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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.

Authors for Policy Hub: Macroblog are Dave Altig, John Robertson, and other Atlanta Fed economists and researchers.

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January 12, 2022

Hybrid Working Arrangements: Who Decides?

Even after—or should we say "if"?—working from home eventually becomes less of a necessity, it's likely to stick around in a hybrid form, with some working days performed at home and some in the office. (This recent study Adobe PDF file formatOff-site link, coauthored by three of this post's authors, also makes this case.) Still, much remains undetermined about how that hybrid arrangement will work and who at the firm decides how many and which days employers will require workers to be onsite.

To shed some light on how hybrid working arrangements are working, we posed a few special questions to executives in our Survey of Business Uncertainty (SBU) last July and again last month (December 2021). Specifically, we asked, "Does your firm currently have employees who work remotely?" If they said yes, we followed that up with the question, "Who decides which days and how many days employees work remotely?" Respondents selected options ranging from fully decentralized to company-determined schedules. (The results between the July and December surveys were nearly identical, so we've combined them here to simplify this discussion.) Among firms in our panel, 53 percent have employees who work remotely, and their survey responses are interesting (see chart 1).

Chart 1: Firms are split on who determines hybrid work

As you can see, respondent firms are roughly split, with about 30 percent leaving the decisions up to their employees, 30 percent giving teams (or team leads) decision rights, and nearly 40 percent indicating the decision on how many and which days employees will be remote resides at the company (management) level.

To dig into these results a bit further, we looked at who makes these decisions over working arrangements by industry and firm size. Given the differences across the industrial sector's ability to work from home (see research by Jonathan Dingel and Brent NeimanOff-site link), we find it somewhat surprising that little difference exists across industries about whether the decision to work remotely is fully decentralized, made at the team level, or determined by the company (see chart 2).

Chart 2: At smaller firms, employees themselves are given the ability to decide where to work

However, we see a stark difference when comparing these decision rights by firm size. More than half of the smallest firms in our panel (those with fewer than 25 employees) allow the employees to decide how and when to come into the office, compared to just 10 percent of larger firms (with 250 employees or more). Instead, these larger firms have left decisions about remote work with the team. Although that's certainly far from a rigid, top-down approach, it can suggest a need for coordination among teams, and this variation highlights remote work's big trade-off: balancing employee choice with the coordination that work life sometimes requires.

Allowing employees to choose their teleworking days has the benefit of flexibility, letting them to plan their work schedules around some nonwork commitments. But it has the cost of limiting face-to-face meetings, as on any given day of the week larger teams will likely find one or more members working remotely, which forces meetings partly or completely online. In our discussions with larger firms, they highlight the importance of face-to-face interactions and so have been promoting team- or company-level coordination. Interestingly, smaller firms appear to be walking another path: providing greater individual choice. Which one of these approaches becomes prevalent should become clear by the summer, when employees can (hopefully) return to the office. Though the future of office work appears to be a hybrid one, the form of decision making that will dominate that future has yet to be determined.


December 2, 2021

Atlanta Fed Conference Investigates Inequalities in the Financial System

A commitment to an inclusive society also means a commitment to an inclusive economy. Such an economy would represent a rebuke of systemic racism and other exclusionary structures. It would represent a true embrace of the principles that all are created equal and should enjoy unburdened life, liberty, and the pursuit of happiness.

— Raphael Bostic, president and CEO of the Federal Reserve Bank of Atlanta, from the essay A Moral Imperative and Economic Imperative to End Racism

Despite the nation's progress toward a more inclusive economy over the last half century, vestiges of structural discrimination are still entrenched in US institutions, and often manifest themselves in the form of disparities in economic outcomes. To promote the topic of racial equality, the Atlanta Fed has partnered with other organizations, cohosting, hosting, or participating in several recent events, including the Atlanta Fed-Princeton University conference on Racial Justice and Finance in September 2020 and the Racism and the Economy webinar series, which began in 2020 and will conclude in early 2022.

