Andrea Ichino
email: andrea.ichino@unibo.it

Gerd Muehlheusser
email: gerd.muehlheusser@uni-bielefeld.de

Elena Argentesi

Heski Bar-Isaac

Esther Brügger

Pascal Courty

Winand Emons

Armin Falk

Eberhard Feess

Simon Lörtscher

Niko Matouschek

Mar- Garet Meyer

Massimo Motta

Andreas Roider

Asa Rosen

Karl Schlag

Klaus Schmidt

Kathy Spier

Eyal Winter

How often should you open the door? Optimal monitoring to screen heterogeneous agents

Keywords: D2, D8, M5 Monitoring, probation, screening, asymmetric information D2, D8, M5 Monitoring, probation, screening, asymmetric information

This paper shows that monitoring a partner too much in the initial phase of a relationship may not be optimal if the goal is to determine his loyalty to the match and if the cost of ending the relationship increases over time. The intuition is simple: by monitoring too much we learn less about how the partner will behave when he is not monitored. Only by giving to the partner the possibility to mis-behave might he be tempted to do it, and only in this case is there a chance to learn his type at a time where separation would be possible at a relatively low cost.

A c c e p t e d M a n u s c r i p t 1 Introduction

The need to test the reliability of potential partners at the beginning of a project is a feature typical of many human relationships, not only those of an economic nature. This need is particularly strong in the frequent cases in which, once the project starts, a separation from unreliable partners becomes more difficult. It is therefore not surprising that many partnerships feature, either explicitly or implicitly, an initial period of "probation" in which the persons involved monitor each other and decide, before it is "too late", whether to go on with the relationship. What is perhaps more surprising is that monitoring partners permanently during these probation periods may not be optimal, and in this paper we want to show why.

The intuition is simple. Consider an engagement before marriage in which the woman wants to test the loyalty of the potential husband (or vice versa if you prefer). A simplification not too far from reality is to assume that there are two types of men: those who will never betray their partner and those who instead might fall to the temptation of a love affair if an attractive occasion materializes. In order to find out which type of men the potential husband is, the fiancee might try to spend as much time as possible with him, monitoring him closely in all his daily and night activities. In this way she would apparently learn a lot about him, but effectively she would not learn the most important thing to be learned, which is how the potential husband behaves when, as during marriage, he is not monitored continuously. Only by giving the partner the possibility to mis-behave might he be tempted to do it, and only in this case could his type possibly be revealed when separating would still be feasible at low cost.

A similar situation characterizes labor market contracts where probation-1 A c c e p t e d M a n u s c r i p t ary periods are often specified explicitly. Note that the distinctive feature of these periods is not to make monitoring possible, but to be periods in which allow firing at a relatively low cost. Even when probation is not explicitly foreseen in a contract, various reasons (e.g. sunk costs or investments in job specific human capital) make it easier to fire a worker earlier in a career rather than later. In all these cases we argue that too much monitoring at the beginning of the relationship is not optimal because it prevents the firm from learning how the worker behaves when she is not monitored. As in the case of the engagement before marriage, the firm is typically interested in discriminating between two types of potential employees: those who are "unconditional cooperators" and who therefore exert a maximum level of effort in all instances and those who are instead "rational shirkers" and who would therefore indulge in laziness if the cost of effort is high and the probability of detection sufficiently low. 1 Inasmuch as the "rational shirkers" can mimic the behavior of the "unconditional cooperators" during probation, continuous monitoring ("keeping the office door always open") is suboptimal because the probability of detection would be too high and the "rational shirker" would never concede to the temptation of being "lazy". As a result the two types of workers would be observationally identical during probation, and only when firing becomes costly would the true types be revealed. On the contrary, random monitoring ("opening the door not too often and with no specific pattern") might be more revealing because the "rational shirker"

1 The distinction between those two types of agents is consistent with findings in a recent empirical literature: For example, [START_REF] Nagin | Monitoring, motivation and management: The determinants of opportunistic behavior in a field experiment[END_REF] analyze data from a field experiment in which the monitoring rate is varied to see how individuals react to it in terms of shirking. They find that although there are many "rational shirkers", a significant proportion of agents does not take advantage when the monitoring rate goes down and can thus be classified as "unconditional cooperators". In a similar vein, [START_REF] Ichino | The effect of employment protection on worker effort: Absenteeism during and after probation[END_REF] compare the absenteeism rate of newly hired workers during and after probation in a large Italian bank; 42% of them are never absent while among the others an increase in absenteeism is observed on average when incentives change at the end of probation.

2

A c c e p t e d M a n u s c r i p t would be induced to take a chance to be lazy. Thus, only in this case would there be a chance that the two types of workers might be caught behaving differently. 2 Also in the case of trading between firms, and in general between "buyers" and "sellers", the same type of result might apply. Most firms write long-term contracts with other firms to obtain inputs for their production process. The selection of partners for the provision of inputs may be subject to a trial period similar to the one that characterizes labor or marriage contracts. What this paper suggests is that these periods would be totally uninformative about the reliability of the trading partners if the buyer announced his willingness to monitor extensively the quality of the input acquired during trial. If the unreliable sellers knew that they would be fully monitored during trial, they would try to make their product indistinguishable from the product of reliable sellers. However, this would offer no guarantee that the product would be of high quality after the long-term contract is signed.

Note that our argument apply not only to long-term relationships but is also relevant for one-shot interactions in which the reliability of a partner is so important that it becomes crucial to test it before the main interaction starts, in order to screen out "bad types" from "good types".

There is an interesting link between the mechanism highlighted in our paper and the recent growing literature on how economic incentives may "crowd out" intrinsic motivation. 3 In this line of research, as well as in our paper, a 2 A framework in which it is unclear ex ante whether the right partner is chosen is also analyzed in Watson (1999Watson ( ), (2002)). As in our paper, some of the potential partners are cooperators, while others are more opportunistic and would cheat whenever they find it profitable to do so. In equilibrium, interaction starts with small stakes only, while stakes are increasing over time as more information about the partner is revealed. Contrary to our paper, the role of monitoring is not considered, and therefore these models suggest an alternative channel ("gradualism") through which large losses from doing business with the wrong partner can be avoided.

A c c e p t e d M a n u s c r i p t principal's use of monitoring and control to create effort incentives may be counterproductive. The literature has identified adverse effects of monitoring "good types" whose intrinsic motivation may be reduced by the feeling that the principal does not trust them, believing that explicit incentives are necessary to induce an effort that they would have been happy to exert in any case. Our paper, instead, focuses on the negative effect of monitoring on opportunistic "bad types" who are induced to mimic "good types", which in turn hinders their detection.

In order to focus on the specific intuition that motivates our paper, we abstract from crowding-out aspects and assume that "good types" are indifferent to monitoring and control. Under this assumption, we analyze formally in Section 2 under what conditions principals can expect to be successful in filtering out unreliable partners during probation and what are the potential gains from setting the monitoring intensity optimally. Section 3 will relate and contrast our claim with other possible theories of the relationship between monitoring and productivity, including the above-mentioned literature on crowding-out. Section 4 concludes. All proofs are in the Appendix available on the JEBO website.

The model 2.1 Basic setup

We consider one principal facing N ≥ 1 agents in a relationship lasting at most two periods i = 1, 2. Period 1 is a probation period while period 2 is the time after probation. In each period, agents can choose an action from {E, S} where E and S denote "exerting effort" and "shirking", respectively.

and [START_REF] Falk | Distrust: The hidden cost of control[END_REF]; see also our discussion in section 3.4.

A c c e p t e d M a n u s c r i p t

A shirking agent produces 0 output, while, when exerting effort, each agent produces v i in period i. We have in mind situations in which the output of an agent's effort in period 1 is negligible compared to period 2, and thus we assume v 1 = 0 and v 2 > 0. 4 We interpret v 2 as a Net Present Value, thereby allowing period 2 to be of any length relative to the probation period. In particular, period 2 could last for some time so that v 2 would reflect the overall discounted output in a long-term relationship, or period 2 could be short, indicating, for example, that the principal benefits from the effort of the agent only at a single (but maybe particularly important) occasion.

Although all agents are equally valuable to the principal when exerting effort, they differ with respect to the (privately known) cost of doing so, which is represented by a parameter θ ∈ {G, B}: "bad types", denoted by B, have effort costs c i in period i, where c 1 = c, c 2 = k • c with k > 0, and where c is drawn from an atomless distribution H(c) ∈ C 2 with support [0,1] at the beginning of the game. 5 The parameter k is simply a proportionality factor that allows for appropriately adjusting and discounting effort costs with respect to the length of period 2 relative to period 1. Furthermore, k might also reflect potential differences in the intensity of effort required during and after probation. On the other hand "good types", denoted by G, do not face any costs of exerting effort. 6 In the population of agents, the shares of good and bad types are α and (1 -α), respectively, where 0 < α < 1. Concerning the informational environment, we assume that each agent privately learns his type at the beginning of the game and that α and 4 Assuming v 1 > 0 instead would not affect our results qualitatively; see section 3.1. 5 Our approach is isomorphic to a model with a continuum of types (cost realizations), where the type distribution has an atom at 0.

6 As explained in the Introduction, this view is for example broadly confirmed in a field experiment reported in [START_REF] Nagin | Monitoring, motivation and management: The determinants of opportunistic behavior in a field experiment[END_REF]. Alternatively, we could assume that good types face effort costs that are lower on average than those of bad types. This would not change our arguments qualitatively.

