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Policy Hub: Macroblog provides concise commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues for a broad audience.

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August 20, 2021

How Does a Household's Exposure to Monetary Policy Vary over the Life Cycle?

A recent study by Feiveson et al. Adobe PDF file formatOff-site link establishes the Federal Open Market Committee's interest in the distributional effects of monetary policy. The size and the composition of household income exhibit large variation over the life cycle, so it is likely that household exposures to monetary policy also depend on age. This post summarizes new research by Daisuke Ikeda and me that uses a life cycle model to measure the age profile of household exposures to monetary policy. In the model, a higher nominal interest rate increases the wealth and consumption of households between the ages of 60 and 80, but it reduces the wealth and consumption of younger working-age households and the oldest retirees. The former group also has the highest net worth, and it follows that net worth and consumption inequality increase in the model.

Our new research took as its jumping-off point the premise that a household's age affects its economic opportunities. Both the size and the sources of income vary with age. On average, 55-year-old workers have higher earnings than 25-year-old workers and also higher earnings than 65-year-old workers. Other research by us documents this result for the United States and Japan, but age-earnings profiles are hump-shaped in other high-income economies, too. Beyond age 65, an increasing fraction of individuals in high-income economies have low or no labor earnings as they transition into retirement. Retirees have no labor income, and an important source of income for them is their public pension, which typically only replaces a fraction of their previous labor earnings.

Individuals understand these constraints and cope with them by making asset-allocation decisions. Table 1 depicts the age profile of household net worth and a decomposition of net worth into two categories: liquid assets and illiquid assets. Liquid assets include deposit accounts, CDs, bonds, and all loans, while illiquid assets consist of physical assets like homes, cars, and financial assets such as stocks, which are more costly to acquire and sell. We use Japanese survey data because they provide considerable detail on the various components of household net worth. Younger households have low net worth and negative holdings of liquid assets (they are net borrowers), but they hold positive amounts of illiquid assets. Net worth increases with age up to retirement, which typically occurs between the ages of 60 and 69 and then declines during retirement. Older working-age households and younger retirees hold positive amounts of both liquid and illiquid assets. A limitation of our data is that they don't provide details about asset holdings of the oldest households. Indirect evidence we discuss in Braun and Ikeda (2021) suggests that some older households have negative holdings of liquid assets too.

table 01 of 01
Source: 2014 National Survey of Finances, Income and Expenditures, total households. See Braun and Ikeda (2021) for more details.
Note: The age of a household is indexed by the age of the household head. Liquid assets are net of all household borrowing, and net worth is the sum of liquid and illiquid assets. All numbers are divided by income of the 50–59 age group.

We expect that similar patterns also occur in other countries. However, the specific magnitudes of the age profiles of income, net worth, and their components will depend on institutions in a given country. For instance, households in countries that offer free tuition for higher education will have less student loan debt.

A tighter monetary policy (in other words, a higher policy nominal interest rate) is generally associated with higher real interest rates on deposits and loans (liquid assets), weaker performance of stock and real estate markets (illiquid assets), and slower growth in employment and wages. Given that the size and composition of income and net worth vary with age, one might surmise that a household's overall exposure to monetary policy also depends on its age. Retired households, for instance, may gain because they have no direct exposure to the labor market and hold large positive amounts of deposits whose return goes up. Young working-age households, in contrast, may lose because they have low net worth, loans, and low labor earnings.

Unfortunately, finding data that can be used to directly assess these hypotheses is challenging. In the United States, there is reasonably good survey data about how labor income and financial assets vary by age, but much less information about the size and value of household holdings of physical assets like homes, cars, and TV sets. Moreover, even in countries like Japan, where reasonably comprehensive survey data are available, a cross-sectional snapshot is produced only once every five years. Even if we can identify exogenous changes in monetary policy, we lack high-frequency data to measure how household exposures to monetary policy vary by age.

