These are times where policy coordination between central banks and fiscal authorities seems to be particularly welcome. For one, monetary policy, which seems to be the only sustained and coherent policy, cannot right the ship beyond the short term, and the short term is shorter than the current crisis. For two, fiscal authorities are completely stuck in political wars exactly at the wrong moment. Upcoming elections in Europe and the United States certainly do not help in that. Central bankers have been rather frustrated with the political climate, yet they are still willing scape goats to deflect the furor of the public about unpopular policies.
But sometimes, enough is enough. One such case has been the open criticism of the central banker of Cyprus, who railed against the ineptitude of its government which has completely ignored his advice. Cyprus may not seem a big deal, yet it is a major banking center that may go down with Greece depending on how things unravel there. And this central banker, whose mandate was not renewed, is also not a nobody, as he was previously a senior official at the Board of Governors of the US Fed.
In probably his last paper while in Cyprus, Athanasios Orphanides summarizes all what is wrong with central banking in Europe (Cyprus is part of the monetary union). He recognizes that banking supervision must be taken much more seriously by central bankers, as the stability mandate that was typically meant for prices and sometimes employment or output is now interpreted to include the financial sector as well. Of course, this implies that central banks need to take more responsibilities in supervising the financial all the way to regulating individual institutions, an authority they do not always have at this point. But foremost, Orphanides argues that the biggest liability is economic governance. This is especially important within a monetary union where several governments need to agree. A more uniform fiscal policy would help tremendously, especially when monetary policy, in its more rudimentary form, is applied uniformly across the union. Worse, problems from fiscal policies that are not sustainable in the long term are magnified in a monetary union. You need rules and you need to adhere to them. Politicians are rather bad at this. Central bankers much better.
Showing posts with label macroeconomics. Show all posts
Showing posts with label macroeconomics. Show all posts
Do people know what the Taylor Rule is?
The current doctrine in monetary policy is that central bank need to be very clear about their policy rule so that economic agents can form good expectations about the future path of interest rates and inflation. Whether this communication policy can be questioned, at least from anecdotal evidence, as many people are currently convinced that inflation is currently close to double digits and we are heading towards hyperinflation. But that is only anecdotal. There is better evidence, from the Michigan Survey on Consumers, which ask questions about expectations of future economic conditions.
Carlos Carvalho and Fernanda Nechio ask whether those expectations are consistent with the Taylor Rule that underlies much of monetary policy (at least when the nominal interest is not bound by zero). It turns out that by and large, they are, expect for those with lower education. Surprisingly, the Survey of Professional Forecasters yields less consistent predictions of interest rates and inflation, as if those professional were not believing in the Taylor Rule. It is rather puzzling that the public knows better the monetary policy than the professionals, or is it that the Fed manages to fool the general public, but not the forecasters?
Carlos Carvalho and Fernanda Nechio ask whether those expectations are consistent with the Taylor Rule that underlies much of monetary policy (at least when the nominal interest is not bound by zero). It turns out that by and large, they are, expect for those with lower education. Surprisingly, the Survey of Professional Forecasters yields less consistent predictions of interest rates and inflation, as if those professional were not believing in the Taylor Rule. It is rather puzzling that the public knows better the monetary policy than the professionals, or is it that the Fed manages to fool the general public, but not the forecasters?
The perpetual lag of macroeconomics teaching
When it comes to teaching, nobody likes revamping lecture notes and reforming a curriculum. This is especially true when one is oneself not really conversant in the new material. While I think a Economics PhD should be able to teach almost any undergraduate Economics class, one is still drawn to the path of least resistance and teach only what one knows, even when this is outdated. One consequence of this is that undergraduates get to learn what the profession discredited sometimes decades ago. Nowhere is that more true than in Macroeconomics, which went through a transformation in 1970's and 1980's that to a large extend shelved IS/LM, yet the latter is still the core of undergraduate teaching. The fact that those teaching this today were taught IS/LM is the prime reason, and the textbook writers accommodate this.
Some have called current macroeconomic theory wrong with the current crisis and thus there would be the need to a change in research paradigm and thus also teaching. I am not sure about this claim, I would rather call macroeconomic research before the crisis incomplete rather than wrong. As to the teaching reform, that will take ages. One way to the someway fix the broken IS/LM model to make it more amenable to current events, like Peter Bofinger tries by introducing involuntary unemployment that does not necessarily come from wage rigidity. There have been other such attempts, but frankly, they just make the model even less believable and impossible to teach. The true reform should be to drop IS/LM entirely from the undergraduate classroom, except for History of Economics classes.
Some have called current macroeconomic theory wrong with the current crisis and thus there would be the need to a change in research paradigm and thus also teaching. I am not sure about this claim, I would rather call macroeconomic research before the crisis incomplete rather than wrong. As to the teaching reform, that will take ages. One way to the someway fix the broken IS/LM model to make it more amenable to current events, like Peter Bofinger tries by introducing involuntary unemployment that does not necessarily come from wage rigidity. There have been other such attempts, but frankly, they just make the model even less believable and impossible to teach. The true reform should be to drop IS/LM entirely from the undergraduate classroom, except for History of Economics classes.
The cost of US fiscal imbalance
It is obvious that the US government is currently spend more than normal. It is also obvious that the current level of deficits is not sustainable. But just how bad would it be if the current fiscal imbalance would be maintained? We have models that can calculate welfare costs of such policies, but because the current policy is not sustainable, it is impossible to solve them and get a number. The only solution we can have is to look at what it would cost to delay going back to a sustainable path.
Bertrand Gruss and José Torres do with a heterogeneous agent DSGE model. According to their results, postponing the return to a sustainable path (defined by a pre-crisis debt/GDP ratio) by two decades leads to a permanent loss of output of 17% and a consumption equivalence loss of 7%. That is gigantic. The losses come mostly from the long run, thus it is all about whether the short-term gain is worth the long-term cost. To understand this result, it is thus important to understand the model.
