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Policy advice, secrecy, and reputational concerns
European Journal of Political Economy Vol. 16 Ž2000. 257–271
Policy advice, secrecy, and reputational concerns Otto H. Swank Erasmus UniÕersity and Tinbergen Institute, H7-13, P.O. Box 1738, 3000 DR Rotterdam, Netherlands Received 1 March 1999; received in revised form 1 September 1999; accepted 1 September 1999
Abstract This paper examines how a policy maker reaches decisions under uncertainty when he cares about holding office. An important assumption is that in order to win elections, the policy maker must show that he is able to distinguish good policies from bad policies. Consequently, the policy maker cares about his reputation. I derive two results. First, reputational concerns induce the policy maker to adopt a secret decision procedure. The reason is that disputes between the policy maker and experts damage the policy maker’s reputation. Second, I show that reputational concerns induce the policy maker to ignore important sources of information. q 2000 Elsevier Science B.V. All rights reserved. JEL classification: D72; D82; D83 Keywords: Political economy; Reputation; Advice
1. Introduction Policy makers are often uncertain about the consequences of their decisions. In order to reach better decisions, they can seek advice from experts. Today, governments are assisted by hundreds of agencies that are charged with the task of collecting information and giving advice. In the Netherlands, 230 advisory units assist the government in designing and evaluating policy proposals. The proposition that policy decisions should be based on adequate information about their E-mail address: [email protected] ŽO.H. Swank.. 0176-2680r00r$ - see front matter q 2000 Elsevier Science B.V. All rights reserved. PII: S 0 1 7 6 - 2 6 8 0 Ž 9 9 . 0 0 0 5 4 - 3
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consequences is hardly controversial. Indeed, few scholars blame policy makers for consulting experts and establishing expert agencies. However, some scholars doubt about the efficiency of the information gathering process. In a recent paper, Stiglitz Ž1998. tries to explain why in the United States governments have failed to implement a large number of Pareto improvements. As one of the reasons, he mentions that policy decisions are arrived in secret. According to Stiglitz, policy makers choose for secrecy because they are afraid that people get the impression that the administration is confused and divided. Furthermore, as an insider, Stiglitz was struck by the nonscientific tone of political discourse. In his own words ‘‘What occurred was often worse than Gresham’s Law: it was not only that bad arguments seemed to drive out good, but economists, responding to implicit incentives, adopted bad arguments to win their battles’’ ŽStiglitz, 1998, p. 5.. Secrecy in the policy making process is not limited to the United States. In the Netherlands, for example, bureaucrats are compelled to be loyal to their political masters. In practice, this means that bureaucrats are not allowed to oppose their political masters in public. This paper tries to give answers to Stiglitz’ questions ‘‘Why are policy makers so obsessed with secrecy?’’ or more specifically, ‘‘Why do policy makers dislike disputes over policy to become public?’’. Moreover, this paper examines the incentives for policy makers to seek out the ‘‘best’’ type of advisers. I investigate a model in which the policy maker must make a decision about a project. The consequences of this project are surrounded with two types of uncertainty, e and m. The policy maker receives a signal about m , but not about e . The policy maker can be smart or dumb. When he is smart, he receives an informative signal about m , and when he is dumb, he receives an uninformative signal. I assume that the policy maker aims at keeping office. Because, in general, smart policy makers make better decisions than dumb ones; a policy maker, aiming at reelection, cares about the reputation that he is smart. Before the policy maker makes his decision about the project, he can consult an adviser who, like the policy maker, observes a signal about m. This adviser can also be smart or dumb. Alternatively, the policy maker can consult an adviser who observes a signal about e . I also allow the policy maker to choose between a secret and open decision procedure. Under a secret decision procedure, voters observe the policy decision and the consequences of the project. Under an open decision procedure, voters also observe the signals that have induced the policy decision. I employ the model to address two questions. First, does the policy maker consult an adviser who observes m , or does he consult an adviser who observes e ? Second, does the policy maker choose a secret or an open decision procedure? I derive two results. First, when the policy maker consults an adviser, sharing his own expertise, he has an incentive to conceal disputes. The reason is that voters learn from disputes that either the policy maker or the adviser has received a wrong signal. This excludes the possibility that both the policy maker and the adviser are smart. Consequently, disputes damage the policy maker’s reputation.
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The incentive to conceal disputes induces the policy maker to choose for secret decision procedures. The second result is that when the policy maker has received a favorable signal about the project, he consults an adviser who shares his own expertise rather than an adviser with different expertise. The reason is a ‘‘sharing the blame effect’’. When two experts agree that one type of consequences is favorable, say m , and the outcomes of the project are Žweakly. unfavorable, voters tend to believe that the outcomes of the project are unfavorable because of the other type of uncertainty, e . So voters are inclined to believe that the policy maker is smart, and blame ‘‘exogenous circumstances’’. If the policy maker consulted an adviser, whose expertise differs from that of himself, there would not be a sharing the blame effect. Then, the probability that the unfavorable outcomes are the result of a dumb policy maker is equal to the probability that the unfavorable outcomes are the result of a dumb adviser. Overall, the analysis implies that reputational concerns do not foster a good policy setting. Secrecy makes it harder for voters to assess the policy maker’s competency. Therefore, secrecy distorts the selection of competent policy makers in the sense that secrecy increases the probability that dumb policy makers win elections. Furthermore, reputational concerns lead policy makers to disregard important sources of information. Consequently, reputational concerns increase the probability of policy mistakes. To put it otherwise, reputational concerns imply that policy makers find it more important that voters believe that they make correct decisions than that they actually make correct decisions. There are several papers that examine how policy makers obtain information from advisers. In most of these papers, the policy maker and the adviser care about the consequences of policies. This literature typically addresses two types of questions. First, ‘‘To what extent does the interaction between policy makers and advisers lead to an efficient use of information?’’. Second, ‘‘Who has the greater influence on policy decisions, policy makers or advisers?’’. This literature has contributed much to our understanding of the policy formation process. Several authors have identified the conditions under which experts’ recommendations are credible to political agents. Basically, these conditions require that the policy maker’s and the adviser’s preferences are not too dissimilar. 1 Moreover, several authors have shown how institutional features may constrain advisers to exploit their information advantage.2 Only a few studies examine the role of advisers in the policy decision process when the policy maker cares about his reputation. Exceptions are Levy Ž1999. and
1
See, e.g. Crawford and Sobel Ž1982., Calvert Ž1985., Milgrom and Roberts Ž1986., Austen-Smith Ž1993., Lupia and McCubbins Ž1994, 1998., Letterie and Swank Ž1997. and Swank et al. Ž1999.. 2 See, e.g., McCubbins and Schwartz Ž1984., McCubbins et al. Ž1987., Bendor et al. Ž1985., Banks and Weingast Ž1992. and Bawn Ž1997..
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Ottaviani and Sørensen Ž1999.. The present paper differs from those papers in that we assume that the policy maker does not know his own ability. Moreover, I allow the policy maker to determine the rules of the game by his choice of decision procedure. The paper is organized as follows. Section 2 discusses the model. Section 3 argues why policy makers are so obsessed with secrecy. In Section 4, I show that policy makers, who care about their reputation, have an incentive to disregard sources of information. Section 5 concludes.
2. Description of the model 2.1. The project The model revolves around a project X. A policy maker has to make a decision about this project. There are two alternatives. The policy maker undertakes the project Ž X s 1. or he maintains the status quo Ž X s 0.. The consequences of the project are surrounded with uncertainty. All citizens evaluate the consequences of the project according to the following utility functions: UŽ X s 1< e ,m . s p q e q m , Ž 1. where p denotes the expected net benefits of the project, and e and m are stochastic terms, which can take on two values, yh and h, with equal probability. I assume that the realizations of e and m are mutually independent. I normalize to zero, the utility achieved when the status quo is maintained: U Ž X s 0 . s 0.
