An Empirical Analysis of Property- Liability Insurance Distribution Systems: Market Shares Across Lines of Business

Transcription

1 An Empirical Analysis of Property- Liability Insurance Distribution Systems: Market Shares Across Lines of Business Laureen Regan * Abstract: Tobit regression is used to analyze market shares for a cross section of 273 insurers operating in Lines of business analyzed include personal auto liability and physical damage insurance, homeowners multiperil, commercial general liability, workers compensation, and commercial multiperil. After controlling for size and other factors, evidence indicates that direct writing insurers have consistently higher market shares in personal auto insurance, while independent agency insurers have higher shares in general liability. However, controlling for expense ratio, there is no significant difference in market shares for homeowners, commercial multiperil, or workers compensation across insurers using different distribution systems. P INTRODUCTION roperty-liability insurance firms use a wide variety of distribution systems, with some firms using exclusive dealing arrangements and others contracting the sales function out to independent agents who have ownership rights in the client list and represent a number of competing insurers. Insurers who deal exclusively include those that distribute through autonomous agents who represent one insurer, insurers that use salaried employees rather than contractors, and direct contact insurers, which use mass merchandising methods to distribute products. Under exclusive dealing, the insurer retains the rights to the customer list and captures the residual profits arising from the insurance transaction. * Laureen Regan is an assistant professor in the Department of Risk Management and Insurance at Temple University. 151 Journal of Insurance Issues, 1998, 21, 2, pp Copyright 1998 by the Western Risk and Insurance Association. All rights reserved.

2 152 LAUREEN REGAN Prior research suggests that insurers who rely on the independent agency system are characterized by higher expense ratios than are exclusive dealing insurers (Joskow, 1973; Cummins and VanDerhei, 1979; Flanigan et al., 1979; Barrese and Nelson, 1992; Flanigan et al., 1993). In fact, the independent agency system has lost market share over the past two decades, particularly in personal lines. In 1978, independent agency insurers controlled percent of the market, with a 45.4 percent share of personal lines. 1 By 1996, market shares declined to 51.2 percent overall and just 32.3 percent of personal lines. However, over the same time period, the independent agency share of commercial lines remained relatively stable, with shares declining from percent in 1978 to 71.6 percent in The interesting question is how independent agency insurers continue to survive and even dominate in commercial lines despite higher expense ratios. One argument is that independent agency is associated with higher levels of service. However, support for this hypothesis is mixed (see, for example, Etgar, 1976; Cummins and Weisbart, 1977; Doerpinghaus, 1991; Barrese et al., 1995). An alternative branch of research suggests that independent agency insurers have advantages over exclusive dealers for some environments (Marvel, 1982; Grossman and Hart, 1986; Cummins and Weiss, 1992; Regan and Tennyson, 1996; Regan, 1997). The common thread throughout these latter studies is that independent agency should succeed in lines of business that are more complex, while exclusive dealing insurers should be more effective in more standardized personal lines. This is the hypothesis of interest in this paper. This hypothesis is tested by examining the pattern of market shares across lines of business using both aggregate data and regression analysis of company-level data. Strong support is found for the idea that direct writers are more concentrated in personal lines, while independent agency is more important in commercial lines. The paper proceeds as follows. Section 2 discusses the existing studies that argue for an advantage to independent agency. Section 3 presents the empirical methodology and discusses the results, and Section 4 concludes. THEORETICAL FOUNDATION The principal distinction between independent agency and exclusive dealing arrangements is the agent s ownership rights to the customer list under independent agency. Agency ownership of the list means that the insurer may not solicit an independent agent s client directly, nor may an agent s client be unilaterally reassigned by the insurer. The agent, however, has the unrestricted legal right to place business with a number of compet-

