Thirty-three brothels in rural and small-town Nevada, which contain between 225 and 250 prostitutes, are legal or openly tolerated and strictly controlled by state statute, city and county ordinances, and local rules. Twenty-two of the brothels are in places with populations between 500 and 8,000, and the remaining eleven are in rural areas. The legal and quasi-legal restrictions placed on prostitutes severely limit their activities outside brothels. These restrictions in conjunction with historical inertia, perceived benefits of crime and venereal disease control, and the good image of madams contribute to widespread positive local attitudes toward brothel prostitution. Interactions between clients and prostitutes in brothel parlors are also restricted and limited to a few basic types which are largely determined by entrepreneurial philosophy. KEY WORDS : Nevada, Political geography, Prostitution, Restricted activity spaces.

ANNALS of the Association of American Geographers

This article, which synthesizes the results of more than 140 economic models analyzing the causes of tropical deforestation, raises significant doubts about many conventional hypotheses in the debate about deforestation. More roads, higher agricultural prices, lower wages, and a shortage of off-farm employment generally lead to more deforestation. How technical change, agricultural input prices, household income levels, and tenure security affect deforestation-if at all-is unknown. The role of macroeconomic factors such as population growth, poverty reduction, national income, economic growth, and foreign debt is also ambiguous. This review, however, finds that policy reforms included in current economic liberalization and adjustment efforts may increase the pressure on forests. Although the boom in deforestation modeling has yielded new insights, weak methodology and poor-quality data make the results of many models questionable.

Rethinking the causes of deforestation: lessons from economic models.

Rethinking the Causes of Deforestation: Lessons from Economic Models

As international concern over tropical deforestation has grown over the last ten years, researchers have sought to understand the causes of deforestation and possible solutions using quantitative economic models. This book reviews the results and methodology of over 150 of these models and synthesizes the main lessons that can be learned from them. Higher agricultural prices, lower wages, less off-farm employment, and more roads generally lead to more deforestation. Major doubts remain on the impact of technological change, agricultural input prices, household incomes, and tenure security. The role of macro level factors such as population growth, poverty reduction, national income levels, economic growth and foreign debt is still largely uncertain. While the boom in deforestation modeling has yielded new insights, many model results should be regarded with caution because of poor data quality and methodological weaknesses. In particular, the book finds most multi country regression models to be of limited value. It recommends a shift in future research towards household and regional level studies, instead of the current emphasis on national and multi-country studies.

http://www.mekonginfo.org/assets/midocs/0002807-environment-economic-models-of-tropical-deforestation-a-review.pdf

Economic models of tropical deforestation: a review.

Using the framework of the Land Use and Cover Change (LUCC) Science/Research Plan this study takes 152 studies of deforestation in different regions of varying size from around the tropics and analyses them to assess how important different causes of deforestation really are. It claims to be the first which quantifies the impact of cultural or socio-political driving forces upon deforestation.The study gives a brief rationale why subnational – and not country-wide – case study evidence constitutes an important tool in LUCC and outlines the analytical concept of proximate and underlying causes of land change used in LUCC research. The authors then attempt to generalize results across regions or broad geographical entities (Africa, Asia, Latin America). Results are presented in three sections:frequency of occurrence of broad clusters of causes and more specific activities (or actor-driven processes) associated with tropical deforestation. patterns of causality (interlinkages) both at the proximate and underlying levels (and between them), in terms of the mode of connection of causesvariations of results other than by broad geographical entities – i.e., by forest type, area size, topography, spatial pattern and process at work, deforestation rate, and poverty- versus capital-driven deforestation. Finally the paper compares its findings against other empirical evidence on tropical deforestation and conclusions are drawn.Empirical findings versus prevailing explanationsCauses and drivers of tropical deforestation cannot be reduced to a single variable, or to a few variables even. Rather, the interplay of several proximate as well as underlying factors drive deforestation in a synergetic way. While the expansion of cropped land and pasture is clearly the most important proximate cause of tropical deforestation, shifting cultivators are not always the key agentsChain-logical causation in the form of simple tandems (or 2-factor chains) underlies about two thirds of the proximate as well as underlying causes. On average, 4 to 5 tandems are associated with each case of tropical deforestation. Rather than single or direct fundamental causes, underlying driver tandems were identified to be most important. These are mainly economy-, policy and institution - and culture - driven tandems impacting upon the proximate level Population pressure in the form of natural increases in number of population due to high fertility is clearly not the major underlying driving force. Rather, inmigration into forested (not natural increase in densely populated) areas plays an important role in cases of frontier colonization. In all cases, however, population does not operate as a single force but is interlinked with other underlying factors. With view on variations of cause frequencies and causality patterns, there is empirical indication that in cases with high rates of annual deforestation pre-disposing biophysical factors are at work or shape the pattern of deforestation.The explanatory power of PAT variables (population, aff luence, technology) is astonishinglypoor. This model obviously fails to consider policy and institutional factors shaping market opportunities as powerful explanatory factors of tropical deforestation.The multiple factors intervening in tropical deforestation also make it particularly difficult to develop generic and widely applicable policies that best attempt to control the process. Many land-use policies are underlain by simplifications on the drivers of change. Such simplification suggest simple technical solutions and sometimes may serve the interests of critical groups (Lambin et al., 2001). From the results of the meta-analysis it is clear that any universal policy or global attempt to control deforestation (e.g., through poverty alleviation) is doomed to failure.Implications for modelling and controlling deforestationDeforestation is a complex, multiform process which cannot be represented by a mechanistic approach. This has implications for modelling as many of the simulation models of land-use change tend to be mechanistic. The case study evidence examined in this meta-analysis clearly suggests that we still lack an overarching theory to encompass the different factors which intervene in the processes of deforestation.Empirical evidence shows that the complexity and diversity of driving factors of deforestation is reduced when looking at specific processes – e.g., subsistence agriculture, commercial agriculture, colonisation activities or logging activities – and specific geographic situations – i.e., frontier areas, roadside areas, peri-urban areas.The overall dominance of the broad cluster of agricultural expansion is well perceived in the modelling of tropical deforestation. However, this is not always the case when it comes more specific agricultural uses and other than agricultural land uses such as logging.Implications for future case study comparisonsThe LUCC research framework proved to be a fruitful platform from which to proceed to develop a general understanding of the drivers of land use and land cover change.Concerning regional representation of case studies in future comprehensive comparisons, the study found that weighting bias in our meta-analysis was low, but also found indication that future work will have to include considerably more African less Asian and about the same number of Latin American cases, Concerning weighting bias in terms of agents involved in the process of deforestation, a better understanding of logging company behaviour and/or industrial forestry plantation activities is requiredFinally the study found a systematic comparison of local-scale case studies is an extremely productive methodology.[authors]

