After the Storms: Property Insurance Markets in Florida

Transcription

1 After the Storms: Property Insurance Markets in Florida Draft: December 18, 2006 Martin F. Grace Robert W. Klein Center for Risk Management & Insurance Research Georgia State University Contact Information: Robert W. Klein Center for RMI Research Georgia State University P.O. Box 4036 Atlanta, GA Tel: Note: The authors express their appreciation to a number of people and organizations in helping to provide information and data used in this paper, including Komal Gaba, James Bowman, the Wharton Risk Center Extreme Events Project, the Florida Office of Insurance Regulation, the Property Casualty Insurance Association of America and the Insurance Services Office. The opinions expressed in this paper are solely the authors and do not necessarily represent the views of any other persons or organizations.

2 After the Storms: Property Insurance Markets in Florida Abstract The intense hurricane seasons of 2004 and 2005 have caused substantial instability in property insurance markets in coastal states with the greatest pressure in Florida and the Southeast. The developments in these states have generated considerable concern and some controversy among various groups of stakeholders. As both insurers and property owners seek to adjust and respond to changing circumstances, public officials are wrestling with how to deal with market changes and looking for remedies that will ease the pressures on insurers and consumers. In this context, it is important to understand how property insurance markets have been changing and analyze the forces driving their dynamics. This paper presents an analysis of property insurance market conditions and developments in Florida, which continues to be the state facing the most severe pressure due to increased hurricane risk. Our analysis documents the significant restructuring of this market, the rising price of and tighter availability of insurance, and the substantial losses suffered by insurers that have adversely affected the supply of coverage. This paper builds on previous papers written by the authors and will be succeeded by subsequent papers that will expand the analysis to other states as well as probe market forces and conditions in greater depth. I. Introduction The intense hurricane seasons of 2004 and 2005 have caused substantial instability in property insurance markets in coastal states with the greatest pressure in Florida and the Southeast. The increased risk of hurricanes striking the US prompted significant changes in these same markets beginning in the early 1990s, but the particularly intense hurricane activity during the last two years has led to another wave of market adjustments. Both the loss shocks of the storm seasons as well as the belief that hurricane risk has risen to a new, higher level (higher than that perceived prior to 2004) have been major drivers of the recent market adjustments. Following Hurricane Andrew in 1992, rates increased gradually (as regulators allowed them to do so) and insurers managed their exposures more carefully (see Grace, Klein and Kleindorfer, 2004). In Florida, there were also significant changes in the 1

3 structure of the homeowners insurance market as some insurers exited or retrenched and others came to in to fill the gap. The early 1990s also witnessed the increasing use of catastrophe modeling as a means to assess, manage and price hurricane risk. It appeared that by 2004 insurance markets had stabilized to a large degree and would remain relatively stable. However, the four major hurricanes that struck the Gulf Region in 2004 began to destabilize insurance markets and the tragic storm season of 2005 led by Hurricane Katrina further exacerbated market problems. The 2005 season was the most intense on record with 26 named storms and 14 designated as hurricanes (Insurance Information Institute, 2005). This has led to another market shakeup as insurers have sought to implement further rate increases and other adjustments to respond to a perceived increase in hurricane risk. Understandably, the new situation has generated considerable concern and some controversy among various groups of stakeholders. In the face of increased risk and uncertainty, insurers are seeking to establish rate structures and portfolios of exposures that will ensure their economic viability in the short and long term. Reinsurers are also making substantial adjustments their prices have increased as new capital has flowed in to replace recent losses and to at least partially respond to the increased demand for catastrophe reinsurance. Affected property owners are very unhappy about sharp premium hikes and the diminished availability of coverage. 1 Legislator and regulators are squeezed between insurers needs and consumers growing displeasure as they seek to develop policies that will sustain viable insurance markets as well as their political support. Although the relatively benign storm season of 2006 has been a welcome relief 1 A series of articles in Florida newspapers document the growing displeasure of homeowners about the rising price and tighter availability of insurance. 2