Ž 2.
Throughout, I assume that p - 0 and h ) yp. The implication of p - 0 is that without further information about e and m , the policy maker should maintain the status quo. The implication of h ) yp is that without further information about e and m , the policy maker runs the risk of making a wrong decision concerning the project. 2.2. The policy maker The policy maker receives a signal that can take on two values, sGP , meaning m s h, and s BP , meaning m s yh. There are two types of policy makers: smart ones and dumb ones. Neither citizens nor the policy maker himself knows whether the policy maker is smart or dumb. In case the policy maker is smart, which occurs with probability p P Ž0 - p P - 1., the signal observed by the policy maker gives perfect information about m : Prob Ž sGP < m s h,smart . s 1
Ž 3.
Prob Ž s BP < m s yh,smart . s 1.
Ž 4.
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However, if the policy maker is dumb, the signal gives no information about m : Prob Ž sGP < m s h,dumb . s 1r2
Ž 5.
Prob Ž s BP < m s yh,dumb . s 1r2.
Ž 6.
It is evident that when the project is undertaken, the expected utility of the policy maker, conditional on the signal he has received, is E U Ž X s 1 < sGP . s p q p P h
Ž 7.
E U Ž X s 1 < s BP . s p y p P h.
Ž 8.
I assume that p P h ) yp, implying that the signal received by the policy maker may induce him to change his preferences over policies. It is worth emphasizing that the policy maker is not sure about the realization of m , because p P ) 1. However, the policy maker can consult an adviser to obtain more information about m. The policy maker does not observe an informative signal on e . Initially, I assume that he cannot acquire information about e by consulting an adviser. In Section 4, I will relax this assumption. 2.3. The adÕiser Like the policy maker, the adviser observes a signal S A g sGA , s BA 4 , where sGA means m s h, and s BA means m s yh. The adviser is smart with probability p A or dumb with probability 1 y p A . For simplicity, I assume that p s p P s p A . If the adviser is smart, she receives a fully informative signal about m. If she is dumb, she receives an uninformative signal. Initially, I assume that the adviser reports honestly her signal to the policy maker. Later, I will relax this assumption. 2.4. The decision process The policy maker makes a decision about the project after the adviser has reported her signal to him. Clearly, the project yields a positive expected utility only if the signal set is sGP , sGA 4 .3 Consequently, when the policy maker receives the signal s BP , he needs not to consult an adviser to examine if the project yields a positive expected benefit. To reduce straightforward algebra, I assume that in case the policy maker observes s BP , he maintains the status quo and the game ends.4 One of the objectives of this paper is to explain why policy makers are so obsessed with secrecy. I allow the policy maker to choose between a secret 3
For, EwUŽ X s1 < sGP , s BA .x s EwUŽ X s1 < s BP , sGA .x s p and p- 0. This assumption does not affect the results if p is large enough. However, if p is small, the policy maker may want to consult an adviser, because he has an incentive to undertake the project when the signal set is s BP , sGA 4 Žsee Section 3.. 4
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decision procedure and an open one. Under a secret decision procedure, neither the policy maker nor the adviser reveals their signal to the public. Under an open decision procedure, both the policy maker and the adviser honestly report their signal to the public. Of course, allowing the policy maker to choose for an open decision procedure is somewhat academic. Usually, legislation, which compels the policy maker Žor the adviser. to reveal private information, is difficult to enforce. I allow the policy maker to choose the type of decision procedure to examine the incentives being at work. 2.5. Preferences The policy maker is assumed to maximize the expected posterior probability that he is smart Ždenoted by pˆ P .. The idea behind this assumption is that the policy maker aims at re-election, and that this requires that voters believe that he is a smart policy maker. When different strategies of the policy maker lead to the same posterior probability that the policy maker is smart, he chooses the strategy that is expected to yield optimal policy outcomes.5 Voters update their beliefs about the policy maker’s type at the end of the game, that is, after the policy maker has made a decision about the project. When the policy maker has undertaken the project, voters observe the total consequences of the project Ž e q m ., but they do not observe e and m separately.
3. Why are policy makers so obsessed with secrecy? 3.1. The formal argument As discussed in Section 2 under a secret decision procedure, voters observe X s 1 or X s 0, and if X s 1, they also observe e q m. Under an open decision procedure, voters in addition observe the signals received by the policy maker and the adviser. In this section, I show that a policy maker, who tries to convince voters that he is smart, prefers secrecy to openness. Lemma 1. When the policy maker chooses a secret decision procedure, denoted by S, it is optimal for him to choose X s 1 if the signal set is {sGP , sGA }, and to choose X s 1 with probability argmin {a s (1 y 2p 2 ) r (1 y p 2 ), 1} if the signal set is {sGP , sBA }. Proof. I have to show that the policy maker’s strategy posited in Lemma 1 maximizes the expected posterior probability that the policy maker is smart, 5
To put it differently, the policy maker cares about both re-election and policy outcomes, but he finds staying in office always more important tyhan ‘‘good’’ policy.
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pˆ P Ž sGP .. To calculate pˆ P Ž sGP ., I first derive the posterior probabilities that the policy maker is smart for all possible outcomes of the game. There are four possible outcomes. I. X s 1 n e q m s 2 h From this outcome, voters can infer that m s h, and that the signal set is sGP , sGA 4 or sGP , sGA 4 . From Bayes’ rule, it follows that
pˆ P Ž X s 1, e q m s 2 h < S . 1 1 p 2 q p Ž 1 y p . q ap Ž 1 y p . 2 2 s 1 1 1 2 2 pq Ž1yp . q p Ž1yp . q Ž1yp . a 4 2 4 s
2p Ž 1 q p . q 2 ap Ž 1 y p . 2 Ž1yp . qa Ž1yp 2 .
.
Ž 9.
The numerator of Eq. Ž9. gives the prior probability that with a smart policy maker, outcome I occurs. The denominator gives in addition the probability that with a dumb policy maker, outcome I occurs. After the policy maker has received his signal, but before the adviser has received her signal, the probability that outcome I occurs is: Prob Ž X s 1, e q m s 2 h < S, sGP . s
1 8
1
2 Ž 1 q p . q aŽ 1 y p 2 . .
8
Ž 10 .
II. X s 1 n e q m s 0 From this outcome, voters can infer that m s h or m s yh, and that the signal set is sGP , sGA 4 or sGP , s BA 4 . From Bayes’ rule, it follows that
pˆ P Ž X s 1, e q m s 0 < S . s
p Ž 1 q p . q ap Ž 1 y p . 1qp 2 qa Ž1yp 2 .
.
Ž 11 .
The probability that outcome II occurs is Prob Ž X s 1, e q m s 0 < S, sGP . s
1 4
1
Ž 1 q p 2 . q a Ž 1 y p 2 . . Ž 12 . 4
III. X s 1 n e q m s y2 h From this outcome, voters can infer that m s yh, and that the signal set is sGP , sGA 4 or sGP , s BA 4 . Consequently, voters know that the policy maker is dumb:
pˆ P Ž X s 1, e q m s y2 h < S . s 0.
Ž 13 .
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The probability that this outcome occurs is Prob Ž X s 1, e q m s y2 h < S, sGP . s
1
1
2 2 Ž 1 y p . q aŽ 1 y p . . 8 8 Ž 14 .
