Contract Length: Negotiation Costs, Specific Investments, and Uncertainty∗ Meng-Chi Tang National Chung Cheng University October 2009

Abstract: This paper empirically tests how contract length is affected by negotiation costs, specific investments, and uncertainty. Using contract information from the National Football League and the franchising industry, I find that contract length increases with negotiation costs and specific investments. In addition, contract length increases with uncertainty when the seller (player) is more risk-averse than the buyer (team), and decreases with uncertainty when the seller (franchisor) is less risk-averse than the buyer (franchisee).

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This is the first chapter of my dissertation. I am grateful to my advisor, Mike Conlin, for his continuous guidance and support to this project. I also thank Thomas Jeitschko, Jay Wilson, Kent Miller, Jeff Wooldridge, and Jay Pil Choi for their comments and suggestions, as well as Rob Bond and Richard Duell for their expertise on the franchising industry. The author is benefited from the presentation in the 19th Annual Meeting of the American Law and Economics Association, as well as the seminars in Academia Sinica, National Tsing Hua Univesity, National Chung Cheng University, Fudan University, Shanghai University of Finance and Economics, Shanghai Jiao Tung University, National Chengchi University, and National Chi Nan University. Financial support from the Department of Economics at Michigan State University is greatly appreciated.

1. Introduction Why do some contracts have longer duration than other contracts? For example, in the National Football League (NFL), some players signed contracts with longer duration than the other players. Some franchisors in the franchising industry, on the other hand, also provide significantly longer contracts than the other franchisors’. In a world with unforeseeable contingencies, writing a complete contract is virtually impossible. Every contract negotiation when deciding on the duration of the relationship must consider the tradeoffs associated with contract length such as negotiation costs and the cost of being bounded in the future. However, the empirical literature testing contract theory provides thin evidence on the determinants of contract length due to the focus on incentive contracts and firm boundaries. 1 Since contract length is one of the most important parameters of nearly every contract, this paper provides evidence on how negotiation costs, specific investments and uncertainty affect the length of commercial and individual labor contracts. Most of the research on contract length falls into the literature of transaction cost theory, or incomplete contract theory. 2 The central issue is how specific investments relate to contract length. In particular, Klein, Crawford, and Alchian (1978, hereafter KCA) argued that if a long-term contract specifying the terms of future transactions can be provided ex ante, the level of opportunistic behavior can be mitigated ex post and thus the specific investment can be made more efficient (i.e, the hold-up problem). This 1

See Chiappori and Salanié (2003) for a survey on the empirical research related to contract theory, and Lafontaine and Slade (2007) for a survey on the empirical literature of vertical integration. While the career concerns literature also addresses the problem by relating long-term contracts with the moral hazard problem, it falls into the literature of incentive contract. For example, see the textbook treatment by Bolton and Dewatripont (2005, p. 470). 2 See Guriev and Kvasov (2005) for a summary of the theoretical literature on contract length and specific investments, and Shelanski and Klein (1995) for a survey on the empirical literature.

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prediction has been tested in primarily commercial contracts. For example, Joskow (1987) tested the prediction using the contracts between coal suppliers and electric utilities. He found that the more important are specific investments, the longer the contract. Similar evidence is also found in natural gas contracts (Crocker and Masten, 1988), franchise contracts (Brickley, Misra, and Van Horn, 2006, hereafter BMV) and tenancy agreements (Bandiera, 2007).3 The research relating contract length to uncertainty consists of labor and macroeconomics literature that focuses on how longer contracts trade off the cost of being bounded against the cost of renegotiation. Theoretically, the relationship between contract length and uncertainty is ambiguous. While Gray (1978) and Dye (1985) suggest that contract length is negatively related to uncertainty, Harris and Holmstrom (1987) and Danziger (1988) find that contract length is positively related to uncertainty. On the one hand, the negative relationship argument is supported by the efficient production hypothesis (Gray, 1978), which indicates contract wage will be deviated away from the efficient wage when there is more uncertainty. To maintain the production efficiency, contract length should be reduced to allow more renegotiations when there is more uncertainty. On the other hand, the positive relationship argument is supported by the efficient risk-sharing hypothesis (Danziger, 1988), which suggests a longer contract provides insurance against more aggregate real uncertainty when one of the contracting parties is more risk-averse than the other. 4

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Cheung (1969) first proposed the idea that the tenancy lease duration is chosen to minimize transaction costs, which is defined as the cost to secure and transfer the right to the income generated by private investment, as well as the renegotiation cost. 4 Harris and Holmstrom (1987), on the other hand, emphasize the relationship between information discovery process and contract duration.

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Much of the empirical research uses union-firm contracts data to test the competing hypotheses. While Rich and Tracy (1999) find their data supports the efficient production hypothesis, mixed evidence has also been found in Wallace and Blanco (1991) and Wallace (2001). Instead of using the union-firm contracts, this paper attempts to examine the two hypotheses on the individual contract data with different risk attitudes between the buyer and seller. If the efficient risk-sharing concern is paramount, contract length should increase with uncertainty when the buyer is less risk-averse than the seller, but not the other way around. The efficient production hypothesis, on the other hand, implies the correlation between contract length and uncertainty will not be affected by the different relative risk attitudes between the buyer and seller. While the literature emphasis the tradeoff between flexibility and negotiation costs to use a long-term contract, most of the empirical works focus on the measurement issue on the future uncertainty while negotiation costs is given exogenously. 5 In this paper, I use different proxies as measures of negotiation costs for individual contracts in the NFL and the franchising industry, examine whether the level of negotiation costs is positively related to contract length as argued in Gray (1978) and Murphy (1992).6 This paper empirically tests the effects of negotiation costs, specific investments and uncertainty on contract length, using contract information from the NFL and the franchising industry. The benefits of using both types of contracts are threefold. First, this allows us to examine whether the determinants of contract length vary across labor and

