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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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June 23, 2022

Financial Markets Conference 2022: Exploring the Financial Sector

Note: This is the second of two posts discussing the Atlanta Fed's 2022 Financial Markets Conference. You can read the first part of the conference summary here.

The Atlanta Fed's 2022 Financial Markets Conference, A New Era of Financial Innovation and Disruption: Challenges and Opportunities, featured policy panels, academic paper presentations, and keynote speakers exploring various developments having a significant impact on the financial system. This Policy Hub: Macroblog post covers some of the key takeaways from the discussion of three challenges facing the financial sector: central bank digital currency (CBDC); environmental, social and corporate governance investing; and cybersecurity. All three discussions highlighted how the answers to some seemingly straightforward questions involve a host of complex considerations. (My companion Policy Hub: Macroblog post focused on discussions of the current monetary policy environment, with a focus on shrinking the Fed's balance sheet.) More information on all of the sessions is available at the conference agenda page, which has links to the various sessions' videos, papers, and other presentations.

Which CBDC, If Any, Is Right for the United States?
The issue of whether the central bank should issue a digital currency, and what form such a CBDC should take, is a topic that central banks around the world have been studying with varying degrees of interest, sparked in part by the development of cryptocurrencies. The intensity of that interest increased dramatically with the announcement by Facebook, now renamed Meta, that it was developing a stablecoin called Libra, later changed to Diem. (A stablecoin is a currency that maintains a fixed value relative to some other asset, especially a sovereign currency such as the U.S. dollar.) Meta has since stopped development of Diem and sold its assets. However, the questions surrounding a CBDC remain. The FMC's CBDC panel video fileOff-site link pointed out that this seemingly simple question involves a variety of deep, complex issues for policymakers to consider.

The panel was led off by Nellie Liang, undersecretary for domestic finance at the US Department of the Treasury, who provided broad context for the discussion. Her remarks Adobe PDF file format and slides Adobe PDF file format discussed President Biden's executive order for government departments to study the issues associated with digital assets.

Afterward, Charles Kahn, professor emeritus at the University of Illinois, presented Adobe PDF file format his paper Adobe PDF file format on CBDC. The paper makes the important point that a wide variety of choices need be made in the design of a CBDC and that these decisions should be based the intended benefits from adopting a CBDC. Kahn noted that although a CBDC may have many benefits over the existing system, in many cases it is not clear whether a CBDC is the right tool for obtaining the benefits. He then discussed CBDC developments in four of the CBDC leaders: Sweden, Canada, the Bahamas, and the People's Republic of China. These four countries have different priorities and have taken different paths. The two closest to the United States in terms of economic conditions, Sweden and Canada, have both done extensive work but neither has yet implemented a CBDC.

Following Kahn, David Mills from the Federal Reserve Board presented Adobe PDF file format the Federal Reserve's current thinking about CBDC. He noted that the Federal Reserve had recently published a discussion paper, "Money and Payments: The U.S. Dollar in the Age of Digital Transformation Adobe PDF file formatOff-site link," as a first step in fostering a broad and transparent public dialogue about CBDCs as well as a call for comments on a variety of CBDC-related issues. Mills indicated that the discussion paper raised a wide variety of issues that would need to be considered before adoption of a CBDC. Mills cited support for the US dollar's international role and promotion of financial inclusion as some potential benefits. On the other hand, he noted the potential risks it raises, including consumer privacy and financial system stability.

Paul Kupiec, from the American Enterprise Institute, provided a discussion and an article addressing several issues raised by a CBDC. He concluded that the United States should not adopt a CBDC. Kupiec argued that the issuance of such a currency would likely result in political pressures affecting the type of CBDC issued and, arguably more importantly, could create political pressure on the Fed to manage the rates paid on a CBDC for the benefit of holders rather than for monetary policy purposes. He also noted the risk that a CBDC could lead to a run on banks, with depositors shifting their funds to a CBDC. He offered as an alternative the development of private stablecoins and tokenized bank deposits that could be used for payments.