An alternative approach is to use an economic model. To see how this works, we define wealth as a household's net expected present value of future income from labor, assets, and the government. Wealth is an important economic concept because standard economic theory predicts that a household that sees its wealth increase from a tighter monetary policy will consume at least a fraction of its bonus. Conversely, a household whose wealth falls will consume less. Recent work by AuclertOff-site link builds on this insight. He uses a model to specify the dynamics of household income and decompose a household's consumption response to a change in monetary policy into four components:

  • The income component captures the impact of changes in monetary policy on labor and government income.
  • The unexpected inflation component captures net capital gains or losses associated with holdings of nominal assets. For instance, most government debt is nominally denominated, and a change in monetary policy affects the inflation rate and thus the real value of this nominal asset.
  • The unhedged real interest rate component captures net real capital gains on household assets that are coming due at the time of the shock. For instance, a higher real return on deposits is good for a saver who has no loans, but a higher real interest rate can be bad for a borrower who enters the period with a maturing loan and faces a higher real cost of paying it off.
  • Finally, the substitution component captures how a change in the interest rate affects a household's tradeoff between consuming today and saving today, which allows it to consume more tomorrow.

In our working paper, we propose a model designed to measure how household exposures to monetary policy vary over the life cycle. We specify the model to reproduce the main features about how household income, net worth, and portfolio allocations vary over the life cycle using data from Japan. Our model is rich in the sense that households are active for up to 100 years. They work and make asset-allocation decisions over time and interact in markets with households who have different ages and thus different asset-allocation priorities. Further, we model a government that taxes households, issues nominal debt, and runs a public pension program. Finally, the monetary authority sets the nominal interest rate on liquid assets using a simple rule. Fortunately, the model also has sensible implications for how nominal and real interest rates, wages, and government income respond to a tighter monetary policy.

Our model may sound rather sophisticated, but we make many simplifying assumptions. For instance, we are silent about what determines cross-sectional differences in income and wealth among households with the same age. In addition, households have only two assets that they can use to borrow or save. These simplifications make it easier to understand how age affects a household's exposure to monetary policy.

Figure 1 reports the age profile of household consumption responses to a surprise tightening in monetary policy in the year that monetary policy is tightened (left panel) and its decomposition into the four components we discussed above (right panel).

Figure 1: Consumption Responses in the Year of Tightened Monetary Policy

Note: The left panel is the sum of the four components, which is close to but not exactly the same as the age profile of consumption responses in the model.
Source: Braun and Ikeda (2021)

The sign of the consumption response varies with age in figure 1. Households close to age 68 are increasing their consumption in response to higher wealth, while older retirees and younger working-age households are facing wealth losses. Another way to ascertain differences in exposure is to measure the magnitude of the consumption response. Households around age 30 reduce their consumption most, households close to the retirement age of 68 in the model increase their consumption most, and households that survive to about age 100 reduce their consumption. The magnitude of the consumption response is an imperfect measure of exposure because net worth also varies by age, as reported in table 1. In the model, the two groups who are reducing their consumption most have relatively low net worth. Younger workers are borrowers, and old retirees of age 100 have lived well beyond their expected life span and exhausted their savings. Thus, the biggest negative exposures to a tighter monetary policy in the model are among younger workers and oldest retirees.

The right panel of figure 1 reports the Auclert decomposition of consumption responses. For younger working-age households, the negative income component and the negative intertemporal substitution component are the two biggest factors. They have lower labor income and are at the age of their life cycle where they are accumulating assets, so movements in interest rates are particularly important for them. The other two factors are less important because their net worth is low. For households between 60 and 80, the income component is small, and the two asset-income components primarily drive their consumption responses. A lower inflation rate benefits this group because they are holding relatively large positive positions in nominally denominated liquid securities to provide for their retirement. The unhedged real interest rate component (unhedged R in the chart) is large because these households are savers and are at the stage of the life cycle where they draw down their assets to smooth their consumption during retirement.

In the model, life expectancy is 83 years, and households who survive beyond this age experience declines in all four components. They have been consuming their savings since age 68 and have low net worth. Also, some members of this group have debt. This age group also receives lower net income from the government. Government labor tax revenue is down and interest rate expenses on government debt are now higher so net government transfers to households fall, and this decline is significant for the oldest households in the model.