5

A c c e p t e d M a n u s c r i p t

H(•) are common knowledge.
Period 1 is a probation period in which the principal can monitor each agent at no cost.7 His choice variable is thus a monitoring frequency q ∈ [0, 1]. The outcome of the monitoring process is captured by a variable M ∈ {E, S, 0} where M = E and M = S perfectly reveal whether or not shirking has occurred, while M = 0 denotes the case where an agent has not been monitored. In line with most of the literature, we assume that the principal is able to commit to her chosen monitoring rate.8

After observing the outcome of the monitoring process and updating his beliefs appropriately by use of Bayes' rule, the principal makes a firing decision F ∈ {0, 1}, where F = 1 means that an agent is fired. Firing costs in the trial period are zero, while in the second period they are prohibitively high.9

It is assumed that the population out of which the N agents are drawn is sufficiently large such that, upon monitoring one agent, no inference can be made about the pool composition of the remaining N -1 agents.

As for payments, we denote by t i the transfer from the principal to each A c c e p t e d M a n u s c r i p t agent. During probation, the transfer t 1 could in principle be set equal to zero, although in most situations it would be natural to imagine that some kind of "show-up fee" t 1 > 0 is paid to the worker independently of the probation outcome. In the case of period 2, if the worker is hired at the end of probation, he cannot be fired later in the sense that he is in any case entitled to a transfer t 2 > t 1 independently of his performance. We also make the following assumption:

Assumption 1. v 2 > t 2 ≥ 1,
which implies that the payoff for the principal from each agent who exerts effort in period 2 is positive (v 2 > t 2 ). Furthermore, as explained below, t 2 ≥ 1 implies that in period 1, exerting effort is privately optimal for a bad agent for any value of c when he is monitored with certainty.

Given Assumption 1, and coming back to the firing decision, we want the principal to wish to continue with an agent when his belief after the monitoring process is greater or equal to the prior α. 10 This will imply that the following assumption must hold:

Assumption 2. α • (v 2 -t 2 ) + (1 -α) • (-t 2 ) > 0.
Summarizing, the game has the following stages:

• At stage 0, each agent's type is determined by a nature's move and is only known to the agent.

• At stage 1, the principal sets and commits to a monitoring probability q for the probation period.

10 We can alternatively assume that an agent cannot be fired without being monitored. This would for example be consistent with unjust-dismissal legislation in the US; see [START_REF] Krueger | The evolution of unjust-dismissal legislation in the United States[END_REF].

A c c e p t e d M a n u s c r i p t

• At stage 2, period 1 begins and each agent independently decides on whether or not to exert effort. After the effort choice is made, each agent is monitored with probability q.

• At stage 3, given the outcome of the monitoring procedure, the principal decides on which agents to fire. After the firing decision period 1 ends.

• At stage 4, in period 2, all remaining agents again decide on whether or not to exert effort. Then the game ends.

Equilibrium analysis 2.2.1 Effort choice in period 2

Let us start the analysis of the game at stage 4, and denote by a θ i ∈ {E, S} the action chosen by type θ ∈ {B, G} in period i = 1, 2. Equilibrium values carry an asterisk * . We start with a good type. Since he has no effort costs, he is indifferent between exerting effort and shirking (both actions yield a payoff of t 2 ). Throughout we assume that both types exert effort when indifferent, so that good types will always choose a G * 2 = E in period 2.11 Contrary to that, in period 2, a bad type gets (t 2 -k • c) from choosing E and t 2 from choosing S, so bad types will always shirk in period 2 (i.e. a B * 2 (c) ≡ S ∀c > 0).

Firing decision

Let us now look at the principal's optimal firing decision at stage 3 after monitoring has been carried out. Denote by β ∈ [0, 1] the belief of facing a good type conditional on the outcome of the monitoring process:

β M := P r(θ = G | M ) ∀M = E, S, 0 (1)
A c c e p t e d M a n u s c r i p t

Of course, β 0 = α, and in (a Bayesian perfect) equilibrium, whenever possible, beliefs have to be consistently derived using Bayes' rule from the equilibrium strategies of each type of agent at stage 2 (see e.g. [START_REF] Fudenberg | Game theory[END_REF]. Given that good types will exert effort while bad types will always shirk in period 2, the principal's expected payoff from an agent for period 2 as a function of β is given by

β(v 2 -t 2 ) + (1 -β)(-t 2 ), (2)
which may be positive or negative. It follows that the principal will fire an agent, whenever monitoring "delivers" a belief for this agent to be a good type that is sufficiently low:

F * (β) = 1 if β < t 2 v 2 0 otherwise . (3)

Effort choice in period 1

Now consider the optimal effort decision at stage 2 by each type for a given probability of monitoring q. In doing so, we directly look at the following equilibrium continuation and then see how it can be supported.

Lemma 1. At stage 2, for all q < q := 1 t 2 , there exists an equilibrium continuation in which a) each good type chooses a G * 1 = E independent of q, b) each bad types shirks whenever his realization of c is sufficiently high. This happens with probability (1 -e(q)) > 0,12 c) the principal's beliefs after monitoring has been carried out are given by

β * E = α α + (1 -α)e(q)
> α (4)

β * S = 0, (5)
A c c e p t e d M a n u s c r i p t

and she optimally fires all agents for whom M = S holds and keeps all other agents (including those who have not been monitored).

For an intuition for Lemma 1, let us start with a good type. On the equilibrium path, when choosing E, he gets t 1 in period 1 and t 2 in period 2; if he is monitored, this will lead to M = E, so the principal holds the belief β * E = α α+(1-α)e(q) > α for which, by Assumption 2, F = 0 is optimal. If he is not monitored, the principal holds belief β * = α, and he is not fired either. On the other hand, when choosing S in the first period, his payoff is still t 1 since he does not save in effort costs, but with probability q, he is monitored, found to be shirking and, given belief β * S = 0, fired. It follows that his expected payoff for period 2 is only (1 -q)t 2 and, thus, a deviation is never profitable. Now consider a bad type. When choosing E, he gets (t 1 -c) in period 1. When monitoring occurs, he is taken to be a good type and thus will also get t 2 in period 2, in which he will then shirk, so that he will not again incur any cost of effort in that period. On the other hand, when choosing S, he gets t 1 in period 1 (thus saving on effort costs c), but with probability q he is found to be shirking and fired, so his expected payoff for period 2 is only (1 -q)t 2 . It follows that S is preferred iff

t 1 -c + t 2 < t 1 + (1 -q)t 2 ⇔ c > qt 2 (6)
so that the optimal decision of a bad type as a function of q and c is given by

a B * 1 (q, c) = S if c > qt 2 E otherwise (7)
(i.e. shirking occurs whenever effort costs are sufficiently high). This means that for q ≥ q := 1 t 2 , all bad types choose E independent of their cost parameter c. The threshold q relates the benefit from employment in period 10 A c c e p t e d M a n u s c r i p t 2 (t 2 ) to the maximum cost of effort during probation, which is equal to 1.

Clearly, when t 2 is relatively large, then q is low, which means that shirking in period 1 is undesirable for a bad agent given the prize at stake. Thus, even a relatively low level of q would induce all bad agents to exert effort as long as q is set greater or equal than q. In this case, shirking would no longer occur on the equilibrium path, so there would be no information transmission in equilibrium and β * E = α would hold. However, as will be shown below, it is indeed optimal for the principal to choose some q < q so that both possible actions, E and S, occur with positive probability on the equilibrium path, so there is no leeway in forming off-equilibrium beliefs. Finally, note that the principal's beliefs conditional on M are consistent with the equilibrium strategies of both types.

The principal's optimal choice of q

The optimal choice of q at stage 1, under the assumption that the equilibrium continuation as derived in Lemma 1 is played subsequently remains to be determined. Clearly, the principal's objective is to maximize her expected payoff. Let us analyze each part of it in turn.

Good Types: In period 1, there are α • N good types; none of them shirks in equilibrium, and therefore none of them is fired. Since for simplicity we assumed a negligible output during probation, they yield a negative payoff (-t 1 ) to the principal, but the important point is that this payoff is independent of the monitoring probability q. In period 2, there is again no shirking, and each of the α • N good types yields the principal (v 2 -t 2 ) > 0, which is again independent of q. This means that the choice of q neither influences the number of good types in each period nor their choice of effort. Therefore, in what follows, we can neglect the payoff accruing from good types as it will A c c e p t e d M a n u s c r i p t have no effect on the optimal level of q.

Bad Types: Recall that a bad type will shirk in period 1 whenever c > qt 2 . Thus, from the principal's point of view, the probabilities of shirking and exerting effort are given by, respectively,

s(q) := P r(c > qt 2 ) = max(0, 1 -H(qt 2 )), (8)
e(q) := P r(c ≤ qt 2 ) = min(H(qt 2 ), 1). ( 9)

Clearly we have ds dq ≤ 0, and de dq ≥ 0 and s (q) = -e (q). Since there are (1 -α) • N bad types, the expected payoff generated by them in period 1 is:

π 1 (q) := (1 -α) • N • (e(q) • (-t 1 ) + s(q) • (-t 1 )) = (1 -α) • N • (-t 1 ) (10)
because e(q) + s(q) ≡ 1. Note that this term is also independent of q. This highlights the fact that in period 1 the principal monitors workers not so much because she is interested in their output, which in this period is negligible, but mainly because she needs to detect bad workers.

