- Email: [email protected]
An empirical examination of organizational structure: The economics of the factoring decision
Journai of Corporate Finance 1 (19941 119-13
Janet tiholm
Smith ‘**, Christjahn
Schnucker
b
a Department of Economics, Arizona State Vdrersity, ‘American
Tempe, AZ 85281, USA, Express Corporation, Phoekq AZ 8SO27, USA
Winal version received November
1993)
Abstract Sellers who cxkend trade credik to their business customers choose whether to integrate the management of trade credit or to enter into specialized factoring contracts. Using original data from a broad cross-section of filins we test a model of this decision. The model is based on a theory of the firm that stresses transactions costs (including information costs) as determinants of vertical integration. Consistent with expectations, we find that specificity of assets to the buyer-seller relationship is negatively related ko the decision to factor and that factors are more likely to be used when information and monitoring costs are high.
Key WQV&:Organization; Contracting; Trade credit; Factoring JEL classification: G3; I.2
A selling firm’s decision to extend trade credit to its business customers anagealso requires the seller to decide whether to integrate into credit
* Corresponding author. Telephone: (602) 9654682; fax: (6021 9650748. We wish to thank Jim Brickley. Andrew Christie, Harold cmsetz, Ben Klein, Stuart Smith and Richard Smith for useful comments an scussion. We z&o benefited from comorkshop at Llniversity of Rochrstcr, ?!I(_ ments of seminar participants at UCLA. the Olin DuPont Seminar at RSU and the lnternational S osium on Cash, Treasury and Working Capital Management, San Francisco, 1992. Grants from the Center for Financial System Research and the College of
usiness Arizona State University. arc gratefully acknowvled:ed.
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ment. Rather than integrating, the seller can enter into a market transaction (such as a factoring contract) to arrange for a third party specialist to manage its trade credit. In factoring contracts, all credit management functions commonly are delegated to the factor. ’ In addition, the selling firm may borrow from the factor, using factored receivables to secure the loan. In this paper we view the factoring decision as a choice about organizational structure. We derive testable implications from the industrial organisaGon literature on vertical integration as developed by Coase (1937), Williamson (1975, 1979, 1981, 1985) and Klein et al. (1978), among others. This literature concerns the effects of transaction-specific investments and transactions costs (defined to include information and monitoring costs) on the choice of organizational structure. Generally, we expect to observe factoring when the level of the seller’s specialized investment in buyers is low, when the cost of monitoring buyers is high and when the cost of determining product value is high. These implications are tested with data from 770 firms competing in a variety of industries. We find that transactions costs are important determinants of the choice between integrating credit management and factoring. We also test the empirical importance of economies of scale and traditional explanations (such as seller illiquidity and seasonal sales patterns) for the decision to factor.
2. The nature of factoring contracts When a firm sells its products to a distributor or other business customer it may specify that payment is due before, on, or after delivery. If payment is not required until after delivery, the seller is extending trade credit. As such, the seller is financing the buyer’s inventory and is directly or indirectly involved in assessing and bearing credit risk, monitoring the buyer’s inventory and general financial health, and bookkeeping and collecting activiQies. These credit management functions can be performed by the seller or can be contracted entirely or partly to third parties such as credit-reporting firms, captive finance subsidiaries. collection agencies and factors. A factor com-
’ The term ‘factoring’ is derived from Latin and wac; . ::wJ historically to refer to a mercantile agent who aided iI business in its trade by buying and selling in distant lands, taking goods on czonsignmentand advancing money. In the US the first factors were British textile agents. At first they imported. stored and sold ;extiles but in the latter part of the 19th century large tariffs on imported !ex!iles caused restructuring of the industry and factors limited their services to credit management and financing. Accounts of the development of factoring appear in Silverman t IOK!). and WI C‘richton and Ferrier f I9Hf1).
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monly will perform all these activities, whereas the other choices require the seiler to integrate into some of the trade credit functions. 2 Sellers that employ factors sometimes find that borrowing from the factor compares favorably to other alternatives in terms of interest cost and flexibility, partly because the factor already is involved in managing the seller’s trade credit. Thus, it is not surprising that long-term contracts between sellers and factors commonly provide the opportunity to borrow using receivables as security. An alternative arrangement used by some sellers that provide their own credit management is to engage factors occasionally as lenders ex post to meet short-run financing needs. In these spot transactions the factor exchanges cash for the right to the seller’s receivables. This arrangement appears to be one kind of factoring relationship that has given rise to the common perception that borrowing from factors is expensive relative to alternatives. Another aspect of factoring that leads to this perception is that factored receivables frequently involve products where typical trade credit discounts for prompt payment are large (such as stylish garments) and these discounts are reflected in the implicit interest rates defined by trade credit terms. 3 Many factoring arrangements provide that the selling firm must notify the factor on a continuous basis of all sales contracts into which it intends to enter. The factor then reviews each contract and, at its discretion, makes a decision to approve or reject it. If the contract is approved, the factor becomes the owner of tne receivable from the sale. To facilitate its decision the factor has full access to the seller’s sales ledger and the experience records of each account. In some cases, the factoring contract c:>mpels the seller to disclose all information it has acquired about the buyer’s creditworthiness. 4 For approved contracts the factor assumes all credit risk without recourse. It may even in these cases, however, retain the right to collect from the seller if the buyer disputes the order and declines to pay for reasons such as unsatisfactory product quality or breach of warranty. Thus,
’ In a recent paper, Mian and Smith (1992) examine the choice among alternative accounts receivable management policies, including factoring. A number of implications they derive could not be tested by them due to limitations of their accounting-based data which tend to systematically understate the use of factoring. As discussed below, using a different data source, we find support for several of their hypotheses. 3 For examp!e. credit terms of 8/10 E.O.M. (end-of-month) are typical for firms selling Women’s Blouses and Waists, Women’s Coats and Suits, and Women’s, Misses’ and Juniors’ Dresses. The terms offer an 8% discount if the invoice is paid within 10 days; ctherwise, the full amount of the invoice is due within 30 days. If the customer fails to take the discount, then implicitly the customer is borrowing for 20 days at an effective annual interest rate of 152%. ’ For example, a standard contractual provision requires ‘disclosure of . . . all matters of fact or oninion known to be or held by the supplier . . . concerning the credit-worthiness . . . of any debtor.’
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when the seliing firm delivers a sales contract to the fiictor the contract implicitly is accompanied by the seller’s representation that the agi.eement ~,.‘a:sot ::c breached e~,~~s> a A-c tr2 t?; buyer’s financial distress (which risk is &F:: by the Cactor). In some cases the factor may deem the buyer’s credit risk to be unacceptably high, and will not approve the contract. In such case, the seller can still undertake the sale and engage the factor to finance the receivable and aid in collection if necessary. However, the credit risk is borne by the seller. In this scenario, the factor has recourse to the seller if the account goes unpaid due to financial distress of the buyer. ’ It is apparent from the above discussion that factoring relationships are complex bilateral contracts involving many separate decisions with respect to unspecified contingencies and they create the potential for opportunism. To limit the potential for opportunistic behavior by ,the selling firm the factor commonly requires an exclusive relationship and perfects a security interest in all of the receivables of the seller. Without such an arrangement the seller would have an incentive to ‘cherry pick’, leading to an adverse selection problem for the factor. In addition, since the factor supplies credit insurance, a moral hazard may arise as the seller has incentives to withhold information or provide misleading information about the buyer’s credit-worthiness in an effort to influence the factor’s decision to accepL an invoice. 5 The written contract does little to protect the seller from opportunism by the factor, often specifying no more than that the factor ‘will act in a commercially reasonable manner’ in determining whether or not to approve sale contracts. ‘Accordingly, the reputation of the factor is a critical element of the efficient functioning of factoring markets. The importance of reputation appears to explain why the principal providers of factoring services are a few well-established old-line factors, commercial banks and factoring sub-
5 Regardless of whether receivables are factored with or without recourse, payments received from the factor usually are recorded as reductions of the seller’s accounts receivable balance, despite the fact that contingent liability may remain. f-fence, the decision to factor affects the accounts receivabie and cash positions of the selling firm. This endogeneity limits the usefulness of accounting ratios as explanatory variables of the seller’s decision to factor. ’ The seller (the factor’s customer) also can behave opportunistically by seeking payment from the factor prior to the goods actually being shipped. The most prevalent form of fraud in this market is selling fictitious debt. See Crichton and Ferrier (1986). ’ A review of standard factoring agreements shows the wording ‘commercially reasonable’ frequently is omitted and instead agreements provide that the ‘Factor may in its absolute discretion reject a Deb? . . .’ or ‘The Factor shall be entitled to withdraw its approval . . . it shall be under no obligation to give a reason for so doing.’ The one-sidedness of the contract terms is consistent with Klein (1980). who argues that when both parties to a contract can cheat or hold-up the other, ‘explicit contractual restraints are often placed on the smaller, lesl, wellestablished party . . . while an implicit brand name contract-enforcement mechanism is relied on to prevent cheating by the larger, more well-established party . . .’ ip. 360).