ESG and Money Management
There can be little doubt that interest in the topic of investing based on environmental, social, and corporate governance—commonly known as ESG—has exploded during the last decade. Participants at FMC considered some issues that ESG investing raises for money managers. The discussions highlighted that this seemingly simple concept in fact raises a variety of complex issues whose answers may legitimately vary among different money managers.

Dissecting Green Returns
Do ESG investors pay a financial penalty when accounting for nonfinancial considerations, or are they being rewarded through "doing well by doing good"? In a session moderated by Paula Tkac of the Atlanta Fed, a paper titled "Dissecting Green ReturnsOff-site link" and presented Adobe PDF file format by University of Chicago professor Lubos Pastor addressed these questions. Specifically, Pastor and his coauthors Rob Stambaugh and Luke Taylor looked at the returns associated with environmentally sustainable investments. They note a conflict between theorists and practitioners. Investors, money managers, and some studies suggest that green stocks tend to produce higher returns. However, theory suggests that ex ante expected green returns should be lower than investments that are not environmentally sustainable. Thus, Lubos and his coauthors study the performance of green investments. They find that the past performance was superior, but that this performance reflects the unanticipated increases in the climate concerns of investors and consumers. The superior returns disappear after controlling for changes in investors' level of environmental interest. Their findings imply that the strong historical performance of green assets does not suggest that we should expect higher returns for green assets in the future.

Anna Pavlova, of the London Business School, began her discussion Adobe PDF file format by highlighting the theoretical reason that ESG investing should bring lower returns. She notes that one of the goals of ESG investing is to reduce the cost of capital to green firms, which requires that equilibrium returns on green stocks be below that of the returns on brown stocks (that is, stocks of companies with a large carbon footprint). That said, she also observed that there are a variety of ratings of overall ESG performance and for the environmental component. However, the correlations of these ratings are rather low and sometimes negative for a variety of reasons. Pavlova pointed to a paperOff-site link she coauthored that offers a possible solution for the variation in ratings.

The panel discussion video fileOff-site link on ESG investing, moderated by S.P. Kothari from the Massachusetts Institute of Technology, delved more deeply into the issues associated with this type of investing. Laura Starks from the University of Texas presented Adobe PDF file format a paper Adobe PDF file format that raised a number of points on ESG investing. For example, she noted that the number of institutional investors, and the amount of institutionally managed funds devoted to ESG, have grown substantially.

However, Starks devoted a large portion of her presentation to the difference between ESG values (or values-based) investing versus ESG value investing. Some ESG investors avoid supporting (or investing in) companies that engage in activities that violate the ESG principles. Alternatively, some ESG values investors focus on affecting firms' ESG performance, which can mean limiting their supply of capital to firms that are not strong on ESG or through engagement with the management of firms that are not strong on ESG.

In contrast, Starks said that an ESG value investor approaches ESG from the perspective of the value of the firm as an investment. Thus, an ESG value investor is concerned that firms' poor ESG records are likely to have lower earnings or higher risk in the future, or even both. However, similar to ESG values investors, a value investor can implement the ESG value by avoiding firms with poor records, or by engaging with firms' managers in an attempt to improve the firm's ESG performance.

Lukasz Pomorski, head of ESG research at AQR Capital Management, built on Starks's discussion of ESG value versus values investing. He notes that up to a point, ESG can be valuable for risk management, but at a certain point it becomes a constraint that can have an adverse impact on a portfolio's financial performance. In response to a question from Kothari, Pomorski explained that binding restrictions not only affect portfolio diversification but also the ability of active money managers to exploit their skill. A money manager may have above-average ability to evaluate firms in some disfavored industries, but an excluded industry precludes that money manager from using that skill to benefit investors.

Pomorski also addressed a point that Starks's presentation touched on. Firms can be influenced in two ways: the cost of capital and voting stock ownership. Pomorski emphasized that these mechanisms sit in opposition to each other. The only way to raise the cost of capital is to sell the stock, but only shareholders own votes.

