Informal economies are a significant part of developing countries across the world and according to some estimates can represent around 60 percent of countries’ official GDP (Schneider, et al. 2010). IFC estimates suggest that some 80 percent of micro, small, and medium enterprises in emerging markets and developing countries are informal today. Access to finance is by far the biggest obstacle these firms face (Figure 1). This obstacle is more acute for firms that would like to register, and it becomes critical as firms grow in size (Figure 2). Considering that about two-thirds of full-time jobs in developing economies are provided by such firms, it is essential to better understand issues around access to finance for informal firms. A paper that I recently wrote on the subject (Farazi 2014) as part of the work on the 2014 Global Financial Development Report is an attempt in this direction.
Credit is actively used by only about 8 percent of people in developing countries and about 14 percent in developed countries (World Bank Findex). The observed gaps in financial inclusion thus suggest that greater access to credit is warranted.
However, finance can be a double-edged sword. Rapid financial development and deepening can cause accumulation of systemic risk and lead to costly financial crises (Reinhart and Rogoff 2009). Banking crises in Thailand (1997), Colombia (1982), and Ukraine (2008), for example, were preceded by excessive credit growth of 25 percent, 40 percent, and 70 percent per year, respectively. Providing the right amount of credit—not too much and not too little—is thus a major concern for countries and their policy makers.
When credit provision becomes excessive or insufficient is judged against an unobserved benchmark known as equilibrium credit. Estimating equilibrium credit is one of the most challenging tasks of determining excessive or insufficient credit provision.
- WDR 2014
Attend a seminar or read a report on Islamic finance and chances are you will come across a figure between $1 trillion and $1.6 trillion, referring to the estimated size of the global Islamic assets. While these aggregate global figures are frequently mentioned, publically available bank-level data have been much harder to come by.
Considering the rapid growth of Islamic finance, its growing popularity in both Muslim and non-Muslim countries, and its emerging role in global financial industry, especially after the recent global financial crisis, it is imperative to have up-to-date and reliable bank-level data on Islamic financial institutions from around the globe.
To date, there is a surprising lack of publically available, consistent and up-to-date data on the size of Islamic assets on a bank-by-bank basis. In fairness, some subscription-based datasets, such Bureau Van Dijk’s Bankscope, do include annual financial data on some of the world’s leading Islamic financial institutions. Bank-level data are also compiled by The Banker’s Top Islamic Financial Institutions Report and Ernst & Young’s World Islamic Banking Competitiveness Report, but these are not publically available and require subscription premiums, making it difficult for many researchers and experts to access. As a result, data on Islamic financial institutions are associated with some level of opaqueness, creating obstacles and challenges for empirical research on Islamic finance.
(Non-)rationality in economic decisions
As last year’s choice of the Nobel award for economic sciences well reflects, economists are deeply divided as to whether, and how, rationality should be modified as a basic assumption for modeling asset allocation and pricing decisions.
The three Nobel laureates for 2013 — Eugene Fama, Lars Peter Hansen, and Robert Shiller — epitomize the economics profession’s broad spectrum of positions currently existing on the subject: from Fama’s unflinching faith in the full rationality of economic action to Shiller’s recognition of the influence of non-rational and irrational factors upon human economic determinations, passing through Hansen’s acceptance of “distorted beliefs” as explanations of some otherwise inconsistent economic behaviors empirically observed.
The unresolved differences bear on the scientific status of contemporary macroeconomic analysis, especially since the crisis of 2007-09 has demonstrated the inadequacy of its underlying microfoundations. Particular attention has since been placed by economists on what they really know about asset bubbles, as these cannot be endogenized within purely rational choice models, and policymakers have re-considered whether bubbles can (or should) be managed in the public interest.
How does deposit insurance affect bank stability? This is a question that has been around for a while but has come up again after the global financial crisis. In response to the crisis, a number of countries substantially increased the coverage of their safety nets in order to restore market confidence and to avert potential contagious runs on their banking sectors. Critiques worry that such actions are likely to further undermine market discipline, causing more instability down the line. My earlier research on this issue suggests that on average deposit insurance can exacerbate moral hazard problems in bank lending, making systems more fragile. In other words, particularly in institutionally under-developed countries, banks have a tendency to exploit the availability of insured deposits and increase their risk, making the financial system more crises prone. This is ironic since deposit insurance is supposed to make the systems more stable, not less.