This is a model of occupational choice (entrepreneur/worker), with idiosyncratic employment risk, no borrowing at the individual level, distortionary taxation and lump sum government transfers. There is another public good, wasteful government spending. A major role of the government is thus to insure agents against shocks, which they can also self-insure with accumulating Treasury bonds. Everybody knows exactly the path of policy. There is no aggregate shock except for fiscal policy. To summarize, the only beneficial thing the government does is insure people against shocks, to some extend. Otherwise, the government is harmful: it takes away goods to destroy them and distorts household choices in adverse ways to finance this. It is then no surprise that almost any government spending is harmful, no matter what the circumstances. In particular, the fact that there could be, for example, a temporarily very high unemployment rate that justifies larger public expenses is ignored here.
In other words, the model ignores the potential benefits of current deficits. Not very useful.
Bertrand Gruss and José Torres do with a heterogeneous agent DSGE model. According to their results, postponing the return to a sustainable path (defined by a pre-crisis debt/GDP ratio) by two decades leads to a permanent loss of output of 17% and a consumption equivalence loss of 7%. That is gigantic. The losses come mostly from the long run, thus it is all about whether the short-term gain is worth the long-term cost. To understand this result, it is thus important to understand the model.
This is a model of occupational choice (entrepreneur/worker), with idiosyncratic employment risk, no borrowing at the individual level, distortionary taxation and lump sum government transfers. There is another public good, wasteful government spending. A major role of the government is thus to insure agents against shocks, which they can also self-insure with accumulating Treasury bonds. Everybody knows exactly the path of policy. There is no aggregate shock except for fiscal policy. To summarize, the only beneficial thing the government does is insure people against shocks, to some extend. Otherwise, the government is harmful: it takes away goods to destroy them and distorts household choices in adverse ways to finance this. It is then no surprise that almost any government spending is harmful, no matter what the circumstances. In particular, the fact that there could be, for example, a temporarily very high unemployment rate that justifies larger public expenses is ignored here.
In other words, the model ignores the potential benefits of current deficits. Not very useful.
I do not understand US policy
The current situation in the US can be summarized in the following way: the economy is growing again, although not yet as fast as steady state, and unemployment is still high. Most sectors are doing kind of OK except for the construction sector, which operates roughly at half capacity. Budgets deficits are very high, but not at record level once you factor in cyclical effects. Inflation is moderate and on target around 2%, including its expectations. Everyone is sitting on a lot of cash and nominal interest rates are minimal. The crisis has been going on since 1997, 4.5 years.
What is the Federal Reserve doing? Keep in mind that it cannot address structural issues in the economy and cannot only boost the economy in the short term, if at all. Bernanke and co. are keeping interest rates rock bottom until at least 2014. That would be seven years of emergency measures. If you want to instill some confidence in the economy, you do not go about telling everyone the economy needs to stay in the emergency room three more years.
And by the way, if inflation is targeted at 2% and nominal interest rates are at zero for the foreseeable future, that means real interest rates are negative. Take any model and throw in negative real interest rates. The result are pretty ugly, especially if this is more than temporary. Yet this is what the Fed seems to be advocating.
And why would you need such low interest rates? A Taylor rule would call for low interest rates if inflation (or inflation expectations) are too high (correction: too low). They are not. Or if output is below potential. That may well be the case, but I do not think it is to the extend that the Fed believes it is. The rhetoric coming from the Board indicates that the potential output is simply a continuation of the trend line from before the crisis. I do not think it is adequate. The construction sector is gone, and is going to be gone for a while because of an oversupply of residences and structures. Most households suffered a significant wealth shock that is not going to recuperate soon, and consumption has shifted down. Long time unemployed are simply not employable because of sectoral reallocation. Potential GDP has suffered a permanent shock, and while it will get back to the usual trend growth, it will not get back of the previous path.
For the Fed, this means that it is currently chasing a target it will never be able to reach. Its estimate of potential GDP is much too excessive. And the difference is due to structural issues the Fed does not have the means to address.
Which brings us to fiscal policy. Temporary tax cuts of various sorts are good to address temporary weaknesses in consumption. They work best when targeted towards people with high propensities to consume. These are the poor, and more generally the liquidity constrained. These are not the rich, and certainly not everyone. And if the loss in consumption is permanent, then this cannot be address with such temporary measures. You just have to accept it and live with it. Thus: taxes need to go back up, especially for the rich, also because they got an unnecessary free ride in the past years.
And then there is the sectoral problem. Construction is in the dumps. If you want to do something about it, you target public spending towards construction. Not general tax cuts, not across the board stimulus. And the US could actually need some serious infrastructure replacement and improvements. Actually, it is the perfect time to catch up on lost time here: costs are low, interest rates are low.
Now there is of course the stimulus package. But it has had no impact because it was not sufficiently targeted towards infrastructure, It went to state governments, which just used this manna to avoid getting into debt. It went into all sort of pet projects, very few of which had anything to do with construction. And if there was some construction, it went into initiatives that have such long horizons that they are not going to help anytime soon.
So what needs to be done? Washington needs to acknowledge that the targeted path is too ambitious. Bring interest rates back up, This will entice people and businesses to do something with all the cash they are sitting on. The US Treasury needs to focus on infrastructure spending and restructure tax rates. And do not tell me we first have to wait until the presidential election is over.
What is the Federal Reserve doing? Keep in mind that it cannot address structural issues in the economy and cannot only boost the economy in the short term, if at all. Bernanke and co. are keeping interest rates rock bottom until at least 2014. That would be seven years of emergency measures. If you want to instill some confidence in the economy, you do not go about telling everyone the economy needs to stay in the emergency room three more years.
And by the way, if inflation is targeted at 2% and nominal interest rates are at zero for the foreseeable future, that means real interest rates are negative. Take any model and throw in negative real interest rates. The result are pretty ugly, especially if this is more than temporary. Yet this is what the Fed seems to be advocating.
And why would you need such low interest rates? A Taylor rule would call for low interest rates if inflation (or inflation expectations) are too high (correction: too low). They are not. Or if output is below potential. That may well be the case, but I do not think it is to the extend that the Fed believes it is. The rhetoric coming from the Board indicates that the potential output is simply a continuation of the trend line from before the crisis. I do not think it is adequate. The construction sector is gone, and is going to be gone for a while because of an oversupply of residences and structures. Most households suffered a significant wealth shock that is not going to recuperate soon, and consumption has shifted down. Long time unemployed are simply not employable because of sectoral reallocation. Potential GDP has suffered a permanent shock, and while it will get back to the usual trend growth, it will not get back of the previous path.