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sidiaries of bank holding companies. s There are likely to be economies of scale associated with the factor’s brand name because the factor’s reputational capital iq put on the line with each individual sale of a client. ’ This implies, as Mein (1980) predicts, a lower cost of relying on the brand name of a large firm versus a small firm and implies one side of the contract will be relatively more incomplete. As noted, factors sometimes are engaged to provide immediate cash in exchange for receivables. This type of spot transaction does not necessarily require highly specialized industry knowledge, although the receivables must be valued. However, when a factor is employed to bear credit risk on an ongoing basis, the factor can find it advantageous to monitor both seller and buyer behavior as well as variables such as inventories, sales levels, product quality changes, etc. The highly specialized knowledge that results enables the factor to add value to transactions between market participants. As an example, possession of specialized industry knowledge can enable factors to arbitrate disputes about product quality between buyers and sellers. In this context, demand for factoring is expected to be high where sellers and buyers do not necessarily know each other’s reputations, but each is familiar with the factor. ‘” As another example, factors acquire industry-wide information that enables them to forecast industry sales. Such information can benefit individual clients by aiding them in production planning and marketing efforts. ’ ’ ’ The original American factors are referred to as old-line factors who offered a line of services that included selling, servicing of debts, collection and maintenance of customer relations. ’ The majority of factored sales in the US are handled by a small number of large factoring enterprises. Fifteen firms dominate the market that has grown steadily to levels of over $45 billion in annul-;1 factored sales. The ten largest ccmpanies hold 72% of the market. Large US factors include CIT Group, Heller Financial, Capital Factor- J, and Bank of Boston. Factoring divisions frequently are subsidiaries of financial holding companies. See Dohler, 1990, ‘The new world of factoring’, The CPA Journal, 44-48. ‘” In markets involving sales to final consumers, credit card companies and banks that issue credit cards provide services analogous to non-recourse factoring. The credit card issuer, like a factor, may supply reputational capital that facilitates a sale that is characterized by uncertainty about the seller and/or the buyer. In effect the business that accepts a credit card ‘sells’ the receivable that is created by the sale to the card issuer. Card companies also aid in redressing problems associated with unacceptable merchandise or service and billing disputes. See Edwards (1990, chap. 26) and Hart (1991, p. 3% ” See Christie ei al. (i991) who refer to this type of knowledge as ‘assembled knowledge,’ which IS produced by essembling and analyzing knowledge of particular circumstances. See also Jensen and Meckling (1990, p. 9). The importance of information acquired by a factor is illustrated when there is news that a factor has teas ;E to proLid< fi;naiYcing to a customer. For example, the refusal by Heller Financial to accept invoices from Saks Fifth Avenue in !ate .Iuly of 1991 ivas a leading indicator of Saks’ financial difficulties at the time. Sellers could then use this information to adjust marketing and sales efforts dire,cted at Saks (Business Week, Aug. 12, 1991, pp. 30-31 and Aug. 26, 1991, p. 52). As an anoth* .-example, Leslie Fay’s Chapter 11 bankruptcy filing in 1993 ws proceeded by news that Leslie Fay’s factors were refusing to buy their receivables. Apparently news of the loss of confidence by the factors led suppliers to refuse to offer trade credit to Leslie Fay (W’WD, April 6. 1993, p. 1).
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3. Determinants of the decision to factor Since Coase’s seminal work on the theory of the firm, economists have recognized that the rationale for vertical integration is found in the &sire to reduce or avoid transactions costs arising from using the price mechanism to guide resources. Using the price system is costly because information about resource values is not free. A basic tenet of Coase’s theory is that, when seieeted from among a set of alternatives, a contract is a means of mitigating information cost. 3. I. Asset specificity The decision to factor is a choice to enter into a specialized contract for trade credit management rather than to integrate the functions. Coase contends that choices like this one are made by comparing the transactions costs of contracting for performance of the functions with the costs arising from internalizing the functions within the firm. Work by Williamson (1975, 1979, 1981). Klein et al. (1978) and others suggests that the decision is determined by the nature of the transaction between seller and buyer. If the parties are required by competition to make highly specific, nonsalvageable investments in order to complete the transaction efficiently, then opportunism is more likely and hence vertical integration is more likely, ceteris paribus. As examples, the transaction may require the seller to invest in learning the production process of the buyer or to invest in specific machinery. Asset specificity creates incentives for opportunistic behavior since once an asset is specifically committed to the buyer, the seller is vulnerable to the buyer’s demands to renegotiate the terms of the original agreement, and vice versa. There is a direct connection between the presence of specific assets and the incentive of a seller to extend trade credit to buyers and to internalize credit management. The presence of specialized investments has been modeled by Smith (1987) to be a primary determinant of sellers’ decisions to offer trade credit. By offering two-part trade credit terms (such as 2/l& net 30) a seller can identify prospective defaults more quickly than if financial institutions were the sole providers of short-term financing. For example, terms of Z/10, net 30 offer the buyer a choice between a 2% discount if the invoice is paid within IO days or no discount with the full invoiced amount due in 30 days. Since the terms reflect a high implicit rate of interest, buyers who are experiencing financial difficulties and are unable to secure lower cost financing are mop f likely than others to forego the discount. Hence, the choice rev@& in’ormation to the seller concerning buyer default risk. The selling firm is alerted to this risk earlier by offering trade credit than by selling on cash terms or simple net terms. Hence, the screening process alerts the seller
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to monitor the buyer. Monitoring can indicate whether to continue to extend credit to the buyer or to modify subsequent sales contracts. Eariy information about the buyer is valuabl:: in cases where the seller hz:s made specific investments in buyers since it enables the seller to take actions to protect suck investments. I* A seller that has made specific investments is less likely to want to use a factor to provide financing, monitoring and collecting services for the account. This is because a seller who relinquishes credit management to a factor also limits the ability to preserve the value of its specialized investment by designing timely and flexible credit procedures for troubled buyers. For example, the seller may be able to preserve its investment in a long-term repeat buyer who is faced with financial difficulties by offering trade credit, monitoring the buyer, and then offering flexible payment terms if the seller can determine that the difficulties are not permanent. In contrast, forcing the buyer to accept cash only terms could cause the buyer to fail or to seek a new supplier. The presence of specific assets reduces incentives to factor for other reasons as well. The specific investment may entail, for example, significant point-of-sale effort and other types of human capita1 investment that require the salesperson to spend considerable time with an account. Under these circumstances, monitoring of the account is a by-product of the selling effort. Thus, a factor would not have access to ihe same information about the buyer’s business at the same cost as the seller. In the empirical work that follows we focus on investment in human assets (knowledgeability and ongoing relationships) which tie the selling firm to the buyer. In some industries, for example, it may be necessary for the salesperson to invest substantial time in learning the ‘ins and outs’ of the buyer’s organiz,,+ion or production technology (Anderson and Schmittlein, 1964). Indeed, some rc!ationships may become so important that the buyer exhibits loyalty to the salesperson, rather than the principal (the seller). When the level of these relationship-specific investments is high, vertical integration of trade credit management is likely. Hence the decision to factor is expected to be negatively associated with the extent to which the seller makes a specific investment in buyers as reflected by the need for salespeople to invest substantial time in their accounts.
” The information is relayed more quickly than if a financial institution were tbe lender and cash terms were imposed on the buyer. ‘The information regarding default risk is more valuable to the seller than to financial institutions, thereby providing an explanation for why sellers ge! involved in financing rather than leaving it !o financial institutions. The seiler is able to offer credit to a given risk class of buyers at lower rates than financial institutions.
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3.2 Pnfonntriiun and monitoring costs
Theory suggests information costs have an effect separate from the presence of specialized investment on the choice of whether to integrate trade predit functions. I3 In markets with imperfect information, costs will be * incurred (by the seller) to determine buyer credit-worthiness and (by the buyer) to determine the value of the goods or services to be exchanged. Diamond (1984) develops a general theory of financial intermediation based on minimizing the cost of generating and using information for monitoring. Such monitoring inform.ation is useful for resolving incentive problems between borrowers and lenders. In this context factors can be thought of as intermediaries who are delegated monitoring functions. Factors position themselves as information intermediaries and are able to supply firm-specific information to multiple users. Sellers benefit since factors can accumulate credit information on the buyers and monitor the buyers’ inventories and financial health. Buyers benefit since factors can acquire timely information on the seller’s product quality, shipment regularity, budgetary operations, etc. Diversification across buyers and sellers within an industry is valuable since the factor gains access to more and higher quality monitoring information, The factor, for example, can discern whether a particular buyer’s financial problems are industry-wide OI buyer specific. Hence, an empirical model of cross-sectional patterns of firms’ choices to factor must include variables that reflect the relative magnitudes of these monitoring/ information costs across firms and industries. ‘4 Since factors bear credit risk, the factor will seek information on the credit-worthiness of the buyers. The selling function can be related to credit functions to the extent the salespersons acquire credit information from buyers. On the one hand, sellers can possibly facilitate their factor’s approval of sales invoices if the seller can supply more complete information on credit-worthiness than the factor could obtain directly. Since this information is costly to obtain, some cost savings may be passed on to the seller in the form of lower factoring fees. However, to the extent the seller relies on its salesforce to collect this information, the value-added by a factor from its
” See Demsetz (t988) who emphasizes the important role of information costs in the theorv of the firm. He discusses how the vertical boundaries of a firm are determined by the economies of conserving expenditures on knowledge. ” In addition to the credit management functions described above, factors with specialized industry and firm knowledge sometimes perform managerial and marketing functions. For example, factors may be engaged to help with budget and sales forecasts, buying or selling partnership shares for the seller and acting as an employment agent by placing qualified employees. A factor also can be a useful reference when trying to open new accounts. See Abraham i 1?71).
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own mformation gathering eftorts is reduced, which may lower the likelihood that a factor will be employed. We evaluate these considerations in the empirical work below. Whether the seiling firm will elect to perform its own risk assessment, monitoring and collection functions will depend on the transactions cost differences of alternative ways of organizing these functions. Other things the same, the more heterogenous the buyers in terms of iocation, the higher the costs of integrating the functions. ” These costs must be weighed against the economies of scale and scope associated with using factors, who as specialists, can develop repeat business with disperse buyers. We include a variable to measure the extent of geographic dispersion of the buyers. The expectation is that the broader the customer area, the more likely factoring will be used. More specifically, we test whether sellers with international customers are more likely to factor than sellers with exclusively domestic customers. An advantage for an exporter who uses a factor is the ability to match the payment terms of local competitors since buyers can be offered payment terms on an open account versus being asked to supply a letter of credit or satisfy other credit requirements. Demand for factors in international trade also arises from costs associated with language differences, differing legal requirements governing commercial transactions and the risk of exchange I-ate fluctuations. Another attribute of transactions that contributes to demand for factors is uncertainty as to value of the product or service underlying the transaction. Costs are incurred by both buyers and sellers to obtain such information and these costs can be substantia! when the transaction involves goods or services with highly volatile values (stylish clothes, for example, or customized services such as transportation that may have substantial value to a subset of buyers but not alE buyers). These information costs can give rise to demand for a factor who acts as a middleman in determining whether a sales contract ought to be entered into, and who monitors the status of the receivable and arranges for resale of goods if they must be repossessed. A specialist is likely to arise when the repeat sales frequency of the seller with a given buyer is low but across a group of buyers is high. Under these conditions factoring can reduce the costs of credit extension tc the extent the buyer developmsa stronger business relationship with the factor than with individual sellers. ‘We include a variable to measure the likely extent of uncertainty surrounding value of the product line. The more customized the product line, the greater the expected information costs concerning valne. A positive sign
” Stigler (1968) predicts a relationship between the functional slructure of an industry and its geographical structure. Histcrical accounts suggest geographical dispersion of buyers and distance beween seller and buyer location played an important role in the development of the factoring industry. See Abraham (19711.
