Imports as a “Drag on the Economy”

A Wall Street Journal story of last week, “The Verdict on Trump’s Economic Stewardship, Before Covid and After,” makes many good points. It also falls into some popular economic errors. Here is an obvious one:

Trade itself turned out to be a drag on the economy. U.S. export growth slowed starting in 2018 as Mr. Trump’s tariff battles ramped up. The U.S. trade deficit, reflecting an excess of imports over exports, grew to $577 billion in 2019 from $481 billion in 2016.

We are told that imports or a trade deficit necessarily constitute “a drag on the economy.” This elementary error stems from the misunderstanding of a national-accounting identity: GDP = C + I + G + X – M. This identity is often misunderstood as meaning that M (imports) constitutes a “drag” on GDP because it subtracts from GDP measured as the sum of personal consumption expenditures (C), gross private investment (I), government expenditures for goods and services (G), and exports (E).

I have blamed the Wall Street Journal and other journalists before for repeating this myth: see my Regulation article, “Are Imports a Drag on the Economy,” Fall 2015. Perhaps one can find a serious economic argument to the effect that imports reduce GDP—although I and most economists since David Hume, Adam Smith, James Mill, or Jean-Baptiste Say don’t think so. But if such a serious argument exists, it is not that the trade deficit (X-M) subtract from GDP in an automatic, accounting, arithmetical manner as some people imagine is shown by the accounting identity above.

The demonstration is simple. National statisticians (the Bureau of Economic Analysis in the United States), in one of their ways of measuring GDP (from the expenditure side), subtract M because it is already included in their measures for C, I, and G. Consumption expenditures, as measured in the national accounts (in the United States as elsewhere) already incorporate imported consumption goods; investment expenditures already incorporate imported capital goods; and government expenditures already incorporate imported goods and services (foreign consultants, for example). Why do statisticians subtract M? Because imports, by definition, are not part of GDP (gross domestic product) and must not be included in any measure of the latter. M cannot reduce the measure of GDP because it is not part of it.

For another statement of my argument, see my “A Glaring Misuse of GDP,” Regulation, Winter 2016-2017. In still another Regulation article (“Peter Navarro’s Conversion,” Fall 2018), I summarize and illustrate the argument:

Imports have to be removed because they are not part of GDP, which is gross domestic production. … Think about the guy on the scales who subtracts 1 lb. to factor in the weight of his shoes; his weight doesn’t change if instead he subtracts 2 pounds because on that day he is wearing heavier shoes. Likewise, American output doesn’t change because more imports are both added and subtracted.

An economist with the Federal Reserve Bank of St. Louis, Scott Wolla also pointed out this misleading error: I reported on, and linked to, Wolla’s article in another Econlog post: “The St. Louis Fed on Imports and GDP,” September 6, 2018.

Many former college students who took a macroeconomic class and glanced at the accounting identity GDP = C + I + G + X – M in a (perhaps not so good) macroeconomic textbook make the same error. The Wall Street Journal should not.

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Tim Duy on fiscal stimulus

David Beckworth directed me to an interesting post by Tim Duy:

Most likely, net job growth will continue even if at a slower pace. That job growth will be sufficient to drive income growth, and income growth will support consumption. But what about the missing fiscal stimulus, you say? I know this will be widely hated, but the decline in spending in nominal and real terms at this point pretty much matches the decline in income excluding current transfer payments . . .

The fall in consumption exceeded the fall in incomes early in the cycle while, on net, transfer payments are ending up as forced saving. The virus is the key impediment to growth at this point; there are certain sectors of the economy, leisure and hospitality in particular, with limited prospects until the virus is under greater control. There isn’t really a debate on this point; there is simply a nontrivial supply-side constraint on the economy right now.

I don’t hate Tim Duy for saying that the key problem now is on the supply side, as I’ve also been making that argument.  That’s not to say that demand stimulus would have no value right now—both Duy and I would prefer somewhat higher inflation expectations—but this isn’t the main factor currently holding back the recovery.

Some people complain that the Fed’s new “average inflation targeting” policy is quite vague and ambiguous.  That’s true, but in an earlier blog post I argued that as a practical matter it is pretty clear what the Fed intends to do.  Duy linked to a speech by Chicago Fed president Charles Evans that confirms my prediction:

Forget the many years of underrunning 2 percent since 2008, and let’s just start averaging beginning with the price level in the first quarter of 2020. Core PCE inflation in the SEP is projected to be 1-1/12 percent this year and then gradually rise to 2 percent in 2023.12 Suppose it hits 2-1/4 percent in 2024 and then stays there. In this scenario, cumulative average core inflation starting from the first quarter of 2020 does not reach 2 percent until mid-2026. That is a long time. If you can produce 2-1/2 percent inflation in 2024, you can get there about a year quicker.

That was my view as well, that the Fed would start the clock at the beginning of 2020 and begin to push inflation a few tenths of percent above 2.0% in 2024, until the near-term inflation undershoot was offset.  I don’t think there’s much doubt any longer as to what the Fed intends to do.  The only question now is whether they will do what they promise or renege on their promise.  We’ll probably know the answer by 2025.

