rafmacalaba/datause-encoder-data huggingface dataset:
Survey Measurement Errors and the
            Assessment of the Relationship between Yields and Inputs in
            Smallholder Farming Systems : Evidence from Mali
An accurate understanding of how input
            use affects agricultural productivity in smallholder farming
            systems is key to designing policies that can improve
            productivity, food security, and living standards in rural
            areas. Studies examining the relationships between
            agricultural productivity and inputs typically rely on land
            productivity measures, such as crop yields, that are
            informed by self-reported survey data on crop production.
            This paper leverages unique survey data from Mali to
            demonstrate that self-reported crop yields, vis-à-vis
            (objective) crop cut yields, are subject to non-classical
            measurement error that in turn biases the estimates of
            returns to inputs, including land, labor, fertilizer, and
            seeds. The analysis validates an alternative approach to
            estimate the relationship between crop yields and
            agricultural inputs using large-scale surveys, namely a
            within-survey imputation exercise that derives predicted,
            otherwise unobserved, objective crop yields that stem from a
            machine learning model that is estimated with a random
            subsample of plots for which crop cutting and self-reported
            yields are both available. Using data from a methodological
            survey experiment and a nationally representative survey
            conducted in Mali, the analysis demonstrates that it is
            possible to obtain predicted objective sorghum yields with
            attenuated non-classical measurement error, resulting in a
            less biased assessment of the relationship between yields
            and agricultural inputs. The discussion expands on the
            implications of the findings for (i) future research on
            agricultural intensification, and (ii) the design of future
            surveys in which objective data collection could be limited
            to a subsample to save costs, with the intention to apply
            the suggested machine learning approach.
Impacts of Energy Efficiency
            Projects in Developing Countries : Evidence from a Spatial
            Difference-in-Differences Analysis in Malawi
Spatial difference-in-differences
            analysis is used to study the impacts of a large-scale
            development intervention aimed at improving energy
            efficiency in Malawi. The estimation strategy takes
            advantage of the geographical variation in the
            implementation of different project components and is based
            on a combination of remote-sensing (satellite) data and
            national household survey data. The results suggest that a
            combination of demand-side and supply-side interventions was
            associated with a statistically significant increase in
            electricity access, a decrease in the frequency of
            blackouts, and a switch from traditional fuels to
            electricity as the main source of energy for lighting (but
            not for cooking). At the same time, there is no evidence
            that the intervention caused households to pay more for
            electricity. The results are consistent with an emerging
            view in the literature that there are synergies between
            energy efficiency and energy access, especially in places
            where the bottleneck to wider electricity access is limited
            electricity generation capacity rather than the cost of
            connecting more clients to the grid.
Urban CO2 Emissions : A Global
            Analysis with New Satellite Data
This paper estimates an urban carbon
            dioxide emissions model using satellite-measured carbon
            dioxide concentrations from 2014 to 2020, for 1,236 cities
            in 138 countries. The model incorporates the global trend in
            carbon dioxide concentration, seasonal fluctuations by
            hemisphere, and a large set of georeferenced variables that
            incorporate carbon dioxide&#x2013;intensive industry
            structure, emissions from agricultural and forest fires in
            neighboring areas, demography, the component of income that
            is uncorrelated with industry structure, and relevant
            geographic conditions. The income results provide the first
            test of an Environmental Kuznets Curve relationship for
            carbon dioxide based on actual observations. They suggest an
            environmental Kuznets curve that reaches a peak near or
            above $40,000 per capita, which is at the 90th percentile
            internationally. The research also finds that economic
            development has a significant effect on the direction of the
            relationship between population density and carbon dioxide
            emissions. The relationship is positive at very low incomes
            but becomes negative at higher incomes. The paper also uses
            cities&#x2019; mean regression residuals to index their
            carbon dioxide emissions performance within and across
            regions, decomposes model carbon dioxide predictions into
            broad source categories for each city, and uses the
            regression residuals to explore the impact of subway
            systems. The findings show significantly lower carbon
            dioxide emissions for subway cities.
