The Industrial Organization of the U.S. Life Insurance Industry: Issues and Analysis in the Structure of the Industry

Transcription

1 The Industrial Organization of the U.S. Life Insurance Industry: Issues and Analysis in the Structure of the Industry Martin F. Grace ) Robert W. Klein ) Center for Risk Management and Insurance Research Robinson College of Business Georgia State University PO Box 4036 Atlanta, GA Please do not attribute or quote without permission.

2 The Industrial Organization of the U.S. Life Insurance Industry: Issues and Analysis in the Structure of the Industry I. Introduction The literature on the industrial organization and regulation of the life insurance industry is sparse relative to the property-casualty literature (see e.g., Dionne and Harrington (1992)). While a number of articles examine certain aspects of life insurance markets, there is no foundation literature that establishes a set of critical springboard questions regarding the organization and regulation of the U.S. life industry. 1 This paper is the start of a multiple paper project that will examine the industrial organization of the life insurance industry and how it is evolving in response to changes in the economy and competitive threats from other financial institutions. Our work will begin with applying the standard conduct-structure-performance (CSP) paradigm to the life insurance industry. Although quite useful, CSP does not necessarily cover all of the potential issues in the industrial organization of the industry. We will attempt to bring in issues from the new industrial organization literature on contestability and transactions costs where appropriate to supplement or complement the CSP paradigm. The paper is organized as follows. First, we briefly examine data regarding the consumption of life insurance and associated products. Second, we will focus on one structural aspect of the life insurance industry: Entry and, its complement, Exit. Entry and Exit are interesting to examine given the financial services legal reforms that will ultimately occur. Thus, this paper will provide some background and preliminary analysis regarding entry and exit in the life insurance industry and the related financial services industries. II The Life Insurance Consumer Market: Basic Conditions Before getting to the entry and exist aspect of the structure of the life insurance industry, we need to focus on the conditions the market faces. These are environmental demand and supply conditions. Who Buys Life Insurance? The consumer base for the life insurance industry is those who desire to provide their beneficiaries income replacement due to premature death (Yarri (1965), Pissarides (1980), those who desire to insure for bequest related reasons, (Lewis 1989) and those 1 Joskow (1973) provided such a foundation for the property-casualty insurance industry that led to a number of subsequent articles on the industry s structure, performance and regulation. Recent articles in this vein include Cummins and Weiss (1992) and Klein (1995). 1

3 who might use life insurance for its tax reduction characteristics (Black and Skipper (1995) and IRC 101(a)1). Recent statistics show that the average amount of life insurance coverage per insured household was $165,800 which equals about 34 months of disposable personal income for the average insured household (ACLI, 1998). If we look at the number of policies, the majority of purchases (58 percent) were made by those with incomes between $10,000 and $40,000. However, this group purchased (in terms of face amounts) 34 percent of the insurance sold. Only 13 percent of life insurance purchasers had incomes over $75,000. However, this group purchased 37 percent of the insurance in terms of face amount. (ACLI, 1998). In terms of gender, males purchase 65 percent of the face amount but only 44 percent of the policies. Females have increased both the percent of policies purchased and the percent of the fact amount over the last ten years. In terms of age, most insurance, for both numbers of policies and face amounts, is purchased by those between 25 and 44 years of age (ACLI, 1998). What Type of Life Insurance do Consumers Buy? Consumers are changing their preferences towards term insurance. In 1986, 20 percent of the policies consumers purchased were term products and this amounted to 30 percent of the face value of polices sold that year. By 1996, 35 percent of the polices sold in the U.S. (representing 50 percent of the face amount) were term polices. (ACLI (citing LIMRA data) 1998). Universal life was approximately 32 percent of the face amount written in 1986, but this fell by 1996 to only 11 percent (ACLI, 1998). How is it Sold or Distributed? Life insurance is sold though a number of distribution channels. There are traditional sales agents who will provide services such as financial planning, brokers, direct marketers, mass marketers, and others. Table 1 shows the relative percentage of the life insurance business based on premiums by line and total assets marketed though one of the distribution mechanisms. The marketing distribution information is from the A.M. Best Key Rating Guide (1998). A.M. Best allows firms to describe itself with more than one distribution scheme. We employ as our classification the one listed first by the responding company. In 1997 a majority of total life premiums were written though agents (67.17%) and brokers (15.23). The percentage of total assets allocated through the distribution mechanisms follows the break down in total life premiums. Direct marketers, those that by pass agents and market directly to consumers or business, seem to be relatively strong in individual annuities, credit life insurance, and credit accident and health. Mass 2