IV. X s 0 When the status quo is maintained, voters can infer that either the policy 1 maker has received signal s BP , which occurs with probability , or that the 2 signal set is sGP , s BA 4 . The probability that the signal set is sGP , s BA 4 and 1 X s 0 is equal to Ž1 y a .Ž1 y p 2 .. If s BP has induced X s 0, no informa2 tion becomes available about the policy maker’s competency. In contrast, the signal set sGP , s BA 4 contains information about the policy maker’s competency. The reason is that the signal set sGP , s BA 4 excludes the possibility that both the policy maker and the adviser are smart. For, if both the policy maker and the adviser were smart, they would receive the same signal. Hence, Bayes’ rule implies: 1
pˆ P Ž X s 0 < S . s
2
pq Ž1ya . 1
1 q
2 s
2
1 2
Ž1yp 2 .
p Ž1yp . 1yp 2
Ž1ya . Ž1yp 2 .
p 1q Ž1ya . Ž1yp .
.
Ž 15 .
Ž1ya . Ž1yp 2 . .
Ž 16 .
1q Ž1ya . Ž1yp 2 .
The probability that outcome IV occurs is Prob Ž X s 0 < S . s
1
1 q
2
2
The policy maker’s strategy posited in Lemma 1 implies that if the signal set is sGP , s BA 4 , the policy maker chooses X s 1 with probability a and chooses X s 0 with probability 1 y a . With 0 - a - 1, the policy maker must be indifferent between choosing X s 1 and choosing X s 0 if the signal set is sGP , s BA 4 . From Eqs. Ž9., Ž11. and Ž13., it follows that
pˆ P Ž X s 1, sGP , s BA 4 < S . s
1 2p Ž 1 q p . q 2 ap Ž 1 y p . 2 Ž1qp . qa Ž1yp .
4 q
1 p Ž 1 q p . q ap Ž 1 y p . 2
1qp 2 qa Ž1yp .
,
Ž 17 .
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which should be equal to Eq. Ž15.. After multiplying Eqs. Ž15. and Ž17. by Ž1 q p ., it is easy to show that this requires
as
1 y 2p 2 2yp 2
Clearly, when p G
.
(
Ž 18 . 1
, the policy maker always chooses X s 0 if the 2 signal set is sGP , s BA 4 . Using Eqs. Ž9. – Ž16. and Ž18., it is also straightforward to show that pˆ P Ž X s 1 < sGP , sGA 4 , S . ) pˆ P Ž X s 0 < sGP , sGA 4 , S . . I Lemma 2. Under a secret decision procedure, the expected posterior probability that the policy maker is smart, giÕen that he receiÕes signal sGP , is higher than the prior probability that the policy maker is smart. Proof. By definition: Prob Ž sGP . pˆ P Ž sGP , S . q Prob Ž s BP . pˆ Ž s BP , S . s p . Eq. Ž15. implies that pˆ Ž s BP , S . - p . Furthermore, ProbŽ sGP . s ProbŽ s BP . 1 s . Hence, pˆ Ž sGP , S . ) p . I 2 Lemma 3. When the policy maker chooses an open decision procedure, denoted by O, he chooses X s 1 if and only if the signal set is {sGP , sGA }. Proof. To prove Lemma 3, again I first derive the posterior probabilities that the policy maker is smart, given the posited strategy. The posterior probabilities that the policy maker is smart for the three possible outcomes when the policy maker chooses X s 1 and the probabilities that these outcomes occur are given by Eqs. Ž9. – Ž14. with a s 0. There remain two other possible outcomes. IV. X s 0 n s BP In this case, voters do not learn anything about the policy maker’s type, so that pˆ P Ž X s 0, s BP < O . s p . Ž 19 . 1 The probability that the policy maker receives signal s BP is equal to . 2 V. X s 0 n sGP , s BP 4 From the signal set sGP , s BA 4 , voters infer that the policy maker and the adviser are not both smart. Bayes’ rule implies: p pˆ P Ž X s 0, sGP , s BA 4 < O . s . Ž 20 . 1qp
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266
The probability that outcome V occurs is 1 Prob Ž X s 0, sGP , s BA 4 < O . s Ž 1yp 2 . . 2 To prove Lemma 3, I have to show that pˆ P Ž X s 1 < sGP , sGA 4 , O . G pˆ P Ž X s 0 < sGP , sGA 4 , O .
Ž 21 . Ž 22 .
and
pˆ P Ž X s 0 < sGP , s BA 4 , O . G pˆ P Ž X s 1 < sGP , s BA 4 , O . .
Ž 23 .
From the posterior probabilities that the policy maker is smart for the three possible outcomes when X s 1, and the probabilities that these outcomes occur, it follows that p Ž1qp . pˆ P Ž X s 1 < sGP , sGA 4 , O . s , Ž 24 . 1qp 2 which is equal to
pˆ P Ž X s 0 < sGP , sGA 4 , O . s pˆ P Ž sGP , sGA 4 < O . 1 p 2 q p Ž1yp . 2 s 1 1 2 2 p q p Ž1yp . q Ž1yp . 2 2 p Ž1qp . s . Ž 25 . 1qp 2 Hence, Eq. Ž22. is satisfied. Furthermore, 1 p p 1 2p Ž 1 q p . pˆ P Ž X s 1 < sGP , s BA 4 , O . s q s , 2 4 Ž1qp . 2 1qp 1qp Ž 26 . which is equal to Eq. Ž20.. Hence, Eq. Ž23. is also satisfied. Because the expected posterior probabilities that the policy maker is smart do not depend on his decision about the project, the policy maker maximizes his chances of re-election by choosing X s 1 if the project is expected to benefit society, and by choosing X s 0 otherwise. I Lemma 4. Under an open decision procedure, the expected posterior probability that the policy maker is smart, giÕen that he has receiÕed signal sGP , is equal to the prior probability that the policy maker is smart. Proof. The proof directly follows from Eqs. Ž9. – Ž14. with a s 0, and Eqs. Ž20. and Ž21.. I
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Proposition 1. The policy maker prefers a secret decision procedure to an open one. Proof. Proposition 1 follows directly from Lemmas 2 and 4.
I
3.2. The intuition We have formally derived above that in our model, the policy maker prefers a secret decision procedure to an open one. The simplest illustration why the policy maker favors a secret decision procedure is provided when p G 1r2 . In this case, under both decision procedures, the project is undertaken only if the signal set is sGP , sGA 4 . The only difference between the two procedures is then that under an open decision procedure, voters may observe that the policy maker and the adviser disagree, while in a secret decision procedure, voters do not. The policy maker favors a secret decision procedure, because it conceals disputes. The reason that the policy maker do no want voters to observe disputes, is that from disputes, voters learn that the policy maker and the adviser cannot be both smart. For, if both the adviser and the policy maker were smart, they would agree on the project. Consequently, disputes induce voters to revise the probability that the policy maker is smart downwards. Although the objective of the above analysis is to provide an explanation why policy makers are obsessed with secrecy, it has also two normative implications. First, under a secret decision procedure, voters obtain less information about the policy maker’s ability than under an open decision procedure. Clearly, this distorts the selection of the most competent policy maker. Second, secrecy may induce policy makers to undertake projects that are expected to hurt society. This happens if p - 1r2 . Then, the policy maker sometimes implements the project although the adviser has received a bad signal, implying that the expected net benefit of the project is negative. The lower is the prior probability that the policy maker is smart, the higher is the probability that the policy maker undertakes a project, which is undesirable from a social point of view. So far we have assumed that the adviser reports the signal she has received to the policy maker. However, the adviser may also have incentives to behave strategically. Suppose that the adviser, like the policy maker, tries to convince outside evaluators of her competence. As argued above, this gives an incentive to the adviser to prevent voters from observing disputes. Because a secret decision procedure conceals conflicts, under a secret decision procedure, the adviser has no incentive to lie to the policy maker about the signal she has received.6 Things are different under an open decision procedure. An adviser who knows that the policy maker has observed signal sGP maximizes her expected posterior probability that
'
'
6
Of course, the policy maker and the adviser will say to voters that they have received the same signals.
