In a post last week I took issue with the Trump administration’s claim–repeated ad nauseam in the media–that wages were rising at a 3.1% pace this past year, according to the Labor Dept. In my post I explained the 3 major reasons why wage gains are much lower, or even negative.
First, the 3.1% refers to nominal wages unadjusted for inflation. If adjusted even for official inflation estimates of 1.6%, the ‘real wage’, or what it can actually buy, falls to only 1.5%.
Second, the 1.5% is an average for all the 162 million in the US work force. The lion’s share of the wage gain has been concentrated at the top end, accruing to the 10% or so for the highly skilled tech, professionals, those with advanced degrees, and middle managers. That means the vast majority in the middle or below had to have gotten much less than 1.5% in order for there to be the average of 1.5%. More than 100 million at least did not get even the 1.5%. In fact, independent surveys showed that 60 million got no wage increase at all last year.
Third, the 1.5% refers to wages for only full time employed workers, leaving out the 60 million or so who are part time, temp, gig or others, whose wages almost certainly rose less than that, if at all. Other surveys noted in my prior post found wage gains last year only between -0.8% of 1.1%, depending on the study, and not the 3.1%.
But here’s a Fourth reason why even real wages are likely even well below 1.5%.
As I suggested only in passing only in my prior post, the 1.6% official US government inflation rate is itself underestimated. Not well known–and almost never mentioned by the media–is the fact that Labor Dept. stats do not include rising home prices at all in its estimation of inflation! Incredible, when home prices are among the fastest rising prices typically and always well above the official 1.6% or whatever. And the ‘weight’ of home prices in the budgets of most workers is approximately 30% or more of their total spending. So that weight means the effect on households is magnified even more. If appropriately included in inflation estimates, housing prices would boost the reported inflation rate well above the official 1.6%. How much more? Some researchers estimate it would raise the official inflation rate of 1.6% to as high as 4%. (see the discussion n the August 30, 2019 Wall St. Journal, p. 14).
If the inflation rate is higher, then the nominal 3.1% adjusts to a real wage even less than 1.5%.
If the inflation rate were 4%, not 1.5%, then real wages adjusted for inflation would be -0.9%. And when the ‘averaging’ and ‘full time employed’ effects are considered, real wages for the majority of US workers last year almost certainly fell by as much as -2.0% to 3.0%.
Since we’re talking about housing, here’s another official government stat related to housing that should be reconsidered since it makes US GDP totals higher than they actually are:
US GDP is over-estimated because gross national income (i.e. the income side to which GDP must roughly equal) is greatly over-stated. How is national income and therefore GDP over stated? The US Commerce Dept., which is responsible for estimating GDP, assumes that the approximately 50 million US homeowners with mortgages pay themselves a rent. The value of the phony rent payments boosts national income totals and thus GDP as well. But no homeowners actually pay a mortgage and then also pay themselves an ‘imputed Rent’, as it is called. It’s just a made up number. Of course there’s a method and a logic to the calculation of ‘imputed rent’, but something can be logical and still be nonsense.
Government stats–whether GDP, national income, or wages or prices, or jobs–are full of such questionable assumptions like ‘imputed rents’. The bureaucrats then report out numbers that the media faithfully repeat, as if they were actual data and fact. But statistics are not actual data per se. Stats are operations on the raw or real data–and the operations are full of various assumptions, many questionable, that are explained only in the fine print explaining government methodology behind the numbers. And sometimes not even there.
Here’s another reason why US and other economies’ GDP stats should be accepted only ‘with a grain of salt’, as the saying goes: In recent years, as the global economy has slowed in terms of growth (GDP), many countries have simply redefined GDP in order to get a higher GDP number. Various oil producers, like Nigeria, have redefined GDP to offset the collapse of their oil production and revenue on their GDP. In recent years, India notoriously doubled its GDP numbers overnight by various means. Some of ‘India Statistics’ researchers resigned in protest. Experts agree India’s current 5% GDP number is no more than half that, or less.
In Europe, where GDP growth has lagged badly since 2009, some Euro countries have gone so far as to redefine GDP by adding consumer spending on brothels and sex services. Or they’ve added the category to GDP of street drug sales. But any estimate for drug spending or brothel services requires an estimate of its price. So how do government bureaucrats actually estimate prices for these products and services? Do they send a researcher down to the brothel to stand outside and ask exiting customers what they paid for this or that ‘service’ as they leave? Do they go up to the drug pushers after observing a transaction and ask how much they just sold their ‘baggie’ for? Of course not. The bureaucrats just make assumptions and then make up a number and plug in to estimate the price, and therefore the service’s contribution to GDP. Boosting GDP by adding such dubious products or services is questionable. But it occurs.
The US Commerce Dept. that estimates US GDP has not gone as far as some European countries by adding sex and illicit drug expenditures. But in 2013 the US did redefine GDP significantly, boosting the value of business investment to GDP by about $500 billion a year. For example, what for decades were considered business expenses, and thus not eligible to define as investment, were now added to GDP estimation. Or the government asked businesses to tell it what the company considered to be the value of its company logo. Whatever the company declared was the value was then added to business investment to boost that category’s contribution to GDP. A number of other ‘intangibles’ and arbitrary re-definitions of what constituted ‘investment’ occurred as part of the re-definitions.
Together the 2013 changes added $500 billion or so a year to official US GDP estimates. The adjustments were then made retroactive to prior year GDP estimates as well. Had the 2013 re-definitions and adjustments not been made, it is probable that the US economy would have experienced three consecutive quarters of negative GDP in 2011. That would therefore have meant the US experienced a second ‘technical recession’ at that time, i.e. a second ‘double dip’ recession following the 2007-09 great recession.
The point of all these examples is that one should not blindly accept official government stats–whether on wages, inflation, GDP, or other categories. The truth is deeper, in the details, and often covered up by questionable data collection methods, debatable statistical assumptions, arbitrary re-definitions, and a mindset by most of the media, many academics, and apologists for government bureaucrats that government stats are never wrong.
Dr. Rasmus is author of the forthcoming book, ‘The Scourge of Neoliberalism: Economic Policy from Reagan to Trump’, Clarity Press, October 2019. He blogs at http://kyklosproductions.com and podcasts from his Alternative Visions radio show are available at http://alternativevisions.podbean.com.and tweets @drjackrasmus. His website is