Structuring M&A Offers: Auctions, Negotiations and Go-Shop. Provisions

Size: px
Start display at page:

Download "Structuring M&A Offers: Auctions, Negotiations and Go-Shop. Provisions"

Transcription

1 Structuring M&A Offers: Auctions, Negotiations and Go-Sho Provisions Zhe Wang November 4, 01 Job Market Paer Abstract An imortant yet understudied asect of mergers and acquisitions is the selling rocedure. This aer comares a seller s revenue in a standard English ascending auction to that in a negotiation with a go-sho rovision. In the latter, the target rivately negotiates with a few bidders, signs a tentative merger agreement with one of them, and then solicits additional bids ublicly during a go-sho eriod. With a theoretical framework, I show that a go-sho negotiation generates higher seller revenue than does an auction, when (i) the costs to bidders of learning their valuations are sufficiently high, (ii) the bidders valuations are moderately correlated with each other, and (iii) the bidders rior robabilities of the existence of gains from trade are sufficiently low. The theoretical results are broadly consistent with emirical evidence, and they rovide a novel exlanation for the revalence of go-sho negotiations in rivate equity deals. 1 Introduction The rocedures by which comanies are sold in mergers and acquisitions (M&A) take varying forms. Of articular interest is the revalence of two forms: an ascending auction and a negotiation with a go- I am grateful for the suort I receive from my dissertation committee members Steven Grenadier, Peter DeMarzo, Victoria Vanasco, and Jeffrey Zwiebel. I owe my gratitude to Alexander Gorbenko and Andrey Malenko for generously sharing their data. I have also been fortunate to receive numerous valuable comments from Shai Bernstein, Jeremy Bulow, Yi Chen, Darrell Duffie, Piotr Dworczak, Laurie Simon Hodrick, Xing Li, Paul Milgrom, George Triantis, Jing Zhou, and all articiants in my ractice job market talks. I am resonsible for all remaining errors and omissions. zhewang5@stanford.edu 1

2 sho rovision. While the former rocedure has historically been more revalent, go-sho negotiations have been increasingly oular since emerged in a rivate equity deal in 004. For an examle of a standard auction, consider a merger between two healthcare comanies. On August 18th, 015, the board and the senior management of the target comany Sequenom decided to ursue a business combination in the form of a sale to a strategic buyer. 1 The sale rocess began when the target firm hired the investment bank J.P. Morgan Securities to ublicly solicit bids from 5 otential strategic bidders. Then, the target held an auction in which all interested buyers submitted their bids. Finally, the target signed a merger agreement with one bidder, Laboratory Cororations of America Holdings, which submitted the highest bid $.4 er share, and the deal was settled. This tye of mechanism is also called a re-signing market check, because most market checks are conducted before signing a merger agreement. The other selling rocedure, a go-sho negotiation, aeared before the Leveraged Buyout Boom. An examle concerns the sale of CKE Restaurants to a rivate equity firm Aollo Management. In Setember, 009, three rivate equity firms exressed interest in buying the target. The target s board then set u a secial committee to rivately negotiate with all of them, while excluding the senior management from most of the negotiation rocess. At the end of the negotiation, the target signed a tentative merger agreement with the highest bidder among the three, Thomas H. Lee Partners. The agreement secified a minimum bid $11.05 er share for that bidder, the target s right to solicit other bids in a go-sho eriod after announcing the agreement, and a ayment to Thomas H. Lee in case a suerior roosal aeared during the go-sho eriod. Such ayment includes a $9.8 million termination fee lus a cost reimbursement caed by $5 million. Then, the target ublicly announced the merger agreement in a ress release. During the subsequent 40-day go-sho eriod, the target hired investment bank UBS to contact 4 rivate equity firms and 4 otential strategic buyers, soliciting their interest in making a suerior roosal. Among them, a rivate equity firm Aollo Management toed the original offer with a bid of $1.55 er share, which Thomas H. Lee was not able to match. As a result, Aollo won the deal, while the target aid the termination fee and the cost reimbursement to the initial bidder. Practitioners also refer to such mechanism as a ost-signing market check, because most market checks are conducted after signing a tentative merger agreement. 1 Strategic buyers are usually cororate buyers that look for comanies that will create a synergy with their existing businesses.

3 Standard auctions have been a traditional selling mechanism, which are used in 3% of M&A deals between 003 and 015. A go-sho negotiation, on the other hand, reresents a relatively new mechanism. Originated with deals involving rivate equity buyers, go-sho negotiations continue to be more revalent in deals attracting financial buyers, the majority of which are rivate equity firms. 3 Emirical evidence suggests that the revalence of go-sho negotiations is higher in deals attracting mostly financial buyers (1%) than in deals attracting mostly strategic buyers (3%). 4 The frequency of use of a go-sho negotiation is also higher in bankrutcy sales under Section 33 of Chater 11 (84%) than in non-bankrutcy M&As (5%). 5 In addition, it differs across target industries. The emirical evidence motivates two questions: (1) why are both auctions and go-sho negotiations observed in ractice? () why do we observe cross-sectional variations in the use of go-sho negotiations? Conventional wisdom exlains the use of standard ascending auctions, while attributing the use of go-sho negotiations to agency conflicts. Bulow and Klemerer (009) suggest that an auction generates higher revenue for the seller because it increases bidder articiation. Denton (008) believes that a target management chooses a go-sho negotiation to favor a articular bidder, which has romised the management a large comensation ackage. 7 It has also been heavily debated in courts on whether a go-sho negotiation mechanism has fulfilled the Revlon duties that require the target management to maximize the shareholders value. 8 This aer suggests an alternative exlanation for the use of go-sho negotiations. That is, when information acquisition is costly, a go-sho negotiation generates higher seller revenue than does a standard auction by inducing higher bidder articiation. In such a mechanism, the target bribes one bidder to Source of data: MergerMetrics. 3 Unlike strategic buyers whose synergy with the target comes from combining the two businesses, the synergy between the target and a financial buyer stems from the financial buyer s ability to imrove on the target s cororate governance and caital structure after making the target go rivate. 4 Source of Data: MergerMetrics, As the research of Gorbenko and Malenko (014) shows, deals won by a financial (strategic) buyer attract mostly financial (strategic) bidders. In addition, analysis of MergerMetrics database ( ) imlies that the frequency of use of this mechanism is much higher if the deal is won by a financial buyer (1%) than if the deal is won by a strategic buyer (3%) (it reached % in deals won by a financial buyer in 015). Therefore, go-sho negotiations are more frequently used in deals attracting mostly financial buyers than in those attracting mostly strategic buyers. 5 Source of data of bankrutcy sales: Gilson, Hotchkiss and Osborn (015). Source of data for non-bankrutcy M&As: MergerMetrics In articular, the frequency of use of go-sho negotiations is high if the target is in Consumer Durables, Consumer Non-Durables, and Retail Trade (11%), and it is lower in High-Tech, including Technology Services, Electronic Technology, and Health Technology (3%). Source of Data: MergerMetrics, The author believes that the go-sho eriod in the go-sho negotiation mechanism is essentially window-dressing to reduce litigation risk. See also Antoniades, Calomiris, and Hitscherich (013) about litigation risk concerns. 8 See Subramanian (008) s comarison of the Delaware Chancery Court s decision on In re Tos Comany Shareholders Litigation and on In re Lear Cororation Shareholder Litigation. 3

4 conduct costly information acquisition first and to make a ublic bid. The initial bid, if high enough, will reveal the attractiveness of this deal to other similar buyers for free, and therefore will imrove bidder cometition for this deal. In articular, I build a model in which there are two otential bidders and one seller. It is costly for bidders to learn their values for the target firm, and these values are ositively correlated. I show in the benchmark model that the seller s revenue in a go-sho negotiation is strictly higher than it would be in an English ascending auction when (i) bidders costs of learning their values for the target firm are sufficiently high, (ii) bidders values for the target firm are sufficiently correlated, but not too highly correlated, and (iii) bidders rior robabilities regarding the existence of gains from trade are low enough that no otential bidder would make a serious bid 9 without knowing the existence of gains from trade. I further show that the referential treatment involves both a transfer from the seller to the first bidder in the form of a termination fee, and an inefficient allocation rule that assigns the target firm more often to the initial bidder than to the second bidder. In fact, such referential treatment in favor of the first bidder is inevitable whenever the otimal go-sho negotiation outerforms the otimal ascending auction. The key results of the benchmark model are confirmed by a more elaborate model with normally distributed bidder values and more natural assumtions regarding information technology. I then show that, if the bidders values for the target firm are less correlated, a go-sho negotiation dominates a standard auction within a smaller range of arameters. A rediction of the model is therefore that gosho negotiations are used more often than English ascending auctions when bidders values for the target firm are more correlated. This rediction is broadly consistent with the emirical evidence based on the hand-collected data generously rovided by the authors of Gorbenko and Malenko (014) 10, and the data from MergerMetrics between 003 and 015. The intuition for the key results are as follows. When bidders rior robabilities of gains from trade are low, no bidder will make a serious bid without knowing the existence of gains from trade. This could generate a roblem for an English ascending auction, where information acquisition by bidders must be simultaneous. In articular, when information acquisition is too costly comared to the exected rofit from the bidding game, the cometition among bidders leads to little incentive for all bidders to acquire 9 Here, a serious bid refers to a bid that exceeds the target s stand-alone value. 10 The data was hand-collected from SDC database by the authors. 4

