conversableeconomist

More on Hating Biofuels: The National Research Council

I\’ve posted here and here on how many international organizations hate government subsidies for biofuels. Now it\’s time for the National Research Council to have a whack at this pinata. The Committee on Economic and Environmental Impacts of Increasing Biofuels Production of the National Research Council has published: \”Renewable Fuel Standard: Potential Economic and Environmental Effects of U.S. Biofuel Policy.\” The report was mostly written under the chairmanship of Lester Lave, but was completed after his death last May. As befits a report from the NRC, it is a sober-sided discussion that lays out evidence at great length without seeking to take a particular explicit policy stance. Here are the eight major findings of the study, with a few quick comments from me, as quoted from the \”prepublication copy\” that can be downloaded free of charge:

FINDING: Absent major technological innovation or policy changes, the RFS2-mandated consumption of 16 billion gallons of ethanol-equivalent cellulosic biofuels is unlikely to be met in 2022.
RSF2 is the committee\’s way of referring to the Renewable Fuels Standard passed into law in 2005 and revised in 2007. Cellulosic biofuel is not from corn or soybeans or animal fat, but instead from certain kinds of grasses or wood chips. Cellulosic biofuel has the theoretical advantage that the sources for such fuel are cheap and abundant; however, producing fuel from these sources is harder than producing it from corn or soybeans or sugar, and the technologies for converting cellolosic material to biofuels are far from cost-effective. Indeed, they write \”no commercially viable biorefineries exist for converting lignocellulosic biomass to fuels as of the writing of this report.\”

FINDING: Only in an economic environment characterized by high oil prices, technological breakthroughs, and a high implicit or actual carbon price would biofuels be cost-competitive with petroleum-based fuels.
Indeed, the case for biofuels probably comes down to either very high oil prices or technological breakthroughs that make is much cheaper, because as the next finding notes, it\’s not at all clear that biofuels reduce greenhouse gas emissions.

FINDING: RFS2 may be an ineffective policy for reducing global GHG emissions because the effect of biofuels on GHG emissions depends on how the biofuels are produced and what land-use or land-cover changes occur in the process.
Expanded production of biofuels will almost certainly involve clearing and planting additional land. Depending on how it is done, this process can release more carbon than biofuels save. In addition, it\’s important to remember that the biofuels and agricultural products operate in a global market, so it\’s not just an issue of how U.S. biofuels policies affect clearing and planting of U.S. land, but how it affects clearing and planting of land all around the world.

FINDING: Absent major increases in agricultural yields and improvement in the efficiency of converting biomass to fuels, additional cropland will be required for cellulosic feedstock production; thus, implementation of RFS2 is expected to create competition among different land uses, raise cropland prices, and increase the cost of food and feed production.
FINDING: Food-based biofuel is one of many factors that contributed to upward price pressure on agricultural commodities, food, and livestock feed since 2007; other factors affecting those prices included growing population overseas, crop failures in other countries, high oil prices, decline in the value of the U.S. dollar, and speculative activity in the marketplace.
Many U.S. households can find ways to adjust without too much pain to a slightly higher price of food. But food products are sold in global markets, and for many people around the world, higher food prices can have dire consequences for nutrition and health.

FINDING: Achieving RFS2 would increase the federal budget outlays mostly as a result of increased spending on payments, grants, loans, and loan guarantees to support the development of cellulosic biofuels and forgone revenue as a result of biofuel tax credits.
Even if explicit subsidies for biofuels are allowed to expire, as they are scheduled to do at the end of 2012, the mandates for consuming biofuels will remain in place, which will raise costs for consumers. Also, gasoline is taxed and biofuels are subsidized, so a movement from gasoline to biofuels will reduce government tax revenues.

FINDING: The environmental effects of increasing biofuels production largely depend on feedstock type, site-specific factors (such as soil and climate), management practices used in feedstock production, land condition prior to feedstock production, and conversion yield. Some effects are local and others are regional or global. A systems approach that considers various environmental effects simultaneously and across spatial and temporal scales is necessary to provide an assessment of the overall environmental outcome of increasing biofuels production.
Biofuels are commonly sold on their environmental merits. The committee is saying here, in a very polite way, that when different feedstocks are considered, along with their effects on air, soil, and water, these purported environmental gains have not yet been convincingly demonstrated. 

FINDING: Key barriers to achieving RFS2 are the high cost of producing cellulosic biofuels compared to petroleum-based fuels and uncertainties in future biofuel markets.