Taken together, these findings imply that inequality in net worth increases in the model in the year that monetary policymakers tighten policy. The highest net-worth age groups see their net worth increase, and the age groups with the lowest net worth see it fall. Consumption inequality also increases in the model because households with lower net worth tend to adjust their consumption by more than households with high net worth.

Hopefully, our findings have piqued your interest and left you with new questions. How large and persistent are the changes in inequality? What are the properties of an easier monetary policy? Does the amount of government debt in the economy matter? What about the effective lower bound on the nominal interest rate? I encourage you to read our working paper to find out.

I conclude with an old saying from economics: for each borrower, there is a lender. In our model, monetary policy alters interest rates, and a higher interest rate affects borrowers and lenders differently. It's a burden on younger working-age households and on the oldest retirees who are borrowers, but it's a boon for households close to age 68 who are the savers who provide the funding for the loans to the other two groups.

May 27, 2021

The Role of Central Banks in Fostering Economic and Financial Resiliency

The Atlanta Fed recently hosted its 25th annual Financial Markets Conference, with the theme of Fostering a Resilient Economy and Financial System: The Role of Central Banks. The conference addressed both the adequacy of the monetary policy toolkit and the role of the U.S. dollar (USD) in international financial markets. The conference included two keynote talks. The first day featured a keynote speech by Federal Reserve Board vice chair Richard Clarida, followed by a discussion with Atlanta Fed president Raphael Bostic. The second day began with an armchair discussion featuring Harvard professor Larry Summers and Atlanta Fed research director David Altig. A video of the conference is available here video fileOff-site link. This post reviews some of the highlights from the conference.

Keynote talks
Vice chair Clarida's keynote speechOff-site link focused on global factors that help determine the yield curve for sovereign bonds. Clarida observed that studies of domestic and major foreign government markets have found that most of the movements in the term structure of interest rates can be explained by the overall level of the curve and the slope of the curve. He then reviewed work suggesting that a global factor—one that is highly correlated with estimates of the neutral real interest rate—has a great influence on the level of the curve. Given this information, central banks may not have much ability to influence the yield curve's level unless they are willing to unanchor inflation expectations in their domestic market. Clarida then presented evidence that the slope of the U.S. yield curve is highly correlated with its monetary policy, specifically the deviation of the U.S. neutral nominal policy rate from the actual federal funds rate. He acknowledged that correlation does not equal causation but provided some evidence that central bank decisions (by the Fed and major foreign central banks) have a causal relationship with the slope of the yield curve. These observations led Clarida to conclude that "major central banks can be thought of as calibrating and conducting the transmission of policy...primarily through the slopes of their yield curves and much less so via their levels."

Professor Summers raised a variety of concerns about current policy and the risks to the financial system in his chat on the conference's second day. One of these concerns relates to the monetary policy projections, which suggest that inflation will remain sufficiently low so that the Fed's policy rate may not increase for several years. This expectation of low rates may create a "dangerous complacency," according to Summers, that will make it more difficult to raise rates. The result may be that nominal policy rates remain too low, producing higher inflation that leads to even lower real rates and even higher inflation. The result could be not only a "substantial pro-cyclical bias in financial conditions" but also a threat to financial stability if the low nominal rates result in excessive financial leverage.

Monetary policy panel session
The monetary policy toolkit received some scrutiny in a panel titled "Is the Monetary Policy Toolkit Adequate to Meet Future Challenges?" It was moderated by Julia Coronado, president of MacroPolicy Perspectives. Coronado promised a session with some provocative comments, and each of her panelists delivered. Among the problems addressed by the panelists was central banks' limited ability to counteract economic downturns. Historically, central banks have lowered their nominal interest rate target by several percentage points in response to the onset of a recession, or even the elevated risk of one. The continuing decline in nominal rates, however, has reduced central banks' ability to use rate reductions to fight recessions, instead forcing them to rely more on quantitative easing (or more accurately, large-scale asset purchases). Joseph Gagnon, a senior fellow at the Peterson Institute for International Economics, and Willem Buiter, a visiting professor at Columbia University, provided two alternative ways of restoring the central bank's ability to lower nominal rates by more than 1 or 2 percentage points.

