Initially, it might seem odd to think about the “price of money.” Goods are priced in terms of money. So what is meant by the price of money? Often times, people think of the price of money as simply the reciprocal of the price of the good. In other words, if a banana costs 50 cents, then the price of a dollar is two bananas. Others see the price of hold money as an opportunity cost. In other words, by holding money, I am giving up some amount of rate of return. Thus, “the” interest rate is often considered the price of money. The interest rate, however, is not the price of money. The interest rate is the price of credit. So what is a meaningful definition of the price of money? Fortunately, the literature on monetary aggregation provides an answer to this question that is actually based on economic theory.

To define the price of money, we first need to define what we mean by money. Money consists of a lot of different things. Currency is money, a checking account or a savings account is money, and some have argued that due to things like repurchase agreements, even T-bills can be considered money. So if all these things can be considered money, how can we begin to define the price of money. As it turns out, each different type of money has its own price and every definition of a monetary aggregate has a corresponding price index.

Before getting to this, let’s first take a detour through monetary theory.

Traditional courses on monetary theory often start with a discussion about fiat money. Why would anybody hold fiat currency? It is clearly dominated in rate of return. Thus, shouldn’t people hold something else, like capital? Monetary theory has a lot of different answers to this question. For example, currency is assumed to be more liquid than other assets (i.e. there are lower transaction costs associated with using currency than other assets) or individuals value the constant (zero) rate of return in comparison to a stochastic (perhaps negative) rate of return, etc. Regardless of the reason, the general theme is that there are *characteristics* that currency has and that other assets do not have. Those characteristics create a non-pecuniary yield.

This is not only true of a comparison of say currency and capital, but also true of a comparison of currency with other types of things that we often consider “money”, such as a checking account or savings account, or a certificate of deposit. While these other forms of money might bear interest, some places refuse to accept checks, getting money out of a savings account might require a trip to the bank, withdrawing money from a certificate of deposit requires a transaction fee, etc. Thus, there is a trade-off between money and non-money, but there is also a trade-off between different forms of money. Less liquid forms of money yield higher rates of return, but the transactions costs associated with spending that money are higher.

These characteristics of different types of money are important. The reason that they are important is because they highlight the fact that different types of money and different types of assets more generally are imperfect substitutes for one another, a characteristic that is important when thinking about monetary policy. In addition, consider the counterfactual. If all different types of money were perfect substitutes, then individuals would only hold the money asset with the highest rate of return.

So what does this have to do with the price of money?

When we think about money, it is important to think about money in the way that we think about durable goods. Money provides a flow of services over time. As a result, the proper way to think about the price of money is to think about money in terms of its user cost. As Barnett (1978) derived, the real user cost of a given monetary asset i at time t is given as

where is the user cost of asset i at time t, is some benchmark rate of return, and is the rate of return of asset i. Thus, the user cost of holding a given type of money is the discounted present value of the opportunity cost of holding that asset rather than the benchmark asset that doesn’t provide any sort of monetary services. It is important to note that this captures the features of money describe above. An asset that is more liquid will have a lower rate of return and therefore a higher user cost. Nonetheless, individuals will be willing to hold assets with different user costs because the assets are imperfectly substitutable. The price of a monetary aggregate is then given by the share-weighted average of each of the components in a given monetary aggregate.

So why is this important for monetary policy?

A lot of the analysis of quantitative easing focuses on the fact that the Fed is now swapping an interest-bearing asset for another interest-bearing asset. From the perspective of a bank, reserves are more liquid than T-bills since banks can use reserves to settle payments, but not (directly) using T-bills. Thus, consider how monetary policy ordinarily works according to what Ben Bernanke refers to as the portfolio channel of monetary transmission. Suppose that we begin in equilibrium. A bank is holding a given amount of reserves and a given amount of T-bills. The Federal Reserve then purchases T-bills, reducing the supply of T-bills and the increasing the supply of reserves. Assuming that the bank was content with its allocation, it then decides to re-allocate its portfolio (i.e. get rid of the reserves by purchasing other stuff). This re-allocation then has real effects on the economy.

Some have argued that with the Federal Reserve paying interest on reserves, however, banks have no incentive to do this. In other words, the bank receiving the reserves actually gets a marginal increase in liquidity without sacrificing the rate of return. Thus, there is no reason to re-allocate and no corresponding real effects. However, this ignores the fact that quantitative easing has taken a variety of forms. Not all rounds of quantitative easing has entailed buying T-bills. Nevertheless, some have claimed that buying 10-year Treasury bonds instead of T-bills has no effect other than to change the slope of the yield curve.

Regardless of whether the critics of quantitative easing have been correct in the context of the argument above, there is one thing that hasn’t been discussed: the price of money. What effect do large scale purchases of MBS have on the price of money? Is the price of money more sensitive to the purchases of long term bonds or mortgage-backed securities? The counter-argument to the portfolio view espoused by Bernanke suggests quantities don’t matter because relative prices adjust without any corresponding real effects. However, even if we take that view as true, then it must be the case the price of money is changing. This would seem to matter since shocks to the price of money have been shown to have significant effects on real output.

Anyway, just some food for thought.

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Consider a standard microeconomic story. An individual receives income, , and gets utility from consuming goods and . Let denote the price of and denote the price of . Further, suppose the utility function is given as and has the usual properties. Thus, the consumer maximization problem is

The optimal allocation is therefore given as

where is the marginal utility of and correspondingly for .

Now you are probably wondering, what does this have to do with inflation? Well the answer is quite simple. In the problem above, there was no discussion of money. This was a real economy. Suppose instead that we are dealing with a monetary economy. In this case, income is money income (i.e. the number of dollars that you earn). In order to solve the allocation problem, we now need to deflate money income by some price index such that income is expressed in real terms. If a change in the money supply has an equiproportional impact on all prices, the choice of the price index is entirely arbitrary. The price of any individual good will suffice as a price index. In other words, we could re-write the budget constraint as

Solving the consumer’s maximization problem yields the same equilibrium condition as that above. In addition, since changes in the money supply have an equiproportionate effect on all prices, the relative price of good to good remains unchanged and doesn’t have any effect on the allocation of goods. Additionally, so long as is held constant, then money income will not have any effect on the allocation either.

