The difficulties of reducing long-term unemployment

Since the global financial crisis started there has been a debate about how much of the increase in unemployment is cyclical versus structural. Arpaia and Turrini summarize the results of their analysis of the EU labor market in a recent Vox post.

They start by showing that there has been a significant shift in the relationship between vacancies and unemployment (what is known as the Beveridge curve) in many of the EU countries. This shift, combined with further analysis of how unemployment reacts to changes in labor demand leads them to conclude that there has been a decline in the matching efficiency of the labor market in these countries. From their post:

"...a major drop in matching efficiency was recorded in 2009 in most countries. Unsurprisingly, matching efficiency has been falling mostly in the countries that witnessed a marked outward shift in the Beveridge curve, although some signs of stabilisation or even recovery are visible by 2013Q1"

They then try to understand the reason for matching efficiency to decline and they test several hypothesis: mismatch in skills, industry or regions. It is interesting that although the three play a role in the full sample none of them are statistically significant in the post-2007 period (only skills mismatch is close to being significant).

But out of the controls that they introduce in their regressions, there is one that shows up as a strong determinant of the change in labor market efficiency: the change in long-term unemployment. In other words, one cannot reject the view that a deep recession resulted in a large increase in cyclical unemployment that turned into long-term unemployment because of the duration of the recession and this has led at a decline in the efficiency of the labor market. This is not far from what Blanchard and Summers (back in 1986) labelled as hysteresis in the labor market when describing the performance of also European labor markets in the 70s and 80s. The added insight of Arpaia and Turrini is that the difficulty in reducing long-term unemployment is related to the effect that its high level reduces the overall matching efficiency of the labor market.

The role that long-term unemployment and hysteresis could be playing in the US during the current crisis relative to more structural factors is also a source of debate. What is clear from the data is that the increase in long-term unemployment during this crisis is a lot more pronounced than in any previous crisis, which matches well the deterioration of other labor market indicators (such as the employment to population ratio).

 
Antonio Fatás

Global interest rates and growth (r-g).

The difference between interest rate and growth rates appears as an important parameter in many macroeconomic models. It is also a key variable to assess the sustainability of public finances: higher interest rates make the cost of carrying over debt higher while high growth rates help keep the debt to GDP ratio under control.

In a recent post Floyd Norris criticizes the assumptions used by the US Congressional Budget Office for its fiscal projections because they are assuming lower growth rates ahead but a return to "normal" interest rates. The point that Norris makes is that we tend to think that interest rates and growth rates are correlated, so if growth is going to be much lower going forward we should also forecast lower interest rates (and this will make the fiscal outlook look more positive).

Paul Krugman initially supports Floyd Norris' arguments but later, after checking the data, he realizes that growth and interest rates are not that correlated. Here is the picture of the difference between interest rates and growth rates for the US (from Krugman).

The relationship between interest rates and growth rates shows no clear pattern in the chart. During the 60s interest rates were lower than growth rates (when growth was high). We see a similar pattern in recent years but in this case growth is low. The 80s stand out as a period of high interest rates compared to growth (and growth was around its long-term average).

But there is an additional issue regarding the difference between this analysis of interest rates and growth: Norris and Krugman are looking at interest rates and growth in the context of one economy (the US). But given the global nature of capital markets the relationship between interest rates and growth (if any) should only be present at the global level. What happens if we look at the  differential between interest rates and growth for the world? Here is a quick attempt to measure this difference:

[See footnote for data sources and calculations]

To understand better how the pattern above matches that of GDP growth, here is World growth in each of these decades (measured both in real terms -constant US dollars- and nominal terms - current US dollars).

What is the World pattern of growth and interest rates? As in the US data, the relationship between interest rates and growth rates has varied over the past decades. Real growth is stable across all decades although increasing after 2000 (because of emerging markets).

The 80s stands out as a decade with very high interest rates relative to growth. The 2000s and the 2010-13 period are characterized by very low rates relative to growth (while global growth remains strong).