Gagnon's analysis was based on the Fisher equation, in which the nominal interest rate is approximately equal to the real rate of interest plus the rate of inflation. Gagnon observed that central banks, including the Fed, had set a target inflation rate of 2 percent back when the equilibrium real rate was higher (likely around 2 to 3 percent). Establishing this target rate resulted in equilibrium nominal interest rates around 4 to 5 percent, which gave central banks considerable room to respond to a recession. However, in the period since the inflation targets were set, equilibrium real rates have fallen by 1 to 2 percentage points. This decline greatly reduced central banks' ability to lower rates without taking them negative. Thus, to restore the ability of central banks to respond to higher inflation, Gagnon argued that central banks' inflation target should be increased to 3 to 4 percent.

Buiter implicitly started from the same point: that the decline in the equilibrium real rate had left central banks with too little room to cut interest rates. However, rather than raising the inflation target, Buiter argued that a better solution would be to accept deeply negative nominal interest rates. Several central banks in Europe, as well as the Bank of Japan, have lowered their rates below zero but never as much as 1 percent below zero. Buiter recommended that central banks take the steps necessary to be able to have deeply negative interest rates if that is appropriate for conditions.

Simon Potter, vice chairman at Millennium Management, noted an international dimension to the Fed's policy setting. Potter observed that many emerging markets had taken on considerably more debt to respond to the ongoing pandemic. He argued that these countries would need fast U.S. growth, and the accompanying increase in exports to the United States to be able to service their debt. Absent such increased debt service capacity, he pointed out that changes in the structure of these countries' debt markets would make rescheduling their debts even more difficult than it had been previously.

These provocative comments did not go unchallenged, however, as the other panelists raised concerns about the feasibility and/or desirability about each of these policy recommendations in the subsequent discussion that Coronado moderated.

Global dollar policy session
A panel on the conference's second day had the provocative title "Is the Financial System's Backbone, the U.S. Dollar, Also a Transmitter of Stress?" The panel's moderator was Federal Reserve Bank of Dallas president Robert Kaplan, who began the discussion by highlighting the importance of the USD in both international trade and international financial markets.

Stanford University Professor Arvind Krishnamurthy's presentation Adobe PDF file format supplied further evidence on the importance of the USD in trade and financial markets. He suggested that the USD's important role resulted in it providing a convenience yield to its users, which resulted in lower USD interest rates for those borrowing USD—both domestic and foreign borrowers. These lower rates, however, came with some financial risks, according to Krishnamurthy. For one, lower rates may induce greater financial leverage in U.S. borrowers. Additionally, foreigners who borrow USD to take advantage of the lower rates may be creating a mismatch between the currency they receive as revenue (especially from sales in their domestic markets) and the USD they need to repay their debt.

Thomas Jordan, chairman of the governing board of the Swiss National Bank, also noted the dominance of the USD in international markets and discussed its implications from the Swiss point of view. He noted two ways in which Switzerland is especially vulnerable to developments regarding USD. First, Swiss banks hold substantial amounts of USD assets and liabilities. Second, the Swiss franc is a safe haven currency that experiences increased demand in times of international financial stress. These result in Switzerland having a strong interest in global financial stability and especially in the stability of USD-funding markets. In this respect, Jordan observed that the Federal Reserve's swap lines with other central banks, including the Swiss National Bank, has been "very crucial." The swap lines provide an important liquidity backstop that recently proved valuable during the COVID-19 crisis.

Michael Howell, the managing director at CrossBorder Capital, focused on the potential for another currency to displace the USD in international markets. In his presentation Adobe PDF file format, he argued we should not be "shortsighted" in dismissing other currencies. In particular, he pointed to China, saying that China sees the USD as a rival and wants to displace it, particularly in Asia. He then went on to discuss some of the steps that China would need to take—and is taking—to displace the USD.