5 information at the same time. This may occur due to a high information cost of learning the existence of gains from trade, a essimistic rior robability of the existence of gains from trade, or an exceedingly high correlation between the bidders values for the seller s firm. 11 As a result, there is little bidder articiation, and the seller s revenue is low. The roblem could otentially be alleviated in go-sho negotiations, where information acquisition is sequential. In this mechanism, the seller first incentivizes one bidder to acquire the information about the existence of gains from trade by romising that bidder a termination fee. By announcing the first bid, the seller then reveals the information acquired by the first bidder to the second otential bidder. If the bidders values for the target firm are sufficiently highly correlated, the second otential bidder becomes informed of the existence of gains from trade for free by learning that the first bidder s value is sufficiently high. This raises bidder articiation relative to the case of English ascending auctions. When the benefit of more bidders being informed of the existence of gains from trade outweighs the cost of referential treatment to the first bidder, the seller s revenue is higher in go-sho negotiations. However, if the bidders values are excessively correlated, go-sho negotiations can no longer imrove uon English ascending auctions. This is because the second stage is similar to Bertrand cometition. Execting very low rofit from the second stage auction, the second bidder will not enter the game even if knowing there is gains from trade. I further consider an extension in which the mechanism is the result of a negotiation between the seller and the first bidder. The main results hold in a manner in this extension, as well as in additional variations of the model. Finally, using the data from MergerMetrics and the data rovided by the authors of Gorbenko and Malenko (014), I resent suggestive emirical evidence on the alternative hyotheses that (1) go-sho negotiations are driven by a bidder with strong bargaining ower, and () the target management uses a go-sho negotiation to favor one bidder while sacrificing the shareholders value. The emirical evidence suggests that the former hyothesis is not lausible, though the latter might lay a role in Management Buyouts where agency conflicts are otentially salient. However, the agency conflicts hyothesis is unlikely to be the entire story, because Management Buyouts are only a small fraction of all deals using a go-sho negotiation. 11 When the correlation is too strong, the bidding game if both bidders acquire information is similar to a Bertrand cometition. Therefore, the information rent given to each bidder would be low. The intuition why a high correlation of bidder values leads to low bidder information rent is similar to that of the Linkage Princile in Milgrom and Weber (198). 5

6 The rest of the aer is organized as follows. Following a literature review, Section describes the model setu. Section 3 finds the otimal ascending auction and go-sho negotiation mechanisms, and comares the seller s revenues between the two. Section 4 considers extensions. Section 5 emirically examines the imlications of the model and alternative hyotheses. Section concludes. The aendices rovides the roof and additional emirical evidence. Related Literature To the knowledge of the author, this is the first formal model that catures the institutional features of go-sho negotiations observed in ractice. Still, the aer is related to the literature on sequential negotiations featuring reemtive bidding, including Fishman (1988), Bulow and Klemerer (009), and Roberts and Sweeting (013). These aers show that a high first bid would reemt information acquisition by the second bidder, under the assumtions that it is costly for the bidders to learn the idiosyncratic art of their values, termination fees are not allowed, and the first bidder is free to make any bid. This aer, however, assumes that it is costly to learn the art of the synergy shared by both bidders. Therefore, referential treatment such as termination fees are essential to incentivizing the first bidder to conduct costly information acquisition and to rovide information externality to the second bidder. In addition, this aer assumes that the seller only allows the first bidder to decide whether to bid above a certain threshold, without revealing the actual bid. This assumtion makes reemtive bidding less of a concern, and allows me to focus on the key channel of the aer. Finally, this aer shows that a sequential negotiation generates higher seller revenue than a standard auction because it increases bidder articiation. However, in Bulow and Klemerer (009), a sequential negotiation is dominated by a standard auction because it reduces bidder articiation. This aer is also related to other works on sequential mechanisms. Povel and Singh (00) show that if both bidders are already informed, and the information of one bidder is more imortant to both bidders, then the otimal mechanism for the seller is a sequential bidding game. Betton, Eckbo, and Thorburn (009) considers a sequential negotiation model of hostile takeover with indeendent bidder values and toehold. Glode and O (01) study the trading rotocol for the sale of a financial asset. They comare the social welfare between a sequential trading game and a static auction, in a setting where the two buyers and the seller s values for the security are interdeendent. On the contrary, my aer aims to exlain cororate transactions. Therefore I assume that the seller s stand-alone value (market caitalization before merger) is common knowledge, where the bidders values are otentially correlated. In addition, I focus on seller revenue otimization instead of social welfare.

7 This aer is also related to the following studies on the benefit of information revelation. Milgrom and Weber (198), and Eso and Szentes (007) investigate the information disclosure in auctions, and show that more information revelation increases the seller s revenue. Duffie, Dworczak and Zhu (015) consider a search model of the trading of financial assets, and they show that revealing the common cost of sellers could increase investor articiation. Sherman and Titman (00) and Sherman (005) investigate the IPO book building. They show that IPO underricing serves to comensate the rimary dealers for information acquisition about the quality of the issued equity, and such information is revealed to the secondary market investors by the bids of rimary dealers. My aer is different for the following reasons. First, IPO underricing models involves both the rimary market and the secondary market, while my model involves only the rimary market. Second, all investors values on the issued equity are identical, while in my model it is essential that the bidders values are not erfectly correlated. Third, rimary dealers who care about their reutation are willing to rovide high quality information. In my model, however, the first bidder would like to avoid revealing the existence of gains from trade, so as to minimize second stage cometition. Another related literature is mechanism design with information acquisition. Persico (000) comares the amount of information acquisition in first-rice and second-rice sealed-bid auctions. Assuming the object will always be sold, Bergemann and Valimaki (00) show that the information acquisition exceeds that of the social otimum in a standard English auction when bidder values are indeendent. Assuming instead that the target firm is sold only if the rice exceeds the target s stand-alone value, my model shows that information acquisition is below social otimum in a standard English auction. Shi (01) considers the otimal mechanism with information acquisition and rivate value, while this aer allows for correlated values. The aer is also related to theory works on multi-stage auctions such as Ye (00), and tender offer auctions such as Schwartz (198), Berkovitch, Bradley and Khanna (1989). Finally, the aer is connected to the following emirical studies. First, it is related to Gorbenko and Malenko (014) who investigate the difference between financial bidders and strategic bidders. Second, it is connected to a surrisingly small emirical literature on go-sho rovisions, which are a key feature of go-sho negotiations. Subramanian (008) and Jeon and Lee (014) claim that go-sho rovisions might benefit the seller comared to the deals with no-sho rovisions. Denton (008) states that gosho is chosen over standard auctions due to agency conflicts between the target management and the 7

8 shareholders. Antoniades, Calomiris, and Hitscherich (015) believe that the over-use of go-shos reflects excessive concerns about litigation risks, ossibly resulting from lawyers conflicts of interest in advising targets. Other related emirical literature includes Boone and Mulherin (007b) that comares multibidder takeover deals to single-bidder takeover deals, Boone and Mulherin (007a) and Burch (001) about termination fees and other deal rotections, and Gilson, Hotchkiss and Osborn (015) about stalking horse bid in bankrutcy rocess. Setu of the Model There two bidders and one seller..1 Valuations The seller s outside otion if no sale is m, which can be thought of as the stock market caitalization. The bidders stand-alone values if there is no trade with the seller are both n. The values of the outside otions are common knowledge. The two bidders values for the target firms are W 1 = m + x 1 + V W = m + x + V Therefore, the synergy between bidder i and the target is u 1 = x 1 + V u = x + V where the common art of the synergy is Z, with robability V = Z, with robability 1 with Z > 0. This art is due to the common exertise among the two bidders. The idiosyncratic synergy of bidder i is x i U [l, h], i.i.d., and is also indeendent to the common synergy V. 8

9 I make the following assumtions for the valuations. Assumtion 1. (common synergy as indicator of gains from trade) Z + x i > 0, and Z + x i < 0, x i [l, h]. Assumtion. (uninformed buyer does not bid) E (V ) + x i < 0, x i [l, h]. Discussion on Assumtion 1 and Assumtion. Assumtion 1 imlies that the variation of the common art dwarfs that of the idiosyncratic art, so the common synergy is the indicator of gains from trade. A direct imlication of this assumtion is that bidders values for the target firm are highly correlated. Assumtion states that, if a buyer does not know whether there exists gains from trade, the buyer will not make a bid that exceeds the target s stand-alone value. This is true even if the realized idiosyncratic synergy reaches the highest value ossible. That is, if a otential bidder neither ays the cost to acquire the information of the common synergy nor learns about this information from others, the otential bidder effectively dros out from the bidding game. For this reason, the seller would like as many bidders to become informed about V as ossible.. Information Technology Without information acquisition, neither the seller nor the bidders know V or x i, i = 1,. The seller can invite bidders to conduct information acquisition. If invited, bidder i has the otion to acquire information in the following order: If aying a cost c V, bidder i can learn about V erfectly; Then, if aying a cost c x, bidder i can learn about x i erfectly, indeendent to whether bidder 1 has learned V or not. The information is rivate to the bidder who acquired it. In addition, I follow the tradition of the literature of information acquisition, and assume that the action of information acquisition is non-observable by others. This is because an outsider cannot verify whether a bidder has exerted effort. I make the following assumtion about how the cost of information acquisition is allocated between learning about the common art and the idiosyncratic art. Assumtion 3. (info acquisition mostly on common art) c V > 0, c x = 0. 9

10 Assumtion 3 states that the cost of information acquisition on the common art of the synergy is significant, while the idiosyncratic art of the synergy is negligible. This assumtion is made in accordance with Assumtion 1, following the logic that more (less) information acquisition effort is required if the amount of uncertainty is higher (lower). In addition, I consider the information acquisition of the common art V and the idiosyncratic art x i searately. That is, it is ossible that a bidder learns only x i but does not exert the effort to learn V. I also assume that the otion to learn about the common synergy takes lace before that of the idiosyncratic art of synergy for tractability. 1 In Section 4., I will consider a model with a more natural setting on information acquisition technology and normally distributed valuations. I show with numerical examles that the key results in the benchmark models still hold. Define entry for a bidder in this model as (i) the bidder has learned both V and x i, and (ii) the bidder submits a bid higher than the target s stand-alone value (a serious bid). Under the settings above, knowing V is the necessary and sufficient condition for entry because the idiosyncratic art of synergy x i is always learned 13, and there is no additional logistic bidding cost. The information acquisition cost c V is then equivalent to the entry cost..3 The Ascending Auction and Go-Sho Negotiation Mechanisms I now make formal characterizations of the ascending auction and go-sho negotiation mechanisms by secifying their timelines. A standard English ascending auction t = 0, the seller otimally chooses a reserve rice r, announces it and commits to it. t = 1, the seller invites both bidders for information acquisition, the technology of which is secified in Section.. t =, the seller holds an English auction (ascending auction) with reserve rice r. 1 Hence, there would be no contingent information acquisition on the common art of synergy based on the value of x i. These assumtions allow me to focus on the information acquisition of the common art of the synergy, while avoiding analyzing the interaction between the information acquisition about the common art and the rivate art. 13 For this reason, in my model, a high first bid does not deter entry by the second bidder. 10