On October 14–15, 2021, the Atlanta Fed kicked off the inaugural conference on Racial Inequality and Disparities in Financial Markets to further promote research on inequalities in the financial system. The conference, which was virtual, included presentations and discussions of six papers on racial or gender disparities in various financial markets, including credit markets for mortgages and automobiles, labor markets, and the academic finance profession.

Paula Tkac, associate director of the Atlanta Fed's Research Department, gave the opening remarks. She began by describing how researchers face a dearth of high-quality data in this area, but shared she is hopeful the increased interest in research on racial inequality will spur the effort needed to bring together better data sets. Tkac then called for "a deeper understanding of the 'whys', and insight into potential paths forward toward full economic inclusion" as research progresses. She stressed that this research is crucial in the context of the Fed's monetary policy mission, as a fuller understanding of the barriers stopping individuals from participating to their full potential in labor and financial markets is necessary for good policymaking. Tkac concluded her opening remarks with a quote from Atlanta Fed president Raphael Bostic from last year's Racial Justice and Finance conference:

The influence of race is multidimensional and persists over time. We must look "under the hood" at our institutions to see and truly understand their design and its implications...In your research, think about how you ask questions, particularly how you incorporate historical and institutional realities into your research designs. Examine the role played by institutions and structures and explore how the burdens they impart have contributed to inequities that are still with us...With such an understanding, we can then find more creative and accurate ways to incorporate race into our models, estimation approaches, and narratives. This, I hope, will yield better insights and result in a set of policy prescriptions that can truly create meaningful and lasting change.

Three papers in the conference examined racial disparities in mortgage lending. In "Racial Disparities in Mortgage Lending: New Evidence Based on Processing Time," authors Bin Wei (Atlanta Fed) and Feng Zhao (University of Texas–Dallas) looked at racial disparities in mortgage processing time, which is the time needed for a loan to be processed. Looking at the period prior to the 2008 global financial crisis, they found that Black borrowers experienced significantly longer processing times (about five days more) than did White borrowers for mortgages securitized by the government-sponsored enterprises. In contrast, processing times for the privately securitized mortgages were much shorter for Black borrowers, driven by the fact that Black borrowers were more likely to use nonstandard mortgage financing channels where fast-processing lenders and loan products proliferate.

In the second paper focusing on the mortgage market, "Mortgage Prepayment, Race and Monetary Policy," Kris Gerardi (Atlanta Fed), Paul Willen (Boston Fed), and David Zhang (Harvard) found that Black and Hispanic borrowers pay significantly higher mortgage interest rates than do White and Asian borrowers, and that the primary reason for the large gap in rates is due to differences in refinancing behavior. Minority borrowers are significantly less likely to have refinanced their loans in response to declines in mortgage interest rates, and as a result, they benefited less from lower interest rates.

In the third mortgage paper, "Mortgage Policies and Their Effects on Racial Segregation and Upward Mobility," Nirupama Kulkarni (Centre for Advanced Financial Research and Learning) and Ulrike Malmendier (University of California–Berkeley) noted that housing policies aimed at reducing racial disparities in home ownership can have unintended adverse consequences. Exploiting variation in the ease of mortgage financing created by the 1992 GSE Act, which explicitly targeted underserved neighborhoods, they showed that, while Black home ownership increased in targeted neighborhoods, white families moved out. As a result, segregation increased and the upward mobility of Black children deteriorated. They pointed to declining house prices, reduced education spending, and lower school quality in targeted areas as plausible channels for the decline in upward mobility.

