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October 10, 2015

Latest Posts from Economist's View

Posted: 02 Oct 2015 12:42 AM PDT
Why do Republican politicians support tax cuts for the wealthy despite their unpopularity (as documented in a part I left out), and their failure to spur economic growth?:
Voodoo Never Dies, by Paul Krugman, Commentary, NY Times: So Donald Trump has unveiled his tax plan. It would, it turns out, lavish huge cuts on the wealthy while blowing up the deficit.
This is in contrast to Jeb Bush's plan, which would lavish huge cuts on the wealthy while blowing up the deficit, and Marco Rubio's plan, which would lavish huge cuts on the wealthy while blowing up the deficit.
For what it's worth, it looks as if Trump's plan would make an even bigger hole in the budget than Jeb's. Jeb justifies his plan by claiming that it would double America's rate of growth; The Donald, ahem, trumps this by claiming that he would triple the rate of growth. But really, why sweat the details? It's all voodoo. The interesting question is why every Republican candidate feels compelled to go down this path.
You might think that there was a defensible economic case for the obsession with cutting taxes on the rich. That is, you might think that if you'd spent the past 20 years in a cave (or a conservative think tank). ...
True, you can find self-proclaimed economic experts claiming to find overall evidence that low tax rates spur economic growth, but such experts invariably turn out to be on the payroll of right-wing pressure groups (and have an interesting habit of getting their numbers wrong)... There is no serious economic case for the tax-cut obsession.
Still,... every Republican who would be president is committed to a policy that is both demonstrably bad economics and deeply unpopular. What's going on?
Well,..., it's straightforward and quite stark: Republicans support big tax cuts for the wealthy because that's what wealthy donors want. No doubt most of those donors have managed to convince themselves that what's good for them is good for America. But at root it's about rich people supporting politicians who will make them richer. Everything else is just rationalization.
Of course, once the Republicans settle on a nominee, an army of hired guns will be mobilized to obscure this stark truth. We'll see claims that it's really a middle-class tax cut, that it will too do great things for economic growth, and look over there — emails! And given the conventions of he-said-she-said journalism, this campaign of obfuscation may work.
But never forget that what it's really about is top-down class warfare. That may sound simplistic, but it's the way the world works.
Posted: 02 Oct 2015 12:15 AM PDT
For the Minsky fans:
Volatility, financial crises and Minsky's hypothesis, by Jon Danielsson, Marcela Valenzuela, Ilknur Zer, Vox EU: Received wisdom maintains that financial market volatility has a direct impact on the likelihood of financial crisis.
Perhaps the best expression of this is Minsky's (1982) hypothesis that economic agents observing low financial risk are induced to increase risk-taking, which in turn may lead to a crisis. This is the foundation of his famous statement, "stability is destabilizing".
More recently, this sentiment has found support amongst policymakers:
"Volatility in markets is at low levels, both actual and expected... to the extent that low levels of volatility may induce risk-taking behavior is a concern to me and to the Committee" -- Federal Reserve Chair Janet Yellen, 18 June 2014.
Such views find support in the recent theoretical literature, where economic agents react to volatility deviating from what they become to expect it to be.
Low volatility induces economic agents to take more risk, endogenously increasing the likelihood of future shocks. If the economic conditions deteriorate and the resulting bad investment decisions start to sour, volatility then increases, signaling a pending crisis.
However, we could not find any empirical literature documenting such a relationship between financial market volatility, risk taking, the real economy and crises. Perhaps we have made little empirical progress since Paul Samuelson's famous quip in 1966 that "Wall Street indexes predicted nine out of the last five recessions"!
The decomposition of volatility
This lack of empirical clarity has motivates us to take a new approach to verify the volatility-crisis relationship, focusing on unexpectedly high and unexpectedly low volatility.
Crises are rare events – recent history notwithstanding, an OECD member country suffers a banking crisis only once every 35 years, on average. Consequently, in order to obtain a meaningful statistical relationship between volatility and crises, it is helpful to take the long-term historical view.
Since no comprehensive data on historical volatilities is available, we constructed such a database from primary sources, one that spans 1800 to 2010 and covers 60 countries.
We make use of Reinhart and Rogoff's (2009) banking and stock market dataset as our crisis indicator and use GDP per capita, inflation, change in government debt to GDP ratio, institution quality and fixed effects as controls.