11 t=0 t=1 t= The seller otimally chooses reserve rice, announces it and commits to it. The seller invites both bidders for information acquisition. Each bidder first decides on learning, then learns regardless. The seller holds an English auction (ascending auction) with reserve rice. Figure.1: Timeline: An English Ascending Auction A go-sho negotiation t = 0, the seller otimally chooses the trilet (b 1, T F, r B ) (will be defined in the timeline), announces it and commits to it. t = 1, the seller invites bidder 1 for information acquisition, the technology of which is secified in Section.. t = 1.5, the seller asks if bidder 1 is willing to join the English auction haening at the final date and bid at least b 1, in exchange for termination fee T F. If bidder 1 agrees, the seller romises to ay bidder 1 a termination fee T F if bidder 1 loses the deal; otherwise, bidder 1 is excluded from the game, and the seller moves on to bidder. t = 1.75, the seller announces bidder 1 s decision of accetance or rejection. Then, the seller invites bidder to acquire information regardless, the technology of which is secified in Section.. t =, If bidder 1 is not excluded, the two bidders begin an English auction (ascending auction) with a reserve rice b 1 and a termination fee T F to bidder 1; otherwise, the seller sets a reserve rice r B for an English auction with only bidder. Figure.1 and. illustrate the timelines. The italic arts in Figure. are the key elements in go-sho negotiation that makes the mechanism different from a standard English auction. 11

12 t=0 t=1 t=1.5 t=1.75 t= The seller otimally chooses (,, ), announces them and commits to them. The seller invites bidder 1 for information acquisition. Bidder 1 first decides on learning, then learns regardless. The seller asks if The seller bidder 1 accets to announces bid at least, in bidder 1 s exchange for a decision. termination fee. The seller Yes: bidder 1 gets then invites if not winning; bidder for information No: bidder 1 is excluded. acquisition regardless. The seller holds an English auction (ascending auction). Reserve rice: if bidder 1 accets: ; if bidder 1 rejects:. Figure.: Timeline: Go-Sho Negotiation Note that I assume the auctions to be English ascending auctions. In such auctions, the rice continuously increases beginning with the reserve rice. A bidder dros out from the auction if the rice exceeds the bidder s willingness to ay. If, after a bidder has droed out, there is only one bidder left, then the only bidder that remains wins and ays the rice at which the revious bidder droed out. If all excet one bidder dro out as soon as the rice exceeds the reserve rice, the remaining bidder wins and ays the reserve rice. I assume an English auction because, with multile rounds of bidding, a takeover auction in ractice is more like an English auction comared to sealed-bid auctions (first rice or second rice) or a descending auction. 14 I make the following two assumtions for both mechanisms. Assumtion 4. Termination fee is non-negative. Assumtion 5. Reserve rice is no lower than the target s stand-alone value m. Assumtion. If the second bidder wins, the target reduces the firm value by the amount of the termination fee and ays that amount to the initial bidder, before delivering the firm to the second bidder. Assumtion 4 is a common restriction in bidding games due to bidders concern about the bidding game being a scam. It is essentially a restriction of limited liability that imlies no strictly ositive entry fee. Assumtion 5 is made because it is difficult for the seller to commit to sell at a rice lower than 14 This view is shared by Gorbenko and Malenko (014), who furthermore oint out the comlicated nature of the format of auctions used in mergers and acquisitions. Therefore, an English auction is only a reasonable aroximation of the auction format observed in ractice. 1

13 its outside otion. Section shows that if instead of Assumtion, we assume the seller ays the termination fee out of the roceeds collected from the second bidder, all results remained to be the same. 3 Otimal English Auction and Go-Sho Negotiation, and Comarison between the Two 3.1 Seller s Objective and Equilibrium Concet The seller s objective is to maximize revenue. By choosing an ascending auction, the seller otimizes over the reserve rice r; by choosing a go-sho negotiation, it otimizes over the trilet (b 1, T F, r B ), which includes the minimum bids romised by the first bidder (b 1 ), the termination fee ayable to the first bidder (T F ), and the reserve rice in the final stage auction if the first bidder is excluded (r B ). The equilibrium concet used in this model is Perfect Bayesian Nash Equilibrium. As for the equilibrium refinement criterion for multile equilibria in the bidding stage, I consider the weakly dominant strategy equilibrium; for multile equilibria in the information acquisition stage, I follow the tradition of mechanism design by assuming that the seller induces the most desirable equilibrium; if seller is indifferent among all equilibria, I assume that the seller chooses the equilibrium that is continuous in arameters. 3. Seller s Otimal Revenue in a Standard English Ascending Auction Proosition 3.1 summarizes the seller s otimal revenue and corresonding equilibrium. Proosition 3.1. The seller s revenue under the otimal reserve rice and the otimal equilibrium under the reserve rice are: (1) when c V [0, () ], both bidders acquire information. The seller s revenue is m+ () when c V ( (), c], both bidders acquire information with robability 1 c V () (h+l+3z) The seller s revenue is m + 3((h+l+Z) c V ) 4(h+l+3Z). ( Z + l + 3 ). (0, 1). (3) when c V ( c, () ], only one bidder acquires information. The seller s revenue is m + (Z + l). (4) when c V ( (), (Z + l) + (h l)], only one bidder acquires. The seller s revenue is m + ) (Z + 1 (h + l) c V. (5) when c V ((Z + l) + (h l), + ), no one acquires information. The seller s revenue is m. Here, c = (h+l+z) (Z+l)(h+l+3Z) 3. 13

14 0 h +, h Full Entry: Both bidders acquire info about. Partial Entry: Either both bidder acquire info about with mixed-strategy, or only one bidder acquires. No Entry: No bidder acquires info about. Figure 3.1: Bidder Entry in a Standard Ascending Auction Denote c ( (h l)) = (), and c ( (h l), (Z + l)) = (Z + l) + 1 (h l), we have Figure 3.1 summarizing the extent of entry (number of bidders informed of V ). Intuition for Proosition 3.1 and Figure 3.1 When deciding whether to acquire information in a standard English auction, a bidder trades-off the cost of information acquisition c V against the otential rofit from the bidding game. The otential rofit from the bidding game consists of two arts. The first art is the minimum level of synergy, (Z + l). The second art consists of the information rent due to the uncertainty in the rivate art of the synergy, which is roortional to (h l). Therefore, how c V is comared to (Z + l) and (h l) will determine the level of entry. As c V increases, there would be less information acquisition and hence less entry. Therefore, the mechanism of ascending auction has the roblem of insufficient entry. 3.3 Seller s Otimal Revenue in go-sho negotiations From the discussion on an English ascending auction, we know that, when c V is large, there might be insufficient information acquisition about the existence of gains from trade, and hence, there would be insufficient entry. With a go-sho negotiation in the form of a sequential negotiation, however, we could otentially solve the roblem by comensating one bidder to acquire information and revealing it to the other. In this way, both bidders learn the value of V, and the seller achieves full entry. Following this logic, we focus on go-sho negotiation mechanisms that imlement equilibrium of the following form and otimize within this category: For tractability, I restrict attention to go-sho negotiation mechanisms that induce a ure-strategy equilibrium of infor- 14

15 Bidder 1 acquires information about V ; Bidder 1 accets the rice floor b 1 if and only if V = Z; The seller s revenue is non-negative. I denote this case as the go-sho negotiation fully revealing V, in which bidder 1 s decision to accet the rice floor b 1 fully reveals the value of V. Later, I will show that the otimal go-sho negotiation that fully reveals V remains otimal if considering all otential tyes of equilibrium to imlement, as long as the cost c V is in a reasonable range. Incentive Comatible Problems in go-sho negotiations Before deriving the otimal go-sho negotiation ste-by-ste, it is helful to discuss the key difficulties regarding imlementing the equilibrium above. First, the seller needs to incentivize bidder 1 to acquire information and rovide information externality. There is a hold-u roblem, because information acquisition is not contractable. The solution is to comensation bidder 1 for info acquisition with termination fee T F, conditional on the first bid is high enough (higher than b 1 ), because a high willingness to ay imlies that the information has been acquired. Second, the seller has to incentivize bidder 1 with V = Z not to mimic V = Z, because bidder 1 with V = Z tries to hide the existence of gains from trade to avoid cometition. The solution is to exclude bidder 1 if the first bid is too low (lower than b 1 ). Finally, the seller needs to incentivize bidder 1 with V = Z not to mimic V = Z, because bidder 1 with V = Z tries to mimic V = Z to get the termination fee T F. The solution in this case is to set the rice floor b 1 to be high enough, such that acceting it imlies some chance of winning. Next, we will derive the otimal go-sho negotiation mechanism Otimal go-sho negotiation fully revealing V The following roosition describes the equilibrium induced by the otimal go-sho negotiation mechanism that fully reveals V. mation acquisition. Focusing otimization on this category may not be as restrictive as it may seem. It is ossible that the otimal go-sho negotiation mechanism must induce bidder 1 to acquire information, and bidder 1 accets b 1 only if V=Z, as long as the cost of information acquisition is too large. Intuitively, this is because (1) it is not rofitable for the seller to have at most one bidder informed when it is ossible to make both bidders informed, and () there is no oint in retaining bidder 1 if V=-Z. 15

