Tag Archives: economic growth

Imports Do Not Subtract From GDP: Econ 101

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Chart 1

A.  Introduction

Trump has undermined what had been a strong US economy more quickly than most expected.  The BEA released on April 30 its initial estimate (what it labels the “advance estimate”) of the growth in GDP in the first quarter of 2025.  The economy contracted by 0.3% at an annual rate.  Real GDP grew at solid – indeed excellent – rates while Biden was in office.  The economy grew by 6.1% in 2021 as it emerged from the Covid crisis – faster than in any year since 1984 – and by 2.5% in 2022.  It then grew at a rate of 2.9% in 2023 and 2.8% in 2024.  While the GDP estimate for the first quarter of 2025 will be revised as additional data becomes available in the coming months, this is a terrible start for the new administration.

The cause of this fall in GDP in the first quarter of the Trump administration has been misinterpreted by many.  Prominent among them was Peter Navarro, the primary trade advisor in the White House.  In an interview on CNBC, Navarro asserted:

“when you strip out inventories and the negative effects of the surge in imports because of the tariffs, you had 3% growth.”

No:  Output did not grow.  It fell at a 0.3% rate.  There was indeed an extraordinary surge in imports.  Trump began to impose major tariffs on imports soon after taking office, with a promise of far higher rates to come.  And indeed, on April 2 he announced extraordinarily high (and highly variable) tariff rates on every “country” in the world (including one occupied only by penguins), only to back down on April 9, saying they would be postponed for 90 days.  In anticipation of what might come, imports of goods and services rose in the first quarter of 2025 at an astounding 41% annualized rate and imports of goods only (which can be stored) rose at a 51% rate.

But an increase in imports does not – in itself – affect the calculation of GDP.  GDP is a measure of domestic production (that is what the D stands for in GDP:  Gross Domestic Product).  Domestic production is what it is in the accounting regardless of how much is imported.

The confusion of Navarro and many in the news media stems from the formula that all are taught in an introductory Econ 101 macroeconomics class:

GDP = Consumption + Fixed Investment + Investment in Inventories + Exports – Imports

(where government consumption and investment can be combined with private consumption and investment, which we will do here for simplicity).  Imports are subtracted out at the end of this formula because Consumption, Fixed Investment, Investment in Inventories, and Exports all include the imports that help supply (directly or indirectly) these components of demand.  That is, Consumption (for example) includes consumption of domestic production as well as consumption of whatever is imported and used for that purpose.  And similarly for the other demand components.  Total Imports must then be subtracted out (as it is at the end of the formula) to arrive at what domestic production was.  That domestic production is GDP.

While it is easy to see why there would be such a mistake in the interpretation of how GDP is determined, there is no excuse for policy officials as well as journalists who write on economic issues to make such a mistake.

I have discussed before on this blog how GDP is estimated (see here and here).  But given this widespread misinterpretation of the 2025Q1 figures, it is worth reviewing the issue again.  That will be covered in the first section below.  The section that follows will then discuss the new GDP estimates themselves, and what those figures are telling us about how the economy has responded to the new Trump administration.  This concrete example will also help to reinforce the understanding on how imports enter.

The concluding section will then briefly look at what is in prospect for the GDP figures, both in the coming months and beyond.  While the economy is probably not yet in a recession, the policies of the new Trump administration (and its chaotic implementation) make it increasingly clear that the US will soon enter into a recession, unless Trump quickly reverses what he is doing.  And there is little likelihood of Trump doing that.

B.  Econ 101:  What GDP Means and How it is Estimated

Numerous news sources (as well as the official White House press release) misinterpreted the impact of imports on the GDP estimate for the first quarter of 2025.  As one example among many, the CNBC report on the GDP figures stated:

“Imports subtract from GDP, so the contraction in growth may not be viewed as negatively given the potential for the trend to reverse in subsequent quarters. Imports took more than 5 percentage points off the headline reading.”

Which is wrong.

GDP is an acronym for Gross Domestic Product.  “Product” means what is produced; “Domestic” means what is domestically produced; and “Gross” refers to the gross level of investment being counted rather than investment net of an estimate of depreciation (the latter measure of investment would then lead to Net Domestic Product, or NDP).

So how is GDP estimated?  As was discussed in the earlier blog posts referred to above, the BEA (the government agency that produces the GDP accounts) does this in three different ways.  In principle, all three should lead to the same estimate for GDP.  Because they are all estimates based on surveys and other statistics, they don’t although they should be close. There will always be statistical noise, and the three different estimates serve as a good check on each other to help find whether a mistake was made somewhere.

One approach is to estimate domestic production directly – sector by sector.  However, data for this is the most difficult to come by, and the first BEA estimate of GDP by this method is only provided three months after the end of a calendar quarter, i.e. in late June for the January to March quarter.  A second approach is to estimate domestic production by the incomes generated.  Since whatever is produced and sold will be reflected in incomes (in the wages of the workers employed, and then in the profits that remain following the payments for all the inputs used in production plus the wages paid), this should in principle also sum to GDP.  The BEA provides its first estimate of GDP using this approach (which, to limit confusion, it labels Gross Domestic Income, or GDI) two months after the end of a calendar quarter, i.e. in late May for the January to March quarter.

The third approach – and the one most commonly considered when GDP is referred to – is to estimate GDP from the uses of whatever is produced.  Whatever is produced is used, and if those uses can be estimated, this can be used to arrive at an estimate of what is produced, i.e. GDP.  The BEA can also provide a reasonable estimate of GDP this way relatively quickly after the end of each calendar quarter.  It issues its initial estimate one month after the end of each calendar quarter, i.e. in late April for the January to March quarter.  While the estimate will be revised as more data become available in the subsequent months, it is this estimate of GDP that receives the most attention as it is the first to be released.  Keeping track of the various demands for production is also important in a modern economy since we know from Keynes that production (up to a limit set by full employment) will largely follow from what the demands are.

This estimate is also built around the well-known equation referred to in the introduction above.  Starting with the simplest form in order to make clear that GDP is a measure of domestic production and not of demand, consider an economy where there is no foreign trade.  The equation is then:

GDP = Consumption + Fixed Investment + Investment in Inventories

The final uses of (the final demands for) goods and services are that they are either consumed or invested.  But what is consumed or invested in a period will normally differ from what is produced.  The simple trick, then, is to include along with the final demands the amount that is added to inventories (if production exceeds the sum of the final demands in the period) or taken out of inventories (if production falls short of the sum of the final demands in the period).  Hence by adding the net change in inventories (inventory accumulation, which is an investment) to the final demands for goods and services, one will arrive at what was produced in that period.  (Note that the terms “additions to inventories”, “investment in inventories”, and “accumulation of inventories” all refer to the same thing and are used interchangeably.)

Simple, although it can easily lead to the mistake of treating the demand for goods and services as GDP, when GDP is in fact the production of goods and services.

We can add foreign trade in goods and services to this.  There will be exports (also a final demand for goods and services) as well as imports.  Imports are an additional source of supply of goods and services that add to what is domestically produced.  Putting the supply of goods and services on the left and the demand for goods and services on the right, one has:

Supply of goods and services = Demand for goods and services

GDP + Imports =  Consumption + Fixed Investment + Investment in Inventories + Exports

The supplies of goods and services – whether from domestic production (GDP) or foreign production (Imports) – are used to meet the final demands for Consumption, Investment, and Exports, along with any accumulation of inventories if the total supplied exceeds the final demands (or decumulation of inventories if final demands exceed supplies).