However, suppose that changes in the money supply do not have equiproportionate effects on prices. To use Nick’s example, suppose that the price of is sticky and the price of is flexible. In this case, a change in the money supply will also affect relative prices. In this case, one cannot simply solve the allocation problem by deflating money income by the price of one of the goods. In this case, changes in the money supply will distort the allocation of goods. In addition, this means that it is not sufficient to simply target the sticky price.

The solution to this problem is to choose a price index to deflate money income such that when that index is held constant, there is not any distortion in the allocation of goods. In other words, the objective to choose such that the budget constraint can be re-written as

Given the correct choice of , it is straightforward to show that (1) the allocation of goods is determined by the relative prices of the goods, and (2) when is constant, money income is constant as one moves along an indifference curve.

So how do we construct ? Well, Samuelson gave us a class of examples where there was a specific price index that could solve the problem. And it turns out that the correct price index to use is dependent on the preferences of the representative consumer in the model. In particular, consider the following utility function:

It is straightforward to show that the correct price index to use in this case is

Here is a brief sketch of why this is true. In a real economy, when there is an increase in income, the individual moves to a higher indifference curve (i.e. utility increases). Thus, when an individual moves along an indifference curve, it must be true that income is constant. A different way of stating the problem above is that the objective is to choose a price index such that when that index is held constant, money income is constant when an individual moves along an indifference curve. We can now show that this is true for the utility function and price index above.

Consider the budget constraint:

Suppose the price index is given as , then this can be re-written as

Given the preferences assumed above, the equilibrium condition for the consumer is

Substituting this into the budget constraint yields

Thus, when is constant, a movement along an indifference curve is associated with a constant amount of money income.

So what does all of this mean?

What this means is that if changes in the money supply result in changes in the relative price of goods, then the optimal policy is one in which there is no inflation. However, the choice of how to measure inflation is not arbitrary in this case. Rather, there is a precise index number that must be used to calculate inflation.

Nick’s point, and the accepted wisdom of many in the discipline, is that when changes in the money supply distort relative prices due to price stickiness, the best thing to do is to target the sticky prices and let the flexible prices adjust. However, the example above rejects this idea. If, say, was a sticky price and was a flexible price, targeting would be insufficient. Doing so would prevent money income from affecting utility, but it would not prevent an adjustment in the relative prices of and and would therefore distort the allocation.

What the index number problem suggests is that the choice of the proper price index does not depend on which price is sticky or the source of the relative price variability. Instead, the index number problem suggests that the proper price index is derived from the preferences of the consumer. Thus, when asked if housing prices should be included in the price index used to calculate inflation, the relevant question is not whether housing prices are sticky, but rather whether housing enters a representative consumer’s utility function.

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The basic idea in the Eggertsson and Mehrotra (henceforth EM) paper is that some sort of shock, like a de-leveraging shock, can cause the real interest rate to fall below zero. Since monetary policy is limited by the zero lower bound, the central bank (potentially) cannot equate the real interest rate with the real natural rate of interest. The only solution is for the central bank to increase its inflation target until the real interest rate is equal to the natural rate. In fact, EM argue that there is no equilibrium possible if the inflation rate isn’t raised to minus the real natural rate of interest.

Essentially, my problem with the model is as follows. As I will discuss below, the zero lower bound is only a constraint if individuals can hold currency. However, if individuals are capable of holding currency, when the real interest rate on savings is less than the real rate of return on currency (minus the rate of inflation), then everyone will hold currency. Thus, it is not true that no equilibrium exists when the inflation rate is less than minus the real rate of interest. The inclusion of money has important implications for their model in terms of the welfare effects of the shocks generating the so-called secular stagnation.

The EM model can be summarized as follows. The model is an overlapping generations model in which agents live for 3 periods. Thus, at any one point in time, there are three generations living — young, middle-aged, and old. Agents are assumed to only receive an endowment (or produce) in middle-age. Thus, in order to consume when old, agents have to save some of their endowment for old age. To consume when young, agents have to borrow from middle-aged agents. Middle-aged agents save by lending their endowment to young agents. When young agents become middle-aged, they repay their debt to the now old agents who use the repayment to consume. The model is a pure credit economy in the sense that money serves as a medium of account, but not a medium of exchange. The key feature of the model is that young agents are debt constrained. EM assume that young agents can only borrow an amount less than or equal to . They assume that this constraint is binding such that young agents always borrow an amount, . The key equation in their framework is the equilibrium condition in the savings market, given by

where is the real interest rate, is the discount rate, is the rate of population growth, and is the size of the endowment. Secular stagnation results when the real interest rate falls below zero and the central bank cannot reduce the nominal interest rate sufficiently to clear the market. One potential cause of this phenomenon is de-leveraging. For example, suppose that permanently declines (i.e. young agents find it harder to borrow). In this case, the real interest falls in period and falls again in period . If the decline is large enough, this can cause the real interest rate to be negative.

Now in a pure credit economy, this shouldn’t be a problem. The market rate of interest should just become negative. However, EM assume two things. First, they assume that the central bank determines the nominal interest rate. Second, they assume that “the existence of money precludes the possibility of a negative nominal rate.” The assumption they seem to be making is that nobody holds currency, but the threat that people could hold currency prevents the nominal rate from going below zero. The reason that this is important is because they make the following statement: “…it should be clear that if the real rate of interest is permanently negative, there is no equilibrium consistent with stable prices.” This argument follows directly from the Fisher equation. If prices are constant, the Fisher equation implies that

which is a contradiction since we've assumed that .

However, if we are to take currency seriously, we should consider the conditions under which people would hold currency. To do so, consider a simple modification to their model. Assume that we endow the initial old agents with currency and assume that the supply of currency is constant such that the price level is constant. Now, middle-aged agents face a portfolio allocation decision. They can lend to young agents at the real rate of interest or they can sell their endowment to old agents for money.

In this modified environment there are three possible equilibria. For both debt and currency to be used in equilibrium, it must be true that the rate of return on debt and the rate of return on currency is equal (it is straightforward to show this by adding money to the EM choice problem and solving out the Kuhn-Tucker conditions). If the rate of return on debt is higher than currency, then nobody holds currency and everybody issues debt. If the rate of return on currency (technically, in an OLG model with a constant supply of currency, this is equal to the rate of population growth) is greater than the rate of return on debt, then everybody holds currency.