16 Proosition 3.. (equilibrium under the otimal go-sho negotiations) Suose c V min{ (1 ) Z 1 (h l), (Z + l + 54 (h l))}. Under the otimal (b 1, T F, r B ), there exists an equilibrium in which (i) Both bidders articiate in the mechanism. (ii) Bidder 1 acquires information about V, accets the minimum bid if V = Z regardless of x 1, and rejects otherwise. If acceting the rice floor, Bidder 1 s rice at which to dro out of the English auction is. m + Z + x 1 T F b 1 = m + b 1 if x 1 b 1 + T F Z m if x 1 < b 1 + T F Z m (iii) Bidder learns V from bidder 1 s action and therefore does not acquire information about V. Bidder believes that V = Z iff bidder 1 accets the rice floor b 1. Bidder s rice at which to dro out is m + ˆV + x T F in the English auction, where ˆV is the value of V learned from bidder 1 s action. This roosition illustrates the essential strength of a go-sho negotiation over an ascending auction. That is, by making both bidders informed of the existence of gains from trade, a go-sho negotiation imroves entry. However, the referential treatment in a go-sho negotiation mechanism could otentially be a drawback. To see how the forces weigh against each other, I derive the roof of Proosition 3. and look for the exact form of the otimal (b 1, T F, r B ). Using backward induction, I solve the otimal go-sho negotiation mechanism fully revealing V. Suose that bidder 1 has acquired information. Let us consider the English auction at t =. The case with bidder 1 rejecting the rice floor is straightforward. Bidder 1 is excluded from the trade, and bidder also dros out from the game because V = Z is revealed. The lemma below 1 derives the equilibrium 1 Here is a roof of the lemma. In the English auction, bidder 1 makes the first bid b 1. If at b 1, bidder decides to dro out, and bidder 1 therefore wins, aying b 1. If bidder is able to to b 1, each bidder i continues to to the oonent s bid until the rice level reaches the threshold of droing out, which is b i. To rove the form of b 1 and b, we first consider bidder 1 s dominant strategy. We know that bidder 1 has committed not to dro out until b 1. Starting with m + u 1 T F < b 1, suose b < b 1, i.e., bidder dros out at the beginning of the auction. Then, bidder 1 is indifferent about droing out at any b 1 b 1, because bidder 1 always wins and ays b 1. Suose b b 1 ; then, bidder 1 dros out at b 1 because droing out at any level strictly higher than b 1 weakly increases the chance of winning for bidder 1 and weakly increases the rice to ay for b 1. Since m + u 1 b 1 < T F, winning and aying b 1 already gives bidder 1 negative rofit, not to mention if the rice of winning is higher than b 1. Therefore, to minimize loss, bidder 1 will not dro out at a level higher than b 1. Next, consider the case with m + u 1 T F b 1. Then, following the standard argument with a tyical English auction, droing out at the net value of winning m + u 1 T F is the dominant strategy for bidder 1. Second, we consider bidder s dominant strategy to dro out. The standard argument in a tyical English auction leads to the same conclusion that b = m + u T F. 1

17 of the continuation game in the English auction at t = if bidder 1 accets the rice floor b 1. Lemma 3.1. Suose that both bidders know V erfectly and that, in an English auction, the seller has already set a reserve rice b 1 and bidder 1 has agreed to bid at least b 1 for all x 1 [l, h]. In addition, suose that the seller commits to ay T F to bidder 1 if bidder 1 loses. Then it is a weakly dominant strategy for bidder 1 and bidder to dro out at b 1 = m + max (u 1 T F, b 1 ), and b = m + u T F resectively, where u i = V + x i, i = 1, is the synergy between bidder i and the target. Note that m + u i T F, i = 1, are the bidder i s valuation of the firm if winning the auction, net of the rofit if losing because, for bidder 1, winning gives n + m + u 1, while losing gives n + T F ; for bidder, winning gives n + m + u T F because T F is aid out of the value of the firm according to Assumtion, while losing leads to outside otion n. Termination fee T F and rice floor b 1 together determine the allocation distortion in favor of bidder 1 (i.e. the target firm is inefficiently assigned to bidder 1 more often), and the transfer from the seller to bidder 1. In articular, if b 1 increases while fixing T F, it is harder for bidder to to the first bid b 1. However, b 1, which is the rice that bidder 1 has to ay to the seller if bidder does not to the first bid, would be higher too. Therefore, there is more allocation distortion in favor of bidder 1, but less transfer from the seller to bidder 1. On the other hand, if T F increases while fixing b 1, it is also harder for bidder to to the first bid when taking into account of a higher T F. Moreover, if bidder is able to to the first bid b 1, bidder s bid in the second stage would decrease by the amount by which T F increases; then, bidder 1 has to ay less if winning over bidder in this case. Therefore, the target s firm is also inefficiently assigned to bidder 1 more often, and the transfer from the seller to bidder 1 is higher. Since allocation distortion is affected by both T F and b 1, I will define a new variable to isolate the force affecting allocation inefficiency. In articular, I define as = b 1 (m + Z + l T F ). That is, if V = Z is revealed to both bidders, is the difference between bidder 1 s romised minimum 17

18 bid b 1 and bidder s minimum rice to dro out in the second-stage auction. This term measures how difficult it is for bidder to to the first bid b 1, because the robability of the first bid b 1 being toed is Pr (x > ) = 1. The allocation rule of the game if V = Z is uniquely determined by, according to Lemma 3. below. Lemma 3.. Consider the equilibrium described in Lemma 3.1 and consider the case with V = Z. If [0, h l] so that l + [l, h]. (i) if x 1 l +, or if x 1 < l + and x l +, bidder i wins if and only if x i x i. (ii) if x 1 < l + and x < l +, bidder 1 always wins. If 0, there is no distortion; if > h l, bidder 1 always wins. A direct imlication of Lemma 3. is Proosition 3.3. Proosition 3.3. ( ins down allocation distortion, T F determines transfer) 17 (i) The target firm is inefficiently assigned to bidder 1 if and only if > 0. The exected efficiency ( ) loss from such distortion is l+, which is increasing in. (ii) The termination fee T F is only a transfer from the seller to bidder 1 and does not create distortion. In the case of V = Z, Figure 3. summarizes the bidding strategy of both bidders characterized in Lemma 3.1, and the distortion of allocation in Proosition 3.3. The arrows demonstrate the bidding strategies. The arts marked by bold red segments cature the scenario where there exists allocation distortion. That is, when x 1 < l + and x < l +, bidder 1 always wins the target firm, regardless of how x 1 is comared to x. For the rest of the cases, the target firm is allocated efficiently. Now that we know the bidding strategy of both bidders, we are ready to rove Proosition 3. by looking at incentive-comatible conditions and individual rationality conditions. First, we check if bidder does not acquire information after observing bidder 1 s decision. This is trivially true because bidder 1 s action reveals erfectly the value of V. Bidder s articiation constraint that the equilibrium utility must be higher than the outside otion n is also true because no information acquisition cost is aid and the rofit of an informed bidder in an English auction is non-negative. Bidder s belief is also consistent with Bayesian udating and bidder 1 s strategy. Therefore, we have roven art (iii) of Proosition 3.. Next, we study bidder 1 s accetance and rejection decision after acquiring information. Suose the otimal [0, h l], which will be verified later in the Aendix. 17 A higher while fixing T F also imlies a lower transfer from the seller to the bidder 1, because b 1 is higher. 18

19 x 1 x h h l + Distortion l l Figure 3.: Bidding Strategy and Allocation Distortion If V = Z, bidder 1 is suosed to turn down the rice floor and obtain its outside otion n. If bidder 1 accets the offer instead, he will dro out at b 1 to minimize the chance of winning because bidder s net valuation from winning is n Z + x n = Z + x, which is negative according to Assumtion 1. Therefore, bidder 1 with V = Z rejects the rice floor x 1 [l, h] if P (x < l + ) (n + m Z + x 1 b 1 ) + (1 P (x < l + )) (n + T F ) < n, x 1 T F + h l ( Z + x 1 l ) < 0, x 1 T F < (Z h + l + ). (3.1) h l If V = Z, we need to make sure that bidder 1 accets the rice floor. If x 1 l +, bidder 1 s bid is unaffected by the rice floor b 1 = m + Z + l + T F, since this is the minimum rice for him to dro out of the English auction. Then b 1 = m + u 1 T F, b = m + u T F. Then, bidder 1 s exected ayoff by acceting the rice floor is P (x l + ) (P (x 1 x x l + ) E [n + m + Z + x 1 m Z x + T F x 1 x, x l + ] +P (x 1 < x x l + ) (n + T F )) +P (x < l + ) (n + m + Z + x 1 b 1 ) = n + T F + (x 1 l ) (h l) + h l (x 1 l ) U, T F 0, x 1 [l +, h] 19

20 Therefore, bidder 1 with x 1 l + always accets the rice floor for any non-negative T F. If x 1 < l + and bidder 1 accets the rice floor, he would bid b 1 to minimize his loss. Then, bidder 1 with x 1 accets the rice floor if P (x < l + ) (n + m + Z + x 1 b 1 ) + (1 P (x < l + )) (n + T F ) n h l (x 1 l ) + T F 0 x 1 l + T F h l. Therefore, if T F (i.e., T F 0), then all x 1 < l + accet the rice floor and bid b 1. In this case, bidder 1 s bid is m + Z + x 1 T F, b 1 = b 1, x 1 l + x 1 < l + Therefore, bidder 1 with V = Z accets the rice floor for all x 1 [l, h] if and only if T F h l. (3.) Finally, we look for the conditions under which bidder 1 is willing to acquire information. If bidder 1 does not acquire information and rejects the rice floor, he obtains n. If he accets the rice floor, the best he can do is to bid b 1 in the auction because his synergy is negative for all x 1 according to Assumtion. Therefore, he gets P (x < l + ) (n + m + E (V ) + x 1 b 1 ) + (1 P (x < l + )) (n + T F ) = n + h l (Z + (1 ) ( Z) + x 1 Z l + T F ) + h l T F h l = n + T F + h l ( Z (1 ) + x 1 l ) (3.3) Hence, bidder 1 s exected utility if not acquiring information about V is [ n + E x1 {max 0, T F + ] h l ( Z (1 ) + x 1 l ) }. 0

21 We then derive the exression for bidder 1 s exected utility if acquiring information. In this case, with T F, all x 1 accets the rice floor. Bidder 1 s utility of acquiring information is then U 1 = c V + n + P (x l + ) P (x 1 l + ) {P (x 1 x x 1, x l + ) T F +P (x 1 x x 1, x l + ) E (x 1 + Z Z x + T F x 1 x, x 1, x l + )} + P (x < l + ) E (x 1 + Z Z l + T F x < l + ) + P (x l + ) P (x 1 < l + ) T F [ (h l )3 = c V + n + T F + (h l) + ( l + h l ) ]. h l Hence, for bidder 1 to acquire information, we need [ U 1 n + E x1 {max 0, T F + ] h l ( Z (1 ) + x 1 l ) } (3.4) In addition, for bidder 1 to be willing to enter the mechanism, we need U 1 n. (3.5) Combine the conditions (3.1) to (3.5), recall that Assumtion 4 leads to T F 0, and assume that 0 h l. 18 We can then write down the conditions for a go-sho negotiation to induce a searating equilibrium fully revealing V, and the roblem of the seller s otimization of revenue under those 18 Will be verified in the Aendix. 1