Moving Imports to the right side of the equation, one then has the well-known:

GDP = Consumption + Fixed Investment + Investment in Inventories + Exports – Imports

It is important to keep in mind that imports typically enter indirectly, as an input to what is being produced and thus enabling a greater overall supply.  But one cannot map what share of Consumption, say, came from domestic supply and how much from foreign supply.  Imports are a resource that enables the nation to provide more.  How can one know, for example, whether a gallon of fuel, say, that was imported was used to help produce an item for consumption, or an item for investment, or an item for exports, or was added to inventories?  And even if the imported item can be individually identified, the complex nature of multi-level production (where intermediate goods produced can be used for a variety of different final goods) often makes it impossible to trace what an imported item ended up being used for.

As a result, the BEA cannot produce individual estimates of how much of Consumption, say, came from domestically supplied items and how much came from items produced with imports as a resource.  All it can provide are estimates of each of the demand components (including any addition to – or subtraction from – inventories), and then subtract total imports from the total demands to arrive at an estimate of what domestic production (GDP) was.

Imports in this accounting thus do not subtract from GDP, even though numerous news sources (and Trump officials) asserted precisely that.  If imports had been $1 billion higher, say, then there would have been $1 billion more in Consumption, or in Fixed Investment, or in Investment in Inventories, or in Exports (or some combination).  Subtracting that extra $1 billion at the end of the equation then leaves GDP exactly the same.

This is all accounting, or as economists refer to it, national income accounting.  Domestic production – GDP – did indeed fall at an annual rate of 0.3% in this initial estimate of GDP for the first quarter of 2025.  This was a sharp reduction from the strong and steady growth the country had enjoyed under Biden.  The country had nothing close to “3% growth”, as Peter Navarro wrongly asserted.

The figures for GDP and the components of demand that sum to GDP nevertheless acted in highly unusual ways in this first quarter of the Trump administration.  The next section of this post will examine those.

C.  GDP and Its Demand Components in the First Quarter of 2025

As noted before, the GDP estimates released by the BEA on April 30 are its initial or “advance” estimates of GDP and related figures in the National Income and Product Accounts.  Updated estimates based on more complete data will be provided with the second estimate in late May and again with the third estimate in late June. These estimates will likely differ to some degree from these initial estimates.

Historically, the average change in the estimated growth rate of GDP (in percentage points) from BEA’s advance estimate to its second estimate has only been 0.1% points, and also only 0.1% from the advance estimate to the third estimate.  But one has to keep in mind that those are changes on average, where sometimes the initial estimates are revised up and sometimes revised down.  The very small average difference (only 0.1%) means that there is little bias in the initial estimates historically:  they are as often revised up as revised down.  In absolute terms (i.e. ignoring whether the revisions were positive or negative), the average change from the advance estimate to the second estimate was 0.5%, and from the advance estimate to the third estimate was 0.7%.  Such changes are more significant, and there are even larger changes in periods when, such as now, the economy is going through major disruptions.

Due to the far from normal increase in imports resulting from uncertainty on what tariffs Trump will impose (which appear often to be based on a whim, and announced on social media posts), it is certainly possible and indeed likely that the GDP estimates for 2025Q1 will be revised by more than they normally have in the past.  Investment in inventory accumulation is especially difficult to estimate, and may see an especially large revision.

It is therefore quite possible that once revisions to the accounts are made based on more complete data, growth in real GDP will shift from the small negative (-0.3%) in the current estimate to possibly a small positive.  This should not, however, be viewed as terribly significant.  There is no chance that the revisions will bring growth anywhere close to the almost 3% rates the nation enjoyed under Biden in 2023 and 2024.  So while the analysis here has to be based on the figures released in the advance GDP estimates, the basic story should hold as the second and third estimates of GDP are released in the coming months.

This table summarizes the key figures:

Growth in Real GDP and Its Demand Components

2025Q1 vs 2024Q4 % change $ billion change
Real GDP -0.3%   -$16.2
Personal Consumption  1.8%   $72.4
Gross Fixed Investment  7.8%    $80.9
  o/w Information Processing Equipment 69.3%   $73.6
Investment in Inventories  $131.2
Government Expenditure -1.5%  -$14.6
  Federal Government -5.1%  -$19.8
    o/w Defense Spending -8.0%  -$18.0
  State & Local Government   0.8%     $4.9
Exports  1.8%   $11.6
Imports 41.3% $333.3
Seasonally adjusted annual rates; 2017 constant$

Starting from the top:  Domestic production in real terms (real GDP) fell at an annual rate of 0.3%.  In dollar terms (in constant 2017 prices) the fall was $16.2 billion.  This change in domestic production was far surpassed by the increase in imports (foreign production) of $333.3 billion in real terms, as individuals and businesses sought to get in front of Trump’s promised tariffs.

Much of the increase in imports likely went into the increase in inventories, which rose by $131.2 billion in real terms.  As discussed above, it is not possible to estimate for each of the demand components (the change in inventories being one) how much can be attributed to domestic supplies and how much to imported supplies.  It is likely, however, that with such a sizeable jump in imports (41.3% at an annual rate), a substantial share went into inventories.

But a significant share of the increase in imported supply was also used directly or indirectly for the final demand components of GDP.  As discussed before, each of these reflects the use of a combination of both domestic and imported supplies.  Take Gross Fixed Investment, for example.  It rose at the very fast rate of 7.8% in annual terms.  If one digs into the reported components for this, one will see (in Table 3 of the BEA release) that fixed investment in Information Processing Equipment rose by $73.6 billion in the quarter (69.3% at an annual rate).  That one component of investment accounted for over 90% of the overall increase in Gross Fixed Investment in the period (which was $80.9 billion).  Investment in Information Processing Equipment had not been booming before:  It in fact fell by $10.0 billion in the prior quarter, rose by $21.6 billion in the quarter before that, and rose by $9.7 billion in the quarter before that.

The highly unusual behavior in such investment in the first quarter of 2025 coincided with the uncertainty generated by Trump’s tariffs.  And Information Processing Equipment is the type of equipment that firms will often import directly and have installed.  It will thus count as part of Gross Fixed Investment in the GDP accounts.  Fixed investment rose in the first quarter of 2025, but it is likely that this primarily reflected a rush to import specialized equipment before even higher tariffs (whatever they will be) are imposed by Trump.

There was likely a similar factor that affected the Personal Consumption component, although to a lesser extent than what was seen for Fixed Investment.  Personal Consumption rose by 1.8% in real terms at an annual rate.  That is not all that high (it rose at a 4.0% rate in the fourth quarter of 2024 – the last quarter of the Biden administration – and by 3.7% in the third quarter of 2024).  But at least part of this would have come from businesses and individuals importing items before prices go up due to Trump’s tariffs.  Indeed, it is possible – and indeed likely – that net of what was imported to supply this demand (directly or indirectly), the domestic supply for Personal Consumption may well have decreased.  As a personal example, my wife and I decided to go ahead and buy now a new Apple iMac computer (which is assembled in China) for our home use.  Prices may soon skyrocket.  That purchase counted in the Personal Consumption category of the GDP accounts.

It is therefore a mistake to assert, as Trump officials did, that domestic production grew at a healthy rate.  The Navarro quote cited above refers to 3% growth, and the White House press release (that Navarro may have helped prepare) similarly says:  “Core GDP grew at a robust 3.0%.  This signals strong underlying economic momentum that occurred after President Trump’s inauguration.”  What they both appear to be referring to is what the BEA calls “Final sales to private domestic purchasers”.  It grew at a 3.0% rate.  It is defined as the growth in Personal Consumption and in Gross Fixed Investment together.  But as just discussed, much and possibly more than all of that growth reflected the surge in imports before tariffs go up.  Navarro (and others as well) do not realize that those items in the GDP accounts include imports.

