The Atlanta Fed's macroblog provides commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues.
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May 11, 2017
Are Small Loans Hard to Find? Evidence from the Federal Reserve Banks' Small Business Survey
The Federal Reserve Banks recently released results from the nationwide 2016 Small Business Survey, which asks firms with 500 or fewer employees about business and financing conditions. One key finding is just how small the financing needs of many businesses are. One-fifth of small businesses that applied for financing in the prior 12 months were seeking $25,000 or less. A further 35 percent were seeking between $25,001 and $100,000.
The data also show that firms seeking relatively small amounts of financing (up to $100,000) receive a significantly smaller fraction of their funding than firms who applied for more than $250,000. Chart 1 shows the weighted average of the share of financing received by the amount the firm was seeking.
So what explains this variation in financing attainment across the amount requested? We've heard reports from small business owners that smaller loans are relatively more difficult to obtain, especially from traditional banks. One often-cited rationale is that the administrative burden associated with originating and managing a small loan is often just not worth the bank's time. However, this notion is not entirely consistent with data on the current holdings of small business loans on the balance sheets of banks. As of June 2015, loans of less than $100,000 made up about 92 percent of the number of business loans under $1 million.
So it seems originating a loan for less than $100,000 is not uncommon for a bank after all. So why, then, do business owners say that smaller loans are more difficult to get? Using data from the 2016 Small Business Survey, we can investigate the reason for this apparent disconnect.
Much can be explained by looking at the characteristics of those who borrow small amounts versus large amounts. Firms seeking $25,000 or less are more likely to be high credit risk and younger, have fewer employees, and have smaller revenues than firms applying for more than $250,000. The table below summarizes the differences:
Of particular importance is the credit risk associated with the firm. Controlling for differences in this factor, it turns out that smaller amounts of financing are not more difficult to obtain. Charts 2 and 3 show the weighted average share of financing received by amount sought for low credit risk firms and for middle to high credit risk firms separately.
As charts 2 and 3 demonstrate, low credit risk firms are able to obtain a similar share of the amount requested, regardless of how much they applied for. The same is true for higher risk firms. We also see that medium and high risk firms get less of their financing needs met than low credit risk firms that apply for similar amounts.
From this evidence, it seems that credit approval has more to do with the attributes of the firm than the amount of financing for which the firm applied. These results also highlight the potential importance of alternatives to traditional bank financing so that riskier entrepreneurs—including important contributors to the dynamism of the economy such as startups—have somewhere to turn. A later macroblog post will explore how low and high credit risk firms use financing differently, including where they apply and where they receive funding.
September 08, 2016
Introducing the Atlanta Fed's Taylor Rule Utility
Simplicity isn't always a virtue, but when it comes to complex decision-making processes—for example, a central bank setting a policy rate—having simple benchmarks is often helpful. As students and observers of monetary policy well know, the common currency in the central banking world is the so-called "Taylor rule."
The Taylor rule is an equation introduced by John Taylor in a seminal 1993 paper that prescribes a value for the federal funds rate—the interest rate targeted by the Federal Open Market Committee (FOMC)—based on readings of inflation and the output gap. The output gap measures the percentage point difference between real gross domestic product (GDP) and an estimate of its trend or potential.
Since 1993, academics and policymakers have introduced and used many alternative versions of the rule. The alternative forms of the rule can supply policy prescriptions that differ significantly from Taylor's original rule, as the following chart illustrates.
The green line shows the policy prescription from a rule identical to the one in Taylor's paper, apart from some minor changes in the inflation and output gap measures. The red line uses an alternative and commonly used rule that gives the output gap twice the weight used for the Taylor (1993) rule, derived from a 1999 paper by John Taylor. The red line also replaces the 2 percent value used in Taylor's 1993 paper with an estimate of the natural real interest rate, called r*, from a paper by Thomas Laubach, the Federal Reserve Board's director of monetary affairs, and John Williams, president of the San Francisco Fed. Federal Reserve Chair Janet Yellen also considered this alternative estimate of r* in a 2015 speech.
Both rules use real-time data. The Taylor (1993) rule prescribed liftoff for the federal funds rate materially above the FOMC's 0 to 0.25 percent target range from December 2008 to December 2015 as early as 2012. The alternative rule did not prescribe a positive fed funds rate since the end of the 2007–09 recession until this quarter. The third-quarter prescriptions incorporate nowcasts constructed as described here. Neither the nowcasts nor the Taylor rule prescriptions themselves necessarily reflect the outlook or views of the Federal Reserve Bank of Atlanta or its president.
