Conference – Free Banking systems: diversity in financial and economic growth

Lund University (in Skåne, Sweden) is less than one hour drive from my home in Copenhagen so I very much hope I will be able to participate in the upcoming conference on  “Free Banking systems: diversity in financial and economic growth” at Lund University School of Economics and Management on September 4 – 5 2014. Furthermore, the conference will hopefully lure monetary scholars to Copenhagen as well. I will certainly see whether we could arrange some informal get-together in Copenhagen in connection with the conference.

The conference looks very promising.

I have stolen this from Kurt Schuler at Freebanking.org:

Call for papers:
Conference: Free Banking systems: diversity in financial and economic growth
Lund University School of Economics and Management, September 4 – 5, 2014

Department of Economic History, Lund University, Sweden
For more info on the venue please see: http://www.ekh.lu.se/en

Travelling: Most conveniently to Copenhagen Airport (Kastrup)
There are frequent trains from Copenhagen Airport (Kastrup) to the city of Lund. Travelling time is approximately 35 minutes and the cost for a single journey is around 12 Euros. For more info on travelling please see: http://www.lunduniversity.lu.se/o.o.i.s/24936

Paper proposal deadline: April 30, 2014
We invite all scholars interested in participating to submit an abstract of approximately 400 words and a short bio to the main organizer Anders Ögren on e-mail: anders.ogren@ekh.lu.se

Notification of acceptance: May 30, 2014

Paper deadline: August 15, 2014
Note that as this is a pre-conference to the session S10133 at the WEHC in Kyoto August 3 – 7, 2015 papers can be preliminary at this point in time.

Conference rationale

In 1992 Kevin Dowd edited the important book “The Experience of Free Banking” gathering several historical episodes of Free Banking in a “historical laboratory”. This collective volume aimed at evaluating Free Banking as a way of achieving both banking stability as well as monetary stability. It was found that the problems usually attached to Free Banking, such as rapid inflation and banking instability, in fact were not at all the consequence of Free Banking, underlining instead that these results questioned the idea that the Central Bank’s monopoly on currency issuance is a natural monopoly. In a way this book was a continuation of the theoretical development on Free Banking made in influential works such as Smith’s “The Rationale of Central Banking” (1936), Hayek’s “Denationalization of Money” (1978), White’s “Free banking in Britain” (1984) and Selgin’s “The Theory of Free Banking” (1988) (to name a few).

As a result of the recent crisis Free banking as a way of achieving both banking stability as well as monetary stability is back on the agenda for scholarly debates. Again there are those who argue that Free Banking systems are more prone to banking instability and banking failures with less positive impact on growth than banking systems operating under a state sponsored Central Bank. But to the contrary there are those that argue that banking and monetary instability and slumps in growth due to crises are results of the increased importance of central banks.

Supporters and skeptics of Free Banking alike are using historical episodes as laboratories for empirical testing of their ideas. But to what extent are the features of the alleged Free Banking episodes comparable, not only between different historical episodes but also in relation to theory or in relation to Central Bank based banking systems. Historically many varieties of banking exists between what would be the theoretically pure Free banking system and a Central bank based system. All these varieties provides essential information about how a banking system works and why it obtains certain results in terms of banking and monetary stability and in extension in growth. Thus comparing the diversity of the development of Free Banking systems allows us to understand their different impact on economic growth.

Thus the idea with this conference is to continue the work to make historical cross country comparisons on Free Banking episodes and theories – aiming at understanding what features that are required for different stages of free or central banking and to disentangle the impact of these different variables on banking and monetary stability. We welcome scholars working on empirical cases of what is suggested to be Free Banking – whether their results seem to support Free Banking or Central Banking or a hybrid between the two.

This conference is an open pre-conference to the session S10133 at the WEHC in Kyoto August 3 – 7, 2015. Due to time constraints participation in this conference does not necessarily imply participation at this session at the WEHC conference.

Organizers:

Anders Ögren
Lund University
E-mail: anders.ogren@ekh.lu.se

Andres Alvarez
Universidad de los Andes

 

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Conventional Thinking at the Brink (by Clark Johnson)

From the day I started my blog I have always been happy to invite other economists to contribute to my blog with guest posts.

Today I can present something even better than a guest post. Today I can present a new paper by Clark Johnson – “Conventional Thinking at the Brink: Comments on Ben Bernanke’s The Federal Reserve and the Financial Crisis (2013)”. Clark in his great paper comments on Ben Bernanke’s book “The Federal Reserve and the Financial Crisis”. 

While I obviously do not agree with all of Clark’s points the paper is as usual very informative and insightful. Clark remains an extremely knowledgeable scholar with a deep insight into particularly monetary history.

Enjoy! You can read Clark’s paper here.

Lars Christensen

PS I have earlier published Clark Johnson’s paper “Keynes: Evidence for Monetary Policy Ineffectiveness?”

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The Cuban missile crisis never happened (or at least the stock markets didn’t care)

According to the history books one of the most scary events during the Cold War was the so-called Cuban missile crisis, where according to the history books the world was on the brink of nuclear armageddon.