The other items in the demand components of the GDP accounts did not change as much.  Federal government expenditures on goods and services (i.e. federal government consumption expenditures and gross investment) fell by $19.8 billion in annual terms (5.1%).  But this cannot be attributed to cuts pursued by Elon Musk and his DOGE group.  Of the $19.8 billion fall, $18.0 billion was due to a reduction in Defense Spending.  That has not been a DOGE focus.  Rather, with a change in administrations, decisions on payments and on new procurement contracts are often delayed as the new team comes in.

Finally, a technical note:  Some may have noticed that if one adds up the $ changes in the above table for Consumption, Investment, and so on in the well-known GDP equation, the sum comes to a dollar change of -$51.8 billion.  This is more than the reported fall of -$16.2 billion.  The reason for this difference is that the BEA uses chain-weighted price indices to deflate the nominal estimates of the GDP demand components.  (For a discussion of chain-weighted indices, in the context of how the CPI and Personal Consumption Expenditures – PCE – price deflators are calculated, see this earlier post on this blog.)

Chain-weighted price indices are based on weights derived from expenditure shares of individual items in the current period and in the prior one.  The BEA uses chain-weighted price indices for all the price deflators it calculates.  A property of chain-weighted price indices is, however, that a sum (such as real GDP here) will not necessarily be equal to the sum of the individual components (such as demand components here) in real terms.  The sum will in general be close, but the BEA warns readers that they will not be the same.

D.  Prospects and Conclusion

In the near term, and as noted above, the BEA will issue its second estimate of the GDP accounts for 2025Q1 in late May and its third estimate in late June.  It will then start the quarterly cycle again with its advance estimate of the GDP accounts for 2025Q2 in late July, and so on.

With the major disruptions to the economy due to Trump, there will likely be significant changes in a number of the figures when the second and third GDP estimates are released.  The import estimates will likely not be among them (despite the 41.3% jump in the period, or $333.3 billion) as the foreign trade accounts are fairly well known in real time (as imports are recorded as they go through customs).  But investment in inventories is much more difficult to estimate.  The BEA advance estimate is that they rose by $131.2 billion (in real terms), but I would not be surprised if, in the updated figures based on more complete data reports, inventory accumulation turns out to be higher.  If so, then the estimated growth in GDP will be higher.  If (purely for the sake of illustration – I am not predicting this), investment in inventories turns out to be $50 billion higher than shown in the advance estimate (i.e. $181.2 billion rather than $131.2 billion), and all else is the same as estimated now, then GDP would have grown at a +0.6% rate rather than fallen at a -0.3% rate.

A change of such a magnitude would not be surprising.  GDP growth would still be low, and far below the growth rates achieved when Biden was in office, but possible.  But the basic underlying story would remain that businesses urgently brought in imports out of concern (and great uncertainty) about how high tariffs might soon be.

The continued incoherence in Trump’s policies does not augur well for the economy for the rest of the year either.  This was demonstrated on April 2 as Trump announced (on what he called “Liberation Day”) his so-called “reciprocal tariffs” at rates as high as 50% (and higher for China).  Businesses were in shock, and it took some time before anyone could figure out how Trump’s rates had been set.  They were not at all reciprocal, but rather calculated based on the bilateral trade deficit of the US (for goods only, i.e. excluding trade in services) divided by US imports of goods from the country.  Trump then backed down a week later, and said he would postpone them for 90 days while a series of deals with countries were negotiated.

Businesses are now basically frozen.  They cannot decide on what investments to make – if any – as they cannot know what tariff regime they will be operating in.  They have also seen that Trump is more than willing to use the powers of the state to punish companies that upset him, and to take actions that are in blatant violation of the law (knowing that the judicial system takes time to act, and that once it does act they will be faced with a fait accompli).  A sound legal system that all must abide by – including a president – is fundamental to any modern economy.

Households are similarly wary.  Consumer expectations have plunged, and both the index of consumer sentiment of the University of Michigan and the Consumer Confidence Index of The Conference Board have dropped each and every month of Trump’s term in office from a peak in November/December 2024.  It is especially surprising that such indices of consumer sentiment have fallen so much so fast even though the unemployment rate has been steady.  Firms are not yet laying off workers, but rather remain basically “frozen”, as they wait for greater clarity on what will happen to the economy.  Keeping workers on the payroll while GDP falls means, however, that labor productivity has gone down.  One can easily calculate that GDP per worker employed fell at a 1.6% annual rate in 2025Q1.  This also puts pressure on costs and hence prices.

On top of this, Trump through Musk and his DOGE team have sought to slash federal government expenditures.  The reality is that not much has in fact been cut thus far, but this may soon change.  As of May 8, federal government spending in CY2025 was $133.50 billion higher than it was as of the same date in CY2024.  The day before Inauguration Day, it was $13.9 billion lower.

But eventually the Trump/Musk/DOGE cuts may materialize.  The US economy will then be faced with lower government expenditures, lower private investment as businesses hold back due to the uncertainty, and lower personal consumption spending as households fear what will come next from this administration.  All of this is a recipe for a downturn.  And once unemployment starts to rise, conditions can quickly deteriorate.

At the same time, Trump’s trade wars are now causing major supply disruptions.  Imports from China have basically shut down, and the major US West Coast ports were seeing a steep drop in vessel traffic already in mid-April.  There may soon be empty shelves at US stores, which is certainly unlikely to boost consumer confidence.  As I write this, the Trump administration has just announced that it is backing down on its confrontation with China, and that it will reduce its tariffs on imports from China to “just” 30% for the next 90 days.  But such tariffs are still high and will have a major impact on costs and hence prices.

Along with the other tariffs Trump has imposed (10% on everyone, 25% on steel and aluminum, 25% on autos and auto parts with some exceptions, and a variety of others), costs and hence prices will go up.  The Fed may thus not be able to reduce interest rates in response to a downturn.  Not much commented on in the recent BEA report was that the Fed’s primary indicator of inflation (the deflator calculated by the BEA for Personal Consumption Expenditures excluding food and energy, i.e. the core PCE deflator) already rose at a 3.5% rate in the first quarter of 2025.  This is well above the Fed’s 2.0% target, and was an increase from a 2.6% rate in the last quarter of 2024.  The overall PCE deflator rose at a 3.6% rate, and the GDP deflator rose at a 3.7% rate.  And this was before the numerous new and/or higher tariffs Trump imposed since the start of April.

An economic recession is thus likely soon.  How long it will last will depend on how soon Trump recognizes the harm he has caused to the economy and reverses what he has done.  But Trump has never shown much of a willingness to recognize his mistakes, and will certainly never publicly acknowledge that they were mistakes.  The possibility of an extended downturn is high.

The Economic Record of Biden and Trump Compared to That of Presidents Since Truman

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Chart 1

A.  Introduction

The BEA released on January 30 its first estimate (what it calls its “Advance Estimate” ) of GDP in the fourth quarter of 2024.  This provides the first good estimate of GDP growth during Biden’s full term in office.  We can now see how that growth compares to growth during the terms of other US presidents, and in particular Trump.  Trump has repeatedly claimed that “we had the greatest economy in the history of the world” when he was president, while “Under Biden, the economy is in ruins”.

We now have concrete statistics on this.  Like much of Trump’s bombast, there is no truth to his claims.  This post will examine what the record has been for growth in per capita real GDP, for unemployment, and for inflation, comparing the record we now have for Trump and Biden to that of the other post-World War II presidents.

