• Energy Research

Abstract This paper jointly evaluates the greenhouse gas emissions and economic impacts from producing biofuels in Tanzania. Sequentially-linked models capture natural resource constraints; emissions from land use change; economywide growth linkages; and household poverty. Results indicate that there are economic incentives to convert unused lands to sugarcane-ethanol production, but only grasslands (not forests) have a reasonable carbon payback period. There are also strong socioeconomic reasons to involve smallholders in feedstock production in order to reduce rural poverty, especially since our results indicate that biofuels have little effect on food production. Yet smallholders require more land than large-scale plantations and so face more binding natural resource and emissions constraints. Overall, environmental constraints alter the socioeconomically optimal biofuel strategy for Tanzania by limiting potential poverty reduction. Unlike previous studies, our integrated assessment suggests that a mixed farming system with greater emphasis on large-scale plantations is more appropriate for producing sugarcane-ethanol in Tanzania.

AbstractSouth Africa is considering introducing a carbon tax to reduce greenhouse gas emissions. Following a discussion of the motivations for considering a carbon tax, we evaluate potential impacts using a dynamic economywide model linked to an energy sector model including a detailed evaluation of border carbon adjustments. Results indicate that a phased-in carbon tax of US$30 per ton of CO2 can achieve national emissions reductions targets set for 2025. Relative to a baseline with free disposal of CO2, constant world prices and no change in trading partner behavior, the preferred tax scenario reduces national welfare and employment by about 1.2 and 0.6 percent, respectively. However, if trading partners unilaterally impose a carbon consumption tax on South African exports, then welfare/employment losses exceed those from a domestic carbon tax. South Africa can lessen welfare/employment losses by introducing its own border carbon adjustments. The mode for recycling carbon tax revenues strongly influences distributional outcomes, with tradeoffs between growth and equity.

AbstractWe estimate the carbon intensity of industries, products and households in South Africa using data from a high resolution supply‐use table. Direct and indirect carbon usage is measured using multiplier methods that capture inter‐industry linkages and multi‐product supply chains. Carbon intensity is found to be high for exports but low for major employing sectors. Middle‐income households are the most carbon‐intensive consumers. These results suggest that carbon pricing policies (without border tax adjustments) would adversely affect export earnings, but should not disproportionately hurt workers or poorer households. Seven percent of emissions arise through marketing margins, implying that carbon pricing should be accompanied by supporting public policies and investments.

Abstract Biofuels could offer new economic opportunities for low-income countries. We use a recursive dynamic computable general equilibrium model of Tanzania to evaluate different biofuels production options and estimate their impacts on growth and poverty. Our results indicate that maximizing the poverty-reducing effects of biofuels production in countries like Tanzania will require engaging and improving the productivity of smallholder farmers. Evidence shows that cassava-based ethanol production is more profitable than other feedstock options. Cassava also generates more “pro-poor” growth than sugarcane-based systems. However, if smallholder yields can be improved rather than expanding cultivated land, then both sugarcane and cassava out-grower schemes generate similar pro-poor outcomes. We conclude that, in so far as the public investments needed to establish a biofuels industry are consistent with other development needs, then producing biofuels will enhance economic development in countries like Tanzania.

AbstractEconomy‐wide and hydrological‐crop models are combined to assess the economic impacts of historical climate variability and future anthropogenic climate change in Zambia. Accounting for uncertainty, results indicate that, on average, current variability reduces gross domestic product by 4% over a 10‐year period and pulls 2% of the population below the poverty line. Socioeconomic impacts are much larger during major drought years, thus underscoring the importance of extreme weather events in determining climate damages. Climate change scenarios draw on projections for 2025. Results indicate that, in the worst case scenario, damages caused by climate change are half the size of those from current variability. The paper concludes that current climate variability, rather than climate change, will remain the more binding constraint on economic development in Zambia, at least over the next few decades.

Abstract We apply a probabilistic approach to the evaluation of climate change impacts in Mozambique. We pass a distribution of climate shocks through a series of structural biophysical models. The resulting joint distributions of biophysical outcomes are then imposed on a dynamic economywide model. This framework produces distributions of economic impacts of climate change thus identifying an explicit range of potential economic outcomes and associating probability levels with given sets of outcomes. For example, we find that the economy of Mozambique may be up to 13 % smaller in 2050 compared with a fictional no climate change scenario (and assuming global policy fails to constrain emissions growth). The probability of gross domestic product (GDP) declines of greater than 10 % is relatively small at 2.5 %. These large declines are principally the result of dramatic reductions in flood return periods. To 2050, about 70 % of future climates result in GDP losses of between zero and five percent. In about 9 % of cases, climate change shocks result in higher GDP outcomes. We conclude that, relative to current practice, this structural probabilistic approach provides (i) significantly more information to decision-makers, (ii) more detailed insight into the importance of various impact channels, and (iii) a more holistic and comprehensive approach for evaluating adaptation options.

We adopt a multi-sectoral approach and consider the full range of climate projections. Biophysical damages are translated into economic costs using a dynamic economy-wide model. Our results indicate that the negative impacts on agriculture and roads are modest to 2050. Larger costs are caused by rising sea levels and cyclone strikes. Overall, climate change is likely to reduce national income by between one and two percent by 2050 (relative to a historical baseline). Damages double under more extreme projections. Our findings suggest that there are net benefits from selected pre-emptive actions though careful consideration of opportunity costs is required.