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October 18, 2021
Market Response to Taper Talk
As the Fed discusses reducing its $120 billion in monthly purchases of Treasury and mortgage-backed securities, market pundits have begun to form opinions on whether such talk about tapering will roil markets as it did in 2013. Some believe that, given the size of the Fed's monthly purchases, such discussion will lead to similar market reactions. Others believe that markets today better understand the Fed's decision-making process around its asset purchases and interest rate policy. This market knowledge and experience may help mitigate the negative effect taper talk could have this time. In this post, we provide evidence that both perspectives are at least partially correct.
To be specific, we analyze the past and present discussions on tapering, including the effects that the Federal Open Market Committee's (FOMC) September 2013 meeting, often referred to as the "untaper" meeting because plans for tapering were delayed, and the June 2021 "talking about talking about tapering" meeting had on the market's expectations for the future path of the fed funds rate. We show that a market response similar to 2013 has already occurred in the sense that an increase in the 10-year Treasury rate coincided with market participants expecting an earlier liftoff from a fed funds rate of zero. Subsequent taper talk only marginally affected how the market expects the pace of rate hikes to proceed. In other words, the market responds to increasing Treasury rates by first pricing in a strong opinion about how much time will pass before the first rate hike. Subsequent discussions about tapering have little to no effect on the market expectations for future interest rate policy.
For our analysis, we use the Federal Reserve Bank of Atlanta's, Market Probability Tracker (MPT), to measure the market's expectations for the future course of monetary policy. The MPT is computed and reported every day on the Federal Reserve Bank of Atlanta's website and is described in detail in an Atlanta Fed "Notes from the Vault" post. The MPT uses options contracts on Eurodollar futures to estimate the market's assessment of the target ranges of future effective fed funds rate. Using derivative contracts on Eurodollars has one main advantage over studying the effective fed fund futures directly. Unlike the futures market for fed funds, the options on Eurodollar futures market is one of the most liquid in the world, with a wide collection of traded options. Moreover, Eurodollar futures deliver three-month LIBOR (or London Interbank Offered Rate), which bears a stable relation and high correlation with the effective fed funds rate in global overnight money markets. Together, these features allow the MPT to extract more confidently measures of market expectations of future effective fed funds target ranges.
Turning our attention first to 2013, we look at how the market's expectations for the future path of rates changed as taper talk began to heat up. In figure 1, we plot several of the MPT's daily expected fed funds rate paths from before and after June 2013. Each unlabeled path in the figure is represented by a transparent blue line of the market expectations for the fed funds rate path as of Wednesday of that week. These weekly expected rate paths began on May 1, 2013, and ended on December 18, 2013, when the Fed announced it would begin paring down its asset purchases.
Note: Expectations computed daily with option data on Eurodollar futures contracts from May 1, 2013, to December 18, 2013. Each unlabeled line represents the market's expected path for monetary policy given the data as of Wednesday of the indicated week.
The orange line in figure 1 represents the market expectations as of May 1, 2013. At that time, no substantive discussion about the Fed shrinking its asset purchases had taken place. The FOMC had just released a statement that it would continue to purchase assets "until the outlook for the labor market has improved substantially in a context of price stability." Regarding its interest rate policy, the Committee stated that it "expects that a highly accommodative stance of monetary policy will remain appropriate for a considerable time after the asset purchase program ends and the economic recovery strengthens." Given the Fed's policy, along with the state of the economy, the market expected the first rate hike to be in mid- to late 2015.
Between May 2013 and the next FOMC meeting on June 19, 2013 (the dashed blue line in figure 1), the market's expectation for future monetary policy began to price in an earlier rate hike sometime between late 2014 to early 2015 (see the sequence of transparent blue lines in figure 1 that move up and to the left from the orange to the dashed blue line). During this period between FOMC meetings, Ben Bernanke, then chairman of the Board of Governors, testified to Congress that the FOMC "could in the next few meetings...take a step down in our pace of purchases" (Bernanke Q&A congressional testimony, May 22, 2013).