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Identifying monetary shocks

This post is a follow-up to my recent post on the “masquerading problem”. Recall that changes in interest rates are not a reliable indicator of changes in the stance of monetary policy. A new paper by Marek Jarociński and Peter Karadi discusses an interesting method of identifying monetary shocks:

Central bank announcements simultaneously convey information about monetary policy and the central bank’s assessment of the economic outlook. This paper disentangles these two components and studies their effect on the economy using a structural vector autoregression. It relies on the information inherent in high-frequency co-movement of interest rates and stock prices around policy announcements: a surprise policy tightening raises interest rates and reduces stock prices, while the complementary positive central bank information shock raises both. These two shocks have intuitive and very different effects on the economy. Ignoring the central bank information shocks biases the inference on monetary policy nonneutrality.

I see this as a promising first step toward the market monetarist goal of using asset prices linked to NGDP as an indicator of monetary policy.  To be sure, stock prices are a very noisy indicator of NGDP expectations, but they are better than changes in short-term interest rates, which often don’t even have the right sign.  Tight money can occasionally cause lower nominal interest rates, as NeoFisherians have pointed out.  In the Jarociński and Karadi paper, only interest rate increases associated with falling stock prices are identified as an actual move toward tighter money.  Ideally we’d replace stock prices with NGDP futures prices.

This article was sent to me by Basil Halperin, who also made the following comment about my earlier masquerading problem post:

The Wolf paper mentions the “sign restrictions” identification strategy that is usually credited to Uhlig (2005). . . .
I think of your 1989 JPE with Silver as having done a proto-version of this approach! Both your paper and the Uhlig paper use the idea that “monetary shocks should send output and inflation in the same direction” to identify which episodes are demand shocks, versus which are supply.
Readers who are studying economics might be interested in the background of our 1989 JPE paper.  In the late 1980s, I was interested in studying business cycles.  When I looked at the data, the 1920-21 depression seemed like the purest example I could find of a stereotypical business cycle.  It saw the steepest one-year drop in industrial production, the steepest one-year drop in the monetary base, the steepest one-year drop in the price level, and the steepest one-year rise in real wages.  This made me sympathetic to the sticky wage theory of the business cycle, which is based on the idea that a severe deflation is contractionary because wages fall more slowly than prices.
Later I discovered research that found real wages to be procyclical, falling during booms and rising during recessions.  This surprised me, so I tried to reconcile these results with the evidence from 1921.  It turns out that the more recent studies that found procyclical real wages tended to rely heavily on some business cycles associated with the two oil shocks (1974 and 1979), which were periods when inflation rose and real wages fell during recessions.
Steve Silver and I responded with a study that divided business cycles up into two types, those with procyclical inflation (like 1921) and those with countercyclical inflation (such as 1974 and 1979).  Real wages were countercyclical during demand-side recessions such as 1921 and procyclical during the supply-side recessions of the 1970s.  This pushed me even more firmly into the sticky wages camp, as both findings are consistent with the idea that nominal wages are sticky when the price level moves suddenly and unexpectedly.
This work also dovetails nicely with my general view that NGDP is a good measure of monetary policy.  During supply shocks, prices and output move in the opposite direction, and NGDP doesn’t necessarily change all that much.  In contrast, tight money causes both falling prices and falling output.  If nominal wages are sticky then this results in higher real wages and higher unemployment.  This is why I later switched my focus from price level shocks to NGDP shocks. NGDP measures monetary shocks better than does the price level. George Selgin also reached this conclusion a few decades back, albeit for a slightly different set of reasons.
Perhaps it might seem “unscientific” to base one’s views on a single episode like 1920-21.  But my view is that extreme events are very revealing.  Yes, you should not use data mining to test a model, but data mining is a very good way to develop a model.  Then test it with a completely different set of data.  I’d encourage younger economists to pay close attention to Fed announcements that led to unusually pronounced real time market reactions, such as January 2001, September 2007 and December 2007.  In those cases, the background “noise” is less likely to disguise the causal relationships.  In my book on the Great Depression I discuss numerous such natural experiments.

PS.  There was a slightly steeper drop in IP right after WWII, but that was clearly a very unusual business cycle.  There was a larger drop during the Great Depression, but spread over a much longer period of time.  So I believe 1920-21 is the purest negative demand shock.  Furthermore, the drop in demand was not endogenous.  It wasn’t partly caused by bank failures as in the 1930s; it was almost entirely due to the Fed sharply reducing the monetary base.

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This isn’t a Keynesian business cycle

In the standard Keynesian business cycle model, consumption is driven by changes in disposable income. This underlies the famous “multiplier” concept. But the Keynesian model doesn’t fit this particular business cycle (nor does the monetarist model.)

The current condition of the US economy is very weird. Housing is booming and many retailers are doing OK. Meanwhile, many services that involve human interaction are still deeply depressed, and likely to remain so until there is a vaccine or cure (or herd immunity.) Fiscal stimulus can’t fix that, although I believe their is a humanitarian argument for additional unemployment compensation during an unusual crisis like this one.

