The BLS announced that total nonfarm payroll employment increased 336,000 of which 263,000 came from the private sector as the government sector added 73,000 more workers. In addition, revisions to the two previous months increased employment by another 119,000.
This was a very strong jobs report that seems to have taken those prone to making predictions by surprise:
Economists surveyed by Dow Jones expect that September will show a 170,000 net gain in nonfarm payrolls.
Evidently, forecasting the US economy, or any economy for that matter, is not a simple task.
Total nonfarm employment has rebounded strongly from the depths of the pandemic and is now close to where it would have been had it stayed on the trend line post Great Recession.
The service sector added the bulk of jobs, up 234,000; 96,000 coming from Leisure and Hospitality that was obviously slammed during the pandemic and is still below its pre-pandemic level by 184,000 employees.
Average weekly hours remained at 34.4 and so the increase in total hours of work came solely from the new employees. Average hourly earnings increased from $33.81 to $33.88.
The household survey was remarkable as there was very little movement in any measure. Employment increased by only 86,000, there was no change in the employment to population ratio (60.4) or in the unemployment rate (3.8%).
Looking forward, it appears that what policy makers consider “inflationary pressures” are still hanging around given the strength of the labor market and the overall economy pretty much running on all cylinders. Although many of the price numbers have declined they still remain above the Fed’s 2% target indicating that more weight is likely being put on another rate hike than a continued pause.
It was a pretty busy week for incoming data. Bottom line: The economy continues to reveal strong economic growth and maybe we have not “landed” at all, we are still flying.
Employment Situation
The BLS establishment survey showed that employment rose 187,000 in August. Although the gain was higher than in the previous two months, the June employment numbers were revised down by 80,000 and July down 30,000…employment was 110,000 less than previously reported entering August. The gain was less than the 271,000 average gain over the previous 12 months. Private employment gains led the charge at 179,000 with the service sector adding 143,000. The biggest gain came in health care, up 97,000.
Average hours of work increased from 34.3 to 34.4. That, combined with the 179,000 increase in private employment led to a large increase in total hours of work.
The household survey showed an increase in the unemployment rate from 3.50% to 3.79%. The number of people unemployed did rise by 514,000, however, there was also a 736,000 increase in the labor force. The labor force participation rate has been steadily increasing but is still below the pre-pandemic level. Basically, once the effects of the pandemic have receded there has not been much of a change in the reasons for showing up as unemployed.
Since the unemployment rate is the ratio of the number of people unemployed divided by the labor force (the number of people employed and unemployed), the unemployment rate can increase either because the numerator (the number unemployed) increased, or because the denominator (the labor force) decreased. Which one accounts for the 0.29 percentage point increase in the unemployment rate in August? According to the Household Survey, the number of unemployed rose by 514 thousand in August while employment rose 222 thousand. In other words, the labor force increased by 736 thousand. For August, the increase in the unemployment rate came about due to an increase in the number of individuals unemployed.
The figure below digs deeper into the labor market flows. The arrows reflect flows of people between employment (E), unemployment (U), and not-in-the-labor force (N). The change in employment is obtained by adding the numbers with arrows pointing into E, and subtracting the flows associated with arrows out of E: a net increase in employment of 146 thousand. This number is different from the 222 thousand obtained directly from the employment data from the Household Survey. The reason being that there are some additional inflows and outflows found in this table that have to do with adjustments to population, teenagers turning 16, etc. We can similarly compute the change in the number of unemployed by looking at the flows in and out of U: an increase of 512 thousand (rather closer to the actual change of 514 thousand obtained from the number unemployed with the adjustments). Relative to the flows in and out of unemployment, 512 thousand is not a huge number: the total flows (regardless of sign) sum to 6,180 thousand, and so 512 thousand is 8.3% of the total flows.
The charts below show that the number unemployed rose by 99 thousand due to an increased number of people out of the labor force moving into unemployment, by 75 thousand owing to a decrease in those transiting between unemployment and out of the labor force, by 175 thousand by virtue of more employed people becoming unemployed, and by 281 thousand as a result of fewer unemployed shifting into employment.