Becoming Legible to the State : The
            Role of Identification and Collection Capacity in Taxation
Whereas the tax compliance literature
            emphasizes verifying tax liability amounts, this paper
            highlights two other tax capacity dimensions of particular
            relevance in lower-income countries: identifying taxable
            entities and enforcing collection of known liabilities.
            Leveraging a newly-digitized property database, a randomized
            experiment in Liberia finds that including identifying
            information (owners' names and property photographs) in
            tax notices more than quadruples the payment rate, from 2
            percent to almost 10 percent, when the notice also details
            noncompliance penalties. A second experiment finds that
            signaling greater collection probability to delinquent
            taxpayers further increases compliance. These results
            highlight the importance of targeted investments in tax capacity.
The Macroeconomy After Tariffs
What does the macroeconomy look like in
            the aftermath of tariff changes? This paper estimates
            impulse response functions from local projections using a
            panel of annual data that spans 151 countries over
            1963&#x2013;2014. Tariff increases are associated with
            persistent, economically and statistically significant,
            declines in domestic output and productivity, as well as
            higher unemployment and inequality, real exchange rate
            appreciation and insignificant changes to the trade balance.
            Output and productivity impacts are magnified when tariffs
            rise during expansions and when they are imposed by more
            advanced or smaller (as opposed to developing or larger)
            economies; effects are asymmetric, being larger when tariffs
            go up than when they fall. While firmly establishing
            causality is always a challenge, the results are robust to a
            large number of perturbations to the baseline methodology,
            and hold using both macroeconomic and industry-level data.
Corridors without Borders in West Africa
This paper estimates the welfare gains
            from upgrading several major regional corridors in West
            Africa. It uses a quantitative economic geography framework
            with trade within and across countries and mobility of
            people within countries to assess the economic impacts of
            the reduction in trade costs from road and border
            infrastructure investments. The findings show that the
            upgrade of Dakar-Lagos regional road corridor brings sizable
            economic benefits relative to investment costs, with a
            benefit-cost ratio estimated around 3. The economic benefits
            of road corridor upgrades are doubled and more widely spread
            when combined with measures to reduce current massive border
            delays. The benefits are negligible for Nigeria, but large
            for small fragile states (Guinea-Bissau, Liberia, and Sierra
            Leone). The gains are highest for corridors connecting large
            economies, and smaller and more fragile countries gain
            proportionally more from accessing larger markets. Finally,
            regional investments, including border time reduction
            policies, will reduce spatial inequality in the whole region
            but might increase inequality in some countries.
Demographic and Spatial Disparities
            in Labor Market Outcomes within the Kinshasa Urban Landscape
This paper examines the labor market and
            jobs in urban Kinshasa, by drawing on a recently collected
            household survey and other data sets. It particularly
            focuses on labor supply and employment patterns, job
            characteristics, and their spatial nexus. The analysis first
            shows that female and young workers are more likely to
            experience unemployment and underemployment than other
            workers in Kinshasa. Second, the availability of good
            quality jobs is still limited in Kinshasa. Third, in
            addition to the scarcity of good jobs, which are
            concentrated in the city core, poor accessibility due to the
            limited connective infrastructure and transport system
            further reduces job opportunities for people living in the outskirts.
Urban Agglomeration and Firm
            Innovation: Evidence from Developing Asia
This paper examines the relationship
            between urban agglomeration and firm innovation using a
            recently developed dataset that consistently measures city
            boundaries across Asia together with geo-referenced
            firm-level data. It finds that the spatial distribution of
            innovation by firms is highly concentrated within countries.
            Further, firms in larger cities have substantially higher
            propensities to introduce product and process innovations
            and undertake R&D activities, a result that holds for
            subgroups of countries and even when the largest cities are
            excluded from the analysis. Finally, the presence of high
            quality universities and highly ranked engineering
            departments in cities is positively associated with firm
            innovation, lending support to the idea that the
            accumulation of human capital locally is a key channel
            through which urban agglomeration affects innovation.
