3-1-0 Three minutes to complete the online loan application, one second for approval and with zero human touch for SME loans. This is the marketing slogan used by Ant Financial, one of China’s largest online lenders with more than 400 million active users.
Digital finance is a cost-effective route to financial inclusion for many unbanked and underserved consumers in emerging markets. But digital finance is also still developing and maturing, with many open questions on the impact it will have. One of the most important of these is whether digital finance will ultimately help consumers to make better financial decisions over time.
October 31 is World Savings Day, a day which emphasizes the importance of savings to economic development, and provides a good occasion to look at how fintech may help solve the challenge of savings.
The program of events at the just concluded 2017 World Bank-IMF Annual Meetings was rich, and covered a range of topics instrumental to the World Bank Group’s work.
However, the event closest to my heart was on the role national development banks (NDBs) can play to close the staggering financing gap needed to reach the Sustainable Development Goals, nicknamed going “from billions to trillions” of dollars.
Since the SDGs were announced, the international development community has been looking at ways to tap into new funding venues, attract the private sector and build relevant private-public sector partnerships.
It is easy enough to find data on flows of foreign direct investment (FDI). There are also plenty of anecdotes out there that purportedly encapsulate what businesses worldwide are thinking. It is far more difficult, however, to establish rigorous connections between global investment trends and individual investment decisions by international companies. In the World Bank Group’s newly published Global Investment Competitiveness Report 2017–2018, our team does just this, combining new survey data, rigorous econometric analysis, and extensive literature reviews to reveal what is going on behind the headline numbers.
Here are some of the key takeaways:
But how confident are we that the available data on economic activity paints an accurate picture of a country’s performance?
Measuring Gross Domestic Product (GDP), the most standard measure of economic activity, is especially challenging in developing countries, where the informal sector is large and institutional constraints can be severe.
In addition, many countries only provide GDP measures annually and at the national level. Not surprisingly, GDP growth estimates are often met with skepticism.
New technologies offer an opportunity to strengthen economic measurement. Evening luminosity observed from satellites has been shown to be a good proxy for economic activity.
As shown in Figure 1, there is a strong correlation between nightlight intensity and GDP levels in South Asia: the higher the nightlight intensity on the horizontal axis, the stronger the economic activity on the vertical axis.
However, measuring nightlight is challenging and comes with a few caveats. Clouds, moonlight, and radiance from the sun can affect measurement accuracy, which then requires filtering and standardizing.
On the other hand, nighlight data has a lot advantages like being available in high-frequency and with a very high spatial resolution. In the latest edition of South Asia Economic Focus, we use variations in nightlight intensity to analyze economic trends and illustrate how this data can help predict GDP over time and across space.
About 17 years ago, I began preparations for applying to colleges in America. One of the prerequisites to qualify for an undergraduate program was the Test of English as a Foreign Language (TOEFL), administered at testing centers around the world. I vividly remember calling the number given to see how I faired in the test, standing at an international call center booth on a sunny afternoon in Islamabad, Pakistan, my heart beating fast with anticipation. The call cost Rs.100/minute at the time ($1.05/min at the current rate). But despite the expensive price tag, the service delivered information I desperately needed.
Fast forward to the age of Google Voice, WhatsApp, Viber… You’ll agree that technology has not only advanced but services have become cheaper as well. Technology is entrenched in our everyday tasks—from communication to financial transactions, from expanding education to building resilience to natural disasters, and from informing transport planning to expanding energy to the unserved.
So, ask yourself: am I—a student, teacher, business owner, or a local government representative—reaping the full benefits of the greatest information and communication revolution in human history? With more than 40% of the world’s population with access to the internet and new users coming online every day, how can I help turn digital technologies into a development game changer? And how can the world close the global digital divide to make sure technology leaves no one behind?
IDS 2018 presents statistics and analysis on the external debt and financial flows (debt and equity) of the world’s economies for 2016. It provides more than 200 time series indicators from 1970 to 2016 for most reporting countries. To access the report and related products you can:
- Download the full publication (PDF)
- Download or query the database
- Visit the IDS 2018 Products Page
- Access the statistical tables
- Visit the debt portal for a range of related content
- View the “about the data” section for a full description of the concepts and definitions in IDS.
This year’s edition is released less than 10 months after the 2016 reference period, making comprehensive debt statistics available faster than ever before. In addition to the data published in multiple formats online, IDS includes a concise analysis of the global debt landscape, which will be expanded on in a series of bulletins over the coming year.
Why monitor and analyze debt?
The core purpose of IDS is to measure the stocks and flows of debts in low- and middle-income countries that were borrowed from creditors outside the country. Broadly speaking, stocks of debt are the current liabilities that require payment of principal and/or interest to creditors outside the country. Flows of debt are new payments from, or repayments to, lenders.
