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Policymakers can take actions to prevent local conflict before it begins, if such violence can be accurately predicted. We examine the two countries with the richest available sub-national data: Colombia and Indonesia. We assemble two decades one fine- grained violence data by type, alongside hundreds of annual risk factors. We predict violence one year ahead with a range of machine learning techniques. Models reliably identify persistent, high-violence hot spots. Violence is not simply autoregressive, as detailed histories of disaggregated violence perform best. Rich socio-economic data also substitute well for these histories. Even with such unusually rich data, however, the models poorly predict new outbreaks or escalations of violence. \Best case" scenarios with panel data fall short of workable early-warning systems.

Was the International Monetary Fund (IMF) susceptible to political pressure from the United States and its Western allies during the Cold War? To answer this question, we construct a new database containing the number of conditions applied to over 500 IMF loans since 1970 and analyze how the distance from a borrowing country to its closet communist neighbor affected the IMF conditionality. We show that the fund imposed fewer conditions on loans to countries geographically closer to the communist bloc. Results are stronger when neighboring communist countries were not part of the Warsaw Pact. This pattern persisted during the 1990s, when the fund helped former communist countries in their transition to market economies. However, we find no strong evidence of such discretionary treatment by the IMF after 2001, when thecontainment of communism had ceased to be the West’s top priority.

India is on the edge of a demographic revolution with a rapidly rising working-age population. For the first time in this study, we investigate the role of the rising working-age population on per capita small savings in post offices and banks net of socio-economic characteristics using state-level panel data compiled from multiple sources for the period 2001–2018. Our comprehensive econometric assessment with multiple robustness checks provides three key findings: (1) per capita private savings is increasing because of India’s growing working-age population; thus, the ‘economic life cycle hypothesis’ is evidentially supported; (2) the demographic factors contribute around one-fourth of the per capita private savings inequality across Indian states; and (3) the demographic window of economic opportunity for India can yield maximum benefits in terms of private savings when accompanied by favourable socio-economic policies on education, health, gender equity, and economic growth.

This paper exploits location choices of all generalist physicians graduated in Brazil between 2001 and 2013 to study policies aiming at increasing the supply of physicians in underserved areas. We set up and estimate a supply and demand model for physicians. We estimate physicians' locational preferences using a random coefficients discrete choice model. The demand has private establishments competing for physicians with private and public facilities around the country. Policy counterfactuals indicate that quotas in medical schools for students born in underserved areas and the opening of vacancies in medical schools in deprived areas are more cost-effective than financial incentives.

Data for low- and middle- income countries (LMICs) are used to investigate the effect of the demographic transition on economic growth at sub-national level. We introduce a detailed classification of demographic window phases, determine how these phases are distributed among and within LMICs, and analyze the relationship between the demographic window of opportunity (DWO) and economic growth for 1921 urban and rural areas of sub-national regions within 91 LMICs. Many areas in Asia, Latin America and the Middle East have entered the window, but most of Sub-Saharan Africa is still in the traditional or pre-window phase. Our analyses reveal higher growth rates in areas passing through the DWO. Positive growth effects are particularly strong in rural and more educated regions and in countries with lower levels of corruption. Policy measures aimed at effectively using the DW for achieving growth should combine investments in education and rural development with better governance., Social Indicators Research, 161 (1), ISSN:0303-8300, ISSN:1573-0921

According to neoclassical economics, the most efficient way to organize human activity is to use the free market. By stoking self interest, the theory claims, individuals can benefit society. This idea, however, conflicts with the evolutionary theory of multilevel selection, which proposes that rather than stoke individual self interest, successful groups must suppress it. Which theory better describes how human societies develop? I seek to answer this question by studying the opposite of the market: namely hierarchy. I find evidence that as human societies develop, they turn increasingly to hierarchical organization. Yet they do so, paradoxically, at the same time that the language of free markets becomes more common, and culture becomes more individualistic. This evidence, I argue, contradicts free-market theory, but only if we treat it as a scientific doctrine. If instead we treat free-market theory as an ideology, the pieces come together. Free-market thinking, I speculate, may stoke the formation of hierarchy by cloaking power in the language of ‘freedom’.

The application of deep learning methods to survey human development in remote areas with satellite imagery at high temporal frequency can significantly enhance our understanding of spatial and temporal patterns in human development. Current applications have focused their efforts in predicting a narrow set of asset-based measurements of human well-being within a limited group of African countries. Here, we leverage georeferenced village-level census data from across 30 percent of the landmass of India to train a deep-neural network that predicts 16 variables representing material conditions from annual composites of Landsat 7 imagery. The census-based model is used as a feature extractor to train another network that predicts an even larger set of developmental variables (over 90 variables) included in two rounds of the National Family Health Survey (NFHS) survey. The census-based model outperforms the current standard in the literature, night-time-luminosity-based models, as a feature extractor for several of these large set of variables. To extend the temporal scope of the models, we suggest a distribution-transformation procedure to estimate outcomes over time and space in India. Our procedure achieves levels of accuracy in the R-square of 0.92 to 0.60 for 21 development outcomes, 0.59 to 0.30 for 25 outcomes, and 0.29 to 0.00 for 28 outcomes, and 19 outcomes had negative R-square. Overall, the results show that combining satellite data with Indian Census data unlocks rich information for training deep learning models that track human development at an unprecedented geographical and temporal definition.