I\’m a supporter of expanded energy R&D efforts. Maybe some scientists will find a way to make biofuels that are both cost-effective and clearly an environmental gain, in a way that doesn\’t drive up food prices around the world. But at this stage, subsidizing production of biofuels or mandating that they be used in certain quantities–especially for technologies like cellolosic biofuels that don\’t exist on a commercial basis–is putting the cart way in front of the horse.

conversableeconomist

Using Financial Repression to Reduce Government Debt

The usual ways of reducing a government debt burden over time are fairly well-known: cut spending or raise taxes; have the economy grow faster than the debt burden, so the ratio of debt/GDP declines over time; a burst of inflation, which reduces the real value of past debt; and in some cases an outright default or restructuring of the debt. To this list, Carmen Reinhart, Jacob F. Kirkegaard, and M. Belen Sbrancia offer \”Financial Repression Redux.\”Here are some main themes (references omitted for readability):

Here\’s their definition of financial repression:
\”Financial repression occurs when governments implement policies to channel to themselves funds that in a deregulated market environment would go elsewhere. Policies include directed lending to the government by captive domestic audiences (such as pension funds or domestic banks), explicit or implicit caps on interest rates, regulation of cross-border capital movements, and (generally) a tighter connection between government and banks, either explicitly through public ownership of some of the banks or through heavy “moral suasion.” Financial repression is also sometimes associated with relatively high reserve requirements (or liquidity requirements), securities transaction taxes, prohibition of gold purchases, or the placement of significant amounts of government debt that is nonmarketable…. \”

How financial repression works like a tax
\”One of the main goals of financial repression is to keep nominal interest rates lower than they would be in more competitive markets. Other things equal, this reduces the government’s interest expenses for a given stock of debt and contributes to deficit reduction. However, when financial repression produces negative real interest rates (nominal rates below the inflation rate), it reduces or liquidates existing debts and becomes the equivalent of a tax—a transfer from creditors (savers) to borrowers, including the government. But this financial repression tax is unlike income, consumption, or sales taxes. The rate is determined by financial regulations and inflation performance, which are opaque compared with more visible and often highly politicized fiscal measures. Given that deficit reduction usually involves highly unpopular expenditure reductions and/or tax increases, authorities seeking to reduce outstanding debts may find the stealthier financial repression tax more politically palatable.\”

How is financial repression currently operating in the U.S.?
One potential example of how financial repression is operating in the U.S. is the super-low interest rates. In part, of course, these are an attempt to stimulate the economy, but it also seems plausible to me that they are intended to help the U.S. government in financing its debt. But a more straightforward example is that when the Federal Reserve and other central banks buy U.S. Treasury debt directly—debt that might very well need to pay a higher interest rate if it was sold to outsiders. Back in 1990, outsiders owned about 75% of U.S. Treasury debt; now they own about half.

How is financial repression happening in other countries? 
Central banks in many other countries–for example, the UK, Ireland, Portugal, and Greece–have sharply increased their holdings of government debt. In France and Ireland, major pension funds have been required to invest in government debt.

How much can financial repression reduce government debt?
These authors cite research that financial repression can have a major effect in reducing government debt, through what they call \”the liquidation effect.\” Many of their calculations focus on how government debt burdens were reduced after WWII. They write: \”For the United States and the United Kingdom, the annual liquidation effect [between 1945 and 1980] amounted on average to between 3 and 4 percent of GDP a year. … For Australia and Italy, which recorded higher inflation rates, the liquidation effect was larger (about 5 percent a year).\”


My point here isn\’t to argue for or against what they call financial repression. But if their calculations are roughly right, it\’s an option for reducing government debt that could end up playing a major role, and needs to be better understood.

 

conversableeconomist

2011 Nobel Prize to Thomas Sargent and Christopher Sims

According to the Nobel website: \”The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2011 was awarded jointly to Thomas J. Sargent and Christopher A. Sims `for their empirical research on cause and effect in the macroeconomy.\’\” But what does that actually mean?

The website of the Nobel organization always offers useful background information about the laureates, including a \”Scientific Background\” paper about the winners. This year\’s background paper about Thomas Sargent and Christopher Sims is going to be hard sledding for those uninitiated into academic macroeconomics–by which I mean it has a bunch of equations. But the opening  pages offer an accessible overview of why they are eminently deserving of the prize. Here are some excerpts, mixed with some of my own explanations:

How was macroeconomic analysis done before the work of Sargent, Sims, and others? 
Here\’s my own description: If one looks back at how macroeconomics was typically done in the 1960s and into the early 1970s, the common macroeconomic models were big sets of equations–that is, they added up relationships between elements like consumption, investment, saving, imports, exports and total economic output, along with equations for how interest rates and exchange rates affected each other and these categories. A big category like \”consumption\” would be broken down in to durable goods and nondurable goods, and in turn these categories would be broken down still further. The resulting models would have hundreds of equations all interrelated with each other, and adding up to a picture of the macroeconomy as a whole. But as the Nobel background paper reports: \”This estimated system was then used to interpret macroeconomic time series, to forecast the economy, and to conduct policy experiments. Such large models were seemingly successful in accounting for historical data. However, during the 1970s most western countries experienced high rates of inflation combined with slow output growth and high unemployment. In this era of stagflation, instabilities appeared in the large models, which were increasingly called into question.\”