Job Openings and Labor Turnover Survey
The JOLTS data came out 8/29 and showed the number of job openings declined to 8.8 million in July from 9.2 million and 11.4 million in July of 2022. Having said that, the difference between the number of people unemployed and the available jobs are still much higher than any time pre-pandemic. The quit rate has come down somewhat, but, like the openings rate, still higher than its pre-pandemic level. One interpretation of the quit rate is that quitting and moving to better jobs helps one climb the job and income ladder. Said differently, quit rates fall during recessions as there are fewer opportunities to move. Layoffs remain very subdued as well. The rate of job hiring as fallen considerably over the past year or so and now back to the average rate since 2014 (excluding the pandemic).
Output, Income and Consumption
The second estimate for Q2 real GDP was released by the BEA on August 30, and showed a downward revision from 2.4% to 2.1%. Consumption was revised up from 1.6% to 1.7%.
While the downward revision in Q2 real GDP was not small, the monthly consumption data released on 8/30 by the BEA showed a large increase in consumption for July. Consumption expenditures increased 0.8% in current dollars (9.9% annualized) and 0.6% in chained 2012 dollars, the largest increase since January. The personal savings rate as a fraction of disposable income declined by nearly a full percentage point, from 4.3% to 3.5%
Takeaways
The data describe a growing economy with little, if any, signs of braking. Looking at the headline numbers and article titles, such as this in the 9/1 WSJ: “Job Gains Eased in Summer Months; Unemployment Increased in August,” might suggest a faltering labor market. However, a deeper dive into the underlying data suggests no such thing.
The BLS announced that the all items CPI increased 0.2% over the month and 3.2% year over year. It is interesting to observe the various measures of “inflation” that appear in the media. For example, Bloomberg highlights the monthly change:
CNBC highlights the year over year change:
A New York Times columnist spotlights food prices:
Of course there are many others including the median CPI, trimmed mean CPI and the new “supercore” measure. What all of these analysts are trying to decipher is whether “inflation” has slowed enough to warrant a pause in the FED’s tightening spree. While there are many ways to parse the underlying data, such as the cost of eggs, milk and chicken, the preferred measure of the Econsnapshot is to look at the CPI over a 3-month horizon. Month to month the data is very volatile (hence the notion of core CPI that removes two very volatile components, food and energy) and year-over-year is very slow moving. As seen in the graph below, the annualized 3 month inflation is a bit under the FED’s 2.0% target at 1.9%. The year-over-year ticked up slightly.
The BEA recently released the July PPI (Producer Price Index). While the annualized one month change popped up from -0.5% to 3.6%, this series is very noisy; the annualized 3-month change came in at -0.2% for July, up from -0.6% in June.
In our May post on prices, we noted that the BEA points to the PPI for Consumption Expenditures as being closest in coverage to the CPI. Over the past three months, the annualized growth in this index was -6.8% indicating that by this measure, consumer prices are falling. Looking back a year, the index grew at a rate of -2.7%.
However, as we noted in May, there does not appear to be a very tight relationship between the growth of either of the PPI measures and either the CPI or core CPI.
Both the CPI and PPI measures point to a moderation in prices. Given that, it seems likely that the Fed will take a pause and let the economy speak a little more before a move in either direction.
The BLS announced the employment situation for July. The establishment data showed a 187,000 increase in total nonfarm employment, 172,000 of which was in the private sector. Private service producing employment gained 154,000. Employment gains in May were revised down by 25,000 to 281,000 while June was revised down by 24,000 to 185,000.
Roughly 1/3 of July’s employment gains were in health care (63,000); the rest was fairly evenly distributed across sectors. There were a few declines in employment: nondurable goods, transportation and warehousing, information, to name a few, but the largest came in temporary help services that has seen eight out of the last nine months with a decline.
Average hours of work fell from 34.4 to 34.3 and combining that with the smallish increase in employment led to a fall in total hours of work. Average hourly earnings rose by $0.14 to $33.74
The household survey data from the BLS revealed a 268,000 increase in employment and 116,000 fewer people unemployed. There was almost no change in the labor force participation rate and the employment to population ratio increased slightly. The unemployment rate declined from 3.57% to 3.50%.
The Jobs Openings and Labor Turnover Summary showed almost no change in the rate of job openings, hires and separations. The number of job openings is still much higher than the number of people unemployed. There are roughly 1.64 job openings for each unemployed person.