Additional variables that get plugged into this simple policy rule can influence the rate prescription. To help you sort through the most common variations, we at the Atlanta Fed have created a Taylor Rule Utility. Our Taylor Rule Utility gives you a number of choices for the inflation measure, inflation target, the natural real interest rate, and the resource gap. Besides the Congressional Budget Office–based output gap, alternative resource gap choices include those based on a U-6 labor underutilization gap and the ZPOP ratio. The latter ratio, which Atlanta Fed President Dennis Lockhart mentioned in a November 2015 speech while addressing the Taylor rule, gauges underemployment by measuring the share of the civilian population working their desired number of hours.
Many of the indicator choices use real-time data. The utility also allows you to establish your own weight for the resource gap and whether you want the prescription to put any weight on the previous quarter's federal funds rate. The default choices of the Taylor Rule Utility coincide with the Taylor (1993) rule shown in the above chart. Other organizations have their own versions of the Taylor Rule Utility (one of the nicer ones is available on the Cleveland Fed's Simple Monetary Policy Rules web page). You can find more information about the Cleveland Fed's web page on the Frequently Asked Questions page.
Although the Taylor rule and its alternative versions are only simple benchmarks, they can be useful tools for evaluating the importance of particular indicators. For example, we see that the difference in the prescriptions of the two rules plotted above has narrowed in recent years as slack has diminished. Even if the output gap were completely closed, however, the current prescriptions of the rules would differ by nearly 2 percentage points because of the use of different measures of r*. We hope you find the Taylor Rule Utility a useful tool to provide insight into issues like these. We plan on adding further enhancements to the utility in the near future and welcome any comments or suggestions for improvements.
August 11, 2016
Forecasting Loan Losses for Stress Tests
Bank capital requirements are back in the news with the recent announcements of the results of U.S. stress tests by the Federal Reserve and the European Union (E.U.) stress tests by the European Banking Authority (EBA). The Federal Reserve found that all 33 of the bank holding companies participating in its test would have continued to meet the applicable capital requirements. The EBA found progress among the 51 banks in its test, but it did not define a pass/fail threshold. In summarizing the results, EBA Chairman Andrea Enria is widely quoted as saying, "Whilst we recognise the extensive capital raising done so far, this is not a clean bill of health," and that there remains work to do.
The results of the stress tests do not mean that banks could survive any possible future macroeconomic shock. That standard would be an extraordinarily high one and would require each bank to hold capital equal to its total assets (or maybe even more if the bank held derivatives). However, the U.S. approach to scenario design is intended to make sure that the "severely adverse" scenario is indeed a very bad recession.
The Federal Reserve's Policy Statement on the Scenario Design Framework for Stress Testing indicates that the severely adverse scenario will have an unemployment increase of between 3 and 5 percentage points or a level of 10 percent overall. That statement observes that during the last half century, the United States has seen four severe recessions with that large of an increase in the unemployment rate, with the rate peaking at more than 10 percent in last three severe recessions.
To forecast the losses from such a severe recession, the banks need to estimate loss models for each of their portfolios. In these models, the bank estimates the expected loss associated with a portfolio of loans as a function of the variables in the scenario. In estimating these models, banks often have a very large number of loans with which to estimate losses in their various portfolios, especially the consumer and small business portfolios. However, they have very few opportunities to observe how the loans perform in a downturn. Indeed, in almost all cases, banks started keeping detailed loan loss data only in the late 1990s and, in many cases, later than that. Thus, for many types of loans, banks might have at best data for only the relatively mild recession of 2001–02 and the severe recession of 2007–09.
Perhaps the small number of recessions—especially severe recessions—would not be a big problem if recessions differed only in their depth and not their breadth. However, even comparably severe recessions are likely to hit different parts of the economy with varying degrees of severity. As a result, a given loan portfolio may suffer only small losses in one recession but take very large losses in the next recession.
With the potential for models to underestimate losses given there are so few downturns to calibrate to, the stress testing process allows humans to make judgmental changes (or overlays) to model estimates when the model estimates seem implausible. However, the Federal Reserve requires that bank holding companies should have a "transparent, repeatable, well-supported process" for the use of such overlays.
My colleague Mark Jensen recently made some suggestions about how stress test modelers could reduce the uncertainty around projected losses because of limited data from directly comparable scenarios. He recommends using estimation procedures based on a probability theorem attributed to Reverend Thomas Bayes. When applied to stress testing, Bayes' theorem describes how to incorporate additional empirical information into an initial understanding of how losses are distributed in order to update and refine loss predictions.
One of the benefits of using techniques based on this theorem is that it allows the incorporation of any relevant data into the forecasted losses. He gives the example of using foreign data to help model the distribution of losses U.S. banks would incur if U.S. interest rates become negative. We have no experience with negative interest rates, but Sweden has recently been accumulating experience that could help in predicting such losses in the United States. Jensen argues that Bayesian techniques allow banks and bank supervisors to better account for the uncertainty around their loss forecasts in extreme scenarios.
