Tax Cuts Do Not Spur Growth – There Are Income as well as Substitution Effects, and Much More Besides: Econ 101

gdp-growth-and-top-marg-tax-rate-1930-to-2015

A.   Introduction, and a Brief Aside on the Macro Issues

While there is much we do not yet know on what economic policies Donald Trump will pursue (he said many things in his campaign, but they were often contradictory), one thing we can be sure of is that there will be a major tax cut.  Republicans in Congress (led by Paul Ryan) and in the Senator want the same.  And they along with Trump insist that the cuts in tax rates will spur a sharp jump in GDP growth, with the result that net tax revenues in the end will not fall by all that much.

But do tax cuts spur growth?  The chart above suggests not.  Marginal tax rates of those in the top income brackets have come down sharply since the 1950s and early 1960s, when they exceeded 90%.  They reached as low as 28% during the later Reagan years and 35% during the administration of George W. Bush.  But GDP growth did not jump to some higher rate as a result.

This Econ 101 post will discuss the economics on why this is actually what one should expect.  It will focus on the microeconomics behind this, as the case for income tax cuts is normally presented by the so-called “supply siders” as a micro story of incentives.  The macro case for tax cuts is different.  Briefly, in times of high unemployment when the economy is suffering from insufficient demand in the aggregate to purchase all that could be produced if more labor were employed, a cut in income taxes might spur demand by households, as they would then have higher post-tax incomes to spend on consumption items.  This increase in demand could then spur production and hence GDP.

Critically, this macro story depends on allowing the fiscal deficit to rise by there not being simultaneously a cut in government expenditures along with the tax cuts.  If there is such a cut in government expenditures, demand may be reduced by as much as or even more than demand would be increased by households.  But the economic plans of both Trump and Congressman (and Speaker) Paul Ryan do also call for large cuts in government expenditures.  While both Trump and Ryan have called for government expenditures to increase on certain items, such as for defense, they still want a net overall reduction.

The net impact on demand will then depend on how large the government expenditure cuts would be relative to the tax cuts, and on the design of the income tax cuts.  As was discussed in an earlier post on this blog on the size of the fiscal multiplier, If most of the income tax cuts go to those who are relatively well off, who will then save most or perhaps all of their tax windfall, there will be little or no macro stimulus from the tax cuts.  Any government expenditure cuts on top of this would then lead not to a spur in growth, but rather to output growing more slowly or contracting.  And the tax plan offered by Donald Trump in his campaign would indeed direct the bulk of the tax cuts to the extremely well off.  A careful analysis by the non-partisan Tax Policy Center found that 71% of the tax cuts (in dollar value) from the overall plan (which includes cuts in corporate and other taxes as well) would go to the richest 5% of households (those earning $299,500 or more), 51% would go to the top 1% (those earning $774,300 or more), and fully 25% would go to the richest 0.1% (those earning $4.8 million or more).

[A side note:  To give some perspective on how large these tax cuts for the rich would be, the 25% going to the richest 0.1% under Trump’s plan would total $1.5 trillion over the next ten years, under the Tax Policy Center estimates.  By comparison, the total that the Congressional Budget Office projects would be spent on the food stamp program (now officially called SNAP) for the poor over this period would come to a bit below $700 billion (see the August 2016 CBO 10-year budget projections).  That is, the tax breaks to be given under Trump’s tax plan to the top 0.1% (who have earnings of $4.8 million or more in a year) would be more than twice as large as would be spent on the entire food stamp program over the period.  Yet the Republican position is that we have to cut the food stamp program because we do not have sufficient government revenues to support it.]

The macro consequences of tax cuts that mostly go to the already well off, accompanied by government expenditure cuts to try to offset the deficit impact, are likely therefore to lead not to a spur in growth but to the opposite.

The microeconomic story is separate, and the rest of this blog post will focus on the arguments there.  Those who argue that cuts in income taxes will act as a spur to growth base their argument on what they see as the incentive effects.  Income taxes are a tax on working, they argue, and if you tax income less, people will work longer hours.  More will be produced, the economy will grow faster, and people will have higher incomes.

This micro argument is mistaken in numerous ways, however.  This Econ 101 post will discuss why.  There is the textbook economics, where it appears these “supply siders” forgot some of the basic economics they were taught in their introductory micro courses. But we should also recognize that the decision on how many hours to work each week goes beyond simply the economics.  There are important common social practices (which can vary by the nature of the job, i.e. what is a normal work day, and what do you do to get promoted) and institutional structures (the 40 hour work week) which play an important and I suspect dominant role. This blog post will review some of them.

But first, what do we know from the data, and what does standard textbook economics say?

B.  Start with the Data

It is always good first to look at what the data is telling us.  There have been many sharp cuts in income tax rates over the last several decades, and also some increases.  Did the economy grow faster after the tax cuts, and slower following the tax increases?

The chart at the top of this post indicates not.  The chart shows what GDP growth was year by year since 1930 along with the top marginal income tax rate of each year.  The top marginal income tax rate is the rate of tax that would be paid on an additional dollar of income by those in the highest income tax bracket.  The top marginal income tax rate is taken by those favoring tax cuts as the most important tax rate to focus on.  It is paid by the richest, and these individuals are seen as the “job creators” and hence play an especially important role under this point of view.  But changes in the top rates also mark the times when there were normally more general tax cuts for the rest of the population as well, as cuts (or increases) in the top marginal rates were generally accompanied by cuts (or increases) in the other rates also.  It can thus be taken as a good indicator of when tax rates changed and in what direction.  Note also that the chart combines on one scale the annual GDP percentage growth rates and the marginal tax rate as a percentage of an extra dollar of income, which are two different percentage concepts.  But the point is to compare the two.

As the chart shows, the top marginal income tax rate exceeded 90% in the 1950s and early 1960s.  The top rate then came down sharply, to generally 70% until the Reagan tax cuts of the early 1980s, when they fell to 50% and ultimately to just 28%.  They then rose under Clinton to almost 40%, fell under the Bush II tax cuts to 35%, and then returned under Obama to the rate of almost 40%.

Were GDP growth rates faster in the periods when the marginal tax rates were lower, and slower when the tax rates were higher?  One cannot see any indication of it in the chart. Indeed, even though the highest marginal tax rates are now far below what they were in the 1950s and early 1960s, GDP growth over the last decade and a half has been less than it what was when tax rates were not just a little bit, but much much higher.  If cuts in the marginal tax rates are supposed to spur growth, one would have expected to see a significant increase in growth between when the top rate exceeded 90% and where it is now at about 40%.

Indeed, while I would not argue that higher tax rates necessarily lead to faster growth, the data do in fact show higher tax rates being positively correlated with faster growth.  That is, the economy grew faster in years when the tax rates were higher, not lower.  A simple statistical regression of the GDP growth rate on the top marginal income tax rate of the year found that if the top marginal tax rate were 10% points higher, GDP growth was 0.57% points higher.  Furthermore, the t-statistic (of 2.48) indicates that the correlation was statistically significant.

Again, I would not argue that higher tax rates lead to faster GDP growth.  Rather, much more was going on with the economy over this period which likely explains the correlation. But the data do indicate that very high top marginal income tax rates, even over 90%, were not a hindrance to growth.  And there is clearly no support in the evidence that lower tax rates lead to faster growth.

The chart above focuses on the long-term impacts, and does not find any indication that tax cuts have led to faster growth.  An earlier post on this blog looked at the more immediate impacts of such tax rates cuts or increases, focussing on the impacts over the next several years following major tax rate changes.  It compared what happened to output and employment (as well as what happened to tax revenues and to the fiscal deficit) in the immediate years following the Reagan and Bush II tax cuts, and following the Clinton and Obama tax increases.  What it found was that growth in output and employment, and in fiscal revenues, were faster following the Clinton and Obama tax increases than following the Reagan and Bush II tax cuts.  And not surprisingly given this, the fiscal deficit got worse under Reagan and Bush II following their tax cuts, and improved following the Clinton and Obama tax increases.

C.  The Economics of the Impact of Tax Rates on Work Effort

The “supply siders” who argue that cuts in income taxes will lead to faster growth base their case on what might seem (at least to them) simple common sense.  They say that if you tax something, you will produce less of it.  Tax it less, and you will produce more of it. And they say this applies to work effort.  Income taxes are a tax on work.  Lower income tax rates will then lead to greater work effort, they argue, and hence to more production and hence to more growth.  GDP growth rates will rise.