International audience; Public sectors around the world, especially in the developing counties, are not functioning well due to widespread fraud, governance, corruption, and inefficacy. For this reason, the world's public sectors need to improve their efficacy by using a sound risk management system. This study attempts to comprehend the phenomenon of current risk management practices among the public sector employees in different service schemes in Malaysia. A questionnaire survey was utilized to collect primary data from 194 department heads in Malaysia's federal ministries. The collected data was analysed using descriptive statistics and factor analysis. Findings revealed that 94.7% of respondents agreed to implementing risk management in their respective departments, but the level of priority for these risk management factors differs based on the service schemes. This study will assist policymakers to identify what is needed to enhance risk management practices in the public sector.

In this paper, I propose a new framework for analysing the short and long-run effects of temporary educational disruptions on the learning progression of children. The framework integrates into a coherent model recent advances in the literature on learning acquisition (Kaffenberger, 2021; Kaffenberger and Pritchett, 2020b, 2021) and the literature on estimating the immediate costs of instructional disruptions (Neidhöfer et al., 2021). The integrated framework includes explicit modelling of continuous parental investments, filling a gap in the literature related to the Potential Pedagogical Function and other explicit models of learning progression and acquisition. In the same way, the model considers the role of economic resources as part of the resources employed by parents to mitigate the effects of a temporary shock in instruction., expanding the notion of attenuation capacity developed by Neidhöfer et al. (2021). Finally, I take this framework to the data to estimate the potential effects of the instructional disruption caused by the COVID-19 pandemic in Mexico. The estimates suggest that, for the Mexican cohort affected by the instructional disruption, the potential persistent loss in learning with respect to the counterfactual lies on average between 20% and 90% of the learning acquired during a usual school year, depending on the effectiveness of the remote learning policies implemented during 2020 and 2021. These results already consider the mitigating role of parental investments. Furthermore, my results suggest substantial variation between inhabitants from different regions of the country and inside inhabitants of the same region, being the South of the country the region where the losses are the largest. (Stone Center on Socio-Economic Inequality Working Paper)

Demand for animal-source foods (ASF) has grown substantially in Africa over the last four decades, fueled mainly by population growth, urbanization, and modest gains in per capita incomes. Further growth over the medium and longer terms is expected as these trends in external drivers continue, with implications of this growth reflecting a multitude of economic, environmental, and public health trade-offs. This paper provides a focused, forward-looking perspective on key emerging issues around changes in ASF consumption and supply in Africa.

Rural poverty in China fell from 96 percent in 1980 to less than 1 percent of the population in 2019. Using PovcalNet data for China and a set of comparable countries, this paper estimates growth-poverty elasticities. It finds that China stands out for its record of sustained, fast growth, rather than because of an unusually high growth-poverty elasticity. In addition, changes in mean consumption, rather than changes in the distribution, drive poverty reduction. Furthermore, until 2010, changes in inequality attenuated the impact of growth on poverty. The paper also studies which channels mattered the most for rural poverty reduction by applying a decomposition framework to multiple rounds of Chinese Household Income Project surveys conducted in 1988, 1995, 2002, 2007, 2013, and 2018. The findings show that broad-based, labor-intensive growth in agriculture was initially the main driving force for rural poverty reduction, followed by the expansion of non-agriculture sectors. As the country’s poverty rate approached 10 percent by 2007, transfers from migrant workers and, later, public transfers became the major drivers of further rural poverty reduction. Throughout the period, the fall in the demographic dependency rate also played a significant role. As China’s living standards continue to rise, the official definition of poverty will have to adjust to the higher minimum. Continued structural transformation and the inclusive growth agenda retain crucial importance for sustained poverty reduction. (Stone Center on Socio-Economic Inequality Working Paper)

This paper analyses the marriage decisions of men and women, focusing on the added attractiveness of sanitation within the living arrangement, in rural India. We exploit district and time variation from the Total Sanitation Campaign (TSC) which increased sanitation by 6.6 percent among households with marriage eligible children and generated an exogenous increase in the composition of households with sanitation. Using data from the Indian Human Development household survey (IHDS) and district level census, we show that exposure to TSC increased the probability of marriage for men and women, from poorer households, by 3.8 pp and 6.5 pp respectively. The reduced form estimates incorporate both general equilibrium effects and heterogeneous program effects – two important components of equilibrium marital behavior. To decompose the overall policy impact on marriage market equilibrium we formulate a simple matching model where men and women match on observed and unobserved characteristics. Through model simulations, we show that cohorts within TSC exposed markets experienced a shift in marital gains both across matches but also within a given match. Specifically, the resultant sorting patterns display a marked gender asymmetry with an increase in marital surplus among matches where men are wealthier than their spouse, and a decrease in surplus where the wife is wealthier. Moreover, the increased access to sanitation for TSC exposed women implied a decline in their expected control over resources within the marriage.

This paper projects potential demographic dividend for India for the period from 2001 to 2061 by using simulation modelling software, Spectrum 5.753 which integrates demographic and socio-economic changes. The simulation results highlight that a combination of favourable demographic changes and the right socio-economic policy scenario can provide a maximum demographic dividend to India. Two key findings, after checking their robustness, from the simulation modelling are: First, the effective demographic windows of opportunity for India is available for the period between 2011 and 2041, giving India roughly 30 years of demographic bonus. It is the period where the maximum of the first demographic dividend can be reaped before the ageing burden starts. Second, favourable demographic changes alone has potential to provide a demographic dividend in terms of GDP per capita over 165,000 rupees which is equivalent to an additional 43 percentage for ‘demographic-emphasis scenario’ (Rs. 548,600) compared to ‘demographic as-usual scenario’ (Rs. 382,750) in 2061. However, reaping demographic dividend is conditional on supporting socio-economic policy environment in terms of investment in human capital and decent employment opportunities.

