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The OPIC Scraped Portfolio Dataset

Despite major improvements in OPIC’s transparency, there still is no single publicly available dataset that includes comprehensive information about the agency’s portfolio. OPIC has a searchable project dataset, but it only includes very basic information. Digging deeper requires clicking through hundreds of project descriptions (in PDF format), which very few people are willing to do. We built a better, scraped dataset, available now with as a detailed collection of nearly 1,500 OPIC projects over the past fifteen years.

Share of Global Area under GMO Cultivation (by country)

More than three-quarters of the acreage under GMO cultivation is in just three countries: the United States, Brazil, and Argentina. And almost all of the modified crops have been designed to either resist insects or tolerate herbicides used to kill weeds, which is helpful only to farmers with access to those chemical inputs.

Area of Land under Cultivation of Genetically Modified Crops (by type)

Large multinational corporations developed most currently available GMOs with large-scale, industrial agriculture in mind. These GMOs have had clear benefits for some farmers, seed companies, and herbicide producers (the latter two are often the same), but less tangible benefits for consumers.

Energy Poverty in Sub-Saharan Africa

Sub-Saharan Africa is both broadly and deeply energy poor: only 32 percent of the total population has “modern energy access” using even the minimal IEA definition. Even in urban areas, access averages only 59 percent.

Income Categories and Proposed Energy Categories

Energy use is highly correlated with a country’s income category. No rich country consumes less than 5,000 kWh/person/year; no poor country consumes more than 300 kWh/person/year. Just as countries are categorized as low, lower middle, upper middle, and high income, energy categories could be established for extreme low energy, low energy, middle energy, and high energy , on the basis of annual per capita energy use.

Median Income / Consumption Data as Extracted from the World Bank’s PovcalNet

By making this data public, we hope to encourage more development professionals to use the median in evaluating individuals’ material well-being in developing (and developed) countries and progress toward broad-based economic growth and shared prosperity. We also hope that wider use of the median will provide an incentive for the World Bank to publish the data in an easily accessible format along with the full distribution, in line with its open data policy.

Median Income versus GDP

Median measures of well-being give us a better picture than the mean of the well-being of a “typical” individual. Take Nigeria and Tanzania: in 2010, Nigeria’s GDP per capita (at PPP) was $5,123; Tanzania’s stood at only $2,111. This suggests that Nigerians were more than twice as well off as Tanzanians. Yet, if we compare consumption medians, a different picture emerges: a Nigerian at the middle of the income distribution lived on $1.80 a day, while his or her Tanzanian counterpart had 20 cents more to spend, at $2 a day.

Shares of Global Aid vs. Shares of Global Poor

There are big gaps between where aid gets spent and where the poor live. In the graph, countries to the right of the diagonal line receive a share of aid that is less than their share of people living in poverty. Asia is the standout case of this mismatch.

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