Matt Nolan

Neat example of the J-curve

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Japan is offering a neat example of the J-curve (short term violation of the Marshal-Lerner condition), showing that the trade balance may deteroriate following a sudden depreciation in the currency – due largely to the fact the volume of exports and imports takes time to respond to price signals (they are sufficiently price inelastic in the short term).

Japan’s trade deficit swelled to a record 1.63 trillion yen ($17.4 billion) on energy imports and a weaker yen, highlighting one cost of Prime Minister Shinzo Abe’s policies that are driving down the currency.

The increase in fuel imports due to the movement away from nuclear energy following the Tsunami – and the drop in Chinese exports due to the Senkaku Island dispute, and implicit embargo – are factors that have helped to drive a deficit overall.  But these recent movements, following a sharp depreciation in the currency after changes in expected monetary policy (the new expectation Japan may actually allow inflation above 0%), provide a new example of the J-curve in action.  A nice teachable moment for people that way inclined!

jamesz

Carney on NGDPLT

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Mark Carney appeared at the Treasury Select Committee today for interrogation before being confirmed as the next Governor of the Bank of England. The big question everybody wanted answered is whether he favoured a move from inflation targeting to NGDP level targeting. The answer is ‘no’, but the reasons are interesting.

Carney is a known proponent of central bank commitment and the use of forward guidance. In recent speeches he has also spoken favourably of NGDPLT and that has prompted a storm of commentary in the UK; little of it was favourable towards the idea. Consequently, all eyes were on Carney’s evidence today. Reading the comments on Twitter suggests that he dismissed NGDPLT and retreated from his previous statements. I don’t think that is true at all.

In both his oral and written evidence he called flexible inflation targeting  “the most effective monetary policy framework implemented thus far.” However, he was at pains to point out that there are problems with it at the ZLB and there are other potential regimes, such as NGDPLT, that might help in those circumstances. In his oral evidence he spoke at length about the benefits of commitment and history dependence when encountering the ZLB. Despite that, he was not in favour of an immediate move away from inflation targeting, as you might expect given the outcome of the Bank of Canada’s review. Some of the reasons he gave are well-known: the problem of revisions and data quality, for instance. Notably, he did not think that NGDPLT would unhook inflation expectations and commented on the additional credibility a central bank could gain by implementing an inflexible rule.

The most interesting argument he made against level targeting was the one he dwelt on in his oral evidence: it relies upon people having rule-consistent expectations. That is to say, the success of a central bank relies on people expecting that it will implement its stated plans, and behaving as if they will come to fruition. Of course, he did not make the naive argument that people’s expectations are irrational. Rather, he pointed out that expectations among the populace have inertia and take time to change. If a large portion of the population have persistently incorrect expectations following a change in target then it would be costly in terms of welfare. He alluded to agent-based modelling done by the Bank of Canada to claim that these transitional costs as expectations gradually adjust could outweigh the gains to the switch.

In summary, he thinks NGDPLT is a great idea but hard to put into practice (data issues) and costly to implement (transitional costs of changing expectations.) Relative to the commentary in the UK press that is a ringing endorsement: one of the top central bankers in world says that the only real barrier is the details of implementation.

Matt Nolan

Menzie Chen on currency wars

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You know I don’t believe that the “currency war” is a negative thing in a world of insufficient demand (*,*,*,*,*).  But Menzie Chen from Econbrowser has the same view – and to be absolutely honest their view is significantly more reputable than mine 😉 .  Furthermore, it was a point that Chen made all the way back in 2010!

The post I have linked to is excellent, I would suggest reading it the whole way through.

The global economy is not a zero sum game.  The fact that we have significant “output gaps” (unused labour and capital) is the justification for trying to get private agents to “bring forward” consumption and investment now – which is what monetary easing in all its forms does.

In New Zealand, the hard question seems to be “how close are we to filling our output gap” – as if we are close (a popular, even mainstream, view in NZ, that I am not sold on) the current high dollar is indeed indicative of NZ inoculating itself from this global monetary easing.  This is a separate issue again from the “persistently high real exchange rate” that New Zealander’s are concerned about – this is an issue largely unrelated to monetary policy, where as a society we have to start being more honest about the trade-offs from different policy settings we have put in place.

Matt Nolan

Housing wealth and consumption – an upper bound, not an estimate

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Via Economist’s View, I saw this paper by Case, Quigley, and Shiller (REPEC).  Let me start with the positives, which are many:

  1. They are excellent writers,
  2. They get to the point – and have a clear idea of how important this sort of issue is for trying to understand cyclical phenomenon,
  3. They have pulled together a large data source consistently, which is a lot of work.