Bernanke's May 2013 testimony may have contributed to pulling forward market expectations for when the Fed would end its highly accommodative monetary policy since many expected the Fed's asset purchases to end before the fed funds rate was increased from its zero lower bound. The chair's testimony is also credited with setting off what is commonly referred to as the "taper tantrum" in the Treasury market. In figure 2, the blue line shows how much the 10-year Treasury rate had changed since May 1, 2013. According to this figure, Bernanke's testimony was certainly followed by an increase in the 10-year Treasury rate, but this increase continued a trend that began back in May 2013. And market participants had been pricing in an earlier and earlier liftoff date while the 10-year rate was increasing in May, not when the chair testified to Congress.
Note: The blue line represents the change from May 1, 2013, to February 24, 2015. The orange line represents the change from November 5, 2020, to August 27, 2021.
The Committee's June 2013 statement on monetary policy changed little from its May statement, but the expected path for the fed funds rate had already steepened (compare the dashed blue line with the orange line in figure 1). Notably, it was over the six days that followed the June FOMC statement that the 10-year Treasury increased by 40 basis points (see the blue line in figure 2). Many believe this increase in the 10-year rate was due to Bernanke's comments during the post-FOMC press conference when, in responding to a question about asset purchases, he said it would be appropriate to moderate purchases "later this year" and to end purchases "around midyear" 2014. However, for our purposes, we point out the muted impact Bernanke's answer had on the expected rate paths plotted in figure 1.
Over the next couple of months, changes in the fed funds rate path continued to be minimal even in response to Bernanke's attempt to calm other markets by assuring market participants the Fed was committed to a highly accommodative monetary policy. By the September FOMC meeting—a meeting sometimes referred to as the "untapering" meeting because the Committee decided to "await more evidence that progress will be sustained before adjusting the pace of its purchases"—the expected funds rate path was statistically indistinguishable from the June rate path (see the dashed black line in figure 1). However, the September announcement to delay the tapering of its purchases appeared to have caught bond investors by surprise. In figure 2, we see that the 10-year Treasury rate (the blue line) dropped by approximately 20 basis points over the coming weeks—all while the market's expectation for the timing of liftoff remained relatively constant.
Over the rest of 2013, the pace of the expected rate hikes stayed relatively stable. Figure 1 shows this stability by the similar curvature of the expected path lines from September to December. Interestingly, the December FOMC formal announcement that the Fed would begin to reduce its monthly purchases of Treasuries and mortgage-backed securities (MBS) by $5 billion each did not change the market's expectations for how long it would be before liftoff (see the solid black line in figure 1). We interpret this as market participants having formed their expectations about the future pace of interest rate hikes when the Treasury rates had increased and as policymakers were beginning to talk about tapering and not when the Fed announced the actual date and pace of its shrinkage in asset purchases.
Now compare figure 1 to the sequence of expected rate paths plotted in figure 3 for the time interval of November 5, 2020, to August 11, 2021. Early in this time period, the orange line in figure 2 shows the 10-year Treasury rate increasing 95 basis points from November 2020 to the end of March 2021 (the high point of the orange line in figure 2). This increase in the 10-year rate was due in part to the improving economic conditions and optimism around the advent of COVID-19 vaccines. This time period also corresponds with a steepening in the market expectations for the fed funds rate path seen in figure 3. The "lower for longer" policy of the Fed can be seen in the flat November FOMC rate path (compare the orange rate paths in figures 1 and 3). But as in figure 1, the expected rate paths in figure 3 gradually steepen while the 10-year rate is increasing.
Note: The fed funds rate path was computed from daily option data on Eurodollar futures contracts from November 5, 2020, to August 27, 2021. Each unlabeled line represents the market's expected path for monetary policy given the data as of Wednesday of the week
The minutes from the April FOMC were released to the public on May 19, 2021 (see the pink rate path in figure 3). These minutes describe several participants suggesting that "it might be appropriate at some point in upcoming meetings to begin discussing a plan for adjusting the pace of asset purchases." Discussion about shrinking the monthly purchases of assets continued into the June 2021 FOMC meeting. Importantly, at the June FOMC press conference, Fed chair Jerome Powell responded to a question about the timeline for reducing asset purchases by saying that people can think of the June meeting as the "talking about talking about" meeting.