4 marketers, which include Mutual of Omaha and others that might advertise on television for fixed (and low) dollar value life insurance, do not have large market sizes. 2 What are its Substitutes? Life Insurance can be thought of as a savings product. If we think of it as primarily that, then there are a number of potential substitutes ranging from bank accounts to individual stock portfolios. Table 2 examines some of the more interesting data from the Federal Reserves Flow of Fund Accounts. The table shows the amounts of various assets held by households (and non-profit organizations) at the end of 1991 and Total financial assets increased approximately 82 percent over this period. Mutual funds increased 326 percent and individual holding of corporate securities increased 147 percent. In contrast, life insurance reserves increased 72 percent, which did not keep up with the average increase in total assets. It is common knowledge that the mutual fund industry has taken in tremendous amounts of individual contributions. It is likely that some of this has come from funds previously allocated to the life insurance industry. Thus, mutual funds are likely competing with life insurance for the savings dollar. If we view life insurance as solely income protection rather than saving, then there is no other substitute financial contract that provides payments in case of death. A cursory look at the data suggest that consumers are switching to term to cover mortality risk, but increasing amounts of funds are flowing to mutual funds or corporate equities rather than into insurance savings products. Historical Demand and Production of Life Insurance Figure 1 shows the major life insurance industry product lines on a real basis over the last thirty years. We see ordinary life insurance growing steadily (approximately the same as GDP), group insurance growing steadily, credit insurance following a cyclical pattern (which probably follows the credit market), and a steady decrease industrial life is decreasing dramatically. Table 3 shows that the level and mix of products of the life industry has changed over time. Within broad lines of coverage, we see that since 1970 real output of the insurance industry (as measured by real premium) grew about 125 percent over the period 1970 to This amounts to an annual average growth rate of about 5 percent. 3 2 With all the hype surrounding the dis-intermediation of the agent in the life insurance value chain, there is not much evidence yet that the distribution network is changing. It is still difficult to instantly purchase large valued term or whole life polices over the phone or over the internet. It is possible to get quotes and information, but a deal can not be consummated with a click. This dis-intermediation may not show up in 1997 data and we may need more time to see trends affecting companies and their supply chains. 3 Growth measured by real services provided to consumers is likely to have increased if there was any gains in efficiency over time (see e.g. Weiss (1986) and Reece (1992)). Further, if there have been any gains in terms of life expectancy over this period, the mortality charge will have decreased (on average). This also increases the real life insurance services. 3

5 While total output increased, the mix of output changed over this period. In 1970 credit insurance represented about 5.5 percent of business written, but by 1987 it had fallen to 1.6 percent. Industrial life has also fallen dramatically. Ordinary life insurance has increased over the period as a percentage of the total, while group life in 1997 is about the same percentage of total life insurance as it was in While it is difficult, if not impossible, to estimate price elasticities for life insurance, a simple national income elasticity in the spirit of Outreville (1990) was estimated by regressing the log of premiums for a given line against the log of GDP. We see in Table 4 that total life insurance has a positive elasticity of about.42. This reflects the fact that ordinary insurance is a normal good. This result is similar for individual and group life insurance. However, for industrial life and for credit life insurance we see that the income elasticity is negative. This suggests that these are inferior goods. That is as the percentage of income increases the quantity-demanded decreases. If we look at a plot (Figure 1) of these products over time we see that industrial life is decreasing and that credit insurance appears cyclical. Credit insurance increases in lower income periods and decreases in higher income periods. It appears that ordinary and group life insurance still have relative value in the market place while industrial and credit are reducing in their importance. These insurance markets are changing and are adding and shedding companies to respond to the changes. Next we need to look at the how the industry is responding to these changes in the market. The next section will examine how firms enter and exit the life insurance market. II. Structure of the US Life Insurance Market: A Look at Entry and Exit In the conduct-structure-performance paradigm we focus on those relationships that help organize a particular market. This section will focus on entry and exit which is a part of structure. Structure also includes the numbers of buyers and sellers, product differentiation, barriers to entry, cost structures, and vertical integration (See Scherer and Ross 1989). It is often difficult to talk about one structural component without discussing another. We will primarily focus on entry and its implications although there are many natural links to concentration and performance. Entry: What is the Market? This industry actually sells a number of different products other than life insurance such as annuities, disability, and accident and health insurance. The life insurance market is also broken into various sub-markets such as group and individual products, interest and non-interest sensitive products, and credit based life and health insurance. Table 5 shows the range of products and their relative importance to the industry. 4