But this is wrong, at several levels.  One can start with some simple math.  The argument confuses what would be (by their argument) a one-time step-up in production, with an increase in growth rates.  Suppose that tax rates are cut and that as a result, everyone decides that at the new tax rates they will choose to work 42 hours a week rather than 40 hours a week before.  Assuming productivity is unchanged (actually it would likely fall a bit), this would lead to a 5% increase in production.  But this would be a one time increase. GDP would jump 5% in the first year, but would then grow at the same rate as it had before.  There would be no permanent increase in the rate of growth, as the supply siders assert.  This is just simple high school math.  A one time increase is not the same as a permanent increase in the rate of growth.

But even leaving this aside, the supply sider argument ignores some basic economics taught in introductory microeconomics classes.  Focussing just on the economics, what would be expected to happen if marginal income tax rates are cut?  It is true that there will be what economists call “substitution effects”, where workers may well wish to work longer hours if their after-tax income from work rises due to a cut in marginal tax rates. But the changes will also be accompanied by what economists call “income effects”.  Worker after-tax incomes will change both because of the tax rate changes and because of any differences in the hours they work.  And these income effects will lead workers to want to work fewer hours.  The income and substitution effects will work in opposite directions, and the net impact of the two is not clear.  They could cancel each other out.

What are the income effects, and why would they lead to less of an incentive to work greater hours if the tax rate falls?:

a)  First, one must keep in mind that the aim of working is to earn an income, and that hours spent working has a cost:  One will have fewer hours at home each day to enjoy with your wife and kids, or for whatever other purposes you spend your non-working time. Economists lump this all under what they call “leisure”.  Leisure is something desirable, and with all else equal, one would prefer more of it.  Economists call this a “normal good”.  With a higher income, you would want to buy more of it. And the way you buy more of it is by working fewer hours each day (at the cost of giving up the wages you would earn in those hours).

Hence, if taxes on income go down, so that your after-tax income at the original number of hours you work each day goes up, you will want to use at least some portion of this extra income to buy more time to spend at home.  This is an income effect, and will go in the opposite direction of the substitution effect of higher after-tax wages leading to an incentive to work longer hours.  We cannot say, a priori, whether the income effect or the substitution effect will dominate.  It will vary by individual, based on their individual preferences, what their incomes are, and how many hours they were already working.  It could go either way, and can only be addressed by looking at the data.

b)  One should also recognize that one works to earn income for a reason, and one reason among many is to earn and save enough so that one can enjoy a comfortable retirement. But in standard economic theory, there is no reason to work obsessively before retirement so that one will then have such a large retirement “nest egg” as to enjoy a luxurious life style when one retires.  Rather, the aim is to smooth out your consumption profile over both periods in your life.

Hence if income tax rates are cut, so that your after-tax incomes are higher, one will be able to save whatever one is aiming for for retirement, sooner.  Hence it would be rational to reduce by some amount the hours one seeks to work each day, and enjoy them with your wife and kids at home, as your savings goals for retirement can still be met with those fewer hours of work.  This is an income effect, and acts in the direction of reducing, rather than increasing, the number of hours one will choose to work if there is a general tax cut.

c)  More generally, one should recognize that incomes are earned to achieve various aims. Some of these might be to cover fixed obligations, such as to pay on a mortgage or for student debt, and some might be quasi-fixed, such as to provide for a “comfortable” living standard for one’s family.  If those aims are being met, then time spent at leisure (time spent at home with the family) may be especially attractive.  In such circumstances, the income effect from tax cuts might be especially large, and sufficient to more than offset the substitution effects resulting from the change in the after-tax wage.

Income effects are real, and it is mistake to ignore them.  They act in the opposite direction of the substitution effect, and will act to offset them.  The offset might be partial, full, or even more than full.  We cannot say simply by looking at the theory.  Rather, one needs to look at the data.  And as noted above, the data provdes no support to the suppostion that lower tax rates will lead to higher growth.  Once one recognizes that there will be income effects as well as substitution effects, one can see that this should not be a surprise.  It is fully consistent with the theory.

One can also show how the income and substitution effects work via some standard diagrams, involving indifference curves and budget constraints.  These are used in most standard economics textbooks.  However, I suspect that most readers will find such diagrams to be more confusing than enlightening.  A verbal description, such as that above, will likely be more easy to follow.  But for those who prefer such diagrams, the standard ones can be found at this web posting.  Note, however, that there is a mistake (a typo I assume) in the key Figures 2A and 2B.  The horizontal arrows (along the “leisure” axis) are pointed in the opposite direction of what they should (left instead of right in 2A and right instead of left in 2B).  These errors indeed serve to emphasize how even the experts with such diagrams can get confused and miss simple typos.

D.  But There is More to the Hours of Work Decision than Textbook Economics

The analysis above shows that the supply-siders, who stress microeconomic incentives as key, have forgotten half of the basic analysis taught in their introductory microeconomics classes.  There are substitution effects resulting from a change in income tax rates, as the supply-siders argue, but there are also income effects which act in the opposite direction. The net effect is then not clear.

However, there is more to the working hours decision than the simple economics of income and substitution effects.  There are social as well as institutional factors.  It the real world, these other factors matter.  And I suspect they matter a good deal more than the standard economics in explaining the observation that we do not see growth rates jumping upwards after the several rounds of major tax cuts of the last half century.

Such factors include the following:

a)  For most jobs, a 40 hour work week is, at least formally, standard.  For those earning hourly wages, any overtime above 40 hours is, by law, supposed to be compensated at 50% above their normal hourly wage.  For workers in such jobs, one cannot generally go to your boss and tell him, in the event of an income tax increase say, that you now want to work only 39 1/2 hours each week.  The hours are pretty much set for such workers.

b)  There are of course other workers compensated by the hour who might work a variable number of hours each week at a job.  These normally total well less than 40 hours a week.  These would include many low wage occupations such as at fast food places, coffee shops, retail outlets, and similarly.  But for many such workers, the number of hours they work each week is constrained not by the number of hours they want to work, but by the number of hours their employer will call them in for.  A lower income tax rate might lead them to want to work even more hours, but when they are constrained already by the number of hours their employer will call them in for, there will be no change.

c)  For salaried workers and professionals such as doctors, the number of hours they work each week is defined primarily by custom for their particular profession.  They work the hours that others in that profession work, with this evolving over time for the profession as a whole.  The hours worked are in general not determined by some individual negotiation between the professional and his or her supervisor, with this changing when income tax rates are changed.  And many professionals indeed already work long hours (including medical doctors, where I worry whether they suffer from sleep deprivation given their often incredibly long hours).

d)  The reason why one sees many professionals, including managers and others in office jobs, working such long hours probably has little to do with marginal income tax rates.  Rather, they try to work longer than their co-workers, or at least not less, in order to get promoted.  Promotion is a competition, where the individual seen as the best is the one who gets promoted.  And the one seen as the best is often the one who works the longest each day.  With the workers competing against each other, possibly only implicitly and not overtly recognized as such, there will be an upward spiral in the hours worked as each tries to out-do the other.  This is ultimately constrained by social norms.  Higher or lower income tax rates are not central here.

e)  Finally, and not least, most of us do take pride in our work.  We want to do it well, and this requires a certain amount of work effort.  Taxes are not the central determinant in this.

E.  Summary and Conclusion

I fully expect there to be a push to cut income tax rates early in the Trump presidency.  The tax plan Trump set out during his campaign was similar to that proposed by House Speaker Paul Ryan, and both would cut rates sharply, especially for those who are already well off. They will argue that the cuts in tax rates will spur growth in GDP, and that as a consequence, the fiscal deficit will not increase much if at all.

There is, however, no evidence in the historical data that this will be the case.  Income tax rates have been cut sharply since the Eisenhower years, when the top marginal income tax rate topped 90%, but growth rates did not jump higher following the successive rounds of cuts.

Tax cuts, if they are focused on those of lower to middle income, might serve as a macro stimulus if unemployment is significant.  Such households would be likely to spend their extra income on consumption items rather than save it, and this extra household consumption demand can serve to spur production.  But tax cuts that go primarily to the rich (as the tax cuts that have been proposed by Trump and Ryan would do), that are also accompanied by significant government expenditure cuts, will likely have a depressive rather than stimulative effect.