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on the variable would indicate that the decision to engage a factor is influenced by demand for reducing asset value uncertainty. 3.3. Dtstribu tion characteristics As recognized by Mian and Smith (1992), many of the same functions that factors perform also can be performed by other intermediaries such as wholesalers. Hence we include variables to reflect the nature of the buyers’ economic functions. The distribution channel affects the credit extension process in several ways. It can affect (and reflect) the level of asset specificity in the transaction and can affect the information costs of va!uing the traded assets and costs of recovering assets if sales contracts are breached. To evaluate the importance of the buyer’s attributes in the seller’s decision to factor we include four categories of dummy variables to classify customer types: 1. The firm sells to original equipment manufacturers or serr+ce-proGders. Since these buyers consume the purchased input in their production processes, the value of the input as collateral is low or nonexistent and hence factoring is less likely. 2. The firm sells to wholesalers. Introduction of a wholesaler between manufacturer and retailer affects the credit-extension process in some of the same ways a factor does, making factoring less likely. Thus, selling to a wholesaler who offers trade credit to retailers (and who manages the trade credit) is a substitute for selling to retailers directly and factoring the receivables. Mass merchandisers are included in this category since they have integrated the wholesaling function. 3. The firm sells to retailers. It is expected that trade credit is more likely to be extended and that factoring of receivables is more likely when selling to retailers than for the above two categories of buyers since these buyers either provide substitute services for factors or make factoring costly for the sellers. 4. Other. A control category is included for those sellers who do not identify a primary customer type. In the regression models presented below the omitted category is retailers. Hence the estimated coefficients test whether each customer type produces effects that are different from those of a firm primarily selling to retailers. The expected coefficients for the first two dummy variables are negative and we have no a priori expectation for the control variable. We also include a dummy variable to indicate whether the seller is a wholesaler. As an intermediary, the wholesaler is likely to devzkb:, specialized knowledge in both buyers and suppliers and to realize the information monitoring benefits described by Diamond. Thus, wholesalers are more likely, other things constant, to internalize trade credit functions.
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3.4. Economies of size in credit management
Firm size also is expected to affect the decision. The fixed costs associated with credit management will be spread over more customers as the firm’s customer-base expands and as the proportion of sales made on credit increases. If few sales are made on credit it becomes more economical for the firm to delegate credit functions to a factor. We include two variables to measure economies of scale-firm size (measured as the log of the seller’s total assets) and the percentage of the seller’s customers to whom trade credit is offered. The expected impacts of these scale variables on the use of factoring are negative. 3.5. Traditional explanations for factors A common perception is that factors are predominantly used by firms with cash flow management problems such as firms with seasonal sales. Traditional measures of firm liquidity cannot be used in the regression. These measures are affected by accounts receivable, cash, and short term liabilities, all of which depend on the factoring choice, making the traditional liquidity measures endogenous. Instead, we measure liquidity using a proxy for the seller’s cash flow-net income plus depreciation, standardized by total assets. Nonetheless, to the extent the decision to factor improves a firm’s cash flow, we will not be able to discern an impact of this variable. To determine if seasonality of sales is important in explaining factoring, we include a variable that measures how frequently a typical buyer places orders and expect factoring to be more likely the less frequentiy orders occur. l6 4. Empirics The data used to examine the testable implications are compiled from two sources. The primary source is a large-scale mail survey of credit managers of firms throughout the US. Second, each company’s response is matched with financial data from Compustat. To be included in the study the firm must have a Compustat record and report a single four-digit SIC code. The latter screen is used to minimize problems associated with multi-product firms that may have credit policies that vary across product lines. The survey instrument was designed to obtain information on individual seller credit terms and policies from a broad cross-section of firms and industries. The questions ” Emery (1987) develops a theory of trade credit based on its use as a financial response to deterministic variations in demand. Following this reasoning, factoring of credit functions may be more likely if sales are seasonal to the extent the factor can diversify across sellers with variable demand and thereby provide the services at lower cost than could sellers.
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Table 1 Descriptive statistics on factoring choices and trade credit choices by industry cross-sectional sample of 770 public firms surveyed in 1991 lndustry category a
Two-digit SIC
Mining
IO-14
Manufacturing Food and tobacco products Textiles and apparel Lumber. wood and furniture Paper, printing Chemicals, petroleum Rubber and leather prodllcts Stone, glass and metal Industrial machinery Electronic and transport equip. instruments and misc.
Number of firms
grouping
Percent of firms that factor
Percent of customers offered trade credit
29
17.2
67.2
20-21 22-23 24-25 26-27 28-29 30-3 1 32-34 35 36-37 38-39
43 28 20 30 67 24 50 117 126 119
X8.6 21.4 25.0 16.7 17.9 20. I 10.0 22.2 22.2 17.6
Total manufacturing
20--39
624
19.4
78.0
Transportation
40-49
49
30.6
65.n
50-5 1
55
12.7
80.3
misc.
13
7.7
89.0
770
19.4
77.1
and communication
Wholesale trade Agriculture. All
construction
and other
for a
a Firms are classified by SIC code groupings of primary product lines as reported on Compustat, and verified by survey respondents. Firms with SIC codes OIOO-5199 were surveyed.
elicit data not only on selling firm attributes and product line characteristics, but also on buyer attributes and the nature of the seller’s relationship with buyers. The instrument was pretested and the survey was conducted in early 1991. A second mailing was made to reach non-respondents. The response rate of 39% is typical of surveys of large public corporations. Statistics describing industrial representation appear in Table 1 for the 770 firms in the sample that offer trade credit. The table shows that 19% of the firms use factors. While textiles, apparel and related industries do rely heavily on factoring, factoring has expanded outside these traditionai industries. ” The highest percentage of use occurs in the transportation and
” The data verify that factoring still occurs in industries that historically have used factors such as textiles. furniture. toys, shoes, plastics and electronics but also occurs in such vcried industries as petroleum products, computer hardware and peripherals, auto parts and accessories, pharmaceuticals, telecommunications equipment, surgical and dental equipment, food products, publishing and transportation.
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Table 2 Means and standard deviations ef explanatory variables
Percent of buyers offered trade credit Seller’s size (log of total assets) Specialized investment made by seller a Buyer consumes product/service as input (OEMs) (0 = no; 1 = yes) Buyer is wholesaler (0 = no; 1 = yes) Buyer type not identified (0 = no; I = yes) Seller is whoies?ler (0 = no; 1 = yes) Product line is customized a Geographic dispersion of buyers ’ Credit information obtained by salespersons a Sales are seasonal a Seller’s cash flow/total assets a Responses are based on an anchored-five-point
Mean
Standard deviation
77 3.70 1.98 0.61
22.60 2.1c 1.01 0.49
0.38
0.49
0.07
0.25
0.07
0.26
2.84 0.67 2.85 2.74 0.12
1.34 0.47 1.35 1.19 0.08
scale as described in the Appendix.
manufacturing sectors. As documented below, factors are used extensively in international trade; of the firms in our sample that engage factors, 67% have international customers. Table 2 contains summary statistics for the variables used in the study. Variable definitions, relevant survey questions, and data sources are reported in the Appendix. The dependent variable is the decision to use a factor and equals 1 if the firm uses a factor to manage receivables and 0 otherwise. Since the dependent variable is binary, a linear probability model would result in heteroscedasticity of the error term and could yield predictions which lie outside the (0, 1) interval. To address these concerns a probit model is used which transforms the dependent variable so that predictions lie in the (0, 1) interval. The transformation is based on the cumulative normal probability function. Assume there is an underlying index, Zi, which represents the ‘propensity’ of a firm to use a factor and which is a linear function of the independent variables we have identified. Observations on Zi are not observable; instead we observe only whether an individual firm is in one category (high value of Zi) or another (low level of Zj). Let Zi equal the critical cutoff value that determines whether a firm uses a factor or not. The probit model assumes Zi* is a normally distributed random variable so that the probability that ZT < Z; can be determined from the cumulative normal probability function. The standardized function is Pi = F( Zi) =
&_/f’CceeS2i2ds,
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where s is a normally distributed random variable with mean zero and unit variance. Hence F;, the probability that the firm uses a factor, lies in the (0, 1) interval and Pi is larger the larger is the value of Z;. The srobabiiity, Pi, that results from the mode1 is an estimate of the conditional probability that firm i will use a factor, given the values of the independent variables. 4.1. Empitid
resu!ts
Table 3 contains results of two empirical models. Eq. (1) includes all the explanatory variables discussed above. The results show that the percentage of trade credit customers, transactions cost variables, and variables describing distribution channels provide significant explanatory power. However, seasonal&y of sales, firm size and the firm’s cash flow do not appear to be significant determinants of factoring. ” The presence of economies of scale in the management of trade credit is indicated by the negative relationship between factoring and percent of customers offered trade credit. Absolute firm size is not a significant variable, which suggests that economies arise not so much from the volume of business as from the proportion of transactions that involve credit extensions. Equation (2) is included to test whether a mode1 that includes transactions cost vdiiables does a significantly better job explaining factoring than does a simple mode1 of integration based on scale economies. We compare the -9uimized likelihood functions of the two models and logarithm of the .._.____ generate a likelihood ratio test statistic. The null hypothesis, that p = 0 for all other independent variables in model (1) is rejected at the 0.05 level. I9 The results show that the measure of relationship-specific capital is associated with a greater likelihood of integration of trade credit management. To the extent the selling firm makes specialized investments in the buyer, the investment has no alternative use value. The presence of this investment ties the two firms together. These conditions make short-term (spot market) contracts between buyer and seller inefficient and make long-term, flexib!e relationships more likely. The prediction in our case is that management of debt arising from such transactions will be internalized by the seiler to provide the seller flexibility in protecting the return on the specific investment. The effect of a one-standard deviation increase in the value of this response above from the mean response is a 2.6% decrease in the probability that a factor will be engaged. The results show factoring is more likely if the product line is customized and hence costlier to value. These valuation costs give rise to demand for a Ix We also estimated the two equations using the sample of manufacturing firms only. Coefficient estimates are not materially different from those shown in Table 3. “) The siatistic c is distributed x2 with 10 degrees of freedom. We find c = 2(362.4+372.3) 19.8. The critical value for significance at the 0.05 level is 18.3.