However, the history books might be wrong – at least if you look at what happened to the US stock market during the crisis. If we indeed were on the brink of the third world war we would certainly have expected the US stock market to drop like a stone.

What really happened, however, was that S&P500 didn’t drop – it flatlined during the 13 days in October 1962 the stand-off between the US and the Soviet Union lasted. That to me is pretty remarkable given what could have happened.

There might be a number of reasons why we didn’t see a stock market collapse during the stand-off. Some have argued that the crisis was an example of what has been called Mutual Assured Destruction (MAD). Both the US and Soviet Union knew that there would be no winners in a nuclear conflict and therefore neither of them had an incentive to actually start a nuclear war. It might be that investors realised this and while the global media was reporting on the risk of the outbreak of the third World War they were not panicking (contrary to popular belief stock markets are a lot less prone to panic than policy makers).

Another possibility is of course that the markets knew better than the Kennedy administration about the geopolitical risks prior to the crisis. Hence, the stock market had already fallen more than 20% in the months prior to the Kennedy administration’s announcement that the Soviet Union was putting up nuclear missiles in Cuba.

And the market was of course right – there was not third World War and after 13 days of tense stand-off the crisis ended.

That said, the Cuban missile crisis did not go unnoticed by consumers and investors. However, we should think about such geopolitical shocks as primarily supply shocks. A geopolitical crisis increases “regime uncertainty” – in an AS/AD framework this shifts the AS curve to the left, which reduces real GDP growth and increases inflation for a give monetary policy stance. This was actually not very visible in 1962-63, but later in the 1960s it became very clear that regime uncertainty was reducing real GDP growth.

In terms of stock market valuation it is important that we remember that equity prices are nominal rather than real and therefore it is not necessarily given that stock prices should drop if the central bank keeps nominal spending/aggregate demand on track. Obviously stocks could drop if the risk premium on stocks increases, but we should not necessarily expect nominal earnings growth to drop.

Therefore, we need to think about the monetary policy response to a geopolitical crisis to understand how it is impacting the stock market performance. This of course is highly relevant for what is going on right now in regard to the Ukrainian-Russian conflict.

The horrors of Russian and Ukrainian central banking

The recent sharp rise in geopolitical tensions is a significant negative supply shock to both the Russian and the Ukrainian economy – visible in the sharp weakening of both countries’ currencies. However, unlike in the case of the US stock market in October 1962 the Russian and Ukrainian stock markets have sold off dramatically.

Given the amount of regime uncertainty it is not surprising that investors have become a lot less happy to hold Russian and Ukrainian stocks. However, central bankers in the two countries are not making life easier for anybody either. Hence, the Russian central bank (CBR) has reacted to the sharp sell-off in the Russian ruble by intervening heavily in the currency markets and thereby tightening monetary conditions and the CBR has also increased its key policy rate by 150bp to prop up the ruble and more rate hikes might be in the pipeline. And this week the Ukrainian central bank followed the (bad) example from the CBR and hiked its key policy by 300bp.

So what both of the central banks are doing now is to tighten monetary conditions in response to negative supply shock. Obvious page 1 in the central banker’s textbook tells you not to respond to supply shocks in this way. Unfortunately most central bankers never read the textbook and hence are happy to make things worse by “adding” a negative demand shock to the negative supply shock.

And this of course is going to be negative for stock markets. Monetary tightening causes nominal spending to drop and hence causes a contraction in nominal earnings growth and that of course is bad news for stocks.

Paradoxically we can also on the other hand imagine a situation where a geopolitical crisis can be good news for stocks (measured in local currency). Imagine that central bankers freak out about the possible negative growth consequences of a geopolitical shock and respond to this by easing monetary policy. Actual that might be what is happening in the euro zone at the moment (on a small scale). Or at least judging from comments from ECB-chief Mario Draghi the ECB thinks that the Ukrainian crisis potentially could have significant negative ramifications for European growth and it seems like the ECB has become somewhat more dovish after the Ukrainian crisis began. The Polish central bank has similarly become more dovish in its rhetoric since the outbreak of the crisis.

Central banks should not react to negative (or positive) supply shocks, but if they do ease monetary policy in response to a negative supply shock then it will increase nominal GDP growth (but not necessarily real GDP growth). That is positive for stocks (whether or not real GDP growth increases). I am not arguing that that is what is happening now, but I am using this as an example to illustrate that we should not necessarily assume that geopolitical shocks automatically will lead to lower stock prices. It all comes down to the monetary policy response.

The story of the 1960s: The stock market is a nominal phenomenon

Returning to the Cuban missile crisis it is helpful to have a look a the development in nominal GDP to understand what was going on in the US stock market during the Cuban missile crisis and in the aftermath.

In 1961 US NGDP growth had been accelerating significantly – with NGDP growth going from only 0.5% y/y in Q1 1961 to 9% y/y in Q1 of 1962. That reflects a rather massive monetary expansion. However, from early 1962 a monetary contraction took place and NGDP growth started to slow significantly. This I believe was the real reason for what at the time became to be known as the Kennedy Slide in the stock market. This was prior to the Cuban missile crisis.