The supply-siders base their argument, however, for why tax cuts should lead to an increase in the growth rate of GDP, not on the macro effects but rather on what they believe will be the impact on microeconomic incentives.  They argue that income taxes are a tax on work, and a reduction in the tax on work will lead to greater work effort.

They are, however, confused.  What they describe is what economists call the substitution effect.  That may well exist.  But there are also income effects resulting from the changes in the tax rates, and these income effects will work in the opposite direction.  The net impact is not clear, even if one keeps just to standard microeconomics.  The net impact could be a wash.  Indeed, the net impact could even be negative, leading to fewer hours worked when there is a cut in income taxes.  One does not know a priori, and you need to look at the data.  And there is no indication in the data that the sharp cuts in marginal tax rates over the last half century have led to higher rates of growth.

There is also more to the working hours decision than just textbook microeconomics. There are important social and institutional factors, which I suspect will dominate.  And they do not depend on the marginal rates of income taxes.

But if you are making an economic argument, you should at least get the economics right.

The Economics of Health Insurance and the Health Care Market: Econ 101

A)  Introduction

The health care market and especially the health care insurance market, need to be understood if we are to come up with a viable health care reform.  Health care services are obtained from, and are paid through, such markets, but these markets have particular characteristics which set them apart from what might be considered an ordinary market.  Because of these characteristics, the health care market does not lead to what economists would call an efficient outcome.  Rather, they lead to limited competition in local markets, high administrative and other costs, where the most efficient providers are not rewarded, and where there is little market pressure to move the system to those who provide the highest value to those in need of health care services.

This Econ 101 post will review these characteristics, structured around an approach based on defining some of the strange terms and language that economists use to describe such markets.  Not all terms will be covered – only those important to an understanding of what is needed in health reform.  And the focus will be on aspects relevant to the US system, not necessarily to systems elsewhere.  The first section below will be on health insurance, and the next section then on the broader market for the provision of health care services and its funding.

Most (although not all) of the discussion will be couched in terms of individuals buying health insurance directly.  It is recognized that most Americans are covered indirectly through their employer (who purchases insurance for them as part of their wage compensation package) or through government programs such as Medicare and Medicaid.  But the primary problems are in the individual health insurance market.  The Obamacare reforms are designed to address some of these, but issues will remain.  And the problems in the individual markets are important not only in themselves, but also as they illustrate issues that arise as well in the markets for insurance through employers or government backed programs.  Hence it is necessary to understand what lies behind the failures of the individual health insurance markets prior to the Obamacare reforms, which have led to the extremely high costs and limited access and coverage that Americans have faced in trying to obtain and pay for health care.

B)  Health Insurance

1)  Insurance:  Insurance is a contractual agreement between two parties:  The insurer providing the insurance, and the insured party (or insuree, or client, or customer, or patient) purchasing the insurance.  The insured party makes a regular payment (often monthly) to the insurer (the payment is called the  premium), and in return the insurer will pay part or all of the costs incurred if some event occurs (a claim, as contractually set out).  The event will be some health related event for health insurance.  The timeline is important (and will be discussed further below):  The premium payments are paid first, and the insurance claims are paid at some later point in time when an insured event occurs.

2)  Risk pool:  An insurance company is a financial institution, with sufficient capital (monitored by regulators) to allow it to pay claims that may come due, and with a high degree of statistical confidence that the capital they have on hand or have access to will indeed suffice.  One does not know for any individual whether they will incur health costs leading to an insurance claim in the next period.  However, with a large enough pool of clients being insured, the insurance company can work out with some degree of statistical confidence what the total claims will be in any given period, and from this what insurance rate (premium rate) they will need to charge to cover such costs.  The group they are insuring is called the risk pool.

3)  Unbiased sample:  To work out what to charge, the insurance company will need to know the characteristics (in terms of expected health claim costs) of those they are insuring.  If they are an unbiased sample taken from the population as a whole, then the health characteristics of the population as a whole (with the characteristics, such as age, of those in the risk pool) can be used to determine the level of claims to expect in any given period, and therefore what to charge.

4)  Biased sample:  A biased sample, in contrast, is one with a heavier share (or weighting) of some sub-group who will have a different likelihood of making a claim.  If that sub-group tends to have higher health care claims than the broader group, then the health care characteristics of that broader group will underestimate the costs that will in fact be incurred by the group being insured.

5)  Asymmetric information:  Markets do not function well when the parties on one side of a transaction have more information on what is being traded than the parties on the other side.  In health insurance, the insured individual will know more about their personal health status than a health insurance company will know.

6)  Adverse selection:   If the insurance is being priced to cover the costs of a risk pool that the insurance company assumes will be an unbiased sample from the general population, and an individual knows he or she has some illness or condition which will likely result in higher insurance claims than for an average person, then that individual will in general be eager to purchase such insurance.  And if an individual knows he or she is relatively more healthy than others, then he or she may decide to forego the purchase of such health insurance despite the risks, as on average their expected costs will be lower.  As a result, the insurer will end up with a risk pool that is biased towards those who will likely have higher insurance claims.  This is adverse selection.  The premium rate that was calculated based on an unbiased sample will not then suffice to cover the costs.

7)  Death spiral:  In a situation where there is asymmetric information and the individual can choose whether or not to purchase health insurance, a premium rate sufficient to cover costs for an unbiased risk pool will lose money for the pool actually enrolled.  The insurance company will respond by raising the premium rates in the next period.  But at the higher premium rates, some individuals who were at the borderline of deciding whether or not to enroll (as they were relatively more healthy than those in the biased risk pool), will decide not to re-enroll.  This will lead to an even more biased risk pool, leading to another round of the insurance company raising premium rates, and to another round of those then at the new borderline deciding not to re-enroll.  There might eventually be a stable equilibrium of relatively high cost enrollees and relatively high premium rates, but it is also possible and indeed likely, depending on the characteristics of the population, that there will be fewer and fewer enrollees in each round until it all collapses.  This is the death spiral.

8)  Free riders:  Individuals may choose not to enroll in a health plan because they believe they will have lower health costs than others.  But it is not that they necessarily believe their health costs will be lower than for others for the rest of their lives, but rather only for a period until they once again have the option of enrolling in a health insurance plan.  If insurance companies are required to enroll anyone who wishes to enroll at any time, then some might try to enroll literally on the day before they are scheduled to go to a hospital for a major operation.  Insurance companies try to address this by limiting open enrollment only to certain periods at some regular time each year, but this will be only partially successful.  Many medical procedures can be planned months ahead (such as whether to have a hip or knee replacement, or whether to try to become pregnant or not).  Free riders are those who try to game the system by paying in premiums for only a short period before they incur what they know will be major medical costs.  And free riders include not only those who seek to postpone coverage just to the next open enrollment period when they know they will incur some major medical expense, but also those who might be relatively young and aim to enroll only decades later when, due to their then advancing age, they know there health care costs will be high.

9)  Biased selection:  It is not only the insured parties who use the asymmetric information they have on their own health needs or who seek to exploit the system as free riders, who can play this game.  Insurance companies have become quite capable at designing health insurance plans to exclude, or at least to discourage, those who could be expected to incur higher health claim costs.  One way has been to exclude those with pre-existing medical conditions.  Those in the population who have some existing medical condition that has required treatment will generally continue to require higher than average treatment.  Insurance companies will deny them coverage if they are legally can.  Until Obamacare, they generally could.

10)  Individual mandate:  These problems of adverse and biased selection will be largely resolved if all in the population are required to secure health insurance coverage.  This is the individual mandate.  Individuals cannot then game the system as free riders, or choose to avoid cover if they expect (based on the information they know about themselves, which the insurers will not know) that their health care costs will likely be relatively low, at least until the next open enrollment period.  And with an individual mandate in place, insurers can then be required to offer coverage at non-discriminatory rates to all, including those with pre-existing conditions.  The death spiral would not then take hold.

11)  Biased selection II:  But issues may still remain.  The individual mandate requirement under Obamacare is not terribly strong, with only modest penalties for those who choose not to obtain insurance coverage (and with campaigns also underway by conservative groups to try to stop or at least discourage Americans from enrolling in any health care plan).  Insurance companies can play more subtle tricks as well.  Even though they will not now be able to block enrollment by someone with a pre-existing condition, they can design plans that will be unappealing to those who might have certain types of medical expenses, that might signal conditions associated with overall higher than average medical expenses.  Their hope is that such individuals will then choose to enroll in a health plan offered by some other insurer.  Or they can design plans that might be especially appealing to those who are more healthy.  The classic example of this is to include the price of gym membership in the insurance plan.  The premium rates will be higher than otherwise to cover the cost of gym membership, and those not interested in gym membership will then not find this to be an advantageous plan.  But it would be attractive to those who are already paying for a gym, or who wish to enroll in one.  The advantage to the health insurer is not so much that their enrollees will now start to go to the gym more often (although that will help), but more that those in the population who do use a gym are generally more healthy than the overall population for many reasons, including diet and other activities.