This graph shows the unusual and “unKeynesian” nature of the current business cycle:

Those are supposed to be positively correlated.  Disposable income took another dive in August, but consumption actually increased.  The economy is not being held back by a lack of income.  Where people feel they can spend safely, they are doing so.  To get back to full employment we need to address the pandemic.  If we do so, the labor market will recover very quickly (assuming any sort of half decent monetary policy.)

Today’s jobs report highlights the weird nature of this “business cycle”.  In October 2009, unemployment peaked at 10.0%.  It took 35 months for the unemployment rate to fall below 8%.  In July, the unemployment rate was 10.2%.  It took two months for the rate to fall below 8%.  And those two months were a period of severe “fiscal austerity” when Keynesian economists told us we could expect the recovery to stall. In fairness to the Keynesians, if the pandemic continues then I expect the unemployment rate to level off soon, as certain service sectors will remain severely depressed.

Whatever you want to call this, it isn’t you grandad’s recession.

PS.  I agree with Jim Bullard, who’s views are discussed in an excellent Tim Duy post.

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The masquerading problem

For the past four decades, I’ve been complaining about the way the profession does empirical work on monetary policy. The studies often use “vector autoregressions” to estimate the impact of changes in the policy interest rate. Unfortunately, interest rates are not monetary policy. You can try to estimate the part of interest rate movements that are “exogenous” and hence reflective of monetary policy, but in practice this is almost impossible.

So after four decades of VAR studies by the best and the brightest in the economics profession, where are we? Here’s the abstract to a promising new paper by Christian Wolf of Princeton University:

I argue that the seemingly disparate findings of the recent empirical literature on monetary policy transmission are in fact all consistent with the same standard macro models. Weak sign restrictions, which suggest that contractionary monetary policy if anything boosts output, present as policy shocks what actually are expansionary demand and supply shocks. Classical zero restrictions are robust to such misidentification, but miss short-horizon effects. Two recent approaches – restrictions on Taylor rules and external instruments – instead work well. My findings suggest that empirical evidence is consistent with models in which the real effects of monetary policy are larger than commonly estimated.

Many previous VAR studies have found monetary shocks to have relatively weak effects on the economy.  But these shocks tend to conflate reductions in interest rates with expansionary monetary policy.  In fact, in the vast majority of cases a decline in interest rates reflects slower growth in aggregate demand, not easier money.  So it’s no surprise that lower interest rates don’t seem to provide much of a boost to the economy.  Lower interest rates are not easier money:

Sign restrictions, as in Uhlig (2005), are vulnerable to expansionary demand and supply shocks “masquerading” as contractionary monetary policy shocks, which then seemingly boost – rather than depress – output. . . . For monetary policy transmission, my results encouragingly suggest that, first, recent advances in identification effectively address the masquerading problem, and second, even small sets of macro observables may carry a lot of information about policy shocks. Viewed in this light, I conclude that existing empirical work quite consistently paints the picture of significant, medium-sized effects of monetary policy on the real economy.

This “masquerading problem” is sometimes called the identification problem; it’s what happens when people engage in reasoning from a price change.

After forty years, economists yet to develop a generally accepted VAR model of the monetary policy transmission mechanism.  Like fusion power, there’s a small chance that it may happen some day.  But there’s almost no chance I will live long enough to see this approach yield useful results.  The profession would be much better off switching to an approach that used NGDP growth expectations as the primary indicator of monetary policy shocks, and then develop models to estimate those expectations using real time data from asset markets.  Interest rates are not a useful variable when analyzing monetary policy.

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Stephen Williamson on NGDP level targeting

Over at TheMoneyIllusion I did a post discussing Steve Ambler’s presentation on NGDP targeting, and Nick Rowe’s subsequent discussion. Now I’d like to address some concerns expressed by Stephen Williamson.

One concern is that NGDPLT (or average inflation targeting) might be rather complicated to communicate. I believe that’s true of average inflation targeting, but not NGDPLT. Williamson mentioned that each year there would be a different NGDP target growth rate, depending on whether current NGDP was above or below the target path. But I believe it’s a mistake to think in terms of growth rates when evaluating a level targeting regime.

Consider the analogy of exchange rates under the Bretton Woods regime. The British pound was targeted at $2.80, plus or minus 1%. In my view that’s a very simple and easy to understand system. But if you consider the exchange rate in terms of growth rates, it might seem very complicated. Thus if the current exchange rate is $2.82, (i.e. slightly overvalued) then the Bank of England might be said to “target a negative growth rate of the exchange rate” until the pound returns to $2.80. The opposite would be true if the exchange rate were currently $2.78. And how long would it take to return the exchange rate to the target?

I favor a system where the Fed targets 12-month forward NGDP at exactly the rate implied by a predetermined target path, growing at 4% per year. The focus should not be on current NGDP, or the expected growth rate over the next 12 months, rather the focus should always be on the expected level of NGDP in 12 months. And that expected value should always be equal to the target value. In other words, monetary policymakers should “target the forecast”. Over time, I believe that people would begin to think in level terms, just as with they did with exchange rates under Bretton Woods.

If 12 months is too short (arguably true in the special case of Covid-19) then use a 24-month forward target.  But even with inflation targeting there will be special cases, as with severe supply shocks.