In other words, from the principal's point of view, monitoring in period 1 matters only because it influences the number of bad types in period 2.

Precisely for this reason q must be set in a way that induces some shirking in period 1; otherwise no bad type would be detectable. Formally, the number of bad types in period 2 is determined as follows. Each bad type shirks with probability s(q) but is detected only with probability q so that (1 -α) • N •

(1 -q) • s(q) bad types remain in period 2. Moreover, each bad type exerts effort with probability e(q) and is thus not identified through monitoring, so

another (1 -α) • N • e(q) of them survive the probation period. Taking this together, since each bad types generates a payoff of (-t 2 ) to the principal, A c c e p t e d M a n u s c r i p t her expected payoff from the bad types in period 2 is given by

π 2 (q) := (1 -α) • N • ((1 -q) • s(q) + e(q)) • (-t 2 ) ∀q ∈ (0, q). (11)
We can therefore state the following result concerning the optimal monitoring frequency q * . Proposition 1. Given the equilibrium continuation characterized in Lemma 1, the optimal monitoring frequency for the principal induces shirking on the equilibrium path (i.e. 0 < q * < q := 1 t 2 ).

Note first that q * < q implies that the equilibrium continuation as determined in Lemma 1 also applies.

Intuitively when q is too low, only a few bad agents are identified while when q is too high, each bad agent is less likely to shirk in period 1 and thus cannot be identified through monitoring either. As bad types shirk with probability 1 in period 2 (yielding a negative payoff -t 2 < 0), too much monitoring is not in the principal's interest. Note that again this argument does not rely on monitoring costs, which are assumed to be zero, since with positive monitoring costs, the optimal monitoring rate would be even lower.

Comparative statics: Potential gains from monitoring optimally

We now analyze the potential magnitude of the gain induced by setting q optimally instead of monitoring "too often". For this purpose, we perform a comparative statics analysis w.r.t. the distribution of effort costs and consider distribution functions of the class H(c) = c n where n ≥ 1. The case n = 1 is then just the uniform distribution, and by increasing n, the function becomes more convex, and there is more probability mass on high realizations of effort costs.

13

A c c e p t e d

M a n u s c r i p t

With H(c) = c n it then follows from Eqn. ( 9) that a bad agent exerts effort during probation with probability e(q) = q n t n 2 for all q < q so that from Eqn. (11) the objective function of the principal can be written as max

q π 2 (q) = (1 -α) • N • (1 -q + q n+1 t n 2 ) • (-t 2 ). ( 12
)
Therefore the FOC is q n t n 2 (n + 1) -1 = 0 and the optimal monitoring rate is then given by

q * (n, t 2 ) = 1 t 2 n 1 n + 1 . ( 13
)
This leads to the following result.

Proposition 2. The optimal monitoring rate q * (n, t 2 ) is strictly increasing

in n satisfying lim n→∞ q * (n, t 2 ) = 1 t 2 (= q).
Intuitively, when more and more probability mass is shifted towards high realizations of effort costs, more shirking takes place during probation, making monitoring more effective at the margin. Note, however, that for any finite n, the optimal monitoring rate is bounded from above by q ≤ 1 such that it is never optimal for the principal to monitor with probability 1. In the limit, when virtually all mass is on the highest realization c = 1, if the monitoring rate were q ≥ q, all bad agents would prefer to exert effort so that the principal would not learn anything at all. However, just slightly reducing the monitoring rate below q would induce shirking with probability 1 so that the principal would learn a lot.

Using these results, we now show that, for n large, reducing q just slightly below q will also make a big difference to the principal in terms of profit. As a benchmark, we take the case where monitoring is excessive (q ≥ q), which, in terms of profits for the principal, is also equivalent to the case q = 0. In both cases, she does not detect any of the bad agents, so her expected payoff A c c e p t e d M a n u s c r i p t from these bad agents in period 2 is a pure loss equal to

π 2 (q = 0) = π 2 (q ≥ q) = (1 -α) • N • (-t 2 ) < 0. ( 14
)
On the other hand, when q * is chosen instead, the probability that a bad type remains in period 2 is strictly less than 1 and given by 1 -q * • s(q * ) < 1.

Thus, the principal is able to filter out at least some of the bad types so that the loss caused by the remaining bad agents is

π 2 (q = q * ) = (1 -α) • N • (1 -q * • s(q * )) • (-t 2 ). ( 15
)
By taking the difference between ( 15) and ( 14), her absolute gain from choosing the optimal "interior" monitoring rate q * compared to monitoring excessively at some q ≥ q is:

∆π := π 2 (q = q * ) -π 2 (q ≥ q) = (1 -α) • N • (-q * • s(q * )) • (-t 2 ) > 0, ( 16
)
which can be usefully expressed in percentage terms as

∆π % := ∆π |π 2 (q = 0)| = q * • s(q * ). ( 17
)
With H(c) = c n and q * (n, t 2 ) as determined in Eqn. ( 13), this leads to the following result.

Proposition 3. The percentage gain for the principal from monitoring optimally is strictly increasing in n satisfying lim n→∞ ∆π % = 1 t 2 (= q).

When high realizations of effort costs become more likely, bad agents prefer to shirk more often for a given monitoring rate. We have seen in Proposition 2 that in this case, the principal prefers higher monitoring rates so that, while always remaining positive, the "distance" between q and q * A c c e p t e d M a n u s c r i p t decreases. As Proposition 3 shows, while the difference q -q * (n) is decreasing in n, the gain for the principal from choosing q * instead of q is increasing in n (i.e. there is a lot to be gained for the principal by not monitoring too much when there is a lot of probability mass on high realizations of effort costs). In the limit, when n becomes very large, the difference between q and q * becomes arbitrarily small, but the gain for the principal is maximum: at q = q -, the principal induces shirking with probability 1, so that monitoring is highly effective, while at q = q, all bad agents exert effort so that monitoring is useless. Thus, as high realizations of effort costs become more likely, reducing the monitoring rate just by "an " might have a strong effect on profits, and this effect is maximum when t 2 is small. It is in such situations where we would expect probation periods to be particularly useful for the principal.

For the extreme case where, in addition to n → ∞, also t 2 → 1, it can be shown that the principal would detect all bad agents with probability one.

Discussion

In the setting described above, monitoring during probation serves as a screening device that increases profits inasmuch as it allows the principal to identify and fire shirkers before this becomes too costly or even impossible. This is, however, not the only mechanism through which monitoring may affect profits. In this section we briefly discuss alternative mechanisms, contrasting them with the one identified by our paper.

Effect of monitoring on productivity during the monitoring period

One immediate modification of the basic model allows for a non-zero output in the probation period. In the simplified setting of section 2, monitoring has

Page 19 of 34

A c c e p t e d M a n u s c r i p t no effect on productivity during probation simply because, by assumption, work done by agents in this period has no value for the principal.

It is straightforward to show that if v 1 > 0 instead, our argument survives as long as v 1 is not too large. From Eqn. (10), the expected payoff of the principal for period 1 becomes

π 1 (q) = (1 -α) • N • (e(q) • (v 1 -t 1 ) + s(q) • (-t 1 )), (18)
which is increasing in q, since e (q) > 0. Clearly, while increasing the optimal monitoring intensity, as long as output during the probation period is not too important to the principal, the effect we emphasize remains.

More subtle is instead the contrast with the results by [START_REF] Cowen | More monitoring induces less effort[END_REF] and [START_REF] Dubey | Competitive prizes: When less scrutiny induces more effort[END_REF] who show that less monitoring might induce agents to exert more effort during the monitoring period such that a principal benefits from having a "less accurate picture" about an agent's behavior.

In the first paper, an agent trying to exceed a given threshold, such as passing an exam, might exert more effort when he is monitored with low frequency only. For example, the principal announces that there will not be an exam question on each topic covered in class. The reason is that with fewer questions, the risk of failing is higher when the student has not studied the whole material. In the second paper, the principal wants to induce maximum effort by all agents. Agents have different skills and are monitored at random.

The agent with the highest observed output receives a prize. To give the low ability agents incentives to exert effort also, the principal has an interest in keeping the sample of observations small (i.e. to monitor less often) since large samples would tend to favor high ability agents as they are more likely to produce a high output.

A c c e p t e d M a n u s c r i p t levels, the principal strictly prefers q = 1 because of the higher productivity of (shirking) agents.

Thus, whenever the optimal monitoring intensity is given by q * * (a), the optimal monitoring intensity tends to be higher compared to the basic model, but it is again not excessive in the sense that it does not prevent shirking overall since the selection motive still matters to the principal.

At a more general level, which purpose of monitoring prevails in a given context clearly depends on whether the heterogeneity of types tends to be exogenous and persistent, in which case screening becomes the main objective for the principal (as in our framework), or whether the principal can somehow influence the degree of heterogeneity over time such that learning or habit formation become more relevant. In our view, nothing seems to suggest that the screening purpose of monitoring should in principle be less relevant to the principal than these alternative purposes.

Endogenous pool of agents ex ante

A further potentially beneficial effect of a high monitoring frequency is suggested by Wang and Weiss (1998) who show that the prospect of being monitored intensively can deter potential shirkers workers from applying for the job.14

Note first that in our model the parameter α (i.e. the fraction of good types in the agent pool) can be interpreted as a proxy for the usefulness of the screening process of applicants. Obviously, from Eqn. ( 11), the principal's equilibrium payoff is increasing in α.