Forced Displacement, Gender, and
            Livelihoods : Refugees in Ethiopia
This study uses the Ethiopia Skills
            Profile Survey (2017) to examine the gender differences in
            livelihood opportunities and activities between refugees and
            host communities. The results show that refugees are
            significantly less likely to be in employment, and that
            household characteristics influence women’s economic
            opportunities. While having a female household head, access
            to agricultural land, and the number of female adults
            increased female participation in economic activities,
            conversely, higher numbers of children in the household
            significantly reduce women’s opportunities. Higher education
            attainment boosts both male and female refugees’
            participation in wage employment. Among refugees, Somali
            refugees have relatively better access to employment
            opportunities compared to other refugee groups, especially
            refugees from South Sudan and Sudan.
Mangroves as Coastal Protection for
            Local Economic Activities from Hurricanes in the Caribbean
In recent decades, hurricane frequency
            and intensity have increased in the Caribbean Basin. From
            2000 to 2012, more than 100 hurricanes impacted lives,
            infrastructure, and economic activity along the region’s
            shorelines. Studies suggest that mangrove forests’ dense
            root systems might mitigate the impact of hurricanes, which
            would help stabilize the coastline and prevent erosion from
            waves and storms. Although many tropical mangroves are found
            on Caribbean coasts, climatic and anthropogenic events have
            been clearing these wetland ecosystems at an annual rate of
            1 percent since the 1990s. This study quantifies the effects
            of hurricane windstorms on economic activity using
            nightlight as a proxy at the highest spatial resolution data
            available (1 square kilometer). Using different widths of
            the mangrove belt, it measures levels of mangrove natural
            protection against the impact of hurricanes and studies the
            broader socioeconomic and environmental effects of this
            protection. The results suggest that while major hurricanes
            reduce nightlight by approximately 2 percent and up to 16
            percent in storm surge prone areas, the presence of
            mangroves on the coast mitigates the impact of hurricanes,
            reducing nightlight by 1–6 percent.
Estimating the Impact of Weather on Agriculture
This paper quantifies the significance
            and magnitude of the effect of measurement error in remote
            sensing weather data in the analysis of smallholder
            agricultural productivity. The analysis leverages 17 rounds
            of nationally-representative, panel household survey data
            from six countries in Sub-Saharan Africa. These data are
            spatially linked with a range of geospatial weather data
            sources and related metrics. The paper provides systematic
            evidence on measurement error introduced by (1) different
            methods used to obfuscate the exact GPS coordinates of
            households, (2) different metrics used to quantify
            precipitation and temperature, and (3) different remote
            sensing measurement technologies. First, the analysis finds
            no discernible effect of measurement error introduced by
            different obfuscation methods. Second, it finds that simple
            weather metrics, such as total seasonal rainfall and mean
            daily temperature, outperform more complex metrics, such as
            deviations in rainfall from the long-run average or growing
            degree days, in a broad range of settings. Finally, the
            analysis finds substantial amounts of measurement error
            based on remote sensing products.  In extreme cases, the
            data drawn from different remote sensing products result in
            opposite signs for coefficients on weather metrics, meaning
            that precipitation or temperature drawn from one product
            purportedly increases crop output while the same metrics
            drawn from a different product purportedly reduces crop
            output. The paper concludes with a set of six best practices
            for researchers looking to combine remote sensing weather
            data with socioeconomic survey data.
What Has Been the Impact of COVID-19
            on Debt Turning a Wave into a Tsunami
This paper presents a comprehensive
            analysis of the impact of COVID-19 on debt, puts recent debt
            developments and prospects in historical context, and
            analyzes new policy challenges associated with debt
            resolution. The paper reports three main results. First,
            even before the pandemic, a rapid buildup of debt in
            emerging market and developing economies—dubbed the “fourth
            wave” of debt—had been underway. Because of the sharp
            increase in debt during the pandemic-induced global
            recession of 2020, the fourth wave of debt has turned into a
            tsunami and become even more dangerous. Second, five years
            after past global recessions, global government debt
            continued to increase. In light of this historical record,
            and given large financing gaps and significant investment
            needs in many countries, debt levels will likely continue to
            rise in the near future. Third, debt resolution has become
            more complicated because of a highly fragmented creditor
            base, a lack of transparency in debt reporting, and a legacy
            stock of government debt without collective action clauses.