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For example, see Murphy (1992) and Wallace (2001). Rich and Tracy (1999, pp. 281) mentioned that “…no direct measures of negotiation costs are available.” 6 Since negotiation costs increase with the quasi rents generated from the contracting relationship, proxies measuring negotiation costs also provide the indirect measures for quasi rents. KCA mentioned the positive relationship between quasi rents and contract length, and Crocker and Masten (1988) empirically tested the relationship using natural gas contracts.

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commercial contracts. Second, while the seller (player) is more risk-averse than the buyer (team) in the NFL, the seller (franchisor) is less risk-averse than the buyer (franchisee) in the franchising industry. Analyzing both contract environments enables the comparison between two contracting environments with different relative risk attitudes of the buyer and seller. Third, using both types of contracts enables multiple proxies of negotiation costs, specific investments and uncertainty to be applied in the empirical test. The paper proceeds as follows. The next section describes the contract information and institutional details of the NFL and the franchising industry. Section 3 proceeds to argue why contract length is related to negotiation costs, specific investments, and uncertainty. Section 4 discusses the empirical strategy, while Section 5 presents the evidence that contract length increases with negotiation costs and specific investments. In addition, contract length increases with uncertainty when the seller is more risk-averse than the buyer in the NFL, and decreases as the seller is less risk-averse than the buyer in the franchising industry. Section 6 concludes.

2. Data and Institutional Details I use both labor contracts from the NFL and commercial contracts from the franchising industry to test the determinants of contract length. In this section, the data and institutional details are discussed for both industries.

2.1 National Football League Contracts The NFL conducts their annual draft in late April. There are multiple rounds in a draft, and in each round each team owns one pick to select a player. The order of picks is

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based on the prior year's performance, with the first pick going to the worst performing team. A team may trade its pick to another team for specific players and/or picks. After being drafted, the draftee and his agent negotiate a contract with the team. The team has exclusive rights on the draftee which prohibits other NFL teams from signing the player. Almost all draftees agree to contractual terms with the NFL team holding their rights. If a draftee is unable to reach a contractual agreement, he can either sit out a year and reenter the subsequent year's draft or play for another professional football league (such as Canadian Football League). The contract information of those players drafted comes from two time periods, 1986-1991 (hereafter 86-91) and 2001-2007 (hereafter 01-07). Every contract specifies the duration of the contract and monetary payments, which includes signing bonus and base salary. Besides early round draft choices in the 01-07 drafts, almost all the contracts are not guaranteed in the sense that the team has the right to cut a player and not pay his base salary. Signing bonus, on the other hand, is guaranteed money and paid upfront. Some contracts also include incentive clauses. Teams spend more resources on negotiating the contracts with more signing bonus and incentive clauses, mostly with the early draftees. After the NFL and the NFL Player's Association (NFLPA) entered into a new collective bargaining agreement (CBA) in 1993, the general structure of the contract has become more varied because of the introduction of salary cap. The salary cap limits team's spending on player salaries with signing bonus prorated evenly over the duration of the contract. The NFLPA provided the contract data, along with players' position, college, selection number in draft, and drafting team. The data include 1,872 contracts from 86-91

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and 1,782 contracts from 01-07. There were 28 teams having a single pick in each of the 12 rounds from 86-91, and 32 teams having a single pick in each of the 7 rounds from 0107. 7 Team information is obtained from the NFL Record and Fact Book (1986-1991, 2000-2007), including team's paid attendance, stadium capacity, win-loss record, and head coach tenure. College teams’ divisions were obtained from the 1995 Official National Collegiate Athletic Association College Football Records Book, where the Division IA schools are the schools with larger budgets for athletic programs than the other schools. At last, the population in the metropolitan statistical areas (MSA) is interpolated/extrapolated from the 1990 and 2000 U.S. census. Table 1 presents the summary statistics for each time period. As the table indicates, the average length of the contracts in the 01-07 dataset is about one year longer than in 86-91. Contract length ranges between one and six years in the 86-91 dataset, and one and seven years in the 01-07 dataset.8 Figure 1 presents the distribution of contract length for both time periods. Figure 2 presents the average contract length by round, as well as the proportion of non-Division IA school draftees by round. Average contract length decreases across rounds and the rate of the decrease is similar across time periods. The fact that signing bonus is allowed to be prorated evenly over the duration of the contract after imposition of the salary cap is one explanation as to why the average contract length in every round is longer for the 01-07 data. Since teams pay more signing

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There were only 31 teams in 2001 because the Houston Texans joined the NFL in 2002. The Texan's 12 contracts in 2002 are dropped in the regression analysis since there are no observations for the variables related to the prior year. 8 Section 5 of Article XVII of the 2006 CBA states: “The initial Players Contract of a Rookie, including any Club option, may not exceed four years in length, except that the initial Player Contract of a Rookie drafted with a selection in the first half of the first round (e.g., the first sixteen of thirty-two selections in the 2006 Draft), including any Club option, may not exceed six years in length, and the initial Player Contract of a Rookie drafted with a selection in the second half of the first round, including any Club option, may not exceed five years in length.”