The key role of expectations in this analysis
Many of the public policy discussions in the stagflation of the 1970s focused on expectations. What if workers were expecting higher wages? What if firms could promise higher wages because they expected prices to rise? Were the expectations causing inflation and recession, or were inflation and recession causing the expectations, or were there feedback loops in all of these and other economic factors? The macroeconomics of that time had no clear-cut tools for dealing with these issues.

The background paper puts it this way: \”In any empirical economic analysis based on observational data, it is difficult to disentangle cause and effect. This becomes especially cumbersome in macroeconomic policy analysis due to an important stumbling block: the key role of expectations. Economic decision-makers form expectations about policy, thereby linking economic activity to future policy. Was an observed change in policy an independent event? Were the subsequent changes in economic activity a causal reaction to this policy change? Or did causality run in the opposite direction, such that expectations of changes in economic activity triggered the observed change in policy? Alternative interpretations of the interplay between expectations and economic activity might lead to very different policy conclusions. The methods developed by Sargent and Sims tackle these difficulties in different, and complementary, ways.\”

Sargent and structural econometrics
Instead of trying to build a macroeconomic model on a pile of statistics, and how those statistics added up and interrelated, the approach of Sargent (and others) was to build a macroeconomic model starting from the idea that economic actors like households and firms were doing their best to pursue their own interests. This approach has sometimes been called \”rational expectations,\” but that term is probably misleading. The \”rationality\” here doesn\’t mean that economic actors have all available information, can calculate everything perfectly, and always make correct decisions. It only implies that they won\’t make the same mistake over and over again. In Sargent\’s hands, at least, this approach explicitly leaves open the question of just how people form expectations and learn.

Here\’s the background paper: \”Sargent began his research around this time [the early 1970s], during the period when an alternative theoretical macroeconomic framework was proposed. It emphasized rational expectations, the notion that economic decisionmakers like households and firms do not make systematic mistakes in forecasting. This framework turned out to be essential in interpreting the inflation-unemployment experiences of the 1970s and 1980s. It also formed a core of newly emerging macroeconomic theories. Sargent played a pivotal role in these developments. He explored the
implications of rational expectations in empirical studies, by showing how rational expectations could be implemented in empirical analyses of macroeconomic events–so that researchers could specify and test theories using formal statistical methods–and by deriving implications for policymaking. …
In fact, the defining characteristic of Sargent\’s overall approach is not an insistence on rational expectations, but rather the essential idea that expectations are formed actively, under either full or bounded rationality. In this context, active means that expectations react to current events and incorporate an understanding of how these events affect the economy. This implies that any systematic change in policymaking will influence expectations, a crucial insight for policy analysis.\”

I would add that instead of a model of the macroeconomy with potentially hundreds of variables, Sargent and others worked with models that on the surface appeared much simpler: for example, one example in the \”background\” paper is a model of the macroeconomy that has only three variables: inflation, output, and a nominal interest rate. But the inferences about cause-and-effect in these models are defensible and logical.

Sims and vector autoregressions
Sims pointed out that the earlier generation of macroeconomic models were built on a series of assumptions about how certain economic factors or policies \”caused\” other policies. But in an model of expectations, these statements about \”cause\” needed to be demonstrated, not assumed. Thus, instead of having a model in which some factors caused other factors, Sims proposed that macroeconomic analysis should begin with a model in which is was possible for every factor to \”cause\” a change in every other factor, and in addition for past values of every factor over the last few years to \”cause\” a change in every factor. This approach is called a \”vector autoregression,\” but I often preferred to think of it as starting from a position of honest ignorance.

You then plug in all your data–say, quarterly data over a period of years–and see what patterns emerge. As you might imagine, it immediately looks clear that certain factors are not affecting others. Sims proposed a process for figuring out when certain factors aren\’t connected. As you begin to rule out what is NOT connected, what is left behind is a model of connections that actually exist. It\’s sort of like the way that a sculptor starts with a block of stone, and by gradually removing pieces, ends up with an image.