The paper "Testing Models of Economic Discrimination Using the Discretionary Markup of Indirect Auto Loan" by Jonathan Lanning (Philadelphia Fed) examined racial discrimination in auto lending. Lanning presented some compelling empirical evidence for taste-based discrimination in the auto loan market. Auto loans are typically the largest consumer loans after mortgages. More than 80 percent of these loans are indirect, meaning they are arranged by a dealer on the borrower's behalf. The dealer has the discretion to mark up an indirect auto loan by as much as 250 basis points over the rate at which the lender is willing to extend credit. In exchange for the rate increase, the dealer receives additional compensation from the lender. Lanning found that the average markup for Black borrowers is about 14 basis points higher than for White borrowers. More importantly, the racial disparity in the markup is shown to be consistent with the taste-based discrimination theory developed by Becker (1957).

The final two papers in the conference examined the gender gap in the academic finance profession and in the labor market. In the paper "Diversity, Inclusion, and the Dissemination of Ideas: Evidence from the Academic Finance Profession," authors Renee Adams (University of Oxford) and Michelle Lowry (Drexel University) examined how diversity relates to variation in career outcomes within the academic finance profession. They conducted their research based on a survey they administered to current and recent past members of the American Finance Association (AFA) on the professional climate in the field of finance. The survey had 1,628 respondents, about 30 percent of them female. Survey results suggest that female finance faculty members in general have a lower satisfaction level than do their male counterparts. The authors found that gender discrimination is one of the most important causes for this discrepancy.

In the final paper, "Hidden Performance: Salary History Bans and Gender Pay Gap," Jesse Davis (University of North Carolina), Paige Ouimet (University of North Carolina) and Xinxin Wang (University of California–Los Angeles) looked at how salary history bans affected the wage gap between male and female workers. These bans prevent employers from requesting and using a job candidate's prior salary information. Many states have adopted these bans with the explicit intent of reducing the gender pay gap. The idea is that historical pay discrimination against women is propagated if employers are allowed to use past salary information to set pay for new female hires. Presumably, imposing bans should prevent the perpetuation of past discrimination. However, the bans have the additional, negative consequence of preventing potential employers from observing a signal of worker productivity. So the overall effect of salary history bans on the gender gap is unclear. Using a large-panel data set of disaggregated wages covering all public sector employees in 36 states, the authors do not find evidence that salary history bans significantly decrease the gender pay gap.

All in all, the conference proved to be a memorable event. Papers incorporated high-quality micro data and state-of-the-art empirical methods that uncovered evidence of racial and gender inequalities across a variety of financial markets. The paper presentations and thoughtful discussant presentations spurred a lot of dialogue and debate around the nature of the disparities and their implications for future policy. We hope to hold similar conferences in the future, perhaps on an annual or biennial frequency, to continue to promote and raise awareness of this topic.

November 10, 2021

Compositional Distortions to a Measure of Wage Growth during the Pandemic

Measures of year-over-year growth in wages (or hourly earnings) used in economic analysis often tell a fairly consistent story. For example, chart 1 makes it apparent that wage growth was generally higher heading into the 2007–09 recession than heading out of it and that wage growth stayed low for the first half of the 2010s before trending up moderately over the second half of the decade. However, with the onset of the COVID-19 pandemic, growth in average hourly earnings from the US Bureau of Labor Statistics' (BLS) establishment survey (the blue line in the chart) deviated substantially from the other two series depicted.

Chart 1: Wage growth, 1997-2021

The leisure and hospitality industry provides a useful illustration of why the establishment survey measure of hourly earnings growth spiked in March and April of last year. In February 2020, average hourly earnings for production and nonsupervisory workersOff-site link in leisure and hospitality were 40 percent lower than they were for all private nonfarm payroll workers. And although the leisure and hospitality industry accounted for just under 14 percent of private nonfarm production and nonsupervisory jobs in February 2020, it accounted for nearly 40 percent of the lost private production and nonsupervisory jobs in the subsequent two months. The 4.5 percentage point increase from February 2020 to April 2020 in the blue line in chart 1 falls by 1.9 percentage points if we remove leisure and hospitality from the calculation.