12)  Time inconsistency:  A further issue in health insurance is the arrow of time.  One enrolls in some health insurance plan, pays the premium for a period of time, and at some later point might have a health insurance claim.  But health insurance plans can be extremely complex (often deliberately so), with details buried in the fine print that may give the insurer an excuse to deny a claim that the patient had thought would be insured.  For a more normal product the customer would then absorb the loss and choose to switch to a different vendor, after receiving what they see as bad service or a broken promise.  But this can be difficult in health insurance.  First, the loss incurred on the medical care obtained could well be huge and not easy to absorb.  A study published in 2009 by Harvard Medical School researchers found that 62% of all personal bankruptcies filed in 2007 in the US were caused by medical problems.  Furthermore, these were not mostly bankruptcies of individuals without health insurance.  The Harvard researchers found that 78% of those filing for bankruptcy had medical insurance at the start of their illness.

But a second reason (and until the Obamacare reforms the more important one), is that a person in need for medical care cannot at that point choose to switch to a different health insurance provider.  At precisely that point when he realizes his existing health insurer is not performing, the person needs major medical care and hence has a pre-existing condition, and no new insurer will willingly take them on.  While denial of cover due to pre-existing conditions will now not be allowed under the Obamacare reforms, the individual will still not be able to switch insurance plans in the middle of the year, but only during an open enrollment period.  Depending on the treatment needed and its urgency, the patient will not be able to switch to another insurer precisely when he or she needs insurance the most.

The Obamacare reforms, with effective access for those with pre-existing conditions as well as minimum standards on other aspects of health insurance plans (such as no annual or lifetime limits, and requirements on what will be covered), will be a major step to resolving the time inconsistency problem.  But it will still not be fully resolved.

13)  Moral hazard:  Another commonly cited issue, in particular in conservative circles, is the concern that when patients do not face the full cost of the health care treatment (as insurance covers a part of the cost, and perhaps almost all of it), they will then “over-consume” health care.  They will obtain treatments that they do not really need, or choose more expensive treatments than necessary.  This is actually an issue that exists in principle for any type of insurance, whether for health or something else.  It is called “moral hazard”.

Whether this is an important issue in practice for health care is not so clear.  First, few of us want to go into surgery or be subject to some other major medical procedure unless it is really necessary, even if free.  Second, it is the doctor and not the patient who will normally decide and recommend whether some medical procedure is warranted.  And third, the recommended response by conservatives to the moral hazard issue is high deductible health insurance plans, as was discussed in a previous posting on this blog.  They argue that patients will then face the full cost of care when within the deductible.  But a high deductible plan is simply not relevant for addressing moral hazard for those who need a major medical procedure or treatment.  At that point, the deductible is no longer relevant as it would have already been paid.  Incentives and expenses will be the same.

Rather, high deductible plans will, at best, lead to lower expenditures for initial doctor visits to determine if there is a problem, as the consumer will face 100% of those costs (when still within the deductible for the year).  But as noted in the blog cited above, such expenditures are not where our medical costs primarily lie.  The bottom 50% of the population only accounts for 3% of all medical expenditures, so even cutting these in half, say, would have an insignificant impact on overall costs.  Indeed it might well lead to higher costs in the end, as visits to doctors are postponed and what would have been minor problems develop into something major.

14)  Race to the bottom:  Most working age Americans obtain their health insurance coverage through either their employer or the employer of their spouse (or parent, if a child).  Most employers, and especially employers with 50 or more employees, offer health insurance coverage to their employees as part of their wage compensation package.  Due to substantial tax advantages (as health insurance payments are not subject to income tax, while regular wages are), it is a good deal less expensive for the employer to offer health insurance coverage instead of not doing so and then paying the worker higher wages sufficient to allow them then to purchase on their own equivalent insurance.  Those higher wages would be subject to income tax.

This system can provide health insurance at reasonable cost for firms with a high number of employees (say a few hundred employees or more).  Such a large number of workers will provide a relatively unbiased sample of workers for the risk pool.  If all of the workers and their families (both young and old, sick and not so sick) are enrolled, then a death spiral will not take hold.  There would be no problem of free riders.  While there are coverage issues for those not employed and for those working in small firms (too small to provide a reasonably diversified risk pool), the system worked well enough in the 1950s and 1960s for those employed at larger firms.

However, issues developed as more and more spouses entered into the work force.  If both spouses worked for employers offering health insurance coverage, then the spouses could choose from which firm they would obtain their health insurance.  Family plans are normally cheaper than two individual plans.  The spouses would of course normally choose that plan which was most advantageous to them.  That would be the plan of the employer offering the best benefits.

The result was that those employers offering the plans with the best benefits, which would also be the more expensive plans, would see families choose them rather than a less generous plan offered by the employer of the other spouse.  The costs of the firms offering the more generous plans would then rise, as spouses switched to the better plans.  The incentive, then, was for employers to offer less and less generous plans, in the hope that employees would choose to enroll in the health plan of the employer of the other spouse.  This was a race to the bottom.  The consequence is that employer sponsored health insurance plans have become less and less adequate in recent decades, compared to what they covered before.

The Obamacare reforms will address this partially by setting minimum standards for what a health insurance plan must cover, for it to be considered an acceptable health insurance plan.  This will set a floor.  However, the standards are not high, and there will remain pressures on firms to go down to that floor.

C.  The Health Care Market

1)  Bilateral Oligopoly:  There are tens of thousands of health care providers in the US, and dozens of significant insurers.  However, medical care markets are overwhelmingly local, so what matters is not the number of providers at the national level but rather at the local level.  And medical care providers are of course divided into specialties.  There may also only be a few hospitals which one can effectively reach, and possibly only one or two.  As a result, when treatment in needed for some medical condition, one may effectively have only limited choices.

Similarly, there may be only a few insurers who offer insurance policies in any locality.  This is in part due to regulatory reasons, as insurance companies are regulated in the US at the state level.  As noted above, regulation of insurance is important to ensure that the companies maintain adequate capital to allow them to pay claims with a high degree of statistical confidence.  But even without regulation at the state level, insurance companies will pick and choose which localities to focus their activities in, depending on their knowledge of that local market and the activities of their competitors.

The primary model of health insurance coverage now in the US is for the insurance company to establish a network of “preferred providers” of health care services in each local market, with strong financial incentives for their insurance customers to choose services from members of that network.  The insurance company will negotiate payment rates with each member of that preferred provider network for the services they provide, with these payment rates well below the list prices (or “chargemaster” rates, when referring to hospitals) of those providers.  Indeed, as noted in an earlier blog in this series on health care, the rate negotiated with the preferred provider can be sometimes be ten times (or even more) lower than the rate that same provider would charge for someone with a different insurer or with no insurer.  There are therefore strong incentives to seek out services from members of the preferred provider network of your insurer.

(Health Maintenance Organizations, or HMOs, are also a common model of health care coverage in the US.  There is an even more restrictive network of health care providers in an HMO, and the HMO will generally not cover any of the costs incurred when an out-of-network provider is used.  In contrast, in a preferred provider network the health insurance will still cover some portion of the costs incurred when on out-of-network provider is used, but what is covered is much less than for an in-network provider.  For the discussion below the distinction is not important, so for brevity it will be couched in terms of preferred provider networks.)

The rates paid for health care treatments are therefore largely determined in the negotiations between health insurers and the local health care providers in their preferred provider network.  If there is only one insurer active in some region, that insurer will then have a good deal of leverage over providers to force them to accept low compensation rates.  If the health care provider does not accept those rates, they will see few patients as the patients will instead seek out those providers who joined the preferred provider network at the compensation rate agreed to with the insurance company.

At the other extreme, if there is effectively only one health care provider in some locality for some medical specialty or service (say one large hospital), but a number of insurers, then those medical providers will have a great deal of leverage over the insurers to force them to accept the compensation rates they demand.  The insurance company cannot offer health care coverage if the local hospitals or medical specialists refuse to work with them.  The insurance company must then agree to compensate those health care providers at the rates they demand.