Moreover it is also straightforward to extend our basic model to allow

A c c e p t e d M a n u s c r i p t

for an endogenous pool of agents: Assume that, prior to the effort choice, an agent can also choose whether or not to accept the job at all or quit, in which case she gets her reservation payoff W .

From the incentive condition ( 6), an agent prefers to shirk in period 1 if c > c := qt 2 . In this case his payoff along the equilibrium path is t 1 +(1-q)t 2 , and thus he will not quit in the first place as long as his outside option W is sufficiently small. Define the critical level W such that an agent with effort cost c > c is indifferent between quitting and shirking by

W = t 1 + (1 -q)t 2 . ( 21
)
He will thus prefer to quit for all W > W , and since d dq W = -t 2 < 0, a higher monitoring intensity tends to induce more agents with high effort costs (who would otherwise shirk) to refrain from working for the principal. Therefore, as in section 3.2, the consideration of the mechanism considered by Wang and Weiss shifts the tradeoff in favor of more monitoring with respect to what implied by the basic version of our model. However, note that even in this case, our intuition would still apply inasmuch as some residual heterogeneity in the propensity to shirk remains in the pool of hired agents. 15Moreover, in a world in which both mechanisms coexist, it is also interesting to consider their interaction. In this case, the principal's ex ante commitment to excessive monitoring during probation to deter bad applicants may be time-inconsistent when the screening process is not perfect and the firm hires bad workers in equilibrium. The principal would still have an obvious incentive to reduce monitoring during probation, as suggested by our paper, in order to identify the remaining bad agents before the relevant productive activity starts. This reasoning leads to the preliminary conclu-A c c e p t e d M a n u s c r i p t sion that workers should be sceptical about a principal's announcement of excessive monitoring when it is clear that if the principal maintained the commitment, she would not learn anything about the potential shirkers possibly still present among workers under probation.

Crowding-out of intrinsic motivation

Thus far we have maintained the assumption that only bad types react to the monitoring intensity, while the behavior of the good and intrinsically motivated types remains unaffected. This is in contrast to a large recent literature on the interaction of psychological and economic incentives arguing that the latter might crowd-out intrinsic motivation. 16The underlying rationale for such dysfunctional responses is that explicit incentives may convert a human relationship into a purely economic one, and that this may reduce intrinsic motivation and behavior based on fairness. More concretely, it has been argued that economic incentives, in particular small ones, might simply insult individuals, and this may give rise to a non-monotonic relationship between economic incentives and performance [START_REF] Gneezy | The W effect of incentives[END_REF]Rustichini 2000b and[START_REF] Gneezy | The W effect of incentives[END_REF]. Moreover, economic incentives might provide new information concerning the importance or cost of an individual's activity [START_REF] Gneezy | The W effect of incentives[END_REF]Rustichini 2000a and[START_REF] Benabou | Intrinsic and extrinsic motivation[END_REF][START_REF] Benabou | Intrinsic and extrinsic motivation[END_REF]. Finally, economic incentives might not be in accordance with social norms of cooperation, fairness or trust [START_REF] Fehr | Detrimental effects of sanctions on human altruism[END_REF][START_REF] Fehr | The hidden costs and returns of incentives-Trust and trustworthiness among CEOs[END_REF]and Sliwka 2007).

With respect to the intensity of supervisors' control in human relationships, [START_REF] Frey | Does monitoring increase work effort? The rivalry with trust and loyalty[END_REF] and [START_REF] Falk | Distrust: The hidden cost of control[END_REF] suggest that individuals might A c c e p t e d M a n u s c r i p t perceive control as a signal of distrust to which they respond with low effort.

In such situations, a principal might benefit from foregoing the possibility to control agents too intensely.

In terms of our model, when such motives are present, then the behavior of the good types, which are intrinsically motivated, could be negatively affected by the monitoring intensity, while we have assumed that they are indifferent to monitoring. Clearly, in such an augmented framework, there would then be two reasons for principals not to monitor excessively: Not only would it induce bad types to make themselves non-identifiable during probation (as pointed out in our paper), but it might also reduce the intrinsic motivation to exert effort of the good types. In the light of these arguments, our result could then be interpreted such that excessive monitoring is not optimal for a principal even if crowding-out of intrinsic motivation is not a concern. When it is, then the optimal monitoring intensity would tend to be even lower.

Conclusion

We have shown in this paper that monitoring a partner too much in the initial phase of a relationship may not be optimal if the goal is to determine her loyalty to the match and if the cost of terminating the relationship increases over time. If too much monitoring induces the partner to behave well even if her inclination in the absence of monitoring would be to mis-behave, the principal does not learn what needs to be learned at the beginning of a relationship. Note that this mechanism is completely independent of the costs of monitoring, and thus the result holds even if monitoring is costless. This general intuition applies to many social relationships characterized by asymmetric information with respect to the types of agents such as for example, Furthermore, we show that the use of probation periods, together with some monitoring during such periods, is beneficial to the principal when agents' the cost of exerting effort during probation tends to be high compared to the benefit of future interaction. In this case, bad agents give in to the temptation of shirking more frequently during probation, so that monitoring is an effective tool in filtering out these agents provided that it is not too frequent. On the contrary, when the costs of effort tends to be low, our model suggests that probation would be a waste of time as a method to detect bad agents through monitoring.

Our streamlined framework allows us to derive our basic result in its purest form at the cost of some simplifications. Apart from the further potential impacts of monitoring already discussed in section 3, we have also maintained the assumption that the principal cannot use incentive schemes to screen workers or elicit effort from bad types. Clearly such schemes would be costly for the principal because of informational rents, which will tend to be the higher, the larger the heterogeneity of types. Moreover, the screening process can often not be expected to work perfectly, possibly due to institutional constraints such as in the case frequently encountered in reality where workers in same job must also get the same (fixed) wage. This is the case we consider, but our results do not qualitatively depend on it; as long as some heterogeneity of types remains after some incentive structure has been implemented, the principal would still have an incentive to use also her monitoring policy as a screening device as stressed in our paper. After all, the fact that probation periods exist in many long-term relationships of different natures hints at the difficulty of relying solely on incentive contracts as a screening device. Monitoring during probation (but not too much) is therefore needed (1 -e(q * ) + q * • e(q * ))(-t 2 ) > (-t 2 ) ⇔ e(q * ) < 1, which is true for all q * < q. Thus, the principal's payoff is strictly higher when an interior level of q is chosen.

B Proof of Proposition 2

Taking the derivative of q * (n, t 2 ) with respect to n yields d dn q * = -1 (n + 1)n 2 {n + (n + 1)(n ln t 2 + ln 1 t n 2 (n + 1) )} (24) so that it has to be shown that the term in curly brackets is negative. We proceed in two steps:

Step 1: We first show X(n, t 2 ) := (n ln t + ln 1 t n (n+1) ) < 0 for all n ≥ 1 and t 2 > 1. Note first that X(n, 1) = ln 1 1+n < 0 for all n > 0. Furthermore, we have d dt 2 (n ln t) = n t 2 . Finally,

d dt 2 ln 1 t n 2 (n + 1) = - nt n-1 2 t n 2 = - n t 2 , (25)
so that X(n, t 2 ) is in fact constant in t 2 and equal to ln 1 1+n < 0. and that Y (0) = 0 so that Y (n) < 0 for all n ≥ 0.

  23

  * ) -Z(0) > 0 ⇔

  Step 2: It has to be shown that Y (n) := n + (n + 1)X(n) < 0. Taking the derivative w.r.t. for all n > 0. It follows that Y (n) is maximum at n = 0

This literature is surveyed, among others, in[START_REF] Frey | Motivation crowding theory[END_REF],[START_REF] Gneezy | The W effect of incentives[END_REF]

Note that the mere objective of filtering out bad agents will be sufficient for our analysis, and assuming costless monitoring makes our point particularly striking. Therefore, our results are qualitatively different from the literature on law enforcement building on[START_REF] Becker | Crime and Punishment: An economic approach[END_REF] where optimal detection probabilities are typically less than one due to convex enforcement cost functions (see also[START_REF] Besanko | Antitrust enforcement under asymmetric information[END_REF] and[START_REF] Polinsky | The economic theory of enforcement of law[END_REF]).

8 Exceptions include[START_REF] Khalil | Auditing without commitment[END_REF] and[START_REF] Khalil | Catching the agent on the wrong foot: ex post choice of monitoring[END_REF] where the principal decides on her monitoring policy ex post, after agents have chosen their actions. As will become clear below, in our model, the principal would benefit from the ability to increase the monitoring rate ex post. However, from an ex ante point of view she would be better off with commitment, so credibility is an important issue for the principal to overcome this problem of time inconsistency. For example, one possibility to achieve this would be to commit only a limited amount of resources to the monitoring technology so that it would be technically unfeasible to monitor all agents at a higher rate than the announced

one. 9 All we need is that splitting becomes more costly for the principal as the length of the relationship increases, which is often the case in reality. For example, in many countries employment protection is increasing in tenure with the firm, such that the principal is interested in identifying bad agents as early as possible, in order not to remain stuck with them when firing becomes too expensive or virtually impossible. The same is true in situations of match-specific human-capital investments at the beginning of a relationship.