3 PROPERTY-LIABILITY INSURANCE DISTRIBUTION SYSTEMS 153 ing insurers. It is argued that this contractual relationship imposes costs on insurers because the agent can command higher compensation by threatening to move customers (Grossman and Hart, 1986; D Arcy and Doherty, 1990). However, several researchers have argued that the advantages of independent agency can outweigh the costs, particularly for complex lines of business. These studies typically focus on agency or transaction cost theories to support the coexistence of both independent agency and exclusive dealing. Agency theory arguments center on the independent agent s superior ability to intervene in conflicts between the policyholder and insurer. The ownership of the expirations list allows the agent to credibly threaten to move her portfolio of business if the conflict is not resolved in the policyholder s favor. This conflict resolution service is argued to be relatively more important in complex lines of business, because conflicts are more likely, as well as more costly, than for more standardized lines (Mayers and Smith, 1988; Barrese and Nelson, 1992; Cummins and Weiss, 1992). Both Marvel (1982) and Grossman and Hart (1986) argue that the choice of exclusive dealing versus independent agency relies on the relative importance of efforts to attract and maintain clients. If the advertising or service efforts of the insurer are more important, then exclusive dealing should be used, because exclusive dealing prevents the agent from freeriding on the investments of the insurer. Alternatively, when the efforts of the agent in attracting and retaining clients are more important, then independent agency should be used. The implication of these arguments is that insurer investments are more important for more standardized lines of business. Thus, exclusive dealing should prevail in personal rather than commercial lines of business. Regan and Tennyson (1996) offer an alternative theory, arguing that independent agency adds value when agent participation in risk classification is more important. Since risk classification is an important determinant of insurer profitability, insurers may rely on agents to provide supplementary, subjective information about applicant risk type that would be costly for the insurer to verify. 2 Under independent agency, the agent can recover the cost of her effort in gathering this information, even if the applicant is rejected by the initial insurer, by placing the risk with a competing insurer. This option is not open to exclusive dealing agents. Moreover, since insurers can develop standardized risk assessment tools for relatively less complex lines of business, agent participation in risk assessment is less valuable for these lines. Regan (1997) adds an additional argument. Because independent agents represent several insurers, any adverse experience with a particular

4 154 LAUREEN REGAN line or market can be diversified across the agent s entire portfolio of insurers and lines. Since the tied agent s revenue is directly linked to the experience of a single insurer under exclusive dealing, tied agents would demand a relatively higher payment for bearing the risk associated with adverse loss experience in a line. Thus, exclusive dealing insurers should focus on less complex lines and markets. While each of these studies argues for an advantage to independent agency in complex lines and direct writing in standardized personal lines, 3 direct empirical tests of the hypothesis are lacking. The work of Cummins and Weiss (1992) documents aggregate market shares across lines of business for alternative distribution systems, but does not control for other factors that might influence market shares. While the analysis of Barrese and Nelson (1992) makes an argument for the advantages of independent agency, it focuses on aggregate firm level expense ratios rather than market shares, with no analysis on a line of business basis. Regan (1997) performs logistic regression on the choice of distribution systems and finds that independent agency insurers are characterized by a significantly higher proportion of business in complex lines. While Marvel does measure aggregate independent agency market share across lines, market share is related to commission levels and advertising expenses. Similarly, Regan and Tennyson (1996) measure direct writer market shares across states, not firms, and find that direct writers are more common in less complex underwriting environments. The contribution of the current paper is to directly test the association between insurance distribution system and market share by line of business for a cross section of insurers. This test has not appeared in the literature previously, and adds additional insight into the determinants of insurer market shares. Other factors that might have an impact on market share are controlled for to focus on the relationship between market share and distribution systems. EMPIRICAL ANALYSIS This study tests the hypothesis that the independent agency system will be more common in nonstandard, complex lines of business. An examination of aggregate market shares by line of business supports this idea. The personal lines of business used in this analysis are private passenger auto physical damage, private passenger auto liability, and homeowners multiperil. Private passenger auto liability and physical damage insurance are separate lines of business, but are usually sold together. Homeowners multiperil is also marketed to individuals, and it provides

5 PROPERTY-LIABILITY INSURANCE DISTRIBUTION SYSTEMS 155 coverage for residential property damage and any liability claims against the insured that do not arise out of a commercial relationship or out of the operation of a motor vehicle. Insurers often offer multiple-product discounts to policyholders who purchase homeowners and auto insurance together, so that there is likely to be some correlation across market shares in these lines. The commercial lines include commercial multiperil, workers compensation, commercial general liability, fire, ocean marine, boiler and machinery, and commercial auto insurance. Commercial multiperil is similar to homeowners and is marketed primarily to smaller businesses. Workers compensation provides no-fault coverage for employers when employees are injured within the scope of employment. Commercial general liability covers many sources of third party liability and includes two particularly problematic coverages products liability and environmental impairment liability. Products and environmental liability are very longtailed lines of business and are subject to frequently changing regulatory and judicial standards. Thus, an insurer offering commercial general liability products faces a much more difficult underwriting and claims environment than one offering only auto physical damage coverage. Commercial multiperil, workers compensation, and general liability are the largest of the commercial lines in terms of premiums written. Fire insurance is a first party named perils property coverage, while ocean marine covers ocean-going ships and their cargo. Boiler and machinery insurance covers both direct and indirect losses caused by boiler and machinery damage and is characterized by intensive loss control activities. Finally, commercial auto insurance includes both property and liability coverage for owners and operators of commercial vehicles. Table 1 indicates the change in market shares across time by distribution system for these individual lines of insurance. The results of Table 1 provide support for the hypothesis that independent agency dominates in more complex lines. It is clear from the table that exclusive dealing insurers have captured the majority of the market for personal lines, with shares for independent agency declining consistently across time. 4 While independent agency remains the dominant distribution system for every commercial line shown, exclusive dealers have made slow gains in commercial multiperil and ocean marine insurance. However, independent agency has increased its share of the market in workers compensation, general liability, boiler and machinery, and commercial auto insurance over this time period. Since Table 1 examines aggregate market shares only, the results are consistent with several very large or many small independent agency (direct writer) insurers dominating commercial (personal) lines. It is not