B.  Growth in Per Capita Real GDP

The chart at the top of this post shows what most take as the broadest measure of economic performance:  the growth in real GDP per capita.  The figures were calculated from BEA National Income and Product Account (NIPA) data (as updated on January 30), accessed via FRED.  They show the average rate of growth in per capita real GDP for each four-year presidential term going back to Truman’s second term (as quarterly GDP data only began to be estimated in 1947).  The presidential terms are defined from the first quarter of their inaugural year to the last full quarter of the final year of their term.

Per capita real GDP grew at an average annual rate of 2.5% under Biden, which is the highest in any presidential term since Clinton’s second term.  And it is almost twice as high as the average rate of growth of just 1.3% per year during Trump’s first term.  Compared to the 19 presidential terms since Truman, Biden would have been sixth (i.e. in the top third) while Trump would have been thirteenth (on the border of the bottom third).

Trump claims that this poor growth performance should be blamed not on him but on the onset of the Covid pandemic in 2020.  Covid would, indeed, have been difficult to manage by even the most capable of administrations.  The Trump administration was, however, certainly far from the most capable.  His mismanagement of the pandemic (including, for example, his repeated claim that it would simply “go away” on its own, his lack of leadership in not calling on his supporters to wear masks, his promotion of wacky “cures” that had no basis in actual evidence, and much more) made things far worse than they would have been.

But even if we allow Trump to claim a mulligan (as he reportedly often demands in his golf game) and leave out 2020, growth during Trump’s first three years in office would have averaged 2.2% per year – still less than what it has been under Biden.  Growth in Trump’s first three years would also have been well less than in Clinton’s second term (when per capita real GDP grew at a 3.1% rate), as well as under Reagan (both terms), Kennedy and Johnson (both terms), and Truman.  It would have been about the same as growth during Clinton’s first term, Carter’s term, and that of Nixon.  Still nothing special.

In other words, even when we leave out the chaos of 2020 during the Covid pandemic, Trump’s economic record was middling at best – with substantially slower growth than under a number of post-World War II presidents.  It was certainly far from the “greatest” in history.  And for his full term, Trump’s growth record ranks at about the bottom-third mark.

C.  Unemployment Rate

Another common measure of economic performance is the unemployment rate:

Chart 2

These figures were calculated from BLS data (via FRED), and are the simple averages of the unemployment rate over presidential terms from January of their inauguration year through to December of their final year.  (One could reasonably argue that the period should start only in February of the inauguration year and end in January, but that one month shift would not lead to a significant difference in the four-year average.  Plus, as I write this I do not yet have the unemployment statistic for January 2025.)

Unemployment under Biden has been exceptionally low, at an average of just 4.2% over his full term.  It was well below the average rate under Trump (5.0%).  Indeed, the average unemployment rate under Biden was lower than under any president since Johnson’s full term in office (1965 through 1968, when it averaged 3.9%), although the average rate in Clinton’s second term (4.4%) was not too much higher.  Over the full post-World War II period, Biden’s record on unemployment was the second-best out of the 19 presidential terms.  Trump’s record was tied with two others for the sixth through eighth ranking.

Again, if we give Trump a mulligan and count only the first three years of his term, the average unemployment rate would have been 4.0%.  Quite good, although the unemployment rate averaged an even lower 3.8% during Biden’s final three years in office.  Also, and as noted in an earlier post on this blog, the unemployment rate during Trump’s first three years in office simply reflects a continuation of the same downward trend it had been on during Obama’s presidency.  What can be said is that in his first three years in office, Trump did not wreck the path the economy was following during Obama’s second term in office (with GDP growth also similar).  The wreck then came in Trump’s fourth year.

D.  Inflation

The main criticism directed at Biden’s economic record was the increase in the rate of inflation (with data from the BLS via FRED):

Chart 3

As measured by the CPI, inflation during Biden’s term averaged 4.9% at an annual rate, the highest since Reagan.  Inflation rose sharply in much of the world following the supply and other disruptions arising from the 2020/21 Covid pandemic, with supply chain issues continuing to mid-2022.  The Russian invasion of Ukraine in February 2022 also added to price pressures as the prices of oil, natural gas, wheat, and other commodities soared for a period.  Overall consumer prices rose in the US, as they did in other developed OECD economies (and by more than in the US in most of them).

Inflation came down sharply (as well as suddenly) in the US in mid-2022 as the supply chain issues were resolved.  Since then inflation has remained above the Fed target of 2% solely because of (not just largely because of, but entirely because of) the rising cost of housing.  Rising housing prices are certainly important – and I plan to address the issue in an upcoming post on this blog – but to address inflation effectively one should be clear on the cause.  One should also recognize that the mirror image of the rising cost of housing is that homeowners are enjoying rising home values, and that two-thirds of US households own their homes.  Those two-thirds are benefiting from the rising values.

Inflation as measured by the CPI was 1.9% over Trump’s first term in office.  This was basically similar to the average rate of inflation since Clinton’s second term, although a bit below where it had been from Clinton through Obama’s first term.  And it was higher than inflation in Obama’s second term (which was arguably too low).

The Trump record on inflation was helped by especially low inflation in 2020 due to the Covid crisis.  With much of the economy shut down, the overall price index in fact fell.  This is highly unusual for the seasonally adjusted rates.  The seasonally adjusted overall CPI fell in each month from March to May, and it was not until August that it returned to where it had been in February.

Particularly noteworthy was the drop in the price of crude oil.  In terms of today’s prices (i.e. the CPI of December 2024), the price of the benchmark West Texas Intermediate crude oil fell to just $23.19 per barrel in April 2020.  This was below its inflation-adjusted price of $25.36 in July 1973 – just before the first OPEC oil price increase – and the lowest in real terms of any month since then except for the single month of November 1998 (when oil prices fell to $21.59 in a brief but intense international financial crisis following from Russia’s financial collapse that year).

A crisis – such as the one brought on by Covid in 2020 – that leads to a sharp and sudden drop in demand can certainly lead to low inflation for a period.  Prices will often then bounce back as the economy recovers.  But one should certainly not want to cause a crisis – where in 2020 the unemployment rate shot up to the highest it had been since the Great Depression of the 1930s – to keep inflation low.

E.  Conclusion

Assessing the economic performance of a presidential term by just three measures is simplistic, of course.  There is much more going on.  These are also aggregate measures, and the measures of relevance to any individual can be quite different.  Distribution matters when looking at growth in GDP per capita; the unemployment rate matters most to those who are at risk of losing their jobs; and what matters in terms of price increases will vary by person (where, for example, increases in home prices are a benefit – not a cost – to the two-thirds of US households who own their own homes).

Still, the three measures of growth in real output, of the unemployment rate, and of consumer price inflation are important and are a common focus in assessments of the economic record of a period.  They receive a good deal of attention in the press and by the public.

One can also question whether the record of any president should be measured by periods that begin and end with the inauguration date.  It can reasonably be argued that the record should begin only three months later, or six months later, or even twelve months later, as new presidential policies and management will only begin to have an influence with a lag.  While there is certainly some lag, what that lag might be is not at all clear.  Also, that lag might be different at different times and for different conditions, depending on the state of the economy when the president takes office.

Given the impossibility of determining what the appropriate lag might be, it is probably fairest to begin the measurement from the date the president takes office.  But one could argue that it should be later.

More fundamentally, some might argue that the influence a president has on economic developments is limited.  No doubt there are limitations, with many underlying economic forces that a president alone cannot affect – at least in the near term.  But while recognizing such limitations, it is too extreme then to say that a president has no influence.  Policy matters, and it is reasonable to assess a president’s success in determining the right policies, getting them passed and implemented, and then seeing the outcome.