The result has been an arms race:  Both health insurers on one side, and health care providers on the other side, will seek to merge and consolidate with others offering similar services in each local market across the US, in order to strengthen their bargaining position in these key negotiations.  And that is what one has seen over the last two decades.  Health insurers have merged at the national level or have bought up what were previously local or regional insurers, while doctor groups and especially hospitals have merged into chains.

This has led to what are now highly concentrated local markets.  The American Medical Association (representing doctors) has been publishing a report each year for the last 12 years on concentration in health insurers in US states as well as in each of the metropolitan statistical areas of the US (metropolitan areas as defined by the US Bureau of the Census).  The 2013 edition of the report (released in November 2013, and based on data for 2011) reported that health insurance markets would be deemed “highly concentrated” (based on the 2010 guidelines issued by the US Department of Justice and Federal Trade Commission) in 71% of the 388 metropolitan statistical areas of the US.  They also noted that just two insurers accounted for over 50% (together) of the health insurance market in 45 of the 50 US states, and that just one insurer accounted for over 50% of the market in 15 states.  The 2012 edition of the report noted that at least one insurer accounted for over 30% alone of the health insurance market in 89% of US metropolitan areas, and that just one insurer accounted for over 50% of the market in 38% of the US metropolitan areas.  And concentration has increased further since these reports were prepared.

Health insurers have not surprisingly strongly criticized the AMA reports, and have responded with a commissioned report of their own, criticizing health care providers for high and increasing concentration among hospitals.  This report concluded that hospital ownership is “highly concentrated” (by the guidelines of the US Department of Justice and Federal Trade Commission) in 80% of the US metropolitan statistical areas, and is “moderately concentrated” in a further 13% metro areas.  And there was only one hospital in 11% of the metro areas.

So who is right in this debate?  Actually, both are.  US health insurance markets are highly concentrated by local area, as are the local markets for hospital services.  And each side is racing to consolidate further.  Monopolies are still rare in the local markets, but with only a few players on each side, the markets have developed into what economists term “bilateral oligopolies”, where a small number of suppliers (health care providers) must sell their services to a small number of buyers (health care insurers, acting on behalf of their insured clients).

Without further information, one cannot predict whether health insurers or health care providers will be more profitable in a situation of bilateral oligopoly.  It will depend on their relative strength in each of the local markets, and this will vary from one market to the next depending on the local conditions.  However, the party that will face high prices regardless will be the ultimate consumers.  Suppose one is in a market where there are only a few local health care providers but many insurers.  The few health care providers will have a great deal of negotiating leverage with the insurers, and can demand high prices for their services.  The insurers, all of whom face these high prices, will then have to pass along these high prices to their insured customers in high premium rates.

Alternatively, suppose one is in a market where there are many health care providers (note this would be for each medical specialty as well as for hospital services), but only a few insurers (and maybe even effectively only one).  The health insurers would then have a good deal of leverage to drive down the doctor and hospital rates.  However, since there will then not be much (if any) competition among the health insurers (as there will be only a few and maybe effectively only one), there will be little or no competitive pressure to pass along these low prices to their insured customers.  The insured customers will again face high prices.

There have therefore been strong incentives for the US health care market to evolve over recent decades into a system of local bilateral oligopolies, with health care providers on one side and health insurers on the other.  There has been strong pressure on each to consolidate, and both have done so in an “arms race” like fashion.  The result is now highly concentrated local markets, where your profitability depends on your ability to negotiate favorable prices.  But whether it is the health insurers or the health care providers who win in these negotiations (and this will vary by locality), the consumer loses and ends up paying high prices.  This is the major reason for the extremely high US health care costs, where the high prices in the US (compared to other countries) was discussed in earlier posts in this series on health care (see here and here).

2)  Competing on Risk Pool Selection, and Other Sources of High Insurance Costs:  In addition to high health care costs as a consequence of the largely unregulated bilateral oligopolies in most local markets in the US, health costs are high also due to the high administrative costs of private health insurers.  Administrative costs are high since health insurers compete primarily on their ability to assemble networks of preferred providers of health care services in each locality (with prices negotiated with each provider for each possible service), as discussed immediately above, but also based on their ability to assemble a pool of insurees which excludes those who are of higher risk.  The open individual health insurance exchanges will limit this under the Obamacare reforms (or at least shift it to more subtle games in how health insurance plans are structured, as discussed above), but at least until now, the focus on risk pool selection has led to high administrative expenses, since individual applicants had to be vetted.

Health insurance costs are high also because of the high salaries and other compensation paid to the CEOs and other senior management of the insurance companies, as documented in a previous post in this series on health care, as well as their high profitability.  The result is administrative cost margins (which includes the net profits of the insurers in the data as assembled) of the private health insurers.  As was discussed in the blog post just cited, in 2011 the administrative cost margin (including profits) of private health insurance came to 14.0% of the cost of benefits paid.  The admin costs of private insurance companies were even higher for the programs they managed on behalf of government (such as the Medicare Advantage program of Medicare).  Those costs came to 18.6% of benefits paid.

Since the government does not incur the high costs that private health insurers do as a consequence of seeking to bias the risk pool to those of lower risk and other such actions, nor pay out profits or high salaries to CEOs and other senior managers, the administrative cost margin for direct government administered health insurance programs are far below that of private insurers.  As discussed in the blog post cited above, administrative costs for the Medicare programs the government administers directly was only 2.1% of benefits in 2011, far below the costs private insurers incur.

Total private administrative costs (including profits) of private health insurers came to $157.6 billion in 2011, based on the recently released new estimates of the National Health Expenditures data set of the Center for Medicare and Medicaid Services (CMS).  Of this, $109.9 billion was spent on the administrative costs (including profits) of the private health insurers for their privately provided health insurance plans, and $47.7 billion was spent on the administrative costs (including profits) of the private health insurers for the government health insurance plans (primarily Medicare and Medicaid, but also others) that the private health insurers administer on behalf of the government.

If the costs of administering health insurance plans were at the low cost Medicare incurs (of 2.1%) rather than the 14.0% and 18.6% that the private insurers incur, the nation would have saved $135.7 billion in 2011.  This is proportionately a huge savings in administrative costs, of 86%.  Still, a savings of $135.7 billion should also be compared to the roughly $900 billion in savings one would have needed in 2011 for US health care costs in that year (out of total health care costs of $2.7 trillion in 2011) to fall, as a share of GDP, to what the second most expensive OECD country spends on health care (as discussed in an earlier blog post; note that total health care costs of $3.0 trillion are expected in 2014, so a one-third reduction would now be $1.0 trillion).  The $135.7 billion in savings in 2011 would have been significant, but still only 15% of the overall savings needed.

D.  Conclusion

US health care costs are high and excessive, compared to what any other country in the world spends on health care.  These high costs are a consequence of the structure of the health care market in the US, with its focus on private health insurance plans.  As discussed above, there are a number of reasons (including asymmetric information, adverse selection, free riders, and biased selection, as well as non-competitive local markets of bilateral oligopolies), for why private health insurance markets will act quite differently than what economists would call a “normal” market.  They will not be efficient and low-cost.  Rather, a reliance on a private health insurance focussed system has led to inefficiency and high costs, but also high profits for the insurers.

There therefore needs to be a fundamental change in the structure of these health care markets, and the incentives for how they operate, if one is to reduce US health care costs to what other countries in the world have been able to achieve.  Future blog posts in this series on health reform will discuss what such a system might be.

An Increase in Government Spending Can Reduce the Debt to GDP Ratio: Econ 101

Most people realize that it is not the absolute value of the government debt that matters, but rather the ratio of that debt to GDP.  A larger economy can support a larger debt.  But most people will also think instinctively that an increase in government spending will necessarily lead to an increase in the government debt to GDP ratio.  It is not surprising that they should think so.  But it is wrong.

Whether the government debt to GDP ratio will rise or will fall when government spending increases will depend on economic conditions and other structural factors.  In conditions of high unemployment and where the Central Bank has driven the interest rates it can control essentially to zero, such as exist now in the US and Europe, an increase in government spending will increase the demand for goods and services, and hence will increase the demand for labor to produce those goods and services.