However, as the geopolitical crisis hit the Federal Reserve moved to ease monetary policy – initially not dramatically but nonetheless the Fed moved in a more accommodative direction and NGDP growth started to accelerate towards the end of 1962 – a few months after the end of the Cuban missile crisis. I am certain this helped keep a floor under US stock prices in the later part of 1962.

In fact it is notable to what extent geopolitics came to determine monetary policy during the 1960s and we might of course equally argue that geopolitical concerns to some extent were a driving force behind president Kennedy and particularly president Johnson’s expansion of the welfare state measures in the US in the 1960s. The Federal Reserve during the 1960s actively supported the expansion of government spending by trying to intervene in the US bond market to keep bond yields down for example through the (in)famous operation twist. The Fed’s policies became increasingly inflationary during the 1960s.

During the early period of the 1960s the easing of monetary conditions primarily boosted real GDP growth (in line with the acceleration in NGDP growth), but as the negative impact of war spending and spending on social welfare schemes started to be felt US productivity growth started to slow significantly and as a result the continued expansion of nominal spending led to a significant increase in US inflation in the second half of the 1960s.

In regard to the US stock market it notable to what extent the development in the stock market follows in the development in nominal GDP. In fact from 1960 to 1970 US stock prices rose 80-90% – more or less in line with the development in NGDP. This is illustrated in the graph below:NGDP SP500 1960s

This illustrates that higher geopolitical risks are not necessarily negative for stocks, but it might make central banks make stupid decisions. That is certainly the case of the Fed during the 1960s. Whether that is any guide for what will happen to global monetary policy today if we continue to see an escalation of geopolitical tensions is certainly not easy to say.

Currency union and asymmetrical supply shocks – the case of Finland

This morning I am flying to Finland to speak about the outlook the Polish economy at a seminar in Helsinki. That is the inspiration for what I will talk about in this post – or rather I will tell the story of how an asymmetrical negative supply shock – combined with euro membership – has sent the Finnish economy into recession. It is (partly) a story of the demise of Finland’s best known company Nokia.

A cornerstone in Optimal Currency Area theory is that two countries should only join in a currency union if the shocks that hit the economies tend to be symmetrical. Hence, economic shocks should tend to hit both economies at the same time and by more or less the same magnitude.

A shock the oil price is a good example of a symmetrical supply shock to the euro zone countries as all the euro area countries tend to be oil importers. However, in recent years the Finnish economy has been hit by an asymmetrical supply shock – a shock which have not hit the other euro area countries.

Nokia’s lagging competitiveness as a negative supply shock

Do you remember this cell phone?

Nokia_3310_blue

Nokia  used to be the Apple of the day. Today everybody have iPhones, but back in the 1990s and the early 2000s everybody had a Nokia cell phone. I still sometimes miss my old reliable Nokia cell phone – I have had a few.

However, within the past 10 years things have changed. Nokia no longer command the technological superiority that it once used to have – even I who certainly is no expert on the Telecoms sector realises this.

There is really nothing unusual about Nokia’s story in the since that companies come and go. However, what is unusual is just how important Nokia became in 1990s for the Finnish economy. I personally remember when Nokia 10-15 years ago was close to 90% of the overall market cap for the Finnish stock market. The Finnish economy was Nokia.

However, over the past 10 years things have changed for Nokia. The company has been loosing in the technological race between the global telecoms companies. In economic terms this is a negative shock to what economists like to call Total-Factor-Productivity (TFP).

I like to think of TFP as a measure of how well we are at putting together the production factors we have – labour, capital and raw materials. Obviously Nokia makes more technological advanced phones today than 15 years ago, but Nokia’s global competitors have just developed even faster.

I most stress that I am generalising wildly here – after all I am not expert on the telecoms industry or on Nokia and the purpose is not to talk about Nokia as company, but the macroeconomic impact of the negative TFP shock to Nokia. Hence, a negative TFP shock for Nokia is a negative TFP shock for the entire Finnish economy.

As usual the AS/AD framework is useful

We can think of the negative TFP shock to the Finnish economy as a negative and permanent supply shock to the Finnish economy. Within the AS/AD framework this shifts the long-run aggregate supply (LRAS) curve to the left as illustrated in the graph below.

LRAS shock

A negative LRAS shock, which shifts the LRAS curve to the left, reduces longterm real GDP growth to y’ from y and increase inflation from p to p’.

Or this would be the story if we were in an nominal GDP targeting regime where the central bank essentially ensures a stable growth rate of aggregate demand – the AD curve is fixed. However, this is not the story for the Finnish economy.

A negative TFP shock becomes a negative demand shock

Finland is a member of the euro area and this have clear implications for how the negative shock to Finnish TFP has been playing out.

In a situation where Finland had not been in the euro area and the central bank had been targeting NGDP a negative TFP shock would have caused the Finnish currency – in the old days the Markka – to depreciate. That would have kept aggregate demand growth “on track”, but it would still have lower real GDP growth in the longer run as the shock to TFP is assumed to be permanent.

Hence, the Finnish economy would have gone through an adjustment to the lower productivity growth oath through a depreciation of the currency. This option is not possible for Finland today as a member of the euro area.