4 to insurers and others, it also has undermined public acceptance of insurers rate increases and other actions, as well as increased political pressure on government officials to constrain insurers and to ease conditions for consumers. This paper is one in a series of papers by the authors that analyze property insurance market conditions and developments that are strongly affected by hurricane risk. In this draft, we present a preliminary analysis of data and information accumulated to date with the main focus on Florida. Subsequent iterations of this paper will extend the analysis to other states and probe market developments in greater depth and detail. Also, as new data become available, it will be possible to update our understanding of more recent developments. The next section of this paper reviews the environmental, economic and regulatory context for property insurance. Sections III and IV examine the structure, conduct and performance of the homeowners insurance market in Florida with particular emphasis on recent developments. A second paper by Klein (2006) examines associated regulatory issues and policies. The last section of this paper concludes with a summary of the key observations and the plans for further research. II. Hurricane Risk and Insurance Markets To understand developments in property insurance markets in Florida, one must understand the environmental, economic and regulatory context in which these markets function. The environmental context comprises short-term and long-term weather patterns and cycles principally the frequency and intensity of tropical storms and hurricanes striking the state. The natural environment interacts with the important aspects 3

5 of the economic environment the growth and geographic distribution of commercial and residential property development. Together these factors heavily influence property exposed to hurricanes and the demand for and supply of insurance. The governmental framework overlays and affects insurance markets in a number of ways and also influences the pattern of economic development and its vulnerability to hurricanes. A. Shifting Risk and Storms History and meteorological science document the cyclical nature of weather patterns and storm activity. The recorded history of storm activity is relatively short but still reflects its cyclical nature. Figure 1 plots the number of hurricanes striking the U.S. by decade from and also distinguish the number of more severe Category 3-5 hurricanes. 2 Hurricane frequency and intensity increased over the first three decades of this period and then fell during the next three decades. Storm activity intensified again starting in the late 1980s through the present. It is important to distinguish between short-term and long-term weather patterns. Storm activity can be relatively low during any given year in a long-term cycle of more intensive activity. This reflects the many factors affecting storm activity in any slice of time. This is illustrated by the very active storm seasons of 2004 and 2005 followed by what has been a relatively quiet storm season in A detailed discussion of weather patterns is beyond the scope of this paper, but the emergence of a rapidly developing El Nino combined with large-scale weather patterns over the southeastern US have been cited by the National Oceanic and Atmospheric Administration (NOAA) principal factors 2 The reader should note that these are hurricanes that struck the US and do not include other hurricanes in the Atlantic and Gulf areas that did not strike the US. Hurricane intensity is measured on the Saffir- Simpson scale (see NOAA, 2006). 4

6 30 Figure 1 U.S. Hurricane Strikes By Decade All Major -Category 3-6 Number of Hurricanes Source: NOAA 5

7 that decreased the number of hurricanes and tropical storms and tended to push them away from the US (NOAA, 2006). Hence, while storms tend to follow cyclical patterns there is still a significant random component to the occurrence of damaging hurricanes in any given year or even in several years depending on the confluence of both short-term and long-term weather variables. Nature s capriciousness is further demonstrated by the nature and paths of the hurricanes that do occur. There can be a high number of storms in a given year but the damages they cause are determined by where they strike and their other characteristics. By the same token, one severe storm striking a highly developed area could cause a large amount of economic losses. This random nature of storm activity complicates insurers efforts to supply insurance coverage under relatively stable terms that will protect their short-term and long-term viability. The ability to develop credible estimates of the risk of hurricanes and the limits of catastrophe risk modeling (i.e., parameter uncertainty ) further affect insurers approach to hurricane-prone insurance markets. It is not surprising that insurers appear to differ in their assessments of the level and nature of the hurricane risk they face in coastal areas, although there is a general consensus that the risk has increased. B. Economic Development Storm activity is only one element of the conditions that determine the nature of catastrophe risk and the potential economic losses from hurricanes. The second important factor is the pattern of economic development. During the active storm cycle in , coastal areas were less developed so storms striking these areas caused less damage. During the next three decades there was considerable economic growth in these 6