=
J.K Smith. C. Schnucker /Journal
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Table 3 Probit estimates of sellers’ decisions to factor a Independent
variables
(2) - 0.593
Ecottomies of size variables Percent of buyers offered trade credit Seller’s size (log of total assets) Transactions costs vanahles Specialized investment made by seller Buyer consumes product/service
as input IBEMs)
Buyer is wholesaler Buyer type not identified Seller is wholesaler Product line is customized Geographic
.I (1)
Constant
dispersian
Credit information
of buyers
olltained bysalespersons
Traditiortalexpianatory t~arirrhles Sales are seasonal Seller’s cash flow
133
- 0.877
-0.151 (-2.985) *** - 0.086 ( - 1.277)
-- 0.104 (-- 1.922) - 0.346 t-23671 . . - 0.324 ( - 2.3&J - 0.562 (- 2.132: - 0.307 f - 1.297) 0.103 (1.842) 0.149 (1.255) 0.071 (1.280)
-0.151 t-3.085) *** - 0.083 (- I.3121
* ** ** **
**
- 0.068 (- 1.167) 0.006
(0.008) Log likelihood
- 362.41
***
- 372.33 * * *
a The sample includes 770 firms surveyed in 1991. The dependent variable equals 1 if the firm uses a factor and equals 0 otherwise. Variable definitions and data sources appear in the Appendix, t-ratios, based on two-tailed tests, appear in parentheses below each coefficient. * * * = significant at the 0.01 level, ** = significant at the 0.05 level, * = significant at the 0.10 level.
specialist who has expertise in valuing receivables arising from sakes of suck products and the benefits derived from the specialist outweigh the costs associated with collateralization. The coefficient implies that a response to this question that is one standard deviation above the mean response is associated with a 4% higher probability that a firm wi!! engage a factor. When 3 seller transacts with distantly located firms, information costs and monitoring costs are expected to be higher than if the buyers are nearby. Consistent with this we find sellers with internatiova! customers are more
134
likely
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to use factors than those with only domestic customers, however. the
relationship is only marginally significant. to the variab?e measuring the extent to which the seller’s salesforce acquires i&mnatisn akmt the buyer’s credit-worthiness is only marginally significant, although the sign is positive, suggesting factoring is more likely when sellers .-a EfimP -a*.= r@Q~~~+~ .r.q.W~Wac8en+ln PUS1‘I&. acsumulate credit information, on their customercV.Im relationship is surprising since factors also produce credit information and may be viewed as a substitute service. However, since the seller’s invoices and credit limits for buyers must be approved by the factor, such approval may be facilitated at lower cost if the salesperson produces some of this information. Also, if the factor does not approve the invoice the seller can still make the sale (with factor recourse) and this decision is aided by acquisition of credit information. ThG three variables describing the buyers are all statistically significant. ~?Ils!!Te,CX;: with Wan and Smith’s prediction, seCling to wholesalers or origina! equipment manufacturers lowers the likelihmd of factoring relative to selling to a retailer. ” if the buyer is a wholesaler, the probabiiity of factoring is reduced by 7%. If the buyer is an OEM or service provider, the probability of factoring is reduced by 8%. The results are consistent with the idea that a factor adds value to transactions by aggregating or assembling sales data that can be useful to buyers in discerning demand and cost trends. If the seller transacts with buyers who are positiqned, as wholesalers are, to assemble this type of information then demand for a factor is reduced. Similarly, a seller whc, is a wholesaler is less likely to engage a factor, although the variable indicating whether the seller is a wholesaler is of marginal significaitce. Overali, there is iittle mllinearity among the independent variables, By construction, variables describing buyer gracips are collinear since the classifications are negatively correlated. The basic finding from these variables is that sales to retailers are significantly distinct from sales to other types of buyers (whether other buyers are mass merchandisers, wholesalers, OEMs, or service firms). Sales to retailers are more likely to involve factoring than sales -“’ Recent data regardirrg the growing importance of import and export factoring are available in Cox and MacKenzie I19&46), Crirhton and Fei rier (19%) and Wulberg (1989). The estimated dollar volume of international factoring in 1992 was $1.7 billion, which is a 453% incrsase over the 1982 Cevet.Factoring is an alternative to the traditional letter of credit method of facilitating international trade. A prime mover in the continuing growth of international factoring is Factors Chain kiternational, an association of 75 member companies in 24 countries. The FCI promotes factoring by faciiirating cooperaGo among its members, sharing information, and standardizing procedures. (The Financial Times Ltd., b~mmmbnal Trade Finance, March 12, 19931. ” Reclassifying mass merchandisers as retailers does not affect the results in ‘L’ablc 3 in any substantive way, although the significance level for the variable ‘buyer is wholesaler’ dreps somewhat (f = 1.67).
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1:15
to these other groups. We also find seller size and seasonality of sales are negatively correlated, bttt, as shown in Table 3, the coefficient on seller size is substantially the same when seasonal sales is dropped from the model. None of the other correlation coefficients among independent variables is above 0.2. To the extent factors are engaged to improve cash flow and therefore do affect a firm’s cash position, it is difficult (with cross-sectional data) to determine the significance of cash flow problems as a motivating factor. Our measure of the firm’s cash flow is not statistically significant as an explanatory variable. 22Also, seasonality o_f =a=% _ 1 s does not appear to be a significant variable affecting factoring. Our data indicate factoring occurs across a broad cross-section of industries and is not limited to a short list of industries with seasonal sales. 5. Conclusions
In this paper we develop and test a model of the decision to factor trade receivables that is based on a transactions costs theory of organization. While the results of the paper pertain to one type of organizational choice, the results are encouraging since previous efforts to explain managerial and integration choices have been limited to experiences in single industries. 23 The findings here help establish generality since the results are from a broal cross-section of firms and industries. Consistent with theory, the presence of specific sunk investments in buyer-seller relationships leads to a greater likelihood that the seller will integrate credit functions. Information and monitoring costs also affect integration as do buyer characteristics. For example, buyers who are wholesalers perform, in effect, many of the same functions that a factor performs and are positioned, as a factor is, to diversify risk across customers. Hence, factoring is less likely if the buyer is a wholesaler than if the buyer is a retailer. We find that the presence of economies of scale affects the decision to integrate, as the likelihood of internalizing credit management is greater the larger the selling firm and the greater the firm’s percentage of trade credit customers. It appears that factoring is most beneficial for those sellers with geographically disperse buyers and few repeat sales to any given buyer. Factors also are beneficial to buyers who have limited information about the sellers. In these settings, by combming information across buyers and sellers, factors gain access to credit risk and product risk information at a lower cost than could indrvidual firms.
” Silverman (1962, p. 22) states that 40% of factors’ business volume comes from clients with adequate working capital funding. 22 See Anderson and Schmittlein (1984) and Monteverde and Teece (1982;. Both studies find a positive relationship between measures of asset specificity aud vertical integration.
136
LK. Smi& C. Schn:;cker JJ~umal
GfCorpomte Finance I (19941 119- I.?8
-tic-k-. ._ ._
._
._
e-3-e
II
y= -
II
!I
II
II
Christie
AA
M.P.
aml R-L..
wms,
tion 4, 141-161. Diamond, D.W., Edwards. B.. ed.. imall ~~a~a~
response
to variable
mand.
an
mrti n A p-L_‘” I_...-..1 -a3&=4!_ E..m11. LT., sixI3 1’11. C.Baa‘..;s.r. a mLl.n.w~. rl SIvulGIx a\Iu1’I,sl. VI P”.a..npM;~I LWlii~.~.~,(ll n.+ cast. I&&s& iedge, contra! and orga~~~t~~a~ structure. Jensen, MC. and W.H. Meckling. Unpublished working paper, Harvard University. Klein. B., 1980. Transaction cost determinants of ‘unfair’ contrdctuai arrangements. American Economic Kevitw, Papers and Proceedings 7010,356-362. Klein. B., R. Crawford and A. Alchian, 1975, Vertical integration, appmpriable rents and the competitive contracting process, Journal of Law and Ezmomics 21.297-326. Man. S.L. and C.W. Smith. 1992. Accounts receivable management poo&iey:Theory and ,:vidence. The Journal of Finance 47, 169-200. Monteverde. K. and D.J. Tesece. 1982. Ap~ropriab~e rents and quasi-vertical integration. Journal of Law and Economics 3, Xl-.MZ. Moskowitz. L., 1977. Dun and Bradstreet’s modern factormg and commercial finance (Dun aad Bradstreet. Toronto). Rutberg. S., 1989. Factoring husinrru heats up internationally. Secured Lender 45, 30-33. Silverman, H.R.. 1952, From cloth factor to the new force in finance Q’%~ncei
Janet tiholm
Smith ‘**, Christjahn
Schnucker
b
a Department of Economics, Arizona State Vdrersity, ‘American
Tempe, AZ 85281, USA, Express Corporation, Phoekq AZ 8SO27, USA
Winal version received November
1993)
Abstract Sellers who cxkend trade credik to their business customers choose whether to integrate the management of trade credit or to enter into specialized factoring contracts. Using original data from a broad cross-section of filins we test a model of this decision. The model is based on a theory of the firm that stresses transactions costs (including information costs) as determinants of vertical integration. Consistent with expectations, we find that specificity of assets to the buyer-seller relationship is negatively related ko the decision to factor and that factors are more likely to be used when information and monitoring costs are high.
