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.

/pdf/recent-developments-in-the-econometrics-of-program-42vjewfvjw.pdf

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

Governments seeking to provide food assistance have a choice between providing in-kind food directly to beneficiaries, or providing vouchers that can be used to purchase food on the market. To understand the differences between these policies, the Government of Indonesia randomly phased in the transition from in-kind delivery of subsidized rice to approximately equivalent vouchers usable to buy rice and eggs across 105 districts comprising over 3.4 million beneficiary households. We find the transition led to substantial changes in the allocation of aid in practice. The vouchers provided concentrated assistance to targeted households, who received 45 percent more assistance in voucher areas than in in-kind districts. As a result, for households in the bottom 15 percent at baseline, poverty fell by 20 percent. Vouchers also allowed households to purchase higher-quality rice, and led to increased consumption of egg-based proteins. We find vouchers have little effect on aggregate rice prices, although we observe modest price increases in remote villages. Overall leakage from the program was not affected, but the administrative costs of benefits delivery substantially fell. In short, the results suggest that the change from in-kind food aid to vouchers led to substantial impacts on poverty through the way it changed how programs were implemented on the ground.

Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

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Food vs. Food Stamps: Evidence from an At-Scale Experiment in Indonesia

Many developing country governments determine eligibility for anti-poverty programs using censuses of household assets. Does this distort subsequent reporting of, or actual purchases of, those assets? We ran a nationwide experiment in Indonesia where, in randomly selected provinces, the government added questions on flat-screen televisions and cell-phone SIM cards to the targeting census administered to 25 million households. In a separate survey six months later, households in treated provinces report fewer televisions, though the effect dissipates thereafter. We find no change in actual television sales, or reported or actual SIM card ownership, suggesting that consumption distortions are likely small.

https://www.nber.org/system/files/working_papers/w25362/w25362.pdf

The (lack of) Distortionary Effects of Proxy-Means Tests: Results from a Nationwide Experiment in Indonesia

In 2015 and 2016, migrant flows into the European Union (EU) surged, with Greece and Italy the main entry points. Many of the migrants applied for international protection in Europe, becoming asylum seekers. This spike in EU asylum seekers, as well as the increasing numbers of those granted refugee status, brought a need for information on who they are their sociodemographic characteristics; their education and work experience; their experience on the journey to Italy and Greece; and what it cost them not only financially but also physically and emotionally to get there. This study took a rigorous approach to ensure that it produced hard data to support policy decisions, decisions made not only in receiving countries but also in countries of origin and transit. This report then, contributes to knowledge of aspects of migration and forced displacement, but much more has yet to be learned.

Asylum seekers in the European Union : building evidence to inform policy making

Using the most comprehensive data file ever compiled on air pollution, water pollution, environmental regulations, and infant mortality from a developing country, the paper examines the effectiveness of India’s environmental regulations. The air pollution regulations were effective at reducing ambient concentrations of particulate matter, sulfur dioxide, and nitrogen dioxide. The most successful air pollution regulation is associated with a modest and statistically insignificant decline in infant mortality. However, the water pollution regulations had no observable effect. Overall, these results contradict the conventional wisdom that environmental quality is a deterministic function of income and underscore the role of institutions and politics.

Environmental Regulations, Air and Water Pollution, and Infant Mortality in India

Economic theory suggests that, when designing aid programs, ordeal mechanisms that impose differential costs for rich and poor can induce self-selection and hence improve targeting ("self-targeting"). We first re-examine this theory and show that ordeal mechanisms may actually have theoretically ambiguous effects on targeting: for example, time spent applying imposes a higher monetary cost on the rich, but may impose a higher utility cost on the poor. We then examine these issues empirically by conducting a 400-village field experiment within Indonesia's Conditional Cash Transfer program. Targeting in the program is usually conducted by automatically enrolling candidates who pass an asset test. We compare whether instituting an ordeal mechanism, where villagers come to a central application site to apply and take the asset test, improves targeting over the existing automatic enrollment system. Within self-targeting villages, we find that the poor are more likely to apply, even conditional on whether they would pass the asset test. On net, self-targeting villages have a much poorer group of beneficiaries than status quo villages. However, marginally increasing the ordeal does not necessarily improve targeting: while experimentally increasing the distance to the application site reduces the number of applicants, it screens out both rich and poor in roughly equal proportions. Estimating the model structurally, we show that only one would need to increase the ordeal dramatically (e.g. tripling wait times to 9 hours or more) to induce detectable additional selection. In short, ordeal mechanisms can induce self-selection, but marginally increasing the ordeal can impose additional costs on applicants without necessarily improving targeting.

Rema Hanna

Papers

Food vs. Food Stamps: Evidence from an At-Scale Experiment in Indonesia

The (lack of) Distortionary Effects of Proxy-Means Tests: Results from a Nationwide Experiment in Indonesia

Asylum seekers in the European Union : building evidence to inform policy making

Environmental Regulations, Air and Water Pollution, and Infant Mortality in India

Ordeal Mechanisms In Targeting: Theory And Evidence From A Field Experiment In Indonesia