The final panelist, Mikhaelle Schiappacasse from Dechert LLP, reviewed the evolving ESG rules in Europe, especially those related to green finance. She observed that the European Commission has set a goal of net zero carbon emissions by 2050 and is intent on using regulations on investment to support that goal. Thus, the European rules are pushing firms and investors to divest activities with big carbon footprints and invest in those with smaller carbon footprints. However, Schiappacasse also discussed some complications in implementing these goals. One major issue is often called "greenwashing"—firms and investment managers creating only the appearance, but not the reality, of being green. Another complication she discussed is that ESG money managers can get a good rating only by investing in green assets, so they can't work with brown firms in an attempt to shrink their carbon footprint.

Cyber Risk in the Financial Sector
Finance and cyber risk management often have a hard time understanding each other, according to Patricia Mosser of Columbia University, the moderator of the FMC's cyber risk panel video fileOff-site link. In part, the lack of understanding arises from having different goals. Cyber risk is about avoiding adverse shocks, but adverse shocks are unavoidable in finance, so finance's goal is resiliency to those shocks. Another important difference is the nature of the shocks. Cyber risks, and their resulting theft or disruption, are the intention of whoever created them. Moreover, cyber shocks are not random but happen at moments of increased vulnerability. The occurrence and timing of financial shocks, on the other hand, are not intentional.

The presentation Adobe PDF file format , by Jason Healey from Columbia University, noted that the nature of the cybersecurity problem has increased considerably from the early years. Then, it was simply a matter of controlling access to the computer room, but more recently anyone connected to the internet is conceivably a threat. In some respects, however, the problem has not changed much since the mid-1990s, and many of the risks remain the same. What has changed is our capacity to respond. For example, in response to an audience question, Healey noted the development of cloud computing, which allows individual firms to reduce their individual exposure to cyber risk but at the expense of increased systemic risk by concentrating risk in relatively few vendors. Healy also listed the ways that cyber risks could become a financial issue, and then he listed some ways a cyber-driven financial issue could become a financial stability issue.

Stacey Schreft, of the US Department of Treasury's Office of Financial Research and currently on assignment at the Federal Reserve Board, discussed some issues and responses to cyber risk. Schreft's presentation Adobe PDF file format included figures showing some of the parties in the financial sector who are vulnerable to cyber risk and linking these to concerns about traditional financial sector risk. Among the responses she mentioned is the mitigation of vulnerabilities through the supervision of financial firms from the grassroots level. Another response has been increased collaboration across the financial sector, both within the United States and globally. These responses are attempts to strengthen vulnerabilities in the financial system's stability and improve the way we measure cyber risk.

June 3, 2022

Financial Markets Conference 2022: Normalizing the Fed's Balance Sheet

The Atlanta Fed's 2022 Financial Markets Conference (FMC), A New Era of Financial Innovation and Disruption: Challenges and Opportunities, featured policy panels, academic paper presentations, and keynote speakers who explored various developments having a significant impact on the financial system. This Policy Hub: Macroblog post offers some highlights from the conference keynote speakers as well as an academic paper and policy panel on normalizing the Fed's balance sheet. More information on all of the sessions is available on the conference agenda page, which has links to the various sessions' videos, papers, and presentation materials.

The four conference keynotes touched on a variety of issues. However, because of concern about inflation running well above the Fed's 2 percent target and about how the Fed will respond, a large part of the keynotes addressed monetary policy–related issues. The conference kicked off with a fireside chat video fileOff-site link featuring Roger W. Ferguson Jr. from the Council on Foreign Relations and Atlanta Fed president Raphael Bostic. President Bostic asked questions touching on all four of the policy themes, taking advantage of Ferguson's diverse background as a former Federal Reserve vice chair and chief executive officer of the Teachers Insurance and Annuity Association–College Retirement Equities Fund. In talking about current Fed policy, Ferguson referred to a survey he led of corporate CEOs that included a question effectively asking if the CEOs think the Fed will successfully bring inflation down. The answer that many CEOs gave is that so many factors and forces are at work they cannot be 100 percent certain the Fed can do this.

