Lise Tole

Is there an environmental Kuznets curve for deforestation

Abstract This paper examines the relationship between deforestation and gross domestic product (GDP) per capita; in particular, whether an inverted-U relationship (indicative of worsening then improving deforestation) exists between them. We note that previous work has used models with restrictive assumptions, and recommend a more flexible random coefficients specification which allows for a greater degree of cross-country heterogeneity. Empirical results using data for 76 developing countries between 1961–1992 suggest that the inverted-U shaped relationship observed in other studies does not appear to be an empirical regularity with our less restrictive specification. Statistical tests indicate that this specification is supported by the data. We argue that such results are not surprising in view of the wide diversity of physical and social characteristics that exist across countries.

Measuring the health effects of air pollution: to what extent can we really say that people are dying from bad air?

Estimation of the effects of environmental impacts is a major focus of current theoretical and policy research in environmental economics. Such estimates are used to set regulatory standards for pollution exposure; design appropriate environmental protection and damage mitigation strategies; guide the assessment of environmental impacts; and measure public willingness to pay for environmental amenities. It is a truism that the effectiveness of such strategies depends crucially on the quality of the estimates used to inform them. However, this paper argues that in respect to at least one area of the empirical literature - the estimation of the health impacts of air pollution using daily time series data - existing estimates are questionable and thus have limited relevance for environmental decision-making. By neglecting the issue of model uncertainty - or which models, among the myriad of possible models researchers should choose from to estimate health effects - most studies overstate confidence in their chosen model and underestimate the evidence from other models, thereby greatly enhancing the risk of obtaining uncertain and inaccurate results. This paper discusses the importance of model uncertainty for accurate estimation of the health effects of air pollution and demonstrates its implications in an exercise that models pollution-mortality impacts using a new and comprehensive data set for Toronto, Canada. The main empirical finding of the paper is that standard deviations for air pollution-mortality impacts become very large when model uncertainty is incorporated into the analysis. Indeed they become so large as to question the plausibility of previously measured links between air pollution and mortality. Although applied to the estimation of the effects of air pollution, the general message of this paper - that proper treatment of model uncertainty critically determines the accuracy of the resulting estimates - applies to many studies that seek to estimate environmental effects.

Deforestation, distribution and development

This paper investigates the role played by distributional factors in mediating the effects of growth and development on forest depletion in tropical developing countries. A key finding of the paper is that the distributional profile of a country significantly determines whether economic development will have either a positive or a negative effect on the rate of forest loss. In countries where levels of inequality are high, development will tend to exacerbate deforestation rates while in countries where distributional profiles are more egalitarian, the negative effects of growth and development on forest cover will be ameliorated.

Reforms from the Ground Up: A Review of Community-Based Forest Management in Tropical Developing Countries

After an initial burst of enthusiasm in the 1990s, community-based forest management (CBFM) is increasingly being viewed with a critical eye. Evidence suggests that many programs have failed to promote their stated objectives of sustainability, efficiency, equity, democratic participation and poverty reduction. A large volume of academic literature now exists on CBFM, examining both the success and failure of such initiatives in a wide variety of countries. Through analysis of key themes, concepts and issues in CBFM, this article provides a review of CBFM initiatives in tropical developing countries for policymakers, practitioners and planners wishing to gain an understanding of this wide-ranging, interdisciplinary academic literature. The article identifies key institutions and incentives that appear to significantly affect the success or failure of CBFM initiatives. In particular, it reports that consideration of institutional and socioeconomic factors along with personal characteristics of key stakeholders such as beliefs, attitudes, financial resources and skills are important determinants of CBFM outcomes. However, local incentive structures also appear to be important. There is increasing recognition in the literature of the need to consider the conditions under which local politicians entrusted with carrying out CBFM initiatives will deem it worthwhile to invest their scarce time and resources on environmental governance.

An Investigation of Thresholds in Air Pollution-Mortality Effects

In this paper we introduce and implement new techniques to investigate threshold effects in air pollution-mortality relationships. Our key interest is in measuring the dose-response relationship above and below a given threshold level where we allow for a large number of potential explanatory variables to trigger the threshold effect. This is in contrast to existing approaches that usually focus on a single threshold trigger. We allow for a myriad of threshold effects within a Bayesian statistical framework that accounts for model uncertainty (i.e. uncertainty about which threshold trigger and explanatory variables are appropriate). We apply these techniques in an empirical exercise using daily data from Toronto for 1992-1997. We investigate the existence and nature of threshold effects in the relationship between mortality and ozone (O3), total particulate matter (PM) and an index of other conventionally occurring air pollutants. In general, we find the effects of our considered pollutants on mortality to be statistically indistinguishable from zero with no evidence of thresholds. The one exception is ozone, for which results present an ambiguous picture. Ozone has no significant effect on mortality when we exclude threshold effects from the analysis. Allowing for thresholds we find a positive and significant effect for this pollutant when the threshold trigger is the average change in ozone two days ago. However, this significant effect is not observed after controlling for PM.

Measuring differential forest outcomes: A tale of two countries

Abstract This paper empirically analyzes the growth/deforestation trajectories of El Salvador and Puerto Rico, two Latin American tropical developing countries which have witnessed widely different economic and forest scenarios since the early 1960s. Although both countries began the period with relatively abundant forest resources and similar levels of development, only Puerto Rico witnessed an increase in forest cover during this period. After briefly discussing each countrys respective socioeconomic and land use changes, the paper empirically measures possible factors mediating these different deforestation outcomes. Empirical results presented here suggest that Puerto Ricos forest success has depended significantly on its rapid economic growth and development, in particular, its high levels of industrialization, social welfare provision, and domestic investment. Having successfully avoided the scarcity-induced forms of forest exploitation that have destroyed El Salvadors forests, Puerto Rico must now devote the considerable resources generated by this growth to protecting its forest cover from the negative effects of unrestricted urban and industrial development.