For the Fed, this means that it is currently chasing a target it will never be able to reach. Its estimate of potential GDP is much too excessive. And the difference is due to structural issues the Fed does not have the means to address.
Which brings us to fiscal policy. Temporary tax cuts of various sorts are good to address temporary weaknesses in consumption. They work best when targeted towards people with high propensities to consume. These are the poor, and more generally the liquidity constrained. These are not the rich, and certainly not everyone. And if the loss in consumption is permanent, then this cannot be address with such temporary measures. You just have to accept it and live with it. Thus: taxes need to go back up, especially for the rich, also because they got an unnecessary free ride in the past years.
And then there is the sectoral problem. Construction is in the dumps. If you want to do something about it, you target public spending towards construction. Not general tax cuts, not across the board stimulus. And the US could actually need some serious infrastructure replacement and improvements. Actually, it is the perfect time to catch up on lost time here: costs are low, interest rates are low.
Now there is of course the stimulus package. But it has had no impact because it was not sufficiently targeted towards infrastructure, It went to state governments, which just used this manna to avoid getting into debt. It went into all sort of pet projects, very few of which had anything to do with construction. And if there was some construction, it went into initiatives that have such long horizons that they are not going to help anytime soon.
So what needs to be done? Washington needs to acknowledge that the targeted path is too ambitious. Bring interest rates back up, This will entice people and businesses to do something with all the cash they are sitting on. The US Treasury needs to focus on infrastructure spending and restructure tax rates. And do not tell me we first have to wait until the presidential election is over.
Economics and facts
I have sometimes expressed here my frustration over the disconnection between research and reality. The scientific process is about trying to explain some data. Any paper that just tries to see what could result from a model without looking at data or restrict parameter value in any way is useless. What do we learn if a model tells us anything could happen with some parameter values, but the authors are not capable of telling us in which range those parameter values lie? And what use is a model that is not, or worse cannot, be tested in any way?
Harald Uhlig opines on the relationship of Economics and reality from four different angles. The first is Economics as a science, where he has largely the same arguments as me above. Economics is also an art, as it is vain to find a great unified theory of Economics, as life is too complicated. One can only hope to explain observations in batches, and then the most elegant theory wins. But that theory still has to be tested against data, at least for the observations at hand.
Economics is also rhetoric. Indeed, convincing others is a big part of the success of a theory, and how that theory does with explaining the data is unfortunately not always central. This competition of ideas also spills over into politics, as Economics is in the end about giving policy advice. And this is where data and empirical relevance becomes the least important.
Uhlig then goes on to relate this to various aspects of macroeconomics. While there is much introspection in macroeconomics these days, I wish he would have defined Economics to be broader than that. Some areas of Economics need indeed to be much more closely related to data and trying to explain empirical observations. Game theory would be a prime example. public economic theory as well, if not much of microeconomic theory. Mainstream macroeconomic theory has always tried to relate to data, which is probably why it has changed over the decades: some crucial facts have changed.
Harald Uhlig opines on the relationship of Economics and reality from four different angles. The first is Economics as a science, where he has largely the same arguments as me above. Economics is also an art, as it is vain to find a great unified theory of Economics, as life is too complicated. One can only hope to explain observations in batches, and then the most elegant theory wins. But that theory still has to be tested against data, at least for the observations at hand.
Economics is also rhetoric. Indeed, convincing others is a big part of the success of a theory, and how that theory does with explaining the data is unfortunately not always central. This competition of ideas also spills over into politics, as Economics is in the end about giving policy advice. And this is where data and empirical relevance becomes the least important.
Uhlig then goes on to relate this to various aspects of macroeconomics. While there is much introspection in macroeconomics these days, I wish he would have defined Economics to be broader than that. Some areas of Economics need indeed to be much more closely related to data and trying to explain empirical observations. Game theory would be a prime example. public economic theory as well, if not much of microeconomic theory. Mainstream macroeconomic theory has always tried to relate to data, which is probably why it has changed over the decades: some crucial facts have changed.
On the ineffectiveness of a fiscal stimulus
When is a fiscal stimulus going to work? If you listen to economists these days, it would be difficult to know. One reason is that protagonists quickly become sidetracked by the associated political discourse. The other is that one would first need to define the fiscal stimulus. Depending on whether it is provided by tax rebates, public expenses or tax delays makes a big difference. Also, who is targeted matters a lot. Thus one needs to get the specifics of the fiscal stimulus to give a proper answer. The general rule, though, is that a fiscal stimulus works best if the credit or liquidity constraint households obtain additional cash. They are going to spend it right away. The other households would reduce consumption only slightly in anticipation of future increased taxes due to a wealth effect. In the aggregate, consumption would then go up, but not a lot. But there can be other circumstances where it would work better.
Thorsten Drautzburg and Harald Uhlig study a situation similar to the one now in the Unites States: nominal interest rates getting very close to zero. Then, they claim the fiscal multipliers are still rather small, but may be positive despite distortionary taxation. Now contrast this with the results of Lawrence Christiano, Martin Eichebaum and Sergio Rebelo, who argue that the fiscal multipliers become very large (and positive) when nominal interest rates are close to zero. Who is to believe? Both use a rather elaborate DSGE model, in both cases estimated. Both use the Calvo fairy. Or a Taylor rule. The first has financial frictions, while the second has investment adjustment costs, which should come to the same. If anybody can figure out why the results are so different, I would appreciate it.
It particular it would be interesting to understand why now would now be the wrong time to institute an austerity regime. To me, it would even make perfect business sense: why not build infrastructure when the cost in terms of financing and labor are low? Keep in mind that every unemployed worker that is hired does not need unemployment benefits...
