Methods that use satellite data and machine learning present a good peek into how Big Data and new analytical methods will change how we measure poverty. I am not a poverty specialist, so I am wondering if these data and techniques can help in how we estimate job growth.
China has seen a booming tourism industry during the last few decades, thanks to a fast-developing economy and growing disposable personal income. , and 8.4% of the country’s total employment. Not surprisingly, cultural heritage sites were among the most popular tourist destinations.
But beyond the well-known Great Wall and Forbidden City, many cultural heritage sites are located in the poorer, inland cities and provinces of the country. If managed sustainably, —especially ethnic minorities, youth, and women—find jobs, grow incomes, and improve livelihoods.
“[Sustainable tourism] is not only the conservation of the cultural assets that are very important for the next generations to come, but, also, it’s the infrastructure upgrading, it’s the housing upgrading, and it is the social inclusion to really preserve the ethnic minorities’ culture and values – it is an interesting cultural package that is very valuable for countries around the world,” says Ede Ijjasz-Vasquez, a Senior Director of the World Bank.
To help reduce poverty and inequality in China’s lagging regions, —with the Bank’s largest program of this kind operating around 20 projects across the country. These projects have supported local economic development driven by cultural tourism.
“Over the years, the program has helped conserve over 40 cultural heritage sites, and over 30 historic urban neighborhoods, towns, and villages,” according to Judy Jia, a Beijing-based Urban Analyst.
Watch a video to learn from Ede Ijjasz-Vasquez (@Ede_WBG) and Judy Jia how cultural heritage and sustainable tourism can promote inclusive growth and boost shared prosperity in China, and what other countries can learn from this experience.
Also available in: 中文
I have just finished writing up and expanding my recent policy talk on active labor market policies (ALMPs) into a research paper (ungated version) which provides a critical overview of impact evaluations on this topic. While my talk focused more on summarizing a lot of my own work on this topic, for this review paper I looked a lot more into the growing number of randomized experiments evaluating these policies in developing countries. Much of this literature is very new: out of the 24 RCTs I summarize results from in several tables, 16 were published in 2015 or later, and only one before 2011.
I focus on three main types of ALMPs: vocational training programs, wage subsidies, and job search assistance services like screening and matching. I’ll summarize a few findings and implications for evaluations that might be of most interest to our blog readers – the paper then, of course, provides a lot more detail and discusses more some of the implications for policy and for other types of ALMPs.
Fatima brimmed with optimism. The 19-year-old recently established a poultry enterprise with the support of a micro-grant, and was thrilled at the prospect of financial independence.
“After my family moved from Pakistan, I had few options for work,” she said from her home in the Paghman district in the outskirts of Kabul. “The grant not only allowed me to start my own poultry business, but let me work from my own home.”
With over half the population under the age of 15, Afghanistan stands on the cusp of a demographic dividend. To reach their full potential, Afghanistan’s youth need to be engaged in meaningful work – enabling young people to support themselves, but also contribute to the prosperity of their families and communities.
When we think of agriculture and food, we think of a farmer working in a rural area producing food for consumption and selling some surplus. With growing urbanization and increasing demand for food, food system has moved away from just agricultural production. It involves aggregating, value addition, processing, logistics, food preparation, restaurants and other related services. Many enterprises from small to large are part of the enterprise ecosystem. The potential for new jobs for youth who start and are also employed by their enterprises is significant. The Africa Agriculture Innovation Network (AAIN) has developed a business agenda targeting establishment of at least 108 incubators in 54 African countries in the next 5 years focusing on youth and women among other actors. At least 600,000 jobs will be created and 100,000 start-ups and SMEs produced through incubation and 60,000 students exposed to learn as you earn model and mentored to start new businesses.
In recent past, there have been many innovations in areas of technology, extension, ICT, education, and incubation leading to new generation of enterprises and enterprise clusters resulting in the creation of good quality and new jobs in agriculture and food systems. A key challenge in the future is how we create more and better jobs in the agriculture and food system value chain. One of the major requirements for creating more jobs is a radical change in the way youth are taught agriculture and entrepreneurship. The skills required for a modern agriculture and food system are of a higher order and need to be upgraded significantly.
We are developing Macro Simulation Models to estimate how investments and interventions may generate jobs. Following the Jobs Study conducted by the International Finance Corporation (IFC), the World Bank Group’s private sector arm, the Let’s Work Partnership was established to develop, refine, and apply tools to estimate direct, indirect, and induced job effects. Macro models are one of these tools.
This year’s International Women’s Day “Women in the Changing World of Work: Planet 50-50 by 2030” places great emphasis on equality and economic empowerment. When countries give women greater opportunities to participate in the economy, the benefits extend far beyond individual girls and women but also to societies and economies as a whole. Addressing gender gaps in accessing good quality jobs is not just the right thing to do from a human rights perspective; it is also smart economics. A recent study shows that raising labor participation of women at par with men can increase GDP in the United States by 5 percent, in the UAE by 12 percent and in Egypt by 34 percent.
My colleague Victoria and I had an opportunity recently to meet with students at the Tajik-Russian Slavonic University in Dushanbe, Tajikistan, as part of our research and preparation for a new report called Tajikistan Jobs Diagnostic: Strategic Framework for Jobs.
Curious to learn about their future professional ambitions, we asked one class of students how many of them would like to work in the private sector after they graduate. Only about 10% of the students raised their hands. We also asked them how many would like to work for the government. This time, around 20% raised their hands.
In addition to correctly measuring the jobs directly generated from interventions and investments, development agencies also need to estimate the resulting indirect impacts and general equilibrium effects. These are hard to measure. My recent blog highlighted the progress that donors, international financial institutions, and other multilateral agencies are making in developing standardized tools to measure these impacts. In addition to standardization, the focus is now on strengthening existing measurement tools and addressing the challenges that are left.
Depending on to whom you listen, automation, robotics, and artificial intelligence (AI) will either solve all our problems or end the human race. Sometime in the near future, machine intelligence is predicted to surpass human intelligence, a point in time known as “the singularity.” Whether the rise of the machines is an existential threat to mankind or not, I believe that there is a more mundane issue: robots are currently being used to automate production.