This point is not a mere formality. The reason is because EM argue that the world blow up with price stability (actually when they say there is no equilibrium, I think they actually mean that autarky is the equilibrium result). However, the simple addition of currency to the model implies that if the real interest rate ever became negative, all middle-aged agents would simply sell their endowment to old agents in exchange for currency rather than lend to young agents. Thus, if young agents become sufficiently debt constrained, nobody lends to young agents and young agents do not consume. Nonetheless, there is an equilibrium consistent with stable prices.

The importance of the explicit inclusion of currency is as follows. The central bank therefore faces a trade-off. If the central bank increased the growth rate of currency and thereby the inflation rate, they could increase the inflation rate sufficiently such that the inflation rate was equal to minus the real rate of interest. In this case, individuals would be indifferent between debt and currency and the debt market would clear at the desired negative real interest rate. This allows young agents to borrow, which given the assumption of diminishing marginal utility of consumption, means that welfare increases. However, this increase in welfare comes at the expense of a reduction in welfare via inflation. It is well-known that in OLG models, the optimal policy is a constant money supply.

This point might seem subtle, but I think it is important. The reason that I think it is important is because by arguing that the zero lower bound causes autarky when the real rate of interest is sufficiently negative, this overstates the welfare losses from the so-called secular stagnation. Introducing a constant supply of currency in this environment, significantly improves welfare relative to autarky. In fact, in standard OLG models, a constant supply of currency produces an optimal allocation.

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Steve Williamson has taken a lot of flak from fellow economics bloggers because he has relentlessly defended this statement over the years. So last week I did a radical thing, I talked to Steve about this very controversy. In doing so, Steve confirmed what I believed to be his view all along and one that I think is correct: Kocherlakota was correct in his statement AND so was Milton Friedman. To understand why, we need to think about the Fisher equation and the behavior of monetary aggregates.

The entire debate centers around the Fisher equation:

where is the nominal interest rate, is the real interest rate, and is expected inflation. In the long run, we tend to think of the real interest rate as being determined by real factors, like productivity and preferences. The reason that the Fisher equation is important is because to understand Friedman’s point, we need to understand the effects of monetary policy in the short run and the long run. Thus, we need to understand both the liquidity effect of monetary policy and the Fisher effect.

Suppose, for example, that the central bank increased the rate of money growth. The liquidity effect implies that the short term interest rate would initially decline. However, over time, the Fisher effect implies that expectations of future inflation would increase and push the nominal interest rate higher. Thus, Friedman’s point was as follows. Suppose the current nominal interest rate was 3% and the central bank wanted to peg the nominal interest rate at 2%, in the short run they could achieve this by increasing money growth (i.e. through the liquidity effect). However, the Fisher effect would ultimately push the nominal interest rate higher. Thus, the only way that the central bank could achieve this interest rate peg would be through continuously increasing the rate of money growth to produce lower rates through the liquidity effect. The result of this sort of policy would then be one of ever-increasing rates of money growth and inflation. This result was largely viewed as unsustainable and therefore central banks could not peg the interest rate in this manner.

Kocherlakota’s point was that pegging the nominal interest rate would ultimately lead to deflation. This sounds contradictory to Friedman because he arrives at the opposite conclusion. However, the two points are actually two sides of the same coin. What Kocherlakota is effectively (or perhaps not so effectively, given the outcry) saying is that if the central bank wanted to peg the interest rate at a particular level, then this would require that the central bank start reducing money growth. In fact, for the case in which the central bank kept the nominal interest rate pegged at zero, a positive real interest rate would imply that the central bank would have to pursue a negative rate of money growth to maintain the target.

Thus, Kocherlakota is taking the objective of holding the interest rate constant as given and asking how it is that the central bank can maintain this policy. Friedman, on the other hand, is thinking about how the central bank is likely to try to pursue this policy.

What both Kocherlakota’s argument and Friedman’s argument have in common are what is important. The common element of the argument is that if the Federal Reserve adopts an interest rate peg over a long period of time, the ability to maintain that peg is dependent on the rate of money growth. *The central bank can either adopt the rate of money growth consistent with the interest rate peg or they cannot maintain the interest rate peg.*

What seemed to confuse people about this entire issue is that their understanding of Federal Reserve policy clearly contradicted any prediction of deflation. Nonetheless, this is the wrong way to interpret Kocherlakota’s argument. The argument he was making was essentially that if the Federal Reserve chose to leave the interest rate at zero for an extended period of time, this would imply that eventually they would have to pursue a policy that was deflationary. If they didn’t pursue that type of policy, they couldn’t maintain their peg of the nominal interest rate. In addition, since we don’t expect the Federal Reserve to pursue a policy consistent with negative rates of money growth, the statement should be seen as a criticism of the Federal Reserve’s original attempt at forward guidance which suggested that the FOMC would keep the interest rate at zero for an extended period of time.

There is an important lesson to be learned from this controversy and debate. The lesson is that even though policy is conducted with the federal funds rate as an intermediate target or with interest on reserves as an instrument, it is still necessary to know the underlying path of the money supply associated with this interest rate policy.

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Economists have common ways of dealing with that question. There are vast literatures on optimal policies of all different types. The literature on optimal policy has a very consistent theme. First, the economist writes down a set of assumptions. Second, the economist solves for the efficient allocation given those assumptions. Third, the economist considers whether a decentralized system can produce the efficient allocation. If the decentralized allocation is inefficient, then there is a role for policy. The optimal policy is the one that produces the efficient allocation.

When Piketty and others talk about inequality and policy, however, they aren’t really talking about efficiency. Meritocracy-type arguments are about fairness. Economists, however, often shy away from discussing fairness. The reason is often simple. Who defines what is fair? Let’s consider an example. Suppose there are two workers, Adam and Steve, who are identical in every possible way and to this point have had the exact same economic outcomes. In addition, assume that we only observe what happens to these individuals at annual frequencies. Now suppose that this year, Adam receives an entirely random increase in pay, where random simply refers to something that was completely unanticipated by everyone. However, this year Steve loses his job for an entirely random reason (e.g. a clerical error removed Steve from the payroll and it cannot be fixed until next year). After this year, Adam and Steve go back to being identical (the clerical error is fixed!) and continue to experience the same outcomes the rest of their lives.