Harvard economics professor Kenneth Rogoff gave the Monday night keynote speech video fileOff-site link on the importance of the political economy. Most of Rogoff's speech recounted the economic and political conditions that led to the current relatively high inflation rates. He concluded by noting that if secular stagnation returns, the Fed could find inflation and market interest rates once again near zero. Should this happen, Rogoff argued, the Fed should be given the tools to drive nominal interest rates well below zero, if necessary, to counteract an economic downturn.

The Tuesday morning keynote video fileOff-site link , "Inflation and the Policy Response to Supply Shocks," was given by Charles Goodhart of the London School of Economics and Manoj Pradhan, founder of Talking Heads Macroeconomics. In their presentation Adobe PDF file format, they contended that the low inflation rate observed in recent decades was largely the result of a large increase in the labor supply, mainly due to China's integration into global markets. They noted, however, that this growing labor supply is in the process of reversing almost everywhere except in African countries. They contend that this reversal is likely to lead to slower growth, and potentially stagflation, in the medium run.

The final keynote was a fireside chat video fileOff-site link featuring Bostic taking questions from Julia Coronado of MacroPolicy Perspectives. Their chat devoted considerable attention to the current state of the economy, including both the recent negative shocks to supply and the potential for positive shocks to supply. One potential positive shock that Bostic discussed is the adoption of new productivity-enhancing technologies. Coronado pointed to a 2019 conference jointly held by the Federal Reserve Banks of Atlanta, Dallas, and Richmond titled Technology-Enabled Disruption: Implications for Business, Labor Markets, and Monetary PolicyOff-site link. Bostic indicated that at the time of this 2019 conference, monetary policymakers were concerned that technology was disrupting markets in a way that would be adverse to workers' human capital but the current problem is a shortage of workers.

Discussing the Federal Reserve's balance sheet
During and after the financial crisis, the Federal Reserve increased the size of its balance sheet from under $1 trillion to more than $4 trillion. These purchases, part of a process often called quantitative easing (QE), were initially intended to support financial market functioning and later intended to provide additional monetary policy accommodation because the Federal Reserve decided to keep its federal funds target rate above zero. As the economy strengthened in the late 2010s, the Fed reduced its balance sheet to just under $3 trillion in what was often referred to as quantitative tightening (QT). However, with the onset of the pandemic, the Federal Reserve once again expanded its balance sheet to more than $8 trillion in assets. As with the first rounds of QE in the wake of the financial crisis, the initial goal was to support financial market functioning but later focused more on providing monetary policy accommodation.

With a relatively low unemployment rate and inflation rates far above the Fed's 2 percent target, the current focus on policy has shifted to reducing monetary accommodation, which includes shrinking the Fed's balance sheet. Along with several keynote speeches touching on this issue, one of the academic papers presented at the 2022 FMC addressed one aspect of the reduction—the effect of QT on financial conditions—and one of the policy panels examined a variety of issues associated with shrinking the Fed's balance sheet.

Addressing the Unexpected Supply Effects of QE and QT
One challenge with analyzing the effect of monetary policy on the financial system is that market participants often partially anticipate policy moves, and market prices might at least partially incorporate the moves before a policy move is even announced. Stefania D'Amico of the Chicago Fed and her coauthor Tim Seida sought to get around this problem in the cases of QE and QT by looking at unexpected changes in the supply of Treasury securities at specific maturities in their paper "Unexpected Supply Effects of Quantitative Easing and Tightening Adobe PDF file format." D'Amico explained that their methodology sought to identify the effect of QE and of QT by looking for kinks in the yield curve arising from the unexpected changes in supply. They found that Treasury yields are more sensitive to QT surprises than to QE surprises. These effects do not diminish during periods of market calm amid economic expansion but are increased by interest rate uncertainty.