After these remarks by the panelists, Kaplan moderated a question-and-answer session that took a closer look at these and other issues.

May 3, 2021

Is There a Global Factor in U.S. Bond Yields?

The answer to this question seems obvious simply from observing the secular comovement of global nominal yields across some advanced economies plotted in chart 1.

Chart 1: 10-Year Bond Yields, 1992-2021

This observation raises the possibility that domestic bond yields, including those in the large U.S. Treasury market, may be anchored by global economic developments (see, for example, hereOff-site link and hereOff-site link), provision of global liquidity, and international markets arbitrage. The synchronized dynamics in global yields during the last few months serve as a stark reminder of the powerful role that global bond markets play in the transmission of country-specific shocks as well as of monetary and fiscal impulses.

Yet the standard term structure models (see, for example, hereOff-site link), that policymakers and market participants use to form their expectations about the future path of the policy rate, are typically estimated only with information embedded in domestic yields. Global influences enter only via the term premia—that is, the extra returns that investors demand to hold long-term bonds—and are influenced by the flight to safety and arbitrage across international markets. But because the term premia are obtained as a residual component in the model, any misspecification of the factor structure that drives equilibrium interest rates—by omitting a common global factor, for example—may result in erroneously attributing some fundamental movements to the term premia.

Chart 2 illustrates this point, presenting a less-noticed and even overlooked empirical regularity between the term premiaOff-site link on the spread between the 10-year U.S. bond and the 10-year/2-year German bond, which is the benchmark bond for the Eurozone government bond market. This comovement has proved remarkably strong since 2014.1

Chart 2: German Bond Spread and U.S. Term Premia, 2010–21

Take, for example, the pronounced decline in the term premia and the accompanying slide in the German bond spread between 2014 and 2019. Although technical factors might be behind the downward trend in the German bond spread—for example, large Eurozone bond outflows triggered by the euro-area crisis and the introduction of negative interest rates—the slope of the yield curve could also convey important information about the fundamentals of the economy. If the term premia on the 10-year U.S. bond reflect an exogenous "distortion" in the U.S. yield curve due to a flight to safety or an elevated demand for global safe assets, yields are likely to return to normal levels when the uncertainty shock dissipates. In contrast, if investors interpret the yield curve's decline as an endogenous "risk-off" response—that is, a switch to less risky assets—to a deteriorated global environment that can spill over to the U.S. economy, the term structure model would require a "global" factor whose omission may otherwise contaminate an estimate of the term premia.

So how sensitive is the estimate of the future path of policy rate to model specification? I next illustrate this sensitivity by augmenting the factor space in a standard (five-factor) term structure model with incremental information from an additional global factor, not contained in the other factors. Given the reasonably tight correlation between the term premia for the 10-year U.S. bond and the 10-year/2-year German bond spread, it seems natural to use the latter as an observed proxy for a global factor, although other statistical approaches for extracting one or more common global factors are certainly possible.

To quantify the potential effect of the global factor, I focus on yield curve dynamics seen in 2019, a period characterized by elevated economic, trade, and geopolitical uncertainty that led to a material decline in observed yields. But did a fundamental shift in the expected path of policy rate, or lower term premia, drive this decline? In the left panel of chart 3, I plot the expected policy rate paths for the second quarter (or midpoint) of 2019, obtained from models with and without a global factor. (Recall that in the second quarter of 2019, the target range for the federal funds rate was 2.25 percent to 2.50 percent.)

Chart 3: Model-Implied Paths of Policy Rate

The difference in the shape of the expected policy rate paths implied by the two models is striking. (The models' estimates use unsmoothed yield data at quarterly frequency, with continuous bond maturities from one to 80 quarters.) Although the expected policy rate path for the standard model is fairly flat, the rate path for the model with a global factor is deeply inverted up to five-year maturities, suggesting that over this horizon one could have expected rate cuts of almost 100 basis points. These expectations occurred against the backdrop of stable growth and inflation outlook in the United States but deteriorating global economic and trade conditions. The right panel of chart 3 displays the evolution of the expected rate path, estimated from the global factor model, for the two quarters before and the two quarters after the second quarter of 2019, as the Federal Reserve started to adjust its policy rate lower. It is worth noting that the strong effect of the German 10-year/2-year spread in the term structure model with global factor is a relatively recent phenomenon. (Additional results suggest that this factor has only a muted impact on the model estimates prior to 2014.)