6 Table 5 shows the breakdown in the types of policies written into a number of categories. If we focus on group versus individual we see that the group coverage amounts to approximately 36 percent of the industry. In terms of term versus whole life we see that term insurance now accounts for approximately 62 percent of the ordinary life sold in the US. One interesting thing about this industry is the extent to which the products overlap in theory but not in practice. For example, one could purchase traditional term life insurance or credit life insurance to cover future mortgage payments in case of an early death. The traditional term policy is allegedly cheaper than a similar valued credit life policy. Consumers, however, do not think of these products as substitutes and, therefore, behave quite differently than if the products were viewed as substitutes. Another interesting observation is that there have been few true estimations of the demand for life insurance (See Babbel (1980) for an exception). We know the basic rationales for the demand for life insurance, income protection, tax avoidance, savings, and bequest. However, we have no estimates of the sensitivity of changes in the motives for purchasing insurance to the various insurance products, nor do we have any estimates of the substitutability of one type of life insurance for another. Finally, we have no estimates of the substitutability of life insurance with other types of financial services. 4 Thus defining the market is quite difficult given our current tools. This lack of information may be a barrier to entry because new entrants may have to conduct expensive marketing studies to determine the demand for their products. In addition, other barriers may exist that reduce the effect of competition in the market. The next section discusses the theory of barriers to entry and provides some evidence regarding these barriers (or lack thereof) in the life insurance industry. Entry Theory One of the major determinants of the competitiveness of a market is the ease at which new firms can enter or exit. Bain (1956) discussed the types of barriers and he makes three major classifications: absolute cost advantages, product differentiation advantages, and economies of scale. Absolute cost advantage means that a firm can produce a level of output at a less expensively than another. In the pure life insurance industry this may be hard to empirically measure as price for a given age and health status is based on a common set of actuarial calculations employed by many firms. The major difference per dollar of coverage would have to be administrative expenses and the likelihood of ruin for the firm. 4 Some literature such as D Arcy and Lee (1987) compare various pollicies with other financial contracts. However, these tend to be simulations rather than en examination of actual consumer choices. In contrast, we see that term insurance has increased dramatically as a percentage of total insurance. This happened concurrently with the growth of mutual fund contributions. However, we still have no good evidence on behavior here. Questions that need to be addressed are those such as: Are people buying term and investing the rest?; What is the elasticity of substitution between the product (term + mutual fund investment) and an interest sensitive life policy? 5

7 Product differentiation advantages would be the case where one firm is able to produce a product preferred over the products of other firms and the other firms are not able to replicate the first firm s offering. A number of facts peculiar to the life insurance industry mitigate against the likelihood of product differentiation advantages. The first is that since an insurance product is written on a piece of paper, it is easy to copy by another firm. Black and Skipper (1994) describe the origins of universal life insurance as predominantly academic and thus in the public domain. Further, universal life was introduced in 1979 and by 1985 had a 38 percent market share. There are few impediments to mimicking the contracts of others. Finally, economies of scale are a barrier to entry as a larger firm may be able to produce at a lower per unit cost than a smaller firm. A number of studies have examined economies of scale in the insurance industry. The first studies such as Harrington (1982) was were based upon expense ratio analysis, that is the expense ratio was regressed against other explanatory variables including total premium. Kellner and Mathewson and (1983 for Canadian Life Industry) and Grace and Timme (1992 for the U.S. Life Industry) were among the first to employ a multi-product and neo-classical cost function estimation for the life insurance industry. Using 1987 data, Grace and Timme found that the largest 100 or so life insurers had constant returns to scale while the next three hundred largest companies experienced various degrees of increasing returns to scale. Yuengert (1993) employed a stochastic frontier method and found increasing returns to scale for all except the largest companies and Cummins and Zi (1998), using DEA, found similar results. 5 Thus, it appears that there is a rage of production that sees increasing returns to scale and all but the largest firms are operating at this relatively inefficient level. An interesting question is why so many firms are operating at less then efficient scale. Over time one would expect a majority of the industry would be at constant returns to scale. It may be that regulation plays a role in that inefficiencies result from the multi-state licensing arrangement. It also may be that it takes time to achieve equilibrium in the life market. This implies that the long run for the life industry is much longer than in other industries. 6 Figure 2 shows the percent of 1997 total assets of companies that started in a given year. The figure covers the period If we look at certain milestones based on the accumulation of assets by companies starting in a given year we see that 50 percent of current assets are owned by companies that were in place in To go further, 75 percent of current assets are owned by companies in place in 1959, and 90 percent of current assets are owned by firms in place in Firms with start-up dates within the 5 Another implication of the empirical results is that not all companies are in the same market. National companies, regional companies, and single state companies exist. Each of these producers could have different production technologies and by combining them into one empirical cost or profit function we may miss actual differences in the companies. 6 M.R. Greenberg, President of AIG Inc., stated at a seminar at GSU, It takes a long time to kill a life insurance company. This implies that the long run is quite long, as decisions made today may not have an effect for numbers of years into the future. 6

