Viewpoints

In an April 16, 2024 Bloomberg News article entitled “What If Fed Rate Hikes Are Actually Sparking US Economic Boom?”, it is argued that the Fed’s increase in the federal funds rate from 0.08% in March 2022 to 5.33% in July 2023, which, in turn, pushed up other interest rates, stimulated US domestic aggregate demand for goods and services by increasing interest income to holders of fixed-income assets. Wow! This novel hypothesis, if valid, turns monetary policy theory on its head.

Let’s look at some data. As can be seen in Chart 1, there does indeed seem to be some positive correlation between the level of the federal funds rate and the level of personal interest income. For example, when the Federal Open Market Committee (FOMC) hiked the federal funds rate from the beginning of 2016 through the first quarter of 2019, personal interest income moved up sympathetically. Although personal interest income had started increasing in 2014, before the FOMC had begun raising the federal funds rate. Similarly, as the FOMC began hiking the federal funds rate in 2022, personal interest income starting rising, too. So far, so good for this hypothesis that FOMC federal funds hikes raise personal interest income.

The Federal Reserve's persistent use of the 'forward guidance' policy tool, which involves offering forecasts of growth, inflation, and policy rates to influence financial market conditions, is a misguided approach. This tool operates under the assumption that the Fed can accurately predict the future, a notion that is inherently flawed given the unpredictable nature of economic conditions.

In 2023, policymakers used its forward guidance policy tool to signal an end to its tightening policy cycle, thinking it had or would, in time, arrest the cyclical inflation cycle. At the end of the year, it went further, as it offered forecasts for 2024 that promised three official rate cuts.

Yet, in hindsight, forward guidance backfired. Promises of no more rate hikes followed by promises of lower official rates triggered a 100-basis drop in long bond interest rates and double-digit increases in equity prices. The dramatic change towards much easier financial conditions has helped produce economic results that the Fed was not expecting in its forward guidance. (Note: Q1 real GDP growth is estimated at 3%, while core consumer prices rose at an annualized rate of 5%, compared to forward guidance growth estimates of 2% and core inflation of 2.4%).

The challenge for policymakers is how to navigate the modification or discontinuation of the forward guidance policy tool. Forecasts from forward guidance are updated only four times a year, with the next update scheduled for the June meeting. While the Fed chair can provide an informal update at any time, official policy announcements are made at regularly scheduled meetings. A sudden deviation from the last forecast could disrupt the financial markets and undermine the Fed's credibility, if it still has any.

Yet, the problem with "forward guidance" goes well beyond the announcement dates. Policymakers offer forecasts on growth, inflation, unemployment, and policy rates for two years and a longer-run equilibrium level for each. And, regardless of whether current economic conditions are too hot or soft or inflation is too low or high, the Fed's forward guidance forecasts say, through the magic of monetary policy, growth, unemployment, and inflation will gravitate to trend.

Like everyone else, the Fed has had difficulty forecasting what the economy will be like in the next year, let alone in two or three years. Yet, unlike other forecasters, policymakers link an official rate path to its forecasts. That linkage makes official policy more predictable. However, it also creates the potential for a significant easings in financial market conditions, similar to what occurred since late 2023, long before policymakers achieved their intended outcomes.

Policymakers spent time "normalizing" official rates, and now they need to "normalize" their policy statement, making it shorter and with fewer promises. Eliminating forward guidance would also be a positive step because even though it implies "it all depends," it still drives market expectations of official rates.

I enjoy examining data. It used to be a hobby that I got paid to do. Now, it is just a hobby. Below are some random sets of data of that I found interesting. Perhaps some others will, too.

As shown in Chart 1, starting in 2022, household interest payments as a percent of their after-tax income (Disposable Personal Income) started rising after declining in 2020 and 2021. By Q4:2023, household interest payments as a proportion of after-tax income had moved up to 5.4%. This compares with 5.0% in Q4:2019, just before the Covid pandemic hit the US. Notice that the main driver in of this proportional increase in household interest payments has been non-mortgage debt. With many 30-year home-mortgage rates locked in at around 3% in 2020 and 2021, households have been able to increase their spending relative to their after-tax income by increasing consumer loans, such as credit card and auto debt. Although household debt-service ratios are rising, they are a far cry from those that obtained just before the onset of the Global Financial Crisis, but …

State real GDP growth rates in 2023:4 ranged from Nevada’s 6.7% to Nebraska’s 0.2%. Growth tended to be weaker in the center of the nation, with agriculture being a major drag.