Additionally, I have previously argued that the existing capital standards provide further way of mitigating the weaknesses in the stress tests. The large banks that participate in the stress tests are also in the process of becoming subject to a risk-based capital requirement commonly called Basel III that was approved by an international committee of banking supervisors after the financial crisis. Basel III uses a different methodology to estimate losses in a severe event, one where the historical losses in a loan portfolio provide the parameters to a loss distribution. While Basel III faces the same problem of limited loan loss data—so it almost surely underestimates some risks—those errors are likely to be somewhat different from those produced by the stress tests. Hence, the use of both measures is likely to somewhat reduce the possibility that supervisors end up requiring too little capital for some types of loans.
Both the stress tests and risk-based models of the Basel III type face the unavoidable problem of inaccurately measuring risk because we have limited data from extreme events. The use of improved estimation techniques and multiple ways of measuring risk may help mitigate this problem. But the only way to solve the problem of limited data is to have a greater number of extreme stress events. Given that alternative, I am happy to live with imperfect measures of bank risk.
Author's note: I want to thank the Atlanta Fed's Dave Altig and Mark Jensen for helpful comments.
June 06, 2016
After the Conference, Another Look at Liquidity
When it comes to assessing the impact of central bank asset purchase programs (often called quantitative easing or QE), economists tend to focus their attention on the potential effects on the real economy and inflation. After all, the Federal Reserve's dual mandate for monetary policy is price stability and full employment. But there is another aspect of QE that may also be quite important in assessing its usefulness as a policy tool: the potential effect of asset purchases on financial markets through the collateral channel.
Asset purchase programs involve central bank purchases of large quantities of high-quality, highly liquid assets. Postcrisis, the Fed has purchased more than $3 trillion of U.S. Treasury securities and agency mortgage-backed securities, the European Central Bank (ECB) has purchased roughly 727 billion euros' worth of public-sector bonds (issued by central governments and agencies), and the Bank of Japan is maintaining an annual purchase target of 80 trillion yen. These bonds are not merely assets held by investors to realize a return; they are also securities highly valued for their use as collateral in financial transactions. The Atlanta Fed's 21st annual Financial Markets Conference explored the potential consequences of these asset purchase programs in the context of financial market liquidity.
The collateral channel effect focuses on the role that these low-risk securities play in the plumbing of U.S. financial markets. Financial firms fund a large fraction of their securities holdings in the repurchase (or repo) markets. Repurchase agreements are legally structured as the sale of a security with a promise to repurchase the security at a fixed price at a given point in the future. The economics of this transaction are essentially similar to those of a collateralized loan.
The sold and repurchased securities are often termed "pledged collateral." In these transactions, which are typically overnight, the lender will ordinarily lend cash equal to only a fraction of the securities value, with the remaining unfunded part called the "haircut." The size of the haircut is inversely related to the safety and liquidity of the security, with Treasury securities requiring the smallest haircuts. When the securities are repurchased the following day, the borrower will pay back the initial cash plus an additional amount known as the repo rate. The repo rate is essentially an overnight interest rate paid on a collateralized loan.
Central bank purchases of Treasury securities may have a multiplicative effect on the potential efficiency of the repo market because these securities are often used in a chain of transactions before reaching a final holder for the evening. Here's a great diagram presented by Phil Prince of Pine River Capital Management illustrating the role that bonds and U.S. Treasuries play in facilitating a variety of transactions. In this example, the UST (U.S. Treasury) securities are first used as collateral in an exchange between the UST securities lender and the globally systemically important financial institution (GSIFI bank/broker dealer), then between the GSIFI bank and the cash provider, a money market mutual fund (MMMF), corporation, or sovereign wealth fund (SWF). The reuse of the UST collateral reduces the funding cost of the GSIFI bank and, hence, the cost to the levered investor/hedge fund who is trying to exploit discrepancies in the pricing of a corporate bond and stock.
Just how important or large is this pool of reusable collateral? Manmohan Singh of the International Monetary Fund presented the following charts, depicting the pledged collateral at major U.S. and European financial institutions that can be reused in other transactions.
So how do central bank purchases of high-quality, liquid assets affect the repo market—and why should macroeconomists care? In his presentation, Marvin Goodfriend of Carnegie Mellon University concluded that central bank asset purchases, which he terms "pure monetary policy," lower short-term interest rates (especially bank-to-bank lending) but increase the cost of funding illiquid assets through the repo market. And Singh noted that repo rates are an important part of the constellation of short-term interest rates and directly link overnight markets with the longer-term collateral being pledged. Thus, the interaction between a central bank's interest-rate policy and its balance sheet policy is an important aspect of the transmission of monetary policy to longer-term interest rates and real economic activity.
Ulrich Bindseil, director of general market operations at the ECB, discussed a variety of ways in which central bank actions may affect, or be affected by, bond market liquidity. One way that central banks may mitigate any adverse impact on market liquidity is through their securities lending programs, according to Bindseil. Central banks use such programs to lend particular bonds back out to the market to "provide a secondary and temporary source of securities to the financing market...to promote smooth clearing of Treasury and Agency securities."
