Rules versus Discretion: Insights from Behavioral Economics

monetary economics, behavioral economics, discretionary monetary economics
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behavioral economics, monetary economics, discretionary monetary policyFor half a century now, the “rules versus discretion” debate in monetary economics has focused on the so-called “time inconsistency” problem.  The problem is that, although a discretionary central bank might promise not to allow the inflation rate to rise above zero (or some other ideal value), the fact that an inflation “surprise” can boost employment and output in the short run will tempt it to break its promise.  Realizing this, market participants will anticipate higher inflation.  The long-run result is a higher inflation rate with no improvement in either employment or output.  By limiting the central bankers’ options, a monetary rule solves the time inconsistency problem.

An earlier rules-versus-discretion debate had taken place in the 1920s and 1930s.1  The later one, which was inspired by the stagflation of the 1970s, differed in that it was influenced by the New Classical revolution that was taking place around the same time.  Consequently, the later critics of monetary discretion, including Finn Kydland and Edward Prescott,  Guillermo Calvo, Benn McCallum, Robert Barro and David Gordon, and John Taylor,2 differed from their predecessors by building their arguments on the premise that central bankers were both well (if not quite perfectly) informed and well intentioned.  Discretion, according to them, leads to less than ideal outcomes not because central bankers are ignorant or misguided, but because of misaligned incentives.

Naturally, champions of discretionary monetary policy also regarded monetary policy makers as well-meaning and well-informed experts.  Their counterargument was simply that such experts could in principle out-perform any rule.  Well-trained monetary technocrats might, after all, resist the short-run temptation to take advantage of established inflation expectations by creating inflation surprises.

But just how likely is it that technocrats will behave well in practice?  Even such a technocratically-inclined proponent of discretion as Joseph Stiglitz recognizes that the “decisions made by the central bank are not just technical decisions; they involve trades-offs, judgments.. .”3  Will such “judgments” typically be wise ones?  Although the sub-discipline didn’t even exist when the rules-versus-discretion debate was revived in the 1970s, let alone when it was first aired in the 1920s, the findings of behavioral economists are the natural place to turn to for answers to this question.  At least some of those answers seem to decidedly favor the rules side of the rules-versus-discretion debate.

As Nobel winning economist and psychologist Daniel Kahneman has observed, experts suffer from all sorts of biases that result in bad decisions and outcomes.  Building upon the work of Paul Meehl,4 Kahneman argues that expert decisions can be inferior to simple algorithms (like a Taylor Rule) because experts “try to be clever, think outside the box, and consider complex combinations of features in making their predictions.”5

In the studies reviewed (and sometimes conducted by) Kahneman, experts are always looking for that one additional data point that suggests a different course of action.  Fed officials have behaved that way lately in repeatedly insisting that their decisions will be “data-dependent,” without actually saying what data they have in mind or how its components will be weighted.  Kahneman also notes that experts are often inconsistent, giving different answers to the same (or similar) question.  Here, too, Fed experts conform to the theory, thereby making it difficult if not impossible for market participants to grasp the direction of monetary policy.  Kahneman reaches  the “surprising” conclusion that “to maximize predictive accuracy, final decisions should be left to formulas, especially in low-validity environments.”6  With respect to monetary policy, that  conclusion would seem to favor a policy rule over discretion.

In research conducted with psychologist Gary Klein, Kahneman has also investigated the conditions that are or are not favorable to discretionary decision making.  Previous scholars had  found that firefighters often have surprisingly good intuition about such things as when the floor of a burning building is about to collapse.7  Kahneman and Klein find, however, that such expert skills must be built up over time.  Novice firefighters do not possess them in the way that veterans do.

Interestingly, Fed officials often liken themselves to “firefighters.”  If the analogy is a good one, and Kaheman and Klein are also correct, then having long (14 year) terms for Fed governors is a good idea.  Unfortunately, Fed governors seldom serve more than a modest fraction of their maximum terms.  As major economic crises and downturns happen only so often — every 13 years in case of U.S. crises, according to Reinhart and Rogoff8 — relatively few Fed governors ever experience more than one crisis, and most are unlikely to witness more than two cyclical turning points.  For a Fed staffed by such novices, the case for rules is especially strong.  Indeed, because monetary policy operates with “long and variable lags,” as Milton Friedman famously put it, even seasoned Fed governors cannot be counted on to employ discretion responsibly.

To summarize these implications of behavioral economics, experts can be expected to employ their discretion advantageously when 1) they operate in a regular, predictable environment, and 2) there is an opportunity for learning via repeated practice.  Neither of these conditions characterize monetary policy.  Behavioral economics has sometimes been presented as an avenue to justify government intervention to correct the failings of ordinary people.  But the same literature reminds us that even the most expert policymakers also suffer from a variety of biases.  Just as default rules may be useful in minimizing consumer errors, monetary rules can serve to minimize errors of monetary policy.

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[1] For an overview of earlier debates see Robert Hetzel, “The Rules versus Discretion Debate Over Monetary Policy in the 1920s.” Federal Reserve Bank of Richmond Economic Review ( November 1985), p. 1-12 and George Tavlas, “In Old Chicago: Simons, Friedman and the Development of Monetary-Policy Rules.” Journal of Money, Credit and Banking 47(1) (January 2015), p. 99-121.

[2] Finn E. Kydland and Edward C. Prescott, “Rules rather than discretion:  The inconsistency of optimal plans,” Journal of Political Economy, 85(3) (June 1977), p. 473-490; Guillermo A. Calvo, “On the Time Consistency of Optimal Policy in a Monetary Economy,” Econometrica 46(6) (November 1978), p. 1411-1428; Bennett T. McCallum, “Monetarist Rules in the Light of Recent Experience,” American Economic Review 74(2) (May 1984), p. 388-91; Robert J. Barro and David B. Gordon, “Rules, Discretion, and Reputation in a Model of Monetary Policy,” Journal of Monetary Economics 12(1) (July 1983), p. 101-121; Robert J. Barro and David B. Gordon, “A Positive Theory of Monetary Policy in a Natural-Rate Model,” Journal of Political Economy 91(4) (August 1983), p. 589-610; and John B. Taylor, “What Would Nominal GNP Targeting Do to the Business Cycle?” Carnegie-Rochester Conference Series on Public Policy 22 (9) (January 1995), p. 61-84.

[3] Joseph Stiglitz. “Central Banking in a Democratic Society,” De Economist 146(2) (July 1998), p. 199-226.

[4] Paul E. Meehl, Clinical vs. Statistical Prediction: A Theoretical Analysis and a Review of the Evidence (University of Minnesota, 1954).

[5] Daniel Kahneman, Thinking, Fast and Slow (New York: Farrar, Straus, and Giroux, 2011). Especially chapters 21 and 22.

[6] Ibid.

[7] Perhaps the most well known popular version of these arguments is found in Malcolm Gladwell, Blink (New York: Little Brown and Company, 2005).

[8] Carmen M. Reinhart and Kenneth S. Rogoff, This Time is Different: Eight Centuries of Financial Folly (Princeton, NJ: Princeton University Press, 2009), p. 150, Table 10.2.