Williamson also argued that NGDPLT might lead central banks to adopt a “lower for longer” policy after an event like 2008, as both RGDP and inflation would be below trend.  In contrast, with an inflation target the central bank need not make up for depressed RGDP.  (Actually, with the Fed’s dual mandate that distinction is less clear, but I’d like to focus on some other issues.)

I have two responses to the questions raised by Williamson:

1.  I believe it’s incorrect to treat the severe NGDP gap of 2008-09 as a given.  In my view, the big drop in NGDP was mostly caused by the Fed’s unwillingness to adopt a policy of 5% NGDP level targeting in 2007.  Had such a policy been in place, the drop in NGDP during 2008-09 would have been far smaller.  This is consistent with models developed by Michael Woodford and others, where current levels of aggregate demand (NGDP) are heavily dependent on expected future aggregate demand, i.e. expected future path of monetary policy.  In 1933, FDR raised current gold prices by promising to raise future gold prices.  Then in 1934, FDR did raise the price of gold from $20.67 to $35/oz.  If the Fed promises to quickly push NGDP back to the 5% growth trend line, then NGDP will fall less sharply below the trend line in the short run.  (Of course that’s not to say there wouldn’t be a recession in 2008-09, but it would have been considerably milder.)

2.  I believe it is a mistake to assume that if a central bank did X and fell short of its inflation and/or NGDP goal, it would have had to do 2X or 3X to have hit the goal.  My claim sounds counterintuitive, but in fact my argument has an affinity to NeoFisherian ideas that have been developed by Williamson.  The very low interest rates of 2009-15 to some extent reflected the low levels and growth rates of nominal GDP during this period.  With higher NGDP and/or faster expected growth in NGDP, the equilibrium (natural) interest rate would have been higher in nominal terms, perhaps allowing the central bank to hit its policy target with a higher policy interest rate.

In 2001, Lars Svensson proposed a “foolproof” method for Japan to escape its liquidity trap.  Svensson’s proposal called for a one-time depreciation of the yen, but the most important part of the proposal was that the yen would subsequently be pegged to the US dollar.  In the long run, this would raise Japan’s inflation close to US levels, due to purchasing power parity.  But due to interest parity it would also raise Japan’s nominal interest rates up to US levels, which were still well above zero back in 2001.  I believe Williamson would recognize Svensson’s proposal as being NeoFisherian in spirit, even though Svensson himself is a New Keynesian.  Svensson reassured his readers that the policy would be expansionary “in spite of” of higher Japanese nominal interest rates, but a NeoFisherian would say there’s no need to say “in spite of”.

Monetary policy affects interest rates in two ways.  First, policy can target a short-term interest rate.  Second, a change in the policy regime can impact the equilibrium or natural rate of interest.  In monetary policy models, the policy stance is often described as the difference between the policy interest rate and the equilibrium rate.  My argument is that a shift to a 5% NGDPLT target path in 2007 would have radically boosted NGDP growth expectations during 2008.  Actual NGDP expectations fell sharply in the second half of 2008, even for 2009 and 2010.  With NGDPLT, expectations for future NGDP would have held up better during 2008, and thus the equilibrium interest rate would have been higher.

This does not mean that the Fed could have gotten by with a higher target interest rate.  We know that the actual target rate was too high to maintain adequate NGDP growth (or even 2% inflation) in 2009.  So we needed a lower interest rate relative to the equilibrium rate. Whether we needed a lower interest rate in absolute terms is uncertain.  If a switch to NGDP level targeting had raised the equilibrium interest rate in 2008, then the effect on the actual short-term interest rate would be ambiguous.  It depends on whether the Keynesian effect or the NeoFisherian effect was dominant.

We should never assume that if low rates and lots of QE failed, then even lower rates and even more QE would have been needed to hit the target.  That’s one option, but regime change is another.  The Australian central bank did not cut rates to zero, and didn’t do any QE, and yet completely avoided recession in 2008-09.  A credible and successful policy of maintaining adequate NGDP growth expectations in the long run is the best way of keeping equilibrium interest rates above zero, and avoiding the need to do QE.

 

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Congress >>> economics profession

The Joint Economic Committee in Congress put out its annual report on the economy, written by Alan Cole. My overall impression is that the JEC has a better grasp of real world macroeconomics than many people at top 10 econ departments.

Let’s start with their diagnosis of the Great Recession:

Unfortunately, Federal Reserve policy from 2007-2018 erred too far towards curbing the growth of nominal spending—a stance known colloquially as “too tight” monetary policy. The result was a long, persistent “output gap,” or shortfall in GDP relative to what the economy could have produced with more ample nominal spending. While not the only policy problem of the time period, the output gap was a clear consequence of the Federal Reserve’s choice of policy anchor and its level of commitment to the anchor.

The mass unemployment that followed the 2008 financial crisis was an economic disaster whose effects will be felt for years to come. Americans lost trillions of dollars of income and tens of millions of years of work. The job losses were also concentrated among disadvantaged groups, increasing inequality along the dimensions of both education and race.