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bonus instead of salary to the player to save more spending space, they ask for the longer contract with player because the signing bonus is paid upfront.9 In addition, the number of non-Division IA school draftees increases across rounds for both time periods, while there were more non-Division IA school players drafted in the 86-91 drafts. Summary statistics of the other variables are similar for both time periods, except for the empty seat percentage. The empty seat percentage is much smaller during 01-07 because attendance has increased approximately 24 percent while there was only a three percent increase in the average stadium capacity.

2.2 Franchise Contracts A franchise contract specifies the agreement on the franchisee's right to use the franchisor's trademark or the right to sell his product in a given place for a specific duration (Lafontaine, 1992). To test the effect of negotiation costs, specific investments, and uncertainty on franchise contract duration, I obtained information from the Bond's Franchise Guide (Bond, 2007), which includes detailed survey responses from 1,005 franchisors. Table 2 presents the summary statistics.10 The mean duration of the initial contracts is slightly more than eleven years; with 51 percent having ten year durations; 19 percent having five year durations; and 12 percent having 20 year durations. Table 2 also indicates that ten percent of the franchisors

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The tradeoff between contract length and signing bonus is discussed in Duberstein (1991). In the survey, a franchisor was asked contact information, background details, required financial and contract terms of his franchisee, specific expansion plans in the near future, as well as the support and training provided for his franchisee. Moreover, instead of a single value response, some franchisors provided a range of values for some financial and contractual variables. In such case the average of the lowest and the highest values are used as their responses. For estimation purpose, the averages of contract duration that are not integer have been rounded up. Finally, replies that are ambiguous or a non-response are treated as missing.

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were listed in Bond's Top 100 franchisors (Bond, 2006).11 About half of the franchisors offer area development agreement, which allows the franchisee to develop a large geographical area. In addition, the survey asked each franchisor what building type was allowed for a franchise outlet. Most of the franchisors provided several choices for prospective franchisee, with 19 percent allowing a home-based unit or a kiosk. Table 3 shows the proportion of franchisors who allow each building type. Moreover, Table 2 reveals that the franchisors having average 20 years of franchising experience and providing their franchisees an average of 23 days of on- and off-site training. 12 The franchisors have on average 492 units in a chain, where 88 percent of the franchisors' units are franchised. About 12 percent of the franchisors were in equipment rental services, business aids and services, or educational products and services sectors, and Table 4 presents the distribution of franchisors by business sector.13 Finally, many states in the U.S. have statues that regulate the franchising industry. Most of these states require good cause for termination and non-renewal of the existing franchising relationship.14 Table 2 indicates that 31 percent of the franchisors are headquartered in the states restricting termination of a franchise contract.

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Bond's Top 100 franchisors broke the franchising industry into food-services, retail, and service-based franchises, evaluated companies on the basis of historical performance, brand identification, market dynamics, franchisee satisfaction, the level of initial training and on-going support, litigation record, and financial stability, etc (Bond 2006). 12 Franchisors responded to this question using different measures, including hours, days, and weeks. All responses are converted into days, where a training day is defined as a business day (8 hours a day, 5 days a week). Moreover, the off-site training includes training at headquarter, training center, classroom, and current operating unit, while the on-site training indicates training at franchisee's own site. 13 Business sectors are categorized as Blair and Lafontaine (2005, Table 1-1). 14 A good cause for termination is the franchisee's failure to comply with the material terms of the franchise contract (Blair and Lafontaine, 2005). The sixteen states which limit termination for good cause are Arkansas, California, Connecticut, D.C., Delaware, Illinois, Indiana, Iowa, Michigan, Minnesota, Nebraska, New Jersey, Tennessee, Virginia, Washington, and Wisconsin (Klick, Kobayashi, and Ribstein, 2006, Table 4). See also the discussion about contract duration and the termination laws in BMV, footnote 21, and Blair and Lafontaine (2005, p. 279).

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3. Hypotheses

In this section, I discuss why contract length is related to negotiation costs, specific investments and uncertainty, using the NFL and franchising contracts as examples. Negotiation Costs. A long-term contract saves the times of negotiation and thus the negotiation costs. For example, the NFL teams often spend more resources in negotiating with early draftees while contacting the later ones using phone calls. The early draftees, on the other hand, also hire multiple agents to negotiate with the draft team while the later draftees often use a friend or family member as his representative. Consequently, the early draftees and the draft team have more incentives to sign a longterm contract with fewer negotiations in the future, compared to the contracts signed between the later draftees and the draft team. In the franchising industry, the good franchisors are often less willing to negotiate outside the standard franchise agreement which is a part of their Franchise Disclosure Document, because negotiation as a course of business would require modifications to the Federal Disclosure Document and perhaps system changes. In addition, to negotiate with good franchisors, potential franchisee needs experienced franchise attorneys who know the areas that the good franchisor is willing to negotiate but are also more expensive.15 Consequently, more costs are required for the contract negotiations between the good franchisors and potential franchisees. Longer contracts, therefore, are offered more often from the good franchisors than the other franchisors.

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I am grateful to Mr. Richard Duell for providing his experience in the franchise negotiation.

