The world's greatest risks can't be confined within borders. This is clearly the case with the ongoing refugee crisis, which is unprecedented in scale and affecting people and places far from the scene of civil war, fragility and conflict. The UK vote to leave the European Union showed, in part, the volatility and reach of the impact of forced displacement.
Since more than 50% of small and medium-sized businesses (SMEs) worldwide lack adequate access to credit, the international community is proposing reforms that will help countries strengthen their financial infrastructure and make it easier for SMEs to borrow funds needed to operate and expand.
The United Nations General Assembly recently adopted the Sustainable Development Goals (SDGs) in New York in the midst of great expectation and hype. The 17 SDGs, with 169 specific targets, are now becoming the road map for governments and the international development community for the next 15 years.
Now that all the publicity and excitement are starting to settle down, it seems opportune to look at the media coverage of the SDGs and developing countries to get a sense of how that coverage has played out over the past few weeks, and what some of the insights are that we can learn from for the way forward. This coverage mainly includes articles from various publications, websites, and blog posts in the English language. It does not include social media statistics from Tweeter or Facebook.
An analysis of this media coverage featuring the key words “SDGs” and “developing countries” show that, over the past three months, more than 2,400 articles mentioned these two key words somewhere in the text of the articles. The analysis, using the Newsplus database, covers the period July 8-October 8. It shows that almost a quarter of that coverage (more than 600 entries) took place during the last week of September when the UN meetings were held. However, the second week of July, right before the summer break, was also active in terms of SDG-related coverage, signaling an important communications effort in the lead up to the UN September meetings.
Later this year the Financing for Development summit will take place in Addis Ababa. The discussion will focus on the post-2015 agenda and the implementation of the Sustainable Development Goals (SDGs), which will need a massive amount of financing.
What is the main difference between high-income and developing countries?
Here is my take: People in the former have much more of pretty much everything. Almost everyone living in high-income countries has access to electricity; in poor (low-income) countries, 7 out of 10 people don’t. Most families in rich countries own a car, but only a few people living in the developing world do. On per capita basis, rich economies have 15 times more doctors than poor countries, consume 40 times more energy, have 50 times more ATMs, and so on.
Luck has struck the region of East Africa: for a couple of years now, new announcements of natural resource discoveries are being made every few months. Mozambique has found some of the largest natural gas deposits in the world, while Tanzania, Uganda, and Kenya have also discovered gas and oil. Exploration is still ongoing, so even more discoveries could be forthcoming. Luck has definitely struck the region, but the main question is: how will the people in these countries benefit from this?
Paul Collier and Justin Sandefur are discussing migration with recent postings on the popular From Poverty to Power blog hosted by Duncan Green of OXFAM. But, can we please first agree on the question?
Collier’s blog-post starts with the question of how emigration affects people in countries of origin, and goes on to emphasize that the pertinent issue is “whether poor countries would be better off with somewhat faster, or somewhat slower emigration than they have currently.” His answer, in a nutshell, is that it depends: on the country of origin (“in small countries that are falling further behind … brain drain predominates” when there is further skilled migration) and the emigrant (students – good, unskilled – fine, skilled worker – may already be excessive). To this, one could also add that it depends on the host country (and the scope for migrants realizing their potential there) and the circumstances of the migration (voluntary or forced).
In an earlier post, we highlighted a feature of the global pattern of investment in recent times: that since 2000, developing countries have gradually increased their share of global investment, moving from around 20 percent through much of the second half of the last century, to around 46 percent by 2010. The rapidity of this rise notwithstanding, the natural question is whether this trend will continue into the future.
Answering this question---on changing patterns of global investment---is one of the main concerns of the most recent edition of the Global Development Horizons report, entitled Capital for the Future. In order to frame the question, the report considers how different countries will distinguish themselves in the global economy and, consequently, how by doing so they will provide investment opportunities that would attract financing from the pool of global saving.
My previous blog ended with a question about the usefulness of anticipating the long-term future if that future is highly uncertain. Ever since the 1982 article on “Trends and random walks in macroeconomic time series” by Nelson and Plosser, there has been a debate about the long-term statistical properties of GDP and other macroeconomic variables. Nelson and Plosser could not reject the hypothesis of a random walk (with drift), which means that random shocks have a permanent impact on the level of GDP and that the uncertainty interval around forecasts becomes wider and wider with every year you try to peek farther into the future. The message seems to be: If next year’s world is already very uncertain, don’t even bother forecasting the world in 2030.
Others found that “macroeconomic time series are best construed as stationary fluctuations around a deterministic trend function”, if you allow for a few structural breaks in the trend. The consequences for long-term forecasting are huge because, in this case, random shocks are transitory, there is mean reversion, and it is in fact easier to analyze long-term trends than short-term fluctuations.