But what if the impact of deposit insurance on stability varies depending on the economic conditions? Does deposit insurance help stabilize banking systems by enhancing depositor confidence during turbulent times?
Worldwide, agriculture is the main source of income among the rural poor. Relative to other sectors, agricultural growth can reduce rural poverty rates faster and more effectively (Christiaensen and others 2011). As discussed in the GFDR 2014, one relevant vehicle to achieve growth in the sector may be finance.
Farmers’ decisions to invest and to produce are closely influenced by access to financial instruments. If appropriate risk mitigation products are lacking, or if available financial instruments do not match farmers’ needs, farmers may be discouraged to adopt better technologies, to purchase agricultural inputs, or to make other decisions that can improve the efficiency of their businesses. Improving access to finance can increase farmers’ investment choices and provide them with more effective tools to manage risks (Karlan and others 2012a, Cai and others 2009).
Microcredit has become a buzzword over the past couple of decades and many have hoped that small loans would help microenterprises grow and raise the incomes of their owners. Recently, a number of rigorous studies have measured the effect of credit on microenterprises. The results paint a nuanced picture; with most studies showing no strong impact on microenterprise growth (see Chapter 3 of the World Bank Group’s Global Financial Development Report 2014 for a summary of these findings).
Researches have uncovered several reasons why microcredit may not lead to the expected increase in firm growth. For example, to mitigate default risk, microloans often have joint liability. However, joint liability may discourage investment because group members have to pay more if a fellow borrower makes a risky investment that goes bad, but they do not enjoy a share of the profits if the investment yields returns. Also, looking beyond microcredit, recent studies suggest that providing other financial instruments, such as savings products and microinsurance, can spur microenterprise investment and growth.
Housing finance is a hot topic across the developed and developing world, though for different reasons. With some developed economies just coming out of a housing slump and others still in the middle of it (including my current host country, the Netherlands), often caused by easy and excessive access to mortgage credit before the crisis, households in many developing countries suffer rather from a dearth of long-term financing options. To illustrate this discrepancy, total mortgage debt outstanding in the Netherlands is equivalent to 83% of GDP, whereas it amounts to less than one percent of GDP across many low- and lower-middle-income countries in Asia and Africa. What explains these differences? Are underdeveloped housing finance systems just a symptom of the general shallowness of financial systems across developing countries? Or are there country factors and policies that specifically explain underdeveloped mortgage markets?
In a recent paper with Anton Badev, Ligia Vado and Simon Walley, we try to answer some of these questions with new data on mortgage depth and penetration. Specifically, drawing on a painstaking exercise of putting together country-level information on the depth of mortgage finance systems across countries and over time and using the recent data on the use of housing finance in the Global Findex database, we explore factors explaining the large cross-country variation in housing finance across the world
More than 50 countries have recently published explicit financial inclusion strategies and committed to formal targets for financial inclusion. These strategies and commitments reflect a growing recognition of the role of financial inclusion in reducing poverty and boosting shared prosperity. The Financial Inclusion Strategies Database—one of the supporting materials for the World Bank Group’s Global Financial Development Report 2014—summarizes the national strategies in a format that eases comparisons across countries, thus assisting research in this area. In this post, we present an introductory statistical analysis of the dataset.
While there is a consensus among researchers and policy makers that the 2008–2009 crisis was triggered by financial market disruptions in the United States, there is little agreement on whether the transmission of the crisis and the subsequent prolonged recession were caused by credit factors or a collapse of demand for goods and services. On the one hand, a credit crunch, defined as a reduction in the ability of firms to get loans or a sudden tightening of the conditions required to obtain a bank loan, squeezes firms’ working capital and hurts their production. On the other hand, adverse demand shocks to firms come from declines in demand for firms’ products and services. Each type of factor has fundamentally different policy implications. If credit factors are found to play the main role, the solution would be to provide more and cheaper credit. But if demand factors are the main drivers, the focus should be on boosting investors’ and consumers’ confidence. Interestingly, most of the effort to understand the impact of the crisis focuses on credit and not on demand.