What determines interest rates then? The usual narrative of the post 2000 sample is that of the saving glut that stars in the late-90s with the increase in saving rates in regions like Asia (partly as a response to the Asian crisis). Theoretically, such a global shift in saving should lead to lower interest rates and increasing growth rate in the world.

In summary, given that interest rates are determined by global conditions, anything could happen when comparing them to growth rates for a given country (of course if the country is large enough to influence global variables then national and global conditions are correlated). The right way to look at these two variables is at the world level. But the empirical evidence confirms that, even if we look at a global level, one cannot rule out future scenarios of movements in interest rates and growth rates in opposite directions (they still need to be justified in terms of the global dynamics of investment and saving, but they are possible).

Antonio Fatás

[Some data issues: World GDP is coming from the IMF World Economic Outlook (converted to USD using market exchange rates; using PPP does not make a difference). I have taken the average of interest rates and growth rates over a decade (each of these decades includes some global recession so cyclical factors might not matter much except for the 2010-2013 period). Unfortunately data starts in the 80s so I cannot say much about the 60s and 70s (yet). Interest rates are from US treasuries under the assumption that this is the closest we can get to a World interest rates on riskless assets (using interest rates from other advanced economies will not change the pattern much; using interest rates from emerging markets can make some of a difference because of the volatility of risk premia). I have done the calculation using both a 10-year and a 1-year bond -- as it is clearly from the chart, the overall pattern is similar.]

Financial markets arbitrage: reassuring or lovely?

John Cochrane has a new blog post summarizing recent research by Budish, Cramton and Shim on the effects of high frequency trading. The paper shows that as high frequency trading spreads the correlation of a particular asset price across two US markets (Chicago and New York) has become higher at intervals that are very short. Any price deviations across the two markets disappear in less than one second. As Cochrane puts it,

It is lovely to see the effect of "arbitrageurs" making markets "more efficient."

As an academic I enjoyed reading the post as it provides a very nice example of a clean empirical test of how high frequency trading makes the comovements of two markets stronger. This is what we look for in academic papers, a clean test of a very simple theory that produces very credible and robust results.

But as much as I enjoyed reading the post, it also reminded me of how limited is the ability of academic research to help us understand phenomena that really matter. In this particular case, the analysis compares the price of the same security in two nearby markets (geographically but also linked by very fast communications). As communications and trade become faster and faster, price deviations between the two markets disappear in a shorter period of time. This is really nice to see but is this a big surprise? One would expect that at a minimum, very basic arbitrage opportunities do not exist in integrated financial markets. So it is reassuring that arbitrageurs help markets be more efficient but I am not sure I would go as far as saying that this is "lovely".

What would be more interesting (at least to me) is understand whether high frequency trading helps getting financial prices right. And by "right" I mean prices that are consistent with economic fundamentals, prices that do not generate volatile dynamics and bubble-type behavior. If we could prove that this is the case then I would find the result "lovely".

Antonio Fatás

The permanent scars of economic pessimism

Gavyn Davies at the Financial Times reflects on the growing pessimism of Central Banks regarding the growth potential of advanced economies. In the US, the Euro area or the UK, central banks are reducing their estimates of the output gap. They now think about some of the recent output losses as permanent as opposed to cyclical.

It output is not far from what we consider to be potential, there is less need for central banks to act and it is more likely that we will see an earlier normalization of monetary policy towards a neutral stance.

Why did they change their mind? Is this evidence consistent with the standard economic models that we use to think about cyclical developments?

Measuring potential output or the slack in the economy has always been challenging. One can rely on models that capture the factors that drive potential output (such as the capital stock or productivity or demographics) or one can look at more specific indicators of idle capacity, such as capacity utilization or unemployment rate.

Narrow measures of idle capacity do signal a potential permanent reduction in output. For example, unemployment rates, in particular in the US, are coming down. Capacity utilization is also approaching levels that can be considered as close to normal. As an example, in the most recent Inflation Report, the Bank of England writes "Surveys suggest that the margin of spare capacity within companies narrowed in 2013 such that companies were, on average, operating at close to normal levels of capacity utilization".