The distribution of personal income growth was comparable to real GDP with Nevada again on top with a 6.7% growth rate, while Iowa and North Dakota tied for last with each having a growth rate of 0.8%. Over the last few years, the extension and withdrawal of federal transfers connected to the pandemic often grossly distorted movements in state personal income, and the ranking of states. This has become less evident in recent quarters, though the range of annual growth rates for transfers in 2023:4 did run from 8,1% in Mississippi to -5.0% in Arizona. The large drop in Arizona certainly had a visible effect on its overall income growth; Mississippi’s large gain was less meaningful, since other income components there also grew substantially.

The Federal Reserve Bank of Philadelphia’s state coincident indexes in January generally showed moderate, but generally unspectacular, increases. 9 states show declines from December, but none especially large. Massachusetts had a robust 1.1 percent increase. New York was the only other state with a gain as large as .5 percent. Over the 3 months ending in January, Montana was the only one to show a decline, while Massachusetts was up 2.4 percent---a fairly low reading to the leader—while Arizona and Nevada were the only other states with increase of 1 percent or more. Over the last 12 months Massachusetts was also on top, and, again, its 4.6 percent increase was unimpressive for number one. Montana was down a sharp 3 percent, and Maine and West Virginia were also down.

The independently estimated national figures of growth over the last 3 months (.6 percent) a bit lower than the state estimates would have suggested, but the 12-month figure (2.6) percent) looks to be roughly in line with the state numbers.

The state coincident index measures are primarily based on state payroll employment data, and calibrated to state real GDP estimates. This report is a bit of an odd duck—it’s for January, even though the February payroll numbers have been released—and Q4 state GDP numbers will soon be released. On April 3 the February estimates will be available.

State labor markets were at best mixed in February. Only four states had Eight states had statistically significant gains in payrolls (Illinois, Iowa, Michigan, and Texas—Iowa was the only one with an increase larger than ½ of one percent). The other states, and DC, had no signicant change, with numbers showing point declines.

Three states had statistically significant increases in their unemployment rates in January, while three had significant declines. The largest move was an increase of .3 percentage point in Rhode Island. The highest unemployment rates were in California (5.3%), Nevada (5.2%) and DC (5.1%). No other states had unemployment rates of 4.9% (one point above the national rate) or higher. Maryland, Massachusetts, Minnesota, Nebraska, New Hampshire, North Dakota, South Dakota, Utah, Vermont, and Wyoming had rates of 2.9% or lower, with North Dakota at 2.0%.

Puerto Rico’s unemployment rate remained at 5.7 percent, with the island’s job count little-changed.

In its January 31, 2024 FOMC statement, the Fed said: “In assessing the appropriate stance of monetary policy, the Committee will continue to monitor the implications of incoming information for the economic outlook.” The translation of this Fedspeak is that the Fed’s target level of the federal funds going forward would depend on the forthcoming data as they relate to the Fed’s dual mandates of promoting price stability and full employment. But what if the data upon which the Fed were depending to determine the level of the federal funds rate were undependable? In what follows, I will provide examples of “undependable” data and recommend a solution for how the Fed might conduct monetary policy in the face of undependable data.

In the Bureau of Labor Statistics (BLS) February 2024 Employment Situation, it was reported that the level of January 2024 nonfarm business establishment payrolls was 157,533 thousand, revised down from its preliminary estimate of 157,700 thousand. Mind you, this is just the first revision of January 2024 nonfarm payrolls. When the BLS releases its March 2024 Employment Situation report, there will be a second revision to January 2024 nonfarm payrolls. And then in 2025, there will be annual “benchmark” revisions to 2024 nonfarm payrolls, including those of January 2024. The level of February 2024 nonfarm payrolls reported on March 8, 2024, 157,808 thousand, was said up 275 thousand compared to the first-revised January 2024 level of nonfarm payrolls. However, compared to the first-reported level of January 2024 nonfarm payrolls, the level of February 2024 nonfarm payrolls was up only 108 thousand. And, of course, in the next two 2024 BLS Employment Situation reports, the February 2024 level of nonfarm payrolls will be revised twice. Because of monthly and annual revisions, the monthly reports of nonfarm payrolls would seem to be undependable data upon which the Federal Reserve might use to determine monetary policy.