The August 2020 FRBSF Economic Letter—aptly titled "The Illusion of Wage Growth"—by Erin E. Crust, Mary C. Daly, and Bart Hobijn shows that restricting the sample to people employed in the second quarters of 2019 and 2020 reduced growth in median usual weekly earnings over that period by nearly 8 percentage points from the published rate of 10.4 percent. The Atlanta Fed's Wage Growth Tracker, which uses the same type of restriction, and the Employment Cost Index (ECI), which controls for employment share changes among industries and occupationsOff-site link , were not subject to the illusion of wage growth shown by the blue line in chart 1.

Unfortunately, the adjustments used in the Wage Growth Tracker and the ECI are not feasible with the establishment survey measure of hourly earnings because that measure is constructed solely from the information in each month's employment report. As an alternative, Goldman Sachs provides an adjustmentOff-site link for what it terms the composition bias in the establishment survey measure. This adjustment keeps hours worked fixed at their year-ago level in the wage calculation using industry-level data.

I've written an appendix Adobe PDF file format that provides the details of a related approach for calculating a composition-adjustment term from the monthly establishment survey data. Besides adjusting for industry composition, this approach also adjusts for types of workers: production and nonsupervisory workers versus nonproduction/supervisory employees. The appendix also shows that adjusting for worker type and industry rather than industry alone materially affects the composition-adjusted measure of average hourly earnings for April 2020. It also shows that—unlike measures from the BLSOff-site link and the San Francisco FedOff-site link, which control for educational attainment—the measure of labor composition (sometimes called labor quality Adobe PDF file format) constructed with only establishment survey data has not trended up much since the mid-2000s.

The basic intuition underlying the approach described in the appendix is that, apart from some trivial rounding error, the BLS measure of aggregate weekly payrollsOff-site link is equal to the product of average hourly earnings and aggregate weekly hours worked. So, in much the same way that we can express nominal gross domestic product (GDP) as the product of real chain-weighted GDP and a GDP price deflator, aggregate weekly payrolls can also be decomposed as the product of composition-adjusted measures of wages and hours worked. This approach maintains the equality with aggregate payrolls since the composition adjustments to hourly earnings and hours worked offset each other exactly.

Chart 2 shows the results of adjusting for changes in both industry and worker type for measures of average hourly earnings growth and aggregate hours worked during the pandemic. Adjusting for composition makes average hourly earnings growth during the pandemic more like the ECI and Wage Growth Tracker measures, but, nevertheless, some important differences exist. Unlike the composition-adjusted measure of nominal wage growth, the ECI and Wage Growth Tracker measures languished in the second half of 2020 and surged in their most recent readings. Composition-adjusted hourly earnings grew 1.1 percent from March 2020 to April 2020, which is less than the 4.6 percent spike in the unadjusted measure but still strong enough to suggest that the adjustments made here still miss some meaningful changes in worker composition in the earliest months of the pandemic.

Chart 2:  Average hourly earnings and aggregate hours worked during the pandemic

As you look at this chart, note that the adjustment is constructed using wage and hours data for 253 industry groups, all but 10 of which are further split into production and nonsupervisory and nonproduction/supervisory employee groups.

The right panel in chart 2 shows private nonfarm payroll employment alongside the standard measures of aggregate hours worked and a measure adjusted for industry and worker-type composition. In October, private nonfarm payroll employment, hours worked, and composition-adjusted hours worked were 2.5, 1.7, and 1.2 percentage points, respectively, below their February 2020 levels.

The composition-adjustment factor (industry by production/supervisory worker employment type) as well as the associated measures of composition-adjusted hours worked and hourly earnings are available here Microsoft Excel file. Future updates of this Excel file will also be available at this link.

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.

Figure 1: Market Expectations for the Fed Funds Rate Path

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.

Figure 2: Change in the Daily 10-Year US Treasury Rate

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.

Figure 3: Market Expectations for the Future Fed Funds Rate Path

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.