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Experience and gender effects in acquisition experiment with value messages

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Abstract

In the bargaining experiment, the privately informed seller of a company sends a value message to the uninformed potential buyer who proposes a price for acquiring the company. Participants are constantly either seller or buyer and interact over 30 rounds with randomly changing partners. How are overstating the value of the company, underpricing the received value message and acceptance of price offers affected by experience and gender (constellation)? We control via treatments for awareness of gender (constellation) and show that gender (constellation) matters and that the main experience effects apply across gender (constellations).

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Notes

  1. As already mentioned, our analysis neglects antitrust regulation to prevent acquisitions which would question market competition and thereby harm customers (see for such regulation Posner 2009).

  2. Considering such true or false reporting and gender, Dreber and Johannesson (2008), as well as Erat and Gneezy (2011) and Gneezy (2005), find that men are more likely to lie for a monetary gain than women and Houser et al. (2012) observe that men are more likely to incorrectly report the result of a private coin flip than women (unlike in bargaining such false reporting does not harm another participant but the experimenter), yet they do not investigate whether those gender differences in cheap talk persist when controlling for experience.

  3. Croson and Gneezy (2009) provide an extensive overview of gender differences documented in studies on risk attitude, social preferences (ultimatum and dictator games, trust and reciprocity, prisoner’s dilemmas, social dilemmas and public good provision) and competitive behavior.

  4. Without considering cheap talk value messages for which we allow in our experiment, but which are rarely studied in auction experiments (see Kagel and Levin 2014).

  5. According to our data “selfish black lies,” however, coexist with significant and persistent understating and truth-telling.

  6. Valley et al. (2002) compare such free format replay communication and a no communication control treatment for situations with two-sided incomplete information.

  7. A significant share of participants frequently and persistently signals the value consistent with truth-telling what, however, does not suffice that buyer participants, who often and repeatedly experience false signals, will trust in “Kantian imperatives.”

  8. We refrain from postulating convergence of the interacting dynamics after 30 rounds.

  9. The common priors assumption in the tradition of Harsanyi (1967–1968) is philosophically interesting, and possibly informative, but very unrealistic.

  10. Seller participants, for instance, hardly ever accepted a minor loss even when being aware that trade is very profitable for the buyer.

  11. The English translation of the Instructions of the whole experiment is reported in Appendix 2.

  12. For the results of the incentivized trial round, we refer to Di Cagno et al. (2016).

  13. Except for noise, we do not expect buyers to offer \(p\ge \hat{v}\).

  14. In Fig. 5 we report the frequencies of truth-telling by phase and by gender.

  15. Recall that the optimal price offer is \(p=q\) for \(q \leq 0.5\) and \(p=0\) for \(q>0.5\), while expected earnings are \(0.5-q\) for \(q \leq 0.5\) and zero for \(q>0.5\).

  16. We use the STATA command xtreg for suspicion and “make-up” and xtprobit for acceptance. As a robustness check, we also estimate a dynamic panel data model with xtabond2 which allows to fit the Arellano and Bover (1995) and Blundell and Bond (1998) estimators. The results obtained are qualitatively similar, even though xtreg and xtprobit are preferred with dataset characterized by large T (in our case, 30 rounds) and large N. The estimates of the dynamic panel data model are available upon request.

  17. The regression analysis in Table 6 focuses on the relation between acceptance and past experience, controlling for \(q\),\(v\) and \(p\). Therefore, the analysis of path dependence is the main point of the table. Nonetheless, we were aware that price proposals may depend on seller’s value message. To address this potential endogeneity, we estimated a reduced form of our model with three equations representing separately the subjects’ choice sequence: first, the value message by the seller, then the price proposal by the buyer and finally the acceptance decision by the seller. This approach leads to the same qualitative results as those discussed in Table 6, and therefore it confirms that the endogeneity issue does not affect the absence of path dependence. Table 15 reported in Appendix 1 shows the estimates of the reduced form model.

  18. One of our anonymous reviewers pointed to the fact that sellers via their value signals, \(\hat{v}\), may have influenced the price offer and beware of such influence what might have affected their acceptance. When including additionally \(\hat{v}\) as an explanatory variable in Table 6, the effect of \(\hat{v}\) is significant. In our view, the effect of \(\hat{v}\) on \(p\) is quite ambiguous: a seller with large \(v\) signaling a large \(\hat{v}\) might be annoyed by a low price offer, whereas one with low \(v\) but an overstating large \(\hat{v}\) should not be at all surprised.

  19. “Field of study”  and “Field of Study constellation”  as implemented experimentally does not significantly affects making-up and acceptance.

  20. Using data from the Treatment Other Confound, we also investigate potential effects of including the partner’s field of study. We find that this variable does not have any effect with all our results being confirmed.

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Correspondence to D. Di Cagno.

Appendices

Appendix 1: Tables

See Tables 11, 12, 13, 14 and 15 and Fig. 8.