On June 2, for example, the New York Fed lent $17.8 billion of UST securities from the Fed's portfolio. These operations are structured as collateral swaps—dealers pledge other U.S. Treasury bonds as collateral with the Fed. During the financial crisis, the Federal Reserve used an expanded version of its securities lending program called the Term Securities Lending Facility to allow firms to replace lower-quality collateral that was difficult to use in repo transactions with Treasury securities.
Finally, the Fed currently releases some bonds to the market each day in return for cash, through its overnight reverse repo operations, a supplementary facility used to support control of the federal funds rate as the Federal Open Market Committee proceeds with normalization. However, this release has an important limitation: these operations are conducted in the triparty repo market, and the bonds released through these operations can be reused only within that market. In contrast, if the Fed were to sell its U.S. Treasuries, the securities could not only be used in the triparty repo market but also as collateral in other transactions including ones in the bilateral repo market (you can read more on these markets here). As long as central bank portfolios remain large and continue to grow as in Europe and Japan, policymakers are integrally linked to the financial plumbing at its most basic level.
To see a video of the full discussion of these issues as well as other conference presentations on bond market liquidity, market infrastructure, and the management of liquidity within financial institutions, please visit Getting a Grip on Liquidity: Markets, Institutions, and Central Banks. My colleague Larry Wall's conference takeaways on the elusive definition of liquidity, along with the impact of innovation and regulation on liquidity, are here.
April 13, 2016
Putting the MetLife Decision into an Economic Context
In a recently released decision, a U.S. district court has ruled that the Financial Stability Oversight Council's (FSOC's) decision to designate MetLife as a potential threat to financial stability was "arbitrary and capricious" and rescinded that designation. This decision raises many questions, among them:
- Why did MetLife sue to end its status as a too-big-to-fail (TBTF) firm?
- How will this decision affect the Federal Reserve's regulation of nonbank financial firms?
- What else can be done to reduce the risk of crisis arising from nonbank financial firms?
Why does MetLife want to end its TBTF status?
An often-expressed concern is that market participants will consider FSOC-designated firms too big to fail, and investors will accord these firms lower risk premiums (see, for example, Peter J. Wallison). The result is that FSOC-designated firms will gain a competitive advantage. If so, why did MetLife sue to have the designation rescinded? And why did the announcement of the court's determination result in an immediate 5 percent increase in the MetLife's stock price?
One possible explanation is that the FSOC's designation guarantees the firm will be subject to higher regulatory costs, but it only marginally changes the likelihood it would receive a government bailout. The Dodd-Frank Act (DFA) requires that FSOC-designated firms be subject to consolidated prudential supervision by the Federal Reserve using standards that are more stringent than the requirements for other nonbank financial firms.
Moreover, the argument that such designation automatically conveys a competitive advantage has at least two weaknesses. First, although Title II of the DFA authorizes the Federal Deposit Insurance Corporation (FDIC) to resolve a failing nonbank firm in certain circumstances, DFA does not provide FDIC insurance for any of the nonbank firm's liabilities, nor does it provide the FDIC with funds to undertake a bailout. The FDIC is supposed to recover its costs from the failed firm's assets. Admittedly, DFA does allow for the possibility that the FDIC would need to assess other designated firms for part of the cost of a resolution. However, MetLife could as easily have been assessed to pay for another firm as it could have been the beneficiary of assessments on other systemically important firms.
A second potential weakness in the competitive advantage argument is that the U.S. Treasury Secretary decides to invoke FDIC resolution only after receiving a recommendation from the Federal Reserve Board and one other federal financial regulatory agency (depending upon the type of failing firm). Invocation of resolution is not automatic. Moreover, a part of any decision authorizing FDIC resolution are findings that at the time of authorization:
- the firm is in default or in danger of default,
- resolution under other applicable law (bankruptcy statutes) would have "serious adverse consequences" on financial stability, and
- those adverse effects could be avoided or mitigated by FDIC resolution.
Although it would seem logical that FSOC-designated firms are more likely to satisfy these criteria than other financial firms, the Title II criteria for FDIC resolution are the same for both types of firms.
How does this affect the Fed's regulation of nonbank firms?
Secretary of the Treasury Jack Lew has indicated his strong disagreement with the district court's decision, and the U.S. Treasury has said it will appeal. Suppose, however, that FSOC designation ultimately does become far more difficult. How significantly would that affect the Federal Reserve's regulatory power over nonbank financial firms?
Although the obvious answer would be that it would greatly reduce the Fed's regulatory power, recent experience casts some doubt on this view. Nonbank financial firms appear to regard FSOC designation as imposing costly burdens that substantially exceed any benefits they receive. Indeed, GE Capital viewed the costs as so significant that it had been selling large parts of its operations and recently petitioned the FSOC to rescind its designation. Unless systemically important activities are a core part of the firm's business model, nonbank financial firms may decide to avoid undertaking activities that would risk FSOC designation.
