Download the January 2019 Global Economic Prospects report.
Global growth sputtered in 2018 amid weakening trade and manufacturing, tighter financing conditions, and elevated policy uncertainties.
Growth decelerated in almost 80 percent of advanced economies and in nearly half of emerging market and developing economies in 2018. This year, it is expected to slow further in a majority of advanced economies and in about a third of emerging market and developing economies.
In all, global growth is predicted to moderate from 3.0 in 2018 to 2.9 percent in 2019 and an average of 2.8 percent in 2020-21, below previous forecasts.
Risks of even slower-than-expected growth have become more acute. Financial market pressures and trade tensions could escalate, denting confidence and further setting back growth prospects in emerging market and developing countries.
Here is a look at global economic prospects in five figures:
1. Global growth is moderating as trade and manufacturing lose momentum. The deceleration in global activity was more pronounced than previously expected in 2018, as reflected in softening export orders and industrial production growth. The slowdown in global trade came against the backdrop of ongoing trade tensions involving major economies. A. Global industrial production andnew export orders
A. Global industrial production and new export orders
Download the January 2019 Global Economic Prospects report.
Combinatorial innovation is driving innovation in satellite-based economic measurements at unprecedented resolution, frequency and scale. Increasing availability of satellite data and rapid advancements in machine learning methods are enabling a better understanding into the fundamental forces shaping economic development.
Why satellite data innovations matter
The desire of human beings to “think spatially” to understand how people and objects are organized in space has not changed much since Eratosthenes—the Greek astronomer best known as the “father of Geography”—first used the term “Geographika” around 250 BC. Centuries later, our understanding of economic geography is being propelled forward by new data and new capabilities to rapidly process, analyze and convert these vast data flows into meaningful and near real-time information.
We spoke with David Robalino, former Manager of the Jobs Group of the Social Protection and Jobs Global Practice. He discusses his report “Lending for Jobs Operations” that describes a general framework to inform the design of a new generation of World Bank lending operations. These operations have explicit objectives to either create jobs, improve the quality of existing jobs, or increase access to jobs for vulnerable populations.
He also describes tools that the Jobs Group has built to support jobs focused lending operations including the “Monitoring and Evaluation of Jobs Operations Guide,” and “Economic Analysis of Jobs Investment Projects.”
Follow the World Bank Jobs Group on Twitter @wbg_jobs.
Kofi Annan once said that ‘There is no tool more effective than the empowerment of women.’ This is definitely true in the agriculture sector: Male Outmigration and Women’s Work and Empowerment in Agriculture, which explores the impacts of rural outmigration on the lives and livelihoods of women who stay behind on the farms. The first in what will be a series of publications, this report uses innovative survey data to produce rigorous evidence on the gendered impacts of rural outmigration.
Why does it matter? The available evidence suggests that across the globe, migration originating from rural areas is predominantly male, which could potentially lead to significant socioeconomic changes in rural areas, including changes in traditional gender norms. Using data from two comparable, surveys for Nepal and Senegal collected between August and November 2017, we studied the effects of male outmigration from rural, primarily agricultural areas on women’s work and empowerment--both in agriculture and in the household.
Whether matching drivers with riders or landlords with lodgers, digital platforms like Uber and AirBnB push the marginal cost of matching supply and demand to an unprecedented low. Large infrastructure projects like China’s One Belt, One Road Initiative - which aims at more closely linking the two ends of Eurasia, as well as Africa and Oceania - could create an opportunity to alter the future of Central Asia’s agriculture, if food supply and demand can be matched more efficiently.
In our daily lives we are bombarded by offers to get more for less. And we respond accordingly as we strive to balance our household budgets. This saves us a few dollars here and there, perhaps hundreds of dollars on a big-ticket item, and we get to feel good about ourselves and our financial skills.
This is a question that is difficult to answer.
As practitioners we often focus our attention on operational efficiency. What were this year’s costs compared to last year’s? Is efficiency increasing or decreasing? There are suites of tools to give technical comfort to back up such assessments – from simple ratio analyses through to more sophisticated approaches such as econometric modeling and Data Envelope Analysis.
But what about capital efficiency? The assessment is not so simple as, in most cases, this is a prospective assessment – that is to say, a comparison of what was spent compared to a hypothetical of what might have been spent. It is rare to have a side by side comparison. Yet in the water sector, annualized capital costs can be equal to the annual operating costs. So, when we focus on operational efficiency, we are in fact only looking at half the story.