Integrated Assessment Models of Global Climate Change are an established tool to explore possible pathways of climate change mitigation and adaptation. The models are a quantitative backbone for IPCC reports. But can the models be trusted? This manuscript discusses how the models can be scrutinized and where limits to model validation exist.

In this paper, we assess the economic benefits of demographic changes in India by employing econometric models and robustness checks based on panel data gathered over a period of more than three decades. Our analysis highlights four key points. First, the contribution of India’s demographic dividend is estimated to be around 1.9 percentage points out of 12% average annual growth rate in per capita income during 1981–2015. Second, India’s demographic window of opportunity began in 2005, significantly improved after 2011, and will continue till 2061. Third, our empirical analysis supports the argument that the realisation of the demographic dividend is conditional on a conducive policy environment with enabling aspects such as quality education, good healthcare, decent employment opportunities, good infrastructure, and gender empowerment. Fourth, the working-age population in India contributes around one-fourth of the inequality in per capita income across states. Thus, to reap the maximum dividends from the available demographic window of opportunity, India needs to work towards enhancing the quality of education and healthcare in addition to providing good infrastructure, gender empowerment, and decent employment opportunities for the growing working-age population.

Nations have and will continue to shape their economies through industrial policy. Nevertheless, the empirical literature on these interventions is thin, dwarfed by the attention industrial policies receive from policymakers across the world. In this paper, I discuss the difficulties of empirically studying industrial policy and review how new econometric work is confronting these issues. Through careful research design and attention to institutional detail, I argue that emergent studies are rapidly expanding what we know—and updating what we thought we knew—about these policies. As well, I argue tools from policy evaluation allow us to study the impact of endogenous industrial interventions. This review is a proposal to take industrial policy, along with their complexities, more seriously as objects of inquiry. Doing so requires not only more serious evaluations of past policy but also a reevaluation of past empirical work and consensus.

COVID-19 has lent a fresh lease of life to local production initiatives particularly in Africa. New initiatives, such as the recently announced mRNA hub for COVID-19 vaccines by the World Health Organization in collaboration with the Government of South Africa, and several other projects and programs, are now focusing on creating disseminated manufacturing capacity for current and future pandemic response. This is an important and welcome development for several reasons: it can boost national health security and safeguard lives in regions that have had longstanding problems of access to lifesaving medicines, while also promoting economic development, technological learning, export capacity and regional trade. But current local production efforts raise several serious questions of sustainability. This paper tackles several of these questions: When can we realistically expect production capacity to be built? What might be the potential impact of current efforts to expand supply capacity of COVID-19 vaccines, more generally at the global level, on African investments into local manufacturing? How will these markets evolve at the global and regional levels? Will markets still be available for local manufacturers to tap into by end of 2022 or 2023, and if so, how can we address the technological and market uncertainties related to these investments? What lessons can we glean from local production experiences in the region previously for building vaccine capacity on the continent?

I study the impact of industrial policy on industrial development by considering a canonical intervention. Following a political crisis, South Korea dramatically altered its development strategy with a sector-specific industrial policy: the Heavy and Chemical Industry (HCI) drive, 1973-1979. With newly assembled data, I use the sharp introduction and withdrawal of industrial policies to study the impacts of industrial policy---during and after the intervention period. I show (1) HCI promoted the expansion and dynamic comparative advantage of directly targeted industries. (2) Using variation in exposure to policies through the input-output network, I show HCI indirectly benefited downstream users of targeted intermediates. (3) I find direct and indirect benefits of HCI persisted even after the end of HCI, following the 1979 assassination of the president. These effects include the eventual development of directly targeted exporters and their downstream counterparts. Together, my findings suggest that the temporary drive shifted Korean manufacturing into more advanced markets and created durable industrial change. These findings clarify lessons drawn from South Korea and the East Asian growth miracle. Current Version: June 2022 [First Draft: October 2016]

Data deficits in developing countries impede evidence-based urban planning and policy, as well as fundamental research. We show that residential electricity consumption data can be used to partially address this challenge by serving as a proxy for relative living standards at the block or neighbourhood scale. We illustrate this potential by combining infrastructure and land use data from Open Street Map with georeferenced data from ~2 million residential electricity meters in the megacity of Karachi, Pakistan to map median electricity consumption at block level. Equivalent areal estimates of economic activity derived from high-resolution night lights data (VIIRS) are shown to be a poor predictor of intraurban variation in living standards by comparison. We argue that electricity data are an underutilised source of information that could be used to address empirical questions related to urban poverty and development at relatively high spatial and temporal resolution. Given near universal access to electricity in urban areas globally, this potential is significant

India’s national lockdown in 2020, in response to the Covid-19 crisis, was one of the harshest in the world. Multiple household surveys indicate that the lockdown and the economic recession that followed led to a severe nutrition crisis. Food deprivation was most intense during the national lockdown but continued throughout the year. Relief measures helped, but they compensated for just a fraction of people’s income losses, even among poor households. It is doubtful that employment, income and nutrition among informal-sector workers and their families ever regained their pre-lockdown levels before a second wave of the Covid-19 epidemic hit the country in early 2021. The Indian government’s failure to put in place more effective relief measures is a serious denial of people’s right to food. With relief measures off the table in 2021, at the time of writing, there is a serious danger of another wave of intense food deprivation. [This paper was prepared for the Centre for Health Equity, Law and Policy (C-HELP).]