6 156 LAUREEN REGAN Table 1. Changes in Independent Agency Market Shares by Lines of Business (in percent) a Line Private Passenger Auto Damage Private Passenger Auto Liability Homeowners Multiperil Commercial Multiperil Workers Compensation General Liability Commercial Auto Fire Ocean Marine Boiler and Machinery All Lines a Note that market shares are calculated on the basis of net premiums written. Data are from Best s Aggregates and Averages, 1981 through 1995 editions. possible to distinguish the allocation of market shares across individual insurers at this level, nor does this analysis control for other factors that might influence market shares across insurers. To investigate this further, a regression analysis of market shares is undertaken to control for other possible influences. The measure of market share used here is the firm s share of total net premiums written in a line compared to the market as a whole. Premiums are adjusted by dividends paid to policyholders because some firms charge premiums in excess of expected costs in the expectation of returning dividends to policyholders. Therefore, using the unadjusted premium measure would lead to inflated estimates of market share for some firms. Data and Methodology Market shares are analyzed for a cross section of insurers operating in the market in 1990 for personal auto liability, auto physical damage, and homeowners insurance, as well as commercial multiperil, workers compensation, and general liability insurance. These six lines were chosen because they provide a broad comparison across personal and commercial lines and because they are the largest lines in terms of premiums written, together accounting for approximately 70% of the market. Controlling for other factors, it is expected that independent agency firms will allocate

7 PROPERTY-LIABILITY INSURANCE DISTRIBUTION SYSTEMS 157 more of their underwriting capacity to commercial general liability, workers compensation, and commercial multiperil, and direct writers will concentrate more in the personal lines. This hypothesis is tested using accounting data gathered from publications of the A.M. Best Company. Four hundred groups and unaffiliated insurers operating in 1990 were initially chosen. After the elimination of reinsurers, risk retention groups, and firms that had incomplete information, 273 firms remained. 5 The primary predictive variable of interest is the distribution system of the insurer. Because of the importance of the allocation of the ownership rights to the list on the incentives of agents to perform certain tasks, firms are classified as either independent agency or exclusive dealers, according to the classification system used by A.M. Best. 6 Thus, both brokers and independent agency insurers are classified as independent agency, while exclusive agency, direct writing, and mass merchandising insurers are classified as exclusive dealers. In more complex lines, independent agency insurers are expected to have higher market shares, while exclusive dealers are expected to have higher shares in personal lines. To capture this effect, a dummy variable is used that takes on the value of 1 if the firm is an independent agency insurer, and 0 otherwise [Agency]. Other researchers have argued that there exists a relationship between a firm s level of risk, line of business choice, and ownership form. Mayers and Smith (1988) argue that stock insurers should be more prevalent in risky or complex lines because managers are given more discretion in stock than are mutual insurers. In addition, stock insurers have an advantage over mutuals in raising capital, which is more valuable for more complex or risky lines of business. They further argue that the independent agency system offers advantages in limiting agency conflicts that might arise when managerial discretion is higher that is, in stock firms. These conflicts might be more important for complex lines (see also Barrese and Nelson, 1992; Cummins and Weiss, 1992; Regan, 1997). A dummy variable is included to control for alternative ownership forms within this industry. This variable is equal to 1 if the firm is classified as a stock insurer, and 0 otherwise [Stock]. Independent agency should also have an advantage over exclusive dealing when the insurer is exposed to higher levels of underlying risk, because the multiple placement opportunities available to independent agents allow the agent to diversify her portfolio both across insurers and across lines of business. Further, since independent agents participate in the profitability of business underwritten through profit-contingent commission arrangements, an adverse shock that reduces insurer profitability can be partially absorbed by the distribution system (Cather, 1994; Regan,