8 areas but storm activity had lessened and does not appear to have been a major impediment to growth. Hence, considerable development occurred when hurricane losses and insurance rates were relatively low. A myopic sense of security contributed to large movements of people and the associated property development that would be at risk when storm activity began increasing in the 1980s. It also appears that little attention was paid to hazard mitigation (e.g., building hurricane-resistant homes) that also has contributed to the catastrophe risk problem. 3 Table 1 shows the increase in population growth from 1980 to 2003 in coastal areas of the ten leading states for this activity (Insurance Information Institute, 2006). As can be seen from the table, Florida and Texas ranked 2 nd and 3 rd in terms of coastal population growth. Figure 2 compares population levels between 1970 and 2000 in selected Florida counties. Table 2 compares the amount of residential property insured (homeowners insurance) by county between 1997 and 2006 (coastal counties are in bold type). As can be seen from these figures, Florida has a large amount of its population and residential property concentrated in several coastal areas that also face high hurricane risk. This pattern of economic development has contributed to the economic damages caused and the number of households affected by storms striking these areas as well as their need for insurance coverage. Consequently, the pressure on property insurance markets rises because of economic development in areas subject to greater hurricane risk. Insurers and reinsurers are expected to increase the supply of insurance to meet greater demand but they heighten 3 Goodnough, A. (2006), As Hurricane Season Looms, State Aim to Scare, The New York Times, May 31. 7

9 their catastrophe risk if they add to their exposures in high-risk areas. This strains existing risk transfer and diversification mechanisms and tightens the availability of insurance coverage. Table 1 Leading States in Coastal Population Growth Total Change Rank State (Millions Persons) 1 California Florida Texas Washington Virginia New York New Jersey Maryland Michigan Massachusetts 0.7 Source: Insurance Information Institute 2,500,000 2,000,000 Figure 2 Population Growth in Selected Florida Coastal Counties ,500,000 1,000, ,000 0 Miami-Dade Palm Beach Pinellas County County County Source: data from Bureau of Labor Statistics Brevard County Lee County Sarasota County Manatee County St. Lucie County 8

10 County Table 2 Amount of Homeowners Insurance by County in Florida ($) (sorted by 2006 exposures; coastal counties in bold type) % Change County % Change Palm Beach 51,245,380,993 94,162,686, % Highlands 2,842,623,519 5,851,307, % Broward 48,506,531,343 88,186,850, % Nassau 1,689,121,905 5,060,525, % Hillsborough 28,687,742,939 80,068,350, % Sumter 676,336,864 4,653,297, % Orange 31,086,359,611 77,819,385, % Walton 993,853,165 2,787,725, % Dade 46,083,110,440 70,800,728, % Putnam 1,260,044,465 2,517,287, % Pinellas 30,300,055,866 56,808,320, % Columbia 1,038,090,200 2,314,638, % Duval 23,993,888,069 55,836,399, % Jackson 818,792,047 1,658,287, % Lee 16,770,033,307 46,957,899, % Gadsden 724,595,314 1,496,155, % Brevard 18,042,019,710 40,793,835, % Okeechobee 618,691,411 1,307,428, % Seminole 16,343,276,080 35,714,282, % Levy 536,122,975 1,177,661, % Sarasota 12,985,343,432 34,158,728, % Desoto 545,207,944 1,164,566, % Volusia 16,119,690,076 34,072,901, % Suwannee 479,320,656 1,120,105, % Polk 13,943,798,107 32,173,942, % Wakulla 342,414,765 1,095,716, % Collier 9,685,396,136 30,269,086, % Hendry 552,103,390 1,080,158, % Pasco 11,207,665,171 26,934,800, % Baker 344,038, ,244, % Lake 6,849,790,715 24,490,094, % Bradford 401,238, ,956, % Manatee 7,317,090,348 24,350,281, % Washington 301,192, ,183, % St. Johns 5,353,057,175 19,301,840, % Taylor 353,407, ,829, % Marion 6,916,004,022 18,823,597, % Hardee 411,758, ,900, % St. Lucie 6,488,112,894 17,398,194, % Jefferson 241,693, ,207, % Leon 8,210,621,080 17,206,369, % Monroe 659,240, ,761, % Osceola 4,919,815,917 17,024,808, % Madison 251,478, ,702, % Charlotte 7,010,149,343 16,188,710, % Gulf 274,339, ,758, % Escambia 8,036,033,925 15,440,937, % Holmes 259,897, ,497, % Martin 7,386,738,707 14,653,900, % Gilchrist 179,516, ,879, % Clay 4,970,256,028 13,972,487, % Franklin 221,914, ,226, % Okaloosa 5,284,301,711 13,353,846, % Calhoun 194,390, ,369, % Alachua 5,992,695,083 12,730,315, % Dixie 138,434, ,609, % Hernando 5,319,503,642 11,578,667, % Glades 120,138, ,156, % Citrus 4,466,681,782 11,050,521, % Union 118,025, ,321, % Indian River 5,020,738,479 10,517,963, % Hamilton 117,330, ,398, % Santa Rosa 4,397,084,908 10,231,789, % Liberty 83,140, ,546, % Bay 4,297,799,042 9,488,599, % Lafayette 81,805, ,246, % Flagler 2,331,552,997 8,589,551, % TOTAL 503,438,620,448 1,133,649,335, % Source: FLOIR 9