The fairly weak recent jobs data does not provide much guidance as to how the Fed might respond. Had the reports been very strong it would have likely given reasons to continue to jack up the funds rate. Conversely had the reports been really weak, a pause would be likely. The decision will become clearer as the price data come in.
The BLS announced the CPI and PPI for June. The CPI rose 0.18% from May to June on a seasonally adjusted basis, 2.18% when annualized, and was up 3.1% year over year. Rather than strip out a lot of goods that comprise the CPI, we look at the CPI on a three month average basis. As shown in the graph, the year over year continues to decline while both the annualized monthly and the 3 month ticked up slightly. The CPI-X (ex food and energy) differs, however. The annualized monthly rate grew 1.91%, below the Fed’s 2% target.
Of course, the question the Fed faces comes down to: What has been happening to the trend in inflation? Given the 2% target, the Fed hopes to see progress toward that goal. But, as we have commented on in several previous posts, what measure of inflation is the best indicator? Headline CPI (PCE)? Core CPI (PCE)? The Fed’s new Supercore CPI (PCE) (the price of services excluding energy and housing services)? Paul Krugman (NYT, July 11) has his own measure of supercore: “My preferred measure these days is “supercore,” which excludes food, energy, used cars and shelter (because official measures of housing costs still reflect a rent surge that ended a year ago.)” And goes on to say he is not a fan of the Fed’s measure, “The Fed has a different measure of supercore — non-housing services — but when you look at the details of that indicator, it’s a dog’s breakfast of poorly measured components that I find hard to take seriously.” Here is a graph of the Fed’s supercore measure:
So what are we to make of all of this? The main problem is that all of these measures are purely arbitrary; there is no underlying theory as to how, or what to measure. The BLS states, “Inflation can be defined as the overall general upward price movement of goods and services in an economy. The U.S. Department of Labor’s BLS has various indexes that measure different aspects of inflation.” These new so-called supercore measures omit various categories of goods that are purchased in the market. The overall CPI is comprised of 243 commodities and services measured in 32 different geographic areas. To show just how big these omissions are, the following table recreates a subset of the BLS table where the relative importance is the share of total expenditure used to weight the respective change and the May 2023-June 2023 column gives the monthly change:
Expenditure category
Relative importance
May 2023-June 2023
All items
100%
0.2
Food
13.4%
0.1
Energy
6.9%
0.6
All items less food and energy
79.7%
0.2
Services less energy services
58.3%
0.3
Shelter
34.7%
0.4
The table above shows that the core CPI includes about 79.7% of all expenditures. Removing shelter from the core means the price measure includes only 45% of the things we buy. If only services prices are included that would vastly reduce the set of prices used to calculate inflation.
The BLS announced that the Producer Price Index (PPI) for final demand increased 0.1% from May to June or 1.65% annualized. Year over year it increased 0.24%. Our 3 month measure fell -0.69%, the third consecutive month with a decline.
Trend Inflation
What we (the writers of this blog) mean by “trend inflation” is a series that tracks the movements of actual monthly inflation but somewhat smoothed (taking out the more extreme fluctuations). As we’ve discussed before, this is a signal-extraction problem. Every month, we get a new CPI number from which we want to make an inference concerning the current trend inflation rate. Trend inflation is the “signal”. However, the news (the new CPI number) is a noisy indicator of this signal, both because the CPI is reported in levels and because of transitory factors affecting monthly inflation. Further, the nature of the data is such that we cannot easily extract the signal (trend inflation) from the data. With all of this in mind, the reason for looking at core or supercore CPI inflation is that it has a higher signal-to-noise ratio than CPI inflation. Both seem promising in that they omit the more volatile price components of CPI: in the case of core CPI, food and energy; in the case of super core CPI, lots of other stuff. However, the charts above show that over the past couple of years, core CPI inflation has been running well above actual CPI inflation while the Fed’s supercore inflation has been well below actual.
An alternative to slicing and dicing CPI is to compute inflation over a horizon longer than a month. The idea in this case is that the monthly noise is an independent draw (in the jargon of economics, it’s independently and identically distributed) while trend inflation has memory and changes relatively slowly over time. Consider headline inflation. Typically, it’s calculated as the 12 month percentage change in the CPI. But a different way to think about this calculation is as the average of the 12 one month inflation rates. If there is no change in trend inflation over this period of time, the 12 noise terms will have a mean of roughly zero, and the year-over-year inflation rate will provide a good estimate of trend inflation. The rub is that there have been changes in trend inflation over the past couple of years. Consequently, the year-over-year inflation rate also takes an average of trend inflation over the past year. This is why, in the chart above, year-over-year inflation has consistently exceeded the monthly inflation rate for the last year and a half.