Key WQV&:Organization; Contracting; Trade credit; Factoring JEL classification: G3; I.2
A selling firm’s decision to extend trade credit to its business customers anagealso requires the seller to decide whether to integrate into credit
* Corresponding author. Telephone: (602) 9654682; fax: (6021 9650748. We wish to thank Jim Brickley. Andrew Christie, Harold cmsetz, Ben Klein, Stuart Smith and Richard Smith for useful comments an scussion. We z&o benefited from comorkshop at Llniversity of Rochrstcr, ?!I(_ ments of seminar participants at UCLA. the Olin DuPont Seminar at RSU and the lnternational S osium on Cash, Treasury and Working Capital Management, San Francisco, 1992. Grants from the Center for Financial System Research and the College of
usiness Arizona State University. arc gratefully acknowvled:ed.
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ment. Rather than integrating, the seller can enter into a market transaction (such as a factoring contract) to arrange for a third party specialist to manage its trade credit. In factoring contracts, all credit management functions commonly are delegated to the factor. ’ In addition, the selling firm may borrow from the factor, using factored receivables to secure the loan. In this paper we view the factoring decision as a choice about organizational structure. We derive testable implications from the industrial organisaGon literature on vertical integration as developed by Coase (1937), Williamson (1975, 1979, 1981, 1985) and Klein et al. (1978), among others. This literature concerns the effects of transaction-specific investments and transactions costs (defined to include information and monitoring costs) on the choice of organizational structure. Generally, we expect to observe factoring when the level of the seller’s specialized investment in buyers is low, when the cost of monitoring buyers is high and when the cost of determining product value is high. These implications are tested with data from 770 firms competing in a variety of industries. We find that transactions costs are important determinants of the choice between integrating credit management and factoring. We also test the empirical importance of economies of scale and traditional explanations (such as seller illiquidity and seasonal sales patterns) for the decision to factor.
2. The nature of factoring contracts When a firm sells its products to a distributor or other business customer it may specify that payment is due before, on, or after delivery. If payment is not required until after delivery, the seller is extending trade credit. As such, the seller is financing the buyer’s inventory and is directly or indirectly involved in assessing and bearing credit risk, monitoring the buyer’s inventory and general financial health, and bookkeeping and collecting activiQies. These credit management functions can be performed by the seller or can be contracted entirely or partly to third parties such as credit-reporting firms, captive finance subsidiaries. collection agencies and factors. A factor com-
’ The term ‘factoring’ is derived from Latin and wac; . ::wJ historically to refer to a mercantile agent who aided iI business in its trade by buying and selling in distant lands, taking goods on czonsignmentand advancing money. In the US the first factors were British textile agents. At first they imported. stored and sold ;extiles but in the latter part of the 19th century large tariffs on imported !ex!iles caused restructuring of the industry and factors limited their services to credit management and financing. Accounts of the development of factoring appear in Silverman t IOK!). and WI C‘richton and Ferrier f I9Hf1).
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monly will perform all these activities, whereas the other choices require the seiler to integrate into some of the trade credit functions. 2 Sellers that employ factors sometimes find that borrowing from the factor compares favorably to other alternatives in terms of interest cost and flexibility, partly because the factor already is involved in managing the seller’s trade credit. Thus, it is not surprising that long-term contracts between sellers and factors commonly provide the opportunity to borrow using receivables as security. An alternative arrangement used by some sellers that provide their own credit management is to engage factors occasionally as lenders ex post to meet short-run financing needs. In these spot transactions the factor exchanges cash for the right to the seller’s receivables. This arrangement appears to be one kind of factoring relationship that has given rise to the common perception that borrowing from factors is expensive relative to alternatives. Another aspect of factoring that leads to this perception is that factored receivables frequently involve products where typical trade credit discounts for prompt payment are large (such as stylish garments) and these discounts are reflected in the implicit interest rates defined by trade credit terms. 3 Many factoring arrangements provide that the selling firm must notify the factor on a continuous basis of all sales contracts into which it intends to enter. The factor then reviews each contract and, at its discretion, makes a decision to approve or reject it. If the contract is approved, the factor becomes the owner of tne receivable from the sale. To facilitate its decision the factor has full access to the seller’s sales ledger and the experience records of each account. In some cases, the factoring contract c:>mpels the seller to disclose all information it has acquired about the buyer’s creditworthiness. 4 For approved contracts the factor assumes all credit risk without recourse. It may even in these cases, however, retain the right to collect from the seller if the buyer disputes the order and declines to pay for reasons such as unsatisfactory product quality or breach of warranty. Thus,
’ In a recent paper, Mian and Smith (1992) examine the choice among alternative accounts receivable management policies, including factoring. A number of implications they derive could not be tested by them due to limitations of their accounting-based data which tend to systematically understate the use of factoring. As discussed below, using a different data source, we find support for several of their hypotheses. 3 For examp!e. credit terms of 8/10 E.O.M. (end-of-month) are typical for firms selling Women’s Blouses and Waists, Women’s Coats and Suits, and Women’s, Misses’ and Juniors’ Dresses. The terms offer an 8% discount if the invoice is paid within 10 days; ctherwise, the full amount of the invoice is due within 30 days. If the customer fails to take the discount, then implicitly the customer is borrowing for 20 days at an effective annual interest rate of 152%. ’ For example, a standard contractual provision requires ‘disclosure of . . . all matters of fact or oninion known to be or held by the supplier . . . concerning the credit-worthiness . . . of any debtor.’
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when the seliing firm delivers a sales contract to the fiictor the contract implicitly is accompanied by the seller’s representation that the agi.eement ~,.‘a:sot ::c breached e~,~~s> a A-c tr2 t?; buyer’s financial distress (which risk is &F:: by the Cactor). In some cases the factor may deem the buyer’s credit risk to be unacceptably high, and will not approve the contract. In such case, the seller can still undertake the sale and engage the factor to finance the receivable and aid in collection if necessary. However, the credit risk is borne by the seller. In this scenario, the factor has recourse to the seller if the account goes unpaid due to financial distress of the buyer. ’ It is apparent from the above discussion that factoring relationships are complex bilateral contracts involving many separate decisions with respect to unspecified contingencies and they create the potential for opportunism. To limit the potential for opportunistic behavior by ,the selling firm the factor commonly requires an exclusive relationship and perfects a security interest in all of the receivables of the seller. Without such an arrangement the seller would have an incentive to ‘cherry pick’, leading to an adverse selection problem for the factor. In addition, since the factor supplies credit insurance, a moral hazard may arise as the seller has incentives to withhold information or provide misleading information about the buyer’s credit-worthiness in an effort to influence the factor’s decision to accepL an invoice. 5 The written contract does little to protect the seller from opportunism by the factor, often specifying no more than that the factor ‘will act in a commercially reasonable manner’ in determining whether or not to approve sale contracts. ‘Accordingly, the reputation of the factor is a critical element of the efficient functioning of factoring markets. The importance of reputation appears to explain why the principal providers of factoring services are a few well-established old-line factors, commercial banks and factoring sub-
5 Regardless of whether receivables are factored with or without recourse, payments received from the factor usually are recorded as reductions of the seller’s accounts receivable balance, despite the fact that contingent liability may remain. f-fence, the decision to factor affects the accounts receivabie and cash positions of the selling firm. This endogeneity limits the usefulness of accounting ratios as explanatory variables of the seller’s decision to factor. ’ The seller (the factor’s customer) also can behave opportunistically by seeking payment from the factor prior to the goods actually being shipped. The most prevalent form of fraud in this market is selling fictitious debt. See Crichton and Ferrier (1986). ’ A review of standard factoring agreements shows the wording ‘commercially reasonable’ frequently is omitted and instead agreements provide that the ‘Factor may in its absolute discretion reject a Deb? . . .’ or ‘The Factor shall be entitled to withdraw its approval . . . it shall be under no obligation to give a reason for so doing.’ The one-sidedness of the contract terms is consistent with Klein (1980). who argues that when both parties to a contract can cheat or hold-up the other, ‘explicit contractual restraints are often placed on the smaller, lesl, wellestablished party . . . while an implicit brand name contract-enforcement mechanism is relied on to prevent cheating by the larger, more well-established party . . .’ ip. 360).