So as you can tell from that, I have a lot of respect for them, their work, and what they are doing.  However, I have a giant misgiving about the way they’ve framed the result they have found.  Fundamentally they HAVE NOT estimated the causal impact of housing wealth on retail sales/consumption.  In the introduction they do not make this claim hunting down an “association” … but by the conclusion this is what they are starting to claim they have done:

The importance of housing market wealth and financial wealth in affecting consumption is an empirical matter … we do find strong evidence that variations in housing market wealth have important effects upon consumption.

These descriptions are veering on causal, which is very inappropriate in a situation where you have an obvious, and likely significant, case of omitted variable bias!

Let us think about this.  Demand for housing is similar to demand for other durable goods – when confidence is high, unemployment is low, income expectations are elevated, and financial conditions are good, demand for both will rise, pushing up prices.  As a result there are some “third variables” that will drive up demand for both.  They cover this off at the end by stating:

Underlying our analysis is an assumption that it is useful to think of causality as running from wealth components to consumption, and not that, for example, the two are determined by some third variable, such as general confidence in the economy. We believe even more strongly that these new results demonstrate that it is useful to think of consumption as determined in accordance with the models we have presented. In consulting this evidence, recall that our measure of housing wealth excludes wealth changes due to changes in the size or quality of homes, changes that are likely to be correlated with consumption changes merely because housing services are a component of consumption. We have alluded elsewhere to others’ evidence using data on individuals that the reaction of consumption to stock market increases is stronger for stockholders than for non-stockholders (Mankiw and Zeldes, 1991), and that the reaction of consumption to housing price increases is stronger for homeowners than for renters. This lends additional credibility to our structural models when compared to a model that postulates that general confidence determines both consumption and asset prices.

To think about this point let’s think about housing.  Housing is a durable consumer good.  As the price of housing goes up relative to other goods and services, then given other goods and services constitute a “normal good”, spending on other goods and services should fall!  Of course, it also constitutes a transfer of wealth from homeowners to renters – and as a result, we have to ask about these separate markets in order to figure out what is going on.

As a result, the point that homeowners and renters behave differently is VERY useful, and justifies the study.  However, it in no way supports ignoring omitted variables and just deciding that the model is causal – in fact the way they have dismissed OVB is far too casual, given that there was no effort to deal with it (FE estimators deal with unobserved heterogeneity that is constant through time – this is not the case with our OV’s).

The evidence here appears to point at the fact that changes in house prices are a good proxy for changes in access to credit – hardly surprising given that housing is an asset and a durable consumer good.  When trying to understand the tendency of movements in retail spending, and the set of risks going forward for such spending, using house prices as a proxy for a set of “real structural” variables is useful.  However, this evidence is far from suggesting a causal relationship – and even further from suggesting that there is anything policy relevant here (as we need to understand the structure of the relationship in order to understand how changing policy settings will change outcomes – a change in policy settings can change the fundamental relationship between variables, think Lucas Critique!).

When the authors began to discuss this as causal, they should have stated that this provides an “upper bound” on the impact of housing wealth on consumption – and that more detailed analysis would be required.  They could even have gone further and stated that “given the size of the link, it is more likely that there is a tendency for higher house prices to drive up consumption” – that would have been mildly contentious, but reasonable.  As it is, their comments that they are estimating the size of a causal link are misleading.

jamesz

With great power comes great responsibility

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Romer and Romer think monetary policy could do more if only central bankers believed in themselves. Scott Sumner might agree these days.

Our thesis in this paper is that overly pessimistic views about the power of monetary policy have been a more important source of these errors than have overly optimistic views. There is little doubt that an overinflated belief in the power of monetary policy has contributed to some major policy errors. Most famously, policymakers in the mid-1960s believed that they faced an exploitable long-run inflation-unemployment tradeoff, and thus that monetary policy could move the economy to a sustained path of low unemployment and low inflation. This belief led them to pursue highly expansionary policy, starting the economy down the path to the inflation of the 1970s. The record of such errors has led many to argue that perhaps the most important attribute of a successful central banker is humility.

In this paper, we present evidence that the opposite belief—an unduly pessimistic view of what monetary policy can accomplish—has been a more important source of policy errors and poor outcomes over the history of the Federal Reserve. At various times in the 1930s, faced with the Great Depression, Federal Reserve officials believed that the power of monetary policy to combat the downturn or stimulate recovery was minimal. In both the midand late 1970s, faced with high inflation, policymakers believed that monetary policy could not reduce inflation at any reasonable cost. And there is evidence that in the past few years, faced with high unemployment and a weak recovery, monetary policymakers believed that policy was relatively weak and potentially costly. In each episode, the belief that monetary policy was ineffective led to a marked passivity in policymaking.