This is clearly a ridiculously stylized example. However, we can use this example to illustrate the difference between how economists evaluate policies. For someone concerned with a meritocratic view of fairness, the ideal policy in the ridiculous example above is quite clear. Adam, through no actions of his own, has received a windfall in income. Steve, through no fault of his own, has lost his income for an entire year. Someone only concerned with meritocracy would argue that the ideal policy is therefore to tax the extra income of Adam and give it to Steve.

Most economists, armed with the same example would not necessarily agree that the meritocratic policy is ideal. The most frequently used method of welfare analysis is the idea of Pareto optimality. According to Pareto optimality, a welfare improvement occurs when at least one person can be made better off without making another person worse off. In our example above, Pareto optimality implies that the optimal policy is to do nothing because taxing Adam and giving the money to Steve makes Adam worse off.

Advocates of meritocracy, however, are unlikely to be convinced by such an argument. And there is reason to believe that they shouldn’t be convinced. For example, if Adam and Steve both knew that there was some random probability of unemployment ex ante, they might have chosen to behave differently. For example, suppose that Adam and Steve each knew in advance that there was some probability that one of them would lose their job. They might have each purchased insurance against this risk. If we assume the third party insurer can costly issue insurance and earns zero economic profit, then when Steve became unemployed, he would receive his premium back plus what is effectively a transfer from Adam.

Of course, in this example, there still isn’t any role for policy. Private insurance, rather than policy, can solve the problem. Nonetheless, as I detail below, this does give us a potentially better starting place for discussing fairness, efficiency, and inequality.

Suppose that inequality is entirely driven by random idiosyncratic shocks to individuals and that these events are uninsurable (e.g. one cannot insure themselves against being born to poor parents, for example). There is a potential role for policy here that is both fair and efficient. In particular, the policy would correspond to what economists traditionally think of as ex ante efficiency. In other words, a fair policy would be the policy that individuals would choose before they knew the realization of these random shocks.

As it turns out there is a sizable literature in economics that examines these very issues and derives optimal policy. The conclusions of this literature are important because (1) they take the meritocratic view seriously, and (2) they arrive at policy conclusions that are often at odds with those proposed by advocates of meritocracy.

It is easy to make an argument for meritocracy. If people make deliberate decisions that improve their well-being, then it is easy to make the case that they are “deserving” of the spoils. However, if people’s well-being is entirely determined by sheer luck, then those who are worse off than others are simply worse off due to bad luck and a case can be made that this is unfair. Unfortunately, for advocates of meritocracy, all we observe in reality are equilibrium outcomes. In addition, individual success is often determined by both deliberate decision-making and luck. (No amount of anecdotes about Paris Hilton can prove otherwise.) I say this is unfortunate for advocates of meritocracy because it makes it difficult to determine what amount of success is due to luck and what is due to deliberate actions. (Of course, this is further muddled by the fact that when I say luck, I am referring to entirely random events, not the definition of the person who once told me that “luck is when preparation meets opportunity.”)

Nevertheless, our economic definition of fairness allows us to discuss issues of inequality and policy without having to disentangle the complex empirical relationships between luck, deliberate action, and success. Chris Phelan, for example, has made a number of contributions to this literature. One of his papers examines the equality of opportunity and the equality of outcome using a definition of fairness consistent with that described above. Rather than examining policy, he examines the equality of opportunity and outcome within contracting framework. What he shows is that inequality of both opportunity and outcome are both consistent with this notion of fairness in a dynamic context. In addition, even extreme inequality of result is consistent with this definition of fairness (such extreme inequality of opportunity, however, are not supported so long as people care about future generations).

Now, of course, this argument is not in any way the definitive word on the subject. However, the main point is that a high degree of inequality is not prima facie evidence of unfairness. In other words, it is not only difficult to disentangle the effects of luck and deliberate action in determining an individuals income and/or wealth, it is actually quite difficult to figure out whether a particular society is fair simply by looking at aggregate statistics on inequality.

This point is especially important when one thinks about what types of policies should be pursued. Advocates of a meritocracy, for example, often promote punitive policies — especially policies pertaining to wealth and inheritance. Piketty, for example, advocates a global, progressive tax on wealth. The idea behind the tax is to forestall the importance of inheritance in the determination of income and wealth. While this policy might be logically consistent with that aim, but it completely ignores the types of things that we care about when thinking about optimal policy.

For example, consider the Mirrlees approach to optimal taxation. The basic starting point in this type of analysis is to assume that skills are stochastic and the government levies taxes on income. The government therefore faces a trade-off. They could tax income highly and redistribute that income to those with lower skill realizations. This represents a type of insurance against having low skills. On the other hand, high taxes on income would discourage high skill workers from producing. The optimal policy is one that best balances this trade-off. As I note in my review of Piketty in National Review, this literature also considers optimal taxation with regards to inheritance. The trade-off here is that high taxes on inheritance discourage wealth accumulation, but provide insurance to those who are born to poor parents. The optimal policy is the one that best balances these incentives. As Farhi and Werning point out in their work on inheritance, it turns out that the optimal tax system for inheritance is a progressive system. However, the tax rates in the progressive system are *negative* (i.e. we subsidize inheritance with the subsidization getting smaller as the size of the inheritance gets larger). The intuition behind this is simple. This system provides insurance without reducing incentives regarding wealth accumulation.

Economists are often criticized as being unconcerned with fairness. This is at least partially untrue. Economists are typically accustomed to thinking about optimality in the context of Pareto efficiency. As a result, economists looking at two different outcomes will be hesitant to suggest that a particular policy might be better than another if neither represents a Pareto improvement. Nonetheless, this doesn’t mean that economists are unconcerned with the issue of fairness nor does it suggest that economists are *incapable* of thinking about fairness. In fact, economists are capable of producing a definition of fairness and the policy implications thereof. The problem for those most concerned with fairness is the economic outcomes and policy conclusions consistent with this definition might not reinforce their ideological priors.