The background paper puts it this way: \”Sims launched what was perhaps the most forceful critique
of the predominant macroeconometric paradigm of the early 1970s by focusing on identification, a central element in making causal inferences from observed data. Sims argued that existing methods relied on \”incredible\” identification assumptions, whereby interpretations of \”what causes what\”
in macroeconomic time series were almost necessarily flawed. Misestimated models could not serve as useful tools for monetary policy analysis and, often, not even for forecasting. As an alternative, Sims proposed that the empirical study of macroeconomic variables could be built around a statistical tool, the vector autoregression (VAR). Technically, a VAR is a straightforward N-equation, N-variable (typically linear) system that describes how each variable in a set of macroeconomic variables depends on its own past values, the past values of the remaining N – 1 variables, and on some exogenous \”shocks.\” Sims\’s insight was that properly structured and interpreted VARs might overcome many identification problems and thus were of great potential value not only for
forecasting, but also for interpreting macroeconomic time series and conducting monetary policy experiments.\”

Other thoughts and resources
Sargent and Sims were colleagues at the University of Minnesota for about 15 years. The Federal Reserve Bank of Minneapolis puts out a readable publication called \”The Region,\” which often does in-depth interviews with prominent economists about their work. An interview with Sargent from the September 2010 issue is available here; an interview with Sims from the June 2007 issue is available here.

Also, Sims published an article in the Spring 2010 issue of my own Journal of Economic Perspectives called \”But Economics Is Not an Experimental Science,\” on issues of how to draw defensible cause-and-effect inferences from naturally-occurring data. Like all article in my journal, it is freely available courtesy of the American Economic Association.

While no one quite knows what the Nobel committee is thinking when they choose laureates, it seems clear that one standard is whether the ideas have been important enough to launch a sustained research literature. The ideas of Sargent and Sims from back in the 1970s and early 1980s certainly meet this test. Both these authors, and hundreds of others, have built on these ideas for decades.

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conversableeconomist

After Japan\’s Quake, the Intervention to Stabilize the Yen

In the aftermath of the dreadful earthquake and tsunami which hit Japan on March 11, 2011, I completely missed that there was an international intervention to stabilize the exchange rate of the Japanese yen. Fortunately, Christopher J. Neely tells the story and offers useful context in \”A Foreign Exchange Intervention in an Era of Restraint.\” Here are some highlights of what has happened, and what lessons can be drawn: 


Foreign exchange intervention has become rare for the G-7 countries
Back in the late 1980s and early 1990s, many major central banks stopped frequent intervention in exchange rate markets, as shown on the figure. In fact, there have been only three exchange rate interventions for these countries since 1995: an intervention after Japan\’s quake in March 2011, an intervention soon after the start of the euro in September 2000, and an intervention in the yen after East Asia\’s financial crisis in 1998. 

 
The FX intervention after Japan\’s March 2011 Quake
 Japan\’s currency started falling sharply after the earthquake. Here\’s how Neely describes what happened:  \”Nevertheless, the G-7 finance ministers and central bank governors held a conference call on the evening of Thursday, March 17 (Friday morning in Tokyo) and decided to conduct a coordinated intervention to weaken the JPY. The G-7 issued a press release containing the following text:

 In response to recent movements in the exchange rate of the yen associated with the tragic events in Japan, and at the request of the Japanese authorities, the authorities of the United States, the United Kingdom, Canada, and the European Central Bank will join with Japan, on 18 March 2011, in concerted intervention in exchange markets. As we have long stated, excess volatility and disorderly movements in exchange rates have adverse implications for economic and financial stability. We will monitor exchange markets closely and will cooperate as appropriate (G-7, 2011).

 Figure 7 shows that the yen reacted immediately to the intervention announcement, surging
almost 4 percent within the hour against the USD …\”

As Neely reports, the total intervention was about $10.4 billion. Notice that the yen starts stabilizing when the announcement is made, and then moves to a certain level and more-or-less sticks at that level for awhile. The volatility of the yen foreign exchange rate diminishes a great deal.

What did the 1998 exchange rate intervention look like?
Neely describes the background to the 1998 intervention this way: \”The June 1998 intervention also followed a financial crisis, the 1997 Asian exchange rate crisis in which international capital fled many developing Asian countries, such as Thailand and South Korea. In early June 1998, the main macroeconomic concern was that the yen was unusually weak and weakening further, which made goods and services from other Asian countries less competitive with Japanese goods and
services and harmed those countries’ recoveries. Policymakers probably feared that a falling yen
might cause China to devalue the renminbi (RMB), possibly sparking competitive devaluations, inflation, and instability throughout the region.\”

The pattern of the 1998 intervention is qualitatively similar to the 2011 intervention: that is, a reaction just before the announcement is made, a movement to a new level, and volatility is stabilized.