Table 11 Time (s) for acceptance by \(p\), \(q\), experience and gender
Table 12 Time (seconds) for price proposals by buyer participants, separately for phase and gender
Table 13 Time for message by truth-telling, overstating and understating
Table 14 Winner’s curse, measured by differences in earnings and prices
Table 15 Acceptance behavior, reduced form
Fig. 8
figure 8

Value message and the true value by phase

Appendix 2: Instructions

1.1 Introduction

Welcome to our experiment!

During this experiment, you will be asked to make several decisions and so will the other participants.

Please read the instructions carefully. Your decisions, as well as the decisions of the other participants, will determine your earnings according to some rules, which will be shortly explained later. In addition to your earnings from your decisions over the course of the experiment, you will receive a participation fee of 10 euro. Besides this amount, you can earn more euro. However, there is also a possibility of losing part of the participation fee, as it will be explained in the next section of these instructions. But do not worry: you will never be asked to pay with your own money, as your losses during the tasks will be covered by the participation fee. The participation fee and any additional amount of money you will earn during the experiment will be paid individually immediately at the end of the experiment; no other participant will know how much you earned. All monetary amounts in the experiment will be computed in ECU (Experimental Currency Units). At the end of the experiment, all earned in ECUs will be converted into euro using the following exchange rate:

$$\begin{aligned} 30 \hbox { ECU} = 1 \hbox { euro} \end{aligned}$$

You will be making your decisions by clicking on appropriate buttons on the screen. All the participants are reading the same instructions and taking part in this experiment for the first time, as you are.

Please note that hereafter any form of communication between the participants is strictly prohibited. If you violate this rule, you will be excluded from the experiment with no payment. If you have any questions, please raise your hand. The experimenter will come to you and answer your questions individually.

1.2 Description of the experiment

This experiment is fully computerized. This experiment consists of the following four phases, each composed by a different number of rounds: Phase I of 1 round, Phase II of 30 rounds, Phase III of 12 rounds, and Phase IV of 10 rounds. After completing Phase I, you will proceed to Phase II; after completing Phase II, you will proceed to Phase III; after completing Phase III you will proceed to Phase IV. You can earn money in each phase of the experiment.

At the beginning and at the end of the Experiment, you are asked to reply to a short questionnaire.

At the beginning of the Experiment, each participant is randomly assigned one of two possible roles. Half the participants will be assigned the role of Buyer; the other half will be assigned the role of Seller. You will remain in the same role you have been assigned throughout the experiment.

In each of Phase I, II and III and in each of their rounds you will be matched with a different participant randomly assigned to you. In Phase IV you will decide individually and independently of your role.

1.2.1 Description of the task: Phase I

In Phase I selling of a firm between a Seller, who owns the firm, and Buyer can take place. You will be told if you are Buyer or Seller, and will be matched with one of the other participant in the other role. For example, if you are selected as Buyer, then you will be randomly and anonymously matched with another participant who is a Seller.

The computer will randomly select the value of the firm among the following values: 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90 and 95 (all the values are equally likely). This value will be communicated only to the Seller. The Buyer will not learn the value of the firm selected randomly by the computer.

The Seller’s evaluation of the firm is proportional to the value of the firm selected by the computer. This proportion will be randomly selected by the computer and can only take one of the following values: 10, 20, 30, 40, 50, 60, 70, 80 or 90 percent (all the values are equally likely). The Seller’s evaluation is the value of the firm multiplied by the selected proportion. The proportion will be communicated to both, Buyer and Seller, whereas the value of the firm will be known only to the Seller. Do not worry: the software will provide the information on the decision screen, depending on your role, Seller or Buyer.

As an example, suppose that the computer selected a value of the firm equal to 90 and a proportion of 50 percent, so that the Seller’s evaluation of the firm will be 45, corresponding to 50 percent of 90. In this case, the Seller will find on the screen of the computer that the value of the firm is 90, the proportion is 50 percent and that the Seller’s evaluation is 45; the Buyer will find on the screen only the proportion of 50 percent. Another example: suppose that the computer selected a value of the firm equal to 90 and a proportion of 80 percent. In this case, the Seller’s evaluation will be equal to 72, corresponding to 80 percent of 90. In this case, the Seller will find on the screen of the computer that the value of the firm is 90, the proportion is 80 percent and that the Seller’s evaluation is 72; the Buyer will find on the screen only the proportion of 80 percent.

The Seller sends a value message to the Buyer about the value of the firm, which can be either true or false. Therefore, the value message is not necessarily equal to the firm value nor to the Seller’s evaluation of the firm. The message consists of an integer value between 0 and 100.

After having received the message, the Buyer makes a take-it-or-leave-it offer to the Seller by proposing a price, an integer number between 0 and 100. When making this offer, the Buyer just knows the value message and by which proportion of the value the Seller evaluates the firm.

After having received the price offer of the Buyer, the Seller decides whether to accept it or not. If she accepts, the firm will be sold for the offered price to the Buyer. If she does not accept, no trade takes place. After the Seller has decided, the payoffs of Buyer and of Seller are calculated and individually communicated at the end of Phase I. These payoffs are calculated as explained below, and they are paid to all participants at the end of the experiment.