8 last ten year period in the data ( ) account for only 1.62 percent of the assets in the industry. One possible problem with Bain s approach is that two (absolute cost differences and economies of scale) can be rectified by changes in technology in the long run. Over time technology will allow new entrants to copy the best practice firms and achieve constant returns to scale by producing at the minimum of the long run average cost curve. An interesting question then is to look at the firms that do enter to see how they perform relative to the firms in the market. The next section examines entry and exit in the life industry. Entry and Exit in the Life Insurance Industry There are a number of possible methods a firm may employ to enter the market for life insurance. First, a firm can be a de novo start-up. Capital can be raised and a firm can obtain a license and then go into business. A second method of entry is when a seasoned, or established, firm enters a new line of business. For example, a life insurer can decide to enter the annuity business or a term life provider decides to offer interest sensitive products. In practice, this can mean that a firm sets up a new infrastructure to produce and market this new line of business or it can purchase the business from another established firm. In both of these cases the established firm is entering a new market. A third related method of entry is based on entering a new geographical market. This can be done by expanding production and distribution to the new state or by purchasing the business of an established company. De Novo Start-ups and Established Entry Table 6 shows a number of lines of business: ordinary life, ordinary annuities, group life, group annuities, and the total amount of premiums and annuity considerations sold by the U.S. industry. Looking at Panel A (ordinary life) we see that between 1992 and 1997 there were 64 companies that either (1) did not exist in 1992 or (2) did not write ordinary life insurance in The first group is de novo entrants. In the period there were 23 de novo entrants and in 1997 they had a combined market share of 1.37 percent. The 41 established companies that entered the ordinary life business between had a combined market share of approximately one-half percent. If we look at the ordinary annuity business in Panel B we see the opposite story. Established firms entered and earned a larger market share than de novo entrants. This pattern is repeated for the other lines of business described in Panels C-F. Established firms are more likely to get greater market share than de novo entrants. Further, entrants of both types were not likely to gain much market share except in the group life and group annuities markets. 7

9 Exits Looking at Table 6 we can see the exits by line. Panel A shows ordinary life insurance and exits. We see that 192 firms that were doing business in 1992 were no longer there by These 192 firms were responsible for approximately 8 percent of the 1992 market. It is likely that some of these so-called exists are the result of mergers, but not all. Across most of the other lines of business we see that exists represented a relatively large percent of the 1992 market. The exceptions are group life and group annuities. Recall that these two markets had among the largest amounts of entry in terms of 1997 market share. Table 7 shows a slightly different view of entry and exit over the last few years. This table shows the number of entities entering and exiting. Panel A of Table 7 shows that for the total line of business there were over 50 percent more exists than entries over this period. Most lines of business experienced a net decrease in the number of companies writing in a given line. Only ordinary life (and the unimportant all other line) stayed stable over the period. Panel B shows the complement in terms of entry. The major point is that in terms of entities, exists dominated during this period. Another way to measure exit of an established company without necessarily quitting the industry completely is to examine the firms with negative premiums in a given year. This may be an indication that the firm sold its business to another. If a firm had negative premiums for a given line of business, then it is possible the firm has exited from that line of business. Table 8 shows two years 1992 and 1997 and the number of firms that experienced negative premiums by line of coverage. The major difference between the two years is that in 1992 the amounts for the most of the lines are much greater than their 1997 counterparts. The total amount in both years is not a significant source of market share. Regulation and Licensing: A Barrier to Entry? The previous two tables document some of the entry and exit occurring in the market during the recent past. We might be interested in the effect state regulation plays on whether a seasoned firm expands to serve another geographical market. If it pays to do so then a firm will enter. Before examining a simple empirical test, we need to briefly discuss the type of regulation facing the life industry. Insurance regulation is divided into two primary areas: 1) financial or solvency regulation; and 2) market regulation. The basic structure for the financial regulation of life insurers is similar to that of non-life insurers, with specific standards, policies and procedures tuned to the particular characteristics and risk factors of each sector. The regulation of life insurance markets also is tailored to the specific nature of these markets and the types of abuses that are most likely to arise. 8

10 Each state controls entry by requiring life insurers to become licensed or admitted in order to business in their jurisdiction. Insurers must meet minimum capital requirements (fixed minimum and risk-based) and other financial requirements to become and remain licensed. Like other insurers, life companies are required to file annual and quarterly statutory financial statements, independent audit reports, and actuarial opinions. Regulators analyze this information and monitor insurers financial condition, using early warning systems and other tools. Life insurers are subject to periodic and targeted regulatory examinations and regulators are authorized to seize companies in hazardous financial condition. The financial regulation of life insurance companies is most distinct in the areas of reserves, investments and asset-liability matching. The rules for life insurers reserves tend to be more prescriptive based on standard actuarial procedures and assumptions. Company actuaries must perform a number of tests to demonstrate that it has adequate reserves to cover its benefit obligations and the duration of assets and liabilities are appropriately matched. Further, life insurers are required to set aside reserves to cover potential fluctuations in the value of their assets. The Asset Valuation Reserve (AVR) sets reserve requirements for all major asset classes, including real estate and mortgage loans. The Interest Maintenance Reserve (IMR) also requires insurers to amortize interest-related gains and losses over the remaining life of a disposed asset. Investment laws also have been strengthened with respect to the types of assets insurers may hold, their relative amounts, and diversification. These regulations attempt to constrain life insurers financial risk and implicitly limit the products and contract terms they can offer. Unlike personal auto and home insurance, the prices or premiums for life insurance and annuities are not explicitly regulated. However, life products and policy forms must be filed and approved by regulators. Insurance policies and related materials are reviewed for proper representation, adequacy of benefits and the reasonableness of other contract terms. Requirements for minimum non-forfeiture values have been strengthened in recent years. Obtaining regulatory approval can delay the introduction of new products or product changes. The market conduct of life insurers has received increasing regulatory scrutiny as severe abuses have been uncovered in agents sales practices. Several large life insurers received hefty fines and agreed to refund millions of dollars to policyholders that have been victims of sales abuses. These kinds of abuses are not surprising given the complex array of investment-oriented products offered by life insurers that some consumers may find difficult to fully understand. Regulators have wrestled with how to regulate life insurance sales illustrations so that buyers can reasonably compare policies. The NAIC went through a long process with considerable input from the life insurance industry, software developers and consumer representatives to design an illustration requirement that would help consumers understand this complex product. In addition, the model regulation developed sets actuarial limitations on the numbers that may be used in the illustration so they will be closer to reality. The model regulation developed by the NAIC 9