But both of these measures while they might be ok are capturing short-run idle capacity are very problematic as indication of potential growth . In the case of unemployment, one of the main reasons why it has decreased in the US is because of the fall in participation rates. But some of these permanent changes in the labor force are the result of a long recession. There is evidence that in the US long-term unemployed workers are giving up, and leaving the labor market at increasing rates. A similar argument can be made about capacity utilization: it might be that we are getting close to normal utilization levels, but is capacity at a normal level? A long period of low investment rates will naturally lead to lower installed capacity. This is Say's Law backwards, demand (investment reacting to cyclical conditions) creates its own supply (capacity). [Several years ago I wrote a paper with a model and some empirical evidence in favor of this hypothesis].

Both of these arguments point in the same direction: business cycles can leave permanent (or at least very persistent) scars on output through the effects they have on the capital stock or the labor force. But it is important to understand that the permanent effects are the consequence of the recession itself. If we could manage to reduce the length and depth of the recessions we would be minimizing those permanent effects. And in that sense, accepting these changes as structural and unavoidable is too pessimistic, leads to inaction and just makes matters worse. If you read the evidence properly, you want to do the opposite, you want to be even more aggressive to avoid what it looks at a much bigger cost of recessions.

Antonio Fatás

ECB and its excuses for inaction

Mario Draghi showed great skills in handling all questions in yesterday's press conference. When pressed about why the ECB is not doing more in the presence of low inflation and possibly deflationary pressures he answered that they are are doing enough and that there is no deflation in the Euro area but simply a period of "low inflation from a protracted period of time". Technically he is right, inflation is low but remains positive and expectations of inflation do not point in the direction of immediate deflation.

But what remains unclear is the message that he is giving about future actions. How low should inflation be and for how many months before the ECB considers that it is necessary to have more expansionary monetary policy? And why is the ECB ignoring the second pillar of its strategy (the money supply) when the numbers show growth rates that are clearly below target? [I am not a fan of the monetary pillar but it is always fascinating to see how the ECB feels compelled to report M3 growth numbers and then ignores them.]

Draghi gives two reasons to justify his inaction. One is the usual statement that there are risks on both sides:

"Both upside and downside risks to the outlook for price developments remain limited, and they continue to be broadly balanced over the medium term."

This sentence reminds me of the language used by the Bank of Japan to defend their inaction during the many years with deflation. Here is a quote from the minutes of the Bank of Japan monetary policy meeting in April 2010:

"Regarding risks to prices, some members said that attention should continue to be paid to a possible decline in medium- to long-term inflation expectations. One member expressed the view that attention should also be paid to the upside risk that a surge in commodity prices due to an overheating of emerging and commodity-exporting economies could lead to a higher-than-expected rate of change in Japan's CPI."

How could it be that in 2010 in Japan, after more than 20 years of struggling with deflation and in the middle of a global crisis, the perception of risks looked balanced and that some had the fear of overheating? And even if risk look balanced, what about erring once on the other side of this balance?

The second reason that Draghi gives is that the situation is very complex and that they need to wait for more data in March. Maybe this was a way of saying that action is coming, but it is confusing and it remains unclear why uncertainty should lead to inaction.

Draghi is right, the Euro area does not have deflation today, but if the risks to price developments are perceived as balanced by the ECB, and uncertainty is another excuse for inaction it looks as if the ECB is doing its best to ensure that the Euro area remain close enough to deflation (not to 2%) and Draghi can be sure that he will get the same exact questions in future press conferences.

Antonio Fatás

The conservative bias of economic models

Chris House has an interesting post on why economists tend to be more conservative than academics in other fields. His argument is that many economic facts have a conservative bias (e.g. when you look for evidence on politically loaded questions such as the effects of the minimum wage or high taxes).