            National policy makers and the global community need to act
            rapidly and forcefully ensure that the fourth wave does not
            end with a string of debt crises in emerging market and
            developing economies as earlier debt waves did.
Political Prioritization of Early
            Childhood Education during the COVID-19 Pandemic : A
            Comparative Policy Analysis of Low- and Middle-Income Countries
Despite strong evidence of its
            importance to the welfare of children and societies, early
            childhood education has been comparatively neglected as a
            policy priority both before and during the COVID-19
            pandemic. This paper seeks to understand what factors have
            contributed to the lack of priority for early childhood
            education in distance learning and school reopening plans,
            by applying a political prioritization framework to the
            pandemic context in four low- and middle-income countries:
            Ethiopia, Jamaica, Liberia, and Pakistan. Some aspects of
            the pre-COVID-19 status quo, which disfavored early
            childhood education, have continued, including a lack of
            cohesive support from civil society and a greater focus by
            international partners on norm promotion and technical
            assistance than financing. In other respects, the pandemic
            put early childhood education at an even greater
            disadvantage. These include perceptions that early childhood
            education is less suited to distance delivery than other
            levels of education, concerns about young children’s ability
            to comply with health protocols, and competition with
            high-stakes examinations for education ministries’
            attention. Previous country experience with pandemics (in
            Liberia) and a strong coordinating entity (in Jamaica) were
            mitigating factors. These results point to an urgent need to
            elevate priority for early childhood education in normal
            times and improve the resilience of early childhood
            education in future crises.
Occupational Hazards : Migrants and
            the Economic and Health Risks of COVID-19 in Western Europe
This paper investigates the economic and
            health risks arising from the COVID-19 pandemic for migrant
            workers in the European Union. It first assesses migrants’
            economic and health vulnerabilities using ex ante measures
            based on both supply and demand shocks. The analysis finds
            that immigrants were more vulnerable than native-born
            workers to both income- and health-related risks, and that
            this greater exposure stems from the occupations in which
            migrant workers are concentrated. Migrants work to a greater
            degree than native-born citizens in occupations that are
            less amenable to teleworking arrangements, and in economic
            sectors that experienced greater reductions in demand during
            the pandemic. This has led to an increase in both their
            income and employment risks. The paper shows that individual
            characteristics, such as educational attainment, age, and
            geographical location, fail to explain the native-migrant
            gap in exposure to economic and health risks posed by the
            pandemic. Limited language ability, the concentration of
            migrants in jobs with labor shortages among native-born
            workers, and a reliance on immigrant networks to find jobs
            all appear to play significant roles in migrants’ exposure
            to pandemic-related risks. Finally, the paper finds that
            actual job losses in 2020, the first year of the pandemic,
            are highly correlated with ex-ante vulnerabilities:
            immigrant workers experienced significantly higher rates of
            job losses, which partly originates from their greater
            concentration in non-teleworkable jobs. Ex-ante
            vulnerabilities, however, only explain part of the
            migrant-native gap in job losses that followed the pandemic
            and being an immigrant still imposes additional risks.
Building State Capacity : What Is
            the Impact of Development Projects
Although research has established the
            importance of state capacity in economic development, less
            is known about how state capacity comes about and the role
            of external partners in the process. This paper estimates
            the impact of an external project designed to build state
            capacity in a low-income country. Specifically, it evaluates
            a multilateral development bank project in Tanzania,
            designed to incentivize investments in local state capacity
            by offering grants conditional on institutional performance
            scores. This program typifies many development projects to
            build state capacity implemented around the world by
            development agencies. The paper uses a
            difference-in-differences methodology to estimate the
            project impact, comparing outcomes between 18 project and 22
            non-project local governments over 2016–18. Outcomes were
            measured through two rounds of primary surveys of nearly 500
            local government officials and nearly 3,000 households. Over
            the course of the project, measured state capacity improved
            in project areas, but due to comparable gains in non-project
            areas, the project’s value-added to change in state capacity
            is estimated to be zero across all the dozens of relevant
            variables in the surveys. The data suggest that improvements
            in state capacity in Tanzania resulted from endogenous
            changes in trust and legitimacy in the country rather than
            from financial incentives offered by external partners.