8 158 LAUREEN REGAN 1997). However, a riskier firm might be preferred to a less risky firm by some buyers if the increased risk is accompanied by a lower price. To control for this, underwriting risk is measured by the coefficient of variation of the ratio of losses incurred to net premiums. Because the coefficient of variation adjusts for differences in means across insurers, this measures the relative risk of the firm s underwriting portfolio in a particular line, rather than the absolute level. A firm with a higher coefficient of variation thus has a riskier underwriting portfolio [Cvlr]. A further control for differential risk across firms is also included in the analysis. In addition to underwriting risk, firms are exposed to the possibility of insolvency through unexpected shocks in the financial environment. Because independent agents represent several insurers, they can diversify this risk more effectively than can exclusive dealers. The assetsto-liabilities ratio, which is similar to the measure of leverage commonly used in non-financial firms, is included to capture this effect. As assets increase or liabilities decrease, this ratio increases, and the insurer becomes relatively more safe 7 [Leverage]. Advertising is designed to generate market share for a firm. Thus, advertising should be an important determinant of market share. Advertising expenditures are likely to be more important for direct writer insurers because these investments cannot be expropriated at the agency level. Also, since advertising cannot carry enough information to allow comparisons of complex products, advertising is likely to be more prevalent in personal lines (Marvel, 1982; Grossman and Hart, 1986; Regan, 1997). Since advertising is typically undertaken at the firm level, with effects dispersed over all lines of business of the firm, advertising is measured as the ratio of advertising expenditures to net premiums written [Advertising]. In a competitive market, market share should also be influenced by price. One measure of the price of an insurance product is the inverse of the loss ratio. Premiums are received by the insurer in exchange for the promise to pay future losses arising under the contract. Therefore, the premium-to-loss ratio measures the price relative to the value received and is expected to be inversely related to market share. However, since insurance products are not necessarily homogeneous within lines, it might be that a higher price reflects differences in the types of products being sold. Given this, it is possible that higher prices do not decrease market shares [Price]. The firm s expense ratio is included to control for systematic differences in the relative acquisition costs on market shares. This is important if higher expense ratios result in significantly lower market shares for independent agency insurers. The expense ratio is measured as the ratio of

9 PROPERTY-LIABILITY INSURANCE DISTRIBUTION SYSTEMS 159 underwriting expenses to premiums written net of reinsurance transactions [Expense Ratio]. The reputation of a firm may be an important factor in generating market share. Some personal and large commercial buyers will not purchase from a low-rated carrier. A dummy variable based on the firm s A.M. Best rating is included to account for the effect of differences in quality on insurer market share. The variable takes on a value of 1 if the firm is rated A+ by the A.M. Best Company, and 0 otherwise 8 [Quality]. Since the sample consists of both group and single insurers, a dummy variable that is set equal to 1 if the firm is a group and 0 otherwise is also included in the analysis [Group]. Also, most firms rely on access to reinsurance markets to underwrite certain types of business. A firm s reinsurance activity can affect its overall market share because reinsurance allows a firm to write more business than it could otherwise. This is controlled for by including a variable measuring reinsurance activity, the ratio of net to direct premiums written [Retention]. Finally, it is likely that larger insurers have higher market shares in most lines of business compared to smaller insurers, all else equal. The insurers included in this study span a wide range of size. The largest insurer had assets in 1990 of more than $44.7 billion, while the smallest insurer s assets were just over $4.7 million. 9 In terms of net premiums written, insurer size ranges from $1.6 million to $24 billion. Several variables to control for firm size were considered, including assets and output measures such as premiums written or losses incurred. However, these are so highly correlated with market share, particularly for the personal lines of insurance in this study, that their use would introduce serious bias into the estimation. Therefore, the size effect is controlled for by including a dummy variable that is set equal to 1 if the insurer is identified as a national insurer, and 0 otherwise. National insurers are those that are permitted to sell insurance in every contiguous state, on either an admitted or a nonadmitted basis 10 [National]. The variable names and definitions are shown in Table 2, while Table 3 contains the correlation matrix for the numerical variables included in the full sample estimation. Because the independent variables used in this analysis are firm level variables, multicollinearity is a potential problem. While there are some correlations that are significantly greater than zero, none of the correlation coefficients is sufficiently high as to be a concern. 11 The dependent variable is the firm s share of business in each of the six lines discussed above. Because not all firms have positive market shares in each of the six lines, tobit estimation is used to analyze the effect of distribution system on market shares for the complete sample. However, if a firm has zero market share in a particular line of business, the price,