To understand the transmission mechanism of the shock through the Finnish economy it is useful to think of the initial level of inflation, p, as also being the level of inflation in the euro area overall.

A negative shock to Finnish productivity increases inflation to p’ – hence above euro zone inflation (p). Hence, this is essentially a negative competitiveness shock.

The shock to Finland’s competitiveness has been very visible in Finland current account situation over the past decade Finland’s current account surplus has collapsed.

This is a very interesting difference between Finland and other crisis hit euro zone economies. In the case of the so-called PIIGS countries we have seen a sharp improvement in the overall current account situation in countries like Ireland and Spain. This is mostly due to a collapse in aggregate demand (NGDP) since crisis hit in 2008, but also due to improved competitiveness due to lower inflation and lower wage growth.

In some ways one can say that Finland’s economic troubles are worse than that of the PIIGS in the sense that one could expect growth to pick swiftly in the PIIGS continues if just the ECB eased monetary policy (I will believe it when I see it…), while monetary easing would do nothing to improve the competitiveness of the Finnish economy. Said in another way – Mario Draghi can increase aggregate demand in Ireland or Spain, but he cannot invent the cell phone of the future.

Therefore, for Finland there is indeed a “New Normal” – real GDP growth looks set to be permanently lower than it was in the 1990s and 2000s. And that will be the case no matter what monetary regime Finland has.

That is not to say the monetary policy regime is not important for Finland. In fact euro membership is likely to be a drag on growth as well at the moment. To understand this we return to the AS/AD framework.

Finland cannot not permanently have higher inflation (and unit labour costs) than the other euro zone members. Hence, in the AS/AD framework we need to see inflation drop back to p (the euro zone inflation) from p’.

This happens “automatically” in a currency union through what David Hume termed the specie-flow mechanism. As the current account situation has worsened Finland have seen an increasing currency outflow.

In a currency union or any other fixed exchange rate regime such currency outflows automatically lead to a similar decline in the money base, which lower nominal spending/aggregate demand in the economy – this is pushing the AD curve to the left. This monetary contraction will basically continue until competitiveness is re-established and inflation is back at the euro zone level (p). This is what is illustrated in the graph below.

LRAS shock monetary tigthening 2

This process would be smooth if prices and wages were fully flexible. However, that is obviously not the case (in the short-run the AS curve is not vertical, but rather upward sloping) – particularly not in Finland. In fact particularly wage growth seems to have shown considerably downward rigidity in Finland in recent years. As a result unemployment has increased.

While there is not much to do about the long-term productivity problem monetary policy can help ease the pain when shifting to a lower level of productivity growth. Hence, had Finland – like for example Sweden – operated a floating exchange rate regime – then the needed adjustment in competitiveness could have happened via a weakening of the currency rather than through lower wage and prices.

This would not have “solved” the productivity problem, but at least the unemployment problem would have been significantly smaller – at least in the short to medium term.

However, as a member of the euro zone Finland does not have that option (other than of course leaving the euro). Furthermore, while weak demand growth is a problem for the wider euro zone and hence one can argue that the ECB should do something about that (and hence help the PIIGS) it is harder to argue that the ECB should act to ease the pain from an asymmetrical shock, which have only hit Finland.

We didn’t think of that…
When the euro was set-up it was the general assumption that asymmetrical supply shocks were rare and economically not important. However, the economic development in Finland over the past decade shows that asymmetrical supply shocks indeed can be very important economically.

As I am landing in Finland I am reminded that another asymmetrical shock has just hit the Finnish economy – Finland’s most important trading partner is Russia. The Russian economy is heading for recession – that is hardly something that will help the Finnish economy…

PS I should once again stress that this is a post about asymmetrical shocks in a currency union rather than about Nokia. Furthermore, there is a lot more to the Finnish story rather than just Nokia (for example the server problems in the paper and pulp industry).

10 fallacies of the Great Recession

I am getting a new (work) computer so I have been doing a bit of clean up on my old computer. While doing the clean-up I came across the following list that I apperantly did at some point.

This is 10 fallacies of the Great Recession:

1)      Low interest rates = easy monetary policy

2)      The price of money is the interest rate (credit and money is the same thing)

3)      Confusing shifts in demand and supply curves: No, lower oil prices is not helping the US economy if it is caused by a drop in global AD

4)      Competitive devaluations won’t help if everybody devalue at the same time

5)      We are in a “New Normal” – the hangover the theory of the Great Recession. We are in a balance sheet recession

6)      We are out of ammunition – interest rates are near zero so we can ease not monetary policy anymore (we need fiscal easing)

7)      The Great Recession was caused by a property market bubble

8)      Fiscal policy is a useful tool to combat the crisis

9)      Central banks are printing money like hell – we will get hyperinflation (confusing demand and supply for money)

10)   Higher inflation is bad for private consumption

Šimon Biľo on Hayek’s Business Cycle Theory

There is a new Working Paper out on Hayek’s version of the Austrian Business Cycle Theory. While I long ago has given up on ABCT I still think there are insights from ABCT that we should understand and which makes of better able to understand the world we live in.