Thorsten Drautzburg and Harald Uhlig study a situation similar to the one now in the Unites States: nominal interest rates getting very close to zero. Then, they claim the fiscal multipliers are still rather small, but may be positive despite distortionary taxation. Now contrast this with the results of Lawrence Christiano, Martin Eichebaum and Sergio Rebelo, who argue that the fiscal multipliers become very large (and positive) when nominal interest rates are close to zero. Who is to believe? Both use a rather elaborate DSGE model, in both cases estimated. Both use the Calvo fairy. Or a Taylor rule. The first has financial frictions, while the second has investment adjustment costs, which should come to the same. If anybody can figure out why the results are so different, I would appreciate it.
It particular it would be interesting to understand why now would now be the wrong time to institute an austerity regime. To me, it would even make perfect business sense: why not build infrastructure when the cost in terms of financing and labor are low? Keep in mind that every unemployed worker that is hired does not need unemployment benefits...
Meta-analyzing the price puzzle
Meta-analysis is the analysis of the literature on, say, the estimate of a particular elasticity. This is common in medical studies, where each individual study has usually little statistical significance, but aggregating them may give the results more power. In Economics, there are few meta-analyses (although there is a society on the topic) as study samples are statistically much more sound and each study takes so much time that there is little incentive to do a lot o the same topic. Yet, this happens for some themes.
One such theme is the price puzzle: many vector-autoregression models show that a monetary contraction is immediately followed by a rise in the price level, which is rather counter-intuitive. Marek Rusnák, Tomáš Havránek and Roman Horváth found 70 articles from 31 countries providing 210 estimates of the response at five horizons. Can one then simply do a statistical analysis on these estimates? That is not so easy, as there may be a publication bias. As the puzzle is now well documented, journal editors are not particularly interested in studies that demonstrate it again. The authors claim that there is such a bias, but I have to confess I do not understand how they come to that conclusion.
The price puzzle is on average present, and prices eventually decrease as suggested but all theories. But there is substantial variance in the results, which the authors show can be explained by what variables are included or what variant of a vector-autoregression is run. This unfortunately confirms my frustration with this field: there is a dizzying array of methods and specifications that yield different results, and it is impossible to tell which one is right. Maybe we need a bit more theory to discipline this.
One such theme is the price puzzle: many vector-autoregression models show that a monetary contraction is immediately followed by a rise in the price level, which is rather counter-intuitive. Marek Rusnák, Tomáš Havránek and Roman Horváth found 70 articles from 31 countries providing 210 estimates of the response at five horizons. Can one then simply do a statistical analysis on these estimates? That is not so easy, as there may be a publication bias. As the puzzle is now well documented, journal editors are not particularly interested in studies that demonstrate it again. The authors claim that there is such a bias, but I have to confess I do not understand how they come to that conclusion.
The price puzzle is on average present, and prices eventually decrease as suggested but all theories. But there is substantial variance in the results, which the authors show can be explained by what variables are included or what variant of a vector-autoregression is run. This unfortunately confirms my frustration with this field: there is a dizzying array of methods and specifications that yield different results, and it is impossible to tell which one is right. Maybe we need a bit more theory to discipline this.
No convergence in the Caribbean
I have always found the Caribbean fascinating because it is a microcosm of the world, with tiny countries trying to get a workable government without the economies of scale the rest of the world enjoys. But as a readers of Economics research, the presence of this myriad of too-small countries lead to many frustrations, as they bias results in cross-country regressions. But sometimes, these micro-countries can be useful for research.
Roland Craigwell and Alain Maurin use them to study whether there is convergence in the Caribbean. It is well established that there is no convergence on world-wide country data, but it is very visible on subsets, such as US states. In the later case, all US states are under the same currency and roughly the same laws and government systems, there is some cross-state redistribution and no trade barriers. As you drop these features, which one gets you lack of convergence. In the case of the Caribbean, there is a partial monetary and trade union, laws and governments are more dissimilar than in the US and there is no redistribution. And as Craigwell and Maurin show, that is sufficient to make convergence disappear. Once more, it looks like once more institutions and to a lesser extent globalization are the keys to development for the poorest economies.
Roland Craigwell and Alain Maurin use them to study whether there is convergence in the Caribbean. It is well established that there is no convergence on world-wide country data, but it is very visible on subsets, such as US states. In the later case, all US states are under the same currency and roughly the same laws and government systems, there is some cross-state redistribution and no trade barriers. As you drop these features, which one gets you lack of convergence. In the case of the Caribbean, there is a partial monetary and trade union, laws and governments are more dissimilar than in the US and there is no redistribution. And as Craigwell and Maurin show, that is sufficient to make convergence disappear. Once more, it looks like once more institutions and to a lesser extent globalization are the keys to development for the poorest economies.
Monetary and fiscal policy cooperation in a liquidity trap
We are living interesting times in terms of macroeconomic policy: the world faces big shocks and substantial challenges, and many current circumstances have no historical precedents. This means that policy makers cannot draw from experience and need to invent new policies from somewhere better than their guts. And after a few hesitations, theory is now in much better shape to answer questions from policy makers. For example, what should one do when there is a liquidity trap in a globalized economy, especially if the trap itself is globalized?
David Cook and Michael Devereux show how, and it borders on a political miracle. Not only does one need to get the cooperation of fiscal and monetary authorities (something the US is not close to achieving) but one needs the cooperation across countries even if it entails some costs to the "winners" (something the Chinese have so far refused and the Swiss recently abandoned).
Specifically, Cook and Devereux show that with so many countries currently with negative real interest rates, we have a worldwide liquidity trap. In an open economy, the policy prescription differs from a closed economy. If there is a negative demand shock, fiscal policy needs of course to raise aggregate demand, but with a global economy, this can come from anywhere in the world and thus a coordinated fiscal policy is due. But to channel the impulse to the relevant countries, monetary policy coordination is necessary to raise interest rates in the foreign countries, even if they are in a liquidity trap. And this takes some serious courage. One can always dream.
David Cook and Michael Devereux show how, and it borders on a political miracle. Not only does one need to get the cooperation of fiscal and monetary authorities (something the US is not close to achieving) but one needs the cooperation across countries even if it entails some costs to the "winners" (something the Chinese have so far refused and the Swiss recently abandoned).
