Much of the macroeconomic literature on the `rules versus discretion' debate proposes that precommitment take the form of a non-contingent or `open-loop' k percentage money supply rule. Such open-loop policies prevent governments from responding to unforeseen shocks; and although feedback rules derived from control theory can provide the flexibility required, they may prove difficult for a sceptical private sector to monitor. If private agents are unable to distinguish between a government's reaction to a contingency and its reneging on a commitment, such `contingent rules' cannot be credible.

In Discussion Paper No. 515, Research Fellow Paul Levine notes that a private sector that knows the full nature of the government's calculations can conduct its own evaluations of the precommitment rule and deduce the relevant policies for different contingencies. For the rule to be incentive compatible, there must be a trigger mechanism whereby the private sector `punishes' a reneging government by believing only in discretionary policy for some `punishment period'. The recent literature on credibility has focused on games with less than full information to assess governments' attempts to eliminate the inefficiencies of discretionary policy. All this literature assumes, however, that the private sector knows the general nature of government behaviour and lacks only some limited information concerning parameters such as the weight on output in the welfare function. The private sector can therefore observe policy instruments such as the money supply and infer the values of these unknown parameters.

Levine assumes instead that a less well-informed public estimates the policy rule directly by observing the data and applying a recursive estimation procedure to infer the rule. For an overlapping contracts model with rational expectations, he shows that the optimal rule with precommitment takes the rather complicated form of a error-correction mechanism. Learning a rule of this type proves slower than learning a simpler rule of lower order. Although the simple rule is sub-optimal in a complete information setting, its performance becomes significantly better than its originally optimal counterpart when information is withdrawn and learning introduced.

Levine maintains that these results support the case for conducting macroeconomic policy on the basis of a a simple rather than the more complex `optimal' rule. Other arguments for simple rules include their intuitive appeal, ease of implementation and relative robustness in the face of model uncertainty. He concludes that these issues are primarily empirical, however, and can only be resolved on the basis of results derived from empirical models.

Should Rules Be Simple?
Paul Levine

Discussion Paper No. 515, March 1991 (IM)