This is the abstract from Šimon Biľo’s new paper “Hayek’s Theory of Business Cycles: Theory That Will Remain Obscure”

Hayek’s theory of business cycles has been criticized for its unfeasible policy prescriptions, weak empirical support, and lack of technical rigor. Although the theory can be defended against these criticisms, it violates the rational expectations hypothesis, a criterion by which economists tend to judge the quality of economic arguments. Since Hayek and his followers failed to remedy or justify the violation, the theory cannot capture the interest of the economics profession today. To change this outcome, Hayek’s theory either needs a satisfactory restatement, or it has to wait until economists change the criteria for judging the quality of arguments.

While I did not read the paper yet I certainly agree with the main points in the abstract. So I better read the rest of the paper soon – and so should you.

HT Will Luther

A framework for applied macroeconomic forecasting (part 2)

In my previous blog post I outlined a four-equation model to be used for real-world macroeconomic forecasting. In today’s post I will look a bit closer at one of these equations – or rather I will discuss how we can think about forecasting the supply side of the economy.

So we basically want to understand how and why the (short-run) aggregate supply (AS) curve shifts in our AS/AD framework. I will discuss the different kinds of supply shocks we can think of and then I will discuss how we can use financial market data to forecast the impact of such shocks on aggregate supply.

But first let us think about how most real-world macroeconomic forecasters think about supply shocks. The theoretical economist might be surprised to learn that there basically is no supply side in the “mental models” most forecasters are using.

Rather most real-world forecasters think of supply shocks as a kind of demand shock. Lets for example think of an increase in the price of oil. In an AS/AD framework an oil price hike would shift the AS curve (for an oil importing country) to the left causing real GDP growth to drop and inflation to increase. This is basically a story of higher production costs leading companies to reduce output.Supply shock

However, in the thinking of real-world forecasters an oil price hike is something which increase inflation and as a direct consequence causes real disposable incomes to drop. As real disposable income drops so does private consumption growth and given that most of these real-world forecasters are doing what I have termed national accounting economics a drop in private consumption automatically leads real GDP to drop (remember Y=C+I+G+X-M).

In reality most real-world forecasters therefore assume two things. 1) Prices are not only sticky, but fixed and 2) the monetary policy regime is a fixed exchange rate regime meaning there will be no monetary offset to what effectively is an velocity-shock. Therefore “translating” what real-world forecasters are doing into a AS/AD framework when thinking about oil prices is to think of an oil price increase as a drop in aggregate demand and at the same time assume that the AS is flat. Hence, in the real-world forecaster’s model an oil price increase shifts the AD curve to the left as illustrated below.

ASAD flat AS

We see that this causes real GDP growth to drop, while leaving inflation unchanged (due to the flat AS curve). The real-world forecaster obviously doesn’t think an oil price hike will not cause inflation to increase. However, she will model that in a separate (mostly) unrelated model.

In fact as a general rule the real-world forecaster will think of the determination of real GDP as 100% demand side driven and at the same time think of inflation as 100% supply side driven. In that sense I don’t think I am wrong when claiming that to most real-world forecasters inflation is never a monetary phenomena, but rather completely driven by supply side/cost factors.

Hence, she will probably use inflation models that mostly rely on developments in wages, oil prices, food prices and exchange rates, while probably also assuming some “mean-reversion” in the sense that over 2 or 3 years inflation will converge towards a given inflation target.

This kind of faulty thinking is also what leads some economists to believe that an earthquake or war is great for the economy. What they see is the effect on aggregate demand, while completely ignoring the supply side part of the story.

What I here will argue is that we should stop thinking about supply shocks as quasi-demand shocks. A supply shock is not the AD curve moving along the AS curve, but rather the AS curve shifting left or right and moving along the AD curve.

Different types of AS shocks

To be able to practically do forecasting of the impact of supply shocks we need first to think of what kind of supply shocks we have. To do this I think this rudimentary production function is useful:

(1) Y= A*f(K, L, O)

Here Y is the level of real GDP, while K, L and O are capital, labour and raw materials (such as oil). A is what we call the Total Factor Productivity (TFP) – or said in another way how clever we are at using the three productions factors in production.

Hence, we can basically think of shifts in the AS curve as shocks to one or more of these four variables (A, K, L or O). These shocks can be permanent of temporary.

Getting practical with supply shocks

Doing real-world macroeconomic forecasting often is about dealing with practical matters rather than with theoretical issues (that is why most real-world forecasters over time turn into pretty bad theoretical economists). What I am trying achieve here is how we can maintain a sober theoretical approach to forecasting while at the same time keeping things practical.

Furthermore, it should be noted that a lot of “forecasting” is not really forecasting in the sense of forecasting the future. Rather it is about “forecasting” how for example quarterly GDP data for the present quarter will come in when they are published at a later stage. So what we really are looking for are real-time indicators. Here I believe the financial markets are extremely useful.

Furthermore, financial markets are also giving us insight into the future impact on real GDP growth and inflation of shocks.

But lets get practical and that also means that I here only will focus on two of the four different types shocks outlined above – capital shocks and raw material shocks. I focus on these two primarily because I think those are the most important and common supply shocks that we empirically are facing.