The discussion Adobe PDF file format by Morten Bech from the Bank for International Settlements highlighted the implications of the paper for both US domestic markets and the markets of other developed countries. In domestic terms, D'Amico's paper estimates the average supply effect of about 21 basis points (bp) per $1 trillion in balance sheet reduction, which increases to more than 70 bp when uncertainty about the 10-year Treasury rate is especially elevated. He noted that these estimates are consistent with Fed chair Jerome Powell's estimate of 25 bp per $1 trillion (which Powell says has "very wide error bands") and one market participant's range of 7 bp to 42 bp per $1 trillion. On the international front, Bech noted that the Bank of Japan and the European Central Bank have balance sheets that are significantly larger, as a proportion of their economies, than the Fed's. Thus, QE and potentially QT are not only a US issue but one relevant to other major central banks.

Examining Challenges during Balance Sheet Normalization
The panel discussion video fileOff-site link of monetary policy and normalizing—or shrinking—the Fed's balance sheet started with the panel's moderator, Vincent Reinhart from Dreyfus-Mellon, presenting Adobe PDF file format a review of the current situation. Reinhart noted that the unemployment rate had dropped to near prepandemic lows and that inflation rates were at 40-year highs, prompting the Federal Open Market Committee (FOMC) to announce plans to raise its federal funds target rate and reduce its securities holdings.

Cleveland Fed president Loretta Mester provided additional perspective on balance sheet normalization. She observed that the FOMC's planned reduction will reduce securities holdings faster than what occurred after the financial crisis, but that this faster reduction reflects the current strength of the economy and the high levels of inflation. She also observed that the FOMC's statement didn't address two items. First, the announced plan talks only about reduced reinvestment of maturing securities and does not address the issue of balance sheet sales. In the panel's question-and-answer period, Mester observed that such sales of agency securities may be necessary if the FOMC is to meet its goal of having its portfolio consist predominantly of Treasury securities. Second, the FOMC had not set a target for the size of its balance sheet, only that it intends to operate in an environment of ample reserves.

The next panelist, Seth Carpenter from Morgan Stanley, forecast that the peak of the fed funds rate would be about 3.25 percent and that it would take the Fed about two-and-a-half to three years to reach its balance sheet target. He added his belief that financial market prices (except for some credit markets) already reflect most of the effects of the announced changes. Carpenter also suggested that it was unlikely the Fed would engage in the sale of mortgage-backed securities, observing that housing is among the most cyclical of sectors and that tighter monetary policy would likely slow it down enough.

Brian Sack from D.E. Shaw noted that it is not often that a market participant announces a planned reduction in the size of its balance sheet by $2 billion to $3 billion, as the Fed has done. He said he anticipates that QT will likely have a moderate effect on market rates, perhaps raising the 10-year Treasury yield by somewhere in the range of 25 bp to 30 bp. However, Sack observed, the reduction in reserves could lead to a strain in funding markets, like that experienced in September 2019. Sack suggested that although pricing is a clearer signal than balance sheet size per se, the Fed should watch behavior in money markets closely to judge when reductions could lead to strain in the markets.

The last panelist was former Federal Reserve Board governor and current Harvard professor Jeremy Stein, who focused on QT's potential to cause strains in money markets and threaten financial stability. In his view, the villain is the minimum leverage ratio requirement (the minimum ratio of capital to total assets a given bank must hold) imposed on banks by their regulators and especially its effects on the largest banks, which are also critical participants in money markets. Stein noted that the problem with the leverage ratio is that it does not account for the risks different types of assets pose. In Stein's telling, the ratio effectively penalizes banks' holdings of low-risk assets, especially the holding of reserves. Ideally, he said, the risk-based capital ratio that does not impose a similar penalty on low-risk assets would be binding, but he thinks that regulatory policy is unlikely to be changed in such a way that the risk-based ratio would become binding. Thus, Stein suggested that the Fed narrow the gap between the interest paid on bank reserves and the rate with which the Fed engages in reverse repurchase agreements with some money funds and other money managers, which would result in banks holding lower reserves and thereby relaxing the constraint imposed by the leverage ratio.

Please check Policy Hub: Macroblog soon to read my post summarizing the rest of the 2022 FMC. I will highlight three other important issues discussed there: central bank digital currency; environmental, social, and corporate governance (commonly known as ESG) investing; and cybersecurity.