But there’s nothing magic about year-over-year inflation rates, and we’ve previously advocated for annualizing the three month inflation rate as a good compromise between capturing changes in trend in a timely fashion, and seeing through the noise in monthly inflation rates. By construction, the three month inflation rate tracks movements in monthly inflation while removing much of the noise – as can be seen in the chart above. One thing that the three month inflation rate lacks is a fancy name like supercore; oh, and the NYT soap box.
The BLS released the Job Openings and Labor Turnover Survey (JOLTS) for May on July 6. The data reveal a pretty mixed view. Job openings fell 496,000 and now stands at 9.8 million vacancies. The number of unemployed workers in May was 6.1 million so that there were 1.6 jobs available for each unemployed worker.
The JOLTS data also contains information on the rate at which workers are hired, laid off, quit and job openings. The rates are determined by dividing by the level of employment. The JOLTS covers about 95% of all nonfarm payroll jobs in the US. While the openings rate declined the hiring rate and the quit rate rose. The layoff rate remains at one of its lowest rates since the inception of the JOLTS in December of 2000. Note that all of the other rates are well above their historic average.
The JOLTS data provides some evidence for those looking for nascent signs of a recession. Quit and hiring rates fell through the March-November 2001 and December 2007-June 2009 recessions, and both series started falling prior to the latter recession. The declining quit and hiring rates since early 2022 fit this pattern. Unfortunately, JOLTS only covers three recessions, so it’s tough to make much of the historic precedents, particularly since the February-April 2020 recession was due to COVID-19. Another potentially confounding factor is that both quits and hires are at historically high rates, and the recent declines may be due to reversion to the mean.
The data on initial and continued claims for unemployment insurance also came out on July 6. Initial claims rose slightly but remain relatively subdued. Continued claims have been trending down over the past few months.
On July 7, the employment situation report for June was released by the BLS and showed a payroll employment increase of 209,000 but downward revisions for April and May totaling 110,000 for the two months. One way to think about these changes is that roughly half of the employment gains reported for June were offset by the downward revisions in the previous two months. The employment change in the private sector was the smallest increase over the past couple of years.
The phrase “little changed” was peppered throughout the press release for the Employment Situation Report. The report highlighted gains in employment in government (60,000), health care (41,000), social assistance (24,000) and construction (23,000). Yet the gains in professional and business services, and leisure and hospitality (both 21,000) were described as “little changed”. It would seem that the difference between a gain warranting notice, and “little changed” is 22,000.
Average hours worked in the non-farm sector inched up 0.1 hours to 34.4. That increase, combined with the increase in private employment led to about a 5% in total hours of work in the private sector. There was little change in average hourly earnings.
One way to combine data from JOLTS and the employment report is through the Beveridge curve which plots the vacancy rate (from JOLTS) against the unemployment rate (the household survey). As seen in the chart below, the data up to and including the Great Recession (2007-09) appears to lie on a stable Beveridge curve. After the Great Recession, the Beveridge curve shifted out. And after the pandemic, the Beveridge curve shifted out yet again, with the most recent data in the north west quadrant. One interpretation of an outward shift in the Beveridge curve is that it reflects lower efficiency in the matching process between jobs and workers. Under this interpretation, at a given level of unemployment, firms need to post more vacancies in order to fill jobs. An alternative interpretation is that the outward shifts in the Beveridge curve are due to lower costs of recruiting workers: firms post more vacancies because doing so is simply much cheaper that in the past. One way to distinguish between these two alternative interpretations is to look at how quickly vacancies are filled: less efficient matching says it should take longer while lower job posting costs implies a shorter period of time. Unfortunately, the speed at which vacancies are filled is no longer available.
According to the BLS household survey, employment increased 273,000, the number of people unemployed fell by 140,000 and the labor force increased by 133,000. The participation rate and employment to population ratio were unchanged. The unemployment rate fell from 3.65% to 3.57%.