What happened in the September 2000 intervention? 
Neely sets the stage: \”On January 1, 1999, the ECB began conducting a common monetary policy with a new currency, the euro, for the 11 original nations of the European Monetary Union (EMU). From its inception, the euro tended to depreciate against the dollar, falling from about 1.18 USD/EUR on the inception date to less than 0.85 USD/EUR in September 2000. Doubts about the policies of the new central bank probably contributed to this weakness. At the same time, the U.S. economy was slowing—it would officially enter a recession in March 2001—and the strong dollar/weak euro was perceived as detrimental to U.S. exporters. In addition, the Japanese feared that an overly strong yen would price Japanese exports out of the European markets. Against this backdrop, the ECB, the United States, and Japan decided to intervene to support the euro on September 22, 2000.\”

Again, the qualitative pattern is the same: the exchange rate takes a jump, but then stabilizes at a new level with diminished volatility.

What are the overall lessons?
 Neely summarizes the lessons this way: \”Since 1995 most advanced governments/central banks have used intervention only very sparingly as a policy tool. Examination of coordinated interventions during this period shows that intervention is not a magic wand that authorities can use to move exchange rates at will. It can be a very effective tool in certain circumstances, however, to coordinate market expectations about fundamental values of the exchange rate and calm disorderly foreign exchange markets by reintroducing two-sided risk.\”

Those who are talking about pressuring China to adjust its exchange rate vs. the U.S. dollar have a reasonable case to make. But they would be wise to take to heart the practical issues here. Foreign exchange rate intervention can stabilize a disorderly  market in a short-run situation where everyone is betting the currency will move in only one directly, but is not a magic wand to move exchange rates at will.

conversableeconomist

America as Conventional Energy Powerhouse?!?

I\’ve been trying to wrap my mind around the issues and possibilities created by the new technologies for extracting oil and gas from North America. Amy Myers Jaffe, an energy expert who runs the Baker Institute Energy Forum at Rice University, has a nice provocative short article in the most recent issue of Foreign Policy magazine called  \”The Americas, Not the Middle East, Will Be the World Capital of Energy.\” Jaffe writes: 

\”By the 2020s, the capital of energy will likely have shifted back to the Western Hemisphere, where it was prior to the ascendancy of Middle Eastern megasuppliers such as Saudi Arabia and Kuwait in the 1960s. The reasons for this shift are partly technological and partly political. Geologists have long known that the Americas are home to plentiful hydrocarbons trapped in hard-to-reach offshore deposits, on-land shale rock, oil sands, and heavy oil formations. The U.S. endowment of unconventional oil is more than 2 trillion barrels, with another 2.4 trillion in Canada and 2 trillion-plus in South America — compared with conventional Middle Eastern and North African oil resources of 1.2 trillion. The problem was always how to unlock them economically.

But since the early 2000s, the energy industry has largely solved that problem. With the help of horizontal drilling and other innovations, shale gas production in the United States has skyrocketed from virtually nothing to 15 to 20 percent of the U.S. natural gas supply in less than a decade. By 2040, it could account for more than half of it. … Meanwhile, onshore oil production in the United States, condemned to predictions of inexorable decline by analysts for two decades, is about to stage an unexpected comeback.\”

Jaffe\’s article sent me back to the sober-sided Annual Energy Outlook 2011 published in April by the U.S. Energy Information Administration. Here\’s a figure showing how the new \”enhanced-oil recovery\” techniques are expected to raise oil production in the lower 48 states in a way that offsets declining production from Alaska. The report says: \”Rising world oil prices, growing shale oil resources (i.e., liquid oil embedded in non-porous shale rock), and increased production using EOR [enhanced oil-recovery] techniques contribute to increased domestic crude oil production from 2009 to 2035 in the AEO2011 Reference case (Figure 95). The Bakken shale oil formation contributes to growth in crude oil production in the Rocky Mountain Region, and growth in the Gulf Coast region is spurred by the resources in the Eagle Ford and Austin Chalk formations. Some of the decline in oil production in the Southwest region is offset by production coming from the Avalon shale formation.\”

And here\’s a figure showing that the share of U.S. oil consumption that is imported peaked in 2005, and is expected to fall over the next couple of decades. The report says: \”[W]hile consumption of liquid fuels increases steadily in the Reference case from 2009 to 2035, the growth in demand is met by domestic production.The net import share of U.S. liquid fuels consumption fell from 60 percent in 2005 to 52 percent in 2009. The net import share continues to decline in the Reference case, to 42 percent in 2035 …\”

Of course, there are potential environmental issues. There are issues about what kinds of risks are posed by these technologies for extracting oil, as well as about the conventional pollutants and carbon dioxide emitted by burning these fossil fuels. But for the next few decades, substantial quantities of fossil fuels will continue to be used. The carbon dioxide produced will be essentially the same regardless of where these fossil fuels are produced. Thus, if the local environmental issues can be worked out–that is, the issues about extracting these resources and about conventional pollutants–then there is no inconsistency in moving toward fossil fuels produced and refined by U.S. workers, rather than imported fossil fuels produced and refined by foreign workers, as we continue to seek ways of reducing global carbon emissions.  

conversableeconomist

Why Didn\’t Dot-Com Crash Hurt Like Housing Crash Did?