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Specific Investments. One of the main focus of the transaction cost theory is a long-term contract provides a solution to the holdup problem as mentioned in KCA. The hypothesis is confirmed empirically using evidence mainly from the commercial contract as previously discussed. Since the specific investments are also important to the labor contract, such as the human asset specificity argued by Willamson (1983), contract length is expected to increase with specific investments in the labor contract as well as in the commercial contract. Uncertainty. While the efficient risk-sharing hypothesis predicts that contract length increases with uncertainty when the buyer is less risk-averse than the seller, the efficient production hypothesis indicates contract length is always negatively related to uncertainty. Therefore, whether the effect of uncertainty on contract length varies depending on the relative risk attitudes between the buyer and seller is a key difference between the two competing hypotheses. For example, in the NFL contract negotiations, teams are less risk-averse than players because teams are more financially sufficient and diversified. Teams are thus able to sign longer contracts with players when there is more uncertainty in the player’s future contribution. Players, on the other hand, will accept the contract to reduce the impact of uncertainty.16 In the franchising industry, franchisees are more risk-averse than franchisors because franchisees are often less financially sufficient and diversified relative to franchisors. If the future development of the business is uncertain to the franchisee, a long-term contract increases his risk to be locked-up in an unprofitable relationship. Since there is greater possibility that the investment will be less

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The fact that the NFL contracts are not guaranteed does not affect the argument because of the positive relationship between long-term contract and signing bonus (Duberstein, 1992). While contract duration may not provide the actual insurance for player, the more signing bonus associated with the longer contract, which is paid upfront, suggested that the insurance for player is at least partially provided.

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efficient with more uncertainty, while it is also costly for franchisees to breach the contract, franchisees will not prefer a longer contract when the business is more risky. Consequently, comparing to the efficient production consideration, the concern of efficient risk-sharing is more important to the NFL contract negotiations but less important to the franchising contract negotiations.

4. Empirical Strategy In this section, I discuss the proxies for negotiation costs, specific investments and uncertainty from the NFL and franchising datasets. Table 5 compares these proxies for the two types of contracts.

4.1 National Football League Contracts Negotiation Costs. Player's selection number is a proxy for negotiation costs. As mentioned above, teams spend more resources in negotiating with the early draftees, whose contracts often include more lucrative monetary payments and incentive clauses. Those early draftees also hire multiple agents as their representatives to negotiate with the draft team. Therefore, more resources are spent in the negotiations between the draft team and the early draftees comparing to the ones between the later draftees and the draft team. In addition, more resources will also be spent when there is more expected surplus to be split from the contracting relationship. Team's number of empty seats and wins last year are proxies of expected surplus. A team with more empty seats and/or fewer wins is willing to pay more for an early draftee to make immediate contribution, compare to a team with fewer empty seats and/or more wins last year. Contracts between the former

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team and the early draftees will therefore generates more surplus to be split and provides incentives for the contracting parties to spend more resources in the negotiations. An early draftee of a team with more empty seats and/or fewer wins last year should thus negotiate a longer contract. Specific Investments. We use whether a player’s position is quarterback as a proxy for specific investments. Compared to other positions, a quarterback requires more team-specific training because he must learn the team's offensive system and play calling. More team resources are thus invested in the quarterback than the other positions. Since contract length is expected to increase with firm-specific investment, a quarterback's contract should be longer than the contract for other positions. Uncertainty. Whether a player attended a Division IA school is a proxy for uncertainty, because the NFL performance of non-Division IA draftee is more uncertain. Players from those small programs went through less intensive games with fewer resources for training, compare to their bigger school counterparts.17 Because the team is less risk averse than the player, contract duration should be greater for draftees that attended non-Division IA school.

4.2 Franchise Contracts Negotiation Costs. Whether a franchisor is selected in the Bond's Top 100 franchisors is a proxy for negotiation costs. As mentioned previously, the top 100 franchisors and their potential franchisees spend more on the contract negotiations than the other franchisors and their potential franchisees. Moreover, whether the franchisor

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The same uncertainty measure has been used by Hendricks, DeBrock, and Koenker (2003). See footnote seven in their paper for more discussion on the uncertainty proxy.

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offers area development agreement for potential franchisees also suggests the level of negotiation involved, because there is much more negotiation required for a multi-unit deal than a single-unit purchase.18 Specific Investments. Whether a franchisor allows a home-based unit or a kiosk for outlet is a proxy for specific investments, because the sunk cost of a home-based unit or a kiosk is likely less than for other building types. In addition, since much of the training is firm-specific, the number of required training days is another proxy for specific investments.19 Uncertainty. Since a franchisee is likely more risk averse than the franchisor, contract length is expected to decrease with uncertainty. To measure the risk incurred by a franchisee, Lafontaine and Bhattacharyya (1995) used the yearly average proportion of discontinued outlets between 1982 and 1986 in each sector as a measure of risk faced by a prospective franchisee.20 They found the top three sectors with the highest discontinued outlets during 1982 to 1986 were equipment rental services, business aids and services, or educational products and services sectors.21 Accordingly, whether franchisor is in those three business sectors is applied as a proxy for uncertainty.