11 was adopted as a requirement by the majority of states by the middle of 1998, and companies are generally following the model format even when it is not required. The intent of the illustration requirement is that companies avoid the use of footnotes and explain terminology used to consumers. Most importantly, the illustration must not give undue prominence to non-guaranteed elements or imply in any way that these results are guaranteed. Insurers may not talk about vanishing premiums or imply a policy will be paid up when, in fact, the cash value is being used to pay premiums. Another problem that is not new but has become more acute in recent years is the practice of churning, twisting, or the improper replacement of life insurance policies when it is not in the best interest of policyholders. Consumers are encouraged to use the cash value of an existing policy to purchase a new policy. However, once the cash value is exhausted in paying premiums on the new policy, the consumer must begin paying additional premiums or lose the original policy. Churning is encouraged by insurers ability to skim economic value from the policies replaced and high front-end agents commissions. Consumers difficulty in ascertaining the financial impact of replacing a policy make them vulnerable to making choices which favor the insurer and agent at the expense of the policyholder. Recently adopted NAIC model laws and regulations governing sales illustrations and replacement of life and annuity policies could assist consumers understanding the financial implications of replacing a policy as well as notifying the company which issued the policy. In addition, regulators are considering several options to further control churning, including: 1) regulation of commissions to decrease agents incentives to replace policies unnecessarily; 2) institution of a cooling-off period to allow consumers to review the replacing policy or reinstate the old policy; 3) mandatory notice to consumers outlining the risk of replacement; and 4) closer regulatory and company monitoring of agents sales activities. As can be seen by the above discussion, there may be governmental barriers to entry. The compliance costs of these regulatory activities may be enough to dissuade firms from entering another state. Thus, it may be possible to get an understanding of the cost profitability of this conditional entry on the firm. Conditional entry is defined as entry into another state (or a set of states) given that you are already have entered, and obtained a license, in one geographic market. Table 9 shows the simple performance elasticity estimates of adding states licensed to do business to four sized based groupings. Quartiles 1-4 represent size groupings based on total assets. For the life insurance industry a simple regression was estimated between the log of total costs and a simple output measure, the log of the various outputs produced. This is a restricted quadratic cost function where the restrictions are placed on the coefficients on the input prices. The regression we estimate is: ln( M ) a a ln( Y ). 5 b ln( Y ) ln( Y ) h ln( SLicense) (1) k o i i i j i ij i j 10

12 where ln(y i ) is then natural log of output (i = ordinary life, group life, individual annuities, group annuities, investment activities, and accident and health premiums). 7 The term η represents the elasticity of Licenses with respect to the various performance measures M k (k = cost, revenue, and profit). The table reports the coefficient on the log of states licensed, η, by quartile for each of the performance measures. We see that for quartiles (based on total assets) 1 through 4 the cost elasticity with respect to state licenses ranges between.0152 and This means that a ten percent increase in the number of state s licensed be associated with an approximately 2 percent increase in the costs of the firm. However, we see from the revenue elasticity that revenue is about one-half as elastic as costs. That is a ten-percent increase in the number of states licensed yields an increase in revenues of approximately one percent. The largest firms have slightly higher revenue elasticity of approximately 1.96 percent. What is most interesting is that the profit elasticity is much lower and is only significantly different from zero for the largest sized companies. This implies that only the largest firms would experience increase in profits from entering more states. These large companies already account for 91 percent of premiums written and already are in an average of 31 states. Thus, they are most likely to be the ones that enter a new state. Entry and Size of Entry One of the interesting questions to ask is what the minimum efficient size is for an entrant. Typically, this means examining the minimum point of the long run average cost curve. This information is not yet available for this data set, but can still look at the entrants to see the relative size of de novo entrants. We can see empirically what the entrants look like after a few years of seasoning. Figure 3 shows the median value of total assets in 1997 based on a firm s year of entry. Thus, for group affiliated firms that entered in 1987, we see that they had a median value of total assets approximately $6.1 million in In 1996, in contrast, the firms with group affiliation had total assets in of approximately $2.58 million. Over most of the recent past, the median total assets of firms entering in as part of a group was higher than the median total assets of non-affiliated singles in most years. 8 Thus, group companies appear to employ higher levels of start up capital than non-group affiliated companies. This pattern is robust and repeats itself if we look at previous years. 7 This model is similar to one employed by Grace and Timme (1992). The major difference is that wages are omitted from the model. This model was estimated for simplicity rather than completeness, thus, these elasticities should be interpreted and used with care. 8 In 1992 we see a spike because of the formation of the Savings Bank Life Insurance (SBLI) Company of Massachusetts. This company took as its assets the life insurance assets of all sellers of SBLI products. Thus, it is really a merger or change in organization form, rather than a true new entry. 11

