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What’s a countercyclical capital buffer?

A new monetary policy tool, that's what

The Federal Reserve has tools to achieve its monetary policy goals: the discount rate, reserve requirements, open market operations, the interest rate on reserves… and now also the countercyclical capital buffer (CCyB). The CCyB is intended to avoid the banking failures of the Great Recession by ensuring individual banks and the banking sector as a whole have enough capital on hand to provide a flow of credit to the economy without jeopardizing the solvency of this sector. To achieve this goal, a monetary authority (such as the Fed) would require banks to hold a percentage of their capital in a reserve or buffer account. The exact percentage can be changed depending on the state of the economy. If the authority believes too much credit exists, then the percentage of banks’ capital held in reserve must be increased to reduce banks’ ability to lend or provide credit. On the other hand, if the authority believes the economy needs to be stimulated, the percentage of banks’ capital held in reserves can be reduced to encourage more lending.

In practice, this is accomplished by setting a minimum value for the ratio of banks’ Tier 1 capital relative to its risk-weighted assets. Tier 1 capital can be thought of as stockholder equity and retained earnings, while risk-weighted assets are mostly the risk-weighted value of outstanding loans. The more risky the outstanding loans relative to held capital, the lower this ratio will go. To raise this ratio, banks can hold more capital and/or issue fewer risker loans.

The first graph shows the ratio of Tier 1 capital to risk-weighted assets since 2010 (blue-line) for the banking sector. Even without the CCyB, the minimum capital requirement and capital conservation buffer ensures that this ratio should not decline below 8.5% for any bank (the lower green line). The Fed could use the CCyB to raise this minimum value by up to 2.5 percentage points, to 11% (the higher green line). Currently, however, the Federal Reserve hasn’t used its authority to set a CCyB and so the lower bound for this ratio remains at 8.5%. As the graph shows, the aggregate banking sector ratio (blue line) hasn’t fallen below the 11% maximum ratio that the Federal Reserve can put in place.

In some sense, the aggregate ratio of Tier 1 capital to risk-weighted assets could be misleading: Even though the overall average is relatively high, the individual ratio of any given bank may very well be below the 11% or even the 8.5% cutoff. By looking at public call report data, we can get some idea of the position of individual banks. From our calculations, assuming the data are normally distributed, about 16% of banks will have ratios below the dotted red line. The line for this subset of banks is above the 8% line and crossed the 11% line beginning in the first quarter of 2018. This suggests that raising the minimum ratio level would have a significant effect on many banks. (Of course, this is only an approximation: The data aren’t exactly normally distributed. Instead, there are a substantial amount of firms clumped around the 8.5% lower limit, because dipping below that limit will introduce substantial regulatory burdens. In either case, however, the conclusion that a significant portion of banks would be effected by a rising CCyB holds true.)

So how do the monetary authorities decide when to use a CCyB in this way to limit the amount of credit in the economy? In other words, how much credit in the economy is “too much?” It’s not enough to simply look at the total amount of credit because any given amount of credit may be too much or too little depending upon the size of the economy. To resolve this quandary, the Federal Reserve monitors the ratio of total credit to GDP and detrends the series to ignore any long-run movements in the ratio unlikely to be associated with any given financial crisis. Perhaps the simplest method of detrending is to create a line of best fit for the data, as we have done in the second graph. Whenever the credit-to-GDP ratio gets high enough above the trend line, say, by 2.5% of GDP, a monetary authority may want to consider increasing the capital buffers to slow the growth of credit.

How these graphs were created: First graph: Search for and select “Financial Soundness Indicator; Regulatory Tier 1 Capital as a Percent of Risk-weighted Assets, Level” and click “Add to Graph. From the “Edit Graph” panel, use the “Add line” feature to add the other data series (red) and the two (green) user-defined lines: For the red line, add the original series again and use the “Formula” bar to specify either plus three or minus three depending on what you’d like to show. For the green lines, use the “Create user-defined line” option and click on “Create line”: Change the “Value start/end” fields to reflect the constant value you want to display (we graphed 8.5 and 11). All colors and line styles can be changes in the “Format” panel.