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she is smart by pretending that she has received the same signal. In the game theoretical literature, this is referred to as herd behavior Žsee Scharfstein and Stein, 1990.. Clearly, herd behavior renders consulting advisers senseless. In fact, the prevention of herd behavior can be regarded as a normative reason for secret decision procedures. 4. The selection of an adviser In Section 3, I have shown that reputational concerns induce the policy maker to adopt a secret decision procedure. In this section, I show that reputational concerns may induce the policy maker to select an adviser in — from a social standpoint — an inefficient manner. Suppose that after the policy maker has received his signal, he can choose between consulting an adviser who may receive an informative signal about e and consulting an adviser who may receive an informative signal about m. In Section 3, we have derived that by consulting the latter adviser, the policy maker can increase the expected probability that he is smart. What is the expected probability that the policy maker is smart when he consults an adviser who receives an informative signal about e ? To answer this question, I make assumptions that are analogous to the ones I made earlier. I assume that the alternative adviser receives a signal S e g sGe , s Be 4 , where sGe means e s h, and s Be means e s yh. The adviser is smart with probability p e or dumb with probability 1 y p e , with p s p P s p A s p e. If she is smart, she receives a fully informative signal. If she is dumb, she receives an uninformative signal. In Appendix A, I show that if the policy maker acquires information about e , he undertakes the project if and only if the signal set is sGP , sGe 4 . Furthermore, I show that the policy maker is indifferent between an open and secret decision procedure, and that after he has received signal sGP , the expected posterior probability that he is smart is equal to p .7 So a policy maker who maximizes the expected posterior probability that he is smart chooses for consulting an adviser who shares his own expertise.8 What is the reason for this result? When the policy maker and his adviser have different expertises, their signals do not provide information about the policy maker’s ability. For, it is well possible that the project is favorable with respect to m , but unfavorable with respect to e . Consequently, the policy maker has no reason to conceal disputes. However, the policy maker does not benefit from an adviser who agrees with him either. In terms of reputation, there are no benefits from consensus. When the policy maker consults an adviser who shares his own expertise, there is a ‘‘sharing the blame effect’’. In case the outcomes of the project are weakly unfavorable, voters tend to 7 8
The proofs of these results are in Section 3 of this paper. When the policy maker cares about re-election, this result requires that < p < is small.
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believe that m s h and e s yh. For, there are two experts who agree that e s yh. It is worth noticing that from a social point of view, the policy maker should consult the adviser who receives a signal about e . The reason is that in the model, the amount of uncertainty about m is equal to the amount of uncertainty about e . From this perspective, the policy maker is indifferent between consulting an adviser who receives a signal about m and an adviser who receives a signal about e . However, through his signal, the policy maker obtains information about m. This reduces the social benefits of an adviser who receives a signal about m. 5. Conclusions This paper aims at gaining insight into the way office-motivated policy makers reach decisions under uncertainty. Let me summarize my two main results. First, reputational concerns induce the policy maker to adopt a secret decision procedure. The reason is that disputes between the policy maker and experts damage the policy maker’s reputation. Second, I have shown that reputational concerns induce the policy maker to consult an expert who shares his own expertise rather than an expert who has a different expertise. The reason is that support of an expert, who has the same expertise as the policy maker, implies that voters tend to believe that the policy maker is competent. The implication of these results is that the policy maker’s incentive to show his ability does not lead him to promote the interests of society. Secrecy reduces the amount of information about the policy maker’s ability. Consequently, secrecy increases the probability that incompetent policy makers remain in office. Moreover, I have pointed out that the policy maker’s incentive to consult an adviser who shares his own expertise increases the probability that projects are implemented that hurt society. Acknowledgements I would like to thank Henry Ursprung, Robert Dur, an anonymous referee and participants at the conference on Economic Performance, Economic Policy and Political Culture for their comments. Appendix A In this appendix, I show that when the policy maker consults an adviser, who receives a signal about e , he is indifferent between an open and secret decision process, and the expected posterior probability that he is smart, conditional on signal sGP , is equal to the prior probability that he is smart.
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Suppose that the policy maker chooses X s 1 only if the signal set is sGP , sGe 4 To derive pˆ P Ž sGP ., I first derive the posterior probabilities that the policy maker is smart for the four possible outcomes of the game. I. X s 1 n e q m s 2 h From this outcome, voters infer that the policy maker has received the correct signal. Bayes’ rule implies:
pˆ P Ž X s 1, e q m s 2 h . s
2p
.
1qp
Ž A1.
The probability that outcome I occurs is 1
Prob Ž X s 1, e q m s 2 h < sGP . s
2 Ž 1qp . .
8
Ž A2.
II. X s 1 n e q m s 0 From this outcome, voters infer that either the policy maker or the adviser has received the correct signal. Bayes’ rule implies: 1 1 2p p pˆ P Ž X s 1, e q m s 0 . s 0 q s . 2 2 1qp 1qp
Ž A3.
The probability that outcome II occurs is Prob Ž X s 1, e q m s 2 h < sGP . s
1 4
Ž 1yp 2 . .
Ž A4.
III. X s 1 n e q m s y2 h From this outcome, voters infer that the policy maker has received the wrong signal, so that
pˆ P Ž X s 1, e q m s y2 h . s 0.
Ž A5.
The probability that outcome III occurs is Prob Ž X s 1, e q m s y2 h < sGP . s
1 8
2 Ž 1yp . .
Ž A6.
IV. X s 0 From this outcome, voters cannot infer information about the policy maker’s type, implying:
pˆ Ž X s 0 . s p .
Ž A7.
The probability that outcome I occurs is Prob Ž X s 0 < sGP . s
1 2
.
Ž A8.
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From Eqs. ŽA1. – ŽA6., it directly follows that pˆ P Ž X s 1. s p . Because pˆ P Ž X s 1. s pˆ P Ž X s 0., the policy maker has no incentive to undertake the project if the signal set is sGP , s Be 4 . Moreover, pˆ P Ž sGP , sGe . s pˆ P Ž sGP , s Be . implies that the policy maker has no incentive to conceal conflicting signals.