Employment and output will then rise. How much they will rise will depend on the multiplier, but as was discussed in a previous Econ 101 post on this site, in conditions of high unemployment and close to zero Central Bank controlled interest rates such as currently exist, the multiplier will be relatively high.  The higher incomes that then follow from the higher employment and output will also then lead to higher tax revenues, as a share of the higher incomes will be paid in taxes.

Hence the addition to the deficit and thus the public debt will be less than simply the increase in government spending, due to the higher tax revenues.  With GDP higher due to the greater demand and with the debt also possibly higher but not by as much, the debt to GDP ratio could fall.  And indeed, under conditions such as currently exist in the US and Europe, the debt ratio will almost certainly fall.

To see this, one can start with a simple numerical example.  Suppose one starts with a GDP equal to 100 units (it could be $100 billion), a public debt of 50 (or 50% of GDP, roughly where it was in the US in 2009), a multiplier equal to 2.0 (a reasonable estimate for the US in recent years), and a marginal tax rate on additional income of 30% (also a reasonable estimate for what it is for US federal government level revenues; it would be higher if one included state and local government revenues).

In these conditions, suppose government spending rises by 1 unit.  With a multiplier of two, GDP will then rise by 2 units.  Tax revenues will then rise by 0.6 units, when the marginal tax rate is 30% on the additional 2 units of GDP.  The government deficit, and hence the public debt, will rise by 0.4 units, equal to the extra 1 unit of government spending less the 0.6 units of additional tax revenue.  The resulting public debt will be 50.4, while GDP will then be 102, and the ratio of 50.4/102 is equal to 0.494.  Hence the debt ratio fell from 50% to 49.4% when government spending rose by 1.  Higher government spending led to a reduction in the debt to GDP ratio.  While the total debt rose, GDP rose by proportionately more, leading to a fall in the debt to GDP ratio.

Further numerical examples will help give a feel to what is going on:

Impact on Debt/GDP Ratio from a One Unit Increase in Government Spending
        Scenario: (a) (b) (c) (d) (e)
GDP: Y 100 100 100 100 100
Public Debt: D 50 70 30 50 50
multiplier: m 2.0 2.0 2.0 0.5 3.5
marginal tax rate: t 0.3 0.3 0.3 0.3 0.3
pre-change D/Y 0.500 0.700 0.300 0.500 0.500
Change in G 1 1 1 1 1
Change in Y 2 2 2 0.5 3.5
Change in D 0.4 0.4 0.4 0.85 -0.05
Resulting D/Y 0.494 0.690 0.298 0.506 0.483

Scenario (a) is the case just discussed.  With an initial public debt ratio of 50%, a multiplier of 2, and a marginal tax rate of 30%, a unit increase in government spending will lead the debt to GDP ratio to fall to 49.4%.  This is robust to different initial debt to GDP ratios:  The debt to GDP ratio will fall with higher government spending with an initial debt ratio of 70% (scenario (b), with the debt ratio where it was in FY2012) or at 30% (scenario (c), almost what the debt ratio had fallen to at the end of the Clinton administration, before the Bush tax cuts).

Under conditions where the economy is close to full employment, so that the multiplier will be relatively small, the debt ratio could rise with the higher government spending.  GDP will not rise by much, if at all, if the economy is already producing at or close to full employment levels.  The denominator in the ratio hence will not rise by much, if at all, while the numerator (the level of debt) will rise by the level of extra government spending, with only limited or no extra tax revenues to offset this since GDP has not increased by much.   Scenario (d) provides an example, with a multiplier of 0.5.  The debt ratio will rise from 50% to 50.6% in this example, when government spending rises by 1.

At the other extreme, a very high multiplier may lead to such a large increase in GDP that the extra tax revenues thus generated are greater than the increase in government spending, leading to an actual decrease in the deficit and hence the debt.  Scenario (e) presents an example, with a multiplier of 3.5.  Debt actually falls from 50 units to 49.95 units, despite the increase in government spending by 1 unit, and the debt to GDP ratio falls from 50% to 48.3%.

One will also get this result if the extra tax revenues generated for a given increase in GDP is sufficiently high.  The above examples assume a marginal tax rate of 30%.  More generally, if the marginal tax rate times the multiplier is greater than one (e.g. 30% times 3.5 = 1.05 in the example above), then the absolute value of the debt will fall with the higher government spending.

It may well be unlikely, however, that the multiplier will be as high as 3.5, even with the current high unemployment in the US and Europe.  Thus it is unlikely that the absolute value of the debt will fall with higher government spending, even in conditions of high unemployment.  But as was discussed above, with a reasonable estimate of the multiplier at around 2, one will see the debt to GDP ratio fall, under conditions such as now exist in the US and Europe.

For those with some mathematical expertise, it is straightforward to derive the specific conditions which will determine whether the debt to GDP ratio will rise or fall with an increase in government spending.  This requires some elementary differential calculus, and I will not go through the derivation here.  But the final result is that the debt to GDP ratio will fall if:

(t + D/Y) – (1/m) > 0

and the debt ratio will fall if the sum on the left is less than zero.  That is, the debt to GDP ratio will fall if the marginal tax rate (t), plus the initial debt to GDP ratio (D/Y), minus the inverse of the multiplier (m), is greater than zero (and will rise if the sum is less than zero). Thus if t=30%, D/Y=50%, and m=2 (so 1/m=0.5), with a sum then of 0.3 + 0.5 – 0.5 = 0.3, which is greater than zero, the debt to GDP ratio will fall.

The material above is straightforward.  There is nothing deep or complex.  It also just examines the immediate impact on the public debt to GDP ratio from an increase in government spending.  For a more elaborate look at the long-term impact, see the paper of Brad DeLong and Larry Summers published in 2012.  They show there that higher government spending will not only spur GDP in the short run under conditions such as exist now, but also that such spending will likely pay for itself in the long run through its long term positive impact on growth.

But this post simply focuses on the short term, and shows that counter to what many people might at first believe, higher government spending can lead to a fall in the public debt to GDP ratio.  All this result requires is the recognition that under conditions such as exist now, when unemployment is high and Central Bank controlled interest rates are close to zero, there will be a significant multiplier effect from an increase in government spending.  The resulting increase in GDP along with the extra tax revenues thus generated could very well then lead to a fall in the debt to GDP ratio.  Indeed, with the conditions and parameters such as now exist in the US and Europe, one should expect this result.

The Fiscal Multiplier: Econ 101

A.  Introduction

The “fiscal multiplier” (often referred to as just the “multiplier”) is simply the ratio of how much aggregate GDP will increase for a unit increase of fiscal spending.  Hence if fiscal spending increases by say $100 and aggregate GDP increases by $200 in response, the multiplier is equal to 2.  The concept is also often applied similarly to tax cuts of some dollar amount.

Under conditions where there is significant unemployment in an economy, an increase in government spending can be expected to have a multiple impact on GDP.  There will be a direct contribution to GDP from the increased production to provide for the demand from government, but also an indirect contribution as those being paid for the initial goods (whether newly employed workers or suppliers of inputs to the production of the good) will in turn spend at least some portion of their higher incomes on other goods or services in turn.  And this process will continue in further rounds.

While the concept is simple, the multiplier in practice is difficult to measure.  It is not a constant, but rather a definitional concept whose value will vary depending on the specific economic circumstances of the time and place.  It has also been controversial, as some economists both historically and even currently do not believe it is possible for an economy to be functioning at less than full employment.  For such economists, higher production from an increase in demand is not possible since the economy is already at full employment, and the multiplier must then always and everywhere be uniquely equal to zero.

But most economists recognize that it is possible for the economy to be at less than full employment.  This is especially clear today in most of the developed world, including in the US, Europe, and Japan, with unemployment high in each of these countries or regions.

The real debate, then, is about the size of the multiplier in a particular situation – whether it is low or high.  If low, then fiscal stimulus will not have much of an effect on increasing GDP, while fiscal austerity will not lead to a big reduction in GDP.  If high in contrast, fiscal stimulus will be quite effective in raising GDP, while fiscal austerity will lead to big reductions in GDP and consequent large increases in unemployment.

Recent work at the IMF, a conservative institution, on the size of the multiplier has brought this debate into the general news.  In particular, in June the IMF published a self-evaluation of the IMF supported (as well as EU and ECB supported) economic program in Greece.  It noted there (on page 21) that the fiscal multipliers assumed in that program turned out, based on actual experience, to have been too low.  This self-criticism was picked up in the general press, and many have questioned how the IMF (and the others) could have gotten this so wrong.