Specifically, Cook and Devereux show that with so many countries currently with negative real interest rates, we have a worldwide liquidity trap. In an open economy, the policy prescription differs from a closed economy. If there is a negative demand shock, fiscal policy needs of course to raise aggregate demand, but with a global economy, this can come from anywhere in the world and thus a coordinated fiscal policy is due. But to channel the impulse to the relevant countries, monetary policy coordination is necessary to raise interest rates in the foreign countries, even if they are in a liquidity trap. And this takes some serious courage. One can always dream.
Public consumption and the business cycle
One aspect of government purchases the current crisis has highlighted is how volatile they can be. Quite obviously, they are influenced by politics, to the point of complete reversal between massive spending and severe belt-tightening within months as in the US and the UK. But there could also be a more systematic component that is linked to the business cycle. After all, the government may be trying to improve the welfare of its constituents and for example substitute public consumption for lacking private consumption, or the same for investment.
Ruediger Bachmann and Jinhui Bai look at this using an augmented real business cycle model. They claim that 25-40% of the variance of public consumption can be accounted for by shocks to total factor productivity once implementation lags and costs of public consumption, as well as taste shocks to public vs. private consumption. I am no particular fan of taste shocks, as they are the symptoms of a modeler who is giving up on trying to explain something and simply equates the error term in the Euler equation to a shock. Then much is driven by how this shock is calibrated, in this case to match a four year electoral cycle and some data moments. When I think about shocks in this context, I think indeed about who is in power to decide on public expenditures. But that is not completely exogenous. Indeed, the state of the economy has an impact on who gets elected or reelected. And this can be calibrated without trying to match the data moments one is trying to explain.
Ruediger Bachmann and Jinhui Bai look at this using an augmented real business cycle model. They claim that 25-40% of the variance of public consumption can be accounted for by shocks to total factor productivity once implementation lags and costs of public consumption, as well as taste shocks to public vs. private consumption. I am no particular fan of taste shocks, as they are the symptoms of a modeler who is giving up on trying to explain something and simply equates the error term in the Euler equation to a shock. Then much is driven by how this shock is calibrated, in this case to match a four year electoral cycle and some data moments. When I think about shocks in this context, I think indeed about who is in power to decide on public expenditures. But that is not completely exogenous. Indeed, the state of the economy has an impact on who gets elected or reelected. And this can be calibrated without trying to match the data moments one is trying to explain.
What if the US looses its reserve currency privilege?
Since the Bretton Woods agreement in 1945, the United States have enjoyed the so-called "Exhorbitant Privilege." During the fixed exchange rate regime, the US could conduct monetary policy without regard to what was happening in other countries. The US dollar was a reserve currency, which also helped the US maintain low interest rates and a guarantee that US dollars (and Treasury bonds) would always find a buyer. With flexible exchange rates, not much has changed. But with the recent shenanigans in a Congress that considered reneging on its debt, the likelihood of this advantage changing has dramatically increased. What would the consequences of the loss of the Exhorbitant Privilege be?
Wenli Cheng and Dingsheng Zhang study this scenario using a general equilibrium model where a peripheral country (say, the Asian economies) pegs its currency to the money of a central country (say, the United States), the latter being used as the vehicle currency for international trade. In addition, the foreign exchange reserves of the periphery are invested in government bonds of the center. This means that no matter what current account deficit of the center, it is always financed by the periphery. Yet the center may be tempted to inflate it away. This limitless and to some extend free borrowing is the Exhorbitant Privilege.
Now remove it by assuming that the periphery does not want to invest in the center, either because it views the Treasury bonds are excessively risky or because it does not peg to the dollar any more. This would lead to a dramatic readjustment of the terms of trade to favor the tradable sector of the center. This decpraciation of the dollar would be more pronounced of the center is incapable of raising taxes and finances its debt with inflation. This already all sounds familiar.
Wenli Cheng and Dingsheng Zhang study this scenario using a general equilibrium model where a peripheral country (say, the Asian economies) pegs its currency to the money of a central country (say, the United States), the latter being used as the vehicle currency for international trade. In addition, the foreign exchange reserves of the periphery are invested in government bonds of the center. This means that no matter what current account deficit of the center, it is always financed by the periphery. Yet the center may be tempted to inflate it away. This limitless and to some extend free borrowing is the Exhorbitant Privilege.
Now remove it by assuming that the periphery does not want to invest in the center, either because it views the Treasury bonds are excessively risky or because it does not peg to the dollar any more. This would lead to a dramatic readjustment of the terms of trade to favor the tradable sector of the center. This decpraciation of the dollar would be more pronounced of the center is incapable of raising taxes and finances its debt with inflation. This already all sounds familiar.
Policy risk and the business cycle
The US economy seems stuck in its tracks, and many blame uncertainty about future public policy, including me. Indeed, private firms are currently sitting on a lot of cash and are making very good profits, yet they are not investing or hiring. This really looks like a wait-and-see game. But it this justification well-founded or is it just a cheap excuse to justify higher than usual profits in the face of high unemployment?
Benjamin Born and Johannes Pfeifer put some structure into these arguments by taking a standard New Keynesian model and adding uncertainty about monetary and fiscal policy. They measure this by looking at tax rates and monetary policy shocks with time-varying volatility. Previous literature already looked at the impact of aggregate uncertainty, which policy makers can do little about. But policy uncertainty is another matter. And there is hope, as Born and Pfeifer show that the impact of policy uncertainty is not that important (but much larger than uncertainty about productivity shocks) thanks to monetary policy reaction through a Taylor Rule. So that is somewhat reassuring, but then the size of the current policy uncertainty is an order of magnitude larger than when this paper was written, and monetary policy is bound by non-negative nominal interest rates.
Benjamin Born and Johannes Pfeifer put some structure into these arguments by taking a standard New Keynesian model and adding uncertainty about monetary and fiscal policy. They measure this by looking at tax rates and monetary policy shocks with time-varying volatility. Previous literature already looked at the impact of aggregate uncertainty, which policy makers can do little about. But policy uncertainty is another matter. And there is hope, as Born and Pfeifer show that the impact of policy uncertainty is not that important (but much larger than uncertainty about productivity shocks) thanks to monetary policy reaction through a Taylor Rule. So that is somewhat reassuring, but then the size of the current policy uncertainty is an order of magnitude larger than when this paper was written, and monetary policy is bound by non-negative nominal interest rates.