Matt Yglesias comments.

Matt Nolan

Why revisions matter

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Via James I saw this excellent post by Lars Christensen on why data revisions don’t matter for NGDP targeting.  I think it shows how much traction that the NGDP people are getting, when critiques like this start to appear – and it is good they are making a concerted effort to answer them.

Now I’m not actually someone who thinks that NGDP targeting isn’t what should be done (at this point, I’m still in agreement with the 2011 version of myself) – I don’t think it is terribly far off, and it provides a rule which is the main thing, so if it was to become core policy I wouldn’t be terribly concerned.

Now data revisions.  I think Christensen overstates how little they matter – even more than those who criticise NGDP targeting overstate how important it is.  In truth, the revisions issue is an important one because we are LEVEL targeting, and LEVEL targeting makes policy history dependent.  There are three real differences between flexible inflation targeting and NGDP targeting for a large economy, one of which is that point that NGDP targeting is level targeting and inflation targeting is growth rate targeting (for a small open economy, changes in tradeable good prices cause further issues – and I think NGDP doesn’t do this appropriately) … note, one other is the fact that NGDP targeting allows less discretion around the rule and an easier way to “judge” policy, something every economist outside of a central bank sees as a good thing 😉 … note the third is that one is anchoring expectations of price growth unrelated to the market place, one is ahchoring expectations of the level of nominal income unrelated to the market place – here we can ask “which one is more important for business and household decisions”.

So through the arguments:

We target a forecast in both cases, but forecasts are poor for both NGDP and inflation

This is true.  However, just before Christmas I was reading a paper about how inflation is the variable economic models have some of the most success at forecasting – as compared to GDP forecasts which are significantly worse.  I was going to write on this, and probably will at some point.  But in the interim, here is the RBA 😀

We should be targeting off a market, as that provides expectations

This is just the forecast story again – and we can do that with inflation targeting as well.

The potential problem

“Furthermore, arguing that NGDP data can be revised might point to a potential (!) problem with NGDP, but at the same time if one argues that national account data in general is unreliable then it is also a problem for an inflation targeting central bank. The reason is that most inflation targeting central banks historical have use a so-called Taylor rule (or something similar) to guide monetary policy – to see whether interest rates should be increased or lowered.”

Indeed this is a problem for inflation targeting as well.  But lets think a bit.

CPI, business surveys, and the unemployment rate are virtually never revised (apart from methodology changes), NGDP is revised constantly.  Central banks target a certain measure of core CPI and they use a Taylor rule which relies on deviations from potential output.  What they estimate is the OUTPUT GAP not potential itself.  Oft times, this estimate of potential will use data from business surveys and the unemployment rate as well as the oft revised GDP numbers – and as a result the size of any revisions and any potential error are a lot smaller.

Inflation is dubious

All data is dubious – CPI has had more time spent on it for the fact it is used for policy setting.  If we are worried about whether CPI is systematically biased (which is level terms it likely is, but in growth terms it is not) then the issue is far far worse for the GDP stats!

Conclusion

“However, the important point is that present and historical data is not important, but rather the expectation of the future NGDP, which an NGDP futures market (or a bookmaker for that matter) could provide a good forecast of (including possible data revisions). Contrary to this inflation targeting central banks also face challenges of data revisions and particularly a challenge to separate demand shocks from supply shocks and estimating potential GDP.”

It is exactly right that the point is to set expectations – central bankers know that.  With expectations of inflation anchored, they can then just walk around changing their policy stance to respond to the evolution of demand in the economy – this is what central bank policy should do, aims to do (ignoring the ECB of course 😉 ), and what the NGDP targeters want!  In this way data revisions are pretty irrelevant in so far as both sides are asking each other to do the same thing.

But there is the kicker, the flexible inflation targeters are targeting GROWTH in demand and anchoring expectations of PRICE growth.  NGDP targeters are targeting the LEVEL of demand and anchoring expectations of NOMINAL INCOME.  As soon as we target a level instead of a growth rate we make history relevant – this very history that is filled with data revisions and changes.  As a result, this is definitely a more important issue for NGDP targeting than for flexible inflation or NGDP growth targeting – which is why it is being raised!

It is a cost of level targeting, those in favour of level targeting have to point out the counterveiling benefits of said targeting (outside of a liquidity trap, where the gains are widely accepted but can be done through commitments rather than a change in the rule) that will swamp this and other costs.