It suffices to assume that the expected payoff for the principal in period 2 from having a good (bad) type is positive (negative).

The exact definition of e(q) is given in Eqn. 9 below.

In their model, the productivity of agents is exogenous. The issue of mimicking, which is crucial in our framework, does therefore not arise.

Wang and Weiss confine attention to the two-type case such that, in equilibrium, only agents with high productivity apply for the job.

See for example the seminal contributions by[START_REF] Deci | Effects of externally mediated rewards on intrinsic motivation[END_REF] Titmuss (1970) in psychology and economics, respectively; for surveys see also[START_REF] Frey | Motivation crowding theory[END_REF] and[START_REF] Gneezy | The W effect of incentives[END_REF].

The second author gratefully acknowledges financial support from the Swiss National Science Foundation (grant PA001-108965) as well as the hospitality of the Management & Strategy Department at Northwestern University's Kellogg School of Management. The second author gratefully acknowledges financial support from the Swiss National Science Foundation (grant PA001-108965) as well as the hospitality of the Management & Strategy Department at Northwestern University's Kellogg School of Management. Blinded Manuscript (NO Author Details)

Both papers are static in the sense that a low monitoring rate in a given period might induce more effort and is therefore beneficial for a principal in this period. In contrast, our argument is dynamic in emphasizing the potential benefits from not monitoring extensively in early periods, inducing more shirking in these periods but serving as a screening device from which the principal benefits in later periods of a relationship.

Effect of monitoring on productivity in future periods

We now consider further channels through which monitoring in early periods may affect the principal's future payoff and that are therefore potentially countervailing the selection mechanism we are emphasizing in this paper.

In particular, we consider the case where monitoring has a positive effect on an agent's future productivity. For example, monitoring during probation might trigger a learning/training process or the formation of "good habits", both of which may increase permanently the baseline productivity of all agents including the potential shirkers. In this case, the trade-off between the advantages and disadvantages of monitoring in the first period shifts in favor of increasing monitoring and against the claim of our paper.

Consider the simplest case where the productivity of a shirking agent in period 2 is given by v S 2 (q) = a • q where a ∈ (0, t 2 ) measures the effect of monitoring in period 1 on an agent's productivity in period 2, so that our basic model with a = 0 emerges as the limiting case. 13 The payoff of the principal from a shirking agent in period 2 is then simply v S 2 (q) -t 2 = a • q -t 2 < 0, and thus the upper bound a = t 2 ensures that this payoff is still negative for all q ∈ [0, 1]; otherwise the selection motive vanishes and 13 The productivity of a non-shirking agents is still v 2 .

A c c e p t e d M a n u s c r i p t the principal never wants to fire an agent after probation.

To make our points as clearly as possible, and to get closed-form solutions, we consider the case where H(•) is uniform and where t 2 = 1 so that q * = 1 2 and q = 1 in the basic model (see Eqn. ( 13)). Then, the objective function for the principal becomes:

An interior solution will satisfy the first order condition and is given by

which is strictly increasing in a in the relevant range. This leads to the following result.

Proposition 4. As long as the beneficial effect of monitoring during probation on the productivity of shirking agents in period 2 is not too strong, the principal optimally still induces shirking on the equilibrium path. Formally, the optimal monitoring intensity is given by q * * (a) for all a ∈ (0, a) and q = 1 otherwise, where q * * (a) = q.

Note first that lim a→0 q * * (a) = 1 2 = q * , and thus our result from the basic model emerges as a limit case. Moreover, because of the additional beneficial effect of monitoring, q * * (a) is strictly increasing in a and thus higher than in the basic model. However, q * * (a) is only consistent with the equilibrium continuation of Lemma 1 when below q (i.e. as long as a < a); otherwise, there is no more shirking on the equilibrium path.

When a ≥ a, full monitoring (q = 1) is optimal. In contrast to the basic model, the principal is not indifferent between q = 0 and all q ∈ [q, 1]; although none of the bad agents are filtered out for each of these monitoring We proceed along the following lines: since the objective function of the principal is continuous in the interval [0, q), i) we show that the expected payoff of the principal is strictly increasing at q = 0 and strictly decreasing as q → q, and ii) we show that the absolute expected profit level is also higher at q = q * than at q = 0 and when q approaches q (the payoff function of the principal is flat for all q ≥ q).

To do this, define

where Z (q) = [-1 + e(q) + qe (q)](-t 2 ). ( 23)

Recall that the expected payoff from the good agents and from the bad agents in period 1, respectively, is independent of q. Furthermore, from (11), π 2 (q) = (1 -α) • N • Z(q) so that q * is uniquely determined by Z(q). ad i): We need to show that Z (q = 0) > 0 and Z (q → 1 t 2 ) < 0:

ad ii): Note that we have

A c c e p t e d M a n u s c r i p t

C Proof of Proposition 3

Recall that with H(c) = c n , we have e * (q, n, t 2 ) = q n t n 2 . Inserting q * (n, t 2 ) from Eqn. ( 13) yields e * (n) = 1 n+1 and thus s *

Taking the derivative of ( 27) w.r.t n yields

where the first and the third term are clearly positive so that we have to show that the second term is negative. Notice that this amounts to verifying that n ln t 2 + ln 1 t n 2 (n+1) = X(n) < 0, which was shown to hold in the proof of Proposition 2. Furthermore as for the limit, we have lim n→∞

t 2 as claimed in the Proposition.

D Proof of Proposition 4

We first show that q * * (a) as given in Eqn. ( 20) is increasing in a:

Clearly, the denominator is negative, but the numerator is also negative in the relevant range: First note that it is equal to zero at a = 0. Moreover, it is strictly decreasing in a as

which holds since the inequality holds for a = 0 and since the last two terms are also strictly decreasing in a.

A c c e p t e d M a n u s c r i p t

Finally note that, because q * * ( 1 2 ) = 1 = q, the relevant range is 0 < a < 1 2 so that a = 1 2 in our case and that also √ 1 -a -2a 2 > 0 holds for all a ∈ (0, 1 2 ). It remains to show that, for a < a, the principal's equilibrium profit is also higher when choosing monitoring intensity q * * (a) rather than q = 1.

From Eqn. ( 19), when monitoring at rate q * * (a), the principal's payoff is

When monitoring with q = 1, the principal gets

Taking the difference π 2 (q = q * ) -π 2 (q = 1) yields

which is positive for all a < a = 1 2 . Hence, the optimal monitoring policy is given by q * * (a) for a < a = 1 2 and by q = 1 for a ≥ a. Watson, J., 2002. Starting small and committment. Games and Economic Behavior 38, 176-199.


Cesare Campello¹

Manola Comar¹

Pierlanfranco D ' Agaro¹

Luca Minicozzi²

Albino Rodella³

Poli

C Campello
email: campello@burlo.trieste.it.

A MOLECULAR CASE-CONTROL STUDY ON THE MERKEL 1 CELL POLYOMAVIRUS IN COLON CANCER 2 3

Keywords: Merkel cell polyomavirus, colon cancer, molecular case-control study Merkel cell polyomavirus, colon cancer, molecular case-14

To explore the putative role of the Merkel cell polyomavirus in human 2 colon cancer, a prospective molecular case-control study was undertaken 3 in patients and their relatives enrolled during a screening programme. 4

After informed consent for participation in the principal study had been 6 obtained, colonoscopy was performed under conscious sedation. Among 7 all the relatives screened, the patients in whom a 'large-biopsy' specimen 8 was taken from the colonic mucosa were enrolled because of hyperplastic

20 14 [

 14 [START_REF] Gjoerup | Update on human polyomaviruses and 15 cancer[END_REF]. The hypothesis that polyomaviruses and 21 gastrointestinal malignancies are associated relies on several reports in22 JCV were detected in cancerous tissue, with different 1 rates of prevalence at distinct times and in different geographic areas. In 2 addition, a number of pathogenetic steps in the tumorigenesis associated 3 with JCV have been described[START_REF] White | Polyomaviruses and human cancer: 10 molecular mechanisms underlying patterns of tumorigenesis[END_REF]. A further 4 rationale for the investigation of Merkel cell polyomavirus in colon 5 cancer is that its epidemiological pattern is similar to that of JCV. It has 6 been demonstrated recently that DNA sequences of both Merkel cell 7 polyomavirus and JCV can be detected in sewage and environmental 8 samples at high concentrations, thus supporting the faecal-oral route of 9 their transmission [Boffil-Mas et al., 2010; Loyo et al., 2010]. 10 Investigations of the possible association between Merkel cell 11 polyomavirus and colon cancer are rare. Studies have been carried out 12 solely on formalin-fixed paraffin-embedded archival tissues, and never 13 compared with samples from control subjects enrolled concurrently Kassem et al., 2009; Loyo et al., 2010]. In addition, the presence of 15 Merkel cell polyomavirus in precancerous lesions of the colon has never 16 been explored. 17 To address these issues, a prospective molecular case-control study was 18 undertaken to detect the Merkel cell polyomavirus in patients with colon 19 cancer and in their relatives, who were used as controls. 2006-2008, patients with colon cancer and control subjects 2 were enrolled consecutively at the Teaching Hospital of Verona, Italy. 3 This study was part of a large screening programme for colon-rectal 4 cancer in the first-degree relatives of any cancer patient newly identified.

