Menu Costs^1,2

One reason that prices take time to adjust in an economy is due to menu costs. The basic idea behind menu costs, as stated in the seminal work of Sheshinski and Weiss, is that “price adjustments are not costless” for firms. These costs can come in many forms. Menu costs could be the costs associated with a restaurant physically designing and printing a new menu every time prices change, a supermarket paying an employee to relabel goods, or even the cost associated with disgruntled customers who may be unhappy when they realize a different customer received a different price for the same good purchased only slightly before or after they did.

The result of such costs to a firm for changing prices is that, even with perfect knowledge and foresight of future inflation, firms will hold nominal prices constant for a period of time before changing prices in discrete increments despite continuously changing prices for inputs. That is, firms will adjust prices only if the marginal benefit of doing so outweighs the marginal cost. While certainly an oversimplification of the phenomenon, it is clear that menu costs can prevent the rapid response of prices to shocks. As a shock hits the economy, firms must weigh the costs of changing their prices and the benefits that occur from doing so. The perceived permanence of the shock and impact on expected prices and demand into the future certainly play into the decision-making process.

Anecdotal evidence suggests that technology may be reducing menu costs in some industries. The trend toward e-commerce clearly makes changing prices easier and less costly for firms (Figure 4.2). That said, we do not feel that e-commerce can fully eliminate menu costs. As mentioned earlier, customers likely will become agitated if there is a significant increase in volatility of the prices for goods and services. Take, for example, the challenges faced by companies such as the ride-hailing service Uber, which has the ability to constantly adjust the price for its services through surge pricing. During times of peak demand, fares can rise to multiple times the normal fare, to which the company has received blowback, particularly around crisis situations.³ This has led the firm to limit surge pricing at times, preventing them from maximizing their profits because they deemed the cost of changing prices too expensive—a form of menu costs. Despite these issues, technology has certainly enabled firms to adjust prices faster in response to changing economic environments.

Contracts—Labor/Suppliers/Hedging

Contracts can also contribute to the inflexibility of prices in the economy. A large share of economic contracts—whether they are for inputs to the production of final goods, contracts to sell products to consumers, debt contracts or labor contracts—are priced in nominal terms. That is, they are not typically indexed to the price level. This means that the price of the good or service being exchanged between the involved parties during the life of the contract is fixed in nominal terms, which can lead to lags in adjustments to shocks. Because of the fixed nominal price, expectations are critical in forming the contract. Again, as we have seen before, how economic news and the economy evolve relative to what was expected is relevant to economic decision making. Consider the aviation industry, where the activity of hedging energy costs is commonplace. If an airline hedged some portion of their fuel needs in late 2014, they would likely be slower to lower their fares compared to airlines with no hedging. That is, because they would still be paying the elevated fuel costs for at least a portion of their fuel needs, it would be difficult to lower prices (Figure 4.3). Contracts, such as hedging contracts at the firm level, contribute to slow price adjustment in the economy as a whole.

In addition, labor contracts make it difficult to adjust wages and the level of employment in response to shocks to aggregate demand, which may in turn lead to a slow adjustment process. We will discuss nominal wage rigidities in greater detail shortly, although contracts can certainly contribute to nominal rigidities in the labor market.

Mandated Prices

Examples of mandated prices can be found in many sectors of the economy. Many regulated industries such as utilities and health care have limits on what they can charge for their goods and services. In addition, the price of labor for all firms in the economy is often mandated via minimum wage laws and required benefits. These topics are highly controversial, and there are many stakeholders involved in determining the optimal policies, meaning that a thorough review would not be possible in this text. We simply highlight the impact these policies have on the economy’s adjustment to shocks. Because these prices cannot adjust in response to a changing economic environment, the adjustment process is drawn out, and the allocation of resources may be less efficient in an economic sense due to changes in the relative prices of these goods or services.

Nominal Wage Rigidities in the Labor Market⁴

Another prominent contributor to the sluggishness of price adjustment, and one that has gained more attention following the Great Recession, is the downward nominal wage rigidity in the labor market. That is, it is difficult for employers to reduce nominal wages following a negative shock to aggregate demand. The unwillingness of firms to reduce, or of employees to accept, lower wages can lead to increased unemployment, as firms lay off workers instead of reducing wages or hours for all employees. Downward wage rigidities, therefore, slow the price adjustment process during business cycles. In a recovery period, it takes time for the economy to work through the “pent-up wage deflation” before hiring and wage gains can materialize. The concept of downward nominal wage rigidities and their implications will be discussed in more detail in a later chapter.