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sidiaries of bank holding companies. s There are likely to be economies of scale associated with the factor’s brand name because the factor’s reputational capital iq put on the line with each individual sale of a client. ’ This implies, as Mein (1980) predicts, a lower cost of relying on the brand name of a large firm versus a small firm and implies one side of the contract will be relatively more incomplete. As noted, factors sometimes are engaged to provide immediate cash in exchange for receivables. This type of spot transaction does not necessarily require highly specialized industry knowledge, although the receivables must be valued. However, when a factor is employed to bear credit risk on an ongoing basis, the factor can find it advantageous to monitor both seller and buyer behavior as well as variables such as inventories, sales levels, product quality changes, etc. The highly specialized knowledge that results enables the factor to add value to transactions between market participants. As an example, possession of specialized industry knowledge can enable factors to arbitrate disputes about product quality between buyers and sellers. In this context, demand for factoring is expected to be high where sellers and buyers do not necessarily know each other’s reputations, but each is familiar with the factor. ‘” As another example, factors acquire industry-wide information that enables them to forecast industry sales. Such information can benefit individual clients by aiding them in production planning and marketing efforts. ’ ’ ’ The original American factors are referred to as old-line factors who offered a line of services that included selling, servicing of debts, collection and maintenance of customer relations. ’ The majority of factored sales in the US are handled by a small number of large factoring enterprises. Fifteen firms dominate the market that has grown steadily to levels of over $45 billion in annul-;1 factored sales. The ten largest ccmpanies hold 72% of the market. Large US factors include CIT Group, Heller Financial, Capital Factor- J, and Bank of Boston. Factoring divisions frequently are subsidiaries of financial holding companies. See Dohler, 1990, ‘The new world of factoring’, The CPA Journal, 44-48. ‘” In markets involving sales to final consumers, credit card companies and banks that issue credit cards provide services analogous to non-recourse factoring. The credit card issuer, like a factor, may supply reputational capital that facilitates a sale that is characterized by uncertainty about the seller and/or the buyer. In effect the business that accepts a credit card ‘sells’ the receivable that is created by the sale to the card issuer. Card companies also aid in redressing problems associated with unacceptable merchandise or service and billing disputes. See Edwards (1990, chap. 26) and Hart (1991, p. 3% ” See Christie ei al. (i991) who refer to this type of knowledge as ‘assembled knowledge,’ which IS produced by essembling and analyzing knowledge of particular circumstances. See also Jensen and Meckling (1990, p. 9). The importance of information acquired by a factor is illustrated when there is news that a factor has teas ;E to proLid< fi;naiYcing to a customer. For example, the refusal by Heller Financial to accept invoices from Saks Fifth Avenue in !ate .Iuly of 1991 ivas a leading indicator of Saks’ financial difficulties at the time. Sellers could then use this information to adjust marketing and sales efforts dire,cted at Saks (Business Week, Aug. 12, 1991, pp. 30-31 and Aug. 26, 1991, p. 52). As an anoth* .-example, Leslie Fay’s Chapter 11 bankruptcy filing in 1993 ws proceeded by news that Leslie Fay’s factors were refusing to buy their receivables. Apparently news of the loss of confidence by the factors led suppliers to refuse to offer trade credit to Leslie Fay (W’WD, April 6. 1993, p. 1).
I.%
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3. Determinants of the decision to factor Since Coase’s seminal work on the theory of the firm, economists have recognized that the rationale for vertical integration is found in the &sire to reduce or avoid transactions costs arising from using the price mechanism to guide resources. Using the price system is costly because information about resource values is not free. A basic tenet of Coase’s theory is that, when seieeted from among a set of alternatives, a contract is a means of mitigating information cost. 3. I. Asset specificity The decision to factor is a choice to enter into a specialized contract for trade credit management rather than to integrate the functions. Coase contends that choices like this one are made by comparing the transactions costs of contracting for performance of the functions with the costs arising from internalizing the functions within the firm. Work by Williamson (1975, 1979, 1981). Klein et al. (1978) and others suggests that the decision is determined by the nature of the transaction between seller and buyer. If the parties are required by competition to make highly specific, nonsalvageable investments in order to complete the transaction efficiently, then opportunism is more likely and hence vertical integration is more likely, ceteris paribus. As examples, the transaction may require the seller to invest in learning the production process of the buyer or to invest in specific machinery. Asset specificity creates incentives for opportunistic behavior since once an asset is specifically committed to the buyer, the seller is vulnerable to the buyer’s demands to renegotiate the terms of the original agreement, and vice versa. There is a direct connection between the presence of specific assets and the incentive of a seller to extend trade credit to buyers and to internalize credit management. The presence of specialized investments has been modeled by Smith (1987) to be a primary determinant of sellers’ decisions to offer trade credit. By offering two-part trade credit terms (such as 2/l& net 30) a seller can identify prospective defaults more quickly than if financial institutions were the sole providers of short-term financing. For example, terms of Z/10, net 30 offer the buyer a choice between a 2% discount if the invoice is paid within IO days or no discount with the full invoiced amount due in 30 days. Since the terms reflect a high implicit rate of interest, buyers who are experiencing financial difficulties and are unable to secure lower cost financing are mop f likely than others to forego the discount. Hence, the choice rev@& in’ormation to the seller concerning buyer default risk. The selling firm is alerted to this risk earlier by offering trade credit than by selling on cash terms or simple net terms. Hence, the screening process alerts the seller
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to monitor the buyer. Monitoring can indicate whether to continue to extend credit to the buyer or to modify subsequent sales contracts. Eariy information about the buyer is valuabl:: in cases where the seller hz:s made specific investments in buyers since it enables the seller to take actions to protect suck investments. I* A seller that has made specific investments is less likely to want to use a factor to provide financing, monitoring and collecting services for the account. This is because a seller who relinquishes credit management to a factor also limits the ability to preserve the value of its specialized investment by designing timely and flexible credit procedures for troubled buyers. For example, the seller may be able to preserve its investment in a long-term repeat buyer who is faced with financial difficulties by offering trade credit, monitoring the buyer, and then offering flexible payment terms if the seller can determine that the difficulties are not permanent. In contrast, forcing the buyer to accept cash only terms could cause the buyer to fail or to seek a new supplier. The presence of specific assets reduces incentives to factor for other reasons as well. The specific investment may entail, for example, significant point-of-sale effort and other types of human capita1 investment that require the salesperson to spend considerable time with an account. Under these circumstances, monitoring of the account is a by-product of the selling effort. Thus, a factor would not have access to ihe same information about the buyer’s business at the same cost as the seller. In the empirical work that follows we focus on investment in human assets (knowledgeability and ongoing relationships) which tie the selling firm to the buyer. In some industries, for example, it may be necessary for the salesperson to invest substantial time in learning the ‘ins and outs’ of the buyer’s organiz,,+ion or production technology (Anderson and Schmittlein, 1964). Indeed, some rc!ationships may become so important that the buyer exhibits loyalty to the salesperson, rather than the principal (the seller). When the level of these relationship-specific investments is high, vertical integration of trade credit management is likely. Hence the decision to factor is expected to be negatively associated with the extent to which the seller makes a specific investment in buyers as reflected by the need for salespeople to invest substantial time in their accounts.
” The information is relayed more quickly than if a financial institution were tbe lender and cash terms were imposed on the buyer. ‘The information regarding default risk is more valuable to the seller than to financial institutions, thereby providing an explanation for why sellers ge! involved in financing rather than leaving it !o financial institutions. The seiler is able to offer credit to a given risk class of buyers at lower rates than financial institutions.
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3.2 Pnfonntriiun and monitoring costs
Theory suggests information costs have an effect separate from the presence of specialized investment on the choice of whether to integrate trade predit functions. I3 In markets with imperfect information, costs will be * incurred (by the seller) to determine buyer credit-worthiness and (by the buyer) to determine the value of the goods or services to be exchanged. Diamond (1984) develops a general theory of financial intermediation based on minimizing the cost of generating and using information for monitoring. Such monitoring inform.ation is useful for resolving incentive problems between borrowers and lenders. In this context factors can be thought of as intermediaries who are delegated monitoring functions. Factors position themselves as information intermediaries and are able to supply firm-specific information to multiple users. Sellers benefit since factors can accumulate credit information on the buyers and monitor the buyers’ inventories and financial health. Buyers benefit since factors can acquire timely information on the seller’s product quality, shipment regularity, budgetary operations, etc. Diversification across buyers and sellers within an industry is valuable since the factor gains access to more and higher quality monitoring information, The factor, for example, can discern whether a particular buyer’s financial problems are industry-wide OI buyer specific. Hence, an empirical model of cross-sectional patterns of firms’ choices to factor must include variables that reflect the relative magnitudes of these monitoring/ information costs across firms and industries. ‘4 Since factors bear credit risk, the factor will seek information on the credit-worthiness of the buyers. The selling function can be related to credit functions to the extent the salespersons acquire credit information from buyers. On the one hand, sellers can possibly facilitate their factor’s approval of sales invoices if the seller can supply more complete information on credit-worthiness than the factor could obtain directly. Since this information is costly to obtain, some cost savings may be passed on to the seller in the form of lower factoring fees. However, to the extent the seller relies on its salesforce to collect this information, the value-added by a factor from its
” See Demsetz (t988) who emphasizes the important role of information costs in the theorv of the firm. He discusses how the vertical boundaries of a firm are determined by the economies of conserving expenditures on knowledge. ” In addition to the credit management functions described above, factors with specialized industry and firm knowledge sometimes perform managerial and marketing functions. For example, factors may be engaged to help with budget and sales forecasts, buying or selling partnership shares for the seller and acting as an employment agent by placing qualified employees. A factor also can be a useful reference when trying to open new accounts. See Abraham i 1?71).
J.K Smith, C. Schnucker /Journal
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127
own mformation gathering eftorts is reduced, which may lower the likelihood that a factor will be employed. We evaluate these considerations in the empirical work below. Whether the seiling firm will elect to perform its own risk assessment, monitoring and collection functions will depend on the transactions cost differences of alternative ways of organizing these functions. Other things the same, the more heterogenous the buyers in terms of iocation, the higher the costs of integrating the functions. ” These costs must be weighed against the economies of scale and scope associated with using factors, who as specialists, can develop repeat business with disperse buyers. We include a variable to measure the extent of geographic dispersion of the buyers. The expectation is that the broader the customer area, the more likely factoring will be used. More specifically, we test whether sellers with international customers are more likely to factor than sellers with exclusively domestic customers. An advantage for an exporter who uses a factor is the ability to match the payment terms of local competitors since buyers can be offered payment terms on an open account versus being asked to supply a letter of credit or satisfy other credit requirements. Demand for factors in international trade also arises from costs associated with language differences, differing legal requirements governing commercial transactions and the risk of exchange I-ate fluctuations. Another attribute of transactions that contributes to demand for factors is uncertainty as to value of the product or service underlying the transaction. Costs are incurred by both buyers and sellers to obtain such information and these costs can be substantia! when the transaction involves goods or services with highly volatile values (stylish clothes, for example, or customized services such as transportation that may have substantial value to a subset of buyers but not alE buyers). These information costs can give rise to demand for a factor who acts as a middleman in determining whether a sales contract ought to be entered into, and who monitors the status of the receivable and arranges for resale of goods if they must be repossessed. A specialist is likely to arise when the repeat sales frequency of the seller with a given buyer is low but across a group of buyers is high. Under these conditions factoring can reduce the costs of credit extension tc the extent the buyer developmsa stronger business relationship with the factor than with individual sellers. ‘We include a variable to measure the likely extent of uncertainty surrounding value of the product line. The more customized the product line, the greater the expected information costs concerning valne. A positive sign
” Stigler (1968) predicts a relationship between the functional slructure of an industry and its geographical structure. Histcrical accounts suggest geographical dispersion of buyers and distance beween seller and buyer location played an important role in the development of the factoring industry. See Abraham (19711.