The market's expectation about the fed funds rate path to this taper chatter was muted. Market expectations for the first rate hike had already moved up from the middle of 2024 to the first half of 2023. Given the similarity in the paths at the FOMC meetings in June (see the dotted black line in figure 3) and July (the dashed black line in figure 3), and after Chair Powell's Jackson Hole speech (the solid black line), market participants did not alter their expectations about liftoff. Not even the June FOMC's hawkish Summary of Economic Projections affected the views of market participants on the future course of interest rates.
Comparing the sequence of 2013 and 2020–21 rate paths plotted in figures 1 and 3, we might believe that those who think tapering in 2021 will lead to a similar market reaction as in 2013 are right—but only in the sense that both events corresponded to a sizeable increase in the 10-year Treasury rate and not the actual taper.
That being said, after the rate paths in figures 1 and 3 steepened, the limited impact that taper talk had on the rate paths lends support to those who expect tapering to be a nonevent. The relatively constant pace of expected rate hikes found in 2013 and 2021 suggests that a formal announcement by the Fed on reducing its purchases of Treasuries and agency MBS will likely have a limited effect on the market expectations for the pace of future rate hikes. This is especially true for the 18- to 24-month time horizon of the rate paths.
Regardless of whether we believe that there will or will not be a "taper tantrum" similar to the one in 2013, the market expectations calculated from the Eurodollar futures market clearly show two common effects from the events of 2013 and 2020–21. The first is that as the 10-year Treasury rate begins to rise, market participants expect the Fed to start raising the fed funds rate earlier than before. The second effect is that after the first effect, the expected pace of future rate hikes does not appear to be very responsive to taper talk. Hopefully, knowledge of these tapering-related empirical regularities will help market participants form more accurate predictions about future interest rate policies.
August 20, 2021
How Does a Household's Exposure to Monetary Policy Vary over the Life Cycle?
A recent study by Feiveson et al. 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.
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 Auclert 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).
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.
August 10, 2021
Do Rising Retirements during COVID Reflect Demographic Trends?
Data from the Current Population Survey tell us that, in the second quarter of 2019, 47.8 percent of those aged 55 and older said they didn't want a job because they were retired. By the second quarter of 2021, that share had risen more than 2 percentage points, to 49.9 percent, which is an increase of around 2 million retirees over what would have been expected if the retirement rate for those aged 55 and older had not changed.
These data raise the question of how much of the increase in retirements is over and above what would have been expected based on the ongoing aging of the baby boomer generation—the movement of more people into ages that are more likely to retire. In other words, did the COVID-19 pandemic contribute to an increase in retirements?
The Atlanta Fed's Labor Force Participation Dynamics tool, which we recently updated with data through the second quarter of 2021, allows us to investigate the source of the change in retirement. The increase in the overall retirement rate for those aged 55 and older can be broken into two parts. The first one is the part due to a shift in the distribution of age, sex, race/ethnicity, and educational attainment toward demographics with higher retirement rates. For example, a 65-year-old is more likely to retire than a 63-year-old, and we have more 65-year-old people today than two years ago. The second part is the increase due to higher retirement rates within the age, sex, race/ethnicity, and educational attainment groups.
To illustrate how the decomposition works, let's look at just two factors: age and sex. The following table shows the average retirement rates of men and women aged 55 and older by five-year age groups for the second quarters of 2019 and 2021. The numbers in parentheses show the share of the 55-and-older population in each age/gender group. For example, in the second quarter of 2019, 51.5 percent of women 55 and older were retired, and women made up 53.7 percent of the overall population of people 55 and older.
Looking down the columns of the table, notice that for both men and women, retirement rates are much higher for those in their 70s than in their 60s—and much higher for those in their 60s than in their 50s. This matters because, comparing 2021 with 2019, the share of the population in the older of the age groups for both men and women has increased. This fact alone puts upward pressure on the overall retirement rate for the 55-and-older population between 2019 and 2021.
But in addition to an aging 55-and-older population, the table above shows that retirement rates have also increased within the age/gender groups. Looking across the age rows of the table we see that the retirement rate for each age/gender group is higher in 2021 than in 2019. So not only are there more women and men of ages that have higher retirement rates, the retirement rates themselves have increased.