10 160 LAUREEN REGAN Table 2. Variable Names and Definitions Variable Agency Stock Advertising Price Expense ratio Quality Leverage Cvlr National Group Retention Definition Dummy variable equal to 1 if the firm is classified by A.M. Best as an independent agency insurer, 0 otherwise Dummy variable equal to 1 if the firm is classified by A.M. Best as a stockholder-owned insurer, 0 otherwise The ratio of advertising expenses to net premiums written The inverse of the losses incurred to premiums written ratio The ratio of underwriting expenses incurred to net premiums written for each line of business Dummy variable equal to 1 if the firm was rated A+ by the A.M. Best Company in 1990, 0 otherwise The assets-to-liabilities ratio The coefficient of variation of the loss-to-premium ratio Dummy variable equal to 1 if firm is ranked as a national insurer, 0 otherwise Dummy variable equal to 1 if the firm is classified as a group, 0 if an unaffiliated insurer The ratio of net to direct premiums written Dependent Variable Market Share The ratio of the ith insurer s premium written in each line to total premium written in the line for 1990 reinsurance, and expense ratio variables will appear as zeroes in the analysis, and thus will bias the estimates. Therefore, we estimate two models for each line of business. The first model is estimated using the full sample of firms and includes only firm level, rather than line specific, variables as explanatory variables, while the second uses the subset of firms with positive market share in the line of business analyzed, and the full set of explanatory variables. To maintain consistence with the tobit estimation results, maximum likelihood estimation is used here as well. Because of the extreme variation in firm size, the models are estimated in logarithmic 12, 13 form. Table 4 contains the details of the sample. Of the 273 insurers, 200 are classified as independent agency, while 130 are stock insurers. There are 179 groups, 75 insurers classified as national, and 99 firms that received a rating of A+ from A.M. Best in The firms included in this sample accounted for 82.1% of total premiums written in the market in 1990,

11 PROPERTY-LIABILITY INSURANCE DISTRIBUTION SYSTEMS 161 approximately 93% of the personal lines, and 83% of the commercial lines included in this study. Results The regression results for each line of business are presented in Tables 5 and 6, with estimated coefficients and asymptotic standard errors shown. Model 1 for each line of business estimates the effect of the firm level variables across the complete sample, while Model 2 includes the line specific variables estimated for the subset of firms with positive market shares in a line. Results for two variables were consistent across all lines of business. The size variable [National] is positive and significant for all models, indicating that the ability to serve the national market is an important determinant of market share. In addition, the firm underwriting risk variable [Cvlr] has the expected significantly negative effect on market share and is consistent across all lines of business. Unexpectedly, however, the estimated coefficient for leverage is also negative and significant in eight of the twelve models estimated. This latter result might indicate that as the firm s market share increases, its loss reserve liability also increases, thus reducing the assets-to-liabilities ratio. This explanation may be plausible for longer-tailed liability lines, but not for auto lines. An alternative explanation might be that a lower assets-to-liabilities ratio is a sign of risk only if a firm is insufficiently reserved for the level of business it writes, given its assets. Table 4 shows results for the personal lines of business studied. Results for the private passenger auto physical damage and auto liability market share regressions are shown in columns 1 and 2, respectively. The important variable for this analysis is the distribution system dummy. The coefficient on the dummy variable for distribution system [Agency] is negative and significant at the 1% level for all models, which indicates that exclusive dealers on average have higher market shares in these lines, even controlling for other factors. The dummy variable for ownership form [Stock] is positive and significant for both personal auto physical damage and liability for Model 1, indicating that stock insurers are associated with higher market shares. This result does not support the Mayers and Smith (1988) hypothesis that mutuals will be more successful in relatively more standard, less risky lines of business, where managerial discretion is limited. However, when the expense ratio and price variables are included in Model 2, there is no significant effect of ownership form on market share for the personal auto lines.

12 Table 3. Correlation Matrix, Pearson Correlation Coefficients and Probability > R Variable Group Quality National CGL share CMP share WC share AL share APD share HMP share Total NPW Assets Leverage Cvlr Advertising Group Quality National CGL Share CMP Share LAUREEN REGAN WC Share AL Share APD Share HMP Share

13 PROPERTY-LIABILITY INSURANCE DISTRIBUTION SYSTEMS 163 Total NPW Assets Leverage Cvlr Advertising 1 Note: CGL = general liability, CMP = commercial multiperil, WC = workers compensation, AL = private auto liability, APD = private auto physical damage, HMP = homeowners, NPW = total net premiums written.