But judging the size of the multiplier in a particular place and in particular circumstances is not easy.  This Econ 101 blog post will discuss why the multiplier will vary in different countries and in different country circumstances.  And while it might be understandable how the multiplier might be misjudged ex ante in some concrete case, what is outrageous is not that initial misjudgment.  What is outrageous is that the policies that had been taken based on that earlier misjudgment were not then revised or reversed to reflect what had been learned.

B.  Why the Multiplier Will Vary

As noted above, the multiplier is not a constant, equal to the some particular value in all countries and under all circumstances.  Rather, it is a concept, expressing a relationship (between changes in GDP and changes in government spending) which will in general vary across different economies and across different circumstances in any particular economy.  Hence even if one had a good estimate of what it might be in one particular country under particular circumstances, one should not assume it would have that some value in another country or even in the same country under different circumstances.

Specifically, one should expect:

1)  The multiplier will vary across countries, depending on the size and structure of those countries:  In a large country such as the US, an increase in spending (both direct and indirect) will be met primarily by supplies originating in the US.  The multiplier will then be relatively large.  In contrast, higher spending in a small and open economy, such as Monaco to take an extreme example, will be met primarily by supplies originating elsewhere.  The multiplier will then be relatively small.   Most economies are in between these two in size, and one would expect the multiplier then also to be in between these two in size.

Note that this will depend not only on the size of the economy, but also its economic structure (the type of goods produced within that economy, as opposed to imported) and the nature of its trade regime.  Some economies are more open than others.

2)  The multiplier will vary depending on the current state of the economy – how far or close the economy is to full employment:  If unemployment is significant, an increase in demand can be met with an increased supply of goods, and an increase in employment of workers to produce those goods.  The multiplier will be relatively high.  In contrast, if the economy is at a time of close to full employment, an increase in demand for certain goods can only be met by reduced production of something else (with a shift in jobs from the latter to the former), so overall output might not rise by much.  In such circumstances the multiplier will be relatively low.

Hence if one had a good estimate of the multiplier in some particular economy at a point in time when the economy was close to full employment, one would greatly underestimate what the multiplier would be in that same economy at a different time when unemployment was high.

3)  The multiplier will vary depending on the form of the fiscal stimulus:  Fiscal stimulus programs can take the form of spending on newly produced goods (such as infrastructure), or on transfer programs to households (such as higher or extended unemployment benefits), or on tax cuts or tax rebates.  But while each might have a similar direct dollar impact on the fiscal deficit, the impact on GDP could vary widely.

Direct government expenditures on newly produced goods, such as new roads or school buildings, will likely have the largest impact on GDP.  The newly produced goods will, with certainty, be produced, and such product is a direct component of GDP (GDP stands for Gross Domestic Product).  And those newly employed to produce such goods (e.g. construction workers) will also then spend most or even all of their new earnings on goods they need.  The multiplier will be high.

The multiplier will also likely be relatively high on transfer programs that go to the unemployed and others who are relatively disadvantaged, as they will spend what they receive on goods that they and their family very much need. The multiplier will be less on transfer programs that benefit those who are better off (such as certain farm subsidies, for example, when they mostly benefit large and relatively well-off corporate farms), as such individuals or firms will likely save a higher share of such receipts.

And the multiplier might be quite small for tax cuts or tax rebates that go to upper income households, as they will likely save much of what they receive.

Hence the size of the multiplier will depend on the nature of the fiscal stimulus program.  Programs focussed on the direct production of goods, especially labor-intensive goods (such as the building and maintenance of much of infrastructure), or on transfers to the relatively less well off, can be expected to have a relatively high multiplier effect.  Programs focussed on transfers or subsidies going to the relatively well off, or tax cuts that accrue primarily to the relatively well off, can be expected to have a relatively low multiplier effect.

4)  The multiplier will vary depending on whether the stimulus (or austerity) programs are temporary or expected to be sustained:   Temporary tax cuts or tax rebates are a common component of stimulus programs, in part because they can be implemented quickly and easily.  However, households receiving a temporary tax cut or a one-time rebate will normally simply save a high share of what is distributed to them (or use the funds to pay down outstanding debt they might have).  The multiplier will then be relatively low or even negligible, as there would be little increased demand for goods to be produced.

5)  The multiplier will vary depending on the direction of change:  Many make the simplistic assumption that if the multiplier has some value for an increase in spending or for a tax cut, one will see the same value for the multiplier for a decrease in spending or a tax increase.  But there is no reason to assume this will be the case.  People will in general respond differently if facing an increase in income (such as from a tax cut) or a decrease (such as from an equal tax increase).  With a tax cut, the households might simply save most of what they receive, resulting in a low multiplier.  But with a tax increase (which one might see as part of an austerity program, for example), the households might be forced to scale back their consumption to pay the higher taxes, resulting in a relatively high multiplier when going in this downward direction.

Similarly, the multiplier impact when a worker is newly hired as a result of a stimulus program will likely be different than the multiplier impact when a worker is laid off as a result of an austerity program.  The multiplier impact is likely to be substantially greater (in the negative direction) when workers are laid off as such workers will likely be forced to scale back their consumption substantially.

6)  The multiplier will vary depending on the policy response of others:   While the government might launch a stimulus program, other economic actors might respond with policy changes of their own.  For example, a Central Bank might raise interest rates when the government launches a stimulus program, due perhaps to a concern on inflation (possibly a mis-guided concern, but nonetheless what they are acting on).  Raising interest rates would lead to a cut in investment, and hence the impact of the stimulus program on GDP might be constrained.  The multiplier would then be low.

Importantly, the ability of the Central Bank to respond by lowering interest rates to a cut-back in government spending, to offset what would otherwise be the contractionary effects of such a cut-back, is important to recognize and take into account.  In times like the present in the US, Europe, and Japan, when the interest rates set by the Central Bank are essentially at zero and cannot go lower, a cut-back in government spending cannot be offset by a cut in interest rates (interest rates are already as low as they can go), and the multiplier will be relatively high.  The fiscal contraction will lead to a large reduction in GDP.  In contrast, if the fiscal contraction is delayed until the economy is closer to full employment, with interest rates then positive and significant, the impact on GDP of a cut-back in government spending can be offset at that point by the Central Bank lowering interest rates, and output will not then fall.  The multiplier will at that point be close to zero.

This has extremely important implications for the design of fiscal adjustment programs.  There may well be a need eventually to reduce public debt to GDP ratios, by cutting back on government spending or increasing taxes.  But if this is done when there is significant unemployment and the Central Bank controlled interest rates are at or close to the zero lower bound, then the fiscal austerity programs will reduce demand and lead to a large fall in GDP (and consequent further rise in unemployment).  One should instead maintain fiscal demand until the economy has recovered sufficiently that one is close to full employment and interest rates are no longer at or close to zero.  At that point, a cut-back in government spending (or an increase in taxes) can be offset by the Central Bank through its management of interest rates, and GDP need not then fall.

Unfortunately, the US, Europe, and until recently Japan, have been doing the opposite since 2010.

The financial markets are another economic actor which can have an impact.  For example, in economies where the foreign exchange rate floats, the foreign exchange markets might respond to a stimulus program with a devaluation of the foreign exchange rate.  This devaluation would make exports more competitive (thus spurring production of exports), and imports more expensive (thus encouraging production of domestic substitutes for what had been imported), which would be expansionary.  The multiplier in such circumstances would then be relatively high.

7)  The multiplier will vary depending on the time frame:  So far we have not made any note of the time dimension, and have implicitly treated all the responses as taking place simultaneously.  But the time dimension does matter, as it takes time to implement programs, and then time for the multiple round responses to work themselves out.  Hence one should be clear on whether one is referring to the multiplier as the response in, say, the current quarter of a year, or over the next year, or over the next several years, or what.  The multiplier will be relatively low if measured as the impact on GDP in the current quarter, fairly large over the next year, and then begin to diminish thereafter.  And one then needs to be clear if one is referring to the multiplier in terms of the impact on GDP only within a certain period, or the cumulative impacts over a multi-year range.

C.  Conclusion

The multiplier is important, and a good deal of work has been done over the years to try to measure what it might have been in a particular time and place.  But factors such as those listed above have not always been taken into account when economists (including at the IMF) and analysts have sought to apply those results.