Recognizing these limitations, it is nonetheless clear that the economic record of Biden was relatively good.  Growth was strong, unemployment was low (the lowest of any presidential term since Lyndon Johnson), and consumer price inflation – while relatively high – was largely a consequence of the post-Covid disruptions.  And inflation came down from mid-2022 to target levels or below, with the significant exception of housing.

Trump’s economic record in his first term, in contrast, was relatively poor.  It was not the worst among the post-World War II presidential terms, but in terms of growth it was around the bottom third mark.  It was around the middle if one is generous and leaves out the collapse in 2020 due to Covid.  Unemployment and inflation during his first three years in office were relatively good (although not the best compared to others).  But on each, Trump can basically be commended for not wrecking the path they were on that he had inherited from Obama.  And then 2020 came.  It was certainly not “the greatest economy in the history of the world”.

We will now see what Trump’s record will be in his second term.  Trump is now inheriting from Biden (as he had from Obama) an economy where GDP is growing at a strong rate, unemployment is extremely low, and inflation is low.  But while in his first term Trump did not – during his first three years – upset too much the strong path the economy was on, Trump is now moving much more aggressively in his second term.  As I write this, he has just issued orders that from February 4, the federal government will charge US importers additional tariffs of 25% on all imports from Canada (other than 10% on imports of oil), an additional 25% on all imports from Mexico, and an additional 10% on all imports from China (all additional to whatever the tariffs were before, which varied by item)

Such new tariffs are not just costly for the US firms and ultimately consumers who will pay them, the ones on Canada and Mexico are also in clear violation of the USMCA free trade treaty (better known as NAFTA 2.0, as it was largely the same as the original NAFTA treaty).  The first Trump administration negotiated the USMCA treaty, and Trump himself signed it together with Canada and Mexico in 2018.  While Trump is now claiming the 25% tariffs are being imposed due to some new “emergency”, that justification strains credulity.  What is happening at the border now is not fundamentally different from what was happening in 2018 when the treaty was signed.

If the tariffs are not soon lifted, they will cause significant damage to the US economy.  But this is just the start, and it looks like Trump is imposing such tariffs (including on Canada – probably the closest ally of the US – at least until now) to show no country is exempt from his attempt at bullying.

We will see what results.

Why Voters Are Upset 2: The Proximate Causes of the Underperformance of the US Economy Since the 2008 Crash

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Chart 1

A.  Introduction

The previous post on this blog described the slowdown in US growth since the 2008 crash.  GDP fell sharply in the second half of that year – the last year of the Bush administration – due to the crisis in home mortgages leading to a broad collapse in the financial markets.  It led to what has been termed the “Great Recession”.  But unlike in past recessions, GDP never recovered to its previous trend path, even though the unemployment rate fell to lows not seen since the 1960s.  GDP remains well below that previous path today.  The chart above shows how that gap opened up and has persisted since 2008.

The question is why?  The unemployment rate had averaged 4.6% in 2007 – the last full year before the 2008/09 economic and financial collapse.  While the pace of the recovery from the collapse was slowed by federal budget cuts, the economy eventually did return to full employment.  The unemployment rate was at or below 5% in Obama’s last year in office and then continued on the same downward path during the first three years of the Trump administration.  It averaged 3.9% in 2018 and 3.7% in 2019, and hit a low of 3.5% in September 2019.  After the brief but sharp 2020 Covid crisis, the unemployment rate then went even lower under Biden, reaching a low of just 3.4% in April 2023 and averaging just 3.6% in 2022 and again in 2023.  The unemployment rate has not been this low for so long since the 1960s.

In prior times, GDP would have returned to the path it had been on once the economy had recovered to full employment, with resources (in particular labor resources) being fully utilized.  But this time, despite unemployment going even lower than it had been before the downturn, GDP remained far below the path it had been on.  By 2023, real GDP would have been almost 20% above where it in fact was, had it returned to the previous path.  That is not a small difference.

That is, while the economy recovered from the 2008 collapse – in the sense that it returned to the full utilization of the labor and other resources available to it – economic output (real GDP) with that full utilization of resources was stubbornly below (and remained stubbornly below) what it would have been had it returned to its prior growth path.  The economy had followed that path since at least the late 1960s (as seen in the chart above).  Indeed, that same growth path (in per capita terms) can be dated back to 1950 (as the previous post on this blog showed).

This post will examine the proximate factors that led to this.  The post will look first at the growth in available labor.  It has slowed since 2008.  This has not been due to a fall in the labor force participation rates of the various age groups, as some have posited.  We will see below that holding those participation rates constant at what they were in 2007 (for each of the major age groups) would not have had a significant effect on labor force totals.  Rather, labor force growth slowed in part simply because the growth in the overall population slowed, and in part due to demographic shifts:  A growing share of the adult population has been moving into their normal retirement years.  It is not a coincidence that the first of the Baby Boom generation (those born in 1946) turned 62 in 2008 and 65 in 2011.

The second proximate factor is available capital – the machinery, equipment, and everything else that labor uses to produce output.  Capital comes from investment, and we will see below that net investment as a share of GDP has fallen sharply in the decades since the 1960s.  Overall net fixed investment fell by more than half.  This led to a slowdown in capital growth, and especially so after 2008.  There was an especially sharp reduction in public investment.  Since 2008, net public investment as a share of GDP has been only one-quarter of what it was in the 1960s.  It should be no surprise why public infrastructure is so embarrassingly bad in the US.  And net residential investment (as a share of GDP) is only one-third of what it was in the 1960s.  The resulting housing shortage should not be a surprise.

The third proximate factor is productivity.  Labor working with the available capital leads to output.  How much depends on the productivity of the machinery, equipment, and other assets that make up the capital, and that productivity grows over time as technology develops and is incorporated into the machinery and equipment used.  We will see that the rate of growth in productivity fell significantly after 2008.  Given the reduction in net investment and the consequent slowdown in capital accumulation after 2008, it is not surprising that productivity growth also slowed.

For a rough estimate of the relative importance of these three factors – labor, capital, and productivity – I developed an extremely simple Cobb-Douglas production function model to simulate what could be expected.  Despite being simple, it turned out to work surprisingly well both in terms of tracking what actual GDP was (for given employment levels) and in tracking the trend path for GDP given the trend paths of labor, capital, and productivity.

As noted above, the trend level of GDP in 2023 was almost 20% above what GDP actually was in that year – a year when unemployment was at record lows.  Despite being at full employment, the economy was not producing more.  Based on the Cobb-Douglas model, roughly a quarter of the shortfall can be attributed to a slowdown in productivity growth from 2007 onwards.  Of the remaining shortfall, about 60% can be attributed to a smaller stock of capital and 40% to a smaller labor force (both relative to what they would have been had they continued on the same trend paths that they had followed before 2008).

Section B of this post will examine the labor force figures.  Section C will look at what has happened to investment and the resulting growth in available capital.  Section D will then examine the Cobb-Douglas model used to estimate the relative importance of labor and capital both growing more slowly than they had before and the impact of slower productivity growth.  Section E will conclude.

As noted above, labor growth has slowed due to demographic changes as population growth has slowed and as the population has aged.  A rising share of the population (specifically the Baby Boomers) have been moving into their normal retirement years, and this has led to a slower rate of growth in the labor force.  There is nothing wrong with this, it depends primarily on personal choices, and there is no real policy issue here.