Bill Warren's book, Imperialism, Pioneer of Capitalism, performs a useful service by refuting much of the mythology that the left has embraced in the name of 'anti-imperialism'. On the other hand, he manages to create his own brand of confusion. He does this, firstly, by blaming Lenin's Imperialism the Highest Stage of Capitalism for many of the left's erroneous views. And secondly, he is so busy extolling the historical mission of capitalism, that no effort is devoted to discussing how capitalism is an obstacle to human development and is becoming increasingly obsolete. Despite these shortcomings it is the myth shattering quality of the book that predominates.

Recent work from developed parts of the world has documented a positive association between air pollution and criminal activity. We use high-frequency complaints and air pollution data to estimate air pollution’s causal effects on crime in a developing country. In order to establish causality, we exploit plausibly exogenous local variation in wind direction in an instrumental variable setup. We find that a lower number of complaints are received on the days of high air pollution levels. This effect is more pronounced for property crimes than for violent crimes. Our results are robust to a host of robustness checks and falsification checks. Exploring the potential mechanisms, we find that the decline in criminal activity might result from increased costs of indulging in criminal activity.

En el presente artículo analizo los efectos distributivos de la crisis económica provocada por la pandemia de COVID-19 en México. A partir de la información sobre ingreso laboral disponible en la Encuesta Nacional de Ocupación y Empleo identifico tres resultados principales. En primer lugar, la mayor contracción de ingresos fue experimentada por la población de menores ingresos, lo que llevó a un incremento en la desigualdad de ingresos. En segundo lugar, la entidad federativa en donde el impacto fue mayor fue la Ciudad de México, lo que provocó una reducción en la desigualdad entre estados. Por último, la recuperación de empleo parece seguir un patrón polarizante, pues al cuarto trimestre aún no se habían recuperado los empleos ubicados a la mitad de la distribución.

On March 24, 2020, the Government of India announced a 21-day national lockdown that has since been extended to May 31, 2020. The lockdown left urban food markets in disarray with severe supply bottlenecks and restrictions on doing business. At a time when food prices in India were declining consistently, supply disruptions consequent to the lockdown have reversed the trend on average. Based on an analysis of publicly available data on wholesale and retail prices for 22 commodities from 114 Centres, we find that prices have increased since the lockdown, as of August 1, 2020. There is significant diversity across commodities and geographies that mask aggregate figures. Average price increases were to the tune of over 6% for several pulses, over 3.5% for most edible oils, 15% for potato 28% for tomato in the four weeks post-lockdown compared to prices during the four weeks preceding the lockdown. Price of meat and fish too have registered large increases. Price wedge between retail and wholesale prices increased as did spatial dispersion, both signifying friction in supply chains. We find that smaller cities have seen a much higher increase in prices with some seeing a rise in retail food prices by as much as 20%. Three rounds of surveys, conducted between April and July, of food retailers in 14 Indian cities reveal serious operational challenges. These include, among others, transport and labor shortages, police harassment and social discrimination. At the same time, several innovative arrangements and adaptations have evolved as well suggesting resilience. The paper reviews these aspects and outlines some lessons for food policy in emerging economies.

We conducted an audit experiment to examine whether street vendors in Bogotá (Colombia) exert price discrimination based on buyers’ attributes, such as gender and nationality, and based on product characteristics, such as the increasing marginal valuation of items needed to complete a collection. We exploited the seasonal demand for album stickers related to the FIFA World Cup Russia 2018. In our within-subjects design, experimenters carried out in-person audits and quoted a pre-determined list of missing stickers. They interacted with 59 sticker vendors located in five geographic clusters and collected 287 vendor–buyer interactions. We find that prices quoted to foreign buyers are higher than prices quoted to Colombian buyers. By contrast, we do neither find evidence supporting direct gender-based discrimination, nor that vendors charge a higher price per sticker when the list of missing stickers is shorter. We complement the study with a qualitative analysis based on interviews that reveal vendors’ pricing strategies, their awareness of price discrimination, and the trade of counterfeits. The qualitative results suggest that price discrimination appears to be unconscious.

The report deals with understanding the problems that have arisen in the Pharmaceutical industry and the classes of drugs which are suffering the brunt of Chinese influx in the Indian market. Since our thrust area itself has to deal with the problems being faced by the pharmaceutical industry and the lack of self- reliance when it comes to APIs, we first decided to go with official government data of the APIs being imported from China and work commenced from there. Based on government data, market share, consumption, pricing of drugs and import reports, we selected two drugs, one being an anti-bacterial drug which requires fermentation namely, cephalosporins and the other being a well-known anti-diabetic drug, Metformin. Currently, we are looking at the various technologies being used in producing the two drugs which were shortlisted and, we’ll be further finding out the loopholes in the system and fixing it or suggesting novel techniques to make the Indian Pharmaceutical industry a powerhouse. Both cephalosporins and metformin have been majorly imported from China due to several loopholes in producing them here in India and to add to it, the strategic pricing employed by the Chinese manufacturers gives them an edge over indigenous products. The manufacturing processes and regulations for both cephalosporins and metformin, need to undergo an overhaul in order to compete with giants like China and thus displace them from their position of number 1 in this field. Finding loopholes in the technology and regulatory factors, suggesting novel technologies or improvements within current processes and performing a detailed cost analysis.

