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Abstract This paper reports meta-regressions of substitution elasticities between greenhouse gas (GHG) polluting and nonpolluting inputs in agricultural production, which is the main feedstock source for biofuel in the U.S. We treat energy, fertilizer, and manure collectively as the “polluting input” and labor, land, and capital as nonpolluting inputs. We estimate meta-regressions for samples of Morishima substitution elasticities for labor, land, and capital vs. the polluting input. Much of the heterogeneity of Morishima elasticities can be explained by type of primal or dual function, functional form, type and observational level of data, input categories, number of outputs, type of output, time period, and country categories. Each estimated long-run elasticity for the reference case, which is most relevant for assessing GHG emissions through life-cycle analysis, is greater than 1.0 and significantly different from zero. Most predicted long-run elasticities remain significantly different from zero at the data means. These findings imply that life-cycle analysis based on fixed proportion production functions could provide grossly inaccurate measures of GHG of biofuel.

This paper introduces a nonlinear certainty‐equivalent approximation method for dynamic stochastic problems. We first introduce a novel, stable, and efficient method for computing the decision rules in deterministic dynamic economic problems. We use the results as nonlinear and global certainty‐equivalent approximations for solutions to stochastic problems, and compare their accuracy to the common linear and local certainty‐equivalent methods. Our examples demonstrate that this method can be applied to solve high‐dimensional problems with up to 400 state variables with acceptable accuracy. This method can also be applied to solve problems with inequality constraints. These features make the nonlinear certainty‐equivalent approximation method suitable for solving complex economic problems, where other algorithms, such as log‐linearization, fail to produce a valid global approximation or are far less tractable. New Keynesian DSGE model competitive equilibrium parallel computing sparse grid approximation real business cycle model C61 C63 C68 E31 E52

Abstract The US shale boom has intensified interest in how the expanding oil and gas sector affects local economic performance. Research has produced mixed results and has not compared how energy shocks differ from equal-sized shocks elsewhere in the economy. What emerges is that the estimated impacts of energy development vary by region, empirical methodology, as well as the time horizon that is considered. This paper captures these dimensions to present a more complete picture of energy boomtowns. Utilizing US county data, we estimate the effects of changes in oil and gas extraction employment on total employment growth as well as growth by sector. We compare this to the effects of equal-sized shocks in the rest of the economy to assess whether energy booms are inherently different. The analysis is performed separately for nonmetropolitan and metropolitan counties using instrumental variables. We difference over 1-, 3-, 6-, and 10-year time periods to account for county-fixed effects and to assess responses across different time horizons. The results show that in nonmetro counties, energy sector multiplier effects on total county employment first increase up to 6-year horizons and then decline for 10-year horizons. We also observe positive spillovers to the non-traded goods sector, while spillovers are small or negative for traded goods. In metro counties, there are no significant effects on total employment, although positive spillovers are present in some sectors. Yet, equal-sized shocks in the rest of the economy produce more jobs on average than oil and gas shocks, suggesting that policymakers should seek more diversified development.

More than40%of US grain is used for energy due to the Renewable Fuel Mandate (RFS). There are no studies of the global distributional consequences of this purely domestic policy. Using micro‐level survey data, we trace the effect of the RFS on world food prices and their impact on household level consumption and wage incomes in India. We first develop a partial equilibrium model to estimate the effect of the RFS on the price of selected food commodities—rice, wheat, corn, sugar, and meat and dairy, which together provide almost70%of Indian food calories. Our model predicts that world prices for these commodities rise by 8–16%due to the RFS. We estimate the price pass‐through to domestic Indian prices and the effect of the price shock on household welfare through consumption and wage incomes. Poor rural households suffer significant welfare losses due to higher prices of consumption goods, which are regressive. However, they benefit from a rise in wage incomes, mainly because most of them are employed in agriculture. Urban households also bear the higher cost of food, but do not see a concomitant rise in wages because only a small fraction of them work in food‐related industries. Welfare losses are greater among urban households. However, more poor people in India live in villages, so rural poverty impacts are larger in magnitude. We estimate that the mandate leads to about 25 million new poor: 21 million in rural and 4 million in the urban population.

The optimal response to a potential productivity shock which becomes more imminent with global warming is to have carbon taxes to curb the risk of a calamity and to accumulate precautionary capital to facilitate smoothing of consumption. This paper investigates how differences between regions in terms of their vulnerability to climate change and their stage of development affect the cooperative and non-cooperative responses to this aspect of climate change. It is shown that the cooperative response to these stochastic tipping points requires converging carbon taxes for developing and developed regions. The non-cooperative response leads to a bit more precautionary saving and diverging carbon taxes. We illustrate the various outcomes with a simple stylized North–South model of the global economy.

The principal purpose of this Global Program Review (GPR) is to learn lessons from the experience of the Global Fund and its interaction with the Bank in three areas: (a) the design and operation of large global partnership programs like the Global Fund that are financing country-level investments, (b) the engagement of the World Bank with these partnership programs, and (c) the evaluation of these programs. The Review has an intensive focus on the Bank's engagement with the Global Fund at the country level because of the potential for competition or collaboration between Global Fund-supported activities and the Bank's lending operations at the country level. Therefore, it also focuses on the design and operation of the Global Fund-supported activities at the country level. This review was initiated before the high-level independent review panel on fiduciary controls and oversight mechanisms of the Global Fund was commissioned in February 2011, and it was drafted before their final report, turning the page from emergency to sustainability, was issued on September 19, 2011. While the two studies are complementary and overlap to some extent, they were conducted independently of each other, for different audiences, and for different purposes.

Abstract This paper examines the behavior of intraday crude oil futures return and volatility and how they respond to weekly inventory announcements by the American Petroleum Institute (API) and Energy Information Administration (EIA). The informational content of API reports is measured relative to market analysts' expectations collected by Reuters, whereas that of EIA reports is measured relative to API reports. Results suggest that unexpected inventory changes in both API and EIA reports exert an immediate inverse impact on returns and a positive impact on volatility; but the duration and magnitude of EIA inventory shocks are longer and larger, with the largest impact observed when Reuters and API both err on the same side. While there are no instant asymmetric return responses to positive and negative API shocks, the return and volatility responses to cross-commodity inventory shocks in EIA reports exhibit asymmetry.