In contrast, there are important policy issues to examine on why investment has fallen in recent decades – and especially since 2008 – with the resulting slower rate of capital accumulation as well as slower productivity growth.  But the causes of this are complex, and will not be examined here.  I hope to address them in a subsequent post on this blog.

[Note on the data:  In each chart, I used the most detailed data available for that particular data series, i.e. monthly when available (labor force statistics), quarterly (real GDP), or annual (capital accumulation). The data are current as of the date indicated for when they were downloaded, but some are subject to subsequent revision.]

B.  Growth in the Labor Force

Growth in the US labor force has slowed, but by how much, when did this start, and why?  We will examine this primarily through a series of charts.  Most of these charts will be shown with the vertical axis in logarithms.  As you may remember from your high school math, in such charts a straight line will reflect a constant rate of growth.  The slope of the lines will correspond to that rate of growth, with a steeper line indicating a faster rate of growth.

The trend lines in the charts here (including in the chart at the top of this post) have all been drawn based on what the trends appear to be (i.e. “by eyeball”) in the periods leading up to 2008.  They were not derived from some kind of statistical estimation, nor from a strict peak-to-peak connection, but rather were drawn based on what capacity appeared to be growing at over time.  They were also drawn independently for aggregate real GDP (Chart 1 above), for growth in the labor force (Chart 2 below) and for growth in net fixed assets (Chart 10 below).  Despite being independently drawn, we will see in Section D below that a very simple Cobb-Douglas model finds that they are consistent with each other to a surprising degree, in that the predicted GDP trend corresponds to and can be explained by the trends as drawn for labor and for capital.

Starting with the labor force:

Chart 2

The US labor force grew at a remarkably steady rate from the early 1980s up to 2008.  Prior to the 1980s, it grew at a faster pace (a trend line would be steeper) as women entered the labor force in large numbers and later as the Baby Boomers began to join the labor force in large numbers in the early 1970s.

But then that steady rise in the labor force (of about 1.3% per annum before 2008) decelerated sharply.  The growth rate fell to only 0.5% per year between 2007 and 2023.  Why?

We can start with overall population growth:

Chart 3

Population, too, had grown at a steady pace prior to 2008.  But population growth then slowed.  In this context, it is not surprising to see that growth in the labor force also slowed.

But there is more to it than just this.  Before 2008, the US population had been growing at a similar rate as the labor force, thus leading to a fairly constant share of the labor force in the population (generally in the range of 50 to 51%):

Chart 4

But then, in 2008, the share of the labor force in the US population fell.  Growth in the labor force slowed by more than growth in the US population.  What were the factors behind that?

One assertion that is often made is that labor force participation rates fell.  At an aggregate level this is, almost by definition, true.  As a share of the US adult population (those aged 16 and over), the labor force participation rate fell from 66.0% in 2007 to 62.6% in 2023 (using standard BLS figures).  But one can be misled by focusing on the aggregate participation rate.  The overall participation rate came down not because those in various age groups became less likely to join the labor force, but rather because an increasing share of the population was aging into their normal retirement years.

The BLS provides seasonally adjusted figures for the labor force broken into three age groups: those aged 16 to 24, those aged 25 to 54, and those aged 55 or more.  Labor force participation rates are provided for each of these three groups, and one can calculate what the labor force participation would have been for each had the participation rate always been at that of 2007:

Chart 5

The line in red shows what the labor force then would have been, with the line in blue showing the actual labor force and the line in black the trend (the same trend as in Chart 2 above).  While it would have made a significant difference before the 1980s (as women were not participating in the formal labor force to the same degree then), between 2008 and 2023 it makes very little difference.  The labor force would have still fallen by about the same figures relative to its previous trend.

Rather, the labor force has been aging, with a growing share of the population now in the normal retirement years when labor force participation rates are low.  From the BLS numbers, one can work out the share of the population that are age 55 or older:

Chart 6

The share in the population of those aged 55 or older started to turn sharply upward around 1998.  They thus would have been 65 or older starting around 2008.  And as noted before, this is also when the first of the Baby Boomers (those born in 1946) would have started to reach their normal retirement age.

[Side note:  The discontinuities that one sees at various points in this chart are there because of adjustments made by the BLS in their control totals.  They adjust these control totals once new results are available from the decennial US population censuses.  They need such control totals for the shares of the various demographic groups since the labor force estimates come from its Current Population Survey (CPS), and as with any survey, control totals are needed to generalize from the sample survey results.  But the BLS does not then revise prior CPS estimates once the control totals are updated with each decennial census.  That then leads to these discontinuities.  For our purposes here, those discontinuities are not important.]

Labor force growth thus slowed from 2008 onwards.  This can be explained by basic demographics with an aging population.  This was not due to less willingness to participate in the labor force – an assertion one often sees.  Holding participation rates constant at what they were in 2007 for just three broad age groups led to no significant difference in what the labor force would have been.  Rather, people are just aging into their normal retirement years.

C.  Growth in Capital

Labor works with machinery, equipment, structures, and other fixed assets – which together will be referred to as simply capital – to produce output.  Those assets also reflect the technology that was available and economic (in terms of cost) when they were installed.  Those assets are acquired by investment, and it is important to recognize that net investment has fallen sharply over the last several decades.

This is not often recognized, as most analysts and news reports focus not on net investment but rather on gross investment.  Gross investment figures are provided in the GDP accounts that are released each month, and gross investment as a share of GDP has not varied all that much.  The decade-long averages for gross private fixed investment have varied only between 16 and 18 1/2% of GDP since the 1960s.

But the accumulated stock of capital does not arise simply out of gross investment but rather out of investment net of depreciation – i.e. net investment.  Less attention is paid to net investment figures, and estimating depreciation is not easy.  It is certainly not depreciation as defined by tax law, as tax law as written reflects a deliberate attempt to encourage investment by allowing firms to declare depreciation to be greater than it actually is (e.g. through accelerated depreciation).  Assigning a higher cost to depreciation will reduce reported profit levels and hence reduce what needs to be paid in taxes on that profit income.

For the GDP accounts (NIPA accounts) the BEA needs to record what actual depreciation was, not what depreciation as allowed under the tax code may have been.  The BEA estimates of this are carefully done and are the best available.  However, one still needs to recognize that these are estimates and that there are both conceptual and data issues when estimates of depreciation are made.

Based on the BEA estimates in the NIPA accounts, both public and private net fixed investment levels – as shares of GDP – have fallen sharply since the 1960s:

Chart 7

There are significant year-to-year fluctuations in the shares – especially in the private investment figures – as investment varies significantly over the course of the business cycle.  It falls in recessions and increases when the economy recovers.  The trends may thus be more clearly seen using decade averages of the net investment shares:

Chart 8

Total public and private net fixed investment fell from over 10% of GDP in the 1960s (and almost as much in the 1950s) to just 4.2% of GDP in the period from 2009 to 2023 – a fall of close to 60%.  Total private net fixed investment fell from about 7% of GDP in the 1950s, 60s, and 70s, to just 3.4% since 2009 – a fall by half.  Public net fixed investment fell even more sharply:  from over 3% of GDP in the 1960s to just 0.8% of GDP in recent years – a reduction of three-quarters (in the figures before rounding).  It should be no surprise why public infrastructure is so embarrassingly poor in the US.

The chart also shows private net fixed investment broken down into the share for investment in residential assets (housing) and non-residential assets.  Much of the decline in private net fixed investment was driven by an especially sharp reduction in investment in housing. Still, private investment in assets other than housing has also been cut back substantially, with a reduction of over 40% compared to where it was in the 1980s.