11 C. Insured and Uninsured Losses While economic losses from hurricanes are highly variable, the record shows that catastrophe losses have increased substantially over the last 15 years, coincident with the increased frequency and intensity of storms and coastal development. Figure 3 plots insured catastrophe losses from (Insurance Information Institute, 2006). Although the losses shown arise from all perils, including earthquakes and terrorism, hurricanes account for the lion s share of the catastrophe losses over this period. This is evident from Table 3 which lists the 10 most costly US catastrophes measured in 2005 dollars (Insurance Information Institute, 2006). Eight of the 10 catastrophes were caused by hurricanes which account for 74 percent of the total losses from these events. This observation is not intended to minimize the threats from other catastrophe perils. 4 At the same time, hurricane losses are the primary source of recent industry catastrophe losses and, among natural perils, hurricane risk is the primary source of pressure on property insurance markets along the Atlantic and Gulf coasts. It should be noted that the losses shown in Figure 3 and Table 3 are insured losses and do not reflect uninsured or total economic losses. Uninsured and total economic losses are more difficult to determine but a rough rule of thumb is that insured losses tend to account for about 50 percent of total losses. While the retention of some losses by property owners is probably efficient, there is also the possibility that the distribution and burden of some uninsured losses reduce social welfare. An examination of this issue is 4 Of course, the existence of other catastrophe perils places demands on insurance and reinsurance capacity and hence indirectly affect the supply of insurance to cover hurricane risk. 10

12 Unadjusted Current Dollars Figure 3 Insured Losses for US Catastrophes ($M) Hurricane Katrina Hurricane Andrew 9/11 Attacks Northridge Earthquake Source: Insurance Information Institute Table 3 The Ten Most Costly Catastrophes in the US Insured Property Loss ($M) Dollars When In 2005 Rank Date Event Occurred Dollars 1 Aug Hurricane Katrina $40,600 $40,600 2 Aug Hurricane Andrew $15,500 $21,576 3 Sep Terrorist Attacks $18,800 $20,732 4 Jan Northridge Earthquake $12,500 $16,473 5 Oct Hurricane Wilma $10,300 $10,300 6 Aug Hurricane Charley $7,475 $7,728 7 Sep Hurricane Ivan $7,110 $7,351 8 Sep Hurricane Hugo $4,195 $6,607 9 Sep Hurricane Rita 2 $5,627 $5, Sep Hurricane Frances $4,751 $4,595 Source: Insurance Information Institute 11

