Estimates of climate impacts show that extreme temperatures have large and wide-spread effects. To estimate these effects, a common approach counts days in different temperature ranges and considers how exposure to these distinct 'bins' affects outcomes. This often produces non-linear, U-shaped results, in which high and low temperatures have the largest effects. We show that non-linear approaches like these can generate spurious findings. Specifically, global warming induces trends in extreme temperature exposure that correlate mechanically with a location's baseline temperature. Substantial bias emerges if trends in the outcome variable also correlate with baseline temperature for any reason. We demonstrate this problem theoretically, in simulations, and with real outcomes. We then develop solutions. In applications using US data, some results in the literature are unaffected by these corrections, while other results change substantially. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Many social insurance programs have low take-up, but it is unclear whether this is due to administrative barriers, information, or low insurance valuations. We study a Thai policy that offered large incentives for informal workers in selected provinces to enroll. The incentives increased insurance coverage by 67 percentage points- from 6 percent of informal workers to 73 percent- within two months. However, 12 months later, only 13 percent remained insured. Using choices among insurance tiers to back out revealed valuations, we find that low social insurance enrollment may be due to low ex-ante valuations of insurance, rather than administrative barriers.

Theories of outsourcing often presume that private firms are more efficient producers of goods and services, but that contracting frictions mean that firms do not internalize the government's objective function. But perhaps, for some tasks, the government can actually be more productively efficient? We study this question through an experiment in Chennai, India, where the government randomly selected neighborhoods to have property tax assessments determined by private firms contracted by the government, rather than government tax inspectors. We show that inspections by government tax inspectors yielded almost double the increase in tax revenue as those done by private firms. They were also more accurate, as judged by comparing new assessments to independent assessments done by third-party surveyors we hired. Difficulties contracting with the government discouraged many competent firms from bidding. Perhaps as a result, government inspectors had higher skills and put in more effort than the workers at the private firms. Importantly, the government inspectors also had more authority to enter properties, which may be hard to transfer even to higher quality firms. The results suggest that the limits to government outsourcing may go beyond multitasking issues. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

The reviewers included in this list have provided four or more high-quality and timely reports during the 2020 and 2021 calendar years, or have provided valuable assistance in particularly difficult cases.

Community-based targeting, in which communities allocate social assistance using local information about who is poor, in experimental settings leads to nuanced allocations that reflect local concepts of poverty. What happens when it is scaled up, by either by making the stakes high, or by replicating the process nationwide? We study this by examining community targeting in both a high-stakes experiment, in which villages determined who would receive the Indonesian conditional cash transfer program – worth almost USD 1,000 over 6 years – and in a nationwide scaleup, whereby Indonesia used community-based meetings to allocate COVID-transfers to over 8 million households. We find that both the experimental scale-up and the massive national scale-up had broadly similar performance to the original experimental study. We find strongly progressive targeting as measured by baseline household consumption, though – as in the pilot – not quite as strong as if they had used a fully up-to-date proxy means test. In both scale-ups, we also find that the villages gave additional weight to locally-valued characteristics beyond pure consumption, such as widowhood, recent illness, and food expenditure shares, again echoing the findings from pilots. The results suggest that community targeting can perform well at scale, as predicted by the experimental study.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Concerns about fraud in welfare programs are common arguments worldwide against such programs. We conducted a survey experiment with over 28,000 welfare program administrators and over 19,000 beneficiaries in Indonesia to elicit the "marginal disutility from corruption"-the trade-off between more generous social assistance and losses due to corruption. Merely mentioning corruption reduced perceived program success, equivalent to distributing more than 26 percentage points less aid. However, respondents were not sensitive to the amount of corruption-respondents were willing to trade off $2 of additional losses for an additional $1 distributed to beneficiaries. Program administrators and beneficiaries had similar assessments. (JEL D73, H53, I32, I38, O15, O17)

Social protection programs have become increasingly widespread in low- and middle-income countries, with their own distinct characteristics to match the environments in which they are operating. This paper reviews the growing literature on the design and impact of these programs. We review how to identify potential beneficiaries given the large informal sector, the design and implementation of redistribution and income support programs, and the challenges and potential of social insurance. We use our frameworks as a guide for consolidating and organizing the existing literature, and also to highlight areas and questions for future research.