14 164 LAUREEN REGAN Table 4. Sample Statistics Variable All Lines Auto Damage Auto Liability Homeowners General Liability Workers Comp. Commercial Multiperil Agency (n = ) Stock Group National Quality Net Premium a Mean Minimum Maximum 6.59e8 1.6e5 2.45e e e e e e e e e e9 7.30e e e e e e e e e9 Market Share Mean Minimum Maximum % % 2.29e % 5.9e % 7.9e % 1.388e % 3.767e % 9.58e a Note that the figures for premiums and market share are for those firms with positive market share only. As expected, the coefficient on the expense ratio variable in Model 2 is negative and significant for both auto lines, indicating that larger insurers are characterized by lower expense ratios. While the estimated coefficient for the price variable is negative and a significant predictor of market share for auto physical damage, it is not significant for auto liability. This result might be an indication that there is not very much difference in the price of auto liability insurance among the firms in this sample, or that demand is not very sensitive to price changes. Alternatively, the effect of price might already be accounted for in the expense ratio measure. Interestingly, the coefficient for the quality variable is also positive and significant at better than the 5% level for all models except Model 1 for auto physical damage, where it is not a significant predictor of market share. This finding supports the idea that higher-rated insurers generate higher market shares on average, and that reputation is important in this market. Neither advertising nor reinsurance is significant for either model. The coefficient on the Group variable is significantly related to higher market share for both auto liability and auto physical damage for Model 1. This is consistent with the observed distribution of firms for these lines. However,

15 PROPERTY-LIABILITY INSURANCE DISTRIBUTION SYSTEMS 165 when price, expense ratio, and reinsurance are controlled for, group is no longer a significant predictor of market share. The results for homeowners multiperil are shown in column 3. The theory predicts that direct writers will have higher market shares in this line, and, as expected, the coefficient on the indicator variable [Agency] is negative and significant at the 1% level for Model 1. However, when expense ratio and price are controlled for in Model 2, there is no significant difference in market shares between independent agency and exclusive dealing insurers. The remaining variables are similar to those found for the personal auto lines. Underwriting risk [Cvlr] is negative and significantly related to market share. However, the coefficient for firm level risk [Leverage] is not significant. Surprisingly, the expense ratio variable is negative but not a significant predictor of market share. Likewise, the results of both models indicate that stock firms are not significantly associated with higher market shares for this line. Again, this is contrary to the findings of Mayers and Smith (1988). The results for the commercial lines, shown in Table 5, also offer support for the predictions of the theory. The results of Model 1 indicate that independent agency market shares are significantly higher in commercial general liability, workers compensation, and commercial multiperil. However, when expense ratio, price, and reinsurance are controlled for, the coefficient for distribution system is positive but not significant for workers compensation or commercial multiperil. The results for commercial general liability are shown in column 1. This is a complex line, and thus should be dominated by independent agency insurers. As expected, the variable for independent agency is positive and significant at the 1% level for both models, while the coefficient on the stock variable is also positive and significant at the 1% level, supporting the hypothesis that stock insurers should be associated with more complex lines. For commercial general liability, the coefficient for the underwriting expense ratio is negative and significant. However, market shares in commercial general liability are not sensitive to differences in price, but higher market shares are associated with higher ratings from A.M. Best. The estimate for the quality variable is positive and significant at the 5% level for both models. Even controlling for firms with lower expense ratios and other factors, though, independent agency insurers have significantly higher market shares in general liability. Results for workers compensation and commercial multiperil line are shown in columns 2 and 3, respectively. As expected, the coefficient of variation of the loss ratio is negative and significantly related to market share for all models. The leverage variable is also negative and significantly related to market share in three of the four models estimated.

16 166 LAUREEN REGAN Table 5. Personal Lines Maximum Likelihood Estimation (Estimates and Asymptotic Standard Errors Shown) Auto Damage Auto Liability Homeowners Variable Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Intercept a a a a a a (.0647) (0.118) (0.0904) (0.114) (0.087) (0.094) Agency a a a a b (0.0367) (0.0515) (0.052) (0.0556) (0.0496) (0.048) Stock c c (0.035) (0.048) (0.049) (0.052) (0.048) (0.045) Cvlr a a a a a a (0.115) (0.195) (0.165) (0.182) (0.211) (0.221) Leverage a b c (0.031) (0.051) (0.041) (0.056) (0.038) (0.034) Advertising (0.612) (0.809) (0.878) (0.848) (1.084) (1.794) Quality c c 0.08 c b (0.033) (0.047) (0.047) (0.0489) (0.045) (0.042) National a a a a a a (0.384) (0.055) (0.055) (0.058) (0.053) (0.051) Group b c b (0.035) (0.051) (0.0502) (0.053) (0.05) (0.046) Expense Ratio b b (0.002) (0.0019) (.0022) Price b (0.037) (0.0028) (0.0099) Retention (0.007) (0.0005) (.00024) Chi-squared Pseudo R % 51.2% 35.95% % 66.22% # censored 41/273 41/273 53/273 # obs a significant at the 1% level; b significant at the 5% level; c significant at the 10% level.