Thus, a plausible set of future scenarios is that the Federal Reserve would be supervising few, if any, nonbank financial firms regardless of the result of the MetLife case. Rather, ultimate resolution of the case may have more of an impact on whether large nonbank financial firms conduct systemically important activities (if designation becomes much harder) or the activities are conducted by some combination of smaller nonbank financial firms and by banks that are already subject to Fed regulation (if the ruling does not prevent future designations).
Regardless of how the courts and the FSOC respond to this recent judicial decision, the financial crisis should have taught us valuable lessons about the importance of the nonbank financial sector to financial stability. However, those lessons should go beyond merely the need to impose prudential supervision on any firms that are systemically important.
The cause of the financial crisis was not the failure of one or two large nonbank financial firms. Rather, the cause was that almost the entire financial system stood on the brink of collapse because almost all the major participants were heavily exposed to the weak credit standards that were pervasive in the residential real estate business. Yet if the real problem was the risk of multiple failures as a result of correlated exposures to a single large market, perhaps we ought to invest more effort in evaluating the riskiness of markets that could have systemic consequences.
In an article in Notes from the Vault and other forums, I have called for systematic end-to-end reviews of major financial markets starting with the origination of the risks and ending with the ultimate holder(s) of the risks. This analysis would involve both quantitative analysis of risk measures and qualitative analysis of the safeguards designed to reduce risk.
The primary goal would be to identify and try to correct weaknesses in the markets. A secondary goal would be to give the authorities a better sense of where problems are likely to arise if a market does encounter problems.
April 11, 2016
The Rise of Shadow Banking in China
China's banking system has suffered significant losses over the past two years, which has raised concerns about the health of China's financial industry. Such losses are perhaps not all that surprising. Commercial banks have been increasing their risk-taking activities in the form of shadow lending. See, for example, here, here, and here for some discussion of the evolution of China's shadow banking system.
The increase in risk taking by banks has occurred despite a rapid decline in money growth since 2009 and the People's Bank of China's efforts to limit credit expansions to real estate and other industries that appear to be over capacity.
One area of expanded activity has been investment in asset-backed "securities" by China's large non-state banks. This investment has created potentially significant risks to the balance sheets of these institutions (see the charts below). Using the micro-transaction-based data on shadow entrusted loans, Chen, Ren, and Zha (2016) have provided theoretical and empirical insights into this important issue (see also this Vox article that summarizes the paper).
Recent regulatory reforms in China have taken a positive step to try to limit such risk-taking behavior, although the success of these efforts remains to be seen. An even more challenging task lies ahead for designing a comprehensive and sustainable macroprudential framework to support the healthy functioning of China's traditional and shadow banking industries.
March 15, 2016
Collateral Requirements and Nonbank Online Lenders: Evidence from the 2015 Small Business Credit Survey
Businesses can secure a bank loan by offering collateral—typically a business asset such as equipment or real estate. However, the recently released 2015 Small Business Credit Survey (SBCS) Report on Employer Firms,conducted by seven regional Reserve Banks, found that 63 percent of business owners who had borrowed also used their personal assets or guarantee to secure financing. Surprisingly, the use of personal collateral was common not only among startups. Older and relatively larger small firms (see the following chart) also relied heavily on personal assets.
Source: 2015 Small Business Credit Survey
Note: "Unsure", "None", and "Other" were also options but are not shown on the chart.
Alternative lending options also exercised
Not every small business owner has sufficient hard assets, such as real estate or equipment, that can be used as collateral to secure a traditional bank loan or line of credit. For these circumstances, there are options such as credit cards and products offered by nonbank lenders (mostly operating online) that have less stringent underwriting requirements than banks. Many online nonbank lenders advertise unsecured loans or require only a general lien on business assets, without valuing those business assets.
In the 2015 SBCS, 20 percent of small firms seeking loans or lines of credit applied at nonbank online lenders. These lenders have a good reputation for quick application turnaround, and the collateral requirements can be looser than those applied by traditional lenders. But when borrowers were asked about their overall experience, only a net 15 percent of businesses approved at nonbank online lenders were satisfied (40.6 percent were satisfied and 25.3 percent were dissatisfied). In contrast, small banks received a relatively high net satisfaction score of 75 percent (see the chart).
Source: 2015 Small Business Credit Survey Report on Employer Firms
1 Satisfaction score is the share satisfied with lender minus the share dissatisfied.
2 "Online lenders" are defined as alternative and marketplace lenders, including Lending Club, OnDeck, CAN Capital, and PayPal Working Capital.
3 "Other" includes government loan funds and community development financial institutions.