Cost of capital shocks

Often real-world forecasters think of the cost of capital (the “interest rate”) as something which is determined by monetary policy and something, which is impacting private consumption and investments and hence “aggregate demand” (in the most vulgar Keynesian form).

However, this is not what I think of here. Rather to me the cost of capital is something that determines investments and hence the capital stock in the economy. That is a supply factor.

Let me illustrate what is going on in Russia at the moment. We are seeing massive capital outflows from Russia. The real-world forecaster probably sees this as a negative shock to demand. However, that in my view is not what it is. (The capital outflows, however, can have an indirect impact on aggregate demand if it causes the central bank to tighten monetary policy).

Rather what we are seeing is a drop in the supply of capital available in the Russian economy. Capital is simply becoming less easily available and hence more expensive.

The case of Russia today also provides us with a clue to what kind of financial market indicators we can use to identify shocks to the cost of capital.

I would particularly focus on three different measures of the cost of capital.

First, what is the stock market telling us? If the Russian stock market drops relative to earnings or relative to stock markets in the rest of the world then that is telling us the cost of capital is increasing in Russia.

Second, we can also look at the price of ensuring against a Russian government default – a so-called Credit Default Swap. This is also an indirect measure of the cost of capital in Russia.

Third and finally we can also look at the bond yield spread for Russian bonds – either government or corporate bonds – versus similar bond yields in the US or the eurozone.

Again in practical terms I think it would be useful to create an index of these different measures of the cost of capital to get a single “number” for the shocks to the cost of capital in a given country. I will try to do that in a later post when I try to estimate (or simulate) an AS curve for one or more countries.

Raw material costs – it is mostly about oil prices

Shocks to oil prices seem to be the most common shock to aggregate supply across countries in the world. Furthermore, the correlation between oil prices and other commodity prices historically has been fairly high so in my view for the practically oriented macroeconomic forecaster the most easy way to capture shocks to raw material costs is simply to look at the price of oil in local currency.

Hence, in reality there will be a quite high correlation between the oil price and most other commodity prices. Therefore, for practical purposes using the oil price measured in local currency will be entirely enough to capture most of the raw material shocks to most economies.

Putting it all together

In my previous post I outlined a simple AS curve, which I think would make both economic and econometric sense for most economies in the world.

(1) y = a0 + a1*n + SS

Where y is real GDP growth (%q/q), n is nominal GDP growth and SS is a supply shock. a0 and a1 are coefficients.

Given the discussion above we can now identify SS by thinking of SS as either cost of capital shocks or shocks to the oil price. There are certainly other supply shocks out there, but for practical purposes I think that these two supply side factors “capture” the large majority of of supply side shocks in most real-world economies.

This gives us an expanded AS curve:

(1)’ y = a0 + a1*n + a2*CoC + a3*OP + a4*Ygap(t-1)

Where CoC is an index for the cost of capital and OP is the oil price in local currency (de-trended). Note that I here also have included the output gap (Ygap) lagged one quarter to take into account the equilibrating process towards “full employment” in the economy. a2, a3 and a4 are coefficients.

Next step – lets try to estimate the model

I will try to do that in my next blog post, but my readers are obviously very welcome to do the econometrics on their own on whatever country they want.

PS I use the term “real-world macroeconomic forecasters” above as a generalisation. Some might argue that this is far too much of a generalisation and that the world of forecasting has changed. That might be it and I know a lot of central bankers are terribly proud of their DSGE models, but if they look themselves in the mirror they will soon acknowledge the fact most arguments made by central bank officials are not based on DSGE thinking, but rather on national accounting economics.

 

 

 

 

 

A framework for applied macroeconomic forecasting (part 1)

Most economists who have worked as macro economists for governments, central bank or commercial banks will sooner or later be engaged in doing macroeconomic forecasting.

Oddly enough most economists are not really educated to do forecasting. What we learn in university is mostly theoretical. We learn about different economic schools and models (Keynesian, New Keynesian, RBC, monetarist etc). And maybe we learn about econometric methods to estimate different “models”, but that is very far from the daily realities of real-world macroeconomics forecasters.

The fact is that the challenges that real-world macroeconomic forecasters are facing are of a completely different type than the theoretical models that we learn in university.

Just think about the present discussion about how the weather has influenced US macroeconomic data recently. Or think about the discussion that we constantly have about the quality of Chinese macroeconomic data – can we really trust the data produced by a communist government or any government? Think about the problems of seasonal adjustments. Are seasonal patterns really constant over time? And we could go on about such technical issues. Something we never heard about in the university.

This are the kind of challenges those of us who do macroeconomic forecasting deal with on a daily basis. It is not very sexy, but it is a very large part of real-world macroeconomic forecasting.

I believe that these unsexy challenges actually are among the main reasons why so many macroeconomic forecasters become quite ignorant about theoretical issues and why they tend to practise a quite vulgar form of “Keynesianism” – or what I have earlier termed national accounting economics.