5. Empirical Results

5.1 National Football League Contracts 18

I thank Richard Duell for providing the above insights. BMV used the amount of off-site training as a proxy for human capital investment. Other than the firmspecific training, they also emphasized the amount of travel and opportunity cost the franchisee incurs. Since the focus of this paper is investment specificity, the required total training better serves the purpose. Similar empirical results can be obtained if the off-site training is used as the proxy for uncertainty. 20 See Lafontaine and Bhattacharyya (1995) for other risk measures used in the literature. 21 Lafontaine and Bhattacharyya (1995) obtained the data from Franchising in the Economy, published by U.S. Department of Commerce, which is not available after 1986. 19

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To test whether contract duration is affected by negotiation costs, specific investments and uncertainty, I regress NFL contract length on player's selection number, team's empty seats percentage, team wins the prior year, whether the draftee attended a non-Division IA school, as well as the team's MSA population, head coach tenure, prior year's stadium capacity, and whether stadium capacity has increased or decreased by more than 1,000 seats. Team fixed effect, as well as player's position, draft round, and draft year fixed effects are also included in the regression.22 Binomial regression is applied for the estimation, since contract duration ranges discretely from one to seven years.23 To be specific, the conditional mean to be estimated is assumed as E(lengthi|xi)=p(xiβ)L, where xi denotes the set of regressors; p(xiβ) is a logistic distribution;24 and L is the maximum contract length. Since contract length is restricted, multiplying the estimated probability by L guarantees the fitted value will not exceed the sample range. Columns (1) and (4) of Table 6 present the coefficient estimates from this baseline regression.25 The coefficient estimates support the conjecture that, when the buyer is less 22

The empirical results are similar if different sets of fixed effects are applied. To be specific, instead of including all fixed effects in the regression, I have also run the regression with different combinations of fixed effects, including 1) draft round only; 2) draft round and player's position; 3) draft round, player's position, and draft year. 23 The other three possible choices for estimation are ordinary least square (OLS), ordered probit regression, and Poisson regression. The problem of OLS estimation is that it may predict the fitted value to be more than seven or less than zero. The ordered probit regression is not used since there is no data censoring problem in the contracts used here, which is a common problem in the empirical contract duration literature mentioned by Masten and Saussier (2000). At last, by using Poisson regression, the fitted value is assured to be positive but larger than the upper bound of the variable. While only the results from binomial regression are reported, they are robust to these different estimation methods. 24 The marginal effects are similar if the probability function is assumed to be Gaussian. 25 The coefficient estimates reported in Table 6 are not marginal effects. To calculate the marginal effect of a continuous variable from the binomial regression, the partial derivative of the probability function with respect to the regressor is evaluated at the sample mean of all regressors. For a dummy variable, the

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risk averse than the seller, contract length increases with negotiation costs, specific investments and uncertainty. First, the selection number of player has a negative and statistically significant coefficient for both time periods. If a player was drafted 20 picks later within a round, the duration of his contract will be reduced by about 0.1 years for both time periods. Notice the coefficient estimates were obtained conditional on the round fixed effects. The round dummy coefficients suggests that, compared to players drafted in other rounds, the first round draftees obtained an average of 0.57 year longer contract during 86-91, and 2.17 years during 01-07. The result indicates contract length increases with negotiation costs. In addition, the coefficient on empty seats percentage and number of team wins in prior season vary in sign with the only statistically significant coefficient being the negative coefficient associated with wins for the 01-07 drafts. 26 Second, players from small schools obtained on average 0.08 year longer contracts than their big school counterparts during 86-91, and 0.04 year longer contracts during 01-07. The coefficient estimates indicate that, when the buyer is less risk-averse than the seller, contract length increases with the uncertainty. The coefficient estimates are not precisely measured for the 01-07 dataset because only nine percent of draftees graduated from small schools during 01-07, while 21 percent of draftees were from small schools during 86-91. Third, comparing to other positions, a quarterback had the second shortest contract in the 86-91 dataset, but the longest one in the 01-07 dataset. Since

marginal effect is evaluated as the difference between the estimated probability when the dummy equals one and when it equals zero. 26 All else equal, one percentage increase of empty seats in the prior year is related to a 0.17 year longer contract in the 86-91 dataset, but a 0.38 year shorter contract in the 01-07 dataset. On the other hand, one more winning game in the prior year relates to 0.002 year longer contract in the 86-91 dataset, but 0.012 year shorter contract in the 01-07 dataset.

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players rarely changed teams unless via a trade prior to the 1993 CBA, the holdup issue is more of a concern in the later years.27 Regressions (2) and (5) of Table 6 include an interaction of empty seats and selection number and an interaction of the stadium capacity last year and selection number as regressors. The empirical evidence supports the conjecture that the effect of empty seats on contract length may differ for early and late draftees. All else equal, the empirical results show that the empty seats percentage in prior season is positively related to contract length, but the effect decreases with the selection number. 28 Similarly, regressions (3) and (6) of Table 6 include the interaction term between the number of wins last year and selection number. Compared to other teams, a team with fewer wins last year signed longer contracts with early draftees but shorter contracts with later draftees. 29 These results provide further supports the hypothesis that contract length increases with negotiation costs.

5.2 Franchise Contracts To test whether franchise contract length is affected by negotiation costs, specific investments, and uncertainty, I regress contract length on whether the franchisor was listed in Bond's Top 100 franchisors, whether the franchisor offers area development agreement, whether the franchisor allows a home-based unit or a kiosk as an outlet, the number of days of total training, and whether the franchisor is in the equipment rental 27

For example, the baseline regression indicates a quarterback has an average of 0.13 year longer contract than other positions during 01-07. By using the same specification but excluding the position fixed effect, the regression shows a quarterback has on average 0.05 year shorter contract than other positions during 86-91, but 0.07 year longer contract during 01-07. 28 For example, longer contracts were signed by the teams with more empty seats last year in the 86-91 dataset, but the same teams signed shorter contracts with the draftees after the 190th pick. 29 For example, shorter contracts were signed by the teams with more wins last year in the 01-07 dataset, but the same teams signed longer contracts with the draftees after the 185th pick.