It has unfortunately been the case, for example, that estimates of the multiplier found when the economy was close to full employment, were then assumed to be similar when the economies at some later time were in a downturn and far from full employment.  Or cross-country differences have been ignored when the multiplier found for some small economy, say, was assumed to apply equally to a large economy.  Or the multiplier that might apply in an expansion resulting from a stimulus program was then assumed to apply similarly in a contraction resulting from an austerity program.  Or no attention was paid to how the multiplier will differ in a stimulus program depending on whether one is looking at new infrastructure work, or transfer programs, or tax cuts.  Or the multiplier for tax cut programs was treated as the same whether the tax cuts were going to the relatively poor or the relatively rich.

This has not always been the case.  Some economists and analysts have been careful.  But there has also been a lack of attention to these issues.  This does not mean one should ignore the multiplier, but rather that one needs to work with care.

Contribution to GDP Growth of the Change in Inventories: Econ 101

This is the first post in a series that I will label “Econ 101”.  Their purpose will be to explain some economic concept that might generally not be clear to many, yet often appears (and often incorrectly) in news reports or other items that readers of this blog might see.  This first Econ 101 post is on how changes in private inventories enter into the National Income and Product (GDP) accounts, where there is often confusion on the contribution of rising or falling inventories to the growth of GDP.

In the most recent (December 22) release by the government of the GDP accounts in the third quarter of 2011, growth in overall GDP was an estimated (and disappointing) 1.8%. But many news reports stated that private inventories fell, and that had these inventories not changed, GDP growth would have been 1.4% points higher, or a more respectable 3.2%.  Yet when one looks at the underlying GDP figures issued by the BEA (the Bureau of Economic Analysis, US Department of Commerce), one sees that the change in private inventories was essentially zero (and in fact was slightly positive).  If inventories did not fall, why did many commentators state that a fall in inventories reduced GDP growth in the quarter?

The confusion arises because while the GDP (Gross Domestic Product) accounts measure the flow of production (how much was produced during some period of time), and the flow of how much was then sold (e.g. for consumption or investment), inventories are a stock, and it is the change in the stock of inventories that enters into the GDP accounts.  GDP is the flow of goods and services produced in the economy, and these goods and services are then sold for various purposes, including private consumption, private fixed investment, government consumption and investment, and exports, with imports also a supply of goods that can be sold.  But goods produced in some period will not necessarily match goods sold in that same period.  The difference is accounted for by either a rise or a fall in inventories.  Hence the change in the stock of inventories, when added to final sales (with imports entering as a negative), will equal total goods and services produced, which is GDP.

From one period to the next, we are normally interested in how much GDP rose or fell in that period compared to the previous one.  And we are interested in seeing how much of that growth in GDP will match up with and can be accounted for by growth of consumption, investment, and other elements of final sales.  These demand components are important, particularly in the economy as it is now.  With high unemployment and production well less than capacity, production of goods and services is driven by the demand for them.  Hence one is looking at the change in consumption or fixed investment or government expenditures from one period to the next.  And as the balancing item between GDP production and final sales, one would now be looking at the change in the change in inventories.

The term “the change in the change in inventories”  is a mouthful, and not often seen in news reports (indeed, I have never seen it used).  But that is what then leads to the confusion.  In the third quarter of 2011 (in the estimates released by the BEA on December 22), the change in private inventories was essentially zero, as noted above.  But there had been some positive growth in private inventories in the second quarter of 2011. Hence, the change in the change in inventories, going from something positive to essentially zero, was negative.  That is, if inventories had continued to increase in the third quarter of 2011 as much as they had in the second quarter, GDP growth would not have been 1.8% but rather would have been 3.2%.  The change in the change in inventories meant GDP growth was 1.4% points less than what it otherwise would have been.

The point can perhaps best be illustrated by some simple numerical examples.  Suppose for some fictitious economy, that GDP (the production of goods and services) is initially 1000 (in, say, billions of dollars), while the total of final sales (for consumption, fixed investment, and so on) is 950.  With production of 1000 and sales of 950, inventories will increase by 50.  Assume the stock of inventories at the start of the period is 500, so the stock will total 550 (50 more) by the end of the period.  The figures are as in this table:

Period 1 Period 2 Change % Change
GDP 1000 1050 +50 5%
  Change in Inventories  50  80 +30 3.0% points
  Final Sales 950 970 +20 2.0% points
Stock of Inventories:
    Start 500 550
    End 550 630
In the second period, suppose that production (GDP) increases by 50, or 5%, to 1050, while final sales only grow by 20, to 970.  The difference between production and sales must accumulate in inventories, so the change in inventories will now be 80.  Therefore, the change in the change in inventories will be 30 ( =80-50), and the contributions to the 5% growth in GDP will be 2.0% points from the change in final sales, and 3.0% points from the change in the change in inventories.  It is also worth noting that the stock of inventories has now grown to 630 by the end of the second period, which is substantially higher as a share of GDP or of final sales than it was at the start of period 1.  Hence, there is reason to assume that producers will likely scale back production (GDP) in the near future as long as final sales growth remains so sluggish, as there is likely little reason to accumulate even more unsold inventories on the shelves.
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The second example will illustrate the case where inventories continue to rise, but at a slower pace than in the first period:
Period 1 Period 2 Change % Change
GDP 1000 990 -10 -1%
  Change in Inventories  50  20 -30 -3.0% points
  Final Sales 950 970 +20 +2.0% points
Stock of Inventories:
    Start 500 550
    End 550 570
In this example, final sales still grows by 20 to 970.  But producers here have scaled back production to just 990, or 1% below what it had been, with inventories now growing by just 20 rather than the 80 of the first example.  The change in inventories is still positive (at +20), but the change in the change in inventories is now negative, at -30.  The contributions to the -1% growth in GDP growth is made up of +2.0% points from final sales, and -3.0% points from the change in the change in private inventories.
As a final example, we will look at a case where the change in private inventories is negative.
Period 1 Period 2 Change % Change
GDP 1000 1050 +50 5%
  Change in Inventories -50 -20 +30 +3.0% points
  Final Sales 1050 1070 +20 +2.0% points
Stock of Inventories:
    Start 500 450
    End 450 430
Final sales once again grows by 20, although now from 1050 to 1070.  Sales is greater than production in each period, and inventories are drawn down by 50 in the first period and by 20 in the second period.  But while the change in inventories is negative in each period, that change is less negative in the second period than it is in the first.  That is, the change in the change in inventories is a positive 30, and this accounts for 3.0% points of the 5% growth in GDP.  It is also valuable to note that with inventories falling in each period, the total stock of inventories by the end of the second period is getting fairly low, so it is reasonable to expect that producers will aim to replenish inventories in future periods, with this then acting as a spur to growth.
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Such swings in inventories are often important when economic growth is turning around, as at the start of a recovery from a downturn, or at the start of a downturn following a boom.  An example is seen at the end of the most recent recession, in the middle of 2009. The economy was in a state of collapse in 2008, the last year of the Bush Administration, and this fall carried over into the first half of 2009.  This downturn was then halted and reversed as a result of the policies implemented at the start of the Obama Administration. GDP was falling at a huge 8.9% annual rate in the last quarter of 2008, and at a still very high 6.7% rate in the first quarter of 2009.  Growth was then still negative, but at only a 0.7% rate, in the second quarter of 2009, and then started to grow at a 1.7% rate in the third quarter, and at a 3.8% rate in the fourth quarter.
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The change in private inventories was negative in each quarter throughout this period. Specifically, private inventories fell by $200.5 billion in the second quarter of 2009, fell again by $197.1 billion in the third quarter, and fell again by a further $66.1 billion in the fourth quarter.  But the change in the change in private inventories was positive in the third and fourth quarters (while negative in each, they were becoming less negative), and this then accounted for a positive 0.2% points of the 1.7% growth in GDP in the third quarter, and a strong 3.9% points of the 3.8% growth in the fourth quarter (when final sales in fact declined slightly, accounting for a -0.1% contribution to growth in that period).
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To summarize:  As everyone knows from their first Econ 101 class in Macroeconomics, GDP is equal to Consumption + Investment + Government Spending + Net Exports (Exports minus Imports), where total Investment is equal to Fixed Investment plus the Change in Inventories.  The change in GDP will therefore equal the change in Consumption + the change in Investment + the change in Government Spending + the change in Net Exports, where the change in Investment will equal the change in Fixed Investment plus the change in the Change in Inventories.
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