13 Further, if we examine Figure 4, we see that the median group affiliated firm has higher RBC than the median non-group related firms. Together with Figure 3 this result implies (weakly) that group startups have higher quality capital backing them than non-affiliated start-ups. Figures 5 and 6 show the 1997 market share for two lines of business (life and annuities) for firms based on its start-up year. Figure 5 shows the market share at the group level. This means that if a group started up a new company, then that new company would be added into the group and the group s total market share for a given line of business is reported. For example, in Figure 5 we see that groups with a start-up and unaffiliated singles had 12 percent of the life market and 18 percent of the annuity market in This shows that for the most part, a de novo start-up backed by a group may have strong marketing power as well as other benefits from group membership to bring to bear on the market. If we look at the firm level data in Figure 6, however, we see that if we treat each company as a separate entity, then the market share of the entrants is insignificant even after ten years. Concentration as a Proxy for Barriers to Entry If an industry is highly concentrated, it could imply that there are some implicit or explicit barriers to entry. Thus it might be illustrative to look at market concentration. Nationwide Concentration Table 10 shows two sets of concentration figures. Panel A shows group level data while Panel B shows individual firm level data. Panel A shows the four through twenty firm (CR 4 CR 20 ) concentration ratio, and the Herfindahl-Hirschman Index (HHI) of concentration, and the inverse of the HHI. The inverse measures the number of equal sized firms that would fit in a market. One can argue that the greater the number of equivalent sized firms, the greater is the likelihood that competition exits in the market. The upper section of Panel A shows the concentration measures for the life insurance industry at the group level. That is, all members of a group are merged into one entity and unaffiliated singles are treated as separate entities. Over the period concentration in total in total assets has decreased in the top eight firms, but appears about the same between the two periods from the sixteen firm and twenty firm concentration ratios. Further, the HHI has fallen over time yielding 30 equivalent sized firms in 1986 and 39 equivalent sized firms in The bottom section of panel A shows, on a group basis, concentration measures for the life and annuity industry. For CR 4 CR 8, concentration is about the same, but for CR 16 CR 20 it has increased over time. The HHI has also increased and the equivalent number of rims has decreased from 53 to 44. What is interesting is that for sections of panel A, the year 1990 seems to be out of line with the endpoint years. Recent mergers may have influenced the trend. 12

14 At the group level assets are as concentrated as they were in 1986, but there appears to be a bigger spread throughout the industry based on the HHI. At the firm level of life premiums and annuity considerations, concentration ahs increased at the sixteen and twenty firm level and in the HHI. If we think of assets as reflecting the past sales of insurance of the life insurance industry and premiums written as a measure of current production, then it appears that at the national level concentration is increasing. Panel B shows similar statistics on an individual firm basis. However, the story is much different. We can look back farther using Cummins et al (1972) data from 1968 to see the concentration ratios at the firm level in 1968 were much higher than they are in the 1980s and 1990s. Between 1968 and 1986 the largest 20 firms lost approximately 20 percent of the market assets concentration to the rest of the industry. 9 Further the HHI increased dramatically from 1986 to 1997 from 33 to 50. In terms of premiums we see a reduction in the firm level concentration between 1968 and 1986 for CR 4, CR 8 and CR 20. From 1986 to 1997 all the various concentration measures show modest increase in market share. Statewide Concentration Finally, Table 11 shows the statewide concentration on a firm level for ordinary life premiums in 1997 and The table is constructed to be consistent with Cummins et al. (1972). The concentration ratios were calculated for each state and descriptive statistics were calculated. On a state basis concentration has reduced significantly over time too. Now we are back to the same question as we started: What is the market? Is it the national market figures, which tell us the relative importance of concentration as an indicator of free entry, or is it the state market s concentration? The state markets appear slightly less concentrated (on average) than the national markets. Without knowledge of how consumers search for life insurance, it is difficult to say whether the national is the market or whether the state is the proper relevant market for consideration. Cummins et al. (1972) claim that it is the state market that is important. This is because the consumer can only buy a product licensed in the consumer s state. However, it is clear that the underlying technology of information production may reduce this question s importance over time. The internet and its cost reduction push may make the insurance market more national in scope. 9 Note that the firms in the top 4, top 8, top 16, and top 20 are not necessarily the same in each year. 13