This era is useful to study because it can inform policy in future recessions, including, to some extent, the current one. A well-chosen and consistent monetary policy anchor will not solve every problem—and certainly not ones directly related to public health—but it can facilitate the execution of financial and business contracts and shore up the social contract by lowering uncertainty about the future.

How many macroeconomists understand that the Great Recession was caused by a tight money policy by the Fed?  You could almost count them on one hand.

The report cites Kevin Erdmann’s excellent book on the housing crisis:

[I]n his book Shut Out, Kevin Erdmann notes that the Federal Reserve as a whole would issue statements describing the weakness in the housing market as a “correction,” suggesting a kind of normative view that housing prices should fall.31 The Federal Reserve kept this language even well into the decline of employment measures. The focus on moral hazard and housing prices largely detracted from attention to an ailing labor market.

Most economists believe the Fed was “doing all it could” in 2008.  The JEC reports understands that actual policy was quite schizophrenic, both expansionary and contractionary at the same time:

Taken separately, the bailout and interest rate decisions are coherent. But together, it is difficult to square them. As the Federal Reserve told it, spending enabled by emergency below-market-rate liquidity injections to Bear Stearns was good spending that helps Main Street, while spending enabled by a federal funds rate of (for example) 1.75 percent would have been bad spending that would spur inflation.

This pattern of easier credit for troubled financial institutions but tighter credit than necessary for the rest of us continued throughout 2008: as George Selgin documents, the Federal Reserve actually took care to offset its emergency operations’ effect on overall demand. Increases in credit to troubled banks were matched with corresponding decreases in credit elsewhere in the system.34 In Bernanke’s words, this was done to “keep a lid on inflation.”35

One tool in this offsetting process was interest on excess reserves (IOER). In October of 2008, the Federal Reserve began paying IOER.36 This policy induced banks to hold reserves and earn interest from the government rather than lending to private-sector individuals or institutions. This constrained credit for the private sector, outside of the banks that were rescued with below-market-rate lending.37

It’s as if the Fed simultaneously believed the economy faced a danger of too little spending and too much inflation—-which is literally impossible!!

The report also correctly describes how the Fed completely screwed up its forward guidance:

But there was a problem with forward guidance in the 2010s: Federal Reserve communications often described a hawkish reaction function—an inclination to run monetary policy relatively tightly.

Consider the Federal Reserve Board’s projections from January 201240, when interest rate predictions (often known as “dot plots,” for the way they were frequently charted) had just been issued for the first time. The projections told us that the median participant in the exercise believed that 2014 was the appropriate year for interest rates to rise. They also told us some other things about 2014: that participants believed Core PCE inflation would be below-target in the range of 1.6 to 2.0 percent, and that participants believed the unemployment rate would be in the range of 6.7 to 7.6 percent.

Put together, these predictions paint a clear picture of extraordinarily tight monetary policy. They told us that a Federal Reserve faced with an economy with elevated unemployment and below-target inflation would act to curb spending by tightening credit.

There’s also a recognition that the unemployment rate is often a useful warning sign of recessions—the Sahm Rule:

Recent work by the Federal Reserve has affirmed this view of employment measures. Economist Claudia Sahm devised an algorithm colloquially known as the “Sahm Rule,” which treats sudden rises in the unemployment rate as reliable early warning signs of a contraction.44 While the Sahm Rule is based on the official unemployment rate for simplicity’s sake and to facilitate comparability across time, it is likely that other employment measures, such as payroll surveys or unemployment claims, could be used as additional data points to scan for early signs of recession.

Most economists put too much weight on interest rates as an indicator of the stance of monetary policy, which led them to (wrongly) assume that policy was accommodative during 2008.  The JEC report understands that rates are not a good policy indicator:

FOMC statements have frequently identified low interest rates as a sign of accommodative policy.

This is not always and everywhere correct. Neither is the converse: that high interest rates are a sign of tight policy. As Milton Friedman observed in his famous American Economic Association presidential address:

As an empirical matter, low interest rates are a sign that monetary policy has been tight-in the sense that the quantity of money has grown slowly; high interest rates are a sign that monetary policy has been easy-in the sense that the quantity of money has grown rapidly.45

This observation—made in 1968—has largely held up, and in fact predicted to some degree both the late 1970s (when, despite high interest rates, inflation soared to record levels) and the early 2010s (when, despite low interest rates, inflation remained persistently below target and unemployment remained elevated.)

They suggest that NGDP growth is a superior policy indicator:

Scott Sumner phrases it in an improved and more modern formulation.46

Interest rates are not a reliable indicator of the stance of monetary policy. On any given day, an unexpected reduction in the fed funds target is usually an easing of policy. However, an extended period of time when interest rates are declining usually represents a tightening of monetary policy. That’s because during periods when interest rates are falling, the natural rate of interest is usually falling even faster (due to slowing NGDP growth), and vice versa.

The natural rate of interest is another economic abstraction that is hard to pin down precisely, but Sumner can be loosely translated as follows: during periods where the central bank is cutting interest rates, the risk-adjusted attractiveness of private-sector investments is falling even faster, so savers are still crowding into government bonds even at the lower rates.