22 conditions. max,t F (1 ) m + [P (x < l + ) (m + Z + l + T F ) +P (x l + ) P (x 1 l + ) E (m + Z + min (x 1, x ) T F x 1, x l + ) +P (x l + ) P (x 1 < l + ) (m + Z + l + T F )] = m + (Z } + l + {{ T F } ) (h l ) (h l) rice floorb }{{} 1 extra rofit from cometition s.t. (a) T F 0, (Assumtion 4) (b) 0 h l, (restrictions, will be verified later) (c) T F h l (Z h + l + ), (tye V = Z rejects b 1 ) [ (d) U 1,F A n + E x1 {max 0, T F + ] h l ( Z (1 ) + x 1 l ) }, (Bidder 1 acquires info) (e) T F h l, (V is fully revealed: x 1accets if V = Z) (f) U 1,F A n, (Bidder 1 articiates) (3.) In the case with V = Z, bidder 1 is excluded from the game. Therefore, bidder would also bid below m, and the seller is indifferent between any r B m. Let the otimal r B = m + Z + l. Solving the roblem above leads to the full characterization of the otimal go-sho negotiation mechanism fully revealing V, as stated below. Proosition 3.4. (An otimal go-sho negotiation that fully reveals V) Suose c V < min{ (1 ) Z 1 (h l), (Z + l + 54 (h l))}, and restrict attention to go-sho negotiation mechanisms that induce equilibria in which bidder 1 acquires information and accets the rice floor if and only if V = Z. Then, the otimal (b 1, T F, r B ) within this category includes a rice floor b 1 = m + Z + l + T F and r B = m + Z + l, where (, T F ) is characterized as follows: (i) if c V [ 1/55, min{ (1 ) Z 1 (h l), (Z + l + 54 (h l))}), then ( (, T F ) = 3 17 (h l), 1 (h l) + c ) V.

23 0 h +, h,, Full Entry: Bidder 1 acquires info, and accets rice floor iff =. Bidder learns from bidder 1. Figure 3.3: Bidder Entry in Go-Sho Negotiations (ii) if c V [, 1/55 ), then [0, 3 (h l)) and is the unique solution for [ ] c V = 3 (h l) 3 3 (h l) (h l) and that it is strictly increasing in c V. T F satisfies T F = h l. (iii) if c V [0, ), then (, T F ) = (0, 0). Denote c ( (Z + l), (h l),, Z) = min{ (1 ) Z 1 (h l), (Z + l + 54 (h l))}. Then, similar to Figure 3.1, Figure 3.3 summarizes the level of entry for bidders in go-sho negotiations. Comarison of the two figures show that go-sho negotiations create higher entry for a wide range of c V. 3.4 Go-sho negotiations imlementing other tyes of equilibria The otimal go-sho negotiation mechanism that imlements equilibrium fully revealing V remains to be otimal if I consider imlementation of all tyes of equilibria. Proosition 3.5. The otimal go-sho negotiation mechanism is stated in Proosition

24 0 h +, h,, Seller Revenue: Go-Sho Negotiation = Auction Both: full bidder articiation Seller Revenue: Go-Sho Negotiation > Auction Go-Sho: full bidder articiation Auction: artial/zero bidder articiation Figure 3.4: Comarison between the Two Mechanisms: Seller Revenue and Bidder Particiation 3.5 Revenue Comarison between a Go-Sho Negotiation and an English Ascending Auction This section introduces the key result of the aer by comaring the seller s revenue under the otimal go-sho negotiation mechanism and the otimal ascending auction mechanism. Proosition 3.. Restrict attention to c V such that 0 c V c ( (Z + l), (h l),, Z). (i) If c V is large enough, i.e., c V > c ( (h l)), the seller s revenue in the otimal go-sho negotiation mechanism is strictly higher than that in the otimal ascending auction. (ii) If c V is small enough, i.e., c V c ( (h l)), the otimal go-sho negotiation mechanism achieves the same revenue as in the otimal ascending auction. Moreover, go-sho negotiations can create higher revenue for the seller in go-sho negotiation than in the otimal ascending auction if and only if it increases bidder entry. The result is intuitive. go-sho negotiations imrove the seller s revenue because they increase entry. Recall Figure 3.1 and 3.3 that show the level of entry in the two mechanisms. When c V is very small, both bidders acquire information in an English auction; hence, there is already full entry. Therefore, go-sho negotiations cannot imrove the revenue. When c V is large enough but not unreasonably high, go-sho negotiations induce full entry, while English ascending auctions induce at most artial entry, so the revenue from go-sho negotiations is strictly higher. Figure 3.4 summarizes the key results of the revenue comarison The Trade-offs between a go-sho negotiation and an ascending auction Whenever the revenue in the otimal go-sho negotiation is higher than that of the otimal ascending auction, the difference can be decomoses into the forces in favor of and against go-sho negotiation as 4

Online Appendix for The Timing and Method of Payment in Mergers when Acquirers Are Financially Constrained

Online Appendix for The Timing and Method of Payment in Mergers when Acquirers Are Financially Constrained Online Aendix for The Timing and Method of Payment in Mergers when Acquirers Are Financially Constrained Alexander S. Gorbenko USC Marshall School of Business Andrey Malenko MIT Sloan School of Management

More information

COMMUNICATION BETWEEN SHAREHOLDERS 1

COMMUNICATION BETWEEN SHAREHOLDERS 1 COMMUNICATION BTWN SHARHOLDRS 1 A B. O A : A D Lemma B.1. U to µ Z r 2 σ2 Z + σ2 X 2r ω 2 an additive constant that does not deend on a or θ, the agents ayoffs can be written as: 2r rθa ω2 + θ µ Y rcov

More information

Handout #3: Peak Load Pricing

Handout #3: Peak Load Pricing andout #3: Peak Load Pricing Consider a firm that exeriences two kinds of costs a caacity cost and a marginal cost ow should caacity be riced? This issue is alicable to a wide variety of industries, including

More information

Trading OTC and Incentives to Clear Centrally

Trading OTC and Incentives to Clear Centrally Trading OTC and Incentives to Clear Centrally Gaetano Antinolfi Francesca Caraella Francesco Carli March 1, 2013 Abstract Central counterparties CCPs have been art of the modern financial system since

More information

Optimism, Delay and (In)Efficiency in a Stochastic Model of Bargaining

Optimism, Delay and (In)Efficiency in a Stochastic Model of Bargaining Otimism, Delay and In)Efficiency in a Stochastic Model of Bargaining Juan Ortner Boston University Setember 10, 2012 Abstract I study a bilateral bargaining game in which the size of the surlus follows

More information

SIGNALING IN CONTESTS. Tomer Ifergane and Aner Sela. Discussion Paper No November 2017

SIGNALING IN CONTESTS. Tomer Ifergane and Aner Sela. Discussion Paper No November 2017 SIGNALING IN CONTESTS Tomer Ifergane and Aner Sela Discussion Paer No. 17-08 November 017 Monaster Center for Economic Research Ben-Gurion University of the Negev P.O. Box 653 Beer Sheva, Israel Fax: 97-8-647941

More information

Econ 101A Midterm 2 Th 8 April 2009.

Econ 101A Midterm 2 Th 8 April 2009. Econ A Midterm Th 8 Aril 9. You have aroximately hour and minutes to answer the questions in the midterm. I will collect the exams at. shar. Show your work, and good luck! Problem. Production (38 oints).

More information

Voting with Behavioral Heterogeneity

Voting with Behavioral Heterogeneity Voting with Behavioral Heterogeneity Youzong Xu Setember 22, 2016 Abstract This aer studies collective decisions made by behaviorally heterogeneous voters with asymmetric information. Here behavioral heterogeneity

More information

How Often Should You Reward Your Salesforce? Multi-Period. Incentives and Effort Dynamics

How Often Should You Reward Your Salesforce? Multi-Period. Incentives and Effort Dynamics How Often Should You Reward Your Salesforce? Multi-Period Incentives and Effort Dynamics Kinshuk Jerath Fei Long kj2323@gsb.columbia.edu FeiLong18@gsb.columbia.edu Columbia Business School Columbia Business

More information

4. Score normalization technical details We now discuss the technical details of the score normalization method.

4. Score normalization technical details We now discuss the technical details of the score normalization method. SMT SCORING SYSTEM This document describes the scoring system for the Stanford Math Tournament We begin by giving an overview of the changes to scoring and a non-technical descrition of the scoring rules

More information

Theory of Externalities Partial Equilibrium Analysis

Theory of Externalities Partial Equilibrium Analysis Theory of Externalities Partial Equilibrium Analysis Definition: An externality is resent whenever the well being of a consumer or the roduction ossibilities of a firm are directly affected by the actions

More information

1 Gambler s Ruin Problem

1 Gambler s Ruin Problem Coyright c 2017 by Karl Sigman 1 Gambler s Ruin Problem Let N 2 be an integer and let 1 i N 1. Consider a gambler who starts with an initial fortune of $i and then on each successive gamble either wins

More information

Introduction to Probability and Statistics

Introduction to Probability and Statistics Introduction to Probability and Statistics Chater 8 Ammar M. Sarhan, asarhan@mathstat.dal.ca Deartment of Mathematics and Statistics, Dalhousie University Fall Semester 28 Chater 8 Tests of Hyotheses Based

More information

Economics 101. Lecture 7 - Monopoly and Oligopoly

Economics 101. Lecture 7 - Monopoly and Oligopoly Economics 0 Lecture 7 - Monooly and Oligooly Production Equilibrium After having exlored Walrasian equilibria with roduction in the Robinson Crusoe economy, we will now ste in to a more general setting.