15 III. Conclusions This paper examined some of the entry and exit related issues in the structure of the life insurance market. We see that the life insurance had exit and entry over the recent past. Cases of de novo entry as well as established firm entry were examined. Further, we examined the cost of conditional entry by established firms into other geographic markets. We also saw the exit was occurring. In terms of the numbers of firms, more firms exited than entered. Further, the 1992 market share of those that exited was generally higher than the entrant s 1997 market share. We also found that group affiliated companies tended to be better capitalized and had higher quality capital backing the companies. We also see that concentration is generally lower today than in This can imply that previous entry reduced concentration or that there is a redistribution of premium volume within the industry. It appears, however, that the effect of entry may take time to be realized. Total assets and market share of entrants since 1990 are extremely small relative to the industry. This raises some interesting questions about why firms might start a new company. Group firms may have different motivations than single firms as groups may be readjusting their product portfolio or responding to regulation though the use of separate entities. An interesting extension would be to examine the rational for the formation of the new companies and to see how the various rationales relate to market share growth over time. it seems to take established companies a long time to achieve size in terms of market share or total assets, thus it appears that the market is not very contestable. This is not a foregone conclusion, however, as the link between entry and the ability to contest a market needs to be further explored. There are a number of shell companies with licenses in many states. The assessment of these firms to start-up and compete in a short time is essential to our understanding of the ease of entry to the market. 14

16 Bibliography ACLI, Life Insurance Fact Book 1998, (Washongton, DC: ACLI). Babbel, David F., The Price Elasticity of Demand for Whole Life Insurance, Journal of Finance, 40 (March 1985), Bain, J Barriers to New Competition (Cambridge, MA: Harvard University Press). Black, K. and H.D. Skipper, 1995, Life Insurance (Enlgewood Cliffs: Prentice Hall). Cummins, J. David, Denenberg, Herbert S., Scheel, William C., Journal of Risk and Insurance v39 n2 (June): Cummins, J. David, and Hongmin Zi Comparison of Frontier Efficiency Methods, Journal of Productivity Analysis 10: D Arcy, S. and K. Lee Universal/Variable Life Insurance versus Similar Unbundled Investment Strategies. Journal of Risk and Insurance 54(September): Dionne, G. and Scott Harrington, 1992, An Introduction to Insurance Economics, in Foundations of Insurance Economics (Boston, MA: Kluwer Academic Publishers). Grace, M. and S. Timme, 1992, An Examination of Cost Economies in the U.S. Life Insurance Industry, 59 (March): Harrington, S., 1982, Operating Expenses for Agency and Non-Agency Life Insurers: Further Evidence. Journal of Risk and Insurance 69 (June): Joskow, P Cartels, Competition and Regulation in the Property-Liability Insurance Industry, Bell Journal of Economics 4 (Autumn): Kellner, S, and F. Mathewson. 1983, entry Size Distribution, Scale and Scope Economies in the Life Insurance Industry. Journal of Business 12: Lewis, Frank D Dependents and the Demand for Life Insurance, American Economic Review 79:3 (June), Mathewson, G., Information, Search and Price Variability in the Individual Life Insurance Contracts, Journal of Industrial Economics 32: Outreville, J.F The Economic Significant of Insurance in Developing Countries. Journal of Risk and Insurance 58 (September): Pissarides, C.A., "The Wealth-Age Relation with Life Insurance," Economica 47 (November 1980), Puelz, Robert, "A Process for Selecting a Life Insurance Contract," Journal of Risk and Insurance (March 1991). 15

17 Reece, W. S. 1992, Output Price Indices for the U.S. Life Insurance Industry. 54 Journal of Risk and Insurance 53 (March): Scherer, F. M. and D. Ross, Industrial Market Structure and Economic Performance (Boston, MA: Houghton-Mifflin). Weiss, M. A Analysis of Productivity at the Firm Level: An Application to Life Insurers. Journal of Risk and Insurance 53 (March): Yaari, M.E Uncertain Lifetime, Life Insurance and the Theory of the Consumer. Review of Economic Studies 32 (April): Yuengert, A The Measurement of Efficiency in Life Insurance: Estimates of a Mixed- Normal Gamma Error Model. Journal of Banking and Finance 17 (February):

18 6,000,000 Figure 1 Real Life Insurance in Force over Time (in 1984 $1000s) 5,000,000 Credit Ordinary Ordinary and Group 4,000,000 3,000,000 2,000,000 Group 1,000,000 Industrial Real Ordinary Real Group Real Ind. 17

19 Figure 2 Percent and Cumulative Percent of Assets (in 1997) by Year of Start-up 9.00% 8.00% 7.00% 6.00% Percent 5.00% 4.00% 3.00% 2.00% 1.00% 0.00% % of Total Assets Cumulative % of Assets 18

20 Figure Median Assets by Year of Start Up, By Group and Non-Group Affiliation 120,000,000 Median Total Assetsof Start Up in ,000,000 80,000,000 60,000,000 40,000,000 20,000, Non-Group Affiliated 6,118,345 2,845,597 4,312, ,343 3,706,547 8,278,556 7,035,454 4,699,486 2,744,716 2,581,231 Group 22,864, ,400,000 8,992,892 20,948,944 20,340,374 9,105,051 12,462,121 10,161,085 14,799,199 9,184,458 Year of Start Up 19

