that may be useful for expanded quantification of adverse health effects, and demonstrates the potential of such interdisciplinary approaches. Detailed implementation of the case study framework will be presented in future publications.

How the Location of Roads and Protected Areas Affects Deforestation in North Thailand

Benefit–cost analysis can serve as an informative input into the policy-making process, but only to the degree it characterizes the major impacts of the regulation under consideration. Recently, the US, amongst other nations, has begun to use estimates of the social cost of CO2 (SC-CO2) to develop analyses that more fully capture the climate change impacts of GHG abatement. The SC-CO2 represents the aggregate willingness to pay to avoid the damages associated with an additional tonne of CO2 emissions. In comparison, the social costs of non-CO2 GHGs have received little attention from researchers and policy analysts, despite their non-negligible climate impact. This article addresses this issue by developing a set of social cost estimates for two highly prevalent non-CO2 GHGs, methane and nitrous oxide. By extending existing integrated assessment models, it is possible to develop a set of social cost estimates for these gases that are consistent with the SC-CO2 estimates currently in use by the US federal government.Policy relevanceWithin the benefit–cost analyses that inform the design of major regulations, all Federal agencies within the US Government (USG) use a set of agreed upon SC-CO2 estimates to value the impact of CO2 emissions changes. However, the value of changes in non-CO2 GHG emissions has not been included in USG policy analysis to date. This article addresses that omission by developing a set of social cost estimates for two highly prevalent non-CO2 GHGs, methane and nitrous oxide. These new estimates are designed to be compatible with the USG SC-CO2 estimates currently in use and may therefore be directly applied to value emissions changes for these non-CO2 gases within the benefit–cost analyses used to evaluate future policies.