More information

Transmission charging and market distortion

Transmission charging and market distortion Transmission charging and market distortion Andy Philott Tony Downward Keith Ruddell s Electric Power Otimization Centre University of Auckland www.eoc.org.nz IPAM worksho, UCLA January 13, 2016 1/56 Outline

More information

MANAGEMENT SCIENCE doi /mnsc ec

MANAGEMENT SCIENCE doi /mnsc ec MANAGEMENT SCIENCE doi 0287/mnsc0800993ec e-comanion ONLY AVAILABLE IN ELECTRONIC FORM informs 2009 INFORMS Electronic Comanion Otimal Entry Timing in Markets with Social Influence by Yogesh V Joshi, David

More information

Solutions to exercises on delays. P (x = 0 θ = 1)P (θ = 1) P (x = 0) We can replace z in the first equation by its value in the second equation.

Solutions to exercises on delays. P (x = 0 θ = 1)P (θ = 1) P (x = 0) We can replace z in the first equation by its value in the second equation. Ec 517 Christohe Chamley Solutions to exercises on delays Ex 1: P (θ = 1 x = 0) = P (x = 0 θ = 1)P (θ = 1) P (x = 0) = 1 z)µ (1 z)µ + 1 µ. The value of z is solution of µ c = δµz(1 c). We can relace z

More information

k- price auctions and Combination-auctions

k- price auctions and Combination-auctions k- rice auctions and Combination-auctions Martin Mihelich Yan Shu Walnut Algorithms March 6, 219 arxiv:181.3494v3 [q-fin.mf] 5 Mar 219 Abstract We rovide for the first time an exact analytical solution

More information

Optimal Organization of Financial Intermediaries

Optimal Organization of Financial Intermediaries Otimal Organization of Financial Intermediaries Siros Bougheas Tianxi Wang Setember 2014 Abstract This aer rovides a unified framework for endogenizing two distinct organizational structures for financial

More information

A search cost model of obfuscation

A search cost model of obfuscation RAND Journal of Economics Vol. 43, No. 3, Fall 2012. 417 441 A search cost model of obfuscation Glenn Ellison and Alexander Wolitzky This article develos models in which obfuscation is individually rational

More information

A Social Welfare Optimal Sequential Allocation Procedure

A Social Welfare Optimal Sequential Allocation Procedure A Social Welfare Otimal Sequential Allocation Procedure Thomas Kalinowsi Universität Rostoc, Germany Nina Narodytsa and Toby Walsh NICTA and UNSW, Australia May 2, 201 Abstract We consider a simle sequential

More information

Sequential Choice of Sharing Rules in Collective Contests

Sequential Choice of Sharing Rules in Collective Contests Sequential Choice of Sharing Rules in Collective Contests Pau Balart Sabine Flamand Oliver Gürtler Orestis Troumounis February 26, 2017 Abstract Grous cometing for a rize need to determine how to distribute

More information

Sequential Search Auctions with a Deadline

Sequential Search Auctions with a Deadline Sequential Search Auctions with a Deadline Joosung Lee Daniel Z. Li University of Edinburgh Durham University January, 2018 1 / 48 A Motivational Example A puzzling observation in mergers and acquisitions

More information

Feedback-error control

Feedback-error control Chater 4 Feedback-error control 4.1 Introduction This chater exlains the feedback-error (FBE) control scheme originally described by Kawato [, 87, 8]. FBE is a widely used neural network based controller

More information

Notes on Instrumental Variables Methods

Notes on Instrumental Variables Methods Notes on Instrumental Variables Methods Michele Pellizzari IGIER-Bocconi, IZA and frdb 1 The Instrumental Variable Estimator Instrumental variable estimation is the classical solution to the roblem of

More information

Stationary Monetary Equilibria with Strictly Increasing Value Functions and Non-Discrete Money Holdings Distributions: An Indeterminacy Result

Stationary Monetary Equilibria with Strictly Increasing Value Functions and Non-Discrete Money Holdings Distributions: An Indeterminacy Result CIRJE-F-615 Stationary Monetary Equilibria with Strictly Increasing Value Functions and Non-Discrete Money Holdings Distributions: An Indeterminacy Result Kazuya Kamiya University of Toyo Taashi Shimizu

More information

Contracting With Synergies

Contracting With Synergies Contracting With Synergies Alex Edmans LBS, Wharton, NBER, CEPR, and ECGI Itay Goldstein Wharton John Zhu Wharton June 13, 2013 Abstract This aer studies multi-agent otimal contracting with cost synergies.

More information

MATH 2710: NOTES FOR ANALYSIS

MATH 2710: NOTES FOR ANALYSIS MATH 270: NOTES FOR ANALYSIS The main ideas we will learn from analysis center around the idea of a limit. Limits occurs in several settings. We will start with finite limits of sequences, then cover infinite

More information

ON THE LEAST SIGNIFICANT p ADIC DIGITS OF CERTAIN LUCAS NUMBERS

ON THE LEAST SIGNIFICANT p ADIC DIGITS OF CERTAIN LUCAS NUMBERS #A13 INTEGERS 14 (014) ON THE LEAST SIGNIFICANT ADIC DIGITS OF CERTAIN LUCAS NUMBERS Tamás Lengyel Deartment of Mathematics, Occidental College, Los Angeles, California lengyel@oxy.edu Received: 6/13/13,

More information

Priority pricing by a durable goods monopolist

Priority pricing by a durable goods monopolist Priority ricing by a durable goods monoolist João Correia-da-Silva February 15 th, 17. Abstract. A durable goods monoolist faces buyers with rivately observed valuations in two eriods, being unable to

More information

Econometrica Supplementary Material

Econometrica Supplementary Material Econometrica Sulementary Material SUPPLEMENT TO WEAKLY BELIEF-FREE EQUILIBRIA IN REPEATED GAMES WITH PRIVATE MONITORING (Econometrica, Vol. 79, No. 3, May 2011, 877 892) BY KANDORI,MICHIHIRO IN THIS SUPPLEMENT,

More information

Online Appendix to Accompany AComparisonof Traditional and Open-Access Appointment Scheduling Policies

Online Appendix to Accompany AComparisonof Traditional and Open-Access Appointment Scheduling Policies Online Aendix to Accomany AComarisonof Traditional and Oen-Access Aointment Scheduling Policies Lawrence W. Robinson Johnson Graduate School of Management Cornell University Ithaca, NY 14853-6201 lwr2@cornell.edu

More information

International Trade with a Public Intermediate Good and the Gains from Trade

International Trade with a Public Intermediate Good and the Gains from Trade International Trade with a Public Intermediate Good and the Gains from Trade Nobuhito Suga Graduate School of Economics, Nagoya University Makoto Tawada Graduate School of Economics, Nagoya University

More information

DYNAMIC COSTS AND MORAL HAZARD: A DUALITY BASED APPROACH. Guy Arie 1

DYNAMIC COSTS AND MORAL HAZARD: A DUALITY BASED APPROACH. Guy Arie 1 DYNAMIC COSTS AND MORAL HAZARD: A DUALITY BASED APPROACH Guy Arie 1 Abstract The marginal cost of effort often increases as effort is exerted. In a dynamic moral hazard setting, dynamically increasing

More information

Tests for Two Proportions in a Stratified Design (Cochran/Mantel-Haenszel Test)

Tests for Two Proportions in a Stratified Design (Cochran/Mantel-Haenszel Test) Chater 225 Tests for Two Proortions in a Stratified Design (Cochran/Mantel-Haenszel Test) Introduction In a stratified design, the subects are selected from two or more strata which are formed from imortant

More information

Selling Information. May 26, Abstract

Selling Information. May 26, Abstract Selling Information Johannes Hörner and Andrzej Skrzyacz May 26, 2011 Abstract We characterize otimal selling rotocols/equilibria of a game in which an Agent first uts hidden effort to acquire information

More information

John Weatherwax. Analysis of Parallel Depth First Search Algorithms

John Weatherwax. Analysis of Parallel Depth First Search Algorithms Sulementary Discussions and Solutions to Selected Problems in: Introduction to Parallel Comuting by Viin Kumar, Ananth Grama, Anshul Guta, & George Karyis John Weatherwax Chater 8 Analysis of Parallel

More information

Centralized decision making against informed lobbying

Centralized decision making against informed lobbying Centralized decision making against informed lobbying Rafael Costa Lima Humberto Moreira Thierry Verdier USP FGV PSE March 9, 01 Abstract We re-address the trade-off between centralized and decentralized

More information

Limiting Price Discrimination when Selling Products with Positive Network Externalities

Limiting Price Discrimination when Selling Products with Positive Network Externalities Limiting Price Discrimination when Selling Products with Positive Network Externalities Luděk Cigler, Wolfgang Dvořák, Monika Henzinger, Martin Starnberger University of Vienna, Faculty of Comuter Science,

More information

arxiv: v1 [cs.gt] 2 Nov 2018

arxiv: v1 [cs.gt] 2 Nov 2018 Tight Aroximation Ratio of Anonymous Pricing Yaonan Jin Pinyan Lu Qi Qi Zhihao Gavin Tang Tao Xiao arxiv:8.763v [cs.gt] 2 Nov 28 Abstract We consider two canonical Bayesian mechanism design settings. In

More information

Advance Selling in the Presence of Experienced Consumers

Advance Selling in the Presence of Experienced Consumers Advance Selling in the Presence of Eerienced Consumers Oksana Loginova X. Henry Wang Chenhang Zeng June 30, 011 Abstract The advance selling strategy is imlemented when a firm offers consumers the oortunity

More information

Prospect Theory Explains Newsvendor Behavior: The Role of Reference Points

Prospect Theory Explains Newsvendor Behavior: The Role of Reference Points Submitted to Management Science manuscrit (Please, rovide the mansucrit number! Authors are encouraged to submit new aers to INFORMS journals by means of a style file temlate, which includes the journal

More information

8 STOCHASTIC PROCESSES

8 STOCHASTIC PROCESSES 8 STOCHASTIC PROCESSES The word stochastic is derived from the Greek στoχαστικoς, meaning to aim at a target. Stochastic rocesses involve state which changes in a random way. A Markov rocess is a articular

More information

Topic: Lower Bounds on Randomized Algorithms Date: September 22, 2004 Scribe: Srinath Sridhar

Topic: Lower Bounds on Randomized Algorithms Date: September 22, 2004 Scribe: Srinath Sridhar 15-859(M): Randomized Algorithms Lecturer: Anuam Guta Toic: Lower Bounds on Randomized Algorithms Date: Setember 22, 2004 Scribe: Srinath Sridhar 4.1 Introduction In this lecture, we will first consider

More information

4. CONTINUOUS VARIABLES AND ECONOMIC APPLICATIONS

4. CONTINUOUS VARIABLES AND ECONOMIC APPLICATIONS STATIC GAMES 4. CONTINUOUS VARIABLES AND ECONOMIC APPLICATIONS Universidad Carlos III de Madrid CONTINUOUS VARIABLES In many games, ure strategies that layers can choose are not only, 3 or any other finite

More information

CHAPTER 5 STATISTICAL INFERENCE. 1.0 Hypothesis Testing. 2.0 Decision Errors. 3.0 How a Hypothesis is Tested. 4.0 Test for Goodness of Fit

CHAPTER 5 STATISTICAL INFERENCE. 1.0 Hypothesis Testing. 2.0 Decision Errors. 3.0 How a Hypothesis is Tested. 4.0 Test for Goodness of Fit Chater 5 Statistical Inference 69 CHAPTER 5 STATISTICAL INFERENCE.0 Hyothesis Testing.0 Decision Errors 3.0 How a Hyothesis is Tested 4.0 Test for Goodness of Fit 5.0 Inferences about Two Means It ain't

More information

University of Warwick, Department of Economics Spring Final Exam. Answer TWO questions. All questions carry equal weight. Time allowed 2 hours.