17 PROPERTY-LIABILITY INSURANCE DISTRIBUTION SYSTEMS 167 Table 6. Commercial Lines Maximum Likelihood Estimation (Estimates and Asymptotic Standard Errors Shown) General Liability Workers Compensation Commercial Multiperil Variable Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Intercept a a a a a a (.0817) (0.111) (0.1098) (0.1406) (0.106) (0.139) Agency c c c a (0.0461) (0.0515) (0.059) (0.0681) (0.0543) (0.0618) Stock b a b a a (0.044) (0.052) (0.055) (0.063) (0.0506) (0.0544) Cvlr a a a a a a (0.143) (0.160) (0.177) (0.220) (0.163) (0.163) Leverage a c a a c (0.041) (0.047) (0.052) (0.0595) (0.0534) (0.063) Advertising (0.776) (0.795) (0.939) (2.32) (1.775) (2.415) Quality b b b c c (0.0423) (0.046) (0.052) (0.0562) (0.0482) (0.048) National a a a a a a (0.482) (0.055) (0.059) (0.0653) (0.054) (0.0585) Group b a a (0.044) (0.052) (0.0574) (0.0706) (0.051) (0.0529) Expense Ratio a a (0.0015) ( ) ( ) Price c (0.0171) (0.0142) ( ) Retention (0.0017) ( ) (.08007) Chi squared Pseudo R % 54.84% 30.28% % 65.42% # censored 34/ /273 66/273 # obs a significant at the 1% level; b significant at the 5% level; c significant at the 10% level.

18 168 LAUREEN REGAN As expected, the quality variable is positive for all models, but not significantly related to market share for Model 2 for workers compensation. However, commercial multiperil market shares are significantly related to Best s ratings for both models, which might indicate that smaller commercial policyholders rely more on Best s ratings as a signal of quality than do larger insureds. The coefficient for independent agency is positive and significant for Model 1 for both lines of business, indicating that the independent agency insurers are more successful in these lines. Model 2 indicates that as price increases in commercial multiperil, market shares decline, while market shares are significantly negatively related to expense ratio for worker compensation. The interesting result for Model 2 is that, controlling for line specific variables, independent agency is no longer significantly related to market share for these lines. To investigate further, Model 2 was re-estimated with the expense ratio, price, and reinsurance variables omitted. For both commercial multiperil and workers compensation, independent agency is positive and significantly related to market share at better than the 10% level, while the signs and significance on the other variables are unchanged. This result suggests that independent agency insurers might have lower expense ratios in these lines, and thus that there is a need for further investigation of the relationship between distribution system and expense ratio by line of business. CONCLUSION This study has found evidence that supports the idea of differential advantages across lines of business for insurers using alternative distribution systems. On an aggregate basis, it appears that exclusive dealing insurers are larger than independent agency insurers in terms of market share. However, a closer examination reveals that these advantages are specific to the personal lines of business. It seems that the dominance of exclusive dealing is due to its presence in personal auto and homeowners insurance. Since these three lines accounted for over 44.5% of premiums written in 1990, it is not surprising that the aggregate data indicate that exclusive dealers have higher market shares overall. To summarize the results presented here, insurers using the exclusive dealing system do dominate the market in personal lines, while the evidence supports the idea that independent agency insurers have an advantage in commercial lines. The significant variables across both personal and commercial lines are the quality of the insurer, the insurer s level of underwriting risk, and whether the insurer writes business on a national

