Viewpoints

Auto and light truck assemblies sprinted 21.1% month-to-month (not annualized) in June to a seasonally-adjust annualized level of 13.1 million units, the highest level of monthly of production since July 2015. In May, retail dollar inventories of motor vehicles (and parts) relative to dollar retail sales of them continued their upward trend, reaching 1.93, the highest since April 2020, when Covid infections were in their early stage. The retail inventory-to-sales ratio of motor vehicles will artificially rise higher in June due to the surge in June assemblies and the curtailment of sales related to the computer hacking of car/truck dealers last month. But discounting the likely increase in the I/S ratio in June because of the hacked software, retail inventories of motor vehicles are starting to look a bit excessive, albeit below the ratio to sales pre-Covid. (See Chart 1 for these data.)

I thought that by 2023 the US economy would have entered a recession. My favorite recession indicators, the yield spread between the Treasury 10-year security and the federal funds rate and changes in real “thin-air” credit, both suggested a recession was imminent. When the yield spread enters negative territory and remains negative for as long as it has of late (see Chart 1), since 1970, a recession has occurred. But not this time. Similarly, when the yield spread persists in negative territory, typically, real thin-air credit (depository institution holdings of loans, securities and reserves deflated by the Gross Domestic Purchases chain-price index) contracts and a recession is underway (see Chart 1). The percent contraction in real thin-air credit of late has been the largest since the Great Depression. But still no recession. It’s been a long time coming, but I do believe the US economy finally stands on the precipice of a recession.

State real GDP growth rates in 2024:1 ranged from Idaho’s 5.0% to South Dakota’s -4.2%. Growth tended to be high in the mountain West and the Southeast. Many highly agricultural states in the Plains saw declines, but Illinois, Ohio, Oregon, and Louisiana also saw drops. Pennsylvania is on the verge of becoming the sixth state with current-dollar GDP exceeding one trillion dollars. The five currently above that threshold are California, Texas, New York, Florida, and Illinois; Pennsylvania’s 2024:1 figure was $998 billion, at an annual rate. No other state exceeds $900 billion.

The distribution of personal income growth was comparable to real GDP. South Carolina first with a 9.5% growth rate, while North Dakota’s .6 % was the lowest. It appears that weakness in farm income held down net earnings in the agricultural regions. As always, the distribution of the growth of transfer payments was erratic and influenced the rankings of total personal income growth, but in this instance, generally slower transfer growth in the Plains merely tended to accentuate the effect of weakness in net earnings. 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 May continued to be mixed, but a touch improved from the initial April results. Idaho and Arizona led with fairly moderate increases of .6 percent from April, while Arizona, West Virginia, and New Hampshire also had gains above.5 percent, but a full ten states, scattered across the nation, saw declines, with Rhode Island down .4 percent. Over the three months since February, 11 states had increases of more than 1 percent, with Montana up 2.4 percent. 15 states had gains under .5 percent, with 3 of those experiencing declines. Over the last 12 months, Arizona was on top with a 4.1 percent increase. There were six other states with increases higher than 3 percent. On the down side, four states (none large) had declines, with West Virginia off 1.8 percent (Montana was off 1.4 percent, despite its strong April), and 9 others had increases of less than 1 percent.

The independently estimated national figures of growth over the last 3 (.7 percent) and 12 (2.8 percent) months appear to be roughly in line with the state numbers.

State labor markets were again mixed to moderate in May. Seven states (counting DC here) had statistically significant gains in payrolls , with the most impressive gain Idaho’s .9 percent increase, while both California and Texas had increases over 40,000 The other states, had changes deemed to be insignificant, including New York’s increase of more than 20,000.

Four states had statistically significant declines in their unemployment rates in April, and three had increases. None were larger than .2 percentage point. The highest unemployment rates were in DC (5.3%), California (5.2%), DC (5.2%) and Nevada (5.1%). No other state had rates as much as a point higher than the national 4.0%. Alabama, Hawaii, Iowa, Kansas, Maine, Maryland, Massachusetts, Minnesota, Mississippi, Nebraska, New Hampshire, North Dakota, South Dakota, Tennessee, Utah, Vermont, Virginia, Wisconsin, and Wyoming had rates of 3.0% or lower, with both Dakotas at 2.0%.

Puerto Rico’s unemployment rate was unchanged at 5.8%, while the island’s job count edged up by 700.