What drives tropical deforestation?: a meta-analysis of proximate and underlying causes of deforestation based on subnational case study evidence

Urban Household Energy, Poverty, and the Environment The Urban Energy Transition Household Fuel Choice and Consumption Energy and Equity: the Social Impact of Energy Policies The Urban Energy Transition and the Environment The Energy Transition in Hyderabad, India: a Case Study Toward More Effective Urban Energy Policies

The Urban Household Energy Transition: Social and Environmental Impacts in the Developing World

Household fuelwood demand and supply in Nepal's Tarai and Mid-Hills: Choice between cash outlays and labor opportunity

Forest conversion by agricultural households is the leading cause of deforestation. Yet we know little about agricultural household use of forest and tree products. This article measures household production of and demand for fuelwood and fuel substitutes in two districts in Nepal. Women play a larger role in collection in the district dependant on production from common forestlands. Men and agricultural capital are more important inputs in the district dependant on production from private lands. The article also measures demand elasticities for fuelwood, combustible agricultural residues, and improved stoves (a technological substitute), each by household income group. All price and income demand elasticities are less than one. The substitution elasticities between residues and fuelwood are less than one. Residues are more important substitutes for low income households and improved stoves are more important substitutes for high income households.

Joint production and consumption in traditional households: Fuelwood and crop residues in two districts in Nepal

This book examines the experience of China's forestry sector with respect to the full set of forest and nonforest policy reforrms introduced since 1978. The lessons of this book are important for China, and for the rest of the world as well. For China the analyses in each chapter provides rigorous evidence on those policies that have worked and on how well the have worked. The book consists of 10 chapters: 1. Hyde, W.F., Jintao Xu, Belcher, B. Introduction and Appendix table: policy reform in China's forestry; 2. Liu Dachang, Edmund, D. Devolution as a means of expanding local forest management in South China: lessons from the past 20 years; 3. Jinlong Liu, Landell-Mills, N. Taxes and fees in the Southern collective forest region; 4. Runsheng Yin. Central characteristics of reform: measures of the effects of improved property rights, a stable policy environment, and environmental protection; 5. Daowei Zhang. Policy reform and investment in forestry; 6. Rozelle, S., Jikun Huang, Benziger, V. Forest exploitation and protection in reform China: assessing the impacts of policy and economic growth; 7. Yaoqi Zhang, Uusivuori, J., Kuuluvainen, J., Kant, S. Deforestation and reforestation in Hainan: roles of markets and institution; 8. Ruiz-Perez, M., Belcher, B., Maoyi Fu, Xiaosheng Yang. Forestry, poverty, and rural development: perspectives from the bamboo sector; 9. Sayer, J.A., Changjin Sun. Impacts of policy reforms on forest environments and biodiversity; 10. Hyde, W.F., Jintao Xu, Belcher, B., Runsheng Yin, Jinlong Liu. Conclusions and policy implications.

China's forests: global lessons from market reforms.

This article uses household data from Nepal's two major populated regions (and 27 of 59 districts within those regions) to examine fuelwood consumption and production. In contrast with a purely market assessment, household analysis includes production which is consumed in the producing household. The household regressions yield coefficients and elasticities that are very different from and more reliable than a comparable assessment of market demand and supply. Household results generally support the hypotheses that expenditures on fuelwood are a small share of total household activity and that fuelwood is not sufficiently scarce to alter household behaviour. Fuelwood is sufficiently scarce, however, to alter behaviour for those households in the hill region that do not participate in market exchange. These households may be the best targets for public market interventions designed to alter fuelwood supply and deforestation.

William F. Hyde

Papers

The Urban Household Energy Transition: Social and Environmental Impacts in the Developing World

Household fuelwood demand and supply in Nepal's Tarai and Mid-Hills: Choice between cash outlays and labor opportunity

Joint production and consumption in traditional households: Fuelwood and crop residues in two districts in Nepal

China's forests: global lessons from market reforms.

Nepali fuelwood production and consumption: Regional and household distinctions, substitution and successful intervention