University of Warwick, Department of Economics Spring Final Exam. Answer TWO questions. All questions carry equal weight. Time allowed 2 hours. University of Warwick, Department of Economics Spring 2012 EC941: Game Theory Prof. Francesco Squintani Final Exam Answer TWO questions. All questions carry equal weight. Time allowed 2 hours. 1. Consider

More information

15-451/651: Design & Analysis of Algorithms October 23, 2018 Lecture #17: Prediction from Expert Advice last changed: October 25, 2018

15-451/651: Design & Analysis of Algorithms October 23, 2018 Lecture #17: Prediction from Expert Advice last changed: October 25, 2018 5-45/65: Design & Analysis of Algorithms October 23, 208 Lecture #7: Prediction from Exert Advice last changed: October 25, 208 Prediction with Exert Advice Today we ll study the roblem of making redictions

More information

Combining Logistic Regression with Kriging for Mapping the Risk of Occurrence of Unexploded Ordnance (UXO)

Combining Logistic Regression with Kriging for Mapping the Risk of Occurrence of Unexploded Ordnance (UXO) Combining Logistic Regression with Kriging for Maing the Risk of Occurrence of Unexloded Ordnance (UXO) H. Saito (), P. Goovaerts (), S. A. McKenna (2) Environmental and Water Resources Engineering, Deartment

More information

Hotelling s Two- Sample T 2

Hotelling s Two- Sample T 2 Chater 600 Hotelling s Two- Samle T Introduction This module calculates ower for the Hotelling s two-grou, T-squared (T) test statistic. Hotelling s T is an extension of the univariate two-samle t-test

More information

Information Acquisition in Interdependent Value Auctions

Information Acquisition in Interdependent Value Auctions Information Acquisition in Interdependent Value Auctions Dirk Bergemann Xianwen Shi Juuso Välimäki July 16, 2008 Abstract We consider an auction environment with interdependent values. Each bidder can

More information

Analysis of some entrance probabilities for killed birth-death processes

Analysis of some entrance probabilities for killed birth-death processes Analysis of some entrance robabilities for killed birth-death rocesses Master s Thesis O.J.G. van der Velde Suervisor: Dr. F.M. Sieksma July 5, 207 Mathematical Institute, Leiden University Contents Introduction

More information

Estimation of the large covariance matrix with two-step monotone missing data

Estimation of the large covariance matrix with two-step monotone missing data Estimation of the large covariance matrix with two-ste monotone missing data Masashi Hyodo, Nobumichi Shutoh 2, Takashi Seo, and Tatjana Pavlenko 3 Deartment of Mathematical Information Science, Tokyo

More information

A continuous review inventory model with the controllable production rate of the manufacturer

A continuous review inventory model with the controllable production rate of the manufacturer Intl. Trans. in O. Res. 12 (2005) 247 258 INTERNATIONAL TRANSACTIONS IN OERATIONAL RESEARCH A continuous review inventory model with the controllable roduction rate of the manufacturer I. K. Moon and B.

More information

Dynamic costs and moral hazard: A duality-based approach

Dynamic costs and moral hazard: A duality-based approach Available online at www.sciencedirect.com ScienceDirect Journal of Economic Theory 166 (2016) 1 50 www.elsevier.com/locate/jet Dynamic costs and moral hazard: A duality-based aroach Guy Arie Simon Business

More information

Microeconomics II Lecture 4: Incomplete Information Karl Wärneryd Stockholm School of Economics November 2016

Microeconomics II Lecture 4: Incomplete Information Karl Wärneryd Stockholm School of Economics November 2016 Microeconomics II Lecture 4: Incomplete Information Karl Wärneryd Stockholm School of Economics November 2016 1 Modelling incomplete information So far, we have studied games in which information was complete,

More information

Estimating the Degree of Expert s Agency Problem: The Case of Medical Malpractice Lawyers

Estimating the Degree of Expert s Agency Problem: The Case of Medical Malpractice Lawyers Estimating the Degree of Exert s Agency Problem: The Case of Medical Malractice Lawyers Yasutora Watanabe Northwestern University March 2007 Very Preliminary and Incomlete - Comments Welcome! Abstract

More information

An Analysis of Reliable Classifiers through ROC Isometrics

An Analysis of Reliable Classifiers through ROC Isometrics An Analysis of Reliable Classifiers through ROC Isometrics Stijn Vanderlooy s.vanderlooy@cs.unimaas.nl Ida G. Srinkhuizen-Kuyer kuyer@cs.unimaas.nl Evgueni N. Smirnov smirnov@cs.unimaas.nl MICC-IKAT, Universiteit

More information

STA 250: Statistics. Notes 7. Bayesian Approach to Statistics. Book chapters: 7.2

STA 250: Statistics. Notes 7. Bayesian Approach to Statistics. Book chapters: 7.2 STA 25: Statistics Notes 7. Bayesian Aroach to Statistics Book chaters: 7.2 1 From calibrating a rocedure to quantifying uncertainty We saw that the central idea of classical testing is to rovide a rigorous

More information

Sets of Real Numbers

Sets of Real Numbers Chater 4 Sets of Real Numbers 4. The Integers Z and their Proerties In our revious discussions about sets and functions the set of integers Z served as a key examle. Its ubiquitousness comes from the fact

More information

Elementary Analysis in Q p

Elementary Analysis in Q p Elementary Analysis in Q Hannah Hutter, May Szedlák, Phili Wirth November 17, 2011 This reort follows very closely the book of Svetlana Katok 1. 1 Sequences and Series In this section we will see some

More information

Lecture 14: Introduction to Decision Making

Lecture 14: Introduction to Decision Making Lecture 14: Introduction to Decision Making Preferences Utility functions Maximizing exected utility Value of information Actions and consequences So far, we have focused on ways of modeling a stochastic,

More information

Deceptive Advertising with Rational Buyers

Deceptive Advertising with Rational Buyers Deceptive Advertising with Rational Buyers September 6, 016 ONLINE APPENDIX In this Appendix we present in full additional results and extensions which are only mentioned in the paper. In the exposition

More information

Approximate Market Equilibrium for Near Gross Substitutes

Approximate Market Equilibrium for Near Gross Substitutes Aroximate Market Equilibrium for Near Gross Substitutes Chinmay Karande College of Comuting, Georgia Tech ckarande@cc.gatech.edu Nikhil Devanur College of Comuting, Georgia Tech nikhil@cc.gatech.edu Abstract

More information

Specialization, Information Production and Venture Capital Staged Investment. Jerry Cao Choong Tze Chua a Winston T.H. Koh b Xiaoming Wang c

Specialization, Information Production and Venture Capital Staged Investment. Jerry Cao Choong Tze Chua a Winston T.H. Koh b Xiaoming Wang c ecialization, Information Production and Venture Caital taged Investment Jerry Cao Choong Tze Chua a Winston T.H. Koh b Xiaoming Wang c This version: 8 November 009 * Assistant rofessor of Finance, chool

More information

Partnership Dissolution and the Willingness-to-Pay - Willingness-to-Accept Disparity

Partnership Dissolution and the Willingness-to-Pay - Willingness-to-Accept Disparity Partnershi Dissolution and the Willingness-to-Pay - Willingness-to-Accet Disarity Alexander Heczko RWTH Aachen University This Version: June, 218 Working Paer Abstract A willingness-to-ay WTP) willingness-to-accet

More information

1 C 6, 3 4, 4. Player S 5, 2 3, 1

1 C 6, 3 4, 4. Player S 5, 2 3, 1 University of alifornia, Davis - Deartment of Economics PRING EN / ARE : MIROEONOMI TEORY Professor Giacomo Bonanno ====================================================================== MIDTERM EXAM ANWER

More information

School of Economic Sciences

School of Economic Sciences School of Economic Sciences Working Paer Series WP 2017-1 Information Transmission during the Trial: The ole of Punitive Damages and egal osts Ana Esinola-Arredondo Felix Munoz-Garcia January, 2017 Information

More information

Symmetric and Asymmetric Equilibria in a Spatial Duopoly

Symmetric and Asymmetric Equilibria in a Spatial Duopoly This version: February 003 Symmetric and Asymmetric Equilibria in a Satial Duooly Marcella Scrimitore Deartment of Economics, University of Lecce, Italy Jel Classification: L3, R39 Abstract We develo a

More information

The one-sample t test for a population mean

The one-sample t test for a population mean Objectives Constructing and assessing hyotheses The t-statistic and the P-value Statistical significance The one-samle t test for a oulation mean One-sided versus two-sided tests Further reading: OS3,

More information

The Impact of Demand Uncertainty on Consumer Subsidies for Green Technology Adoption

The Impact of Demand Uncertainty on Consumer Subsidies for Green Technology Adoption "The Imact of Consumer Subsidies for Green Technology Adotion." Cohen, Maxine C., Ruben Lobel and Georgia Perakis. Management Science Vol. 62, No. 5 (2016: 1235-1258. htt://dx.doi.org/10.1287/mnsc.2015.2173