Razor innovation in macroeconomics
Macroeconomics is sometimes like Gillette razors. There is regularly an innovative razor that happens to have more blades than the previous one. And once it gets out of hand, the new razor goes back to fundamentals and has only one blade, before the cycle starts again. In macroeconomics, there was this fad of adding more an more shocks to models until everything became very confusing and unidentifiable. So we returned to simple models (Occam's razor was the innovation) that became more powerful because of the presence of a market friction. Now, these search frictions are appearing everywhere, one-by-one or in pairs, and the latest generation of models has three frictions.
In a pair of papers, Etienne Wasmer alone and then with Nicolas Petrosky-Nadeau introduces search frictions on labor, credit and goods markets. The first is more of an exercise of style, showing it can be elegantly solved in steady-state thanks to block-recursiveness. The second paper is more interesting, as it looks at the dynamic properties of the model and shows that is can better account for the persistence of fluctuations in the data (what frictions are good at) and the volatility of labor flows. Interesting results, especially in the light of the pronounced lag in the recovery of employment in the US these days.
I am waiting for the four-friction model now.
In a pair of papers, Etienne Wasmer alone and then with Nicolas Petrosky-Nadeau introduces search frictions on labor, credit and goods markets. The first is more of an exercise of style, showing it can be elegantly solved in steady-state thanks to block-recursiveness. The second paper is more interesting, as it looks at the dynamic properties of the model and shows that is can better account for the persistence of fluctuations in the data (what frictions are good at) and the volatility of labor flows. Interesting results, especially in the light of the pronounced lag in the recovery of employment in the US these days.
I am waiting for the four-friction model now.
The welfare gain from inflation targeting
It is rather well accepted that transparency is preferred for policy, because it anchors better expectations, people generally do not like uncertainty, and discretion can lead to adverse biases compared to set policy rules. Yet, the United States exhibit little transparancy, with the Federal Reserve being one of the few western central banks not to declare some explicit policy target, and fiscal policy being as uncertain as ever. That would not be a big deal if the welfare costs were low, but you can think that there are high and in the case of fiscal policy are currenctly holding back the recovery.
Giorgio Di Giorgio and Guido Traficante are taking a closer look at the welfare benefits of inflation targeting. For this they use a model where households observe policy interest rates and do not know whether their changes are due to reactions to output gaps or shocks to the inflation target. Households are sophisticated, they use a signal extraction device to estimate the latent, unobservable variable. Yet, they still face substantial costs from the uncertainty. Money is not neutral because of Rotemberg pricing, a variant of Calvo pricing. Oh well, I guess this is what you need to do to get a result with some bite.
Households know there is a policy rule that determines the interest rate from the output gap (unobservable) and the inflation target (stochastic and persistent) as well as known preference and cost-push shocks. In other words, households know a lot about the structure of the economy and the shocks, except for the policy shock, but then somehow cannot figure out what the output gap is. The central bank can, though, but then has for obscure reasons a trembling hand when it comes to set its inflation target. That seems to be quite the opposite of what I would have thought: everyone is confused about the output gap, and only the central bank knows what the inflation target is. Instead of a story of households trying to disentangle output gap and inflation target from the interest rate signal, one would have a story of a central banker not quite sure what to do given the circumstances. Too bad, this could have been an interesting paper.
Giorgio Di Giorgio and Guido Traficante are taking a closer look at the welfare benefits of inflation targeting. For this they use a model where households observe policy interest rates and do not know whether their changes are due to reactions to output gaps or shocks to the inflation target. Households are sophisticated, they use a signal extraction device to estimate the latent, unobservable variable. Yet, they still face substantial costs from the uncertainty. Money is not neutral because of Rotemberg pricing, a variant of Calvo pricing. Oh well, I guess this is what you need to do to get a result with some bite.
Households know there is a policy rule that determines the interest rate from the output gap (unobservable) and the inflation target (stochastic and persistent) as well as known preference and cost-push shocks. In other words, households know a lot about the structure of the economy and the shocks, except for the policy shock, but then somehow cannot figure out what the output gap is. The central bank can, though, but then has for obscure reasons a trembling hand when it comes to set its inflation target. That seems to be quite the opposite of what I would have thought: everyone is confused about the output gap, and only the central bank knows what the inflation target is. Instead of a story of households trying to disentangle output gap and inflation target from the interest rate signal, one would have a story of a central banker not quite sure what to do given the circumstances. Too bad, this could have been an interesting paper.
Do not waste degrees of freedom with macro data
Dealing with microdata is relatively easy, as you have plenty of data points and can freely add explanatory variables with running the risk of running out of degrees of freedom. The story is different for macrodata, as series are much shorter, and one can quickly eat degrees of freedom by using lagged variables. The prime example here are the often abused vector autoregressions (VAR), that get larger and larger, and faster than new data points accumulate. The latest fad is to run regressions with time varying parameters, including in VARs, which is deadly for degrees of freedom as this is roughly equivalent to adding a boatload of dummy variables to the mix. Hence the need to be more parsimonious.
How parsimonious should one be? Joshua Chan, Gary Koop, Roberto Leon-Gonzalez and Rodney Strachan think the solution is in time-varying parsimony. The idea is that sometimes one needs a more complex model, and sometimes a few variables are sufficient. While this allows to spare degrees of freedom when one can do with few variables, this gain on paper is lost, and probably more than lost, by the implicit degrees of freedom used in selecting the right model. This is an old problem than is swept under the rug is many empirical applications, but in this case it becomes even more apparent because so many parameters and models are involved.
How parsimonious should one be? Joshua Chan, Gary Koop, Roberto Leon-Gonzalez and Rodney Strachan think the solution is in time-varying parsimony. The idea is that sometimes one needs a more complex model, and sometimes a few variables are sufficient. While this allows to spare degrees of freedom when one can do with few variables, this gain on paper is lost, and probably more than lost, by the implicit degrees of freedom used in selecting the right model. This is an old problem than is swept under the rug is many empirical applications, but in this case it becomes even more apparent because so many parameters and models are involved.