May 19, 2022

An Evaluation of GDP Nowcasts during the Pandemic

On April 28, the US Bureau of Economic Analysis reported that real gross domestic product (GDP) contracted an annualized rate of 1.4 percent last quarter. This decline "surprised" GDPNow, the Atlanta Fed's GDP tracking model, which had projected a 0.4 percentage point growth rate the day before the official release. Professional forecasters, who generally expected a rate around 1 percent based on economist surveys from ReutersOff-site link and the Wall Street Journal (WSJ)Off-site link, also turned out to be overly optimistic.

The lines in chart 1 represent errors for final forecasts of first-release estimates of real GDP growth from the WSJ Economic Forecasting SurveyOff-site link and GDPNow. In the five-and-a-half years before the pandemic, the WSJ survey and GDPNow both had average absolute forecast errors—that is, without regard to sign, or mean absolute errors (MAEs)Off-site link—of about 0.5 percentage points. Since then, the MAEs have been 1.7 percent and 1.9 percent, respectively. The stacked bars in the chart represent a decomposition of the GDPNow line into forecast errors of subcomponent contributions to GDP growth. The chart makes it evident that the size of the bars has fallen since 2020, but continues to be larger than before the pandemic. Even GDPNow's relatively accurate forecasts for the second and fourth quarters of 2021 were largely the result of the positive and negative subcomponent errors fortuitously offsetting each other. GDPNow's error last quarter was largely concentrated in net exports. The model's final forecast of the growth rate of real final sales to private domestic purchasers—which excludes inventories and government spending in addition to net exports and has been shown to be a better leading indicator of one-quarter-ahead GDP growth than GDP growth itself isOff-site link—was only 0.3 percentage points below the initial estimate of 3.7 percent.

Chart 1 of 4: Errors of Final GDPNow Forecast of Subcomponent Contributions to Real GDP Growth

The deterioration in GDP forecasting accuracy during the pandemic has not been isolated to the shortest horizon projections. Chart 2 shows MAEs for roughly 75-day-ahead forecasts of growth rates of real GDP and its subcomponents (as well as net exports and inventory investment contributions to growth) from both GDPNow and the Philadelphia Fed's Survey of Professional ForecastersOff-site link (SPF). The decline in forecast accuracy for the SPF has been similar to the decline for GDPNow across subcomponents, with the exception of the state and local (S&L) government spending subcomponent, where the deterioration for GDPNow has been much starker. A Macroblog post from a year ago discussed the reasons for this.

Chart 2 of 4: 75-Day-Ahead GDP Subcomponent Forecast Errors for GDPNow and Survey of Professional Forecasters Median Projections

The left-hand panel of chart 3 shows the MAEs for subcomponent contributions to GDP growth prior to the pandemic, and the right-hand panel shows contribution MAEs during the pandemic. Because the errors have been so much larger during the pandemic, the vertical axis is scaled to be six times larger in the right-hand panel than in the left-hand panel.

To show how forecast accuracy has evolved over a typical quarter, the figures in both panels of the charts begin with the MAE after the initial (roughly 90-day ahead) GDPNow forecast, end with the final GDPNow forecast, and use up to five other forecasts following particular data releases in between. Three of these releases are from the Institute of Supply Management's Manufacturing ISM Report On BusinessOff-site link (its manufacturing report, specifically) for each of the three months of the quarter being forecasted, and the other two correspond to the personal income and outlaysOff-site link releases from the US Bureau of Economic Analysis for the first two months of the quarter.

Chart 3 of 4:  GDPNow Subcomponent Contribution to Growth Average Absolute Forecast Errors:   Prepandemic Era (Left Chart) and Pandemic Era (Right Chart)

Notice that although both panels show the subcomponent projections generally becoming more accurate over time, the rank ordering of the subcomponent accuracy has changed in some nontrivial ways during the pandemic. In particular, even though personal consumption expenditures (PCE) on services account for 45 percent of nominal GDP, it was consistently one of the smaller sources of error prior to the pandemic. But during the pandemic, it has been one of the largest. Government spending was also one of the smaller sources of error prior to the pandemic and has remained that way during the early part of pandemic quarters. But this decade, the government spending forecasts have not tended to become more accurate as quarters have progressed, so that recently, just prior to the GDP release, government spending has been nearly as large a source of error as services PCE.