That basically means that most real-world forecasters start out with the familiar national account identity – Y=C+I+G+X-M. And then they simply make “sub-forecasts” for private consumption growth (C), investment growth (I), public expenditures (G), exports (X) and imports (M) and then add up all these elements to a forecast for real GDP growth (Y). This would often (always!) include some fiddling with the data so to ensure a nice “profile” for the forecast path for real GDP as most forecasters prefer that the real GDP growth returns to trend growth within 2 or 3 years.

What is notable about this form of forecasting is that it ignores a lot of factors. Most important in my view is that the monetary policy rule/regime is totally ignored. To the extent any monetary policy is thought about it is mostly considerations about the impact of interest rates on private consumption and investments. Second, supply shocks are mostly reduced to a quasi-demand side story in the sense that for example an increase in the oil price is something, which reduces real disposable incomes rather than something, which is increasing production costs. There is no direct relationship between the production and demand side of the economy and inflation and inflation forecasts are mostly made in other “parallel” models, that are not directly related to the rest of the modeling.

An alternative approach – applied AS/AD forecasting and modelling

I am no saint and I have also for years used a similar approach when I have been involved in macroeconomic forecasting – both working for government and in the financial sector. In many ways I have for years lived in a parallel universe or rather one universe where I was thinking in a certain way (as a Market Monetarist) and another universe where I was doing macroeconomic forecasting (national accounting style).

I had the same problem as everybody else – I had to overcome a lot of practical problems. That led me to continue to do forecasting in a way I fundamentally found unsatisfactory. I am still not fully satisfied with the way I do macroeconomic forecasting in my day-job, but I think I am a lot closer to getting it right now than before. It has been a nearly 20 years journey.

In this post – and more to come – I will try to sketch an alternative approach to do real-world macroeconomic forecasting. Not because I necessarily think it will produce more accurate forecasts (we can’t forecast shocks!), but because I think the approach I will outline here will make a lot more sense economically speaking.

My starting point is a simple AS/AD framework in the spirit of Cowen and Tabarrak. We start with a familiar graph.

ASAD

In the AS/AD framework we basically have only two macroeconomic variables – inflation (p) and real GDP (y). Of course from this we also get nominal GDP (n=p+y).

I think we from this can estimate fairly simple AS and AD curves that will be easy and simple to use in real-world macroeconomic forecasting and analysis.

A four-equation model

In later blog posts I will get into more details with my overall framework, but for now we will start out with a four-equation model.

We start with the AS curve. The important thing is to differentiate between when we “move along” the AS curve and when the AS curve shifts left or right.

It follows from economic theory that the (short-term) AS curve is upward sloping. This means that there is a positive correlation between on the one hand real GDP growth (y) and inflation (p) and therefore also nominal GDP growth. We can use this insight to write a simple equation for our AS curve:

(1) y = a0 + a1*n + SS

Where y is for example the quarterly real GDP growth rate, while n is nominal GDP growth. a0 and a1 are coefficients. SS is a shift variable that will capture exogenous supply shocks (shifts in the AS curve). In a slightly more advanced model we could also include the (real) output gap in model – so real GDP growth would be higher as long as the output gap is negative. That would mean that the output gap would gradually close even if nominal GDP (aggregate demand did not change). That would account for the long-run AS being vertical.

And variations of that equation are easy to estimate and my experience is that there is a very good fit to such models for most countries I have tried to apply this type of model to. The clever reader will realise that this is basically a simple form of a Phillips curve.

In a later post I will return to discuss the AS curve in more detail and I will particularly discuss how to use financial market information to forecast the impact of supply shocks on real GDP growth and to discuss different forms of supply shocks.

In the spirit of Cowen and Tabarrak our AD curve is basically the equation of exchange (in growth rates):

(2) n = m + v

Where n is nominal GDP growth, m is the money supply (for example M2) growth rate, while v is the growth rate of money-velocity.

We can think of different ways to model both m and v. That is our two next equations.

Equation (3) is an equation for the central bank’s policy rule. We assume that the central bank directly controls the money supply. This is of course not necessarily a realistic assumption and in an alternative formulation we could write (2) as n=k*b*v, where k is the money multiplier and b is the money base. However, for simplicity we will start with the simple version here.

We can obviously think of all kind of policy rules – inflation targeting, nominal GDP targeting or some kind of exchange rate targeting. This is the general form of our policy rule:

(3) m = f(TARGETS) + PS

m is the policy instrument, the money supply, while TARGETS is whatever policy target(s) we can think of and PS is discretionary changes in monetary policy (policy shocks).

Whether we want to estimate or “simulate” (3) will depend on whether or not there has been any changes (structural breaks) in the overall monetary policy regime or not.

Finally we have an equation for the development in money-velocity (v). This is basically a model for the development in money demand. There is a huge literature on this, but overall I think it is useful to apply a fairly eclectic approach to modelling v:

(4) v=f(V0, V1,…, VN) + VS

Where velocity is determined as a function of a number of variables – for example the yield curve or the exchange rate etc. VS is a velocity shock, which we should think of as unpredictable shocks to money-velocity – policy induced or not.

Overall, I think this framework can easily be applied to most economies in the world and a major advantage is that we can get down to the basics by just looking at three macroeconomic variables: (the growth rates of) Real GDP, Nominal GDP (or the GDP deflator) and the money supply.