5

 5

4 15 ( 10 The

 1510 The amplification products of regions LT3 and VP1 were analysed by 5 sequencing to confirm their identification and to assess sequence 6 variability. The sequences of the conserved LT3 region were identical to 7 almost all those published, and in particular to sequences of strains 8 isolated in France (not shown). Two representative sequence patterns of 9 the variable region VP1 are reported in Table II, along with the sequences 10 of prototype strains and of other isolates retrieved from GenBank. The 11 strain MCV-ITA61 was identical to the isolate MKT-31 and to other 12 sequences discovered in France and Australia (GenBank accession 13 numbers FM864211, AM992902, FJ009188/9). The strain MCV-ITA71 14 was identical to MKT23 and to some American and European sequences GenBank accession numbers FJ392560, FJ649206, AM992904/5). The 16 level of identity of isolates in this survey was higher than 99% with the 17 reference strain MCC350. Overall, the Merkel cell polyomavirus 18 sequence patterns obtained in this study reproduced those of the 19 genotypes that are circulating worldwide, and especially in France. molecular case-control study reported herein was the first to focus on 1 the role of Merkel cell polyomavirus in incident cases of colon cancer 2 enrolled consecutively. Tissue samples were deep-frozen to ensure the 3 preservation of viral components, because the detection of polyomavirus 4 DNA may be impaired when archival fixed samples are tested [Touzé et 5 al., 2009]. Similarly, the consecutive enrolment of controls was 6 conducted from a cohort of subjects who underwent colonoscopy for 7 cancer screening because they were the first-degree relatives of each 8 patient. The enrolment of controls from relatives of the cases allowed 9 correction for two exposure factors that could have been operating. First, 10 past or present exposures to environmental determinants could have been, 11 at least in part, common to the cases and controls. Second, genetic 12 determinants of colon cancer could have been distributed homogeneously 13 in the cases and their relatives. Hence, the control of both factors may 14 have contributed to the disclosure of the putative role of the oncogenic 15 polyomavirus.

4 adenomas 3 4 The 5 The

 4345 and polyps, in which the rates of prevalence were similar to 5 those of the other intestinal tissues examined. The meaning of these 6 findings remains speculative. The recovery of Merkel cell polyomavirus 7 sequences from tumoral, precancerous and normal tissues should be 8 considered to represent the transient presence of an infectious agent 9 transmitted by the faecal-oral route [Bofill-Mas et al., 2010]. 10 Nevertheless, the possibility of the genomic integration of Merkel cell 11 polyomavirus in permissive precancerous cells could be considered, and 12 its significance in the oncogenic process could then be established. In any 13 case, the oncogenic mechanism of Merkel cell polyomavirus differs from 14 that of other polyomaviruses, including JCV, whose detection in 15 adenomas and polyps has been considered to be an important step in the 16 "hit-and-run" theory of tumorigenesis [Jung et al., 2008; Shuda et al.the findings of this study are consistent with the hypothesis 19 that the ubiquitous Merkel cell polyomavirus [Carter et al., 2009] is 20 present fairly frequently in the gastrointestinal tract, and that its causal 21 cancer, in addition to the role of other human and simian 1 polyomaviruses, should be reassessed. 2 Acknowledgements technical assistance of Mrs M. Nicolis is acknowledged gratefully. Merkel cell polyomavirus positive control (pcDNA.MCV350) was 6 provided generously by Dr Patrick Moore, NIH AIDS Research & 7 Reference Reagent Program, Germantown, USA.

Table I .

 I Main pathological features of the cases and controls, and positive results for Merkel cell polyomavirus

				** MCPyV positive
		n.	%	n. (%)	(95% CI)
	CONTROLS
	No lesion	52	65.0	4 (7.7)	2.09 -19.70
	Adenoma	15	18.8	2 (13.3)	1.61 -48.17
	Hyperplastic polyp	9	11.2	1 (11.1)	0.28 -61.91
	Other conditions	4	5.0	0	--
	F o r P e e r 80 --Adenocarcinoma Total CASES 57 89.0 Mucinous 6 9.4 F o r Adenocarcinoma Neuroendocrine cancer 1 1.1 P Total 64 --e *Fisher exact test: P=0.755 ** MCPyV = Merkel cell polyomavirus e r	7*(8.8) 4 (7.0) 0 0 4* (6.3)	3.52-18.03 1.92 -16.1 ----1.71 -16.01
			R R
			e e
			v i e v i e
				w w
					1 1

Table II .

 II Nucleotide variation in the viral protein 1 (VP1) gene of two representative Merkel cell polyomavirus sequences (in bold) in comparison with a number of GenBank registered sequences.

	1 1	The findings of this survey are consistent with the hypothesis that the
	2 2	Merkel cell polyomavirus, in addition to other human polyomaviruses, Merkel cell carcinoma is a rare skin cancer that originates from
	3 3	can be recovered frequently from the gastrointestinal tract, because it is neuroendocrine cells. This pathological condition has been related
	4 4	VP1 gene -Nucleotide position Accession N. 3825 3875 3909 4023 GenBank transmitted throughout the faecal-oral route. Moreover, the study does Country Strain recently to infection with a novel human polyomavirus, the Merkel cell
	MCC350 Fresh tissue samples from 64 cases of colon cancer (mean age 69.9±11.0 EU375803 T C C T USA 5 not indicate a role for Merkel cell polyomavirus in the genesis of colon 5 polyomavirus [Feng et al., 2008; Zur Hausen, 2008; Becker et al., 2009]. 5
	MCC339	EU375804	C	G	T	A	USA
	MKT-23 years; 40 males) and fresh biopsies from 80 relatives (mean age 53.7±8.6 FM864208 C G C T France 6 cancer. 6 Like SV40 [Vilchez and Butel, 2004], Merkel cell polyomavirus appears 6
	MKT-31	FM864210	C	C	C	T	France
	VP1-Mpt2 MCV ITA 61 HQ262570 AM992903 MCV ITA 71 HQ262569 years; 43 male; 55 son/daughter, 23 brother/sister, 2 parents) were C G C A France C C C T Italy C G C T Italy F o r Word count:249 7 8 9 to play a causal role in tumorigenesis. Tumour induction and expansion is 7 F preceded by a monoclonal integration of the virus into target cells. 8 o r Nonsense mutations or deletions in the early genomic region lead to the 9
	10 10	P e P e expression of truncated large T antigen, loss of viral DNA replication,
	11 12 11 12	e r and cell transformation [Shuda et al., 2008]. e r The assumed oncogenic power of the Merkel cell polyomavirus has
	13 13	R e R e prompted research to explore its role in several human cancers, namely in
	14 15 14 15	v i e non-Merkel skin tumours, in neuroblastoma and other malignancies of the v i e central nervous system, in lung cancer, and mesothelioma. A series of
	16 16	w w high-grade neuroendocrine tumours from different body sites was also
	17 17 17	investigated, with negative results [Duncavage et al., 2009; Gandhi et al.,
	18 18 18	were compared. 2009; Sastre-Garau et al., 2009].
	19 19 19	Sequence analysis of the viral LT3 and VP1 regions showed high Other polyomaviruses, namely JCV and SV40, have been linked
	20 20	homology (>99%) with those of strains circulating worldwide, especially previously to colon cancer [Markovics et al., 2005; Campello et al., 2010;
	21 21	with genotypes detected in France.
	22
								3 4

7

analysed by PCR and sequencing. Precancerous lesions, namely 8 adenomas and polyps, were detected in 15 (18.8%) and 9 (11.2%) of the 9 controls, respectively. In addition, 144 blood samples were examined. 10 Merkel cell polyomavirus DNA was detected in 6.3% of cases and 8.8% 11 of controls. This difference was not statistically significant in the logistic 12 regression analysis, after adjustment for age. Whereas blood samples 13 from both cases and controls tested negative, the DNA Merkel cell 14 polyomavirus was identified in 12.5% of adenoma/polyp tissues. No 15 statistically significant difference was found when prevalence rates of

16

Merkel cell polyomavirus in normal, precancerous and cancer tissues

Ministry for University and Research, Italy (PRIN 2007


Dhanraj ; Samuel
email: dhan.samuel@hpa.org.uk

Lenesha Warrener

Katja Hoschler

Monoclonal antibodies to the Haemagglutinin HA1 subunit of the pandemic influenza A / H1N1 2009 1 virus and potential application to serodiagnosis 2

Keywords: Influenza A/ H1N12009, Monoclonal antibodies, HA1 subuint

Monoclonal antibodies to the Haemagglutinin HA1 subunit of the pandemic influenza A / H1N1 2009 virus and potential application to serodiagnosis

Dhan Samuel, Lenesha Warrener, Katja Hoschler

124

Simultaneously 100µL of Mab culture supernatants, diluted in the same buffer, were added in 125 triplicate to separate wells and incubated at 37 ºC for 1h. The plates were washed as before and 126 100µL of a 1/4000 dilution of rabbit anti-mouse IgG-HRP conjugate was added. After washing the 127 wells four times with PBST, the bound HRP was detected with TMB substrate. 163 Supernatant from Mab 1F5-hybridoma cell-culture was harvested and IgG purified using protein A 164 column and labelled with horseradish peroxidase (HRP) using standard procedures (Ishikawa et al., 165 1983 and[START_REF] Nilsson | A technique for preparing defined conjugates of 392 horseradish peroxidase and immunoglobulin[END_REF]. The purified conjugate contained 1.44 moles of enzyme per mole of 166 IgG and the antibody concentration was approximately 2mG/mL. To streptavidin coated plates (see 167 above) 100µL/well of a 100nG/mL biotin-rHA1 from A/California/06/09 in 1% (w/v) milk PBSTBx was 168 added and incubated at 37ºC for 1h. The plates were then washed four times in PBST. showed that all five clones secreted IgG1 antibodies (Table I).