We then ran a binomial regression model on the incidence of financial crises with lagged averages of volatility and controls as explanatory variables, finding little significance.
We surmise that this is due in part to the theoretical literature emphasizing volatility expectations and deviations therefrom, not the contemporaneous level of volatility.
Furthermore, volatility has a trend that evolves slowly over time, where one can identify regimes of high or low volatiles that last for many years and decades. Consequently, the expected level of volatility can be quite different across countries and time, weakening any empirical analysis focused solely on volatility levels.
We address this by decomposing volatility into unexpectedly low and high volatilities and using these as explanatory variables in the regression model.
In particular, borrowing terminology from the literature on output gap, we interpret the slow running volatility trend, calculated by a one-sided Hodrick-Prescott filter, as long-term expected volatility. Unexpectedly high and low volatility is then the deviation of volatility from above and below its trend, respectively.
Validating Minsky
We find a strong and significant relationship between unexpected volatilities and the likelihood of financial crises.
Unexpectedly low volatility increases the probability of both banking and stock market crises. This holds especially strongly if low volatility persists half a decade or longer.
We further investigate this by using the credit-to-GDP gap as a proxy for risk-taking, finding that unexpectedly low volatility significantly increases risk-taking. This result complements that of Taylor and Schularick (2009), where credit booms are destabilizing, leading to a banking crisis.
For stock market crises, but not banking crises, high volatility also increases the likelihood of a crisis, but only with much shorter lags, up to two or three years.
This is very much in line with what theory predicts and provides strong evidence for Minsky's instability hypothesis. Low volatility induces risk-taking that leads to riskier investments. When those turn sour, the resulting high volatility signals a pending crisis.
These results are robust to a number of alternative specifications, for example on the definition of volatility, filtering, lag lengths, sample selections and model specifications.
We find that the relationship between unexpected volatility and the likelihood of a future crisis becomes stronger over time. This is not surprising since the importance of stock markets and the prevalence of limited liability corporations have steadily been increasing.
The main exception to this is the Bretton Woods era when financial markets were tightly regulated and capital flows controlled, causing the volatility-crisis relationship to weaken significantly.
While the common view maintains that volatility directly affects the probability of a crisis, this has been proven difficult to verify empirically.
In what we believe is the first study to do so, we find direct empirical evidence that the level of volatility is not a good indicator of crisis, but that unexpectedly high and low volatilities are.
This is directly in line with what is predicted by theory and provides a validation of Minsky's hypothesis – stability is destabilizing.
Market volatility is of clear interest to policymakers, with the quote of chairwoman Yellen above just one example.
By documenting how volatility can affect the risk-taking behavior of economic agents and hence, the incidence of financial crises, policymakers and market participants alike would gain a valuable tool in understanding crises, tail events and systemic risk.
Author's note: Jon Danielsson thanks the Economic and Social Research Council (UK). Marcela Valenzuela thanks Fondecyt and Instituto Milenio.
Disclaimer: The views in this column are solely those of the authors and should not be interpreted as reflecting the views of the Board of Governors of the Federal Reserve System or of any other person associated with the Federal Reserve System.
Danielsson, J, M Valenzuela, and I Zer (2015), "Learning from History: Volatility and Financial Crises", SSRN.
Minsky, H (1992), "The financial instability hypothesis", Working Paper.
Reinhart, C M and K S Rogoff (2009), "This Time is Different: Eight Centuries of Financial Folly", Princeton University Press.
Samuelson, P (1966), "Science and stocks", Newsweek.
Taylor, S (2009), "Credit booms go wrong", VoxEU, 8 December.
Yellen, J (2014), press conference, Federal Reserve Board, 18 June.
Posted: 02 Oct 2015 12:06 AM PDT
Posted: 01 Oct 2015 09:29 AM PDT
For a long time, I have been making the argument that part of the reason for the inequality problem is distortions in the distribution of income driven by market imperfections such as monopoly power that allows prices to exceed marginal costs. What I didn't realize is that this can also affect measurements of productivity growth:
The relationship between U.S. productivity growth and the decline in the labor share of national income, by Nick Bunker: One of the ongoing debates about the state of the U.S. economy is the extent to which the profits from productivity gains are increasingly going to the owners of capital instead of wage earners. These researchers are debating the extent to which the labor share of income, once considered a constant by economists, is on the decline.