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David ends his post talking about whether Bitcoin would make for a good form of money. This is an interesting question and one that often isn’t given sufficient thought. In David’s own research, however, he has emphasized that the characteristic that determines whether an asset is useful as money is whether that asset is information-sensitive (this claim is often prevalent in Gary Gorton’s work as well). The basic idea is that if the value of an asset is sensitive in the short-run to news that has private value, but no social value, then short run fluctuations in the price of the asset will preclude its use as a medium of exchange. Thus, David suggests looking at how the value of Bitcoin has changed over time. In his graph, he plots the price of bitcoins in terms of dollars. As you can see if you read his post (or if you know anything about Bitcoin), the price of bitcoins relative to dollars is quite volatile — especially over the last year.

However, I wonder whether looking at the volatility of the exchange rate between Bitcoin and the dollar is the best way to determine whether Bitcoin would be a good form of money. There are two reasons why I say this.

First, as David points out, this volatility could be the result of the fact that people view the supply of Bitcoin as being fixed (the supply of Bitcoin will eventually be fixed), but the demand for Bitcoin is fluctuating. David notes that this is consistent with the type of behavior we observe under commodity standards. When there is a change in the demand for gold, the purchasing power of gold varies (at times considerably) even though the long run purchasing power is constant.

I have heard others make this argument as well and this seems very plausible. Nevertheless, it is useful to recall the way in which free banking systems operated. For example, in a free banking system in which banks issued notes that were backed by gold, the supply of bank notes fluctuated with demand. Increases in the demand for money caused an increase in the supply of notes. These changes in the supply of notes, however, needn’t imply any change in the purchasing power of gold. Issuing bank notes redeemable in gold was thereby capable of reducing the volatility of the purchasing power of gold. Similarly, a financial intermediary today could issue bank notes redeemable in bitcoins and reduce the volatility of the purchasing power of bitcoins.

[A quick note: It is perhaps true that the U.S. government might decide that they don't want to allow financial intermediaries to issue bank notes, in which case my proposed solution to this source of volatility would not be operable. I would add though that it is not operable because of a legal restriction and not the volatility of the asset price.]

Second, and perhaps much more importantly, in models with competing money supplies the exchange rate does not factor in to the choice of allocation or welfare analysis. This is true even of David’s own research. For example, in quoting the price of bitcoins in terms of dollars, David is citing an exchange rate. However, in his research, the price volatility that matters for an asset is the own rate of return volatility. I think that this distinction matters.

To illustrate why I think that this distinction matters, let’s consider a simple overlapping generations model. There are two types of agents, young and old. Each lives for two periods. At any point in time, there is a generation of young and a generation of old. The population is assumed to be constant. There is one good to trade and it is non-storable. The young receive an endowment, y, of the consumption good. The old do not receive an endowment of goods. Thus, money is essential. There are two assets that can be used as a possible medium of exchange. The first is fiat currency. The second is bitcoins. The initial old carry both currency and bitcoins into the first period. The aggregate supply of bitcoins is fixed. The aggregate supply of currency, , is assumed to grow at the gross rate (i.e. ).

Let’s consider the first and second period budget constraints for future generations in our model (i.e. everybody except the initial old). In the first period, future generations can use their endowment for consumption or they can sell some of this endowment for money and/or bitcoins. Thus, the first-period budget constraint is:

where denotes the consumption when young in period t, is real currency balances, and denotes real balances of bitcoins.

Denote as the price of currency in terms of goods at time t. Similarly, denote the price of bitcoins in terms of goods as . Thus, the rate of return on currency is . Now let’s assume that there is some cost, that individuals have to pay when they use bitcoin to make a purchase. The rate of return on bitcoins is then given as . Thus, the second-period budget constraint can be written as

But we can derive a precise definition of the rate of return on money. It follows from our first period budget constraint that we have:

where denotes nominal currency balances. Define the total nominal currency stock as and the size of the population, which as assumed to be constant as . This implies an aggregate demand function for currency:

Thus, the rate of return on money is

From above, we know that the currency supply grows at a gross rate . This implies that in a stationary allocation (i.e. where consumption paths a constant across generations), the rate of return on currency is

By similar logic, it is straightforward to show that in a stationary allocation because the supply of bitcoins was assumed to be fixed.

Thus, our stationary allocation budget constraints are:

In the present model, money and bitcoins are perfect substitutes (i.e. there only purpose is to serve as proof of a previous transaction when trading with future young generations). Thus, the real rates of return on money and bitcoins must be equal for both to exist in equilibrium. In other words, it must be true that . We can re-write the second-period constraint as

Combining these budget constraints, we have a lifetime budget constraint:

Now let’s consider the basic implications of the model. First, the conditions under which both currency and bitcoins would be held in equilibrium is dependent on their relative rates of return. If these rates of return are equal, then both assets are held. This condition is independent of the exchange rate. Second, lifetime budget constraint outlines the feasible set of allocations available given the agents’ budget. Assume that utility is a function of consumption in both periods. The allocation decision in this case is dependent on the rate of return on currency, which is the same as the rate of return on bitcoins. The allocation decision is therefore contingent on the equilibrium rate of return. The exchange rate between currency and bitcoins plays no role in the allocation decision. In addition, one can show that this is the identical lifetime budget constraint that would exist in a currency economy (i.e. one in which Bitcoin doesn’t circulate). This last characteristic implies that neither the existence of bitcoins nor the exchange rate between bitcoins and currency have any effect on welfare.

So what does this mean? Basically what all of this means is that the exchange rate between currency and bitcoins is irrelevant to the decision to hold bitcoins, to the allocation decision, and to welfare. [Note: This isn't new, Neil Wallace taught us this type of thing over 30 years ago.]

The analysis above is a bit unfair to David for two reasons. First, the framework above skirts David’s main point, which is that Bitcoin is information sensitive whereas currency is not. Second, David doesn’t necessarily mean that the exchange rate between the dollar and bitcoins is relevant for the type of analysis above. Rather, what he means is that since the dollar is relatively stable, the exchange rate serves as a proxy for the own price of bitcoins in terms of goods.