Do celebrity endorsements matter? And if so, how can celebrities communicate effectively? We conduct a nationwide Twitter experiment in Indonesia promoting vaccination. Celebrity messages are 72% more likely to be passed on or liked than similar messages without a celebrity’s imprimatur. In total, 66% of the celebrity effect comes from authorship, compared to passing on messages. Citing external medical sources decreases retweets by 27%. Phone surveys show that those randomly exposed to messaging have fewer incorrect beliefs and report more vaccination among friends and neighbours. The results can inform public health campaigns and celebrity public service more generally.

Two factors have elevated recent academic and policy interest in tropical deforestation: first, the realization that it is a major contributor to climate change; and second, a revolution in satellite-based measurement that has revealed that it is proceeding at a rapid rate. We begin by reviewing the methodological advances that have enabled measurement of forest loss at a fine spatial resolution across the globe. We then develop a simple benchmark model of deforestation based on classic models of natural resource extraction. Extending this approach to incorporate features that characterize deforestation in developing countries—pressure for land use change, significant local and global externalities, weak property rights, and political economy constraints—provides us with a framework for reviewing the fast-growing empirical literature on the economics of deforestation in the tropics. This combination of theory and empirics provides insights not only into the economic drivers and impacts of tropical deforestation but also into policies that may affect its progression. We conclude by identifying areas where more work is needed in this important body of research.

We compare how in-kind food assistance and an electronic voucher-based program affect the delivery of aid in practice. The Government of Indonesia randomized across 105 districts the transition from in-kind rice to approximately equivalent electronic vouchers redeemable for rice and eggs at a network of private agents. Targeted households received 46 percent more assistance in voucher areas. For the bottom 15 percent of households at baseline, poverty fell 20 percent. Voucher recipients received higher-quality rice, and increased consumption of eggs. The results suggest moving from a manual in-kind to electronic voucher-based program reduced poverty through increased adherence to program design. (JEL H53, I18, I32, I38, O12)

Designing public transport networks involves tradeoffs between extensive geographic coverage, frequent service on each route, and relying on interconnections as opposed to direct service.These choices, in turn, depend on individual preferences for waiting times, travel times, and transfers.We study these tradeoffs by examining the world's largest bus rapid transit system, in Jakarta, Indonesia, leveraging a large network expansion between 2016-2020.Using detailed ridership data and aggregate travel flows from smartphone data, we analyze how new direct connections, changes in bus travel time, and wait time reductions increase ridership and overall trips.We set up and estimate a transit network demand model with multi-dimensional travel costs, idiosyncratic heterogeneity induced by random wait times, and inattention, matching eventstudy moments from the route launches.Commuters in Jakarta are 2-4 times more sensitive to wait time compared to time on the bus, and inattentive to long routes.To study the implications for network design, we introduce a new framework to describe the set of optimal networks.Our results suggest that a less concentrated network would increase ridership and commuter welfare.

COVID-19 vaccines are widely available in wealthy countries, yet many remain unvaccinated. We report on two studies (United States and France) with millions of Facebook users that tested two strategies central to vaccination outreach: health professionals addressing common concerns and motivating “ambassadors” to encourage vaccination in their social networks. We can reject very small effects of any intervention on new first doses (0.16 pp, United States; 0.021 pp, France), with similar results for second doses and boosters (United States). During the Omicron wave, messaging aimed at the unvaccinated or those tasked with encouraging others did not change vaccination decisions.

Abstract Can information from a credible messenger shift behavior in an information-saturated environment? In a randomized controlled trial involving twenty-eight million individuals in West Bengal, we find that SMS-delivered video messages containing information about COVID-19 symptoms and health-preserving behaviors recorded by a credible messenger increased adherence to targeted and non-targeted preventive behaviors, measured by two objective measures (symptoms reported to a health worker, and phone usage at home), as well as self-reported behaviors. We find large spillovers onto non-targeted recipients. Credible light-touch messaging can play an important role in crisis response, even when similar information is widely available.