In the late 1990s, the U.S. economy suffered the end of the dot-com bubble, but had only a mild recession lasting for 8 months in 2001. But when the housing bubble popped, the U.S. economy had a brutally deep 18 month recession from December 2007 to June 2009, followed by a Long Slump of a recovery. Why did the bursting of the housing bubble hurt so much more? 

The magnitude of the two event is roughly similar. The value of corporate equities owned by households went from $9 trillion in 1999 to $4.1 trillion in the third quarter of 2002, according to stats in Table B.100 of the Federal Reserves Flow of Funds Accounts in September 2003. The value of household real estate dropped from $22.7 trillion in 2006 to $17.1 trillion by 2009, and since then has fallen to $16.2 trillion by the second quarter of 2011, according to stats in Table B.100 of the latest Flow of Funds Accounts released by the Federal Reserve. 

The answer is that when the dot-com boom collapsed, the lost value was in stock prices. Those who bought stocks knew in advance that stock prices could rise and fall. The losses for pension funds and retirement accounts were large, but they didn\’t cause widespread household or firm bankruptcies. However, when the housing price bubble burst, the losses were in the form of debts that couldn\’t be paid off. People couldn\’t pay their mortgages. Banks and financial institutions which were holding dicey mortgage-backed securities faced huge losses, and a financial crisis resulted. If the dot-com boom had been financed by enormous waves of household and business borrowing, and that borrowing had been turned into securities widely held by banks, then the bursting of the dot-com boom would have been much more economically destructive.

The key difference here is between equity and debt. The value of equity is contingent on what happens in the stock market, and so can rise or fall. But debt is typically not contingent on how other values change: you borrowed it, you need to pay it on schedule. Otherwise, defaults, foreclosures, bankruptcies, and financial crisis can result. Kenneth Rogoff thinks through many of these issues in the 2011 Martin Feldstein Lecture to the Natural Bureau of Economic Research: \”Sovereign Debt in the Second Great Contraction: Is This Time Different?\”

Rogoff focuses on this difference between non-contingent debt and contingent equity: [E]ven before the onset of the Second Great Contraction, it should have bothered macro-theorists more that such a large fraction of world capital markets consists of non-contingent debt, including public and private bonds, as well as bank credit. It is difficult to pin down global aggregates, but a recent McKinsey study found that at the end of 2008, the equity market accounted for roughly $34 trillion out of $178 trillion in global assets, with government debt, private credit, and banking accounting for the rest. This figure, of course, is exaggerated by the global stock market crash that occurred after the collapse of Lehman Brothers in 2008, but even at the pre-crisis equity level of $54 trillion, equity markets represented less than one third of the total. True, there is an entire zoology of derivative markets that makes some of the debt contingent, but incorporating these would not dramatically change the basic point.\”

As Rogoff points out, there have been proposals by Robert Shiller and others that when governments borrow, they should do so in a more contingent form–for example, perhaps the debt payments could adjust automatically if their GDP growth is faster or slower than expected. But in practice, given how governments can play games with their own economic statistics, such an approach has had limited appeal. In general, the clear promise to repay debt is easier to monitor and to enforce than a payment schedule linked to some other variable. But this widespread use of non-contingent debt, which in turn is subject to a wide array of poorly-understood risks, contributes to making the world economy a fragile place when bad news arises.

conversableeconomist

When Milton Friedman Blessed Foreign Exchange Futures Markets

Leo Melamed tells the story of “Milton Friedman’s 1971 Feasibility Paper” in the Fall 2011 issue of the Cato Journal: 

“In 1971, as chairman of the Chicago Mercantile Exchange, I had an idea: a futures market in foreign currency. It may sound so obvious today, but at the time the idea was revolutionary. I was acutely aware that futures markets until then were primarily the province of agriculture and—as many claimed—might not be applicable to instruments of finance. Not being an economist, the idea was in need of validation. There was only one person in the world that could satisfy this requisite for me. We went to Milton Friedman. We met for breakfast at the Waldorf Astoria in New York. By then he was already a living legend and I was quite nervous. I asked the great man not to laugh and to tell me whether the idea was “off the wall.” Upon hearing him emphatically respond that the idea was “wonderful,” I had the temerity to ask that he put his answer in writing. He agreed to write a feasibility paper on “The Need for Futures Markets in Currencies,” for the modest stipend of $7,500. It turned out to be a helluva trade.” 