Habitat loss and anthropogenic disturbance in Jamaica's Hellshire Hills area

This study provides empirical assessments of the magnitude of human pressures on forest habitat in Jamaicas Hellshire Hills. The Hellshire Hills represents an outstanding example of the Caribbean regions dry limestone forests. Approximately 160 km2 in area, the Hellshire Hills is home to a unique and rich biodiversity, including the critically endangered Jamaican Iguana (Cylcura collei). The areas biodiversity is under increasing threat from deforestation from subsistence driven encroachment. Using deforestation as a spatial indicator of habitat loss, the study derives satellite based estimates of the rate of habitat destruction within and immediately outside the area. The underlying human driving forces in this destruction are analyzed in a regression analysis of key socio-economic indicators that adusts for these locational differences. Results suggest that immiserating pressures on species habitat, particularly outside the area, are greater than anywhere else on the island. Simulations of species loss and edge-induced disturbances to species habitat also indicate that the potential impacts of forest conversion may be substantial and extend well beyond the areas boundaries. Together, the studys results highlight the intrinsic vulnerablity of the Hellshire Hills to outside disturbance. In particular, they raise doubts about the potential of the area (which has been accorded protected status within the recently established Portland Bight Protected Area) to provide for the long-term preservation and viability of the areas species. It is concluded that appropriate reserve design and species protection will require the collection of detailed empirical data on species diversity, numbers, habitat requirements, and spatial distribution. However, before this information can be collected priorities for biodiversity conservation must be set. Costs and benefits of conversation must also be assessed within the overall context of an integrated rural development plan for the area.

Air pollution, economic activity and respiratory illness: Evidence from Canadian cities, 1974-1994

Many studies have reported a relationship between urban air pollution levels and respiratory health problems. However, there are notable variations in results, depending on modeling approach, covariate selection, period of analysis, etc. To help clarify these factors we compare and apply two estimation approaches: model selection and Bayesian model averaging, to a new data base on 11 Canadian cities spanning 1974-1994. During this interval pollution levels were typically much higher than the present. Our data allow us to compare monthly hospital admission rates for all lung diagnostic categories to ambient levels of five common air contaminants, while controlling for income, smoking and meteorological covariates. In the most general specifications we find the here-observed health effects of air pollution are very small and insignificant, with signs that are typically opposite to conventional expectations. Smoking effects are robust across specifications. Considering the fact that we are examining an interval of comparatively high air pollution levels, and the contrast between our results and those that have been published previously, we conclude that extra caution should be applied to results estimated on short and/or recent data panels, and to those that do not control for model uncertainty and socioeconomic covariates.

A quantitative analysis of the population-land clearnance-land inequality nexus

This paper provides a quantitative investigation of the population-land inequality-land clearance nexus. Drawing on the literature on farmer optimization behaviour, the study formalizes and empirically tests a model of population-induced agricultural land clearance. The model makes several assumptions about this process: (a) The rate at which agricultural land is brought into production due to rising population pressures accelerates with the level of inequality in access to land, (b) Egalitarian systems have a greater capacity to absorb rising numbers of people per unit of land area and, thus, will have lower rates of agricultural land clearance than higher ones and (c) Irrespective of its degree of egalitarianism, the capacity of any system to hold people in one place will eventually break down once a critical population threshold is reached. Due to their lower population absorptive capacity, this level will be reached sooner under unequal systems of land distribution. Thus, the model also hypothesizes that the stimulatory impact of population growth on the demand for new land will exhibit a non-linear threshold pattern. For the farmer, the decision to clear a new plot of land will reflect these population-inequality interactions: Earnings from farming in settled areas will tend to fall as population densities and inequality in access to land increase. Time series results confirm that rural population growth is a significant factor driving agricultural land clearance in many of the 59 developing countries of our sample. Results also suggest that this rate of clearance is largest in countries with highly inegalitarian patterns of distribution. In contrast, cross-sectional regression results do not suggest any direct role for land inequality in population-agricultural land use outcomes. Contrary to the model’s assumption that this relationship should follow a non-linear threshold pattern, cross-sectional results also find no evidence that the absorptive capacity of highly densely populated land systems has been reached on average. However, they do provide support for an indirect linear relationship: Population induced agricultural land clearance is significantly magnified as inequality in access to land increases. Drawing on the empirics of the growth-inequality literature, the study suggests that this magnifying role may be linked to inequality’s impact on the assets of the poor. That is, by undermining the capacity of the rural poor to make productive investments in the land base, inequality in land distribution mediates population pressures in a way that affects both the quality and quantity of assets available to the poor to raise incomes, invest in skills accumulation, and spur demand in the rural economy as a whole.

Population and poverty in Jamaican deforestation: integrating satellite and household census data

This study uses MSS data to derive sub-national level deforestation rates at the constituency administrative level for Jamaica for 1987 and 1992. It then investigates the role of poverty and population in driving forest loss during this period by linking these estimates in a GIS with constituency level demographic and socioeconomic census data for the island. OLS regression results support the importance of population pressures and poverty in driving the destruction of Jamaicas forests and the relative contribution to deforestation of their various measures are noted and discussed. In addition to providing information on Jamaicas deforestation attributes, the study demonstrates how remotely sensed data can be used in conjunction with household census data to derive information on human-forest interactions at the sub-national level. A small simulation experiment based on regression results using key variables suggests that under any scenario, the impacts of key social and demographic changes on Jamaicas remaining forest cover may be substantial by the year 2010.