13 beyond the scope of this paper but it should be noted that the functioning of insurance markets affects the amount of uninsured losses and, in turn, the problems created by uninsured losses can increase political and governmental pressure on insurance markets. D. Market and Regulatory Responses The sections below discuss insurance market developments in greater detail but it is helpful here to provide a brief overview of what has been occurring. After the intense storm season of 2004, it became evident that insurers were reassessing their catastrophe risk in the Southeast and Gulf region and were beginning to make adjustments. These adjustments mainly took the forms of filings for modest rate increases and also some rethinking of insurers portfolio of exposures in high risk areas. It is possible that some insurers began to tighten their supply of insurance towards the end of 2004 and the beginning of The second wave of storms and high losses that occurred in 2005 appear to have greatly increased many insurers concerns about the catastrophe risk they faced, the adequacy of their rate structures and the amount of their exposures. As insurers and reinsurers assessed their losses from the 2005 storms, their pricing and underwriting adjustments escalated. A number of insurers filed for fairly large rate increases and decreased their exposures in high-risk areas. Insurer responses have varied as some initiated stronger pullbacks while others retrenched to a more modest degree. A few insurers are positioned for and have sought to expand their business in these areas to take advantage of the higher prices and policies shed by other insurers. Understandably, insurers with the greatest amounts of exposures in high-risk areas tended to retrench more than insurers with fewer exposures (see Grace, Klein and Liu, 2006). 12

14 Regulators responses to insurers actions have varied as well as evolved. It appears that the initial wave of filed rate increases in 2004 through early 2006 were approved for the most part although they were subject to some constraints (see Klein, 2006). However, most recently, further insurer rate hikes have been challenged and disapproved or reduced by regulators. A combination of growing consumer displeasure over previous rate increases as well as the lack of damaging hurricanes in 2006 are probably influencing regulators resistance to further rate hikes. Still, it appears that regulators do accept the notion that hurricane risk is higher than that perceived prior to 2004 and they continue to call for federal assistance in creating a federal catastrophe reinsurance program (NAIC, 2005). III. Insurance Market Structure in Florida The next three sections dissect insurance market developments using an established industrial organization approach the structure-conduct-performance framework. The basic notion underlying this framework is that structure affects conduct and conduct affects performance. However, it is also understood that path of effects moves in both directions, i.e., conduct and performance can affect structure. Furthermore, this framework is harnessed to analyze developments in a market that is subject to several factors that are not typically found in other industries, requiring some creative extension and application of standard methods. We look at market structure from both a company and a group level to examine how business is being shifted among companies within the same group. We also assess market structure using both premiums and amounts of insurance as measures of quantity. 13

15 A. Insurer Cost Conditions The cost conditions facing firms are a major determinant of the number and size distribution of firms within an industry or market. Typically, economists analyze the relationship between output and cost to determine how many firms can viably operate in a market and the optimal size of a firm in terms of the quantity of a good or service it produces. A typical firm cost function might reflect increasing returns to scale up to some level of output (average costs decline over this range of output) and decreasing returns to scale beyond this level of output (average costs increase past this point). The amount of fixed costs or sunk investments and the optimal output level, if high, can potentially impede entry by new firms. Cost functions in many industries, including insurance, reflect decreasing average costs over an initial range of output and rising average costs beyond this point. The low point in the average cost curve is the minimum efficient scale (MES). This is reflected in the shape of the typical average cost curve which is convex or U-shaped as shown by AC ncr (the average cost curve when there are no correlated exposures or catastrophe risk) in Diagram 1. The explanation for a U-shaped cost curve is that the firm initially benefits from spreading fixed costs over a larger amount of output but at some point this effect is offset by rising variable costs due to rising input prices or other factors that cause the productivity of inputs to fall as production is pushed beyond a certain level. 5 However, the problem of correlated risk exposures or catastrophe risk adds a significant new dimension to insurer cost functions. As an insurer increases the amount of 5 For example, when production is pushed beyond some point communication and coordination among workers and units within a firm can suffer leading to diminishing productivity. See Varian (1992) for an explanation of firm cost functions. 14

16 insurance it sells in a given geographic areas, its risk of catastrophic losses increase. This means that variable costs increase as an insurer adds correlated risk exposures. The increase in variable costs can be reflected in the insurers need to carry additional surplus, 15