References Austen-Smith, D., 1993. Interested experts and policy advice: multiple referrals under open rule. Games and Economic Behavior 5, 3–43. Banks, J.S., Weingast, B.R., 1992. The political control of bureaucracies under asymmetric information. American Journal of Political Science 36, 509–524. Bawn, K., 1997. Choosing strategies to control the bureaucracy: statutory constraints, oversight, and the committee system. Journal of Law, Economics and Organization 15, 101–126. Bendor, J., Taylor, S., Van Gaalen, R., 1985. Bureaucratic expertise versus legislative authority: a model of deception and monitoring in budgeting. American Political Science Review 79, 1041–1060. Calvert, R.L., 1985. The value of biased information: a rational choice model of political advice. Journal of Politics 47, 531–555. Crawford, V., Sobel, J., 1982. Strategic information transmission. Econometrica 50, 1431–1451. Letterie, W., Swank, O.H., 1997. Learning and signaling by advisor selection. Public Choice 92, 353–367. Levy, G., 1999. Strategic Consultation and ‘Yes Man’ Advisers. Princeton University, Princeton, Mimeo. Lupia, A., McCubbins, M.D., 1994. Learning from oversight: fire alarms and police patrols reconstructed. Journal of Law, Economics and Organization 10, 96–125. Lupia, A., McCubbins, M.D., 1998. The Democratic Dilemma. Cambridge Univ. Press, Cambridge. McCubbins, M.D., Noll, R.G., Weingast, B.R., 1987. Administrative procedures as an instrument of political control. Journal of Law, Economics and Organization 3, 243–277. McCubbins, M.D., Schwartz, T., 1984. Congressional oversight overlooked: policy patrols versus fire alarms. American Journal of Political Science 28, 165–179. Milgrom, P., Roberts, J., 1986. Relying on the information of interested parties. Rand Journal of Economics 17, 18–32. Ottaviani, M., Sørensen, P., 1999. Professional Advice. University College London, London, Mimeo. Scharfstein, D.S., Stein, J.C., 1990. Herd behavior and investment. American Economic Review 80, 465–479. Stiglitz, J.E., 1998. Distinguished lecture on economics in government: the private uses of public interests: incentives and institutions. Journal of Economic Perspectives 12, 3–22. Swank, O.H., Letterie, W., Van Dalen, H.P., 1999. A theory of policy advice. Journal of Law, Economics and Organization, forthcoming.
Policy advice, secrecy, and reputational concerns Otto H. Swank Erasmus UniÕersity and Tinbergen Institute, H7-13, P.O. Box 1738, 3000 DR Rotterdam, Netherlands Received 1 March 1999; received in revised form 1 September 1999; accepted 1 September 1999
Abstract This paper examines how a policy maker reaches decisions under uncertainty when he cares about holding office. An important assumption is that in order to win elections, the policy maker must show that he is able to distinguish good policies from bad policies. Consequently, the policy maker cares about his reputation. I derive two results. First, reputational concerns induce the policy maker to adopt a secret decision procedure. The reason is that disputes between the policy maker and experts damage the policy maker’s reputation. Second, I show that reputational concerns induce the policy maker to ignore important sources of information. q 2000 Elsevier Science B.V. All rights reserved. JEL classification: D72; D82; D83 Keywords: Political economy; Reputation; Advice
1. Introduction Policy makers are often uncertain about the consequences of their decisions. In order to reach better decisions, they can seek advice from experts. Today, governments are assisted by hundreds of agencies that are charged with the task of collecting information and giving advice. In the Netherlands, 230 advisory units assist the government in designing and evaluating policy proposals. The proposition that policy decisions should be based on adequate information about their E-mail address: [email protected] ŽO.H. Swank.. 0176-2680r00r$ - see front matter q 2000 Elsevier Science B.V. All rights reserved. PII: S 0 1 7 6 - 2 6 8 0 Ž 9 9 . 0 0 0 5 4 - 3
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consequences is hardly controversial. Indeed, few scholars blame policy makers for consulting experts and establishing expert agencies. However, some scholars doubt about the efficiency of the information gathering process. In a recent paper, Stiglitz Ž1998. tries to explain why in the United States governments have failed to implement a large number of Pareto improvements. As one of the reasons, he mentions that policy decisions are arrived in secret. According to Stiglitz, policy makers choose for secrecy because they are afraid that people get the impression that the administration is confused and divided. Furthermore, as an insider, Stiglitz was struck by the nonscientific tone of political discourse. In his own words ‘‘What occurred was often worse than Gresham’s Law: it was not only that bad arguments seemed to drive out good, but economists, responding to implicit incentives, adopted bad arguments to win their battles’’ ŽStiglitz, 1998, p. 5.. Secrecy in the policy making process is not limited to the United States. In the Netherlands, for example, bureaucrats are compelled to be loyal to their political masters. In practice, this means that bureaucrats are not allowed to oppose their political masters in public. This paper tries to give answers to Stiglitz’ questions ‘‘Why are policy makers so obsessed with secrecy?’’ or more specifically, ‘‘Why do policy makers dislike disputes over policy to become public?’’. Moreover, this paper examines the incentives for policy makers to seek out the ‘‘best’’ type of advisers. I investigate a model in which the policy maker must make a decision about a project. The consequences of this project are surrounded with two types of uncertainty, e and m. The policy maker receives a signal about m , but not about e . The policy maker can be smart or dumb. When he is smart, he receives an informative signal about m , and when he is dumb, he receives an uninformative signal. I assume that the policy maker aims at keeping office. Because, in general, smart policy makers make better decisions than dumb ones; a policy maker, aiming at reelection, cares about the reputation that he is smart. Before the policy maker makes his decision about the project, he can consult an adviser who, like the policy maker, observes a signal about m. This adviser can also be smart or dumb. Alternatively, the policy maker can consult an adviser who observes a signal about e . I also allow the policy maker to choose between a secret and open decision procedure. Under a secret decision procedure, voters observe the policy decision and the consequences of the project. Under an open decision procedure, voters also observe the signals that have induced the policy decision. I employ the model to address two questions. First, does the policy maker consult an adviser who observes m , or does he consult an adviser who observes e ? Second, does the policy maker choose a secret or an open decision procedure? I derive two results. First, when the policy maker consults an adviser, sharing his own expertise, he has an incentive to conceal disputes. The reason is that voters learn from disputes that either the policy maker or the adviser has received a wrong signal. This excludes the possibility that both the policy maker and the adviser are smart. Consequently, disputes damage the policy maker’s reputation.
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The incentive to conceal disputes induces the policy maker to choose for secret decision procedures. The second result is that when the policy maker has received a favorable signal about the project, he consults an adviser who shares his own expertise rather than an adviser with different expertise. The reason is a ‘‘sharing the blame effect’’. When two experts agree that one type of consequences is favorable, say m , and the outcomes of the project are Žweakly. unfavorable, voters tend to believe that the outcomes of the project are unfavorable because of the other type of uncertainty, e . So voters are inclined to believe that the policy maker is smart, and blame ‘‘exogenous circumstances’’. If the policy maker consulted an adviser, whose expertise differs from that of himself, there would not be a sharing the blame effect. Then, the probability that the unfavorable outcomes are the result of a dumb policy maker is equal to the probability that the unfavorable outcomes are the result of a dumb adviser. Overall, the analysis implies that reputational concerns do not foster a good policy setting. Secrecy makes it harder for voters to assess the policy maker’s competency. Therefore, secrecy distorts the selection of competent policy makers in the sense that secrecy increases the probability that dumb policy makers win elections. Furthermore, reputational concerns lead policy makers to disregard important sources of information. Consequently, reputational concerns increase the probability of policy mistakes. To put it otherwise, reputational concerns imply that policy makers find it more important that voters believe that they make correct decisions than that they actually make correct decisions. There are several papers that examine how policy makers obtain information from advisers. In most of these papers, the policy maker and the adviser care about the consequences of policies. This literature typically addresses two types of questions. First, ‘‘To what extent does the interaction between policy makers and advisers lead to an efficient use of information?’’. Second, ‘‘Who has the greater influence on policy decisions, policy makers or advisers?’’. This literature has contributed much to our understanding of the policy formation process. Several authors have identified the conditions under which experts’ recommendations are credible to political agents. Basically, these conditions require that the policy maker’s and the adviser’s preferences are not too dissimilar. 1 Moreover, several authors have shown how institutional features may constrain advisers to exploit their information advantage.2 Only a few studies examine the role of advisers in the policy decision process when the policy maker cares about his reputation. Exceptions are Levy Ž1999. and
1
See, e.g. Crawford and Sobel Ž1982., Calvert Ž1985., Milgrom and Roberts Ž1986., Austen-Smith Ž1993., Lupia and McCubbins Ž1994, 1998., Letterie and Swank Ž1997. and Swank et al. Ž1999.. 2 See, e.g., McCubbins and Schwartz Ž1984., McCubbins et al. Ž1987., Bendor et al. Ž1985., Banks and Weingast Ž1992. and Bawn Ž1997..