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services, business aids and services, or educational products and services sectors. The other covariates are the number of units in a chain, the number of years since the franchisor first franchised, and whether franchisor is headquartered in a state that restricts termination of a franchise contract.30 Since lengths are often much longer for franchise compared to NFL contracts, Poisson regression is an appropriate estimation method.31 In particular, the conditional mean is E(lengthi|xi)==exp(xiβ), where xi denotes the set of regressors, and lengthi given xi has a Poisson distribution. Table 7 presents the coefficient estimates from this specification. These estimates are similar whether or not business sector fixed effects are included. The empirical results support the hypothesis that, when the buyer is more risk averse than the seller, contract length increases with more negotiation costs and specific investments, and less uncertainty. First, all else equal, franchisors listed in the Bond's Top 100 franchisors provided about 18 percent longer contract than other franchisors, and this difference is statistically significant. The franchisor who offered area development agreement also provides three percent longer contract than other franchisors. The results indicate that franchisors offered longer contract when there were more negotiation costs. Second, the franchisors in the equipment rental services, business aids and services, or educational products and services sectors provided 69 percent shorter contract than other franchisors.

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BMV applied the number of total units and the number of years since first franchised as the proxies for learning. They argued franchisor with more experience and units in a chain is able to learn more about the optimal contract terms. The contract length will be longer since the franchisor does not need the flexibility to adjust the contract terms. 31 Similar results can be found by using OLS or binomial regressions.

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This statistically significant difference suggests that, when the buyer is more risk averse than the seller, contract length decreases with the uncertainty. Finally, if a franchisor allows a home-based unit or a kiosk as a franchise outlet, the franchisor on average provides an eight percent shorter contract. If a franchisor reduces the required total training by a day, contract length on average shorten by 0.3 percent. These estimates are statistically significant and provide the evidence that contract length increases with specific investments, which is consistent with the literature.

6. Conclusion The existing research testing contract theory provides limited evidence on the determinants of contract length. While the effects of negotiation costs and uncertainty have been tested using union-firm contracts, the effects of specific investments on contract length have been tested only in commercial contracts. This is the first paper to test the three determinants of contract length for both labor and commercial contracts using NFL and franchising data. The empirical evidence indicates that contract length increases with negotiation costs and specific investments. In addition, contract length increases with uncertainty when the seller (player) is more risk averse than the buyer (team), and decreases with uncertainty when the seller (franchisor) is less risk averse than the buyer (franchisee). Further research is required to see if these relationships hold for other types of commercial and labor contracts.

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References Bandiera, Oriana. "Contract Duration and Investment Incentives: Evidence from Land Tenancy Agreements," Journal of the European Economic Association, 2007, 5(5), pp. 953-86. Blair, Rogert D. and Lafontaine, Francine. The Economics of Franchising, 2005, Cambridge University Press. Bolton, Patrick and Dewatripont, Mathias. Contract Theory, 2005, The MIT Press. Bond, Robert E., et al. Bond's Franchise Guide, 2007, Source Book Publications. ---------. Bond's Top 100 Franchises, 2006, Source Book Publications. Brickley, James A.; Misra Sanjog; and Van Horn, R. Lawrence. "Contract Duration: Evidence from Franchising," The Journal of Law and Economics, 2006, 49(1), pp. 173-96. Cheung, Steven N.S. "Transaction Costs, Risk Aversion, and the Choice of Contractual Arrangements," The Journal of Law and Economics, 1969, 12(1), pp. 23-42. Chiappori, Pierre-André and Salanié, Bernard. "Testing Contract Theory: a Survey of Some Recent Work," CESifo Working Paper Series No. 738, 2002, SSRN: http://ssrn.com/abstract=318780 Collective Bargaining Agreement (CBA): between The NFL Management Council and The NFL Players Association, March 8, 2006. http://www.nflplayers.com/user/template.aspx?fmid=181&lmid=622&pid=0&typ e=l Crocker, Keith J. and Masten, Scott E. "Mitigating Contractual Hazards: Unilateral Options and Contract Length," RAND Journal of Economics, 1988, 19(3), pp. 327-43. Danziger, Leif. "Real Shocks, Efficient Risk Sharing, and the Duration of Labor Contracts," Quarterly Journal of Economics, 1988, 103(2), pp. 435-40. Duberstein, M. J., “On the Sidelines: An Annual Economic Analysis of the National Football League Prepared for Members of the NFL Players Association,” National Football League Association, 1992. Dye, Ronald. "Optimal Length of Labor Contracts," International Economic Review, 1985, 26(1), pp. 251-70. Gray, Jo A. "On Indexation and Contract Length," Journal of Political Economy, 1978, 20