What is a sticky price?
An amazing amount of scholarly effort is devoted to figuring out optimal stabilization policies in developed economies. I am not convinced this effort is well-placed, as fluctuations in developing economies are much larger and long-term trends quickly swamp short-term fluctuations in welfare assessment for developed economies. The last recession in the US may make it worth to look at stabilization though.
Greg Mankiw and Matthew Weinzierl have a piece of rather pedagogical nature trying to convince us that stabilization policy is worthwhile. Their model is essentially the one that is taught to undergraduates: a two-period model with households maximizing intertemporal utility from consumption, a government, and firms that maximize discounted profits. Oddly, firms do not care about the resale value of capital in the second period, which makes investment largely irrelevant. Finally, prices are fixed the first period, but can be changed in the second period.
Beyond the pedagogical merit, can this model be used for serious policy prescriptions, which Mankiw and Weinzierl even quantify? For one, the last recession was sufficiently important that prices and wages actually adjusted down in the short term, which violates the critical premise of the model. Indeed, all what policy tries to do is undo the frictions stemming from price rigidity. Second, when prices do indeed not change in the short-term, it is presumably when it is not worth doing do so, thus policy intervention also does not seem worth it. Of course, it could be that there is a genuine Keynesian lack of demand, but this can be attacked best by dealing with what causes the lack of demand, not by creating artificial demand through government expenses. For the last recession, this would have been easing collateral constraints. Third, the model assumes a money quantity equation, which imposes a constant money velocity. I thought we all had agreed long ago this was a silly assumption.
I really do not understand the point of this paper. After all, as Mankiw likes to say on his blog, all this can already be found in his favorite textbook.
Greg Mankiw and Matthew Weinzierl have a piece of rather pedagogical nature trying to convince us that stabilization policy is worthwhile. Their model is essentially the one that is taught to undergraduates: a two-period model with households maximizing intertemporal utility from consumption, a government, and firms that maximize discounted profits. Oddly, firms do not care about the resale value of capital in the second period, which makes investment largely irrelevant. Finally, prices are fixed the first period, but can be changed in the second period.
Beyond the pedagogical merit, can this model be used for serious policy prescriptions, which Mankiw and Weinzierl even quantify? For one, the last recession was sufficiently important that prices and wages actually adjusted down in the short term, which violates the critical premise of the model. Indeed, all what policy tries to do is undo the frictions stemming from price rigidity. Second, when prices do indeed not change in the short-term, it is presumably when it is not worth doing do so, thus policy intervention also does not seem worth it. Of course, it could be that there is a genuine Keynesian lack of demand, but this can be attacked best by dealing with what causes the lack of demand, not by creating artificial demand through government expenses. For the last recession, this would have been easing collateral constraints. Third, the model assumes a money quantity equation, which imposes a constant money velocity. I thought we all had agreed long ago this was a silly assumption.
I really do not understand the point of this paper. After all, as Mankiw likes to say on his blog, all this can already be found in his favorite textbook.
Socialist economies smooth better the cycle
Capitalism is often presented as a wild economic system where conditions are harsh as everyone fights for his survival. The fact that economic agents are not sheltered against shocks leads them to be more efficient and possibly protect themselves better against events. Incentives are not as well aligned in a socialist economy, as free-riding is more prevalent and weaker agents may be more likely to survive in such a sheltered system. The endless discussions on which system is better ultimately boil down to preferences about risk tolerance and fairness, and on which system offers higher welfare.
Bruno Amable and Karim Azizi point out that more socialist economies appear to be better at smoothing out business cycles in the aggregate. Indeed, they tend to adopt more readily Keynesian policies, which do smooth somewhat economic fluctuations, France being the prime example. But that does not yet mean these economies are better: while fluctuations are lesser, the average level may also be lower. And fluctuations may be optimal, as we have learned from the real business cycle literature. So the jury is still out.
Bruno Amable and Karim Azizi point out that more socialist economies appear to be better at smoothing out business cycles in the aggregate. Indeed, they tend to adopt more readily Keynesian policies, which do smooth somewhat economic fluctuations, France being the prime example. But that does not yet mean these economies are better: while fluctuations are lesser, the average level may also be lower. And fluctuations may be optimal, as we have learned from the real business cycle literature. So the jury is still out.
What is a macroeconomic model?
Critics have had a field day the past couple of years claiming that Economics is not up to the task because its models are too abstract. Macroeconomics has been especially affected because the trigger of the bandwagon was a macroeconomic event, the now Great Recession. I have discussed a few bad attempts at criticism, which were usually bad because ill-informed and because they could not offer any viable alternative.
The latest salvo comes from Hashem Pesaran and Ron Smith. They have several arguments. The first is that macroeconomic modeling of the DSGE brand insists too much on internal consistency and should allow more degrees of freedom to fit the data. Pesaran and Smith should first specify what the goal of the model is before criticizing the approach. If it is short-term forecasting, then go ahead with a purely statistical approach on macro data. If you want policy advice, you need something that withstands the Lucas Critique, and strong micro-foundations is then the way to go. But without a given purpose, any criticism is moot.
Pesaran and Smith, given their track record, are of course strong advocates of purely statistical methods. Throw every possible series in a regression, and see what sticks. I am not saying this cannot be useful, it allows to establish relationships in the data and I regularly report on such results, but this does not allow you to explain things. For this, you need some structure and theory provides you that. This brings me to the title of this post. There appears to be some disagreement about the meaning of the word "model." To me, model is a set of relationships established by theory that can then be used on data, for policy experiments, etc. For Pesaran and Smith, a model is a set of aggregate data series that are used in a statistical analysis of some kind (VAR, non-parametric, etc.). If we cannot agree what we are talking about, of course there will be endless and fruitless discussions.