What I would like to do now is to amend the framework above to make bitcoins information sensitive. The results regarding the exchange rate of bitcoins into dollars remain. However, an interesting result emerges. In particular, one can show that it is the risk premium associated with bitcoins that can help us to understand the choice of whether to hold bitcoins or dollar-denominated currency as well as factor into the allocation decision. I will then speculate as to whether this risk premium is sufficient to explain the differences in rates of return between bitcoins and dollar-denominated currency.

For simplicity, let’s now denote the rate of return on bitcoins as . In addition, we will assume that is stochastic. In particular the assumption is that the rate of return is entirely determined by random news events. Thus, we can re-write our first- and second-period budget constraints, respectively, as

The objective of future generations is to maximize subject to the two constraints above. Combining the first-order conditions with respect to and and using the definition of covariance, we have the following equilibrium condition:

where the second term on the right-hand side measures the risk premium associated with bitcoins (note that this is in fact a risk premium since the covariance between the rate of return on bitcoins and the marginal utility of consumption is negative). If both assets are to be held in equilibrium, then the equibrium condition must hold. If the risk premium is too high, it is possible that nobody would hold bitcoins and they would only hold currency. This confirms David’s view that information sensitivity could affect the decision to hold bitcoins. However, this does not show up in the exchange rate, but rather in the relative rates of return. The risk premium similarly affect the allocation decision. Consider, for example, that the lifetime budget constraint can now be written as

where is used to simplify notation and denote the risk premium and the aggregate supply of bitcoins has been normalized to one. It is straightforward to see that when the risk premium is zero (i.e. bitcoins are not information sensitive) then the lifetime budget constraint is the same as that outlined above. The existence of a positive risk premium alters the budget set.

So what does all of this mean?

Essentially what it means is that looking at the exchange rate between bitcoins and the dollar is not a useful indicator about whether or not bitcoins would actually make for a good money. Even if we view the exchange rate between bitcoins and dollars as a useful proxy of the price of bitcoins in terms of goods, the exchange rate is not the correct measure for analysis. Rather, to evaluate whether bitcoins are a viable alternative/substitute for dollars, we need to know the relative rates of return on bitcoins and dollars and the risk premium associated with the fact that bitcoins are information sensitive.

This might all seem like semantics, after all, if we think the exchange rate is a good proxy of the price of bitcoins in terms of goods, then the rate of return could just be measured as the rate of change in the exchange rate. Nonetheless, this distinction seems especially important given the nature of the exchange rate between bitcoins and dollars. In particular, just looking at David’s graph of the exchange rate, it is plausible that the time series follows a random walk with a drift (I had trouble acquire actual data rather than ready-made graphs on this so if anybody has the data please send it along). This is important because if this is correct, the variance of the exchange rate is time-dependent. However, in terms of rates of change, the data would be stationary and therefore have some constant, finite variance. Thus, in this hypothetical example, looking at the exchange rate using David’s criteria about information sensitivity would indicate that bitcoin is a very bad money because the variance of the exchange rate is time dependent. In contrast, if the rate of return on bitcoin is stationary, then it is not immediately clear from the data whether or not bitcoin is a good money. This is why we need the model as it helps us to understand what properties the rate of return must possess to make a good money.

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The k-percent rule has often been derided as a sub-optimal policy. Suppose, for example, that there was an increase in money demand. Without a corresponding increase in the money supply, there would be excess money demand that even Friedman believed would cause a reduction in both nominal income and real economic activity. So why would Friedman advocate such a policy?

The reason Friedman advocated the k-percent rule was not because he believed that it was the optimal policy in the modern sense of phrase, but rather that it limited the damage done by activist monetary policy. In Friedman’s view, shaped by his empirical work on monetary history, central banks tended to be a greater source of business cycle fluctuations than they were a source of stability. Thus, the k-percent rule would eliminate recessions caused by bad monetary policy.

The purpose of this discussion is not to take a position on the k-percent rule, but rather to point out the fundamental nature of discretionary monetary policy. A central bank that uses discretion has the ability to deviate from its traditional approach or pre-announced policy if it believes that doing so would be in the best interest of the economy. In other words, the central bank can respond to unique events with unique policy actions. There are certainly desirable characteristics of this approach. However, Friedman’s point was that there are very undesirable characteristics of discretion. Just because a central bank has discretion doesn’t necessarily mean that the central bank will use it wisely. This is true even of central banks that have the best intentions (more on this point later).

The economic literature on rules versus discretion is now quite extensive. In fact, a substantial amount of research within the New Keynesian paradigm is dedicated to identifying the optimal monetary policy rule and examining the robustness of this rule to different assumptions about the economy. In addition, there has been a substantial amount of work on credible commitment on the part of policymakers.

Much of the modern emphasis on rules versus discretion traces back to the work of Kydland and Prescott and the idea of dynamic inconsistency. The basic idea is that when the central bank cannot perfectly commit to future plans, we end up with suboptimal outcomes. The idea is important because Kydland and Prescott’s work was largely a response to those who viewed optimal control theory as a proper way to determine the stance of monetary policy. The optimal control approach can be summarized as follows:

The Federal Open Market Committee (FOMC) targets an annual inflation rate of 2% over the long run and an unemployment rate of 6% (the latter number an estimate of the economy’s “natural” unemployment rate).

Under the optimal control approach, the central bank would then use a model to calculate the optimal path of short-term interest rates in order to hit these targets.

In short optimal control theory seems to have a lot of desirable characteristics in that policy is based on the explicit dynamics of a particular economic framework. In addition, it is possible for one to consider what the path of policy should look like given different paths for the models state variables. Given these characteristics, the story describing optimal control linked above is somewhat favorable to this approach and notes that the optimal control approach to monetary policy is favored by incoming Fed chair Janet Yellen. Thus, it is particularly useful to understand the criticisms of optimal control levied by Kydland and Prescott.

As noted above, the basic conclusion that Kydland and Prescott reached was the when the central bank has discretionary power and use optimal control theory to determine policy, this will often result in suboptimal policy. Their critique of optimal control theory rests on the belief that economic agents form expectations about the future and those expectations influence their current decision-making. In addition, since these expectations will be formed based in part on their expectations of future policy, this results in a breakdown of the optimal control framework. The reason that this is true is based on the way in which optimal control theory is used. In particular, optimal control theory chooses the current policy (or the expected future path of policy, if you prefer) based on the current state variables and the history of policy. If expectations about future policy affect current outcomes, then this violates the assumptions of optimal control theory.