Sumner considers the growth rate of NGDP a better guide to the stance of monetary policy. A policy that enables an acceleration in spending—however it is implemented—is loose, and one that forces a deceleration or contraction—however it is implemented—is tight. This formulation—based on effects—seems more appropriate than a measure based on interest rates alone.

The report then explains why measuring the policy stance correctly is so important:

Why are the semantics here important? First, because effects matter. Monetary policy stances are named after their intended effects; loose or accommodative or expansionary monetary policy should presumably be loosening, accommodating, or expanding something. Tight or contractionary policy should presumably be tightening or contracting something.

Second, semantics are important because names have an effect on the policy’s politics. The Federal Reserve in 2015 had essentially achieved some relatively-normal results for years: steady improvement in the employment rate, steady (though below-target) core inflation, and steady four percent growth in NGDP, which is also a normal result. However, it labeled these policies “accommodative.” This lent credibility to the plausible-sounding-but-wrong critique that the low interest rates at the time were “artificial” in a way that higher interest rates would not have been. It put the FOMC under pressure to “normalize” policy by tightening, which it did by the end of the year.

Third, a results-based measure of the stance of monetary policy, such as NGDP growth, appropriately captures the effects of policies that do not involve the setting of short-term interest rates: for example, quantitative easing or forward guidance.

The report also contains excellent policy suggestions:

A number of market indicators can help the Federal Reserve make good predictions about the future. Mechanically tying Federal Reserve actions to market data is largely not a reasonable policy option, but markets can help the Federal Reserve predict the consequences of policy.

And:

The dual mandate leaves much room for ambiguity in terms of how to weight unemployment and inflation concerns; however, it is possible to integrate inflation and unemployment data into a single mandate that implicitly contains both components. The most promising methods for this begin with the observation that inflation is a price, and employment is a quantity. Therefore, they look to measures of price multiplied by quantity.

Fortunately, many such metrics exist. One of the most obvious of these is nominal GDP. The idea of targeting nominal GDP originated with monetary economist Bennett McCallum,48 but also has been advocated by other economists such as Scott Sumner, Christina Romer,49 Jan Hatzius,50 and Joshua Hendrickson.51 While there are some technical issues implementing a nominal GDP target in real time, economist David Beckworth, another advocate, proposes methods to predict nominal GDP more quickly, including the use of new data sources or futures markets.52 At a minimum, stable nominal GDP growth is an excellent medium- and longer-run measure of central bank performance.

Level targeting is especially important:

Level targeting is perhaps the single most effective zero lower bound policy, and likely has benefits even outside of the zero lower bound. The idea of “level targeting” is to have a consistent long-run growth path in mind for the target variable, not just growth rate to target anew each period.

There are two strong reasons to believe a level target would be effective. The first is that level targets would do a better job of anchoring expectations for long-term contracts, such as mortgages. For example, it is considerably easier for a mortgage lender to operate if she has at least a general sense of what nominal incomes in America will look like in the 30th year of the loan. Will they double? Will they triple? A nominal income level targeting regime can actually provide an answer to that question, making long-term contracts considerably easier to write. Similarly, if a pension plan were interested in implementing a cost-of-living adjustment to benefits based on inflation, it would be easy to make long-run projections under an inflation level targeting regime.

The second reason for believing in the effectiveness of a level target is that a level target constitutes a kind of forward guidance, which—through its impact on expectations, can actually work backwards in time. In promising a steady long-run path, it encourages people to invest more steadily in the present, knowing that over the long run, rough patches will be smoothed out.

Nominal GDP level targeting, or NGDPLT, is one of the most popular uses of the level targeting idea. Level targeting dovetails particularly well with NGDP targeting because it turns the target into a long-run goal. In a level-targeting regime, short-run blips like revisions to GDP data are understood to be less consequential; instead the central bank maintains focus on keeping the long-run path steady.

Honestly, this report is far better than 90% of the articles one reads in top level economics journals.  Its fine to be able to write down highly mathematical models of the economy, but one also needs to have an intuitive grasp of which economic concepts are relevant to the sort of macroeconomic problems faced by real world economics.   Alan Cole definitely understands the role of monetary policy in business cycles.

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Lesson of Abenomics

With the recent resignation of Shinzo Abe, there have been a number of articles analyzing the record of Abenomics. There seems to be pretty general agreement on two points:

1. Japan’s economy improved after Abe took office at the beginning of 2013. Deflation came to an end, nominal GDP began rising, the public debt was brought under control, and unemployment fell to just over 2%.

2. The policy was not completely successful. Most notably, inflation continued to run well below the 2% target set by the Bank of Japan.

I believe that summary is correct. Where I part company with other pundits is in the lessons that Abenomics offers for monetary and fiscal policy. The Economist is fairly typical:

The first lesson is that central banks are not as powerful as hoped. Before Abenomics, many economists felt Japan’s persistent deflationary tendencies stemmed from a reversible mistake by the Bank of Japan (boj). It had combined fatalism with timidity, blaming deflation on forces outside its control, and easing monetary policy half-heartedly. In 1999 Ben Bernanke, later a Fed chairman, called on the boj to show the kind of “Rooseveltian resolve” that America’s 32nd president showed in fighting the Depression. . . .