Based on their net fixed investment estimates and other data, the BEA also provides estimates of how the accumulated stock of real fixed capital has changed over time, with those levels shown in terms of quantity indices.  The resulting rates of growth in accumulated capital (which the BEA refers to, more precisely, as the net stock of fixed assets) have declined sharply with the reductions in the net investment shares:

Chart 9

In the 1960s, the annual growth rates varied between 3.5% (for residential fixed assets) and 4.4% (for public fixed assets).  But in the period from 2009 to 2023 those growth rates had fallen to just 1.9% for private non-residential fixed assets, 1.1% for public fixed assets, 0.8% for residential fixed assets, and 1.3% for all fixed assets.  Such a slow rate of capital accumulation will not be supportive of robust growth.

The reductions in the growth rates were especially sharp following the 2008 crisis.  This led capital accumulation to fall well below the trend path that it had previously been on:

Chart 10

As was the case for growth in the labor force, there is again a substantial fall after 2008 in the growth of an important factor in production relative to its previous trend.  This time it is accumulated capital.  It should not be surprising that this slowdown in the growth of both available labor and capital would then be accompanied by a slowdown in the growth of GDP – all relative to their previous trends.  But an open question is how much of the close to 20% shortfall in GDP as of 2023 was due to labor, how much to capital, and how much to the productivity of labor working with the available capital?  This will be examined in the next section.

D.  Modeling GDP:  The Relative Importance of Labor, Capital, and Productivity to the Shortfall

Output (GDP) has fallen relative to the path it was on before – and a 20% shortfall is a lot – as have both the size of the labor force and of accumulated capital.  To estimate how much of the shortfall in GDP can be attributed to the shortfall of labor, how much to the shortfall of capital, and how much to a slowdown in the growth in productivity of that labor and capital, one needs a model.

For this analysis, I used the extremely simple but standard model of production called the Cobb-Douglas.  Its formulation is credited to Paul Douglas (an economist) and Charles Cobb (a mathematician) in 1927, although Douglas recognized and acknowledged that a number of economists before them had worked with a similar relationship.  While extremely simple, it allows us to arrive at an estimate of how much of the shortfall in GDP can be attributed to labor, how much to capital, and how much to a change in productivity growth.  Despite being simple, there was a good fit when the model was tested for its predictions of GDP against what GDP actually was historically.  There was also a very surprisingly good fit against whether the trend growth in GDP was close to what the model predicted based on the trend growth observed for labor and for capital.

The Cobb-Douglas production function is an equation that relates what output (real GDP) would be for given levels of labor and capital as inputs.  The following subsection will provide a brief overview of that equation and of the parameters used.  Those who prefer to avoid equations can skip over this section and go directly to subsection (b) below, where the model was tested via a comparison of the model’s predicted values for GDP to what GDP actually was, both year-by-year and in its trend.

a)  The Cobb-Douglas Equation and Parameters 

The Cobb-Douglas production function can be written as:

Y = A(1+r)tLβK1−β

where Y is real GDP, L is labor, K is capital as measured, r is a rate of growth for the increase in productivity over time (t), A is a scaling factor, and β is an exponent indicating how much output (Y) will increase for a given percentage increase in L as an input.  With constant returns to scale (which is generally assumed), the exponent for K will then be 1- β.  They will also match (under the assumptions of this model) the shares in national income of labor and capital, respectively.  In the NIPA accounts for 2023, the compensation of employees was 62% of national income.  All other income (e.g. basically various forms of profit) was 38% of national income.  I rounded these to just a 60 / 40 split, so β = 0.60 and 1-β = 0.40.

Productivity will grow over time.  That is, the output that can be generated for a given amount of labor and of capital will grow over time.  As technology changes and is reflected in the accumulated stock of capital, labor working with the available machinery and equipment will be able to produce more.  While the contribution of the growth in productivity can be incorporated into the Cobb-Douglas in various different ways, the simplest is to assume that it augments the combination of labor and capital together.  This growth in productivity can then also be referred to as the growth in Total Factor Productivity (TFP).

For the simulations here, I took the year 2007 (the last full year before the 2008 collapse) as the base period, and hence scaled the labor and capital inputs in proportion to what they were in 2007.  Thus they were both set to the value of 1.00 in 2007, and if they were then, say, 10% higher in some future year they would have a value of 1.10 in that year.  The scaling coefficient A would then be equal to real GDP in 2007 ($16,762.4 billion in terms of 2017 constant $).

Finally, the rate of TFP growth was set so that GDP as modeled would roughly track what the actual values for GDP were historically.  It turned out that an annual rate of growth in TFP of 1.20% worked well for the years leading up to 2007, with this then falling to 0.90% per year in the years following 2007 up to and including 2023.  I did not try to fine-tune this to any greater precision (i.e. I looked at annual TFP growth to the nearest 0.1% and not more finely, i.e. to 1.20% or 1.30% but not to 1.21%).  I also constrained the TFP growth to be at just one given rate for all of the years before 2007 (1.20%) and one rate after 2007 (0.90%), even though it is certainly conceivable that it could fluctuate over time.

b)  Comparison of GDP as Modeled by the Cobb-Douglas versus Actual and Trend GDP

The Cobb-Douglas just provides a model, and the first question to address is whether that model appears to track what we know about the economy.  There were two tests to look at:  1)  how well it tracked actual GDP as a function of actual labor employed and capital (net fixed assets), and 2)  how well the model tracked the trend line for GDP growth (as drawn in Chart 1 at the top of this post) as a function of the trend line as drawn for the labor force (Chart 2) and the trend line as drawn for capital (Chart 10).  Keep in mind that these trend lines were drawn independently and “by eyeball” based on what appeared to fit best in the decades leading up to 2008.

This chart shows how well the modeled GDP tracked actual historical GDP:

Chart 11

The line in black shows what actual real GDP was in each year from 1959 to 2023.  The line in red shows what the simple Cobb-Douglas model predicted real GDP would be in each year with the parameters as discussed above and with the labor input based on actual employment in that year rather than the available labor force.  The capital input is always available net fixed assets (as an index, which is all we need for the relative changes), as estimated by the BEA for the NIPA accounts (shown in Chart 10 above).

The line in red for the modeled GDP tracks well the line in black of actual GDP, especially from about the early 1980s onwards.  A reduction in the growth rate for TFP in the years prior to 1980 would have led it to track the earlier years better, but I did not want to try to “fine-tune” the TFP rate.  My main interest is in how well predicted GDP tracks actual GDP over the last several decades.  Over this period, a simple Cobb-Douglas with fixed parameters and with TFP growth of 1.20% for the years before 2007 and 0.90% in the years since, tracked quite well.  And this was over a period when GDP grew from just $7.3 trillion in 1980 (in 2017 constant $) to $22.7 trillion in 2023 – more than tripling.

A second test is whether something close to the GDP trend line (as drawn in Chart 1 at the top of this post) will be generated by the Cobb-Douglas model when the labor force grows on its trend line (as drawn in Chart 2) and capital grows on its trend line (as drawn in Chart 10).  Each of these trend lines were drawn independently and “by eyeball”.

The answer is that it does, and to an astonishing degree.  This may have been the case in part by luck or coincidence, but regardless, was extremely close.  The line for GDP as predicted from the Cobb-Douglas model using labor and capital inputs that each followed their own trend lines, was so close to the GDP trend line that they were on top of each other in the chart and could not be distinguished.