The same issue publishes Friedman’s 1971 paper, “The Need for Futures Markets in Currencies,” for what I think is the first time. Friedman writes: 


\”Bretton Woods is now dead. The president’s action on August 15 [1971] in closing the gold window was simply a public announcement of the change that had really occurred when the two-tier system was established in early 1968. … The U.S. is a natural place for the futures market because the dollar is almost certain to continue to be the major intervention
currency for central banks and the major vehicle currency for international transactions. Exchange rates will almost surely continue to be stated in terms of the dollar. In addition, the U.S. has the largest stock in the world of liquid wealth on which the market can draw for support. It has a legal structure and a financial stability that will attract funds from abroad. It has a long tradition of free, open, and fair markets. It is clearly in our national interest that a satisfactory futures market should develop, wherever it may do so, since that would promote U.S. foreign trade and investment. But it is even more in our national interest that it develop here instead of abroad. As Britain demonstrated in the 19th century, financial services of all kinds can be a highly profitable export commodity.\”


conversableeconomist

Research and Development Tax Credit

Back in the mid-1980s, when the world was young and I was just leaving economics graduate school, I wrote editorials on economic and environmental issues for the San Jose Mercury News for a couple of years. (At that time, the paper was booming, because in those pre-Internet times, it carried much the help-wanted advertising for Silicon Valley.) In 1981, Congress had passed a tax credit for research and development, but it has been passed on a temporary basis. Remarkably enough, in 2011 the
the R&D tax credit still languishing in temporary status, expiring every few years and then being re-authorized, currently set to expire at the end of 2011.

The theoretical case for government support of R&D is unchanged over time: new technology provides social benefits that often greatly exceed the private benefits received by the inventor, and so society can in theory be better off by subsidizing such activity. However, two things have changed  since I was writing editorials advocating a permanent R&D tax credit back in the mid-1980s. There is now a body of research strongly suggesting that the tax credit is cost-effective at increasing research and development. And much of the rest of the world, agreeing with this research, now offers more aggressive support for industry R&D than does the United States.

Research supporting an R&D tax credit

The R&D Credit Coalition hired Ernst and Young to write a report on the evidence. Unsurprisingly, both given the parade of evidence over the years and the source of the funding (!), the report is called: \”The R&D Credit: An effective policy for promoting research spending.\”  Their overall conclusion is that an R&D tax credit could increase industry R&D spending by 10-20% over the long run, depending on design. Clearly, this isn\’t a revolutionary change–just a sensible step to take. Here\’s a useful figure summarizing the results of studies of how an R&D tax credit affects R&D spending.

International Trends

While U.S. policy on an R&D tax credit has been running in place for 30 years, many other countries have embraced such a policy. For example, here is an OECD report from 2008 on the spread of such incentives:  \”Recent years have seen a shift from direct public funding of business R&D towards indirect funding (Figure 3). In 2005, direct government funds financed on average 7% of business
R&D, down from 11% in 1995. In 2008, 21 OECD countries offered tax relief for business R&D, up from 12 in 1995, and most have tended to make it more generous over the years. The growing use of R&D tax credits is partly driven by countries’ efforts to enhance their attractiveness for R&D-related foreign direct investment.\”

Here is the Figure 3 referred to in the quotation. Cross-country comparisons of tax policy can be hazardous, because the conclusions can depend on just how certain provisions are classified. Nonetheless, it\’s striking that the U.S. ranks 24th in its tax support for industry R&D of the countries in the figure.

conversableeconomist

Left-Number Bias in Used Car Prices

Left-number bias is when you pay disproportionate attention to the number on the left. It\’s the reason why you see so many more prices at, say, $69.99 than at $70.01. When buying a used car, left-number bias manifests itself on the odometer: that is, car buyers view the difference between, say, 67,000 and 68,000 miles as of only modest importance, but the difference between 69,000 and 70,000 miles as quite important. Nicola Lacetera, Devin Pope, and Justin Sydnor Heuristic explore this topic with a with a data set of 22 million used car transations in \”Heuristic Thinking and Limited Attention in the Car Market.\” It\’s NBER Working Paper No. 17030, but these papers are gated unless your institution has a membership. 