211

In Western blots, serum from the test bleed of the immunised mouse, used to generate the Mabs, 212 stained all the recombinant haemagglutinin proteins derived from H1N1 influenza strains, but not the 213 recombinant haemagglutinin form H5N1 and influenza B (Figure 1a). Mabs from clones 1F5 and 214 1G10 did not react with any of the proteins in Western blots, although the lack of staining observed for only weak staining with rHA1 from A/California/06/09 (Figure 1c). Mab 9E12 showed weak reaction 219 with rHA derived from A/California/06/09 only (Figure 1d).

220

In a cell-ELISA, all five Mabs reacted with the recombinant virus with

  quantitation of IgG in culture supernatants: Microtitre plates were coated with 100µL/well 121 of rabbit anti-mouse IgG (5µG/mL, Sigma, Dorset, UK) in 0.05M carbonate buffer, pH9.5 overnight at 122 2-8 ºC. The wells were washed and 100µL of dilutions of IgG (derived from clone 1F5) in 1% (w/v) 123 milk in PBSTBx was added to the wells in triplicate for construction of a standard curve.

  128 SDS PAGE and Western Blotting: Recombinant viral proteins were separated electrophoretically 129 under reducing conditions on a NuPAGE 10% Bis-Tris gel (Invitrogen Ltd, Paisley, UK) using MOPS 130 running buffer and the electrophoresed proteins transferred onto nitrocellulose membranes essentially 131 as described by Towbin et al., (1979) and detailed in the product literature from Invitrogen Ltd. The 132 membranes were then incubated with a 1/20 dilution of supernatants derived from each of the cloned 133 Mab producing cell lines in 1% (w/v) milk in PBST or with a 1/100 dilution of serum from the mouse 134 test bleed in the same buffer solution for 1h at room temperature (RT). The membranes were then 135 washed and incubated with a 1/20000 dilution of a rabbit anti-mouse IgG-alkaline phosphatase 136 conjugate (Stratech Scientific Ltd, Newmarket, UK). After washing, the bound Mabs were detected 137 with 5-bromo-4-chloro-3-indolyl phosphate and nitro-blue tetrazolium (NBT/BCIP) as substrate (Leary 138 et al., 1983). 139 Haemagglutination Inhibition (HAI): The ability of the Mabs to inhibit agglutination of 0.5% turkey red 140 blood cells (RBC) by two recombinant influenza A virus strains NIBRG-121 and NIBRG-122, derived 141 from A/California/07/09 and A/England/195/09 respectively and supplied by the National Institute for 142 Biological Standards and Controls (NIBSC), UK, was tested essentially as described earlier (Ellis and with recombinant virus NIBRG-121 at a multiplicity of infection of 0.05 particles per 148 cell and dispensed into wells of 96-well tissue culture plates using standard procedures (Rowe et al., 149 1999). One hundred microlitres of diluted Mab supernatants in 1% (w/v) milk PBSTBx were added to 150 the wells and incubated for 1h at RT. The wells were washed four times by gentle aspiration of the 151 antibody solution and washing with PBST. The wells were incubated with 100µL rabbit anti-mouse 152 IgG-alkaline phosphatase conjugate diluted 1/20000 in 1% (w/v) milk PBSTBx or with 100µL of rabbit 153 anti-mouse IgG-HRP conjugate diluted 1/4000 in the same buffer. The wells were washed four times 154 with PBST as before and further washed twice with water before immunostaining. The HRP 155 conjugates were revealed by the addition of 100µL of a soluble TMB substrate for the cell-ELISA and 156 stopping the reaction after colour development with 100µL 0.5M HCl and reading the optical density at phosphatase conjugates were revealed with the addition of 100µL/well of NBT/BCIP substrate, as 160 described for Western blotting above.

169

  An equal volume of HRP conjugated 1F5 Mab (1F5-HRP) diluted 1/1000 was mixed with an equal hybridoma colonies: Fourteen days post fusion virtually all of the 960 wells from the 189 fusion plates had colonies of hybridoma growth and consequently, supernatant from all the wells were 190 screened by EIA. Three strategies were used for the screening procedure. Reactivity of the 191 hybridoma supernatant to rHA or rHA1 derived from H1N1 (A/California/06/09) coated directly on to 192 microtitre wells or to biotinylated rHA1 derived from H1N1 (A/California/06/09), immobilised using 193 streptavidin coated plate. The serum derived from the test bleed of the immunised mouse gave strong 194 EIA reactivity in all three assays. The five monoclonals taken forward all reacted with biotin-rHA1 195 coated wells. Only one of these Mabs reacted with rHA1 coated directly onto microtitre wells. The EIA 196 positive hybridoma cells were cloned by limiting dilution. 197 EIA for the estimation of IgG concentration culture supernatants: From a standard curve constructed 198 using purified mouse IgG1, the concentration of IgG in the culture supernatants used in the 199 characterisation of Mabs was estimated. The concentrations of antibody in the supernatant for Mabs 200 1F5, 9A4 and 7H4 were between 15-18µG/mL, and for supernatant 9E12, was much higher 201 (26.0µG/mL). The antibody concentration in the supernatant of Mab 1G10 was only 1.0µG/mL (see 202 Table I). 203 Characterisation of the monoclonal antibodies: Since all five clones reacted with biotinylated rHA1 204 subunit derived from A/California/06/09, we assessed their reactivity with biotinylated rHA 205 A/California/06/09 and with biotinylated rHA1 subunit derived from A/Brisbane/07/09 H1N1 and A/ 206 Solomon Islands/03/06 H1N1 in EIA using streptavidin to capture the biotinylated proteins. All five 207 clones were specific for rHA and rHA1 derived from A/California/06/09 and did not react in EIA with 208 the biotinylated recombinant proteins from A/Brisbane/07/09 or with A/Solomon Islands/03/06. Serum 209 from the test bleed reacted with all four biotinylated proteins. Isotyping of the Mab supernatants 210

309

  the amino acid changes in the two haemagglutinins result in a significant change in the epitope 310 recognised by the 1F5 antibody. If there are significant changes in the IF5-epitope in other 2009/10 311 virus isolates, then Mab IF5 could prove useful for tracking antigenic drift in the pandemic influenza 312 A/H1N1 2009 virus strains.313In the competitive EIA, inhibition of 1F5-HRP binding to the biotinylated rHA1 of A/California/06/09 314 would only be expected if competing antibodies either compete directly for the epitope recognised by 315 Mab 1F5 or if the competing antibodies bind to other epitopes on the rHA1 that are close enough to 316 interfere sterically with 1F5-HRP binding. Since Mab 1F5 inhibits haemagglutination of turkey RBC by 317 NIBRG-121, it would follow that any antibodies that inhibit 1F5-HRP in the competitive EIA as a result 318 of steric interference will inhibit haemagglutination. Although this proved to be the case for most of the 319 ferret antisera and post vaccination sera tested (Figures3a and 3b), the correlation between the HAI 320 titres and % inhibition observed in the competitive EIA was poor. This is not surprising, since HAI 321 measures a polyclonal antibody response directed towards a number of antigenic epitopes on the 322 haemagglutinin receptor binding site of the virus, whereas the competitive EIA only measures 323 antibodies in the competing serum that inhibit binding of a single epitope on haemagglutinin of the on the 1F5 epitope structure, inhibiting binding of 1F5-HRP to the biotinylated rHA1.335Our data on a limited number of subjects investigated in this work indicates that vaccination with 336 Celtura ® vaccine induces an immune response to the haemagglutinin and specifically to an epitope 337 shared by 1F5 antibody or to epitopes close to this site. It would be of interest to determine whether 338 individuals infected with the pandemic influenza A/ H1N1 2009 virus also mount a significant antibody 339 response to the 1F5-epitope or epitopes close to this site. If further studies show this to be the case 340 then the competitive EIA described here could provide a potentially useful and specific sero-341 epidemiological tool for studying exposure to infection with the pandemic virus as well as to determine 342 efficacy of vaccination. The competitive EIA has the added benefit that it is simple, safe and not as 343 work-intensive as the haemagglutination inhibition and microneutralisation assays.