In recent years, the Minimum Support Price (MSP) and government procurement especially of paddy and wheat have been discussed widely, but these discussions have often drawn on evidence that is dated and incomplete. Consequently, such discussions have clouded the facts, resulting in a large number of factoids. According to these popular beliefs, very few farmers benefit (6% only), and primarily large farmers of Punjab and Haryana (and to some extent western Uttar Pradesh) benefit. In this article, we examine these three factoids and draw on multiple data sources to distil the facts. We argue that existing evidence suggests a more complex picture – (1) the MSP impacts 13(16)% paddy (wheat) sellers; (2) the geographies of procurement have expanded to new states including notably, Madhya Pradesh, Chhattisgarh and Odisha, and (3) Although, at the national level, there is a large farmer bias, this doesn’t imply exclusion of small and marginal farmers. In fact, majority of the beneficiaries are marginal and small farmers on both the extensive and the intensive margins. Further, we find substantial heterogeneity by states. Haryana for instance has a bias in favour of small and marginal farmers. We conclude that debates on the MSP and procurement must therefore take into account the changed geography of procurement and the profile of sellers and recognize the diversity of experiences with procurement across states.

Humanity's most pressing need is to learn how to live within our planet's boundaries --- something that likely means doing without economic growth. How, then, can we create a non-growth society that is both just and equitable? I attempt to address this question by looking at an aspect of sustainability (and equity) that is not often discussed: the growth of hierarchy. As societies consume more energy, they tend to become more hierarchical. At the same time, the growth of hierarchy also seems to be a key driver of income/resource inequality. In this essay, I review the evidence for the joint relation between energy, hierarchy and inequality. I then speculate about what it implies for achieving a sustainable and equitable future.

This paper maps the balance of benefits and risks underpinning the ECA/PIMCO proposal for a Liquidity and Sustainability Facility that would provide “concessional” repo financing to private investors in African sovereign bonds. In market speak, investors would finance their African sovereign debt holdings with LSF repo loans. The brief first examines the macrofinancial risks for African government bond issuers and for central banks that the LSF repo instrument engenders, as well as the developmental impact of a private-finance-led development paradigm that seeks the structural transformation of local financial systems towards bond-based finance. It then fleshes out the “Reform” and “Rethink” approaches to the ECA/PIMCO proposal. A reform of the institutional design of the LSF can minimise these macrofinancial risks. The Rethink approach in turn maps out alternative development pathways that prioritise local development banking instead of bond finance.

We analyze the effect of adverse health shocks on households' different expenditure shares using a difference in differences approach. We find that households engage in substitution between health and food spending in response to the negative health shocks. We find substantial heterogeneity in this trade-off between current and future health mediated by access to social protection, job contract type, and location (urban-rural). Households from rural areas, with heads holding informal jobs, and without access to safety nets, are more vulnerable than others. We discuss several policy implications.

The concept of "self-reliance" is widespread, but only recently there have been initiatives that not only use the term “self-reliance”, but also try to measure it – rather for refugees outside than in refugee camps, though. Thus, the “Camp Performance Indicator (CPI) system” was developed and applied to different case studies. This paper examines the level of self-reliance for camps in Jordan (Zaatari camp and Azraq camp) and Kenya (Dadaab Complex), but also for refugee settlements in Uganda (Nakivale and Bidibidi) and simultaneously tests the CPI, a tool consisting of 109 indicators. Applying the CPI revealed that the level of self-reliance is generally low in the five camps and settlements studied, backing up our initial hypothesis.

Working Paper - Centre of Excellence in Women and Child Health, UNESCO Chair on Youth Leadership, Aga Khan University, Kenya. Background: Sexual and gender-based violence (SGBV) in Kenya is frequently covered in digital news media. As a powerful influencer of public opinion, news media coverage can have a significant societal impact. This scoping review identifies the extent, nature, and themes of all available digital news media coverage on SGBV in Kenya from June 2019 to July 2020. It analyzes changes in coverage since the start of the COVID-19 pandemic. Method: The methodological framework for scoping reviews developed by Arksey and O’Malley (2005) guided the scoping review. The selected articles were analyzed using NVivo.Results: Analysis of the 340 included articles indicates clear trends in news media coverage on SGBV in Kenya. Before the COVID-19 pandemic, trends include high numbers of news reports, feature articles, and opinion pieces on SGBV, female genital mutilation (FGM) as the most covered form of SGBV, and opinion pieces in line with the Kenya Vision 2030 agenda. Since the implementation of the COVID-19 mitigation measures in Kenya, trends include an increase in news media coverage on SGBV, extensive reporting on the causes of the rise in SGBV cases in Kenya, and increased media attention for domestic and sexual violence.Conclusions: Analysis of the news media coverage demonstrates the health advocacy/agenda-setting role of the media. The increased reporting on SGBV since the implementation of the COVID-19 mitigation measures could facilitate broad-based awareness.

We study a simple savings scheme that allows workers to defer receipt of part of their wages for three months at zero interest. The scheme significantly increases savings during the deferral period, leading to higher post-disbursement spending on lumpy goods. Two years later, after two additional rounds of the savings scheme, we find that treated workers have made permanent improvements to their homes. The popularity of the scheme implies a lack of good alternative savings options. The results of a follow-up experiment suggest that demand for the scheme is partly due to its ability to address self-control 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.