The survey also showed that high interest rates were the primary reason for dissatisfaction at nonbank online lenders (see the chart).
Source: 2015 Small Business Credit Survey Report on Employer Firms
Note: Respondents could select multiple options. Select responses shown due to low observation count.
Merchant cash advances make advances
Most applicants to nonbank online lenders were seeking loans and lines of credit, but some were seeking a product that tends to be particularly expensive relative to other finance options: merchant cash advances (MCA). MCAs have been around for decades, but their popularity has risen in the wake of the financial crisis. Typically a lump-sum payment in exchange for a portion of future credit card sales, the terms of MCAs can be enticing because repayment seems easier than paying off a structured business loan that requires a fixed monthly payment. Instead, the lender is paid back as the business generates revenue, in theory making cash flow easier to manage.
One potential challenge for users of MCA products is interpreting the repayment terms. Instead of displaying an annual percentage rate (APR), MCAs are usually advertised with a "buy rate" (typically 1.2 to 1.4). For example, a buy rate of 1.3 on $100,000 would require the borrower to pay back $130,000. However, a percentage of the principal is not the same as an APR. The table below compares total interest payments made on a 1.3 MCA versus a 30 percent APR business loan repaid over 12 months and over six months. With a 12-month business loan, a 30 percent APR would equal total interest payments of roughly $17,000. With a six-month business loan, repayment would include about $9,000 in interest.
Because an MCA is structured as a commercial transaction instead of a loan, it is regulated by the Uniform Commercial Code in each state instead of by banking laws such as the Truth in Lending Act. Consequently, the provider does not have to follow all of the regulations and documentation requirements (such as displaying an APR) associated with making loans.
Converting a buy rate into an APR is not straightforward for many potential users, as was made clear in a recent online lending focus group study with small business owners conducted by the Cleveland Fed. When asked what the APR was on a $40,000 MCA that required a repayment of $52,000 (the same as a 1.3 buy rate), their answers were the following: (Product A is the MCA type of product; see the study for exactly how it was presented to respondents.)
Source: Federal Reserve Bank of Cleveland
The correct answer is that "it depends on how long it takes to pay back." For example, if the debt is repaid over six months, the APR would be 110 percent (as this calculator shows).
Nonbank online lenders can fill gaps in the borrowing needs of small business. But there may also be a role for greater clarity to ensure borrowers understand the terms they are signing up for. In a September 2015 speech, Federal Reserve Governor Lael Brainard highlights one self-policing movement already well under way:
Some have raised concerns about the high APRs associated with some online alternative lending products. Others have raised concerns about the risk that some small business borrowers may have difficulty fully understanding the terms of the various loan products or the risk of becoming trapped in layered debt that poses risks to the survival of their businesses. Some industry participants have recently proposed that online lenders follow a voluntary set of guidelines designed to standardize best practices and mitigate these risks. It is too soon to determine whether such efforts of industry participants to self-police will be sufficient. Even with these efforts, some have suggested a need for regulators to take a more active role in defining and enforcing standards that apply more broadly in this sector.
Many, but not all, nonbank online lenders have already signed the Small Business Borrower Bill of Rights. Results from the 2015 Small Business Credit Survey Report on Employer Firms can be found on our website.
May 13, 2014
Today’s news brings another indication that low inflation rates in the euro area have the attention of the European Central Bank. From the Wall Street Journal (Update: via MarketWatch):
Germany's central bank is willing to back an array of stimulus measures from the European Central Bank next month, including a negative rate on bank deposits and purchases of packaged bank loans if needed to keep inflation from staying too low, a person familiar with the matter said...
This marks the clearest signal yet that the Bundesbank, which has for years been defined by its conservative opposition to the ECB's emergency measures to combat the euro zone's debt crisis, is fully engaged in the fight against super-low inflation in the euro zone using monetary policy tools...
Notably, these tools apparently do not include Fed-style quantitative easing:
But the Bundesbank's backing has limits. It remains resistant to large-scale purchases of public and private debt, known as quantitative easing, the person said. The Bundesbank has discussed this option internally but has concluded that with government and corporate bond yields already quite low in Europe, the purchases wouldn't do much good and could instead create financial stability risks.
Should we conclude that there is now a global conclusion about the value and wisdom of large-scale asset purchases, a.k.a. QE? We certainly have quite a bit of experience with large-scale purchases now. But I think it is also fair to say that that experience has yet to yield firm consensus.
You probably don’t need much convincing that QE consensus remains elusive. But just in case, I invite you to consider the panel discussion we titled “Greasing the Skids: Was Quantitative Easing Needed to Unstick Markets? Or Has it Merely Sped Us toward the Next Crisis?” The discussion was organized for last month’s 2014 edition of the annual Atlanta Fed Financial Markets Conference.