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Ottaviani and Sørensen Ž1999.. The present paper differs from those papers in that we assume that the policy maker does not know his own ability. Moreover, I allow the policy maker to determine the rules of the game by his choice of decision procedure. The paper is organized as follows. Section 2 discusses the model. Section 3 argues why policy makers are so obsessed with secrecy. In Section 4, I show that policy makers, who care about their reputation, have an incentive to disregard sources of information. Section 5 concludes.
2. Description of the model 2.1. The project The model revolves around a project X. A policy maker has to make a decision about this project. There are two alternatives. The policy maker undertakes the project Ž X s 1. or he maintains the status quo Ž X s 0.. The consequences of the project are surrounded with uncertainty. All citizens evaluate the consequences of the project according to the following utility functions: UŽ X s 1< e ,m . s p q e q m , Ž 1. where p denotes the expected net benefits of the project, and e and m are stochastic terms, which can take on two values, yh and h, with equal probability. I assume that the realizations of e and m are mutually independent. I normalize to zero, the utility achieved when the status quo is maintained: U Ž X s 0 . s 0.
Ž 2.
Throughout, I assume that p - 0 and h ) yp. The implication of p - 0 is that without further information about e and m , the policy maker should maintain the status quo. The implication of h ) yp is that without further information about e and m , the policy maker runs the risk of making a wrong decision concerning the project. 2.2. The policy maker The policy maker receives a signal that can take on two values, sGP , meaning m s h, and s BP , meaning m s yh. There are two types of policy makers: smart ones and dumb ones. Neither citizens nor the policy maker himself knows whether the policy maker is smart or dumb. In case the policy maker is smart, which occurs with probability p P Ž0 - p P - 1., the signal observed by the policy maker gives perfect information about m : Prob Ž sGP < m s h,smart . s 1
Ž 3.
Prob Ž s BP < m s yh,smart . s 1.
Ž 4.
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However, if the policy maker is dumb, the signal gives no information about m : Prob Ž sGP < m s h,dumb . s 1r2
Ž 5.
Prob Ž s BP < m s yh,dumb . s 1r2.
Ž 6.
It is evident that when the project is undertaken, the expected utility of the policy maker, conditional on the signal he has received, is E U Ž X s 1 < sGP . s p q p P h
Ž 7.
E U Ž X s 1 < s BP . s p y p P h.
Ž 8.
I assume that p P h ) yp, implying that the signal received by the policy maker may induce him to change his preferences over policies. It is worth emphasizing that the policy maker is not sure about the realization of m , because p P ) 1. However, the policy maker can consult an adviser to obtain more information about m. The policy maker does not observe an informative signal on e . Initially, I assume that he cannot acquire information about e by consulting an adviser. In Section 4, I will relax this assumption. 2.3. The adÕiser Like the policy maker, the adviser observes a signal S A g sGA , s BA 4 , where sGA means m s h, and s BA means m s yh. The adviser is smart with probability p A or dumb with probability 1 y p A . For simplicity, I assume that p s p P s p A . If the adviser is smart, she receives a fully informative signal about m. If she is dumb, she receives an uninformative signal. Initially, I assume that the adviser reports honestly her signal to the policy maker. Later, I will relax this assumption. 2.4. The decision process The policy maker makes a decision about the project after the adviser has reported her signal to him. Clearly, the project yields a positive expected utility only if the signal set is sGP , sGA 4 .3 Consequently, when the policy maker receives the signal s BP , he needs not to consult an adviser to examine if the project yields a positive expected benefit. To reduce straightforward algebra, I assume that in case the policy maker observes s BP , he maintains the status quo and the game ends.4 One of the objectives of this paper is to explain why policy makers are so obsessed with secrecy. I allow the policy maker to choose between a secret 3
For, EwUŽ X s1 < sGP , s BA .x s EwUŽ X s1 < s BP , sGA .x s p and p- 0. This assumption does not affect the results if p is large enough. However, if p is small, the policy maker may want to consult an adviser, because he has an incentive to undertake the project when the signal set is s BP , sGA 4 Žsee Section 3.. 4
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decision procedure and an open one. Under a secret decision procedure, neither the policy maker nor the adviser reveals their signal to the public. Under an open decision procedure, both the policy maker and the adviser honestly report their signal to the public. Of course, allowing the policy maker to choose for an open decision procedure is somewhat academic. Usually, legislation, which compels the policy maker Žor the adviser. to reveal private information, is difficult to enforce. I allow the policy maker to choose the type of decision procedure to examine the incentives being at work. 2.5. Preferences The policy maker is assumed to maximize the expected posterior probability that he is smart Ždenoted by pˆ P .. The idea behind this assumption is that the policy maker aims at re-election, and that this requires that voters believe that he is a smart policy maker. When different strategies of the policy maker lead to the same posterior probability that the policy maker is smart, he chooses the strategy that is expected to yield optimal policy outcomes.5 Voters update their beliefs about the policy maker’s type at the end of the game, that is, after the policy maker has made a decision about the project. When the policy maker has undertaken the project, voters observe the total consequences of the project Ž e q m ., but they do not observe e and m separately.
3. Why are policy makers so obsessed with secrecy? 3.1. The formal argument As discussed in Section 2 under a secret decision procedure, voters observe X s 1 or X s 0, and if X s 1, they also observe e q m. Under an open decision procedure, voters in addition observe the signals received by the policy maker and the adviser. In this section, I show that a policy maker, who tries to convince voters that he is smart, prefers secrecy to openness. Lemma 1. When the policy maker chooses a secret decision procedure, denoted by S, it is optimal for him to choose X s 1 if the signal set is {sGP , sGA }, and to choose X s 1 with probability argmin {a s (1 y 2p 2 ) r (1 y p 2 ), 1} if the signal set is {sGP , sBA }. Proof. I have to show that the policy maker’s strategy posited in Lemma 1 maximizes the expected posterior probability that the policy maker is smart, 5
To put it differently, the policy maker cares about both re-election and policy outcomes, but he finds staying in office always more important tyhan ‘‘good’’ policy.
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pˆ P Ž sGP .. To calculate pˆ P Ž sGP ., I first derive the posterior probabilities that the policy maker is smart for all possible outcomes of the game. There are four possible outcomes. I. X s 1 n e q m s 2 h From this outcome, voters can infer that m s h, and that the signal set is sGP , sGA 4 or sGP , sGA 4 . From Bayes’ rule, it follows that
pˆ P Ž X s 1, e q m s 2 h < S . 1 1 p 2 q p Ž 1 y p . q ap Ž 1 y p . 2 2 s 1 1 1 2 2 pq Ž1yp . q p Ž1yp . q Ž1yp . a 4 2 4 s
2p Ž 1 q p . q 2 ap Ž 1 y p . 2 Ž1yp . qa Ž1yp 2 .
.
Ž 9.
The numerator of Eq. Ž9. gives the prior probability that with a smart policy maker, outcome I occurs. The denominator gives in addition the probability that with a dumb policy maker, outcome I occurs. After the policy maker has received his signal, but before the adviser has received her signal, the probability that outcome I occurs is: Prob Ž X s 1, e q m s 2 h < S, sGP . s
1 8
1
2 Ž 1 q p . q aŽ 1 y p 2 . .
8
Ž 10 .