128
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on the variable would indicate that the decision to engage a factor is influenced by demand for reducing asset value uncertainty. 3.3. Dtstribu tion characteristics As recognized by Mian and Smith (1992), many of the same functions that factors perform also can be performed by other intermediaries such as wholesalers. Hence we include variables to reflect the nature of the buyers’ economic functions. The distribution channel affects the credit extension process in several ways. It can affect (and reflect) the level of asset specificity in the transaction and can affect the information costs of va!uing the traded assets and costs of recovering assets if sales contracts are breached. To evaluate the importance of the buyer’s attributes in the seller’s decision to factor we include four categories of dummy variables to classify customer types: 1. The firm sells to original equipment manufacturers or serr+ce-proGders. Since these buyers consume the purchased input in their production processes, the value of the input as collateral is low or nonexistent and hence factoring is less likely. 2. The firm sells to wholesalers. Introduction of a wholesaler between manufacturer and retailer affects the credit-extension process in some of the same ways a factor does, making factoring less likely. Thus, selling to a wholesaler who offers trade credit to retailers (and who manages the trade credit) is a substitute for selling to retailers directly and factoring the receivables. Mass merchandisers are included in this category since they have integrated the wholesaling function. 3. The firm sells to retailers. It is expected that trade credit is more likely to be extended and that factoring of receivables is more likely when selling to retailers than for the above two categories of buyers since these buyers either provide substitute services for factors or make factoring costly for the sellers. 4. Other. A control category is included for those sellers who do not identify a primary customer type. In the regression models presented below the omitted category is retailers. Hence the estimated coefficients test whether each customer type produces effects that are different from those of a firm primarily selling to retailers. The expected coefficients for the first two dummy variables are negative and we have no a priori expectation for the control variable. We also include a dummy variable to indicate whether the seller is a wholesaler. As an intermediary, the wholesaler is likely to devzkb:, specialized knowledge in both buyers and suppliers and to realize the information monitoring benefits described by Diamond. Thus, wholesalers are more likely, other things constant, to internalize trade credit functions.
J.K. Smith, C. Schnucker /Journal of Corporate Finance I (1994) 119-138
129
3.4. Economies of size in credit management
Firm size also is expected to affect the decision. The fixed costs associated with credit management will be spread over more customers as the firm’s customer-base expands and as the proportion of sales made on credit increases. If few sales are made on credit it becomes more economical for the firm to delegate credit functions to a factor. We include two variables to measure economies of scale-firm size (measured as the log of the seller’s total assets) and the percentage of the seller’s customers to whom trade credit is offered. The expected impacts of these scale variables on the use of factoring are negative. 3.5. Traditional explanations for factors A common perception is that factors are predominantly used by firms with cash flow management problems such as firms with seasonal sales. Traditional measures of firm liquidity cannot be used in the regression. These measures are affected by accounts receivable, cash, and short term liabilities, all of which depend on the factoring choice, making the traditional liquidity measures endogenous. Instead, we measure liquidity using a proxy for the seller’s cash flow-net income plus depreciation, standardized by total assets. Nonetheless, to the extent the decision to factor improves a firm’s cash flow, we will not be able to discern an impact of this variable. To determine if seasonality of sales is important in explaining factoring, we include a variable that measures how frequently a typical buyer places orders and expect factoring to be more likely the less frequentiy orders occur. l6 4. Empirics The data used to examine the testable implications are compiled from two sources. The primary source is a large-scale mail survey of credit managers of firms throughout the US. Second, each company’s response is matched with financial data from Compustat. To be included in the study the firm must have a Compustat record and report a single four-digit SIC code. The latter screen is used to minimize problems associated with multi-product firms that may have credit policies that vary across product lines. The survey instrument was designed to obtain information on individual seller credit terms and policies from a broad cross-section of firms and industries. The questions ” Emery (1987) develops a theory of trade credit based on its use as a financial response to deterministic variations in demand. Following this reasoning, factoring of credit functions may be more likely if sales are seasonal to the extent the factor can diversify across sellers with variable demand and thereby provide the services at lower cost than could sellers.
130
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Table 1 Descriptive statistics on factoring choices and trade credit choices by industry cross-sectional sample of 770 public firms surveyed in 1991 lndustry category a
Two-digit SIC
Mining
IO-14
Manufacturing Food and tobacco products Textiles and apparel Lumber. wood and furniture Paper, printing Chemicals, petroleum Rubber and leather prodllcts Stone, glass and metal Industrial machinery Electronic and transport equip. instruments and misc.
Number of firms
grouping
Percent of firms that factor
Percent of customers offered trade credit
29
17.2
67.2
20-21 22-23 24-25 26-27 28-29 30-3 1 32-34 35 36-37 38-39
43 28 20 30 67 24 50 117 126 119
X8.6 21.4 25.0 16.7 17.9 20. I 10.0 22.2 22.2 17.6
Total manufacturing
20--39
624
19.4
78.0
Transportation
40-49
49
30.6
65.n
50-5 1
55
12.7
80.3
misc.
13
7.7
89.0
770
19.4
77.1
and communication
Wholesale trade Agriculture. All
construction
and other
for a
a Firms are classified by SIC code groupings of primary product lines as reported on Compustat, and verified by survey respondents. Firms with SIC codes OIOO-5199 were surveyed.
elicit data not only on selling firm attributes and product line characteristics, but also on buyer attributes and the nature of the seller’s relationship with buyers. The instrument was pretested and the survey was conducted in early 1991. A second mailing was made to reach non-respondents. The response rate of 39% is typical of surveys of large public corporations. Statistics describing industrial representation appear in Table 1 for the 770 firms in the sample that offer trade credit. The table shows that 19% of the firms use factors. While textiles, apparel and related industries do rely heavily on factoring, factoring has expanded outside these traditionai industries. ” The highest percentage of use occurs in the transportation and
” The data verify that factoring still occurs in industries that historically have used factors such as textiles. furniture. toys, shoes, plastics and electronics but also occurs in such vcried industries as petroleum products, computer hardware and peripherals, auto parts and accessories, pharmaceuticals, telecommunications equipment, surgical and dental equipment, food products, publishing and transportation.
J.K. Smith, C. Schnucker /Joumal
of Corporate
Finance
I (1994)
119-138
131
Table 2 Means and standard deviations ef explanatory variables
Percent of buyers offered trade credit Seller’s size (log of total assets) Specialized investment made by seller a Buyer consumes product/service as input (OEMs) (0 = no; 1 = yes) Buyer is wholesaler (0 = no; 1 = yes) Buyer type not identified (0 = no; I = yes) Seller is whoies?ler (0 = no; 1 = yes) Product line is customized a Geographic dispersion of buyers ’ Credit information obtained by salespersons a Sales are seasonal a Seller’s cash flow/total assets a Responses are based on an anchored-five-point
Mean
Standard deviation
77 3.70 1.98 0.61
22.60 2.1c 1.01 0.49
0.38
0.49
0.07
0.25
0.07
0.26
2.84 0.67 2.85 2.74 0.12
1.34 0.47 1.35 1.19 0.08
scale as described in the Appendix.
manufacturing sectors. As documented below, factors are used extensively in international trade; of the firms in our sample that engage factors, 67% have international customers. Table 2 contains summary statistics for the variables used in the study. Variable definitions, relevant survey questions, and data sources are reported in the Appendix. The dependent variable is the decision to use a factor and equals 1 if the firm uses a factor to manage receivables and 0 otherwise. Since the dependent variable is binary, a linear probability model would result in heteroscedasticity of the error term and could yield predictions which lie outside the (0, 1) interval. To address these concerns a probit model is used which transforms the dependent variable so that predictions lie in the (0, 1) interval. The transformation is based on the cumulative normal probability function. Assume there is an underlying index, Zi, which represents the ‘propensity’ of a firm to use a factor and which is a linear function of the independent variables we have identified. Observations on Zi are not observable; instead we observe only whether an individual firm is in one category (high value of Zi) or another (low level of Zj). Let Zi equal the critical cutoff value that determines whether a firm uses a factor or not. The probit model assumes Zi* is a normally distributed random variable so that the probability that ZT < Z; can be determined from the cumulative normal probability function. The standardized function is Pi = F( Zi) =
&_/f’CceeS2i2ds,
132
J-K Smith, C. Schnucker
/Journal
of Corporate
Furance I (1994) 119-138
where s is a normally distributed random variable with mean zero and unit variance. Hence F;, the probability that the firm uses a factor, lies in the (0, 1) interval and Pi is larger the larger is the value of Z;. The srobabiiity, Pi, that results from the mode1 is an estimate of the conditional probability that firm i will use a factor, given the values of the independent variables. 4.1. Empitid
resu!ts
Table 3 contains results of two empirical models. Eq. (1) includes all the explanatory variables discussed above. The results show that the percentage of trade credit customers, transactions cost variables, and variables describing distribution channels provide significant explanatory power. However, seasonal&y of sales, firm size and the firm’s cash flow do not appear to be significant determinants of factoring. ” The presence of economies of scale in the management of trade credit is indicated by the negative relationship between factoring and percent of customers offered trade credit. Absolute firm size is not a significant variable, which suggests that economies arise not so much from the volume of business as from the proportion of transactions that involve credit extensions. Equation (2) is included to test whether a mode1 that includes transactions cost vdiiables does a significantly better job explaining factoring than does a simple mode1 of integration based on scale economies. We compare the -9uimized likelihood functions of the two models and logarithm of the .._.____ generate a likelihood ratio test statistic. The null hypothesis, that p = 0 for all other independent variables in model (1) is rejected at the 0.05 level. I9 The results show that the measure of relationship-specific capital is associated with a greater likelihood of integration of trade credit management. To the extent the selling firm makes specialized investments in the buyer, the investment has no alternative use value. The presence of this investment ties the two firms together. These conditions make short-term (spot market) contracts between buyer and seller inefficient and make long-term, flexib!e relationships more likely. The prediction in our case is that management of debt arising from such transactions will be internalized by the seiler to provide the seller flexibility in protecting the return on the specific investment. The effect of a one-standard deviation increase in the value of this response above from the mean response is a 2.6% decrease in the probability that a factor will be engaged. The results show factoring is more likely if the product line is customized and hence costlier to value. These valuation costs give rise to demand for a Ix We also estimated the two equations using the sample of manufacturing firms only. Coefficient estimates are not materially different from those shown in Table 3. “) The siatistic c is distributed x2 with 10 degrees of freedom. We find c = 2(362.4+372.3) 19.8. The critical value for significance at the 0.05 level is 18.3.