Based on these variables and equations we can basically decompose the actual development in any economy between on the one hand supply shocks and on the other hand demand shocks (monetary policy shocks and velocity shocks).

How will we do forecasting with this model?

Operationally we could think of a set-up where we keep (the growth of) money-velocity (v) constant in the forecasting period. Furthermore, we would assume that our three shocks (supply, monetary policy and velocity) are zero as we by definition cannot forecast shocks. However, we could also think of these shocks as “forecastable” in the very short-term (within a quarter). I will in later posts return to this topic – how to use financial variables as an approximation of the expected impact of shocks to aggregate demand and supply.

If we want to apply our model to actual forecasting we first see that the monetary policy rule is the rule that “closes” the model. The central bank is assumed to set the money supply growth rate to hit a given monetary policy target – for example a NGDP target.

So if we for example have a given money supply growth rate at our starting point and NGDP growth is at a rate slower than the targeted growth rate and we are assuming that the central bank will try to hit the target NGDP growth rate in 2 or 3 years then we get a “growth path” for the money supply. We could think of this growth being implemented by the central bank or by the market (for example through a Scott Sumner style NGDP futures market).

This will give us a forecast for the growth rateof  not only the money supply, but also for real GDP and inflation (the GDP deflator). Obviously we can build more or less sophisticated models for private consumption, investments, unemployment, the trade balance etc. to expand the model, but the overall framework would be the same.

What is important is that we with this four-equation set-up can both get an understanding of what shocks are driving the business cycle in real-time and we can at the same time use the model to forecast RGDP growth and inflation (and obviously NGDP growth). And most important – this will not only be empirically useful, but it will also – and this is much more important – allow us to make economically meaningful forecasts.

In the coming weeks I will try to go more into detail with a discussion of the individual equations in the model – including how we can use financial market data to improve macroeconomic forecasting.

And then hopefully at a point I will be able to present a model for a “random” country to show that this set-up actually has a practical application.

PS Returning to the US weather and the macroeconomic development in the US I believe that the framework presented above should make it fairly easy to decompose present US growth to better understand whether we are now seeing a negative demand shock (monetary tightening) or just a short-term negative supply shock (bad weather).

 

Revisiting the discretionary decision to introduce rules

A couple of days ago Scott Sumner had an interesting post on the theme “It’s policy regime that needs fixing”.

In his post Scott made an interesting observation:

“Good policy is rules-based, but first you must use discretion to decide the optimal rule. But we never actually do pick a rule, and hence the frustration of us rules proponents, we are always seeing the wrong debate take place.”

That reminded me about something I wrote back in May 2012. It is very similar to what Scott is saying. This is from my post “The discretionary decision to introduce rules”:

“At the core of Market Monetarists thinking is that monetary policy should be conducted within a clearly rule based framework. However, as Market Monetarists we are facing a dilemma. The rules or rather quasi-rules that are presently being followed by the major central banks in the world are in our view the wrong rules. We are advocating NGDP level targeting, while most of the major central banks in the world are instead inflation targeters.

So we have a problem. We believe strongly that monetary policy should be based on rules rather than on discretion. But to change the wrong rules (inflation targeting) to the right rules (NGDP targeting) you need to make a discretionary decision. There is no way around this, but it is not unproblematic.”

Scott’s as well as my point is that we need to get away from discussing the day-to-day policy actions of central banks. It for example does not make much sense to discuss whether the Federal Reserve should “taper” or not when it is unclear what monetary policy target the Fed is trying to hit.

Hence, we can really only understand whether monetary policy is too tight or too easy if we know what target the central bank is trying to achieve. Obviously we can assume that the Fed has a given nominal target and then argue that given that target it is right or wrong to taper presently.

Focusing on discussing monetary policy rules will also do a lot to unite Free Market economists who during the Great Recession have been split over the issue of how best to respond to the Great Recession. The point is exactly that central bankers should not be fire-fighters who makes discretionary decision to save the world from fires they often themselves have started. Optimally we should get rid of central bankers altogether and let rules and markets determine monetary conditions.

What we should be debating is what monetary policy rules best ensure nominal stability. I personally continue to think that NGDP level targeting is the “best” rule in terms of achieving nominal stability and the smallest level of distortion of relative prices, but there might be pragmatic reasons why other rules might be preferable for certain countries.

PS I am struggling a bit with a writer’s block at the moment. The key reason is that it so far has been an extremely busy year for me as there seems to be a constant flow of bad news for Emerging Markets. Lately of course the Ukrainian-Russian conflict has been taking a lot of my time and mental energy. I must admit that I am deeply worried about events in Eastern Europe and I find myself making historical comparisons that I don’t like to think about. Frustrations over bad central bankers is one thing – it is a completely another thing to worry about men with guns and bombs. Maybe in fact there is a relationship between the two things…anyway I would welcome any suggestions for topics regarding monetary issues that my readers would like to read about.

PPS If you want to understand what I worry about in relationship to the Ukraine-Russia situation you should read this book. Hopefully I am not overly hysterical in my thinking…

This is how worried Dr. Copper is about the Chinese economy (the one graph version)

Dr Copper

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