For example, they are not the first to criticize DSGE models for failing to include housing, finance and the external sector. Well, models (the way I see them) are abstractions, and you do not want to include everything them, or you cannot understand, interpret or do something useful with. It is so across all sciences. You build a model to answer a particular question, and you give it the necessary bells and whistles. The fact that most DSGE models did not include housing and bank liquidity is not a failure of DSGE modelling, it is a failure of recognizing what questions could be important in the future and this is damn hard to do properly.
Pesaran and Smith's solution to what they call the straightjacket of DSGE is to throw all these missing variables in a regression. Essentially, they want to bypass the discipline that theory imposes by letting the data speak. Again this is OK if you want to explore and find relationships, but this is not going to be very useful if you want to explain what is going on. Specifically, they advocate using vector autoregressions (VAR). As they complain that DSGE use representative agents when heterogeneity matters, they call for the use of data from several countries in the VAR, a rather strange argument, but I suppose this is because they are limited to aggregate data (and they neglect all the DSGE models using household level data...). In a statistical sense, the big problem is now that one quickly runs out degrees of freedom, as one has only so many time periods, and every additional variable eats degrees of freedom at a quadratic rate (times the number of lags). The other problem is that interpreting the resulting errors ("shocks") becomes difficult. One is then limited to vague notions like demand and supply shocks, much like in factor analysis. But at least Pesaran and Smith acknowledge that theory can be useful in selecting, say, long-term restrictions.
PS: I gave much of the same arguments in the discussion of a paper by David Hendry. Pesaran appears to be more knowledgeable of DSGE and is more willing to use theory to guide empirics. Unfortunately, Pesaran has the same habit of abusing self-citations, 12 out of 32.
The latest salvo comes from Hashem Pesaran and Ron Smith. They have several arguments. The first is that macroeconomic modeling of the DSGE brand insists too much on internal consistency and should allow more degrees of freedom to fit the data. Pesaran and Smith should first specify what the goal of the model is before criticizing the approach. If it is short-term forecasting, then go ahead with a purely statistical approach on macro data. If you want policy advice, you need something that withstands the Lucas Critique, and strong micro-foundations is then the way to go. But without a given purpose, any criticism is moot.
Pesaran and Smith, given their track record, are of course strong advocates of purely statistical methods. Throw every possible series in a regression, and see what sticks. I am not saying this cannot be useful, it allows to establish relationships in the data and I regularly report on such results, but this does not allow you to explain things. For this, you need some structure and theory provides you that. This brings me to the title of this post. There appears to be some disagreement about the meaning of the word "model." To me, model is a set of relationships established by theory that can then be used on data, for policy experiments, etc. For Pesaran and Smith, a model is a set of aggregate data series that are used in a statistical analysis of some kind (VAR, non-parametric, etc.). If we cannot agree what we are talking about, of course there will be endless and fruitless discussions.
For example, they are not the first to criticize DSGE models for failing to include housing, finance and the external sector. Well, models (the way I see them) are abstractions, and you do not want to include everything them, or you cannot understand, interpret or do something useful with. It is so across all sciences. You build a model to answer a particular question, and you give it the necessary bells and whistles. The fact that most DSGE models did not include housing and bank liquidity is not a failure of DSGE modelling, it is a failure of recognizing what questions could be important in the future and this is damn hard to do properly.
Pesaran and Smith's solution to what they call the straightjacket of DSGE is to throw all these missing variables in a regression. Essentially, they want to bypass the discipline that theory imposes by letting the data speak. Again this is OK if you want to explore and find relationships, but this is not going to be very useful if you want to explain what is going on. Specifically, they advocate using vector autoregressions (VAR). As they complain that DSGE use representative agents when heterogeneity matters, they call for the use of data from several countries in the VAR, a rather strange argument, but I suppose this is because they are limited to aggregate data (and they neglect all the DSGE models using household level data...). In a statistical sense, the big problem is now that one quickly runs out degrees of freedom, as one has only so many time periods, and every additional variable eats degrees of freedom at a quadratic rate (times the number of lags). The other problem is that interpreting the resulting errors ("shocks") becomes difficult. One is then limited to vague notions like demand and supply shocks, much like in factor analysis. But at least Pesaran and Smith acknowledge that theory can be useful in selecting, say, long-term restrictions.
PS: I gave much of the same arguments in the discussion of a paper by David Hendry. Pesaran appears to be more knowledgeable of DSGE and is more willing to use theory to guide empirics. Unfortunately, Pesaran has the same habit of abusing self-citations, 12 out of 32.
The shoe-leather cost of inflation is minimal
One popular way to justify the introduction of monetary frictions in macroeconomic models is to assume that there is some cost associated to changing cash holdings, ATM fees or more generally "shoe-leather" cost. Whether these cost matter at all is controversial and settling this requires a two-pronged approach: first find empirically how large these costs are, and second demonstrate that the costs are large enough to matter in a reasonable model.
Alessandro Calza and Andrea Zaghini estimate the shoe-leather cost for the US. This is by far not the first time this is performed, by it can be worth it as data change, and in this case one can suspect that transaction costs indeed have gone down over a few decades. But there is one critical aspect that they take into account: most on US M1 is not held domestically, and this share has increased to currently 60%. Ignoring this seriously biases estimates, first because it overstates domestic demand and second because the shoe-leather cost stemming from inflation is largely borne by foreigners. At an inflation rate of 10%, the cost amounts to negligible 0.05% of total income. At lower inflation rates, it is even negative thanks to foreigners giving up real resources to acquire US money. In other words, you cannot build a monetary theory on this,
Alessandro Calza and Andrea Zaghini estimate the shoe-leather cost for the US. This is by far not the first time this is performed, by it can be worth it as data change, and in this case one can suspect that transaction costs indeed have gone down over a few decades. But there is one critical aspect that they take into account: most on US M1 is not held domestically, and this share has increased to currently 60%. Ignoring this seriously biases estimates, first because it overstates domestic demand and second because the shoe-leather cost stemming from inflation is largely borne by foreigners. At an inflation rate of 10%, the cost amounts to negligible 0.05% of total income. At lower inflation rates, it is even negative thanks to foreigners giving up real resources to acquire US money. In other words, you cannot build a monetary theory on this,
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