In the GDPNow model, the forecasts of government spending, particularly S&L government sales to other sectors, were distorted by the large swings in the second and third quarters of 2020. This documentation on recent changes made to the GDPNow model Adobe PDF file format describes the changes made to keep these types of distortions to a minimum in the future, which is relevant to the data releases used in chart 3. Generally, a few days after the release of personal income and outlays data, the ISM releases its manufacturing data for the subsequent month, providing one of the first data snapshots for that month. The ISM data for this month are used to estimate the model's factor, that then feeds through to the forecasting equations for much of the yet-to-be-released monthly GDP source data.

Chart 4 shows the MAE from the five quarters beginning in the first quarter of 2021 for real GDP growth and the S&L government contribution to GDP growth. The dashed lines are for the version of GDPNow that had been in use at the time, and the solid lines are for the "COVID-adjusted" model in use since the first quarter of 2022. (The same data releases used in chart 3 are used here.) The modified model shows a clear improvement in the forecasts of S&L government spending. Moreover, forecast accuracy no longer deteriorates following the release of the first-month and second-month ISM manufacturing releases. After the second personal income and outlays report of the quarter—and the final one before the initial GDP report—the accuracy and forecast values of the two models became more similar.

Chart 4 of 4:  Subcomponent Contribution to Growth Average Absolute Forecast Errors 2021Q-2022Q1: Standard and

Although this is good news for improving the forecast accuracy of GDPNow, it is not clear whether near-term forecasts of GDP growth will continue to be less accurate than they were in the decade leading up to the pandemic. Ongoing geopolitical and economic uncertainties remain elevated, which could continue to have a negative impact on forecast accuracy for some time to come.

March 1, 2022

Assessing Recent Labor Market Improvement

The US Bureau of Labor Statistics' (BLS) labor report for January 2022Off-site link showed that the overall labor force participation (LFP) rate increased 0.3 percentage points from December's published level. This increase put the LFP rate at its highest level since the pandemic began and, taken at face value, might make you think that the labor supply problems that have plagued the recovery from the COVID-19 pandemic were easing.

However, it turns out that this jump in the LFP rate was entirely an artifact of the BLS incorporating population control adjustments into the January labor force data. These are independent estimates of the civilian noninstitutionalized population ages 16 and older used to make sure that labor force statistics computed from the Current Population Survey (CPS) accurately reflect the population and are incorporated into the CPS data each January. The latest adjustments are the first to use information from the 2020 decennial census Adobe PDF file formatOff-site link, and showed that the US population was almost 1 million larger than the published estimate for December 2021. By itself, a jump in the size of the population isn't an issue for comparing LFP rates over time. But the new population adjustments also showed that the population was considerably younger than previously estimated (in particular, the share of the population aged 70 and older was smaller). This shift in the age distribution is important because a younger population generally means a higher rate of participation in the labor force.

The BLS does not revise the historical data when new population control adjustments are incorporated into labor statistics. But it did report Adobe PDF file formatOff-site link that the population control adjustment would have lifted the December 2021 LFP rate for the population ages 16 and older by 0.3 percentage points if it had revised the December data. This increase is the same as the increase in the published LFP rate from December to January. In other words, the December-to-January increase in the published LFP rate didn't indicate an improvement in labor force participation at all.

Clearly the latest population control adjustments complicate comparison of 2022 LFP rates to earlier periods. To construct historical LFP rate series that are more comparable over time, we implemented a simple smoothing method the BLS used previously to account for annual population control adjustments (described here Adobe PDF file formatOff-site link). This method essentially distributes the level shifts that result from the population control adjustments back over the relevant historical period for each series. To account for the effects of adjustments (made between the decennial census) to the census 2010 population base that were made in January 2013–January 2021, we first smoothed data for January 2012 to December 2020. Then we smoothed the data for January 2012 to December 2021 to account for the effects of the 2020 census population control adjustment introduced in January 2022. We applied the method separately labor force participation rates for the population ages 16 and older, as well as populations ages 16–24, 25–54, and 55 and older. You can see these series in this spreadsheetMicrosoft Excel file.