More information

Periodic scheduling 05/06/

Periodic scheduling 05/06/ Periodic scheduling T T or eriodic scheduling, the best that we can do is to design an algorithm which will always find a schedule if one exists. A scheduler is defined to be otimal iff it will find a

More information

Research on Evaluation Method of Organization s Performance Based on Comparative Advantage Characteristics

Research on Evaluation Method of Organization s Performance Based on Comparative Advantage Characteristics Vol.1, No.10, Ar 01,.67-7 Research on Evaluation Method of Organization s Performance Based on Comarative Advantage Characteristics WEN Xin 1, JIA Jianfeng and ZHAO Xi nan 3 Abstract It as under the guidance

More information

Measuring center and spread for density curves. Calculating probabilities using the standard Normal Table (CIS Chapter 8, p 105 mainly p114)

Measuring center and spread for density curves. Calculating probabilities using the standard Normal Table (CIS Chapter 8, p 105 mainly p114) Objectives Density curves Measuring center and sread for density curves Normal distributions The 68-95-99.7 (Emirical) rule Standardizing observations Calculating robabilities using the standard Normal

More information

Morten Frydenberg Section for Biostatistics Version :Friday, 05 September 2014

Morten Frydenberg Section for Biostatistics Version :Friday, 05 September 2014 Morten Frydenberg Section for Biostatistics Version :Friday, 05 Setember 204 All models are aroximations! The best model does not exist! Comlicated models needs a lot of data. lower your ambitions or get

More information

Game Theory. Monika Köppl-Turyna. Winter 2017/2018. Institute for Analytical Economics Vienna University of Economics and Business

Game Theory. Monika Köppl-Turyna. Winter 2017/2018. Institute for Analytical Economics Vienna University of Economics and Business Monika Köppl-Turyna Institute for Analytical Economics Vienna University of Economics and Business Winter 2017/2018 Static Games of Incomplete Information Introduction So far we assumed that payoff functions

More information

Information collection on a graph

Information collection on a graph Information collection on a grah Ilya O. Ryzhov Warren Powell February 10, 2010 Abstract We derive a knowledge gradient olicy for an otimal learning roblem on a grah, in which we use sequential measurements

More information

CERIAS Tech Report The period of the Bell numbers modulo a prime by Peter Montgomery, Sangil Nahm, Samuel Wagstaff Jr Center for Education

CERIAS Tech Report The period of the Bell numbers modulo a prime by Peter Montgomery, Sangil Nahm, Samuel Wagstaff Jr Center for Education CERIAS Tech Reort 2010-01 The eriod of the Bell numbers modulo a rime by Peter Montgomery, Sangil Nahm, Samuel Wagstaff Jr Center for Education and Research Information Assurance and Security Purdue University,

More information

Theory of Auctions. Carlos Hurtado. Jun 23th, Department of Economics University of Illinois at Urbana-Champaign

Theory of Auctions. Carlos Hurtado. Jun 23th, Department of Economics University of Illinois at Urbana-Champaign Theory of Auctions Carlos Hurtado Department of Economics University of Illinois at Urbana-Champaign hrtdmrt2@illinois.edu Jun 23th, 2015 C. Hurtado (UIUC - Economics) Game Theory On the Agenda 1 Formalizing

More information

Cowles Foundation for Research in Economics at Yale University

Cowles Foundation for Research in Economics at Yale University Cowles Foundation for Research in Economics at Yale University Cowles Foundation Discussion Paer No. 1743RR SELLING INFORMATION Johannes Hörner and Andrzej Skrzyacz December 2009 Revised November 2012

More information

Distributed Rule-Based Inference in the Presence of Redundant Information

Distributed Rule-Based Inference in the Presence of Redundant Information istribution Statement : roved for ublic release; distribution is unlimited. istributed Rule-ased Inference in the Presence of Redundant Information June 8, 004 William J. Farrell III Lockheed Martin dvanced

More information

Statics and dynamics: some elementary concepts

Statics and dynamics: some elementary concepts 1 Statics and dynamics: some elementary concets Dynamics is the study of the movement through time of variables such as heartbeat, temerature, secies oulation, voltage, roduction, emloyment, rices and

More information

Pro-Consumer Price Ceilings under Uncertainty

Pro-Consumer Price Ceilings under Uncertainty Pro-Consumer Price Ceilings under Uncertainty John Bennett y Ioana Chioveanu z March 11, 2015 Abstract We examine ro-consumer rice ceilings under regulatory uncertainty about demand and suly. In a erfectly

More information

Selling Information. September 5, Abstract

Selling Information. September 5, Abstract Selling Information Johannes Hörner and Andrzej Skrzyacz Setember 5, 2014 Abstract A Firm considers hiring an Agent who may be cometent for a otential roject or not. The Agent can rove her cometence, but

More information

Flirting with the Enemy: Online Competitor Referral and Entry-Deterrence

Flirting with the Enemy: Online Competitor Referral and Entry-Deterrence Flirting with the Enemy: Online Cometitor Referral and Entry-Deterrence January 11, 2016 Abstract Internet retailers often comete fiercely for consumers through exensive efforts like search engine advertising,

More information

arxiv: v1 [physics.data-an] 26 Oct 2012

arxiv: v1 [physics.data-an] 26 Oct 2012 Constraints on Yield Parameters in Extended Maximum Likelihood Fits Till Moritz Karbach a, Maximilian Schlu b a TU Dortmund, Germany, moritz.karbach@cern.ch b TU Dortmund, Germany, maximilian.schlu@cern.ch

More information

Paper C Exact Volume Balance Versus Exact Mass Balance in Compositional Reservoir Simulation

Paper C Exact Volume Balance Versus Exact Mass Balance in Compositional Reservoir Simulation Paer C Exact Volume Balance Versus Exact Mass Balance in Comositional Reservoir Simulation Submitted to Comutational Geosciences, December 2005. Exact Volume Balance Versus Exact Mass Balance in Comositional

More information

GSOE9210 Engineering Decisions

GSOE9210 Engineering Decisions GSOE9 Engineering Decisions Problem Set 5. Consider the river roblem described in lectures: f f V B A B + (a) For =, what is the sloe of the Bayes indifference line through A? (b) Draw the Bayes indifference

More information

CHAPTER-II Control Charts for Fraction Nonconforming using m-of-m Runs Rules

CHAPTER-II Control Charts for Fraction Nonconforming using m-of-m Runs Rules CHAPTER-II Control Charts for Fraction Nonconforming using m-of-m Runs Rules. Introduction: The is widely used in industry to monitor the number of fraction nonconforming units. A nonconforming unit is

More information

Measuring center and spread for density curves. Calculating probabilities using the standard Normal Table (CIS Chapter 8, p 105 mainly p114)

Measuring center and spread for density curves. Calculating probabilities using the standard Normal Table (CIS Chapter 8, p 105 mainly p114) Objectives 1.3 Density curves and Normal distributions Density curves Measuring center and sread for density curves Normal distributions The 68-95-99.7 (Emirical) rule Standardizing observations Calculating

More information

Second Price Auctions with Differentiated Participation Costs

Second Price Auctions with Differentiated Participation Costs Second Price Auctions with Differentiated Participation Costs Xiaoyong Cao Department of Economics Texas A&M University College Station, TX 77843 Guoqiang Tian Department of Economics Texas A&M University

More information

AM 221: Advanced Optimization Spring Prof. Yaron Singer Lecture 6 February 12th, 2014

AM 221: Advanced Optimization Spring Prof. Yaron Singer Lecture 6 February 12th, 2014 AM 221: Advanced Otimization Sring 2014 Prof. Yaron Singer Lecture 6 February 12th, 2014 1 Overview In our revious lecture we exlored the concet of duality which is the cornerstone of Otimization Theory.

More information

Ensemble Forecasting the Number of New Car Registrations

Ensemble Forecasting the Number of New Car Registrations Ensemble Forecasting the Number of New Car Registrations SJOERT FLEURKE Radiocommunications Agency Netherlands Emmasingel 1, 9700 AL, Groningen THE NETHERLANDS sjoert.fleurke@agentschatelecom.nl htt://www.agentschatelecom.nl

More information

Information collection on a graph

Information collection on a graph Information collection on a grah Ilya O. Ryzhov Warren Powell October 25, 2009 Abstract We derive a knowledge gradient olicy for an otimal learning roblem on a grah, in which we use sequential measurements

More information

Tax Evasion, Social Customs and Optimal Auditing

Tax Evasion, Social Customs and Optimal Auditing 1 Tax Evasion, Social Customs and Otimal Auditing Gareth D. Myles and Robin A. Naylor University of Exeter University of Warwick May 1995 Abstract: The otimal audit olicy is analysed for an indeendent

More information

Vickrey-Clarke-Groves Mechanisms

Vickrey-Clarke-Groves Mechanisms Vickrey-Clarke-Groves Mechanisms Jonathan Levin 1 Economics 285 Market Design Winter 2009 1 These slides are based on Paul Milgrom s. onathan Levin VCG Mechanisms Winter 2009 1 / 23 Motivation We consider

More information

Participation Factors. However, it does not give the influence of each state on the mode.

Participation Factors. However, it does not give the influence of each state on the mode. Particiation Factors he mode shae, as indicated by the right eigenvector, gives the relative hase of each state in a articular mode. However, it does not give the influence of each state on the mode. We

More information

Competitive Pressure in a Fixed Price Market for Credence Goods

Competitive Pressure in a Fixed Price Market for Credence Goods Cometitive Pressure in a Fixed Price Market for Credence Goods Fridolin E. Marty University of Berne August 1999 Abstract We consider a market for credence goods. There are two tyes of exerts: ersons who

More information

School of Economics and Management

School of Economics and Management School of Economics and Management TECHNICAL UNIVERSITY OF LISBON Deartment of Economics Carlos Pestana Barros & Nicolas Peyoch José Pedro Pontes A Comarative Analysis of Productivity Change in Italian

More information

Oligopolistic Pricing with Online Search

Oligopolistic Pricing with Online Search Oligoolistic Pricing with Online Search Lizhen Xu, Jianqing Chen, and Andrew Whinston Lizhen Xu is a Ph.D. candidate in the Deartment of Information, Risk, and Oerations Management, Red McCombs School

More information