The owner's equivalent rent (OER) index has received a lot of press lately because it's primarily responsible for keeping reported inflation well above the Fed's 2% target. Yet, if asked, many analysts and even policymakers probably need to learn why OER exists.

OER is a concept unique to how housing units are accounted for in GDP statistics. In GDP, rental units and owner-occupied units are considered the same. To maintain this equivalence, an imputed estimate shows how much money owner-occupied units would have spent if they were renting to match the money tenants paid for housing. This process, which creates an artificial expenditure in consumer spending, necessitates the creation of a price measure or a deflator. That's because the government needs to estimate the imputed 'real' value of money owners spend for rent when calculating Real GDP.

OER is a 'fake price, a unique concept involving zero transactions. No one actually pays OER, and as a result, it does not generate any economic activity such as sales, income, or jobs. Therefore, official rate increases do not affect the demand associated with OER. However, despite its unique nature, it has accounted for a significant part of the increase in consumer price inflation in the last three years. For instance, the increase in shelter costs contributed to more than a third of the 3.4% rise in consumer prices in the past twelve months.

OER is suitable for GDP accounting, but why does the CPI use OER to measure housing costs? It's political because if housing costs were calculated based on house prices and borrowing costs, reported inflation would be much higher nowadays and would have run markedly higher for the past fifty years.

BLS and the Fed should be humble enough to admit that, but they won't.

What accounts for the big disconnect between people's inflation and policymakers' inflation? People consider the total costs of things; based on that measure, inflation remains relatively high. Policymakers view inflation differently, creating a disconnect. Analysts should call out the disconnection and help the Fed avoid another policy blunder.

Inflation Based on Total Costs

People's inflation views are based on the total costs of things; yet, nowadays, inflation measurement is based on list prices/cash transactions ( and excludes financing costs), which makes little sense as fewer and fewer cash transactions occur.

When it comes to measuring inflation, it's crucial to take into account the total costs of goods and services, which includes financing costs. These costs are not only significant in individuals' purchasing decisions but also have a direct or indirect impact on their inflation expectations.

The influence of financing costs on inflation measures is particularly evident in the case of high-value items like vehicles. Here, financing plays a substantial role in determining the total cost of an item. With the prevalence of credit used to finance almost all consumer expenditures, incorporating financing costs in inflation measures could provide a more accurate reflection of people's perception of the cost of goods. A recent study by economists from Harvard and the IMF demonstrated that reported inflation would be significantly higher if current measurements included financing costs.

The PCE measurement method, meanwhile, which policymakers focus on, is notably disconnected from the inflation experienced by the public. It only captures a little over half of what people actually pay. This disconnect is attributed to various factors, such as the exclusion of financing costs and the use of a non-price measure for owners' housing.

Additionally, roughly a third of the index includes administered prices for government-subsidized items (such as health care) or items people never pay for. The PCE index, a hybrid of market and non-market prices, is inherently ambiguous, and for it to track people's inflation would be more a matter of luck than design.

Analysts should call out the disconnect between people's and policymakers' inflation as it raises the possibility of a major policy blunder. That's because policymakers consider the current stance of monetary policy restrictive, wrongly comparing the official rate level to an inflation measure disconnected from people's inflation. However, comparing official rates to people's inflation, which includes financing costs, monetary policy remains easy—which is what the financial markets have been saying for some time.

The Federal Reserve Bank of Philadelphia’s state coincident indexes in April were mixed. Montana’s index rose a robust 1.2 percent from March, and three other states (Arizona, Maine, and Vermont) had gains above.5 percent, but six states, primarily from the middle parts of the nation, saw declines, with Ohio down .3 percent. Over the three months since January, 11 states, all across the nation, had increases of more than 1 percent, with Arizona up 1.8 percent. In contrast, 17 states had gains under .5 percent, with 4 of those experiencing declines. Over the last 12 months, Massachusetts was once again on top, but its increase of 3.6 percent---just edging out Arizona--was somewhat unimpressive in magnitude. There were four other states with increases higher than 3 percent. On the down side, five states had declines, with West Virginia down 2.4 percent (Montana was off 1.4 percent, despite its strong April), and 12 others had increases of less than 1 percent.

The independently estimated national figures of growth over the last 3 (.7 percent) and 12 (2.8 percent) months appear to be roughly in line with the state numbers.