On March 14, 2024, the Census Bureau reported that the level of February 2024 retail sales increased 0.6% compared to the revised level of January 2024 retail sales. However, the level of January 2024 had been revised down by $3,581 million or 0.5% from the originally-reported level. So, the level of February 2024 retail sales was up only 0.06%, not 0.6% from the originally-reported level of January 2024 retail sales. Based on revised data in the February 2024 retail sales report, in the three months ended January 2024, retail sales contracted at an annualized rate of 3.8%. Based on the data reported in the January 2024 retail sales report, in the three months ended January 2024, retail sales contracted at an annualized rate of only 1.8%, less than half the rate of contraction exhibited by the data revised in the February 2024 retail sales report. Again, monthly revisions to retail sales data would suggest that these data are undependable for the purposes of guiding monetary policy.

The next problematic economic report I will discuss is the Consumer Price Index (CPI), more specifically, the Owners’ Equivalent Rent (OER) component of the CPI. At 26.7% of the CPI, OER has the “heaviest” weight in the CPI. That OER has such a high weight in the CPI is understandable given that the US homeownership rate is about 66%. My quarrel is not with the weight of OER but how it is estimated. From what I have read about this estimation process is that a sample of homeowners are asked by the BLS what the respondents think their detached dwelling/condo/townhouse would rent for. How many homeowners, especially owners of detached houses, have a reasonably accurate estimate of what their abode would rent for?

OER was reported to have increased month-to-month annualized 6.94% in January 2024 compared to a 5.22% annualized increase in December 2023. The CPI excluding OER monthly increase was 2.66% annualized in January 2024 compared to 2.03% in December 2023. The month-to-month annualized change in the CPI-All Items was 3.73% in January 2024 compared to 2.83% in December 2023. The BLS received queries as to why there was such a relatively large percent increase in the January 2024 OER compared to December 2023. On February 29, 2024, the BLS issued a statement saying that there are now annual updates effective in January of a year in the weighting of the OER in terms of owner-occupied detached dwellings versus condos/townhouses. The BLS said that “[i]n January 2024, the proportion of OER weighted toward single-family-detached homes increased by approximately 5 percentage points.” My point, again, is not that OER is unimportant, but that its measurement is, for lack of a better term, “flaky”. Given the difficulty in accurately measuring OER, the European Union excludes OER from its calculation of EU consumer price inflation. Plotted in Chart 1 are the year-over-year percent changes in the All-Items CPI (the blue bars) and the CPI excluding OER (the red line). The year-over-year change in the CPI excluding OER in February 2024 was 2.27%, close enough to 2% for Federal Reserve work.

In February, total consumer prices and prices, excluding food and energy, rose 0.4%, resulting in the last twelve-month increases of 3.2% and 3.8%, respectively. The consumer price report is the sole direct measure of retail inflation, capturing what people buy for consumption.

However, the Fed favors the PCE deflator, which is not a direct measure but rather a blend of CPI prices with administered prices (Medicare and Medicaid). This preference is based on the belief that the PCE captures what people purchase in real time, reflecting the substitution effect of price change.

But this claim is misleading. Detailed spending data, crucial for accurate measurement, is unavailable in real-time. The choice of the PCE over the CPI for inflation measurement is driven by political considerations, as it tends to produce a lower rate.

The Bureau of Economic Analysis (BEA), the government agency responsible for estimating and publishing the PCE deflator, faces significant challenges in data collection for various product categories. For instance, while BEA has a small set of product details updated monthly, such as motor vehicles, prescription drugs, gasoline, and tobacco, other categories suffer from a considerable lag.

For instance, food store sales are supplemented with annual scanner data, resulting in a one-year lag. Similarly, the yearly e-commerce survey report provides additional product details with a one-year lag.

Detailed consumer expenditures for services are also unavailable when the PCE deflator for a given month is estimated and released. The Census's Quarterly Survey of Services (QSS) is released three months after a quarter ends. However, the QSS provides aggregate spending figures for various service industries and offers few details of how much of it is household spending.

Without detailed data, the BEA is forced to rely on imperfect product-to-industry ratios, often based on data from the several-year-old 2017 Economic Census, to estimate household product and service spending. This reliance on outdated data is a significant drawback, as it uses spending patterns from years past to explain how current price inflation impacts people's spending decisions. This practice undermines the accuracy and relevance of the PCE deflator, raising concerns about its effectiveness as a current measure of inflation.

The CPI has been criticized for what it is and isn't (See a recent article by Larry Summers on CPI missing financing costs for consumption). The same should apply to the PCE deflator. The PCE is not what people think it is. Choosing the PCE over the CPI is a convenient way for policymakers to argue that they are close to or hitting their target, even when the only direct measure of consumer price inflation (CPI) runs much higher.