Calculation of the payoff in Phase I

The payoff of the unique round in Phase I does not depend on the value message and is calculated as follows:

If the Seller has accepted the offered price, the payoffs are:

  • The Buyer earns the difference between the value of the firm and the accepted price

  • The Seller earns the difference between the accepted price and the Seller’s evaluation of the firm

An example: suppose that the firm value is equal to 45 and that the proportion of the firm value is 80 percent, so that the Seller’s evaluation of the firm is 36. Suppose the Buyer offers a price equal to 40 and that the Seller accepts it. In this case, the Buyer earns \(45 - 40 = 5\), and the Seller earns \(40 - 36 = 4\).

Another example: suppose that the firm value is equal to 45 and that the proportion of the firm value is 80 percent, so that the Seller’s evaluation of the firm is 36. Suppose the Buyer offers a price equal to 55 and that the Seller accepts it. In this case, the Buyer earns \(45 - 55 = - 10\), and the Seller earns \(55 - 36 = 19\).

If the Seller does not accept the Buyer’s offer, the payoffs are 0 for both Seller and Buyer.

1.2.2 Description of the task: Phase II

In Phase II, you will face for 30 rounds the same situation as in Phase I. As in the previous Phase, in each of the rounds you will be matched with a different participant randomly assigned to you.

The same instructions as in Phase I apply to Phase II, also the calculation of the payoffs.

The payment from this Phase will consist of the payoff of one of the 30 rounds randomly selected. For example, if round number five is selected, your payment for Phase II will be the payoff you earned in that round.

Calculation of the payoff in each round in Phase II

The payoff of each round in Phase II does not depend on the value message and is calculated as follows:

If the Seller has accepted the offered price, the payoffs are:

  • The Buyer earns the difference between the value of the firm and the accepted price

  • The Seller earns the difference between the accepted price and the Seller’s evaluation of the firm

An example: suppose that the firm value is equal to 45 and that the proportion of the firm value is 80 percent, so that the Seller’s evaluation of the firm is 36. Suppose the Buyer offer a price equal to 40, and that the Seller accepts it. In this case, the Buyer earns \(45 - 40 = 5\), and the Seller earns \(40 - 36 = 4\).

Another example: suppose that the firm value is equal to 45 and that the proportion of the firm value is 80 percent, so that the Seller’s evaluation of the firm is 36. Suppose the Buyer offers a price equal to 55, and that the Seller accepts it. In this case, the Buyer earns \(45 - 55 = - 10\), and the Seller earns \(55 - 36 = 19\).

If the Seller does not accept the Buyer’s offer, the payoffs are 0 for both Seller and Buyer.

1.2.3 Description of the task: Phase III

In Phase III, you will face for 12 rounds the same situation as in Phase I. As in the previous Phase, in each of the rounds you will be matched with a different participant randomly assigned to you.

The same instructions as in Phase I apply to Phase III.

At the beginning of the Phase, you will be asked if you prefer to be paid on the basis of the payoff of one of the 12 rounds randomly selected or on the basis of the average payoff of the 12 rounds. On the basis of your choice, the computer will calculate your payoff for this Phase.

Calculation of the payoff in each round in Phase III

The payoff of each round in Phase II does not depend on the value message and is calculated as follows:

If the Seller has accepted the offered price, the payoffs are:

  • The Buyer earns the difference between the value of the firm and the accepted price

  • The Seller earns the difference between the accepted price and the Seller’s evaluation of the firm

An example: suppose that the firm value is equal to 45 and that the proportion of the firm value is 80 percent, so that the Seller’s evaluation of the firm is 36. Suppose the Buyer offers a price equal to 40 and that the Seller accepts it. In this case, the Buyer earns \(45 - 40 = 5\), and the Seller earns \(40 - 36 = 4\).

Another example: suppose that the firm value is equal to 45 and that the proportion of the firm value is 80 percent, so that the Seller’s evaluation of the firm is 36. Suppose the Buyer offers a price equal to 55, and that the Seller accepts it. In this case, the Buyer earns \(45 - 55 = - 10\), and the Seller earns \(55 - 36 = 19\).

If the Seller does not accept the Buyer’s offer, the payoffs are 0 for both Seller and Buyer.

1.2.4 Description of the task: Phase IV

Phase IV consists of 10 rounds; during this Phase, you will not interact with other participants. During this phase, you are asked to choose between pairs of lotteries. In particular, in each round for each lottery pair you have to assess which one you would prefer to play.

At the end of the experiment, one round will be randomly selected for payment, and the computer will play on your screen the lottery that you have preferred in this round. The payment of Phase IV is given by the result of this lottery.

1.2.5 Your final payment

Your final payment will be displayed on the screen at the end of the experiment. It is determined as the sum of:

  • Payoff from the unique round in Phase I (in euro)

  • Payoff from one randomly selected round in Phase II (in euro)

  • Payoff from EITHER one randomly selected round OR an average payment between 12 rounds from Phase III (in euro)

  • Payoff from one randomly selected round in Phase IV (in euro)

  • Participation fee.

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Di Cagno, D., Galliera, A., Güth, W. et al. Experience and gender effects in acquisition experiment with value messages. Small Bus Econ 48, 71–97 (2017). https://doi.org/10.1007/s11187-016-9766-1

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