II. X s 1 n e q m s 0 From this outcome, voters can infer that m s h or m s yh, and that the signal set is sGP , sGA 4 or sGP , s BA 4 . From Bayes’ rule, it follows that
pˆ P Ž X s 1, e q m s 0 < S . s
p Ž 1 q p . q ap Ž 1 y p . 1qp 2 qa Ž1yp 2 .
.
Ž 11 .
The probability that outcome II occurs is Prob Ž X s 1, e q m s 0 < S, sGP . s
1 4
1
Ž 1 q p 2 . q a Ž 1 y p 2 . . Ž 12 . 4
III. X s 1 n e q m s y2 h From this outcome, voters can infer that m s yh, and that the signal set is sGP , sGA 4 or sGP , s BA 4 . Consequently, voters know that the policy maker is dumb:
pˆ P Ž X s 1, e q m s y2 h < S . s 0.
Ž 13 .
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The probability that this outcome occurs is Prob Ž X s 1, e q m s y2 h < S, sGP . s
1
1
2 2 Ž 1 y p . q aŽ 1 y p . . 8 8 Ž 14 .
IV. X s 0 When the status quo is maintained, voters can infer that either the policy 1 maker has received signal s BP , which occurs with probability , or that the 2 signal set is sGP , s BA 4 . The probability that the signal set is sGP , s BA 4 and 1 X s 0 is equal to Ž1 y a .Ž1 y p 2 .. If s BP has induced X s 0, no informa2 tion becomes available about the policy maker’s competency. In contrast, the signal set sGP , s BA 4 contains information about the policy maker’s competency. The reason is that the signal set sGP , s BA 4 excludes the possibility that both the policy maker and the adviser are smart. For, if both the policy maker and the adviser were smart, they would receive the same signal. Hence, Bayes’ rule implies: 1
pˆ P Ž X s 0 < S . s
2
pq Ž1ya . 1
1 q
2 s
2
1 2
Ž1yp 2 .
p Ž1yp . 1yp 2
Ž1ya . Ž1yp 2 .
p 1q Ž1ya . Ž1yp .
.
Ž 15 .
Ž1ya . Ž1yp 2 . .
Ž 16 .
1q Ž1ya . Ž1yp 2 .
The probability that outcome IV occurs is Prob Ž X s 0 < S . s
1
1 q
2
2
The policy maker’s strategy posited in Lemma 1 implies that if the signal set is sGP , s BA 4 , the policy maker chooses X s 1 with probability a and chooses X s 0 with probability 1 y a . With 0 - a - 1, the policy maker must be indifferent between choosing X s 1 and choosing X s 0 if the signal set is sGP , s BA 4 . From Eqs. Ž9., Ž11. and Ž13., it follows that
pˆ P Ž X s 1, sGP , s BA 4 < S . s
1 2p Ž 1 q p . q 2 ap Ž 1 y p . 2 Ž1qp . qa Ž1yp .
4 q
1 p Ž 1 q p . q ap Ž 1 y p . 2
1qp 2 qa Ž1yp .
,
Ž 17 .
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which should be equal to Eq. Ž15.. After multiplying Eqs. Ž15. and Ž17. by Ž1 q p ., it is easy to show that this requires
as
1 y 2p 2 2yp 2
Clearly, when p G
.
(
Ž 18 . 1
, the policy maker always chooses X s 0 if the 2 signal set is sGP , s BA 4 . Using Eqs. Ž9. – Ž16. and Ž18., it is also straightforward to show that pˆ P Ž X s 1 < sGP , sGA 4 , S . ) pˆ P Ž X s 0 < sGP , sGA 4 , S . . I Lemma 2. Under a secret decision procedure, the expected posterior probability that the policy maker is smart, giÕen that he receiÕes signal sGP , is higher than the prior probability that the policy maker is smart. Proof. By definition: Prob Ž sGP . pˆ P Ž sGP , S . q Prob Ž s BP . pˆ Ž s BP , S . s p . Eq. Ž15. implies that pˆ Ž s BP , S . - p . Furthermore, ProbŽ sGP . s ProbŽ s BP . 1 s . Hence, pˆ Ž sGP , S . ) p . I 2 Lemma 3. When the policy maker chooses an open decision procedure, denoted by O, he chooses X s 1 if and only if the signal set is {sGP , sGA }. Proof. To prove Lemma 3, again I first derive the posterior probabilities that the policy maker is smart, given the posited strategy. The posterior probabilities that the policy maker is smart for the three possible outcomes when the policy maker chooses X s 1 and the probabilities that these outcomes occur are given by Eqs. Ž9. – Ž14. with a s 0. There remain two other possible outcomes. IV. X s 0 n s BP In this case, voters do not learn anything about the policy maker’s type, so that pˆ P Ž X s 0, s BP < O . s p . Ž 19 . 1 The probability that the policy maker receives signal s BP is equal to . 2 V. X s 0 n sGP , s BP 4 From the signal set sGP , s BA 4 , voters infer that the policy maker and the adviser are not both smart. Bayes’ rule implies: p pˆ P Ž X s 0, sGP , s BA 4 < O . s . Ž 20 . 1qp
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The probability that outcome V occurs is 1 Prob Ž X s 0, sGP , s BA 4 < O . s Ž 1yp 2 . . 2 To prove Lemma 3, I have to show that pˆ P Ž X s 1 < sGP , sGA 4 , O . G pˆ P Ž X s 0 < sGP , sGA 4 , O .
Ž 21 . Ž 22 .
and
pˆ P Ž X s 0 < sGP , s BA 4 , O . G pˆ P Ž X s 1 < sGP , s BA 4 , O . .
Ž 23 .
From the posterior probabilities that the policy maker is smart for the three possible outcomes when X s 1, and the probabilities that these outcomes occur, it follows that p Ž1qp . pˆ P Ž X s 1 < sGP , sGA 4 , O . s , Ž 24 . 1qp 2 which is equal to
pˆ P Ž X s 0 < sGP , sGA 4 , O . s pˆ P Ž sGP , sGA 4 < O . 1 p 2 q p Ž1yp . 2 s 1 1 2 2 p q p Ž1yp . q Ž1yp . 2 2 p Ž1qp . s . Ž 25 . 1qp 2 Hence, Eq. Ž22. is satisfied. Furthermore, 1 p p 1 2p Ž 1 q p . pˆ P Ž X s 1 < sGP , s BA 4 , O . s q s , 2 4 Ž1qp . 2 1qp 1qp Ž 26 . which is equal to Eq. Ž20.. Hence, Eq. Ž23. is also satisfied. Because the expected posterior probabilities that the policy maker is smart do not depend on his decision about the project, the policy maker maximizes his chances of re-election by choosing X s 1 if the project is expected to benefit society, and by choosing X s 0 otherwise. I Lemma 4. Under an open decision procedure, the expected posterior probability that the policy maker is smart, giÕen that he has receiÕed signal sGP , is equal to the prior probability that the policy maker is smart. Proof. The proof directly follows from Eqs. Ž9. – Ž14. with a s 0, and Eqs. Ž20. and Ž21.. I
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Proposition 1. The policy maker prefers a secret decision procedure to an open one. Proof. Proposition 1 follows directly from Lemmas 2 and 4.