Noah Smith replies and argues that there is no such bias in economic facts, quite the opposite, the evidence is weak for some of these questions. So where is the bias coming from? My sense is that it is coming from models to which most economists feel very attached to. And this is partly the case because these models and their economic logic is the one that allows us to show the value that our profession adds. Let me explain.

Economists do not have a great reputation when it comes to forecasting. Given the number of jokes about the inability of economists to forecast anything, about how we assume away any interesting real world phenomena, many macroeconomists stay away from practical questions about policy [As an example, when Chris Sims was awarded the 2011 Nobel Prize in economics, he was very reluctant about giving policy recommendations to get out of the economic crisis.]

But even if you avoid those difficult empirical questions you can still impress your friends by showing how the logic of simple economic concepts can go very far in understanding complex real world phenomena. Talking about opportunity cost, the difference between nominal and real variables, introducing a general equilibrium effect in a macroeconomic question or using game theory to help improve the analysis of a strategic situation are examples where economists thrive and show the added value of the discipline.

And in this spirit, when someone asks us why don't we raise wages to increase demand we use our economic logic to explain that this does not work, that increases in wages will do the opposite by reducing employment and GDP because of the effects on labor costs. And when someone suggests that the central bank should print money and distribute it to every household so that we are all richer, we explain to them that this will only create inflation. This is the origin of the conservative bias of economists, the conservative nature of the benchmark model that economists use. Of course we also have models where increases in wages could lead to higher GDP and there are situations where large increases in the money supply could not generate much inflation but those are much more complex models and they represent an exceptions to the benchmark model that economists tend to start with when they teach or explain their subject to others.

And what is interesting is that this bias does not always show in casual conversations. Many macroeconomists do not use the intuition of the benchmark model when having a casual conversation about economic policy. For example, as Paul Krugman argues today in his blog, most economists share the view that during the current crisis monetary and fiscal policy should have been more aggressive. Similarly, in casual conversations and when confronted with questions about efficiency of financial markets or labor markets or health care economists tend to describe a world full of inefficiencies and where government intervention makes sense. But it is rare that you hear the same strong message when you read their research or when they speak about it in public. Paul Krugman is right in the sense that his views are in many ways mainstream today but it is the fact that he expresses them in such an open manner that sets him aside from many other macroeconomists. I can see why some feel uncomfortable about making such strong policy recommendations given the uncertainty we have about our models or the evidence. I personally find it very refreshing to see more academics being willing to share their views to a broader audience through blogs or articles in a way that enriches the economic debate (even if, unfortunately, it might not have such a big impact on economic policy).

Antonio Fatás

The anti-demand coalition

In yesterday's blog post Paul Krugman summarizes very well the position of some academic economists who deny the potential role that aggregate demand might have in explaining business cycles and, as a result, they reject any policies that might have an effect via the demand channel. Their models are only driven by changes in the productive capacity of an economy which means that the Great Recession (or the Great Depression) must have been the result of some destruction in our capital stock or our inability to remember how to work or produce or somehow our technology got worst than in previous years.

It might be that these economists are just describing an ideal world using assumptions that are very far from the real world but how is it possible that these ideas seem to have such a strong influence in economic policy and even support among the general public? Why is it that countercyclical policy (fiscal or monetary) has been challenged so much during the current crisis? Most policy makers and certainly the public at large do not share the assumptions used by those economic models. In fact, when most people are asked to describe the dynamics of economic crisis, they immediately refer to some notion that shortages of demand cause recessions. When I teach about recessions and I ask my students about the cause of business cycles they immediately tell a story that sounds like the very basic keynesian multiplier (spending reduces income which further reduces spending...). But when the same students are asked to give their views about appropriate economic policies during a crisis, they immediately show their distrust in governments and central banks in their ability to help smooth business cycles. Somehow, expansionary fiscal policy or monetary policy cannot work because it is driven by the government.

So we end up with an odd coalition of views against countercyclical economic policy: those who rely on models where by definition countercyclical policy is ruled out and those who do not believe in these models (they laugh at them if you explain all the assumptions) but because they have no trust in governments they end up reaching the same conclusion.