Second graph: Search for and select “Total Credit to Private Non-Financial Sector, Adjusted for Breaks, for United States.” Then, below the series, select “Percentage of GDP” option to see the ratio of interest. Detrending this data series is the tricky part: FRED doesn’t yet have a built-in function for detrending; but you can add a line to the graph as we did for the previous graph and set it so that seems to come as close to as much of the graph as possible. We downloaded the data as a CSV file using the download button and then performed a quick regression. Next we used the fitted value for 01/01/1952 (60.763) and the fitted value for 10/1/2018 (163.7093) to draw the computer-generated line of best fit in the FRED graph. If you’re more experienced in statistics, read on: The Basel Committee, an international body that set initial international guidelines on the use of CCyBs, recommends detrending with a Hodrick-Prescott filter with a lambda value of 400,000. We did this, too, and our results aren’t substantially different.

Suggested by Ryan Mather and Don Schlagenhauf.

View on FRED, series used in this post: BOGZ1FL010000016Q, QUSPAM770A

Gauging returns and risk in the bond market

The term premium, risk premium, and yield curve

Investors in the corporate bond market routinely make decisions about which bonds to purchase; and they look at, among other things, the rates of return of those bonds. One way of computing a bond’s rate of return is to take into account all future streams of payments (interest coupons) as well as the difference between the price and the principal if the bond is held to maturity. This rate of return is known as the yield of the bond.

The yield on a security allows investors to decide whether to accept the riskiness and the cost of holding that security for an extended period or to invest in a safer, shorter-term bond. In other words, yields capture both a risk premium (the compensation for uncertainty in the streams of payments) and a term premium (the compensation for a longer delay in receiving payments). We can use FRED’s data and graphing tools to produce measures of both the risk premium and the term premium and see how these measures have evolved over time.

The first graph shows three interest rates: the 5-year yield on investment-grade corporate bonds, the 5-year Treasury rate, and the federal funds rate. These three interest rates provide us with information on the returns to a 5-year corporate bond, a 5-year Treasury bond, and an overnight bond. The graph shows that the federal funds rate is typically lower than the other two rates: Lenders require additional compensation to lend for longer periods (5 years in this case). Since both Treasury bonds and federal funds are extremely safe assets, the risk premium is negligible and any difference between the two arises from the term premium.

Mathematically, the term premium is the difference between the Treasury rate for a given maturity and the federal funds rate. The second graph plots the term premium since 1984. This indicator seems to be countercyclical—that is, it falls during expansions and rises during recessions. More interestingly, it tends to go negative right before a recession, and this is what people refer to when talking about a “yield curve inversion.”

As the first graph shows, the yield on 5-year corporate bonds exceeds the yield on 5-year Treasury bonds. Since these two groups of bonds have the same maturity, this difference cannot be explained by the term premium. Rather, it’s explained by the risk premium: the compensation lenders require to invest in a riskier asset (such as a corporate bond) as opposed to investing in a safer asset of equivalent maturity (such as a Treasury bond).

Mathematically, the risk premium is the difference between the yield on a risky bond and the yield on a Treasury bond of equivalent maturity. The third graph plots this difference. Again, this measure is countercyclical. See the prominent spike in 2008-09? The risk premium rose way above its historical average during the Great Recession following the Financial Crisis. If market participants anticipate an increase in risk, as they did in 2008, then the risk premium rises in response. Since the risk premium measures expectations of credit risk and default in the economy, it’s an important way to monitor markets to ascertain whether a downturn is expected in the near future.

How these graphs were created: For the first graph, search for and select the series “5-Year High Quality Market (HQM) Corporate Bond Spot Rate.” Use the “Add Line” option in the “Edit Graph” menu to search for and add the other two series: “5-Year Treasury Constant Maturity Rate” and “Effective Federal Funds Rate.” For the second graph, search for and select the series “5-Year Treasury Constant Maturity Rate.” Then use the “Edit Line 1” tab in the “Edit Graph” menu to add the series “Effective Federal Funds Rate” in the “Customize data” field. In the “Formula” box, type a-b. Repeat these steps for the third graph by searching for and selecting the series “5-Year HQM Corporate Bond Spot Rate” and the series “5-year Treasury Constant Maturity Rate.”

Suggested by Asha Bharadwaj and Miguel Faria-e-Castro.

View on FRED, series used in this post: FEDFUNDS, GS5, HQMCB5YR


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