Prices as Incentive

Imperfect price adjustment can also be an incentive for participants in a marketplace. The lag in price adjustment often introduces opportunity for the clever arbitrageur in many markets, who may take advantage of the discrepancy in price. The simplest example, not surprisingly, is an application to financial markets. That said, the ideas in this section could easily be extended to account for many types of markets.

In financial markets, for example, there is evidence that suggests that price discovery occurs in futures markets rather than cash markets for some assets, and that the futures markets lead the spot market in responding to news.⁵ The lag in response between prices in futures and the cash market can create an arbitrage opportunity. The presence of this opportunity to buy in the lower-priced market and instantaneously sell to the higher-priced market should attract arbitrageurs who would do just this. Buying at the lower price and selling at the higher price would lead to the convergence of the two markets, eliminating the arbitrage opportunity. This introduces an interesting paradox in financial markets, which, stated loosely, suggests that efficient markets require a little bit of inefficiency to reward arbitrageurs, who then make the market more efficient.⁶

Extending this idea to the real economy, we see that there must be some reward for expending the effort and resources necessary to gather information regarding prices and their adjustment in order to better price one’s own goods rather than simply taking prices as given. That is, if prices adjust perfectly and instantaneously, a firm would not expend resources to obtain information about the supply-and-demand schedules of a product and rather simply monitor the prevailing price in the marketplace, taking it as given.

Business Cycles

Likely the largest implication of sticky prices is the introduction of business cycles. If the economy instantaneously moved to a new equilibrium following an economic shock, the short-run aggregate supply curve would be a vertical line, the same as the long-run supply curve. That is, a positive shift in aggregate demand would simply raise the price level and not impact output because prices instantly adjust. Dynamic adjustment, however, leads to a positive sloping short-run aggregate supply curve and allows actual output to persistently deviate from the long-run potential.

It is difficult to discuss economic fluctuations without mentioning the monetarism school of thought. Monetarist theory suggests that money is not neutral in the short run and the money supply is “the chief determinant of current dollar gross domestic product (GDP) in the short run and the price level over longer periods.”⁷ This can be seen through the quantity theory of money, which states that nominal output equals the money supply times the velocity of money.

Where M is the money supply, V is the velocity of money, P is the price level and Q is output. This equation always holds true and is an accounting identity because the velocity of money is defined to make the equation hold. That said, monetarists argue that changes in the money supply can impact real output because prices on the right side of the equation are slow to adjust to a new equilibrium. This imperfect adjustment, therefore, is the foundation of many policy actions and is one of the justifications for the generally accepted belief that monetary policy can have real impacts in the short run.

Buildup of Imbalances

Prices that are mandated or set by governments are an example of frictions that lead to imperfect price adjustment. While there are a number of examples of mandated prices, one of the more straightforward examples with easily accessible data is in the case of currency pegs. When a country pegs its currency to another, it typically stands ready to transact (either buy or sell) at the peg or in some channel around the peg.

Take, for example, the experience of the Swiss franc (CHF) at the beginning of 2015, when the Swiss National Bank shocked markets by allowing the CHF to appreciate against the euro. The central bank had initially introduced the floor on the currency (thereby limiting the appreciation of the CHF) in an effort to maintain the competitiveness of its exports. The CHF, like the dollar, is often seen as a safe-haven currency. With the turmoil in the Eurozone, many traders preferred to hold assets denominated in Swiss francs. To prevent the currency from appreciating beyond the floor set by the Swiss National Bank, the central bank had to commit to buying an unlimited amount of euros, which would be financed by the sale of CHF. In order to defend the floor amidst a rapid depreciation of the euro relative to many currencies, including the dollar, the Swiss National Bank cut short-term interest rates into negative territory to make holding the CHF less attractive and rapidly expanded the monetary base—a by-product of buying euros with newly created CHF. The rapid expansion of the monetary base stoked fears of runaway inflation, which likely contributed to the central bank’s decision to remove the peg. As illustrated below in Figure 4.4, the reaction to the move was abrupt, as the CHF rapidly appreciated versus the euro.