Pedestrian accessibility is an important factor in urban transport and land use policy and critical for creating healthy, sustainable cities. Developing and evaluating indicators measuring inequalities in pedestrian accessibility can help planners and policymakers benchmark and monitor the progress of city planning interventions. However, measuring and assessing indicators of urban design and transport features at high resolution worldwide to enable city comparisons is challenging due to limited availability of official, high quality, and comparable spatial data, as well as spatial analysis tools offering customizable frameworks for indicator construction and analysis. To address these challenges, this study develops an open source software framework to construct pedestrian accessibility indicators for cities using open and consistent data. It presents a generalized method to consistently measure pedestrian accessibility at high resolution and spatially aggregated scale, to allow for both within- and between-city analyses. The open source and open data methods developed in this study can be extended to other cities worldwide to support local planning and policymaking. The software is made publicly available for reuse in an open repository.

Scenarios used by the Intergovernmental Panel on Climate Change (IPCC) are central to climate science and policy. Recent studies find that observed trends and International Energy Agency (IEA) projections of global CO2 emissions have diverged from emission scenario outlooks widely employed in climate research. Here, we quantify the bases for this divergence, focusing on Kaya Identity factors: population, per-capita gross domestic product (GDP), energy intensity (energy consumption/GDP), and carbon intensity (CO2 emissions/energy consumption). We compare 2005–2017 observations and IEA projections to 2040 of these variables, to ‘baseline’ scenario projections from the IPCC’s Fifth Assessment Report (AR5), and from the shared socioeconomic pathways (SSPs) used in the upcoming Sixth Assessment Report (AR6). We find that the historical divergence of observed CO2 emissions from baseline scenario projections can be explained largely by slower-than-projected per-capita GDP growth—predating the COVID-19 crisis. We also find carbon intensity divergence from baselines in IEA’s projections to 2040. IEA projects less coal energy expansion than the baseline scenarios, with divergence expected to continue to 2100. Future economic growth is uncertain, but we show that past divergence from observations makes it unlikely that per-capita GDP growth will catch up to baselines before mid-century. Some experts hypothesize high enough economic growth rates to allow per-capita GDP growth to catch up to or exceed baseline scenarios by 2100. However, we argue that this magnitude of catch-up may be unlikely, in light of: headwinds such as aging and debt, the likelihood of unanticipated economic crises, the fact that past economic forecasts have tended to over-project, the aftermath of the current pandemic, and economic impacts of climate change unaccounted-for in the baseline scenarios. Our analyses inform the rapidly evolving discussions on climate and development futures, and on uses of scenarios in climate science and policy.

Enemies of the people were the millions of artists, engineers, professors, and affluent peasants that were thought a threat to the Soviet regime for being the educated elite, and were forcedly resettled to the Gulag, i.e. the system of forced labor camps across the Soviet Union. In this paper we look at the long-run consequences of this dark re-location episode. We show that areas around camps with a larger share of enemies among camp prisoners are more prosperous today, as captured by firms’ wages and profits, as well as night lights per capita. We also show that the descendants of enemies are more likely to be tertiary educated today. Our results point in the direction of a long-run persistence of education and a resulting positive effect on local economic outcomes. A 28 percentage point increase in the share of enemies increases night lights per capita by 58%, profits per employee by 65%, and average wages by 22%.

Background: A large body of evidence evaluates the impact of cash transfers (CTs) on physical health and economic indicators. A growing amount of research on CTs contains measures of subjective well- being (SWB) and mental health (MH) but no attempt has been made to systematically synthesize this work.Methods/design: We undertook a systematic review and meta-analysis of RCTs and quasi- experimental studies, including peer-reviewed publications and grey literature (e.g. reports, pre-prints, and working papers), conducted over the period 2000-2020, examining the impact of CTs on self- reported SWB and MH outcomes.Results: Two authors (JM and CK) double-screened 1,147 records of potentially relevant studies, finding 38 studies suitable for inclusion in our meta-analysis, covering 100 outcomes and a total sample of n=114,274 individuals. The average effect size (Cohen’s d) of 38 CT studies on our composite outcome of MH and SWB is 0.10 standard deviations (SDs) (95% CI: 0.8, 0.13) for an average time until follow-up of two years. However, there is a substantial amount of heterogeneity in the estimated effects (I-squared = 64% and 95% Prediction interval: 0.0021, 0.215). CT value, both in absolute terms and relative to previous income, are significant predictors of the effect size. We find only weak evidence that the impact diminishes over time. Four randomized controlled trials in our sample were designed to identify the spillover effects of CTs on the SWB and MH outcomes of non-recipients. Two found negative spillovers but the average effect is not statistically significant and is close to zero.Discussion: Cash transfers significantly increase MH and SWB in low- and middle-income countries. More research on the long run (5+ years) effects is needed, as well as further analysis of the community and household spillover effects of cash transfers on MH and SWB outcomes. We encourage the inclusion of MH and SWB metrics in impact evaluations of interventions to enable the assessment of their relative cost-effectiveness at improving lives compared to cash transfers.