Figure 1 .Figure 2 :

 12 Figure 1. Western blot analysis of test bleed and monoclonal anti-HA1 antibodies. 418 Recombinant HA proteins derived from influenza strains were analysed using SDS-PAGE 419 under reducing conditions, transferred to nitrocellulose and immunostained with (A) serum 420 from test bleed and Mabs (B) 7H4 (C) 9A4 and (D) 9E12. Lanes 1 and 12: SeeBlue® Plus2 421 molecular weight standard, Lane 2 and 13: SeeBlue® molecular weight standard, Lane 3: 422 HA (A/New Caledonia/20/99 H1N1), Lane 4: HA (A/California/06/09 H1N1), Lane 5: HA1 423 (A/California/06/09 H1N1), Lane 6: HA (A/Solomon Islands/3/06 H1N1), Lane 7: HA 424 (A/Brisbane/59/07 H1N1), Lane 8: HA (A/Vietnam/1203/04 H5N1), Lane 9: HA1 425 (A/Vietnam/1203/04 H5N1), Lane 10: HA (B/Malaysia/2506/04), Lane 11: Blank. 426

Figure 3a :

 3a Figure 3a: Inhibition by ferret antisera of Mab 1F5-HRP binding in a competitive EIA. The 432 antisera to the influenza A strains are identified on the abscissa and the % inhibition of 1F5-433 HRP binding for each of these is shown on the ordinate. The numbers shown above the bars 434 in the graph are the corresponding HAI titres obtained for each antiserum with NIBRG-121. 435

  An operational consequence of the emergence of the pandemic influenza A / H1N1 2009 was that the 269 pathogen and specimens from suspected cases needed to be handled at a higher biological 270 containment level than for seasonal influenza viruses. This restricted the propagation of virus in cell 271 culture to laboratories with high containment facilities and further restricted availability of the virus or 272 viral proteins for developing serological reagents. However, within three months of the first cases of 273 the pandemic influenza A / H1N1 2009 virus being reported in Mexico and the USA, rHA proteins 274 derived from the pandemic strain in purified form became available commercially. This prompted us to 275 generate monoclonal antibodies to rHA in order to provide additional serological research tools for 276 studying the pandemic influenza A / H1N1 2009 virus strains.

	267
	268	DISCUSSION
	221	differing intensities
	301	and A/New Caledonia/2/99. This is not surprising since there is ~70% amino acid sequence homology
	222	(See Table 1). Mab 1F5 and 9A4 gave the highest OD signals using TMB substrate. Diffuse
	302	between the HA1 of A/California/06/09 and seasonal influenza A/ H1N1 (Ikonen et al., 2010).
	223	cytoplasmic/membrane staining of infected cell was observed with Mabs 1F5 and 9A4 (Figure 2a and
	224 303	2b) using both the insoluble substrates, NBT/BCIP substrate (with alkaline phosphatase conjugate)
	225 304 305 306	and TrueBlue TM (with HRP conjugate). This was different from the weak cytoplasmic/membrane F o r There are only three amino acid changes in the haemagglutinin between A/California/07/09 and F A/England/195/09 (L49I, P91S and I323V) and this was sufficient to result in an eight fold difference in o r HAI titres of 1F5 seen with the two recombinant viruses. Furthermore, in competitive EIA there was
	307	P P greater inhibition of 1F5-HRP binding by ferret antiserum to A/California/06/09 compared to
	230 231	e e In competitive EIA, only serum from the test bleed and the unconjugated tissue culture supernatant e r e r
	232	from clone 1F5 competed effectively with 1F5-HRP labelled antibody. A standard curve for the R R
	283	competitive EIA using purified, unconjugated 1F5 antibody revealed that the detection limit was e e
	284 285 286 287	v i e w success with using biotinylated rHA1 suspended from streptavidin coated plates for identifying reactive hybridomas suggested that conformational presentation of the rHA protein was important. It may be that the rHA1 and rHA undergo changes in conformation on binding to polystyrene wells, as v i e was shown for HA binding to polyvinyl by Yewdell (2010). Yewdell (2010) demonstrated recently that w
	288	some Mabs to discontinuous epitopes on influenza A HA can induce refolding of denatured proteins
	289	bound to polyvinyl plates over a two day incubation period. Thus it is possible that with extended
	290	incubation of the hybridoma supernatant during the screening process, more hybridoma clones
	291	reactive to conformational epitopes in rHA1 may have been identified.
	292	Four of the five Mabs to the pandemic H1N1 influenza A/California/ 06/09 generated in this study
		Page 12

staining pattern observed with 9E12 (Figure

2c

). The weak staining of infected cells by 1G10 may be 226 the result of the low concentration of antibody in the culture supernatant used (Figure

2d

).

227

Only Mab 1F5 inhibited haemagglutination of turkey RBC by recombinant virus NIBRG-121 (derived 228 from A/California/07/09) and recombinant NIBRG-122 (derived from A/England/195/09). The HAI titre 229 of 1F5 with NIBRG-121 was eight fold higher than with NIBRG-122 (Table

1

).

277

Recombinant HA1 derived from A/California/06/09 H1N1 proved to be immunogenic, since serum 278 taken from the test bleed of the immunised mouse showed reactivity with rHA1 subunit and whole rHA 279 (derived from the A/California/06/09 strain) coated wells and with biotinylated rHA1 from the same 280 strain suspended from streptavidin coated wells in EIA. The majority of hybridomas screened did not 281 react with the recombinant proteins coated directly onto polystyrene wells. This may have occurred as 282 a result of failure in the fusion process to fuse splenocytes with specificity for the proteins. However, appeared to recognise different epitopes as demonstrated by the differing pattern of reactivity 293 observed in Western blots, staining of virus infected cells, HAI and in competitive EIA. The 294 concentration of IgG in the culture supernatant of Mab 1G10 was ten times lower than that found for A/England/195/09. Although the observed differences with the animal sera may be due to differing 308 responses to infection in individual ferrets, the combined HAI and competitive EIA data suggest that

Page 21 of 31 John Wiley & Sons Journal of Medical Virology

	Table I
	Monoclonal Antibody		Reactivity in EIA (OD 450/620nm)		HAI titre	Mab reactivity with MDCK cells	Reactivity in
										infected with NIBRG-121 virus in:	Western blot
	Clone	Isotype	Conc.	Biotin-rHA1 subunit	Biotin-Whole rHA	Biotin rHA1 subunit	Biotin rHA1	NIBRG	NIBRG	Cell-ELISA	NBT-BCIP	True-	Whole	Subunit
	Designation		µG/mL	A/California/06/09	A/California/06/09	A/Solomon Is./03/06	A/Brisbane/59/07 subunit	121	122	OD 450/620nm HRP:TMB		Blue	rHA	rHA1
	1F5	IgG1	16.1	0.555	0.357	0.017	0.018	128	16	1.018	+++	+++	-	-
	1G10	IgG1	1.0	0.056	0.050	0.011	0.013	<8	<8	0.177	+/-	+	-	-
	7H4	IgG1	17.7	0.248	0.098	0.014	0.018	<8	<8	0.095	-	-	+++	+++
	9A4	IgG1	15.2	1.138	0.569	0.013	0.016	<8	<8	0.718	+++	+++	+++	+/-
	9E12	IgG1	26.0	0.597	0.108	0.009	0.011	<8	<8	0.170	+/-	+	-	+

Co. Ltd, Poole, UK) in 1% (w/v) milk in PBSTBx and incubated for 30min at 37ºC. The bound HRP

Zambon, 1997). Briefly, supernatants were diluted twofold in PBS, starting at a 1:8 dilution, and 4

Cell-ELISA and Immunostaining of virus infected MDCK cells: Madine-Darby canine kidney (MDCK)

450/620nm. For localisation of Mab staining, the HRP conjugates were visualised after addition of

100µL of a precipitating substrate, TrueBlue™, (KPL, Gaithersburg, MD, USA) and the alkaline

volume of competing antibody. The competing antibodies were undiluted Mab supernatants, or 1/5

dilutions of ferret antisera to influenza A virus strains (see Figure3afor strains) and serum samples

antigen preparation of the reassortant NYMC X-179A virus) in 1% (w/v) milk PBSTBx. One hundred

microlitres per well of this was then added in duplicate to streptavidin-biotin-rHA1 wells for 1h at 37ºC.

1G10 may be explained by its low antibody concentration in culture supernatants. Mab 7H4 gave

recombinant protein (Figure1b). Mab 9A4 gave intense reaction with rHA from A/California/06/09, but

75nG/mL. Partial inhibition of 1F5-HRP binding in EIA was observed with tissue culture supernatants

were specific for the pandemic influenza A/ H1N1 2009 strain and did not cross-react with pre-2009

seasonal H1N1 strains. Unlike the Mabs used in this work, which proved to be specific for

A/California/06/09 in EIA and Western blots, the polyclonal serum from the test bleed mouse showed

cross-reactions with the HA1 of influenza A/Brisbane/59/07 and influenza A/Solomon Islands/03/06

epitope on the virus, albeit represented multiple times on the virion. Ferret antisera and immune

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Smagala J, de Graaf M, Burke DF, Fouchier RA, Pappas C, Alpuche-Aranda CM, López-Gatell H,

Olivera H, López I, Myers CA, Faix D, Blair PJ, Yu C, Keene KM, Dotson PD Jr, Boxrud D, Sambol

AR, Abid SH, St George K, Bannerman T, Moore AL, Stringer DJ, Blevins P, Demmler-Harrison GJ,

Ginsberg M, Kriner P, Waterman S, Smole S, Guevara HF, Belongia EA, Clark PA, Beatrice ST,

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John Wiley & SonsJournal of Medical Virology

ACKNOWLEDGEMENTS

345

The authors would like to thank Dr Joanna Ellis and Dr Monica Galliano for providing information on

human sera effect haemagglutination by binding to multiple epitopes, represented multiple times on 327 the virion.

328

An alternative explanation for the poor correlation between HAI and the competitive EIA may be that 329 antibodies which do not inhibit HAI may nevertheless bind to distal sites on the biotinylated rHA1 and