19 PROPERTY-LIABILITY INSURANCE DISTRIBUTION SYSTEMS 169 basis. Insurers characterized by greater underwriting risk have lower market shares, and these results are consistent across both the personal and commercial lines studied here. In addition, firms that have higher assetsto-liabilities ratios have lower shares in general, all else equal. Finally, the results are inconsistent with the managerial discretion hypothesis of Mayers and Smith (1988), with respect to the relationship between ownership form and market share in the lines studied here. It does not appear that mutual insurers have higher market shares in the personal lines studied here. These results must be interpreted with caution. Market share is not uncorrelated across lines, so that market share in one line is likely to be determined partly by share in another line. Also, the data do not allow a test of within line specialization. Since independent agency does continue to survive in personal lines, economic theory suggests that in a competitive market, independent agency must offer some advantage. Unfortunately, this theory cannot be tested with the current data set. Acknowledgments: The author thanks David Cummins and participants at the 1995 ARIA meeting for valuable comments. This research was supported in part by a research grant from Temple University. NOTES 1 Data are from Best s Aggregates and Averages. The first year for which Best s published these data by distribution system is For example, Launie, Lee, and Baglini (1986) note that agents are often asked to attest to the business and personal reputation of the applicant. Likewise, applications for commercial property insurance commonly ask for the agent s evaluation of the cleanliness and neatness of the insured premises. 3 One exception is a study by Sass and Gisser (1989), which does not rely on differential advantages across lines of business as a rationale for exclusive dealing. Rather, their argument is that exclusive dealing reduces the agency costs associated with monitoring sales effort under commission share contracts. The constraint on this model is that the market and the insurer must be large enough to support a tied agent. In the absence of the size constraint hypothesized by Sass and Gisser, however, the balance of the literature argues that direct writers should focus more on standardized personal lines regardless of firm size. 4 The dramatic decline in homeowners market share between 1985 and 1994 could reflect independent agency withdrawal from catastrophe-prone coastal residential property markets, which were very unprofitable at the time. 5 One of the variables discussed below, the coefficient of variation of the loss ratio, is measured over the period 1980 through Therefore, only firms that had data continuously available over the period 1980 through 1990 were included in the final sample. 6 Although some groups do used a mixed distribution system, the classification used by A.M. Best is used here for the group as a whole. 7 The model was also estimated with the premiums-to-surplus ratio rather than the leverage

20 170 LAUREEN REGAN ratio, but that estimation did not perform as well. 8 Note that A.M. Best expanded its rating system in 1992 to include A++ as the highest rating. However, at the time of this sample, the highest rating was A+. 9 Measured by assets, the largest insurer in the sample is State Farm, while the smallest is the American Independent Insurance Company. 10 These insurers were identified from Best s Insurance Reports, 1991 edition. For groups, if the 48 contiguous states are covered by any combination of firms within the group, the group is classified as a national insurer. 11 Alternate measures of firm size total net premiums and assets are included in the table to support the choice of National as the firm size variable used in this analysis. This variable is relatively highly correlated with market shares across each line of business, but not highly correlated with the other independent variables. However, both total premiums written and assets are extremely correlated with market shares for the personal lines of business, eliminating them from consideration as predictor variables. Further, when the National variable is dropped from the analysis, the results of the remaining variables are unchanged, but the fit of the model is significantly reduced. 12 See Greene (1993) for a discussion of this transformation for the tobit model. 13 Note that the number of observations used to analyze the full set of variables is not equal to the number of non-censored observations in the tobit analysis, because several firms that had positive market shares in a line were deleted as outliers if reported expense ratios were less than zero. REFERENCES Barrese, James, and Jack M. Nelson (1992) Property-Liability Insurance Distribution Systems, Journal of Risk and Insurance, 59, pp Barrese, James, Helen I. Doerpinghaus, and Jack M. Nelson (1995) Do Independent Agent Insurers Provide Superior Service? The Insurance Marketing Puzzle, Journal of Risk and Insurance, 62, pp Cather, David (1994) Agency Theory and Risk Differences Across Distribution Systems. Presented at the annual meeting of the American Risk and Insurance Association. Cummins, J. David, and Jack VanDerhei (1979) A Note on the Relative Efficiency of Property-Liability Insurance Distribution Systems, Bell Journal of Economics, 10, pp Cummins, J. David, and Steven Weisbart (1977) The Impact of Consumer Services on Independent Insurance Agency Performance. Glenmont, NY: IMA Education and Research Foundation. Cummins, J. David, and Mary Weiss (1992) Structure, Conduct, and Regulation of the Property-Liability Insurance Industry, The Financial Condition and Regulation of Insurance Companies, A. W. Kopcke and R. E. Randall, editors. Boston: The Federal Reserve Bank of Boston. D Arcy, Stephen, and Neil A. Doherty (1990) Adverse Selection, Private Information, and Lowballing in Insurance Markets, Journal of Business, 63, pp Doerpinghaus, Helen I. (1991) An Analysis of Complaint Data in the Automobile Insurance Industry, Journal of Risk and Insurance, 58, pp

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