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While some studies predict automation to eliminate jobs at a dizzying rate, disruptive technologies can also create new lines of work. Our working draft of the forthcoming 2019 World Development Report, The Changing Nature of Work, notes that in the past century robots have created more jobs than they have displaced. The capacity of technology to exponentially change how we live, work, and organize leaves us at the World Bank Group constantly asking: How can we adapt the skills and knowledge of today to match the jobs of tomorrow?
One answer is to harness the data revolution to support new pathways to development. Some 2.5 quintillion bytes of data are generated every day from cell phones, sensors, online platforms, and other sources. When data is used to help individuals adapt to the technology-led economy, it can make a huge contribution toward ending extreme poverty and inequality. Technology companies, however well intended, cannot do this alone.
As we mark International Women’s Day 2018, there has never been a more critical time to invest in people, especially in women and girls.
Skills, knowledge, and know-how – collectively called human capital – have become an enormous share of global wealth, bigger than produced capital such as factories or industry, or natural resources.
But human capital wealth is not evenly distributed around the world, and it’s a larger slice of wealth as countries develop. How, then, can developing countries build their human capital and prepare for a more technologically demanding future?
The answer is they must invest much more in the building blocks of human capital – in nutrition, health, education, social protection, and jobs. And the biggest returns will come from educating and nurturing girls, empowering women, and ensuring that social safety nets increase their resilience.
According to UNESCO estimates, 130 million girls between the age of 6 and 17 are out of school, and 15 million girls of primary-school age – half of them in sub-Saharan Africa – will never enter a classroom. Women’s participation in the global labor market is nearly 27 percentage points lower than for men, and women’s labor force participation fell from 52 percent in 1990 to 49 percent in 2016.
What if we could fix this?
Is the era of industrialization and manufacturing exports growth miracles – a period of rapid economic growth exceeding expectations, last seen in East Asian countries, most notably in China – over? If you listen to Harvard’s Dani Rodrik, the answer seems to be: pretty much! Does that mean, Africa, the only continent which hasn’t seen rapid export-led manufacturing growth, would not have many growth miracle stories?
For three days this month, the West African nation of Senegal was in the spotlight of global efforts to combat climate change and improve education in a rapidly changing world.
French President Emmanuel Macron and Senegal’s President Macky Sall co-hosted a conference in Dakar to replenish the Global Partnership for Education (GPE) – a funding platform to help low-income countries increase the number of children who are both in school and learning.
African leaders and partners stepped up to announce their commitment to provide an education that prepares children to compete in the economy of the future and advances socio-economic progress.
Heads of state from across the continent described their challenges—including terrorism, insecurity, the influx of refugee children who need an education, the strain on national budgets, and the cultural bias against educating girls.
Crisis is becoming a new normal in the world today. In 2017 alone, adverse natural events resulted in global losses of about $330 billion, making last year the costliest ever in terms of global weather-related disasters. Climate change, demographic shifts, and other global trends may also create fragility risks.
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. As we said in this month’s Global Economic Prospects report, for the first time since the financial crisis, the World Bank is forecasting that the global economy will be operating at or near full capacity. We anticipate growth in advanced economies to moderate slightly, but growth in emerging markets and developing countries should strengthen to 4.5% this year.
When asked if he would like to have dinner at a highly-regarded restaurant, Yogi Berra famously replied “Nobody goes there anymore. It’s too crowded”. This contradictory situation of very low take-up combined with large overall use is common with some financial products – for example, the response rate to direct mail credit card solicitations had fallen to 0.6 percent by 2012, yet lots of people have credit cards.
It is also a situation we recently found ourselves in when working on a financial education experiment in Mexico with the bank BBVA Bancomer. They worked with over 100,000 of their credit card clients, inviting the treatment group to attend their financial education program Adelante con tu futuro (Go ahead with your future). Over 1.2 million participants have taken this program between 2008 and 2016, yet only 0.8 percent of the clients in the treatment group attended the workshop. A second experiment which tested personalized financial coaching also had low take-up, with 6.8 percent of the treatment group actually receiving coaching.
In a new working paper (joint with Gabriel Lara Ibarra), we discuss how the richness of financial data on clients allows us to combine experimental and non-experimental methods to still estimate the impact of this program for those clients who do take up the program.
The rate of change in human development outcomes varies considerably across countries over long periods of time, as reflected in the two histograms below (Figure 1). For 78 countries in the period 1980-2014, the percentage decline in child mortality was 3.39% on average, with a standard deviation of 1.36%, a smallest rate of 0.89% (Central African Republic) and a highest rate of 8.07% (Maldives). The average percentage increase in school enrollment was 3.35%, with a standard deviation 3.54%, a minimum of 0.37% (Georgia) and a maximum of 19.68% (Maldives). Similar patterns of cross-country variation are found when using alternative proxies for health and education outcomes.