Chart 1 displays the results of the complete decomposition. The blue line is year-over-year change in the retirement rate of those 55 and older going back to the second quarter of 2006. The orange bars represent the part of the change in the overall retirement rate accounted for by changes in the demographic composition (the distribution of age, sex, race/ethnicity, and educational attainment), while the green bars depict the contribution to the overall change from changes in retirement rates within the demographic groups (labeled as behavior).
Notice that up until 2020, behavioral changes were generally contributing to lowering the overall retirement rate of the 55-and-older population. The loss of retirement savings during the Great Recession was arguably an important factor in reducing the ability to retire during that period. At the same time, demographics were also putting mild downward pressure on retirement, with the leading edge of the baby boomer generation still within an age range with relatively low retirement rates. However, since 2013 underlying demographic shifts have been putting upward pressure on the overall retirement rate.
During the COVID-19 pandemic, demographic and behavioral factors appear to have contributed roughly equally to the rise in retirements. Perhaps, for some baby boomers who were already likely to retire within a few years, the pandemic created an incentive to retire sooner than they might have otherwise. A look at the Federal Reserve's Distributional Financial Accounts Overview shows that the annual growth in the net worth of those 55 and older now puts them, on average, in a much better financial position to retire than was the case during the Great Recession (see chart 2).
The ongoing aging of the baby boomer generation will continue to put upward pressure on the retirement rate over the next few years. How much the recent behavioral change will persist is much less clear, and a great deal will undoubtedly depend on the future path of the pandemic and the financial resources of older Americans. The Atlanta Fed's Labor Force Participation Dynamics tool will allow you to investigate the changes for yourself—with data for the third quarter of 2021 available sometime in October—but I'll be back to discuss my own findings with you here.
July 15, 2021
Onboarding Remote Workers: A Hassle? Maybe. A Barrier? No.
As the need for social distancing recedes and government restrictions ease, most people look to regain some notion of normalcy in their day-to-day lives. At the same time, many workers have come to like their office away from the office. And the COVID work-from-home experiment has gone well enough for it to stick around, possibly in a hybrid form. Those are key conclusions in a recent study (by three of this post's authors) titled "Why Working from Home Will Stick."
One frequent concern we hear about remote work is the challenge of hiring and onboarding new employees who rarely—or even never—set foot on the employer's worksite. Yet our evidence suggests that these challenges are modest and aren't a big barrier to finding, onboarding, and integrating new employees.
During the past two months, we asked executives participating in our Survey of Business Uncertainty (SBU) about their experiences hiring remote workers and integrating them into their organizations (see the three charts below). The share of new hires who work almost entirely from home (rarely or never stepping onto business premises) was 15.8 percent, a figure nearly identical to the share of all paid workdays performed at home in earlier pandemic-era snapshots from the SBU. Moreover, the share of new hires varies across industries, just as we'd expect based on research by Jonathan Dingel and Brent Neiman that flags which jobs can be performed remotely. The Survey of Working Arrangements and Attitudes (whose data underpin our aforementioned recent study, "Why Working from Home Will Stick") also suggests that new hires are at least as likely to work from home as the general population.
So as we see, new hires are working remotely to the same extent, and in the same proportion across industries, as incumbent staff. These findings suggest that integrating and training new remote workers isn't a big barrier to hiring. But it must be a pain, right? Otherwise, why all the fuss?
And here, the unanimity dissipates. Of firms with new remote workers, 60 percent say the integration process is more challenging. On average, SBU respondents say it takes about a month or so longer to fully integrate remote-only employees, though the spread about that average is pretty wide—ranging from six weeks less to six months longer.
If you're at a firm that finds it challenging to onboard remote employees, perhaps you'll find some solace in the fact that most of your new staff appear not to notice. In the The Survey of Working Arrangements and Attitudes, 42 percent of workers hired into fully remote positions during the pandemic say that adapting to their new jobs has been neither easier nor harder than adapting to in-office jobs before the pandemic. The other 58 percent are distributed similarly over "easier" and "harder" (see the chart).
Stepping back and taking a broader look, many observers wonder why aggregate U.S. employment remains 6.8 million below its prepandemic peak, despite record numbers of job openings. On the list of potential reasons for this shortfall—such as lingering concerns about the virus, generous unemployment benefits, inadequate childcare options, and more—it appears you can cross off the difficulty of onboarding and integrating remote workers.
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