Opinions among the panelists were, shall we say, diverse. You can view the entire session via this link. But if you don’t have an hour and 40 minutes to spare, here is the (less than) ten-minute highlight reel, wherein Carnegie Mellon Professor Allan Meltzer opines that Fed QE has become “a foolish program,” Jeffries LLC Chief Market Strategist David Zervos declares himself an unabashed “lover of QE,” and Federal Reserve Governor Jeremy Stein weighs in on some of the financial stability questions associated with very accommodative policy:
You probably detected some differences of opinion there. If that, however, didn’t satisfy your craving for unfiltered debate, click on through to this link to hear Professor Meltzer and Mr. Zervos consider some of Governor Stein’s comments on monitoring debt markets, regulatory approaches to pursuing financial stability objectives, and the efficacy of capital requirements for banks.
By Dave Altig, executive vice president and research director of the Atlanta Fed.
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January 31, 2014
A Brief Interview with Sergio Rebelo on the Euro-Area Economy
Last month, we at the Atlanta Fed had the great pleasure of hosting Sergio Rebelo for a couple of days. While he was here, we asked Sergio to share his thoughts on a wide range of current economic topics. Here is a snippet of a Q&A we had with him about the state of the euro-area economy:
Sergio, what would you say was the genesis of the problems the euro area has faced in recent years?
The contours of the euro area’s problems are fairly well known. The advent of the euro gave peripheral countries—Ireland, Spain, Portugal, and Greece—the ability to borrow at rates that were similar to Germany's. This convergence of borrowing costs was encouraged through regulation that allowed banks to treat all euro-area sovereign bonds as risk free.
The capital inflows into the peripheral countries were not, for the most part, directed to the tradable sector. Instead, they financed increases in private consumption, large housing booms in Ireland and Spain, and increases in government spending in Greece and Portugal. The credit-driven economic boom led to a rise in labor costs and a loss of competitiveness in the tradable sector.
Was there a connection between the financial crisis in the United States and the sovereign debt crisis in the euro area?
Simply put, after Lehman Brothers went bankrupt, we had a sudden stop of capital flows into the periphery, similar to that experienced in the past by many Latin American countries. The periphery boom quickly turned into a bust.
What do you see as the role for euro area monetary policy in that context?
It seems clear that more expansionary monetary policy would have been helpful. First, it would have reduced real labor costs in the peripheral countries. In those countries, the presence of high unemployment rates moderates nominal wage increases, so higher inflation would have reduced real wages. Second, inflation would have reduced the real value of the debts of governments, banks, households, and firms. There might have been some loss of credibility on the part of the ECB [European Central Bank], resulting in a small inflation premium on euro bonds for some time. But this potential cost would have been worth paying in return for the benefits.
And did this happen?
In my view, the ECB did not follow a sufficiently expansionary monetary policy. In fact, the euro-area inflation rate has been consistently below 2 percent and the euro is relatively strong when compared to a purchasing-power-parity benchmark. The euro area turned to contractionary fiscal policy as a panacea. There are good theoretical reasons to believe that—when the interest rate remains constant that so the central bank does not cushion the fall in government spending—the multiplier effect of government spending cuts can be very large. See, for example, Gauti Eggertsson and Michael Woodford, “The Zero Interest-rate Bound and Optimal Monetary Policy,” and Lawrence Christiano, Martin Eichenbaum, and Sergio Rebelo, "When Is the Government Spending Multiplier Large?”
Theory aside, the results of the austerity policies implemented in the euro area are clear. All of the countries that underwent this treatment are now much less solvent than in the beginning of the adjustment programs managed by the European Commission, the International Monetary Fund, and the ECB.
Bank stress testing has become a cornerstone of macroprudential financial oversight. Do you think they helped stabilize the situation in the euro area during the height of the crisis in 2010 and 2011?
No. Quite the opposite. I think the euro-area problems were compounded by the weak stress tests conducted by the European Banking Association in 2011. Almost no banks failed, and almost no capital was raised. Banks largely increased their capital-to-asset ratios by reducing assets, which resulted in a credit crunch that added to the woes of the peripheral countries.
But we’re past the worst now, right? Is the outlook for the euro-area economy improving?
After hitting the bottom, a very modest recovery is under way in Europe. But the risk that a Japanese-style malaise will afflict Europe is very real. One useful step on the horizon is the creation of a banking union. This measure could potentially alleviate the severe credit crunch afflicting the periphery countries.
Thanks, Sergio, for this pretty sobering assessment.
By John Robertson, a vice president and senior economist in the Atlanta Fed’s research department
Editor’s note: Sergio Rebelo is the Tokai Bank Distinguished Professor of International Finance at Northwestern University’s Kellogg School of Management. He is a fellow of the Econometric Society, the National Bureau of Economic Research, and the Center for Economic Policy Research.
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December 04, 2013
Is (Risk) Sharing Always a Virtue?