The BLS announced that the Consumer Price Index for all urban consumers (CPI-U) rose 0.1% in May on a seasonally adjusted basis. This 0.1% rise translates into an annualized 1.5%, well below the Fed’s 2% inflation target (the grey line in the figure below). Over the last 12 months it rose 4.13%. The preferred measure of Econsnapshot is a measure of inflation based on a 3 month interval. We prefer this measure because the year-over-year number moves very slowly while the month to month number is very volatile as seen in the graph below. This 3 month inflation rate grew at an annual rate of 2.2%, just above the Fed’s 2% target.
The bad news from the CPI report is that core CPI inflation — which strips out the more volatile food and energy prices — continues to run at 5% or more, much higher than the Fed’s target. Indeed, energy prices have declined significantly, down almost 12% year over year. When looking at core CPI over the last month it is the shelter component that was the largest contributor to the rise in prices, accounting for about 60% of the overall increase. One reason to look at core CPI inflation is that it may be a better measure of trend inflation than headline CPI. If so, the Fed still has work to do to bring inflation back to target.
Of course, Fed watchers know that the Fed focuses on inflation as measured by the personal consumption expenditure (PCE) price index. Over long periods of time, PCE and CPI inflation generally move together. That said, on average PCE inflation runs below both the CPI and core CPI. The PCE for May won’t be released until June 30. Consequently, the recent CPI inflation rates may provide useful information regarding the direction for PCE inflation.
Producer Price Index
Hard on the heels of the CPI report came that for the Producer Price Index (PPI). Inflation as measured by the PPI has been trending down since early 2022. Indeed, at an annual rate, the monthly and 3 month inflation rates are negative meaning that the price index has recently been falling.
Roughly speaking, the CPI reflects prices paid by the typical urban household while the PPI captures prices received by domestic producers of goods and services. Since the PPI captures prices received by domestic producers while the CPI measures prices paid by consumers, it’s tempting to conjecture that changes in the PPI will eventually be reflected in the CPI. However, there are differences in coverage which mean that this logic does not necessarily hold. For example, since the PPI measures prices received by US producers, it does not include prices of imports; the CPI does. Also, nearly 1/4 of the CPI includes the imputed rent of owner-occupied housing; this imputed rent is not included in the PPI. Finally, only some of the goods and services covered by the PPI represent purchases by consumers; the remainder are goods and services used by other producers, capital investment, exports and government. The Bureau of Economic Activity says that the PPI for Personal Consumption comes closest to the coverage of the CPI. Yet, the chart below shows that inflation as measured by this last measure is much more volatile than the CPI. The chart also shows that there is no obvious tendency for PPI inflation to lead CPI inflation.
Automotive Prices
Since the onset of the pandemic, much has been said and written about supply chain problems, with the automotive sector receiving particular attention, such as this article that makes several blunders and left out some important economics as well. Anyone who has tried to buy a new car knows that there are very long delivery lags, especially for electric vehicles. These issues in the new car market has spilled over into the used car market where prices have also risen. Keep in mind that a one time increase in the price of, say, new cars is not what we typically mean by `inflation’. To be sure, such a one time increase will, for a time, lead to an increase in measured inflation. However, this effect will dissipate with time. The chart below is based on price indices from the CPI. The used car inflation rate was much higher than that of new cars from mid-2020 to mid-2022. Recently, used car prices have been falling, and new car price inflation is moderating. Automotive maintenance and repair price inflation continues to increase.
Finally, turn again to the difference between the PPI and other price indices. From the PPI, prices received by domestic automotive producers grew rapidly through 2021 and 2022, with an inflation rate as high as 30%. While those prices have started to decline, the price level has risen 28.5% since May 2020. Granted, automotive inflation as measured by either the CPI or PCE price index also rose, but not nearly as much as recorded by the PPI, and the recent decline in PPI automotive prices has translated into a slowing of these prices as measured by the CPI and PCE.
The June 13-14 meeting of the Fed revealed a pause in rate hikes. As the graphs above show, there are certainly signs that the Fed’s early moves have worked in their favor. As we remarked above, given the core CPI numbers there still may be more work to do…and the Fed made it clear in the statement that more rate hikes are likely.
The BLS announced that payroll employment climbed 339,000 in May. The private sector added 283,000. The bulk of the gain was in the service sector, adding 257,000. The goods sector increased 26,000 but almost all of it, 25,000, in construction.