The central bank is doing everything it can to revive private spending. Until it succeeds, though, the government has to fill whatever gap in demand remains. The shortfall in private spending is what makes government deficits necessary.

This seems to be the consensus as to the “lessons” of Abenomics.  Monetary stimulus is not enough; you also need fiscal stimulus.  And yet if you look at the actual record of Abenomics, there’s not a shred of evidence to support this claim, indeed the opposite seems to be the case.

For nearly two decades before Abe took office, Japan ran perhaps the largest combined monetary/fiscal stimulus in human history, at least during peacetime.  Remember, combined fiscal/monetary stimulus is the new consensus, the policy that most pundits in academia and the media now favor.  And what was the result of this massive stimulus?  Basically zero growth in nominal aggregate demand for almost two decades, a record even worse than seen in slow growing Italy.  If you’d told economists in the early 1990s that over the following 20 years Japan would mostly hold interest rates close to zero and increase the national debt from less than 70% of GDP to roughly 230% of GDP, and still have virtually no growth in nominal GDP, they would have responded that we need to abandon the standard textbook model of economics, as what we are teaching our students is clearly wrong.  Instead, we responded to this amazing analytical failure by doubling down on the very same flawed theory.

The massive fiscal stimulus came to an end with Prime Minister Abe.  Taxes were raised several times and the national debt leveled off at just over 230% of GDP.  Instead of a combined monetary fiscal stimulus, Abe relied on monetary stimulus and fiscal austerity.  And the Japanese economy actually improved!

I must admit that I am perplexed as to how my fellow economists draw their “lessons” from this record.  When people question monetary stimulus by pointing to the fact that Japan fell short of its 2% inflation target under Abe, I respond, “so do more”.  This doesn’t seem to convince anyone.  People seem to think I’m cheating, coming up with a theory that’s unfalsifiable.  “Yeah, you can always say they didn’t do enough.”

But when it comes to fiscal policy, this skepticism goes right out the window.  If I point out that the huge Japanese fiscal stimulus of 1992-2012 failed boost aggregate demand, they say the Japanese should have done even more fiscal stimulus, as if boosting the national debt from less than 70% to 230% of GDP is not enough.  When I point out that the Bush tax cuts of 2008 failed, they say the tax cuts should have been even bigger.  When I point out that the Obama stimulus of 2009 led to an unemployment rate that was far higher than proponents predicted even in the absence of stimulus, they say the stimulus should have been even bigger.  When I point out that the economy actually sped up in 2013, despite widespread Keynesian predictions that it would slow due to austerity, they say that without austerity it would have improved even more.  When I point out that the economy did not fall off the cliff at the end of July when Congress failed to renew the fiscal stimulus, they say it would have improved even more with additional stimulus (even though the fall in unemployment in August was the second largest in history.)

Now it’s certainly possible that I’m wrong and the Keynesians are right about fiscal stimulus.  Counterfactuals are tricky.  Maybe in all of these cases if they had only done more the results would have been better.  But in that case I’m honestly confused as to why I’m not allowed to argue the BOJ should have done more monetary stimulus.  Especially since while fiscal stimulus might become costly in the future if interest rates rise above zero, monetary stimulus is actually profitable, as central banks earn income on the assets they purchase with zero interest base money.  It’s monetary policy that seems to have truly unlimited “ammunition”, not fiscal policy.

Nonetheless, I’ve been beating my head against the wall for so long on this issue that I feel I need to change the argument.  Thus I’ve recently focused not so much on the claim that Japan needed to do more, rather that Japan needed to do different.  The ultra-low rates and massive QE are actually a symptom of previous tight money mistakes.

For example, the yen was about 124 to the dollar in mid-2015.  Today it’s roughly 105 to the dollar.  If Japan had simply pegged the yen to the dollar at 124 back in 2015, Japanese interest rates actually would have been higher over the following 5 years, mirroring the rise in interest rates in the US during this period (due to interest parity).  Monetary policy would have looked tighter to the Keynesian skeptic who (wrongly) feels that the actual Japanese monetary policy was highly expansionary, and ineffective.  And yet because the yen would have been far weaker, Japan would have actually experienced higher inflation than otherwise.  Indeed Lars Svensson made essentially this argument back in 2003, when he described a “foolproof” way for Japan to escape a liquidity trap.  He also noted that the higher nominal interest rates would be nothing to worry about, as this policy would have reduced the real interest rate in Japan, due to higher inflation expectations.

There are political difficulties with pegging the yen to the dollar, but Japan could have achieved a similar result by setting an aggressive price level target combined with a “whatever it takes” approach to QE.

So today I say to Japan, “don’t do more, do different.”

And I say to my fellow economists, “use the same criterion for drawing lessons from monetary policy as you use for drawing lessons from fiscal policy.”

PS.  Some economists do econometric tests of fiscal policy efficacy.  Elsewhere, I’ve criticized those tests for ignoring monetary offset.

 

 

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What do models tell us?