But what if the decline of national income going to labor actually affects the measured rate of U.S. productivity growth? In a blog post published last week, University of Houston economist Dietz Vollrath sketches out a model showing just that scenario. ...
Vollrath argues that businesses with more market power are able to charge higher markups on their goods and services, meaning their pricing is higher than the cost of producing an additional goods or services compared to pricing in a perfectly competitive market. So in this situation where markups are high, goods and services are being produced less efficiently, with the increased profits going to the owners of capital.
Vollrath argues that this is how measured productivity growth is affected by the decline of the labor share of income. Market power is important for thinking about measured productivity growth because, as Vollrath says, it "dictates how efficiently we use our inputs." ... Impeding the most efficient use of capital and labor via marked-up prices will reduce measured productivity. ... Perhaps this could explain some of the reason why measured productivity growth looks so meager in the seeming age of innovation...
But Vollrath's story isn't a complete explanation of the fall in measured productivity, as he acknowledges...
But Vollrath's market power explanation for falling productivity growth, alongside the falling share of national income going to wage earners, is supported by some evidence.  Work by Massachusetts Institute of Technology graduate student Matt Rognlie, for example, found evidence of higher markups.
Whether and how the decline of the labor share of income affects productivity growth is obviously a topic far too large for a couple of blog posts. But Vollrath's model is especially interesting for connecting two important trends in recent years: the slowdown in productivity growth and the declining labor share. It's worth, at the very least, a bit more investigation.
Posted: 01 Oct 2015 09:27 AM PDT
Two posts on housing. First, how will an increase in interest rates impact mortgage markets?:
The costs of interest rate liftoff for homeowners: Why central bankers should focus on inflation, by Carlos Garriga, Finn Kydland, and Roman Ĺ ustek: The Federal Reserve Bank and the Bank of England left their policy interest rates unchanged this month... But an interest rate liftoff in the near future remains on the table in both the US and the UK, provided the headwinds from China ease off and there is further evidence of improvements in the domestic economy. Inflation, however, still hovers in both economies stubbornly around zero percent. 
Interest rates set by central banks influence the economy through various transmission mechanisms. But one channel affects the typical household directly – the cost of servicing mortgage debt. ... Changes in the interest rate set by the central bank affect the size of mortgage payments, but differently for different types of loans. In addition, the real value of these payments depends on inflation. ...
Policy implications
To sum up, the effects of the liftoff on homeowners depend on three factors:
  • The prevalent mortgage type in the economy (fixed or adjustable rate mortgages);
  • The speed of the liftoff; and
  • What happens to inflation during the course of the liftoff.
If inflation stays constant at near zero then in the US, where fixed rate mortgage loans dominate, the liftoff will affect only new homeowners. In the UK, where adjustable rate mortgage loans dominate, the negative effects will in contrast be felt strongly by both new and existing homeowners.
However, if the liftoff is accompanied by sufficiently high inflation as in our examples, the negative effects will be weaker in both countries. In the US, the initial negative effect on new homeowners will be compensated by gradual positive effects on existing homeowners. And in the UK, provided the liftoff is sufficiently slow, neither existing nor new homeowners may face significantly higher real costs of servicing their mortgage debt. But if the liftoff is too fast, both types of homeowners in the UK will face higher real mortgage costs in the medium term, even if the liftoff is accompanied by positive inflation with no change in real rates.
Therefore, if the purpose of the liftoff is to 'normalize' nominal interest rates without derailing the recovery, central bankers in both the US and the UK should wait until the economies convincingly show signs of inflation taking off. Furthermore, the liftoff should be gradual and in line with inflation.
Second, allowing less creditworthy borrowers to refinance could stimulate the economy:
'Home Affordable Refinancing Program': Impact on borrowers, by Sumit Agarwal, Gene Amromin, Souphala Chomsisengphet, Tomasz Piskorski, Amit Seru, and Vincent Yao: Mortgage refinancing is one of the main ways households can benefit from a decline in the cost of credit. This column uses the US Government's Home Affordable Refinancing Program (HARP) as a laboratory to examine the government's ability to impact refinancing activity and spur household consumption. The results suggest that less creditworthy borrowers significantly increase their spending following refinancing. To the extent that such borrowers have the largest marginal propensity to consume, allowing them to refinance under the program could increase overall consumption and alleviate uneven economic outcomes across the country.

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