Although employment climbed 339,000, average weekly hours fell from 34.4 to 34.3 (a decline of 0.1%), throwing a little cold water on the overall report. As shown in the chart below, average weekly hours have trended down since late 2020. Hourly pay, however, climbed 0.3%, from $34.33 to $34.44, and the year over year increase was 4.30%; unfortunately, that growth is still a bit below the year-over-year CPI inflation rate for April, 4.96% (the May CPI has not yet been released).
The household data showed almost exactly the opposite from the establishment survey with an employment decline of 310,000. The employment to population ratio fell slightly from 60.4 to 60.3, and still falls below the pre-pandemic level of 61.1.
The unemployment rate is based on data from the household survey. As mentioned above, employment fell by 310,000 according to the household survey. Combined with a 440,000 increase in the number of unemployed persons, the unemployment rate rose from 3.39% to 3.65%. The changes in the number of employed and unemployed left the labor force participation rate unchanged at 62.6%.
To be “officially” classified as unemployed, an individual must have “actively” looked for a job and available to begin employment. This definition excludes those who are deemed “marginally attached” to the labor force who would like a job, but have not taken sufficiently active measures to find one. The chart below plots the headline unemployment rate along with a measure that includes marginally attached individuals as well as those employed part time for economic reasons (the “U-6” definition). Whereas the headline unemployment rate is 3.7%, the broader measure of unemployment stands at 6.7%. The gap between the two, 3.0%, is about as low as it has been since 1994 when the U-6 measure of the unemployment rate starts.
Until the early 1980s, female unemployment tended to exceed that of men; since then, the pattern has reversed. Since 2021, the male unemployment rate has exceeded that of women by 0.17 percentage points.
Note: We use the terminology of the BLS so as not to add any confusion, in particular, Sex and Race. Also, the BLS uses the terminology Race and Hispanic or Latino Ethnicity.
Historically, Black and African American unemployment rates have exceeded that of other racial groups. Since 1973 (when the data becomes available), the Black and African American unemployment rate has averaged 6.1 percentage points higher than that of whites. Over time, this gap has narrowed; since 2021, it has averaged 3.1 percentage points. Hispanic and Latino unemployment rates lie between that of Blacks/African Americans and whites. (Note that we have seasonally adjusted the Hispanic and Latino unemployment rates using Python’s ARIMA X11 package with default settings; officially seasonally adjusted series are not available.) Over the available data, the Hispanic/Latino unemployment rate exceeded that of whites by 3.15 percentage points; since 2021, by 1.5 points. The Asian unemployment rate is only available since 2003. On average, their unemployment rate is 0.55 percentage points lower than that of whites; since 2021, the gap is only 0.09 points.
We can further look at unemployment rates by sex and race, albeit for those 20 years of age and older. As mentioned earlier, since the early 1980s, for the population as a whole the male unemployment rate has exceeded that of women. While the same is generally true for Blacks/African Americans and whites, the average unemployment rate for Hispanic/Latino women is 0.95 percentage points higher than that of Hispanic/Latino men. Data for Asians is not broken down by sex.
People enter unemployment through various channels. The largest component is for people who lose their job, that represents about half of all of the unemployed. The next largest category is from those who reenter the labor force after a spell of being absent; these are labeled reentrants. Then there are those that voluntarily leave their jobs and those who are just entering the labor force.
Looking across those unemployed, average weeks of unemployment has been trending up somewhat over time. Between 1950 to 1980 average weeks of unemployment hovered between 10 and 15 weeks. Indeed, average weeks never hit 20 weeks until after 1980. Since that time average weeks have hit 20 or more numerous times and today stands at just over 21. The Great Recession and the pandemic had massive effects on weeks of unemployment.
Overall, the labor market continues its strong performance. While the unemployment rate increased it still remains as low as the economy has seen for decades.
The BEA announced that Q1 real GDP increased 1.1% at an annual rate. Many in the press have, obviously, noted the declines over the last two quarters indicates the economy is slowing. Indeed, today’s report “undershot” expectations that were around 2%. However, the underlying components were a bit more mixed and the strength of the economy might be in the eye of the beholder. Real consumption spending increased 3.7%, the largest increase over the last 7 quarters, and disposable personal income rose 8.0%.