For a short overview of the paper in the NBER Digest by Lester Picker, see here. I quote from that overview: \”[T]he authors document significant price drops at each 10,000-mile threshold from 10,000 to 100,000 miles, ranging from about $150 to $200. For example, cars with odometer values between 79,900 and 79,999 miles, on average, are sold for approximately $210 more than cars with odometer values between 80,000 and 80,100 miles, but for only $10 less than cars with odometer readings between 79,800 and 79,899. The authors also find price drops at 1,000-mile thresholds, but these changes are smaller.\”

Here is an illustrative figure. the horizontal axis shows miles on the odometer of the used car, rounded down to the nearest 500. The vertical axis shows average sale price. As you would expect, cars with more mileage on average sell for less. But look at what happens at each 10,000-mile level. Instead of price dropping in a more-or-less smooth line, there is a discrete price drop at each 10,000 mile level, showing the left-number bias at work.

Picker\’s overview in the NBER Digest also says: \”This apparent left-digit bias not only influences wholesale prices but also affects supply decisions. If sellers are savvy and are aware of these effects, then they will have an incentive to bring cars to auction before the vehicle\’s mileage crosses a threshold. Indeed, the authors show that there are large volume spikes in cars before 10,000-mile thresholds.\”

Here\’s a figure showing this effect on the supply side.Again, the horizontal axis shows mileage on the odometers of used cars. This time, the vertical axis shows volume of cars sold with that mileage. As one would expect, relatively few cars are sold with extremely low mileage. But look at the line at the 10,000-mile intervals from 60,000 to 100,000. There is an extra little blip of more cars being sold just before they cross over into the next mileage category. This is smart sellers, taking advantage of the left-number bias on the part of buyers.

conversableeconomist

More Herbert Hoover: Father of the New Deal

Last week I pointed out in Herbert Hoover, Deficit Spender that, contrary to a widespread belief, Hoover didn\’t cut spending or seek to balance the budget. Instead, Franklin Roosevelt ran in 1932 on promise to balance the budget, a promise which he abandoned a few months after taking office. The next day Steven Horwitz published a Cato Briefing Paper called \”Herbert Hoover: Father of the New Deal,\”  with a broader treatment of the actual Herbert Hoover. Here are some tastes of the Horwitz argument (footnotes and citations omitted):
\”The version of Hoover presented in the media’s narrative of Hoover as champion of laissez faire bears little resemblance to the details of Hoover’s life, the ideas he held, and the policies he adopted as president. …\”
\”Hoover had long believed that it was necessary to `transform the structure of the U.S. economy from one of laissez-faire to one of voluntary cooperation.\’ In her biography Herbert Hoover: Forgotten Progressive Joan Hoff Wilson summarizes Hoover’s economic views this way:

Where the classical economists like Adam Smith had argued for uncontrolled competition between independent  economic units guided only by the invisible hand of supply and demand, he talked about voluntary national economic planning arising from cooperation between business interests and the government. . . . Instead of negative government action in times of depression, he advocated the expansion of public works, avoidance of wage cuts, increased rather than decreased production—measures that would expand rather than contract purchasing power.

Hoover was also a long-time critic of international free trade, and favored `increased inheritance taxes, public dams, and, significantly, government regulation of the stock market.\’”
Horwitz provides chapter and verse on how Hoover, as president, increased spending and intervened in the economy. Here\’s an editorial cartoon from 1930 criticizing Hoover for his flood of increased spending. 
As Horwitz points out, leading intellectuals of the Roosevelt administration recognized that Hoover had set the stage for their policies:

\”Rexford G. Tugwell, one of the academics at the center of FDR’s `brains trust\’ said: `When it was all over, I once made a list of New Deal ventures begun during Hoover’s years as Secretary of Commerce and then as president. . . . The New Deal owed much to what he had begun.\’ Another member of the brains trust, Raymond Moley, wrote of that period: 

When we all burst into Washington . . . we found every essential idea [of the New Deal] enacted in the 100-day Congress in the Hoover administration itself. The essentials of the NRA [National Recovery Administration], the PWA [Public Works Administration], the emergency relief setup were all there. Even the AAA [Agricultural Adjustment Act] was known to the Department of Agriculture. Only the TVA and the Securities Act was drawn from other sources. The RFC [Reconstruction Finance Corporation], probably the greatest recovery agency, was of course a Hoover measure, passed long before the inauguration.

Late in both of their lives, Tugwell wrote to Moley and said of Hoover, “we were too hard on a man who really invented most of the devices we used.\”
Horwitz argues that Hoover\’s economic policies were deeply misguided. My point here is not to endorse his evaluation of Hoover\’s policies (I think some were more justifiable than others), but just to point out that as a matter of historical fact, it is incorrect to think of Hoover as a radical free market and budget balancer whose policies were overturned by FDR. Indeed, as Horwitz points out, FDR and others saw Hoover during the 1920s as a possible presidential candidate for the Democrats!
Thanks to Arnold Kling at the EconLog website for the pointer.