Economic growth is measured as the rate of relative change in gross domestic product (GDP) per capita. Yet, when incomes follow random multiplicative growth, the ensemble-average (GDP per capita) growth rate is higher than the time-average growth rate achieved by each individual in the long run. This mathematical fact is the starting point of ergodicity economics. Using the atypically high ensemble-average growth rate as the principal growth measure creates an incomplete picture. Policymaking would be better informed by reporting both ensemble-average and time-average growth rates. We analyse rigorously these growth rates and describe their evolution in the United States and France over the last fifty years. The difference between the two growth rates gives rise to a natural measure of income inequality, equal to the mean logarithmic deviation. Despite being estimated as the average of individual income growth rates, the time-average growth rate is independent of income mobility. (Stone Center on Socio-Economic Inequality Working Paper)

This paper studies the relationship between social capital on the green growth in Malaysia, with the aim of ascertaining whether faith based social capital has a role in sustaining economic growth. The study utilizes the annual data over the period of 1970-2015. This study employs the Autoregressive Distributed Lag (ARDL) model and causality using the Vector Error Correction Model (VECM). The findings demonstrate the long and short-run associations between social capital and green growth in Malaysia. The causality only runs in a unidirection from social capital to the green economic growth. The findings have important policy implications for green economic growth measurement to account for social well-being and to fulfil the objectives of Islamic Sharia.

Glass ceiling is an important issue in the developed world, but there are few studies on the developing world, especially on the private sector of Bangladesh. Therefore, this study aims to determine the influences of the factors of glass ceiling on the job satisfaction and job switching decisions among the female employees in the private sector of Bangladesh. This study conducted structured questionnaire surveys on 192 female employees from two private sector industries – banking and telecommunication in Bangladesh. The data were collected in December 2013 by using random sampling technique. The study used Ordered Logit and Binary Logit regressions. The study found that women employees working in banking sector hold more job satisfaction than those of telecommunication sector. Further, the study found that glass ceiling related variables has no significant relationship with the job satisfaction of women employees but there are several glass ceiling factors that statistically significantly influence on the decisions of changing or switching the existing jobs of women employees. Those who feel they are discriminated by any male colleague or being discriminated to move to higher level management positions or discriminated for promotions or holding less job security are likely to change their existing jobs. To improve the situation, several initiatives need to be taken in the organization like awareness building, standard and ethical human resource practices, strict policies for discriminatory attitudes and behavior etc.

Culture has played a pivotal role in human evolution. Yet, the ability of social scientists to study culture is limited by the currently available measurement instruments. Scholars of culture must regularly choose between scalable but sparse survey-based methods or restricted but rich ethnographic methods. Here, we demonstrate that massive online social networks can advance the study of human culture by providing quantitative, scalable and high-resolution measurement of behaviourally revealed cultural values and preferences. We employ data across nearly 60 000 topic dimensions drawn from two billion Facebook users across 225 countries and territories. We first validate that cultural distances calculated from this measurement instrument correspond to traditional survey-based and objective measures of cross-national cultural differences. We then demonstrate that this expanded measure enables rich insight into the cultural landscape globally at previously impossible resolution. We analyse the importance of national borders in shaping culture and compare subnational divisiveness with gender divisiveness across countries. Our measure enables detailed investigation into the geopolitical stability of countries, social cleavages within small- and large-scale human groups, the integration of migrant populations and the disaffection of certain population groups from the political process, among myriad other potential future applications. Á.C. acknowledges funding from the European Union’s Horizon 2020 innovation action program under grant agreement no. 101019206 (TESTABLE project); and the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M (‘Fostering Young Doctors' Research’, UE-MEASURE-CM-UC3M). R.C. acknowledges funding from H2020 EU Project PIMCITY (grant no. 871370) and the Taptap Digital-UC3M Chair in Advanced AI and Data Science applied to Advertising and Marketing. Á.C., R.C, K.D, I.O.-O. and Ö.Ö. acknowledge funding from ECO2013-42710-P, MDM 2014-0431 and Fundacion BBVA. I.M. acknowledges funding from the Spanish Ministry of education with the FPU programme (FPU15/03518).

We exploit changes in U.S. visa policies for nurses to measure the origin-country human capital response to international migration opportunities. Combining data on all migrant departures and postsecondary institutions in the Philippines, we show that nursing enrollment and graduation increased substantially in response to greater U.S. demand for nurses. The supply of nursing programs expanded. Nurse quality, measured by licensure exam pass rates, declined. Despite this, for each nurse migrant, 9 additional nurses were licensed. New nurses switched from other degree types, but graduated at higher rates than they would have otherwise, increasing the human capital stock in the Philippines.

This paper demonstrates the acute sensitivity of education program effectiveness to the choices of inputs and outcome measures, using a randomized evaluation of a mother-tongue literacy program. The program raises reading scores by 0.64 SD and writing scores by 0.45 SD. A reduced-cost version instead yields statistically insignificant reading gains and some large negative effects (−0.33 SDs) on advanced writing. We combine a conceptual model of education production with detailed classroom observations to examine the mechanisms driving the results; we show they could be driven by the program initially lowering productivity before raising it, and potentially by missing complementary inputs in the reduced-cost version.