I
3.2. The intuition We have formally derived above that in our model, the policy maker prefers a secret decision procedure to an open one. The simplest illustration why the policy maker favors a secret decision procedure is provided when p G 1r2 . In this case, under both decision procedures, the project is undertaken only if the signal set is sGP , sGA 4 . The only difference between the two procedures is then that under an open decision procedure, voters may observe that the policy maker and the adviser disagree, while in a secret decision procedure, voters do not. The policy maker favors a secret decision procedure, because it conceals disputes. The reason that the policy maker do no want voters to observe disputes, is that from disputes, voters learn that the policy maker and the adviser cannot be both smart. For, if both the adviser and the policy maker were smart, they would agree on the project. Consequently, disputes induce voters to revise the probability that the policy maker is smart downwards. Although the objective of the above analysis is to provide an explanation why policy makers are obsessed with secrecy, it has also two normative implications. First, under a secret decision procedure, voters obtain less information about the policy maker’s ability than under an open decision procedure. Clearly, this distorts the selection of the most competent policy maker. Second, secrecy may induce policy makers to undertake projects that are expected to hurt society. This happens if p - 1r2 . Then, the policy maker sometimes implements the project although the adviser has received a bad signal, implying that the expected net benefit of the project is negative. The lower is the prior probability that the policy maker is smart, the higher is the probability that the policy maker undertakes a project, which is undesirable from a social point of view. So far we have assumed that the adviser reports the signal she has received to the policy maker. However, the adviser may also have incentives to behave strategically. Suppose that the adviser, like the policy maker, tries to convince outside evaluators of her competence. As argued above, this gives an incentive to the adviser to prevent voters from observing disputes. Because a secret decision procedure conceals conflicts, under a secret decision procedure, the adviser has no incentive to lie to the policy maker about the signal she has received.6 Things are different under an open decision procedure. An adviser who knows that the policy maker has observed signal sGP maximizes her expected posterior probability that
'
'
6
Of course, the policy maker and the adviser will say to voters that they have received the same signals.
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she is smart by pretending that she has received the same signal. In the game theoretical literature, this is referred to as herd behavior Žsee Scharfstein and Stein, 1990.. Clearly, herd behavior renders consulting advisers senseless. In fact, the prevention of herd behavior can be regarded as a normative reason for secret decision procedures. 4. The selection of an adviser In Section 3, I have shown that reputational concerns induce the policy maker to adopt a secret decision procedure. In this section, I show that reputational concerns may induce the policy maker to select an adviser in — from a social standpoint — an inefficient manner. Suppose that after the policy maker has received his signal, he can choose between consulting an adviser who may receive an informative signal about e and consulting an adviser who may receive an informative signal about m. In Section 3, we have derived that by consulting the latter adviser, the policy maker can increase the expected probability that he is smart. What is the expected probability that the policy maker is smart when he consults an adviser who receives an informative signal about e ? To answer this question, I make assumptions that are analogous to the ones I made earlier. I assume that the alternative adviser receives a signal S e g sGe , s Be 4 , where sGe means e s h, and s Be means e s yh. The adviser is smart with probability p e or dumb with probability 1 y p e , with p s p P s p A s p e. If she is smart, she receives a fully informative signal. If she is dumb, she receives an uninformative signal. In Appendix A, I show that if the policy maker acquires information about e , he undertakes the project if and only if the signal set is sGP , sGe 4 . Furthermore, I show that the policy maker is indifferent between an open and secret decision procedure, and that after he has received signal sGP , the expected posterior probability that he is smart is equal to p .7 So a policy maker who maximizes the expected posterior probability that he is smart chooses for consulting an adviser who shares his own expertise.8 What is the reason for this result? When the policy maker and his adviser have different expertises, their signals do not provide information about the policy maker’s ability. For, it is well possible that the project is favorable with respect to m , but unfavorable with respect to e . Consequently, the policy maker has no reason to conceal disputes. However, the policy maker does not benefit from an adviser who agrees with him either. In terms of reputation, there are no benefits from consensus. When the policy maker consults an adviser who shares his own expertise, there is a ‘‘sharing the blame effect’’. In case the outcomes of the project are weakly unfavorable, voters tend to 7 8
The proofs of these results are in Section 3 of this paper. When the policy maker cares about re-election, this result requires that < p < is small.
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believe that m s h and e s yh. For, there are two experts who agree that e s yh. It is worth noticing that from a social point of view, the policy maker should consult the adviser who receives a signal about e . The reason is that in the model, the amount of uncertainty about m is equal to the amount of uncertainty about e . From this perspective, the policy maker is indifferent between consulting an adviser who receives a signal about m and an adviser who receives a signal about e . However, through his signal, the policy maker obtains information about m. This reduces the social benefits of an adviser who receives a signal about m. 5. Conclusions This paper aims at gaining insight into the way office-motivated policy makers reach decisions under uncertainty. Let me summarize my two main results. First, reputational concerns induce the policy maker to adopt a secret decision procedure. The reason is that disputes between the policy maker and experts damage the policy maker’s reputation. Second, I have shown that reputational concerns induce the policy maker to consult an expert who shares his own expertise rather than an expert who has a different expertise. The reason is that support of an expert, who has the same expertise as the policy maker, implies that voters tend to believe that the policy maker is competent. The implication of these results is that the policy maker’s incentive to show his ability does not lead him to promote the interests of society. Secrecy reduces the amount of information about the policy maker’s ability. Consequently, secrecy increases the probability that incompetent policy makers remain in office. Moreover, I have pointed out that the policy maker’s incentive to consult an adviser who shares his own expertise increases the probability that projects are implemented that hurt society. Acknowledgements I would like to thank Henry Ursprung, Robert Dur, an anonymous referee and participants at the conference on Economic Performance, Economic Policy and Political Culture for their comments. Appendix A In this appendix, I show that when the policy maker consults an adviser, who receives a signal about e , he is indifferent between an open and secret decision process, and the expected posterior probability that he is smart, conditional on signal sGP , is equal to the prior probability that he is smart.
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Suppose that the policy maker chooses X s 1 only if the signal set is sGP , sGe 4 To derive pˆ P Ž sGP ., I first derive the posterior probabilities that the policy maker is smart for the four possible outcomes of the game. I. X s 1 n e q m s 2 h From this outcome, voters infer that the policy maker has received the correct signal. Bayes’ rule implies:
pˆ P Ž X s 1, e q m s 2 h . s
2p
.
1qp
Ž A1.
The probability that outcome I occurs is 1
Prob Ž X s 1, e q m s 2 h < sGP . s
2 Ž 1qp . .
8
Ž A2.
II. X s 1 n e q m s 0 From this outcome, voters infer that either the policy maker or the adviser has received the correct signal. Bayes’ rule implies: 1 1 2p p pˆ P Ž X s 1, e q m s 0 . s 0 q s . 2 2 1qp 1qp
Ž A3.
The probability that outcome II occurs is Prob Ž X s 1, e q m s 2 h < sGP . s
1 4
Ž 1yp 2 . .
Ž A4.
III. X s 1 n e q m s y2 h From this outcome, voters infer that the policy maker has received the wrong signal, so that
pˆ P Ž X s 1, e q m s y2 h . s 0.
Ž A5.
The probability that outcome III occurs is Prob Ž X s 1, e q m s y2 h < sGP . s
1 8
2 Ž 1yp . .
Ž A6.
IV. X s 0 From this outcome, voters cannot infer information about the policy maker’s type, implying:
pˆ Ž X s 0 . s p .
Ž A7.
The probability that outcome I occurs is Prob Ž X s 0 < sGP . s
1 2
.
Ž A8.
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From Eqs. ŽA1. – ŽA6., it directly follows that pˆ P Ž X s 1. s p . Because pˆ P Ž X s 1. s pˆ P Ž X s 0., the policy maker has no incentive to undertake the project if the signal set is sGP , s Be 4 . Moreover, pˆ P Ž sGP , sGe . s pˆ P Ž sGP , s Be . implies that the policy maker has no incentive to conceal conflicting signals.
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