This study examines conservation effects of wildlife trade using demand and supply data from caged-bird markets in Sumatra, Indonesia. When consumers have a strong preference for species rarity, trade could result in wildlife overexploitation and species extinction. Results from a choice experiment show that buyers of caged birds indeed value species rarity. However, not all rare species are equally preferred. Species that are frequently traded lose their rarity value, even if rare in the wild. Analysis of time-series data collected from traders over a period of 20 months between 2013 and 2015 reveals an inelastic supply function for rare species, with market arrivals being insensitive to price changes. This may be due to a declining stock of rare species in the wild. Bird trade together with habitat loss can lead to extinction of a number of rare species in Indonesia. Several policy approaches on regulating caged-bird markets are discussed.

The non-market values of changes in grassland management stimulated by changes in policies were estimated by choice modeling. Four-hundred twenty-seven residents of Hohhot city in Inner Mongolia were selected using the popular mobile phone application WeChat. Conditional logit (CL) and random parameter logit (RPL) models were estimated to analyze the preference of respondents for environmental and social attributes. Based on the preferred RPL model, the average per household willingness to pay over 10 years for the best policy outcome scenarios was estimated to be CNY892 (US$141). The total willingness to pay for this policy change, extrapolated to the population of Hohhot, was CNY208 million (US$33 million). The findings suggest that environmental and social outcomes are valuable to Chinese residents of a regional urban center. Such values should be viewed as a public financial base for market-based mechanisms for grassland protection both in China and internationally. WeChat proved to be convenient but required the application of extrapolation caveats relating to sample representation.

The design of a Payment for Environmental Services (PES) scheme that involves setting a ‘pseudo market price’ per unit of environmental service requires the estimation of demand and supply. This paper presents the results of discrete choice experiments aimed at estimating the demand for environmental and social services generated by a wildlife protection PES scheme in two protected areas in Lao PDR. The discrete choice experiments targeted international tourists sampled at Vientiane airport and the urban Lao population sampled in Vientiane City as potential buyers of the environmental and social services provided by the PES scheme. The survey was customised to a developing country context to address diversity in respondents' literacy levels, language limitations of the interviewers, socio-cultural conventions, and limited trust in confidentiality and anonymity of the survey process. The marginal benefits of the environmental services so estimated were used to inform the development of a PES scheme.

This paper measures the economic impacts of Brazil's climate mitigation strategies contained in its Nationally Determined Contribution (NDC). To do so, we employ the computable general equilibrium MIT Economic Projection and Policy Analysis model and simulate alternative carbon pricing scenarios (sectoral versus economy-wide carbon markets), set to achieve the country's overall emissions targets announced under the Paris Agreement. The results show relatively cheap emissions reductions from land-use changes and agriculture in the short run: the cost of the Brazilian NDC is predicted to be only 0.7 per cent of GDP in 2030. Further efforts to reduce carbon emissions beyond 2030 would require policy changes, since all the potential emissions reductions from deforestation would be finished and the capacity to expand renewable energy sources would be constrained. In this case, an economy-wide carbon pricing system would help substantially to avoid higher compliance costs.

We study the impact of a severe drought on children's educational outcomes in rural Maharashtra, a state in central India. Using pooled cross section data on children's test scores, we employ a difference-in-differences methodology to estimate the impact. We find that the drought caused a decline of 4.14 per cent in math scores and 2.67 per cent in reading scores of affected children. We also study heterogeneity in the impact by gender, age, parents' schooling, and household wealth, finding evidence in support of an income effect whereby households with limited means to smooth consumption disinvest in their children in response to the drought.