We analyze consumption distribution in India purely on the basis of location – a combination of the state and sector (urban, rural) – and find that it explains a third of the variation in living standards. Consumption is also shown to be positively related to locational inequality. The main reason is that in poorer locations, consumption is tightly (less unequally) distributed around a low level, making class a poor predictor of higher living standards compared to the aggregate. In effect, from an individual’s perspective, living standards are higher in richer, but more unequal, locations in India. We analyze these paradoxes as evidence of an ongoing Kuznets type processes. Our results have implications for the persistence of economic migration within a fast-growing emerging economy. Individuals can choose to change their location to enjoy better living standards, but not necessarily trade other social, or individual predictors, like caste, religion and gender.

Neoclassical economists fundamentally misunderstand the role of natural resources in the economy. I discuss here the source of this misunderstanding, and the ways we can better understand the role of energy to human societies.

Authoritative economic growth forecasts are often optimistically biased. Negatively skewed variation--negative shocks being larger than positive shocks--could contribute to bias by making long-run average growth smaller than typical-year (median) growth. This positively biases forecasts based on typical years. We compare medians and means in real per-capita GDP growth across countries, regions, and time windows from 1820-2016. Over decadal periods, we find mean growth rates

The Wall Street Consensus is an elaborate effort to reorganize development interventions around partnerships with global finance. The UN's Billions to Trillions agenda, the World Bank's Maximizing Finance for Development or the G20's Infrastructure as an Asset Class update the Washington Consensus for the age of the portfolio glut, to ‘escort’ global (North) institutional investors and the managers of their trillions into development asset classes. Making development investible requires a two‐pronged strategy: enlist the state into risk‐proofing development assets and accelerate the structural transformation of local financial systems towards market‐based finance that better accommodates portfolio investors. Ten policy commandments forge the ‘de‐risking state’. They create a safety net for investors in development assets, protecting their profits from demand risks attached to commodified infrastructure assets; from political risks attached to (progressive) policies that would threaten cash flows, including nationalization, higher minimum wages and, critically, climate regulation; and from liquidity and currency risks. These risks are transferred to the balance sheet of the state. The new ‘development as de‐risking’ paradigm narrows the scope for a green developmental state that could design a just transition to low‐carbon economies.

This paper offers a historical analysis on how post-Socialist China’s transition to a globalised mixed-market economy led to class restructuring and estimates the drivers of its inter-decile income shares over the period 1978-2015 using Piketty et al. (2019)’s dataset. The key negative determinants of the bottom 50 percent are government consumption, trade openness and unemployment rate. The stable middle 40 percent is explained by the positive effects of government consumption, financial liberalisation and public indebtedness that compensate for the adverse effects of trade openness. Further, we find that government consumption, trade openness, and unemployment rate are positive determinants of the top 10 percent. More strikingly, trade openness disproportionately benefits the top 10 percent and this suggests that even China’s pragmatic world integration has been partial to business elites. Several policy ideas follow. First, China must overhaul its middle class urban-biased fiscal expenditure and second, the pension system must extend to the entirety of its income distribution. Third, stronger social welfare is required in the context of globalisation.

The lockdown of economic activity in many countries as a measure to stop the spread of the COVID-19 pandemic has led to high levels of unemployment and other indicators of a potentially upcoming economic crisis. As a gauge of the seriousness of these concerns some have suggested that current levels of some of these indicators have not been seen in the US since the time of the great depression. This paper explores how General Collective Intelligence, a recent innovation in group decision-making systems, might reliably generate the economic growth needed to avert such a crisis where not reliably achievable otherwise. Current group decision-making systems, whether choosing a human decision-maker, consensus voting on decisions, or automated decision-systems such as conventional collective intelligence, have been suggested to lack the capacity to maximize more than a very few group outcomes simultaneously due to specific limitations. Since impact on collective well-being is determined by impact on an open (unbounded) set of outcomes, this implies lack of the capacity to maximize the necessary range of impacts on well-being for groups if that range is too broad. If so, the breadth of impact required to achieve sustainable “green” economic development while simultaneously solving hunger, solving the environmental degradation that consensus has linked to climate change, as well as providing maximal access to healthcare, education, and other resources, may not be reliably possible with current decision systems. General Collective Intelligence or GCI replicates the adaptive problem solving mechanisms by which nature has demonstrated the ability to optimally respond to an unlimited set of problems, and by which nature has demonstrated the ability to potentially increase sustainability per unit of resources by orders of magnitude so that life is reliably self-sustaining. This paper explores why GCI can potentially be used to reliably drive self-sustaining economic growth to revive economies in the aftermath of the COVID-19 pandemic, and why GCI has the potential to reliably drive a transformation to sustainable green economies while doing so.

A growing demographic literature has examined the impacts of climatic variability on human populations. Most of this work has focused on migration, morbidity, and mortality. Much less attention has been given to the effects of climate change on fertility, which represents an important gap given many plausible reasons to expect such effects. We address this issue by examining the relationship between exposure to flooding and fertility in Bangladesh. We link birth records (n=355,532 person-years) from the Demographic and Health Survey (DHS) with satellite-derived measures of flooding from 2002 through 2014 and estimate statistical models of the relationship between flood exposure and subsequent fertility outcomes. We also conduct secondary analyses of the relationship between flood exposure and four expected causal pathways: women’s marriage, contraceptive use, employment, and health. Results suggest that flood exposure reduces the probability of childbearing, and that this effect operates with a two-year lag. Negative effects are concentrated among women with a primary school education or higher and low-parity women. In contrast, women at high parities (e.g., at or above four) tend to increase their fertility in response to flooding. We find little evidence that observed flooding effects operate through the causal pathways we test, raising questions for future research about the mechanisms that explain our findings.