Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg yr−1 in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W m−2 with 90% uncertainty bounds of (+0.08, +1.27) W m−2. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W m−2. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W m−2 with 90% uncertainty bounds of +0.17 to +2.1 W m−2. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W m−2, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (−0.50 to +1.08) W m−2 during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (−0.06 W m−2 with 90% uncertainty bounds of −1.45 to +1.29 W m−2). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.

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Bounding the role of black carbon in the climate system: A scientific assessment

Many empirical questions in economics and other social sciences depend on causal effects of programs or policies. In the last two decades, much research has been done on the econometric and statistical analysis of such causal effects. This recent theoreti- cal literature has built on, and combined features of, earlier work in both the statistics and econometrics literatures. It has by now reached a level of maturity that makes it an important tool in many areas of empirical research in economics, including labor economics, public finance, development economics, industrial organization, and other areas of empirical microeconomics. In this review, we discuss some of the recent developments. We focus primarily on practical issues for empirical research- ers, as well as provide a historical overview of the area and give references to more technical research.

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Recent developments in the econometrics of program evaluation

The Lancet Commission on pollution and health

A common approach to evaluating robustness to omitted variable bias is to observe coefficient movements after inclusion of controls. This is informative only if selection on observables is informative about selection on unobservables. Although this link is known in theory in existing literature, very few empirical articles approach this formally. I develop an extension of the theory that connects bias explicitly to coefficient stability. I show that it is necessary to take into account coefficient and R-squared movements. I develop a formal bounding argument. I show two validation exercises and discuss application to the economics literature. Supplementary materials for this article are available online.

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Unobservable Selection and Coefficient Stability: Theory and Evidence

A long-standing question in social science is to what extent differences in management cause differences in firm performance. To investigate this, the authors ran a management field experiment on large Indian textile firms, providing free consulting on modern management practices to a randomly chosen set of treatment plants and compared their performance to the control plants. They find that adopting these management practices had three main effects. First, it raised average productivity by 11 percent through improved quality and efficiency and reduced inventory. Second, it increased decentralization of decision making, as better information flow enabled owners to delegate more decisions to middle managers. Third, it increased the use of computers, necessitated by the data collection and analysis involved in modern management. Since these practices were profitable this raises the question of why firms had not adopted these before. Their results suggest that informational barriers were a primary factor in explaining this lack of adoption. Modern management is a technology that diffuses slowly between firms, with many Indian firms initially unaware of its existence or impact. Since competition was limited by constraints on firm entry and growth, badly managed firms were not rapidly driven from the market.

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Does Management Matter? Evidence from India

We use a randomized experiment and a structural model to test whether monitoring and financial incentives can reduce teacher absence and increase learning in India. In treatment schools, teachers' attendance was monitored daily using cameras, and their salaries were made a nonlinear function of attendance. Teacher absenteeism in the treatment group fell by 21 percentage points relative to the control group, and the children's test scores increased by 0.17 standard deviations. We estimate a structural dynamic labor supply model and find that teachers respond strongly to financial incentives. Our model is used to compute cost-minimizing compensation policies. (JEL I21, J31, J45, O15)

/pdf/incentives-work-getting-teachers-to-come-to-school-51oi2h2j75.pdf

Incentives Work: Getting Teachers to Come to School

The brief summarizes the targeting the poor: evidence from a field experiment in Indonesia for the period December 2008 - January 2009. This paper reports an experiment in 640 Indonesian villages on three approaches to target the poor: proxy means tests (PMT), where assets are used to predict consumption; community targeting, where villagers rank everyone from richest to poorest; and a hybrid. Defining poverty based on PPP$2 per capita consumption, community targeting and the hybrid perform somewhat worse in identifying the poor than PMT, though not by enough to significantly affect poverty outcomes for a typical program. Elite capture does not explain these results. Instead, communities appear to apply a different concept of poverty.

/pdf/targeting-the-poor-evidence-from-a-field-experiment-in-56327qtcey.pdf

Targeting the Poor: Evidence from a Field Experiment in Indonesia

We conduct two experiments to understand the process of obtaining a driver’s license in India. In the first experiment, we randomly assign license candidates to one of three groups: bonus (offered a financial reward if they could obtain their license fast), lesson (offered free driving lessons upfront), and control. The control group alone illustrates bureaucratic failures: 71% of the license getters in that group avoided the mandated driving test and 62% failed a surprise driving test. The system responds to private needs— there are more license getters in the bonus group—but at a social cost: there are more license getters who cannot drive in the bonus group. The system however also appears to respond to social considerations, as there are more license getters in the lesson group. Large extra-legal payments are made by license getters: those in the control group pay 2.5 times the official fee. More of these extra-legal payments take place in the bonus group. Surprisingly, these extra-legal payments are not direct bribes to bureaucrats but instead payments to agents. In the second experiment, we perform an audit study to better understand the role of agents. The audit shows that agents can provide licenses to individuals even if they cannot drive; but the audit also shows that agents cannot as easily circumvent all other rules. We argue that our findings are most consistent with agents being the channel for corruption in this system. We also report some suggestive evidence that bureaucrats create red tape, possibly to induce more license candidates to use agents.

Obtaining a Driver's License in India: An Experimental Approach to Studying Corruption

https://www.nber.org/system/files/working_papers/w17302/w17302.pdf

The effect of pollution on labor supply: Evidence from a natural experiment in Mexico City ☆

It is conventional wisdom that it is possible to reduce exposure to indoor air pollution, improve health outcomes, and decrease greenhouse gas emissions in the rural areas of developing countries through the adoption of improved cooking stoves This belief is largely supported by observational field studies and engineering or laboratory experiments However, a new evidence is provided, from a randomized control trial conducted in rural Orissa, India (one of the poorest places in India), on the benefits of a commonly used improved stove that laboratory tests showed to reduce indoor air pollution and require less fuel Households are tracked for up to four years after they received the stove [BREAD Working Paper No 338] URL:[http://iplecondukeedu/bread/papers/working/338pdf]

Rema Hanna

Papers

Incentives Work: Getting Teachers to Come to School

Targeting the Poor: Evidence from a Field Experiment in Indonesia

Obtaining a Driver's License in India: An Experimental Approach to Studying Corruption

The effect of pollution on labor supply: Evidence from a natural experiment in Mexico City ☆

Up in Smoke: The Influence of Household Behavior on the Long-Run Impact of Improved Cooking Stoves