86(1), pp. 1-18. Guriev, Sergei and Kvasov, Dmitriy. "Contracting on Time," American Economic Review, 2005, 95(5), pp. 1369-85. Harris, Milton and Holmstrom, Bengt. "On the Duration of Agreements," International Economic Review, 1987, 28(2), pp. 389-406. Hendricks, Wallace; DeBrock, Lawrence and Koenker, Roger. "Uncertainty, Hiring, and Subsequent Performance: The NFL Draft," Journal of Labor Economics, 2003, 21(4), pp. 857-86. Joskow, Paul L. "Contract Duration and Relationship-Specific Investments: Empirical Evidence from Coal Markets," American Economic Review, 1987, 77(1), pp. 16885. Klein, Benjamin; Crawford, Robert G. and Alchian, Armen A. "Vertical Integration, Appropriable Rents, and the Competitive Contracting Process," The Journal of Law and Economics, 1978, 21(2), pp. 297-326. Klick, Jonathan.; Kobayashi, Bruce H. and Ribstein, Larry E. "The Effect of Contract Regulation: The Case of Franchising," George Mason Law & Economics Research Paper No. 07-03, SSRN: http://ssrn.com/abstract=951464. Lafontaine, Francine. "Agency Theory and Franchising: Some Empirical Results," RAND Journal of Economics, 1992, 23(2), pp. 263-83. ---------. and Bhattacharyya, Sugato. "The Role of Risk in Franchising," Journal of Corporate Finance, 1995, 2, 39-74. ---------. and Slade, Margaret. "Vertical Integration and Firm Boundaries: The Evidence," Journal of Economic Literature, 2007, 45(3), pp. 629-85. Masten, Scott E. and Saussier, Stephane. "Econometrics of Contracts: An Assessment of Developments in the Empirical Literature on Contracting," Revue d'Economie Industrielle, 2000, 92, pp. 215-36. Murphy, Keven J. "Deternimants of Contract Duration in Collective Bargaining Agreements," Industrial and Labor Relations Review, 1992, 45(2), pp. 352-65. Vázquez, Luis. "Determinants of Contract Length in Franchise Contracts," Economics Letters, 2007, 97, pp. 145-50. Wallace, Frederick H. "The Effects of Shock Size and Type on Labor-Contract Duration," Journal of Labor Economics, 2001, 19(3), pp. 658-81.

21

Williamson, Oliver E. "Credible Commitments: Using Hostages to Support Exchange," American Economic Review, 1983, 73, pp. 519-40.

22

Table 1 Summary statistics of the NFL contracts during 1986-1991 and 2001-2007 19861991 2.74 (0.80)

20012007 3.81 (1.02)

Proportion of division IA player

0.79 (0.41)

0.91 (0.28)

Empty seat ratio last year

0.18 (0.14)

0.06 (0.08)

Average paid attendance last year per home game (10,000 seats)

5.31 (0.92)

6.59 (0.80)

Capacity last year (10,000 seats)

6.80 (0.92)

6.97 (0.61)

Dummy=1 if stadium capacity increased more than 1,000 seats from the prior year

0.07 (0.25)

0.08 (0.27)

Dummy=1 if stadium capacity decreased more than 1,000 seats from the prior year

0.02 (0.15)

0.04 (0.20)

Wins last year a

7.77 (2.96)

7.88 (3.05)

Head coach tenure

5.72 (6.38)

3.96 (3.05)

Metropolitan population (1,000,000)

4.78 (4.94) 1872

5.01 (4.95) 1782a

Variable Contract length

Observations

Note: a. Variables related to the prior year have sample size equals 1770. Standard deviations are in parentheses

23

Table 2 Summary statistics of the franchise contracts information from Bond (2007) Variables Length of the initial contract (in year)

Mean 11.15 (6.46)

Dummy=1 if listed as Top 100 franchisors in 2006

0.10 (0.30)

Dummy=1 if area development agreement is offered

0.54 (0.50)

Dummy=1 if allowed building type of unit are home-based or kiosk

0.19 (0.39)

Years since first franchised

19.51 (12.58)

Required total training (in days)

22.82 (25.65)

Number of total units (in 1,000)

0.49 (1.98)

Dummy=1 if the franchisor is in equipment rental services, business aids and services, or educational products and services sectors

0.12 (0.33)

Dummy=1 if headquartered in a state that restricts contract termination

0.31 (0.46) 1005a

Observations Note: a. Sample size varies across variables since some franchisors did not respond to every question in the survey. Standard deviations are in parentheses

24

Table 3 Percentage of building types allowed for franchise outlet Building types Percentage Strip Center 49.95 Free Standing Building 46.67 Store Front 32.57 Regional Mall 25.25 Home-based Unit 18.91 Miscellaneous 7.54 Office Building 5.36 Warehouse 2.51 Industrial Park 2.19 Kiosk 2.08 Convenience Store 1.42 Power Center 1.20 Executive Suite 0.98 Observations 915

25

Table 4 Percentage of franchisors by business sector Sector Percentage Automotive Products and Services 6.17 Business Aids and Services 5.67 Construction, Home Improvement, Maintenance, and Cleaning Services 13.13 Educational Products and Services 5.97 Hotels, Motels, and Campgrounds 2.29 Laundry and Dry Cleaning Services 1.00 Recreation, Entertainment, and Travel 1.89 Rental Services (Auto-Truck) 1.00 Rental Services (Equipment) 0.60 Retailing (Food) 31.54 Retailing (Non-Food) 12.14 Miscellaneous 18.61 Observations 1005

26

Table 5 Proxies for negotiation costs, specific investments, and uncertainty in the NFL and the franchise contracts Determinants NFL Contracts Franchising Contracts Negotiation Selection number in 1. Whether franchisor is listed as a Top 100 franchisor Costs the draft 2. Whether franchisor offers area development agreement Specific Investments