Josh Hendrickson has a new post that defends the use of models that might in some respects be viewed as “unrealistic”. I agree with his general point about models, and also his specific defense of models that assume perfect competition. But I have a few reservations about some of his examples:

Ricardian Equivalence holds that governments should be indifferent between generating revenue from taxes or new debt issuances. This is a benchmark. The Modigliani-Miller Theorem states that the value of the firm does not depend on whether it is financing with debt or equity. Again, this is a benchmark. Regardless of what one thinks about the empirical validity of these claims, they provide useful benchmarks in the sense that they give us an understanding of when these claims are true and how to test them. By providing a benchmark for comparison, they help us to better understand the world.

With all that being said, a world without “frictions” is not always the correct counterfactual.

Taken as a whole, this statement is quite reasonable.  But I would slightly take issue with the first sentence, which is likely to mislead some readers.  Ricardian Equivalence doesn’t actually tell the government how it “should” feel about the issue of debt vs. taxes, even if Ricardian Equivalence is true.  Rather it says something like the following:

If the government believes that debt issuance is less efficient than tax financed spending because people don’t account for future tax liabilities, that belief will not be accurate if people do account for future tax liabilities.

But even if people do anticipate the future tax burden created by the national debt, heavy public borrowing may still be less efficient than tax-financed spending because taxes are distortionary, and hence tax rates should be smoothed over time.

I happen to believe Ricardian Equivalence is roughly true, but I still don’t believe the government should be indifferent between taxes and borrowing.  Similarly, I believe that rational expectations is roughly true, and yet also believe that monetary shocks have real effects due to sticky wages.  I believe that the Coase Theorem is true, but also believe that the allocation of resources depends on how legal liability is assigned (due to transactions costs).  Models generally don’t tell us what we should believe about a given issue; rather they address one aspect of highly complex problems.

Here’s Hendrickson on real business cycle theory:

Since the RBC model has competitive and complete markets, the inefficiency of business cycles can be measured by using the RBC as a benchmark. In addition, if your model does not add much insight relative to the RBC model, how valuable can it be?

[As an aside, I agree with Bennett McCallum that either the term ‘real business cycle model’ means a model where business cycles are not caused by nominal shocks interacting with sticky wages/prices, or else the term is meaningless.  There is nothing “real” about a model where nominal shocks cause business cycles.]

Do RBC models provide a useful benchmark for judging inefficiency?  Consider the following analogy:  “A model where there is no gravity provides a useful benchmark for airline industry inefficiency in a world with gravity.”  It is certainly true that airlines could be more fuel efficient in a world with no gravity, but it’s equally true that they have no way to make that happen.  I don’t believe that gravity-free models tell us much of value about airline industry efficiency.

In my view, the concept of efficiency is most useful at a policy counterfactual.  Thus monetary policy A is inefficient if monetary policy B or C produces a better outcome in terms of some plausible metric such as utility or GDP or consumption.  (I do understand that macro outcomes are hard to measure (especially utility), but unless we have some ability to measure outcomes then no one could claim that South Korea is more successful than North Korea.  I’m not that pessimistic about our knowledge of the world.)

In my view, you don’t measure inefficiency by comparing a sticky price model featuring nominal shocks against a flexible price RBC model, rather you measure efficiency by comparing two different types of monetary policies in a realistic model with sticky prices.

That’s not to say that there are not aspects of RBC models that are useful, and indeed some of those innovations might provide insights into thinking about what sort of fluctuation in GDP would be optimal.  But I don’t believe you can say anything about policy efficiency unless you first embed those RBC insights (on things like productivity shocks) into a sticky wage/price model, and then compare policy alternatives with that model.  I view sticky prices as 90% a given, much like gravity.  (The other 10% is things like minimum wage laws, which can be impacted by policy.)

PS.  Just to be clear, I agree with Hendrickson on the more important issues in his post.  My support for University of Chicago-style perfect competition models definitely puts me on “team Hendrickson”, especially when I consider the direction the broader profession is moving.

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The Fed can create money

Here’s the Financial Times:

The Fed also has acknowledged it lacks the tools to solve all the problems in the economy, since it can only lend money, but not spend it to help businesses or households. And the Fed is acutely aware that its policies have done plenty to save financial markets from distress, but cannot deliver benefits as easily to low-income families and the unemployed.

That’s entirely false.  The Fed doesn’t just lend money; it can and does create money and also spend the new money on assets in order to boost NGDP and help businesses and households.  This policy delivers benefits to unemployed workers by reducing the unemployment rate.

The Fed is worried that the lack of a fiscal agreement will threaten the recovery and make its job harder. The US central bank does not want to be left alone in propping up the recovery.

Why?

This is good:

Some economists have suggested the Fed might tweak that to include a reference to an average 2 per cent inflation objective “over time” — reflecting its new policy framework.

Investors arguing for the new guidance to be rolled out this week say the Fed risks a loss of credibility if it does not act quickly to reinforce its monetary shift.

Today’s Fed meeting will be much more important than the typical meeting.  We will get some indication as to whether the Fed plans to obey the law—fulfill its mandate from Congress—or go sit in the corner and mope about the fact that fiscal policy is not all that it would prefer.

Bonus question: When the government lends money is that policy expansionary?  When the government borrows money is that policy expansionary?  Does the FT believe that the answer to both questions is yes?

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