Put differently, optimal control theory generates a path for the policy instrument for the present policy decision and the future path of policy. This expected future path of the monetary policy instrument is calculated taking all information available today as given — including past expectations. However, this means that the value of the policy instrument tomorrow is based, in part, on the decisions made today, which are based, in part, on the expectations about policy tomorrow.

There are two problems here. First, if the central bank could perfectly commit to future actions, then this wouldn’t necessarily be a problem. The central bank could, for example, announce some state-contingent policy and perfectly commit to that policy. If the central bank’s commitment was seen as credible, this would help to anchor expectations thereby reinforcing the policy commitment and allowing the central bank to remain on its stated policy path. However, central banks cannot perfectly commit (this is why Friedman not only wanted a k-percent rule, but also sometimes advocated that it be administered by a computer). Thus, when a central bank has some degree of discretion, using optimal control theory to guide policy will result in suboptimal outcomes.

In addition, discretion creates additional problems if there is some uncertainty about the structure of the economy. If the central bank has imperfect information about the structure of the macroeconomy or an inability to foresee all possible future states of the world, then optimal control theory will not be a useful guide for policy. (To see an illustration of this, see this post by Marcus Nunes.) But note that while this assertion casts further doubt on the ability of optimal control theory to be a useful guide for policy, it is not a necessary condition for suboptimal policy.

In short Kydland and Prescott expanded and bolstered Friedman’s argument. Whereas Friedman had argued that rules were necessary to prevent central banks from making errors that were due to timing and ignorance of the lag in effect of policy, Kydland and Prescott showed that even when the central bank knows the model of the economy and tries to maximize an explicit social welfare function known to everyone, using optimal control theory to guide policy can still be suboptimal. This is a remarkable insight and an important factor in Kydland and Prescott receiving the Nobel Prize. Most importantly, it should give one pause about the favored approach to policy by the incoming chair of the Fed.

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My commentary on this is going to be somewhat short because I have identified the point at which I think is the source of disagreement. If I am wrong, hopefully Steve or someone else will point out the error in my understanding.

The crux of Steve’s argument seems to be that there is a distinct equilibrium relationship between the rate of inflation and the liquidity premium on money. For example, he writes:

Similarly, for money to be held,

(2) 1 – L(t) = B[u'(c(t+1))/u'(c(t))][p(t)/p(t+1)],

where L(t) is the liquidity premium on money. For example, L(t) is associated with a binding cash-in-advance constraint in a cash-in-advance model, or with some inefficiency of exchange in a deeper model of money.

He then explains why QE might cause a reduction in inflation using this equation:

…the effect of QE is to lower the liquidity premium (collateral constraints are relaxed) which … will lower inflation and increase the real interest rate.

Like Steve, I agree that such a relationship between inflation and the liquidity premium exists. However, where I differ with Steve seems to be in the interpretation of causation. Steve seems to be arguing that causation runs from the liquidity premium to inflation. In addition, since the liquidity premium is determined by the relative supplies of alternative transaction assets, monetary policy controls inflation by controlling the liquidity premium. My thinking is distinct from this. I tend to think of the supply of public transaction assets determining the price level (and thereby the rate of inflation) with the liquidity premium determined given the relative supply of assets and the rate of inflation. Thus, we both seem to think that there is this important equilibrium relationship between the rate of inflation and the liquidity premium, but I tend to see causation running in the opposite direction.

But rather than simply conclude here, let me outline what I am saying within the context of a simple model. Consider the equilibrium condition for money in a monetary search model:

where is the price level, is the discount factor, is consumption, and is the probability that a buyer and seller is matched. Thus, the term in brackets measures the value of spending money balances and the probability that those balances are spent. The product of these two terms we will refer to as the liquidity premium, . Thus, the equation can be written:

So here we have the same relationship between the liquidity premium and the inflation rate that we have in Williamson’s framework. In fact, I think that it is through this equation that I can explain our differences on policy.

For example, let’s use our equilibrium expression to illustrate the Friedman rule. The Friedman rule is designed to eliminate a friction. Namely the friction that arises because currency pays zero interest. As a result, individuals economize on money balances and this is inefficient. Milton Friedman recommended maintaining a market interest rate of zero to eliminate the inefficiency. Doing so would also eliminate the liquidity premium on money. In terms of the equation above, it is important to note that the left-hand side can be re-written as:

where is the inflation rate and is the rate of time preference. Thus, it is clear that by setting , it follows from the expression above that as well.

Steve seems to be thinking about policy within this context. The Fed is pushing the federal funds rate down toward the zero lower bound. Thus, in the context of our discussion above, this should result in a reduction in inflation. If the nominal interest rate is zero, this reduces the liquidity premium on money. From the expression above, if the liquidity premium falls, then the inflation rate must fall to maintain equilibrium.

HOWEVER, there seems to be one thing that is missing. That one thing is how the policy is implemented. Friedman argued that to maintain a zero percent market interest rate the central bank would have to conduct policy such that the inflation rate was negative. In particular, in the context of our basic framework, the central bank would reduce the interest rate to zero by setting

Since , this implies deflation. More specifically, Friedman argued that the way in which the central bank could produce deflation was by shrinking the money supply. In other words, Friedman argued that the way to produce a zero percent interest rate was by reducing the money supply and producing deflation.

In practice, the current Federal Reserve policy has been to conduct large scale asset purchases, which have substantially increased the monetary base and have more modestly increased broader measures of the money supply.

In Williamson's framework, it doesn't seem to matter how we get to the zero lower bound on nominal interest rates. All that matters is that we are there, which reduces the liquidity premium on money and therefore must reduce inflation to satisfy our equilibrium condition.

In my view, it is the rate of money growth that determines the rate of inflation and the liquidity premium on money then adjusts. Of course, my view requires a bit more explanation of why we are at the zero lower bound despite LSAPs and positive rates of inflation. The lazy answer is that changed. However, if one allows for the non-neutrality of money, then it is possible that the liquidity premium not only adjusts to the relative supplies of different assets, but also to changes in real economic activity (i.e. above). In particular, if LSAPs increase real economic activity, this could reduce the liquidity premium (given standard assumptions about the shape and slope of the functions and ).