One should keep in mind that, by construction, the predicted GDP in 2007 from the Cobb-Douglas model will be equal to actual GDP in that year.  The scaling factor was set that way.  But the question being examined is whether the predicted GDP (based on the labor and capital trend lines) would drift away from the trend line for GDP (as drawn) over time.  It did not.  Calculating it back over a 60-year period (i.e. equivalent to going back to 1947 from the 2007 base), the predicted GDP was only 0.7% greater than what GDP on the drawn trend line would have been 60 years before.

This is tiny, and indeed so tiny that I at first thought it might be a mistake.  But after simulating what would have been generated by various alternative parameters for the Cobb-Douglas, as well as alternative trend paths for labor and capital, the calculations were confirmed.  The implication is that the trend lines for GDP, labor, and capital – while independently drawn – are consistent with each other and with this simple Cobb-Douglas framework.

The rate of productivity growth – TFP growth – for the years leading up to 2007 was 1.20%.  It was derived, as noted above, by trying various alternatives and seeing which appeared to fit best with the figures for actual GDP in those years.  Going forward from 2007, however, it would have over-predicted what GDP would have been.  What fit well with the data on actual GDP (and based on actual employment and available net fixed assets) was a reduction in the TFP rate from the 1.20% used for the years up to 2007 to a rate of 0.90% for the years after.

The resulting path for actual GDP versus the path as modeled by the Cobb-Douglas can be more clearly seen in the following chart.  It is the same as Chart 11, but now only for the period from 2000 to 2023:

Chart 12

The red line shows the path for the simulated GDP, where from 2007 onwards the assumed TFP growth rate was 0.90%.  The fit is very good, and especially in 2022 and 2023 – the years of most interest to us – when the simulated GDP (from the Cobb-Douglas) is almost identical to actual GDP.  These are both well below the path (the green line) that would have been followed based on the previous trend growth in labor and capital, as well as the continuation of productivity growth at a 1.20% rate rather than falling to 0.90%.

c)  The Causes of the Below Trend Growth of GDP Since 2008

From this simple Cobb-Douglas model, we can try various simulations of what growth in GDP might have been had the labor force continued to grow at the rate it had before 2008, had capital continued to grow at the rate it had before 2008, and had productivity (TFP) continued to grow at the rate it had before 2008.

The results are shown in the following chart:

Chart 13

The resulting paths for GDP are shown as a ratio to what actual GDP was in each year, with the differences expressed in percentage points.  By definition, there will be no difference for actual GDP, so it is a flat line (in black) with a zero difference in each year.  The line in red then shows what the modeled GDP was in each year in terms of the percentage point difference with actual GDP, using actual labor employed in each year and available capital.  The red line shows at most a 2 percentage point difference with actual GDP – and no difference at all in 2022 and 2023.  The model tracks actual GDP well when the labor input is equal to observed employment.

The line in blue then shows what GDP would have been (according to the model) had capital growth continued after 2007 along its pre-2008 trend path (the path drawn in Chart 10 above) while labor grew at the actual rate of employment.  It shows how much the shortfall in GDP was as a consequence of capital accumulation slowing down from 2008 onwards.  As seen in the chart, the impact of this slowdown has grown over time.

The line in orange shows what GDP would have been had labor growth continued after 2007 on its pre-2008 trend path (the path drawn in Chart 2 above), while capital grew not along its trend but rather as measured.  Here one needs to take into account that the growth rate of actual employment and the growth rate of the labor force will only match between periods when the unemployment rate was the same.  Thus comparisons should be limited to periods when the economy was close to full employment, such as between 2007 (when unemployment averaged 4.6%), 2016 to 2019 (annual unemployment rates of 4.9% to 3.7%), and 2022/23 (annual unemployment rates of 3.6%).  That is, the “peaks” seen in the orange line in 2009 and again in 2020 are not significant, as they reflect labor not being fully used.  This was not because the labor force was not available but rather due to the disruptions of the downturns in those years.

The line in burgundy then shows what GDP would have been (in terms of its percentage point difference with actual GDP) had both labor and capital inputs continued to grow (and been used) on their pre-2008 trend paths.  Note that the values here will not be the simple addition of the percentage point contributions of the slower than trend growth of the labor force and the slower than trend growth of capital.  The Cobb-Douglas relationship is a multiplicative one, not a linear one.  But if one does multiply out the two (the blue and orange lines, but as ratios rather than percentage points), and adjust for the model’s tracking error (the red line), one will get the impact of the two together (the burgundy line).

Finally, there is the impact of the slowdown in TFP growth from 1.20% per year before 2007 to 0.90% after.  That will appear as the difference between what GDP would have been had it followed the previous trend path (the green line in the chart) and the impact of labor and capital both slowing down from their respective trends (the burgundy line).  Its impact grows steadily larger over time.

Based on these simulations, as of 2023 approximately 25% of the shortfall in GDP relative to what it would have been had it continued on its pre-2008 trend can be attributed to a fall in the rate of productivity growth (TFP) from 1.20% to 0.90%.  Of the remaining shortfall, approximately 60% was due to the slowdown in investment and hence capital accumulation, and approximately 40% was due to the slowdown in the growth of the labor force.  Or put another way (and keeping in mind that the impacts are not linearly additive, but only approximately so), of the total shortfall in 2023, about 70% was due to the slowdown in productivity growth together with the related slowdown in capital growth, and about 30% was due to the slowdown in labor force growth.

But these figures are for 2023 and will shift over time.  Going forward, and unless something is done to change things, the shortfall in GDP (its deviation from the pre-2008 trend) will be widening, and the shortfall in capital accumulation (due to the fall in investment as a share of GDP) plus the related reduction in productivity growth, can be expected to account for an increasing share of this increasing shortfall in GDP.  These already accounted for about 70% of the shortfall in 2023, and on current patterns that share will grow in the coming years.

E.  Conclusion

GDP fell sharply in the economic and financial collapse that began in the second half of 2008.  But while there was a recovery, with employment eventually returning to full employment levels, GDP never returned to the path it had previously been on.  This was new.  In prior recessions (as seen in Chart 1 at the top of this post), GDP was back close to its earlier path once employment had recovered to full employment levels.  As a consequence, by 2023 GDP would have been close to 20% higher than what it was had GDP returned to its previous path.  And 20% higher GDP is huge.  In terms of current GDP in current prices, that is close to $6 trillion of increased output and incomes each year.  Total federal government spending on everything is about $7 trillion currently.

The proximate causes of this can be broken down into three.  First, the labor force began to grow at a slower rate in the years following 2008.  This was not due to labor force participation rates falling for individual age groups.  Rather, this in part reflected a slowdown in the growth of the overall US population (and to this extent, will then be offset when GDP is looked at in per capita terms).  But in addition, there was the impact of an aging population, with the Baby Boom generation entering into their normal retirement years.

In policy terms, there is not much one can or should want to do about labor force growth.  Population growth is what it is, and an aging population will see an increasing share of the population moving into their retirement years.  These all reflect personal choices.

In contrast, the slowdown in investment and the resulting slowdown in capital accumulation and productivity growth is a policy question that merits a careful review.  Why are firms investing less now than they did before?  Profits (especially after-tax profits) are at record highs and the stock market is booming.  In a market economy where firms are avidly competing with each other, this should have led to an increase – not a decrease – in net investment.

A future post in this series will examine the factors behind this.  But first, a post will examine the specific case of residential investment.  Net residential investment fell especially sharply after 2008 (see Charts 8 and 9 above), while home prices have shot up.  Housing is important, and its rising cost has been the source of much displeasure in recent years by those who do not own a home and must rent.  The rising cost of housing is the primary (indeed, the only) reason why the CPI inflation index remains above the Fed’s target of 2%.  It merits its own review.