The financial system cannot be made completely safe because it exists to allocate funds to inherently risky projects in the real economy. Thus, an important question for policymakers is how best to structure the financial system to absorb these losses while minimizing the risk that financial sector failures will impair the real economy.
Standard theories would predict that one good way of reducing financial sector risk is diversification. For example, the financial system could be structured to facilitate the development of large banks, a point often made by advocates for big banks such as Steve Bartlett. Another, not mutually exclusive, way of enhancing diversification is to create a system that shares risks across banks. An example is the Dodd-Frank Act mandate requiring formerly over-the-counter derivatives transactions to be centrally cleared.
However, do these conclusions based on individual bank stability necessarily imply that risk sharing will make the financial system safer? Is it even relevant to the principal risks facing the financial system? Some of the papers presented at the recent Atlanta Fed conference, "Indices of Riskiness: Management and Regulatory Implications," broadly addressed these questions and others. Other papers discuss the impact of bank distress on local economies, methods of predicting bank failure, and various aspects of incentive compensation paid to bankers (which I discuss in a recent Notes from the Vault).
The stability implications of greater risk sharing across banks are explored in "Systemic Risk and Stability in Financial Networks" by Daron Acemoglu, Asuman Ozdaglar, and Alireza Tahbaz-Salehi. They develop a theoretical model of risk sharing in networks of banks. The most relevant comparison they draw is between what they call a "complete financial network" (maximum possible diversification) and a "weakly connected" network in which there is substantial risk sharing between pairs of banks but very little risk sharing outside the individual pairs. Consistent with the standard view of diversification, the complete networks experience few, if any, failures when individual banks are subject to small shocks, but some pairs of banks do fail in the weakly connected networks. However, at some point the losses become so large that the complete network undergoes a phase transition, spreading the losses in a way that causes the failure of more banks than would have occurred with less risk sharing.
Extrapolating from this paper, one could imagine that risk sharing could induce a false sense of security that would ultimately make a financial system substantially less stable. At first a more interconnected system shrugs off smaller shocks with seemingly no adverse impact. This leads bankers and policymakers to believe that the system can handle even more risk because it has become more stable. However, at some point the increased risk taking leads to losses sufficiently large to trigger a phase transition, and the system proves to be even less stable than it was with weaker interconnections.
While interconnections between financial firms are a theoretically important determinant of contagion, how important are these connections in practice? "Financial Firm Bankruptcy and Contagion," by Jean Helwege and Gaiyan Zhang, analyzes the spillovers from distressed and failing financial firms from 1980 to 2010. Looking at the financial firms that failed, they find that counterparty risk exposure (the interconnections) tend to be small, with no single exposure above $2 billion and the average a mere $53.4 million. They note that these small exposures are consistent with regulations that limit banks' exposure to any single counterparty. They then look at information contagion, in which the disclosure of distress at one financial firm may signal adverse information about the quality of a rival's assets. They find that the effect of these signals is comparable to that found for direct credit exposure.
Helwege and Zhang's results suggest that we should be at least as concerned about separate banks' exposure to an adverse shock that hits all of their assets as we should be about losses that are shared through bank networks. One possible common shock is the likely increase in the level and slope of the term structure as the Federal Reserve begins tapering its asset purchases and starts a process ultimately leading to the normalization of short-term interest rate setting. Although historical data cannot directly address banks' current exposure to such shocks, such data can provide evidence on banks' past exposure. William B. English, Skander J. Van den Heuvel, and Egon Zakrajšek presented evidence on this exposure in the paper "Interest Rate Risk and Bank Equity Valuations." They find a significant decrease in bank stock prices in response to an unexpected increase in the level or slope of the term structure. The response to slope increases (likely the primary effect of tapering) is somewhat attenuated at banks with large maturity gaps. One explanation for this finding is that these banks may partially recover their current losses with gains they will accrue when booking new assets (funded by shorter-term liabilities).
Overall, the papers presented in this part of the conference suggest that more risk sharing among financial institutions is not necessarily always better. Even though it may provide the appearance of increased stability in response to small shocks, the system is becoming less robust to larger shocks. However, it also suggests that shared exposures to a common risk are likely to present at least as an important a threat to financial stability as interconnections among financial firms, especially as the term structure and the overall economy respond to the eventual return to normal monetary policy. Along these lines, I recently offered some thoughts on how to reduce the risk of large widespread losses due to exposures to a common (credit) risk factor.
By Larry Wall, director of the Atlanta Fed's Center for Financial Innovation and Stability
Note: The conference "Indices of Riskiness: Management and Regulatory Implications" was organized by Glenn Harrison (Georgia State University's Center for the Economic Analysis of Risk), Jean-Charles Rochet, (University of Zurich), Markus Sticker, Dirk Tasche (Bank of England, Prudential Regulatory Authority), and Larry Wall (the Atlanta Fed's Center for Financial Innovation and Stability).
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