=
J.K Smith. C. Schnucker /Journal
ojCorporate Finance
I (1994) 119-138
Table 3 Probit estimates of sellers’ decisions to factor a Independent
variables
(2) - 0.593
Ecottomies of size variables Percent of buyers offered trade credit Seller’s size (log of total assets) Transactions costs vanahles Specialized investment made by seller Buyer consumes product/service
as input IBEMs)
Buyer is wholesaler Buyer type not identified Seller is wholesaler Product line is customized Geographic
.I (1)
Constant
dispersian
Credit information
of buyers
olltained bysalespersons
Traditiortalexpianatory t~arirrhles Sales are seasonal Seller’s cash flow
133
- 0.877
-0.151 (-2.985) *** - 0.086 ( - 1.277)
-- 0.104 (-- 1.922) - 0.346 t-23671 . . - 0.324 ( - 2.3&J - 0.562 (- 2.132: - 0.307 f - 1.297) 0.103 (1.842) 0.149 (1.255) 0.071 (1.280)
-0.151 t-3.085) *** - 0.083 (- I.3121
* ** ** **
**
- 0.068 (- 1.167) 0.006
(0.008) Log likelihood
- 362.41
***
- 372.33 * * *
a The sample includes 770 firms surveyed in 1991. The dependent variable equals 1 if the firm uses a factor and equals 0 otherwise. Variable definitions and data sources appear in the Appendix, t-ratios, based on two-tailed tests, appear in parentheses below each coefficient. * * * = significant at the 0.01 level, ** = significant at the 0.05 level, * = significant at the 0.10 level.
specialist who has expertise in valuing receivables arising from sakes of suck products and the benefits derived from the specialist outweigh the costs associated with collateralization. The coefficient implies that a response to this question that is one standard deviation above the mean response is associated with a 4% higher probability that a firm wi!! engage a factor. When 3 seller transacts with distantly located firms, information costs and monitoring costs are expected to be higher than if the buyers are nearby. Consistent with this we find sellers with internatiova! customers are more
134
likely
IX
Smirh, C. Sckwcker /hmai
ofCorporate Finance
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to use factors than those with only domestic customers, however. the
relationship is only marginally significant. to the variab?e measuring the extent to which the seller’s salesforce acquires i&mnatisn akmt the buyer’s credit-worthiness is only marginally significant, although the sign is positive, suggesting factoring is more likely when sellers .-a EfimP -a*.= r@Q~~~+~ .r.q.W~Wac8en+ln PUS1‘I&. acsumulate credit information, on their customercV.Im relationship is surprising since factors also produce credit information and may be viewed as a substitute service. However, since the seller’s invoices and credit limits for buyers must be approved by the factor, such approval may be facilitated at lower cost if the salesperson produces some of this information. Also, if the factor does not approve the invoice the seller can still make the sale (with factor recourse) and this decision is aided by acquisition of credit information. ThG three variables describing the buyers are all statistically significant. ~?Ils!!Te,CX;: with Wan and Smith’s prediction, seCling to wholesalers or origina! equipment manufacturers lowers the likelihmd of factoring relative to selling to a retailer. ” if the buyer is a wholesaler, the probabiiity of factoring is reduced by 7%. If the buyer is an OEM or service provider, the probability of factoring is reduced by 8%. The results are consistent with the idea that a factor adds value to transactions by aggregating or assembling sales data that can be useful to buyers in discerning demand and cost trends. If the seller transacts with buyers who are positiqned, as wholesalers are, to assemble this type of information then demand for a factor is reduced. Similarly, a seller whc, is a wholesaler is less likely to engage a factor, although the variable indicating whether the seller is a wholesaler is of marginal significaitce. Overali, there is iittle mllinearity among the independent variables, By construction, variables describing buyer gracips are collinear since the classifications are negatively correlated. The basic finding from these variables is that sales to retailers are significantly distinct from sales to other types of buyers (whether other buyers are mass merchandisers, wholesalers, OEMs, or service firms). Sales to retailers are more likely to involve factoring than sales -“’ Recent data regardirrg the growing importance of import and export factoring are available in Cox and MacKenzie I19&46), Crirhton and Fei rier (19%) and Wulberg (1989). The estimated dollar volume of international factoring in 1992 was $1.7 billion, which is a 453% incrsase over the 1982 Cevet.Factoring is an alternative to the traditional letter of credit method of facilitating international trade. A prime mover in the continuing growth of international factoring is Factors Chain kiternational, an association of 75 member companies in 24 countries. The FCI promotes factoring by faciiirating cooperaGo among its members, sharing information, and standardizing procedures. (The Financial Times Ltd., b~mmmbnal Trade Finance, March 12, 19931. ” Reclassifying mass merchandisers as retailers does not affect the results in ‘L’ablc 3 in any substantive way, although the significance level for the variable ‘buyer is wholesaler’ dreps somewhat (f = 1.67).
SK Smieh. C. Schnucker /Jmrnal
of Corporate Fininonce1 (1994) 119-138
1:15
to these other groups. We also find seller size and seasonality of sales are negatively correlated, bttt, as shown in Table 3, the coefficient on seller size is substantially the same when seasonal sales is dropped from the model. None of the other correlation coefficients among independent variables is above 0.2. To the extent factors are engaged to improve cash flow and therefore do affect a firm’s cash position, it is difficult (with cross-sectional data) to determine the significance of cash flow problems as a motivating factor. Our measure of the firm’s cash flow is not statistically significant as an explanatory variable. 22Also, seasonality o_f =a=% _ 1 s does not appear to be a significant variable affecting factoring. Our data indicate factoring occurs across a broad cross-section of industries and is not limited to a short list of industries with seasonal sales. 5. Conclusions
In this paper we develop and test a model of the decision to factor trade receivables that is based on a transactions costs theory of organization. While the results of the paper pertain to one type of organizational choice, the results are encouraging since previous efforts to explain managerial and integration choices have been limited to experiences in single industries. 23 The findings here help establish generality since the results are from a broal cross-section of firms and industries. Consistent with theory, the presence of specific sunk investments in buyer-seller relationships leads to a greater likelihood that the seller will integrate credit functions. Information and monitoring costs also affect integration as do buyer characteristics. For example, buyers who are wholesalers perform, in effect, many of the same functions that a factor performs and are positioned, as a factor is, to diversify risk across customers. Hence, factoring is less likely if the buyer is a wholesaler than if the buyer is a retailer. We find that the presence of economies of scale affects the decision to integrate, as the likelihood of internalizing credit management is greater the larger the selling firm and the greater the firm’s percentage of trade credit customers. It appears that factoring is most beneficial for those sellers with geographically disperse buyers and few repeat sales to any given buyer. Factors also are beneficial to buyers who have limited information about the sellers. In these settings, by combming information across buyers and sellers, factors gain access to credit risk and product risk information at a lower cost than could indrvidual firms.
” Silverman (1962, p. 22) states that 40% of factors’ business volume comes from clients with adequate working capital funding. 22 See Anderson and Schmittlein (1984) and Monteverde and Teece (1982;. Both studies find a positive relationship between measures of asset specificity aud vertical integration.
136
LK. Smi& C. Schn:;cker JJ~umal
GfCorpomte Finance I (19941 119- I.?8
-tic-k-. ._ ._
._
._
e-3-e
II
y= -
II
!I
II
II
Christie
AA
M.P.
aml R-L..
wms,
tion 4, 141-161. Diamond, D.W., Edwards. B.. ed.. imall ~~a~a~
response
to variable
mand.
an
mrti n A p-L_‘” I_...-..1 -a3&=4!_ E..m11. LT., sixI3 1’11. C.Baa‘..;s.r. a mLl.n.w~. rl SIvulGIx a\Iu1’I,sl. VI P”.a..npM;~I LWlii~.~.~,(ll n.+ cast. I&&s& iedge, contra! and orga~~~t~~a~ structure. Jensen, MC. and W.H. Meckling. Unpublished working paper, Harvard University. Klein. B., 1980. Transaction cost determinants of ‘unfair’ contrdctuai arrangements. American Economic Kevitw, Papers and Proceedings 7010,356-362. Klein. B., R. Crawford and A. Alchian, 1975, Vertical integration, appmpriable rents and the competitive contracting process, Journal of Law and Ezmomics 21.297-326. Man. S.L. and C.W. Smith. 1992. Accounts receivable management poo&iey:Theory and ,:vidence. The Journal of Finance 47, 169-200. Monteverde. K. and D.J. Tesece. 1982. Ap~ropriab~e rents and quasi-vertical integration. Journal of Law and Economics 3, Xl-.MZ. Moskowitz. L., 1977. Dun and Bradstreet’s modern factormg and commercial finance (Dun aad Bradstreet. Toronto). Rutberg. S., 1989. Factoring husinrru heats up internationally. Secured Lender 45, 30-33. Silverman, H.R.. 1952, From cloth factor to the new force in finance Q’%~ncei