The policy implications of these findings warrant several remarks. One direct implication is that the common global determinants of the neutral rate of interest, as well as inflationary dynamics, could constrain the potency of domestic monetary policy. A prime example of these constraints was the policy rate normalization phase undertaken by the Fed during the 2016–18 period, which was characterized by global disinflationary pressures, underwhelming economic performance in Europe and Japan, slowing economic growth in China, and escalating trade tensions. These forces were potentially counteracting the Fed's policy efforts and exerting downward pressure on the global neutral rate of interest. The recent economic and financial developments resulting from the COVID-19 pandemic (such as the global nature of the shock, synchronized monetary and fiscal response across countries, and international financial market comovements) and the ongoing recovery appear to only strengthen the case for the importance of incorporating global information in bond-pricing models.

1 [go back] I should note that the correlation between the two series increased from 52.9 percent before 2014 to 76.2 percent after 2014. Interestingly, the beginning of 2014 marks another important shift in financial markets: a sharp and persistent compression in the breakeven inflation forward curve, as a Liberty Street Economics blog postOff-site link recently discussed. A similar flattening is present in the forward term premia of nominal bonds. This is consistent with the interpretation that such flattening—starting in 2014—is likely the result of a new regime, characterized by the compression of inflation risk across maturities.

May 18, 2020

A Couple of Insights from the April Current Population Survey

The latest reading of the Atlanta Fed’s Wage Growth Tracker indicates that wage growth is slowing. It came in at 3.3 percent for April, down from 3.5 percent in March and 3.7 percent in February. This slowing primarily reflects the relatively large decline in the employment of those who typically experience the fastest wage growth: young workers. In February, those aged 16–24 accounted for about 12 percent of employment. By April, that share had dropped to under 10 percent. This change has significant bearing on the Wage Growth Tracker because those aged 16–24 had median wage growth of around 7.8 percent on average over the last year, versus 3.6 percent for all workers. So their decreased share of employment has helped pull overall median wage growth lower (see here for more discussion).

Note that while the tracker reflects the compositional change in who is employed, it didn’t show a spike in wage growth suggested by the average hourly earnings data from the Bureau of Labor Statistics' Payroll Survey. This is because the average hourly earnings data are a snapshot of the average earnings of all workers, hence last year's average will include people who are not employed today (and vice versa). As a result, the spike in average earnings was for an awful reason: a lot of low-wage workers lost their jobs. In contrast, the tracker compares the wages of the fortunate people who were employed both today and a year earlier.

Another wage development to keep an eye on are wage freezes. During the Great Recession, there was a large and persistent increase in the fraction of workers who said their wage was unchanged from a year earlier. We will be examining the Wage Growth Tracker data for evidence of an increased incidence of wage freezes or even wage cuts. The fraction of people reporting no change in their wage has increased from 13.7 percent in February to 14.1 percent in April. In contrast, the cyclical low for this series was 12.7 percent in November of 2019.

The April data also revealed a sharp increase in the number of people who are employed but on unpaid absence from work for "other reasons." As described in this recent macroblog post, these are most likely people whose employers furloughed them. March saw an estimated 1.5 million such workers. In April, that number swelled to 6.2 million. If those people had been counted as unemployed instead of employed, the unemployment rate would have been 18.7 percent in April instead of the official number of 14.7 percent. Going forward, a gauge of the strength of the labor market recovery will be how many of these furloughed workers eventually return to work versus become unemployed—or even leave the labor force. Stay tuned.

John Robertson, a senior policy adviser in the Atlanta Fed's research department