These data are produced as part of the World Bank’s own work to monitor the creditworthiness of its clients and are widely used by others for analytical and operational purposes. Recurrent debt crises, including the global financial crisis of 2008, highlight the importance of measuring and monitoring external debt stocks and flows, and managing them sustainably. Here are three highlights from the analysis presented in IDS 2018:
Net financial inflows to low-and middle income countries grew, but IDA countries were left behind
In 2016, net financial flows into low- and middle-income countries grew to $773 billion - a more than three-fold increase over 2015 levels, but still lower than levels seen between 2012 and 2014.
However, this trend didn’t extend to the world’s poorest countries. Among the group of IDA-only countries, these flows fell 34% to $17.6 billion - their lowest level since 2011. This fall was driven by drops in inflows from bilateral and private creditors.
Small and medium enterprises (SMEs) are the backbone of the economy, being the main contributors to employment in developing and developed countries. Despite their importance, access to finance is relatively limited when comparing to large firms and is a major operating constraint for SMEs. The International Finance Corporation (IFC) estimates that to satisfy the demand by formal SMEs around the world credit had to increase between 900 and 1,100 billion U.S. dollars in 2011.
In a new policy brief (Abraham and Schmukler, 2017), we explore the obstacles to SME finance and some of the solutions that have been put in practice to try overcome them.
For many years, financial globalization has been promoted as a vehicle to raise living standards throughout the world, particularly in developing countries. However, a mounting body of empirical literature shows that in practice the effects of financial globalization have been overall mixed; financial globalization has only brought limited positive effects while it has also increased risks.
This post looks at the recently updated “Global Chinese Official Finance Dataset” from research group AidData. The post is also available here as an R Notebook which means you see the code behind the charts and analysis.
China has provided foreign assistance to countries around the world since the 1950s. Since it’s not part of the DAC group of donors who report their activities in a standard manner, there isn’t an official dataset which breaks down where Chinese foreign assistance goes, and what it’s used for.
A team of researchers at AidData, in the College of William and Mary have just updated their “Chinese Global Official Finance” dataset. This is an unofficial compilation of over 4,000 Chinese-financed projects in 138 countries, from 2000 to 2014, based on a triangulation of public data from government systems, public records and media reports. The team have coded these projects with over 50 variables which help to group and characterize them.
Activity-level data on an increasingly important donor
This dataset is interesting for two reasons. First, China and other emerging donors are making an impact on the development finance landscape. As the Bank has reported in the past (see International Debt Statistics 2016), bilateral creditors are a more important source of finance than they were just five years ago. And the majority of these increases are coming from emerging donors with China playing a prominent role.
Second, this dataset’s activity-level data gives us a look at trends and allocations in Chinese bilateral finance which can inform further analysis and research. Organizations like the World Bank collect data on financial flows directly from government sources for our operational purposes, but we’re unable to make these detailed data publicly available. We compile these data into aggregate financial flow statistics presented from the “debtor perspective”, but they’re not disaggregated by individual counterparties or at an activity-level. So there can be value added from sources such as AidData’s China dataset.
A detailed view, but only part of the picture of all financial flows
However, this dataset has limitations. It only presents estimates of “official bilateral credits”. These are flows between two governments, and are just one part of the total financial flows coming from China. By contrast, the World Bank is able to integrate the granular data it collects from countries into the full set of financial flows to and from its borrowing countries. This situates official bilateral credit among the broader spectrum of providers of long-term financing (such as bondholders, financial intermediaries, and other private sector entities), sources of short-term debt (including movements in bank deposits), and equity investments (foreign direct and portfolio investments). This data integration leads to better quality statistics.
In short, AidData’s China dataset provides more detail on one type of financial flow, but is likely to be less reliable for a number of low-income countries. With these caveats in mind, I’ve done a quick exploration of the dataset to produce some summary statistics and give you an idea of what’s inside.
Looking at foreign assistance by type of flow
First, let’s see what the trends in different types of foreign assistance look like. AidData researchers code the projects they’ve identified into three types of “flow”:
- Official Development Assistance (ODA), which contains a grant element of 25% or more and is primarily intended for development.
- Other Official Flows (OOF), where the grant element is under 25% and the the financing more commercial in nature.
- Vague Official Finance, where there isn’t enough information to assign it to either category.
Here are the total financial values of the projects in AidData’s dataset, grouped by flow type and year:
It looks like more Chinese finance is classed as OOF ($216bn in the period above) than ODA ($81bn), and that 2009 is a bit of an outlier. With this dataset, we next can figure out which countries are the top recipients of ODA and OOF, and also which sectors are most financed.
Now that the Nobel Committee has decided to award the prize once again for work in behavioral economics, it is a good time to study the role of disclosure formats for effective consumer protection.
We partnered with CONDUSEF, the financial consumer protection agency in Mexico, and the Superintendent of Banks in Peru to test which types of product disclosures work best for savings and credit products by low-income consumers in Peru and Mexico.
In a lab experiment, low-income consumers were assigned a financial needs profile—such as having to make two withdrawals per month from a savings accounts and two balance inquiries—and then incentivized to choose the product that best fit their needs. In each round of the experiment, we tested different methods for providing summary product information. In Mexico, we tested comparative tables; in Peru, we tested a key facts statement (KFS) designed by the financial institutions; and in both countries we tested.