Similarly, we can look at the experiences of many Asian economies in the late 1990s, whose currencies came under downward pressure rather than upward pressure like the CHF. In defending their currencies against depreciation, the Asian central banks were forced to sell foreign currency reserves and buy the local currency. This, naturally, cannot go on indefinitely as each country holds a finite amount of foreign currency reserves. If traders view the peg as unsustainable, the country is susceptible to a speculative attack. That is, if “the market” does not believe the country is willing and able to defend its currency peg through selling reserves or raising interest rates, which can exacerbate the problem by weakening the domestic economy and increasing borrowing costs, traders may aggressively sell the currency in question, leading to the peg breaking.

As you can see in Figure 4.5, Thailand consistently built up foreign reserves as their economy experienced rapid growth, leading the country to be viewed as a “model economy.” This caused capital to flow into the country, which would normally put upward pressure on Thai baht. By accumulating foreign exchange reserves, Thailand was able to maintain the currency peg. Once some of the issues in the economy became more pronounced and the baht came under rapid selling pressure, foreign exchange reserves fell rapidly. Once the available reserves were all but exhausted, the central bank capitulated and devalued the baht.

Short Run to Long Run

Another impact of the lag in price adjustment is that short-run impacts and adjustments can spill over to the long run. In the post–Great Recession era, as we have emphasized, many things have changed in the economy. This has resulted in estimates for potential growth seeing significant downward revisions. While the excesses before the crisis masked some of the changes to economic fundamentals, the recession itself likely also contributed to reduced potential in many economies around the globe. The fact that short-term business cycle fluctuations can spill over and impact the long-term growth trajectory of an economy is not conventional wisdom in classical economics. In fact, a recent study found a relationship between the magnitudes of the decline in output relative to potential (output gap) and the subsequent downward revision in potential GDP since the downturn.⁸ They conclude that the hysteresis effects—negative impact on potential growth from economy operating below potential—account for a large portion of this phenomenon.

Don’t Assume Reversion to the Mean

Often, we hear economic data discussed in relation to the long-run average value. Many commentators cite a long-run average as a “normal” value for economic data series without justifying this assertion. As we have mentioned, many economic series are not mean reverting; that is, they do not tend toward a stable mean over time. Therefore, we must be careful when utilizing the long-run average as a guide in decision making by validating that the series is in fact mean reverting before proceeding to do so.

In Table 4.1 we display the results for a series of statistical tests to determine if many of the economic series we discussed in this chapter are in fact mean reverting. First, we utilize the Augmented Dickey-Fuller (ADF) test to test for mean reversion, and we then test for structural breaks using the State-Space approach. As you can see, all of the series we studied contained a unit root, meaning the series is not mean reverting. In addition, all of the series contain structural breaks, meaning their mean and/or variance changed between periods. Therefore, we must be careful when assuming the long-run average as a guide for future behavior with these series.

Time-Varying Equilibrium Rate Resetting Expectations

Similarly, we can investigate the time-varying equilibrium real interest rate (Figure 4.6). Statistical analysis confirms the structural break in the natural rate of interest during the Great Recession. This suggests that the myriad of comments indicating that interest rates should “normalize” or increase back to a “normal” level are statistically unfounded. While there are economic arguments for rates rising, we must be careful of arguments assuming they will rise back to historical levels.

Impulse Response Functions

Now that we have identified that the series we are interested in are not mean reverting, we must apply a few transformations (percent change is a convenient transformation) that would convert the series into one that is in fact mean reverting. Once we have done this, we construct a simple model of the housing market, including home sales, home prices, inventories, and interest rates to illustrate the dynamic adjustment process. We acknowledge that this model fails to capture many of the dynamics in the housing market, but utilize this model for simplicity. We shock the model with a 1 percentage point increase in the 10-year Treasury yield and investigate the dynamics of the model through the impulse response functions plotted in Figures 4.7 through 4.9.

Following a 1 percentage point increase in the 10-year Treasury, home sales steadily decline and continue to decline for a year into the future. Similarly, home prices fall and inventories rise; these changes are also persistent. This simple model clearly illustrates the imperfect price adjustment process. A year after the initial shock to interest rates, the housing market is still in the adjustment process to the new equilibrium. Of course, this model contains significant uncertainty, and the confidence intervals of impulse response functions include zero. Nonetheless, it is informative that the mean response to a shock does display imperfect price adjustment.