Whether player is a quarterback

1. Whether allowable building type for outlet includes home-based unit or kiosk 2. Number of days of total training

Uncertainty

Whether player graduated from Division IA school

Whether franchisor is in equipment rental services, business aids and services, or educational products and services sectors

27

Table 6 Binomial regressions: Dependent variables (Contract length of the NFL contracts) Independent Variables Selection number in the draft

Empty seats percentage in home games last year

(1)

1986-1991 (2)

(3)

(4)

2001-2007 (5)

(6)

-0.004*** (0.001)

-0.003** (0.002)

-0.005*** (0.002)

-0.002* (0.001)

-0.001 (0.002)

-0.002** (0.001)

0.112 (0.132)

0.380** (0.166)

0.108 (0.132)

-0.215 (0.185)

0.346 (0.286)

-0.196 (0.183)

Empty seats percentage in home game last year* selection number in the draft Number of team wins last year

-0.002*** (0.001) 0.000 (0.005)

0.001 (0.005)

Number of team wins last year prior to draft* selection number in the draft divided by 1,000 Dummy=1 if graduated from Division IA school

-0.004*** (0.002) -0.008 (0.007)

-0.007* (0.004)

-0.008** (0.004)

0.055* (0.029)

-0.029*** (0.008) 0.157*** (0.044)

-0.054*** (0.019)

-0.055*** (0.019)

-0.055*** (0.019)

-0.027 (0.031)

-0.026 (0.031)

-0.026 (0.031)

-0.031 (0.049)

-0.030 (0.048)

-0.032 (0.048)

0.097** (0.047)

0.095** (0.046)

0.084* (0.046)

Metropolitan population (1,000,000 person)

-0.161*** (0.054)

-0.159*** (0.055)

-0.160*** (0.054)

0.028 (0.033)

0.028 (0.033)

0.027 (0.033)

Number of head coach tenure at draft year

0.013*** (0.003)

0.013*** (0.003)

0.013*** (0.003)

0.007 (0.004)

0.007 (0.004)

0.006 (0.004)

-0.071 (0.044)

-0.054 (0.046)

-0.069 (0.044)

0.016 (0.037)

0.020 (0.049)

0.016 (0.036)

Dummy=1 if player is quarterbacka

Stadium capacity of team last year (10,000 seats)

Stadium capacity of team last year (10,000 seats)* selection number in the draft divided by 1,000

-0.097 (0.090)

-0.062 (0.235)

Dummy=1 if stadium capacity increased more than 1,000 seats from the prior year

-0.040 (0.049)

-0.042 (0.048)

-0.040 (0.049)

-0.099*** (0.032)

-0.103*** (0.032)

-0.102*** (0.032)

Dummy=1 if stadium capacity reduced more than 1,000 seats from last year Indicator variables, including draft round, player’s position, draft year, and draft team fixed effects Observations R-squaredb

-0.105* (0.058)

-0.109* (0.057)

-0.106* (0.058)

-0.051 (0.039)

-0.050 (0.039)

-0.050 (0.039)

YES

YES

YES

YES

YES

YES

1872

1872

1872

1770

1770

1770

0.65

0.66

0.66

0.68

0.68

0.68

Log-likelihood

-2255.13 -2254.14 -2254.83 -2292.87 -2292.00 -2291.23 Note: a. The coefficients were estimated relatively to the position of defensive linebacker. b. R-squared is the squared correlation coefficient between the observed and the fitted values of the contract length variable. The coefficient estimates are not marginal effects. Robust standard errors are presented in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%.

28

Table 7 Poisson regressions: Dependent Variables (Contract length of the franchise contracts) Independent variables Dummy=1 if listed as Top 100 franchisors in 2006

(1) 0.168*** (0.032)

(2) 0.175*** (0.032)

0.030 (0.021)

0.037 (0.023)

Dummy=1 if allowable building type of unit are home-based or kiosk

-0.119*** (0.028)

-0.075** (0.030)

Number of days of required total training

0.002*** (0.000)

0.003*** (0.000)

Dummy=1 if franchisor is in equipment rental services, business aids and services, or educational products and services sectors

-0.115*** (0.034)

-0.692*** (0.202)

Number of total units divided by 1,000

0.002 (0.005)

0.005 (0.005)

Number of years since first franchised

0.005*** (0.001)

0.004*** (0.001)

Dummy=1 if located in the state requires good cause for termination

0.090*** (0.021)

0.086*** (0.021)

Business sector fixed effect Observations R-squareda Log-likelihood

NO 911 .08 -3055.13

YES 911 .12 -2999.25

Dummy=1 if area development agreement is offered

Note: a. R-squared is the squared correlation coefficient between the observed and the fitted values of the contract length variable. The coefficient estimates are not marginal effects. Standard errors are presented in parentheses. *significant at 10%; ** significant at 5%; *** significant at 1%

29

Figure 1 Contract length 50 45

Proportion of contracts

40 35 30 25 20 15 10 5 0 1

2

3

4

5

Contract Length 86-91

30

01-07

6

7

6

35%

5

30% 25%

4 20% 3 15% 2 10% 1

5%

0

Proportion of Non-DIVIA School Graduates

Average Contract Length

Figure 2 Average contract length and the proportion of Non-Division IA (NonDIVIA) school graduates

0% 1

2

3

4

5

6

7

8

9

10

11

12

Round Length(86-91)

Length(01-07)

Non-DIVIA(86-91)

31

Non-DIVIA(01-07)