The output identity, Y = C + I + G + X – M, tells us the uses of output (the “demand” side). If output growth is down, then one or more of the right-hand side components must be down. From above, consumption growth rose from 1.0% in the fourth quarter to 3.7% in the first quarter. Growth in government spending likewise rose, from 3.8% to 4.7%. However, real investment spending fell 12.5% in the first quarter compared to a 4.5% increase in the fourth quarter. Within real investment, real inventories grew 0.4% (up from -3.7%), non-residential structure investment grew 11.2%, and residential structure investment fell by 4.2% (although this decrease was an improvement over the very negative growth rates for this category late in 2022).
While it has become standard in the U.S. to annualize the quarterly growth in GDP, one could also look at the year-over-year growth rate. Now, Q1 does not look so bad relative to the past few quarters and, in fact, has actually increased over the previous quarter.
The Personal Consumption Expenditure Price Index (PCE) rose 4.2% in the first quarter compared to growing 3.7% in the previous quarter, obviously high above the FOMC’s 2.0% target.
These developments lead to a murkier monetary policy outlook. Output growth has slowed, perhaps reflecting the cumulative effects of monetary policy tightening over the past year. Yet, PCE inflation is still well above the Fed’s 2% target (see also the CPI and PPI), and consumption growth actually accelerated in the first quarter. In previous posts, we have noted that the labor market is still quite strong, with an historically low unemployment rate, and roughly two job openings for every unemployed person. Given that, there is nothing new to dissuade the FOMC from another rate hike or two.
The BEA announced a downward revision from 2.7% to 2.6% in the third and final estimate of Q4 GDP. The revision primarily reflected downward revisions to exports and consumer spending. The final estimate for 2022Q4 GDP did not change the overall stance of the US economy.
Several sources picked up on the fact that the PCE price index, the primary inflation index cited by the Fed, fell. CNBC reported: “On a 12-month basis, core PCE increased 4.6%, a slight deceleration from the level in January.” The New York Times remarked,
The measure of inflation most closely watched by the Federal Reserve slowed substantially in February, an encouraging sign for policymakers as they consider whether to raise interest rates further to slow the economy and bring price increases under control.
The Personal Consumption Expenditures Index cooled to 5 percent on an annual basis in February, down from 5.3 percent in January and slightly lower than economists in a Bloomberg survey had forecast. It was the lowest reading for the measure since September 2021.
NYT, March 31, 2023
However, as we remarked in an earlier post, measured inflation is sensitive to the time horizon over which it is computed. Annualized month-to-month inflation rates are quite volatile; year-over-year inflation is much smoother, but is slow to reflect changes in trend inflation. And it’s trend inflation that policymakers, among others, are concerned about. Yet, identifying trend inflation is difficult. One approach is to average monthly inflation rates over a few months. In the figure below, we include the 3-month average of monthly inflation rates which is our attempt to balance the desire to smooth monthly inflation rates while capturing changes in trend in a timely fashion.
The Fed tends to focus on so-called core PCE inflation for which the volatile food and energy components are removed. Presumably, the reason for looking at core PCE inflation is that it gives a better read on trend inflation. To be sure, core PCE inflation is less volatile, as shown in the chart below. Nonetheless, this measure continues to exhibit large fluctuations when measured on a monthly basis. And, it should not be surprising that the annual (year-over-year) inflation rate is smoother, but slow to reflect changes in trend inflation. Again, we include the 3-month average of monthly inflation rates.
One way to think about the problem of extracting a measure of trend inflation from the data is that observed inflation is composed of trend inflation and an ‘error’ which reflects issues in measuring trend inflation. In the jargon of the profession, we face a signal extraction problem: we are trying to extract the signal (trend inflation) from noisy data (measured inflation). Averaging monthly inflation rates over some horizon (for example, over 3 months, as above) can be thought of as canceling out the positive and negative error terms in this signal extraction problem. (Again, using some jargon, ideally the errors are uncorrelated over time, or independently and identically distributed.)
Finally, what are the policy implications of the latest PCE price index numbers? As mentioned above, some commentators have noted that PCE inflation was down in February relative to January. True enough when looking at either the monthly inflation rate, or the year-over-year inflation rate. However, the 3 month average inflation rate is up. It is hard to make a strong case that there has been a change in trend inflation. In any event, all of the gauges of inflation presented above continue to run well above the Fed’s stated 2% target.