At the same time, we talk about mobilizing more finance to fill the gap between historic investment levels and projected investment needs. Yes, there will always be a financing gap in all countries around the world. However, whilst thinking about bridging that financing gap (“Maximizing Finance for Development” comes to mind), shouldn’t we also be thinking about how to reduce the financing gap by being more efficient in our use of capital?
Despite health-promotion and disease-prevention efforts, we are all at risk of catastrophic health events, which can strike at any moment, in the form of a traffic injury, a newly discovered tumor, a brain hemorrhage, or another sudden affliction affecting us or someone we love. When such events occur, we may abruptly face life-and-death situations that teach us first-hand the critical importance of timely access to medical care.
When I start discussing evaluations with government partners, and note the need for us to follow and survey over time a control group who did not get the program, one of the first questions I always get is “Won’t it be really hard to get them to respond?”. I often answer with reference to a couple of case examples from my own work, but now have a new answer courtesy of a new paper on testing for attrition bias in experiments by Dalia Ghanem, Sarojini Hirshleifer and Karen Ortiz-Becerra.
As part of the paper, they conduct a systematic review of field experiments with baseline data published in the top 5 economics journals plus the AEJ Applied, EJ, ReStat, and JDE over the years 2009 to 2015”, covering 84 journal articles. They note that attrition is a common problem, with 43% of these experiments having attrition rates over 15% and 68% having attrition rates over 5%. The paper then has discussion over what the appropriate tests should be to figure out whether this is a problem. But I wanted to highlight this panel from Figure 1 in their paper, which plots the absolute value of the difference in attrition rates by treatment and control. They note “64% have a differential rate that is less than 2 percentage points, and only 10% have a differential attrition rate that is greater than 5 percentage points.” That is, attrition rates aren’t much different for the control group.
It must be great to have access to so much information and data about so many things.
Yes, that's certainly a perk of the job, I responded, although it can be overwhelming at times.
What's more interesting, and exciting, at least to me (and, truth be told, overwhelming as well), is the access to so many fascinating questions.
(For what it's worth: Most of the information and data with which we are traditionally associated are actually 'open' these days, freely accessible to anyone with a web browser as a result of our access to information policy).
Here's a (lightly anonymized, slightly disguised) sample of questions that arrived in my in-box just today:
- For the first time in a few decades, our country is about to build lots of new schools: Should we be designing them any differently in order to accommodate the use of new technologies?
- What are some compelling examples of how 'edtech' has been 'scaled up' to promote greater equity and inclusiveness that are relevant to our country?
- We want to put all our textbooks online -- how should we do this?
- We need to hire an expert in governance issues in education systems who can help us better understand the opportunities and challenges that new technologies will pose for us in the future: Can you suggest some related terms of reference, and a shortlist of candidates who speak our language and are familiar with operating contexts in our country and region?
- What specs should we include in our big new tender for tablets?
(By the time I've completed this blog post, I expect a few more will have been sent to me as well.)
Whether these should be the types of things we get questions about -- that's another matter. There are no bad questions ... but of course some questions are better than others. Before we attempt to respond to a specific information request, we first pause and consider if we are being asked the 'right question'.
In steering people to the 'right question', or at least to a better question (or, as we like to phrase it when we respond, 'That's a great question! And here's another question that you may also wish to consider ...'), we have concluded that it usually helps to be able to address the one that they have already posed.
To help with this, we are trying to better organize what we know, based on our own work and more generally, to better address the things that we -- and the 100+ governments with which we actively work around the world -- don't know.
As part of this process, we have developed a master list of master list of 50+ key topics related to the use of new technologies in education of potential operational relevance to the World Bank in its strategic advice, lending activities and research going forward. It is not meant to be comprehensive in its consideration of topics related to the use of technology in education, and does not represent a 'framework for how to think about edtech'. Instead, it seeks to document and organize related requests for information and advice into distinct categories. It is not based on what the World Bank has done and supported in the past, but rather on questions we receive related to what governments are looking to do in the future. Reasonable people can and will no doubt disagree about whether we are being asked the 'right' questions or not. (We have strong opinions on this ourselves!)