Chart 1 plots the published and smoothed seasonally adjusted LFP rate series for the population aged 16 and older. Notice that the smoothing method results in a gradually increasing upward shift to the LFP rate over the 10-year period, culminating with the December 2021 smoothed LFP rate 0.3 percentage points higher than the published LFP rate.

Chart 01 of 06: Published versus Smoothed LFP Rate: Ages 16 and Older

The upward shift is even greater for the population aged 55 and older shown in chart 2. Recall that a significant part of the population adjustment was a reduction in the size of the population aged 70 and older. Given that this age group has a lower LFP rate than those aged 55 to 69, the composition shift pushed the LFP rate higher for the 55 and older population overall. The BLS estimated that the population adjustment impact on the December 2021 LFP rate for this population group was 0.7 percentage points.

Chart 02 of 06: Published versus Smoothed LFP Rate: Ages 55 and Older

For the population aged 16–24, the smoothed series shown in chart 3 is lower than the published series through December 2021. This is because the population adjustments revealed that the population aged 16–19 was larger than previously estimated. Because the 16–19 age group has a lower LFP rate than those aged 20–24, the smoothed LFP rate series is lower than the published series. The BLS estimated that the population adjustment impact on the December 2021 LFP rate for this population group was −0.3 percentage points.

Chart 03 of 06: Published versus Smoothed LFP Rate: Ages 16-24

Finally, for the prime-age population (25–54), the smoothed series shown in chart 4 is identical to the published series. The population adjustments had no effect on the LFP rate for this age group.

Chart 04 of 06: Published versus Smoothed LFP Rate: Ages 25-54

It is important to consider how the difference between the published and smoothed series may alter one's assessment of labor market dynamics surrounding the pandemic-induced recession and subsequent recovery. Chart 5 shows that for the initial year of the pandemic, measured here as the change in the LFP rates from January 2020 to January 2021, the published LFP rate data (blue bars) and the smoothed estimates (green bars) tell a very similar story for all age groups: LFP rates declined between 1.5 percentage points and 2.0 percentage points for all age groups, with no material difference in the size of the change between the smoothed and published estimates within each age group.

Chart 05 of 06: Change in LFPR from January 2020 to January 2021

However, the story is much different for the period between January 2021 and January 2022. Chart 6 depicts this difference, showing that the published LFP rate for the population aged 16 and over increased by nearly 0.8 percentage points over that 12-month period. In contrast, the corresponding smoothed estimate increased by only 0.5 percentage points. The discrepancy is even greater for the population aged 55 and older. For that age group, the published LFP rate increased by 0.8 percentage points, whereas the smoothed LFP rate shows an increase of less than 0.2 percentage points during the past year. That is, the smoothed data suggest the increase was less than one quarter as large as the increase in the published data. For the population aged 16–24, the smoothed LFP rate increased by more than the published series (0.7 percentage points versus 0.5 percentage points). Finally, for the population aged 25–54, there is essentially no difference between the change in the published and smoothed estimates. Both increased by close to 0.9 percentage points from January 2021 to January 2022.

Chart 06 of 06: Change in LFPR from January 2021 to January 2022

To sum up, smoothing the labor force data to account for the annual population adjustments like that described here provides a way to allow LFP rates in 2022 to be compared to prior years. These estimates show that the recovery from January 2021 to January 2022 in the overall LFP rate and the rate for the population aged 55 and older is more modest than the published data would imply, while the recovery for the population aged 16-24 is better than implied by the published estimates.

Going forward, the published labor force data for January 2022 will be comparable with data for other months in 2022 since they are all based on the same population control adjustments. In January 2023, the BLS will likely incorporate new population adjustments that use additional 2020 census information. Hopefully those adjustments will be less eventful. Stay tuned as we discuss future data.