21 Figure 4 Median 1997 RBC By Year of Start Up, by Group and Non-Group Affiliation 50,000 45,000 Medain RBC of Start Ups in ,000 35,000 30,000 25,000 20,000 15,000 10,000 5, Non-Group Affiliated 5,104 5, ,376 17, , ,404 Group 14,104 44, ,333 5,255 13,861 5,400 16,526 28,288 10,887 Year of Start Up 20

22 Figure 5 Market Share of Start-ups in 1997 (at Group Level) 20% 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% Start-up Year Life Insurance Market Share Annuity Market Share 21

23 Figure 6 Firm Level Market Share in 1997 of Start-Ups by Year of Start-Up Market Share Year of Start-Up Life Market Share Annuity Market Share 22

24 Table 1 Distribution Systems and Premiums Written, 1997 No of Industrial Ordinary Individual Credit Group Group Group Credit Firms Total Life Life Life Annuity Life Life Annuity AH AH None Listed % 0.00% 0.89% 0.01% 1.10% 0.15% 0.66% 0.13% 1.86% 0.12% Agency % 93.76% 82.09% 51.15% 79.50% 52.88% 78.43% 73.67% 53.91% 53.21% Broker % 1.19% 5.35% 22.43% 11.84% 2.55% 8.71% 17.31% 18.08% 1.44% Direct % 0.77% 5.11% 15.06% 4.67% 25.71% 8.66% 4.96% 3.83% 20.68% Inactive % 0.01% 0.74% 0.25% 0.31% 0.04% 0.16% 0.23% 0.45% 0.06% Mass Mkt % 0.00% 0.33% 0.44% 0.08% 1.10% 0.65% 0.93% 0.90% 1.28% NA % 4.15% 1.88% 5.81% 0.59% 6.98% 2.31% 0.73% 19.56% 5.56% Other % 0.11% 3.61% 4.84% 1.91% 10.59% 0.43% 2.04% 1.41% 17.65% Source: NAIC Annual Tapes and A.M. Best Key Rating Guide,

25 Table 2 Levels of Assets by Category form Flow of Fund Accounts, $Billions in nominal terms Panel A. Total Financial Assets Mutual Fund Shares Pension Fund Reserves Corp Equities Life Insurance Reserves Deposits US Govt Securities , , , %change 132% -5% 37% 61% 149% 231% 107% Panel B. Total Financial Assets Mutual Fund Shares Pension Fund Reserves Corp Equities Life Insurance Reserves Deposits US Govt Securities , ,709 1, , , ,265 3, %change 114% 904% 122% 70% 91% 228% 244% Panel C. Total Financial Assets Mutual Fund Shares Pension Fund Reserves Corp Equities Life Insurance Reserves Deposits US Govt Securities , , ,267 4, ,247 2,498 6, ,155 8, %change 82% 326% 147% 72% 27% 118% 28% Source: Board of Governors of the Federal Reserve System, Flow of Funds Accounts of the U.S. ( 24

26 Table 3 Real Life Insurance In Force and Mix of Insurance In Force Amount in Force (in Real 1984 $1,000) Year Ordinary Group Industrial Credit Total ,893,634 1,421,023 99, ,464 3,613, ,136,498 1,916,693 43, ,504 4,297, ,106,337 2,871,849 18, ,777 7,186, ,790,617 3,287,715 11, ,246 8,221,787 Percent of Business Year Ordinary Group Industrial Credit Total % 39.32% 2.76% 5.52% % % 44.60% 1.02% 4.67% % % 39.96% 0.26% 2.64% % % 39.99% 0.14% 1.61% % Source: ACLI, Life Insurance Factbook,

27 Table 4 Income Elasticity, Simple National Income Elasticities for Lines of Insurance Real Ord. Life in Force Real Industrial In Force Real Group In Force Real Credit In Force Real Total In Force Source: NAIC Data and Authors' Calculations Regression estimated was: Log(Yit)=a+b*log(GDPt)+eit Log(Yit) is the log of real premiums for a given line. Log(GDPt)=log of real gdp. 26

28 Whole Life Table 5 Ordinary Life Insurance in Force, 1997 ($ Millions) % of All Life Face Amount Insurance Variable Life 111, % Other fixed Premium Products 2,623, % Universal Life 2,246, % Variable-Universal Life 838, % Total Whole Life 5,819, % Term Life Decreasing 617, % Other Term 4,437, % Term Additions 68, % Extended Term 109, % Total 5,233, % Endowment Insurance 18, % Total Individual Ordinary Life 11,071, % Group Whole Life 579, % Term 5,615, % Total Group 6,195, % Total Ordinary Life Insurance 17,266, % Ordinary Annuities (billions of $) Individual Group % of Considerations Considerations Variable % Fixed % Other % Total % Variable % Fixed % Other % Total % Total % Source: ACLI Factbook,