During the COVID-19 epidemic, many health professionals started using mass communication on social media to relay critical information and persuade individuals to adopt preventative health behaviors. Our group of clinicians and nurses developed and recorded short video messages to encourage viewers to stay home for the Thanksgiving and Christmas Holidays. We then conducted a two-stage clustered randomized controlled trial in 820 counties (covering 13 States) in the United States of a large-scale Facebook ad campaign disseminating these messages. In the first level of randomization, we randomly divided the counties into two groups: high intensity and low intensity. In the second level, we randomly assigned zip codes to either treatment or control such that 75% of zip codes in high intensity counties received the treatment, while 25% of zip codes in low intensity counties received the treatment. In each treated zip code, we sent the ad to as many Facebook subscribers as possible (11,954,109 users received at least one ad at Thanksgiving and 23,302,290 users received at least one ad at Christmas). The first primary outcome was aggregate holiday travel, measured using mobile phone location data, available at the county level: we find that average distance travelled in high-intensity counties decreased by -0.993 percentage points (95% CI -1.616, -0.371, p-value 0.002) the three days before each holiday. The second primary outcome was COVID-19 infection at the zip-code level: COVID-19 infections recorded in the two-week period starting five days post-holiday declined by 3.5 percent (adjusted 95% CI [-6.2 percent, -0.7 percent], p-value 0.013) in intervention zip codes compared to control zip codes.

This paper examines the link between electoral incentives and environmental degradation by exploiting a satellite dataset on 107,000 forest fires and 879 asynchronous district elections in Indonesia. Fires represent a cheap but illegal means of converting forested land to other uses, but they risk burning out of control and creating substantial negative environmental externalities. We find a significant electoral cycle in forest fires. Ignitions and area burned decline during election years but steeply increase in the year after. The results suggest that politicians may suppress this activity at times when it might particularly dent their electoral chances.

Researchers: Vivi Alatas Abhijit Banerjee Rema Hanna Ben Olken Julia Tobias Sector(s): Political Economy & Governance, Social Protection Location: Jakarta, Indonesia Sample: 5,756 households in 640 villages Target group: Rural population Outcome of interest: Citizen satisfaction Social service delivery Intervention type: Cash transfers Targeting Community-driven development Unconditional cash transfers AEA RCT registration number: AEARCTR-0000099 Data: Download from Dataverse Partner organization(s): Government of the Netherlands, Indonesia, Central Bureau of Statistics (BPS), Indonesian Ministry of Social Affairs, Indonesian National Team for the Acceleration of Poverty Reduction (TNP2K), Mitra Samya, SurveyMETER, World Bank

During the Coronavirus Disease 2019 (COVID-19) epidemic, many health professionals used social media to promote preventative health behaviors. We conducted a randomized controlled trial of the effect of a Facebook advertising campaign consisting of short videos recorded by doctors and nurses to encourage users to stay at home for the Thanksgiving and Christmas holidays (NCT04644328 and AEARCTR-0006821). We randomly assigned counties to high intensity (n = 410 (386) at Thanksgiving (Christmas)) or low intensity (n = 410 (381)). The intervention was delivered to a large fraction of Facebook subscribers in 75% and 25% of randomly assigned zip codes in high- and low-intensity counties, respectively. In total, 6,998 (6,716) zip codes were included, and 11,954,109 (23,302,290) users were reached at Thanksgiving (Christmas). The first two primary outcomes were holiday travel and fraction leaving home, both measured using mobile phone location data of Facebook users. Average distance traveled in high-intensity counties decreased by -0.993 percentage points (95% confidence interval (CI): -1.616, -0.371; P = 0.002) for the 3 days before each holiday compared to low-intensity counties. The fraction of people who left home on the holiday was not significantly affected (adjusted difference: 0.030; 95% CI: -0.361, 0.420; P = 0.881). The third primary outcome was COVID-19 infections recorded at the zip code level in the 2-week period starting 5 days after the holiday. Infections declined by 3.5% (adjusted 95% CI: -6.2%, -0.7%; P = 0.013) in intervention compared to control zip codes. Social media messages recorded by health professionals before the winter holidays in the United States led to a significant reduction in holiday travel and subsequent COVID-19 infections.