This is I think the fundamental area of disagreement between Williamson and his critics — whether his critics even know it or not. If you tend to think that non-neutralities are important and persistent then you are likely to think that Williamson is wrong. If you think that non-neutralities are relatively unimportant or that they aren't very persistent, then you are likely to think Williamson might be on to something.

In any event, the blogosphere could stand to spend more time trying to identify the source of disagreement and less time bickering over prior beliefs.

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We are entering a divisive debate on the Supplemental Nutrition Assistance Program (SNAP), popularly known as food stamps. Unless facts drive the debate, it will be destructive as well.

I certainly agree with this statement. Unfortunately, I found the op-ed misleading and vague (a vague op-ed can be somewhat forgiven since word counts are limited).

The basic premise of Galston’s op-ed is that critics of the increased spending on food stamps are misguided in their criticisms. For example, he explains:

The large increase in the program’s cost over the past decade mostly reflects worsening economic conditions rather than looser eligibility standards, increased benefits, or more waste, fraud and abuse.

[...]

The food-stamp program’s costs have soared since 2000, and especially since 2007. Here’s why.

First, there are many more poor people than there were at the end of the Clinton administration. Since 2000, the number of individuals in poverty has risen to 46.5 million from 31.6 millionâ€”to 15% of the total population from 11.3%. During the same period, the number of households with annual incomes under $25,000 rose to 30.2 million (24.7% of total households) from 21.9 million (21.2%).

Critics complain that beneficiaries and costs have continued to rise, even though the Great Recession officially ended in 2009. They’re right, but the number of poor people and low-income households has continued to rise as well.

Thus, according to Galston, we can explain much of the increase in food stamp spending on the rise of poverty over the last 13 years (and especially the last 6 years). If Galston is correct, then we could examine the ratio of households who are receiving SNAP benefits to the number of people below the poverty line. Supposing that he is correct, we would expect that this ratio would be constant (or at least roughly so). In other words, as the number of people below the poverty line increased, the number of households receiving SNAP benefits would increase in direct proportion.

Such a comparison, however, casts doubt on Galston’s claim. Casey Mulligan, in his book *The Redistribution Recession*, has taken great effort to actually calculate such ratios. What Mulligan found is that from 2007 to 2010, the number of families below 125% of the federal poverty level increased by 16%. That is indeed a large increase. However, the number of households receiving SNAP benefits increased by 58%. This means that the SNAP recipiency ratio, or the ratio of households receiving SNAP to that below 125% of the poverty line (a higher threshold that Galston himself uses), rose by 37%.

So what can explain the fact that recipients are rising so much faster than poverty? One possible explanation are eligibility requirements. Since 2008, there have been several changes to eligibility for food stamps. For example, the Farm Bill passed in 2008 increased the maximum benefit that beneficiaries could receive, it excluded some income from the formula used to determine eligibility, and it weakened the evaluation of assets of potential enrollees. In addition, the American Reinvestment and Recovery Act also loosed eligibility requirements by once again increasing the maximum benefit that one could receive, gave states the ability to loosen the work requirement, and further loosened income requirements.

Galston, however, downplays most of these changes and argues that macroeconomic trends explain the vast majority of the rise of SNAP spending. However, the use of this type of explanation is problematic because it is taking the actual increase in recipients and then explaining the increase in spending ex post. To understand why this is misleading, consider the following example. Suppose that there is an individual who lost his job in 2009. Prior to 2007, he would not have been eligible for SNAP whereas after the changes he is now eligible. Thus, after 2007, this increases the number of recipients of SNAP. Galston might claim that this change is the result of macroeconomic trends because this person would not have enrolled in SNAP had he not lost his job. Others might say that this change is due to eligibility requirements becaus if the worker had lost his job two years prior, he would not have been eligible. While I certainly understand Galston’s perspective on this, the relevant comparison is to the counterfactual. In other words we can’t explain the rise in SNAP recipients ex post, we need to consider what actually happened to what would have happened in the absence of a policy change.

So what do the counterfactuals say?

Again, Casey Mulligan has constructed these counterfactuals. What he finds is that between 2007 and 2010, the increase in per capita SNAP spending was 100%, adjusted for inflation. He then constructs two counterfactuals. The first counterfactual takes macroeconomic trends as given and computes the increase in per capita SNAP spending under 2007 eligibility rules. The second counterfactual does the same thing assuming that in addition to maintaining 2007 eligibility rules, the government had maintained constant real benefit rules (i.e. would not have increased the after-inflation maximum benefit).

The first counterfactual suggests that from 2007 to 2010 per capita SNAP spending would have only increased by 60%, adjusted for inflation. The second counterfactual suggests that per capita SNAP spending would have increased only 24%, adjusted for inflation. Had no policy changes been enacted in 2008 and 2009, per capita spending on SNAP would have been 62% of what it actually was in 2010. Put differently, 48% of the per capita 2010 spending is attributable to changes in eligibility. Thus, contrary to the claims of Galston, a very large fraction of the increase in SNAP spending is explained by changes in eligibility.

An entirely separate question is whether or not this increased spending is worth it. Answering that question is certainly beyond the scope of this post. However, it is important to be mindful that such analysis must consider both the costs and the benefits of the expansion. The benefits are obvious. Households receive assistance in purchasing food and feeding their families. The costs, however, are more complex. A significant fraction of the increase in spending can be explained by changes in eligibility. Thus, we need to consider the counterfactual. One big issue is to consider how much of the increased benefits are going to those who would not have qualified under the asset tests. Another issue is to consider is the effect of changes in eligibility on the labor supply of those at or near the new eligibility requirements, especially given the work requirement waiver. And there is the obvious monetary cost to the taxpayer. Too often those on each side of the debate focus on only the benefits or only the costs.

Whether the policy changes are worth it depends on a careful analysis of these questions. I will remain agnostic with regards to that type of analysis. However, to argue that those concerned about the expansion spending due to changes in eligibility are misguided and driven by “anti-government ideology”, as Galston argues, is an unfair criticism to those who have carefully looked at the data.

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