17 buy reinsurance, or pay a higher return to its owners to compensate them for the higher risk retained by the insurer. The important implications of this conception of insurers cost functions are twofold: 1) the cost function pivots upward; and 2) the shape of the cost function changes. Specifically, the slope of the average cost curve to the left of the MES becomes more shallow, the MES shifts to the left (i.e., decreases), and the average cost curve climbs more steeply to the right of the MES. The average cost curve with catastrophic risk is depicted as AC cr in Diagram 1. These changes in an insurer s cost function will compel it to charge a higher price for the insurance it sells and its maximum efficient output level will be lower than if its loss exposures were not correlated. In terms of market structure, the catastrophe risk cost factor would be expected to decrease the market shares of the leading insurers, all other things equal. The leading insurers will find it more costly to acquire a large share of the market than if catastrophic risk was not a factor. Small insurers also may find it difficult to sustain operations in catastrophe-prone markets because they lack sufficient capital and geographic diversification to counter the risk of correlated exposures they would encounter. Hence, we would expect that market shares of the leading insurers will decrease and some smaller insurers may also exit the market. Overall, we would expect measures of market concentration to decrease as they tend to be based on or dominated by the market shares of the leading insurers. Of course, in the real world, the cost factors that affect the supply of insurance and market structure are more complex than what we have described above. For example, insurers also must consider economies of scope, i.e., the efficiencies gained from selling 16

18 both home insurance and auto insurance to the same household. If an insurer is unwilling to sell home insurance to some homeowners, they lose the associated scope economies from selling auto insurance to the same homeowners. Also, these homeowners may decide to move their auto insurance to another carrier. There are other considerations such as the sunk costs associated with establishing a reputation and distribution networks and adverse regulatory responses. These other factors may dampen the hypothesized structural effects of higher costs due to catastrophe risk, but it is quite possible that they will not eliminate them. Hence, we believe the predictions in the preceding paragraph should still hold. B. The Regulatory Factor The government framework under which firms operate also has significant effects on market structure, conduct and performance. The regulation of insurers is particularly intensive and, hence, can greatly influence insurance markets. Regulation is discussed in greater detail in Klein (2006) but we note several important regulatory factors here. One such factor is the regulation of insurers entry into and exit from a market. The evidence suggests that regulators impose some costs on market entry and these costs, in turn, could have impede entry to some degree (Klein, 1995). In turn, regulators can also make it costly to exit markets. In particular, some states require an insurer to exit all lines of business if it seeks to exit a line subject to availability problems, such as home insurance. This policy could delay the exit of insurers from a state market but not ultimately prevent 17

19 it. 6 At the same time, raising the cost of exit can have the undesired effect of discouraging entry. The extent to which regulators constrain insurers discretion with respect to pricing, policy terms and underwriting can also affect entry and exit and other aspects of market structure. Severe regulatory constraints can deter entry and also hasten insurers retrenchment or exit from a market. As we discuss below, after an initial period of severe regulatory constraints following Hurricane Andrew, it appears that Florida s regulators approval of gradual rate increases during the 1990s helped to encourage new insurers to enter the market and may also have eased pressure on established insurers to retrench or withdraw from the market (Grace, Klein and Kleindorfer, 2004). However, regulators continued compression of rates in some high-risk areas and more recent resistance to further rate increases could push insurer to retrench from the market to a greater degree than they would under more flexible regulatory policies. C. Entries, Exits and Market Concentration The effects of increased hurricane losses and risk on the structure of the Florida market are still developing and there is a lag in the data available to track market changes. Still, it is important to glean what we can from these data and offer observations on how insurers appear to be adjusting their market positions. We can examine data through 2005 and augment these data with anecdotal observations on insurers actions in We begin by looking at shifts in the market positions of leading writers of homeowners insurance in Table 4(a). 6 As discussed by Grace, Klein and Kleindorfer (2004), it is reasonable to expect that there is a point where the losses from staying in a market exceed the costs from exit, even with the additional constraints on and costs of exit. 18

20 Table 4(a) ranks the top 20 homeowners insurers (on a group basis) in Florida in 2005 and also shows their market rankings and shares for the years 1992, 1995 and We do not include the Citizen s Property Insurance Corporation (CPIC) in this aspect of our analysis as it is a residual market mechanism and our interest here is in the voluntary market in which insurers compete and make decisions about how much insurance they are willing to supply. We can see from this table that there have been dramatic changes in the Florida market since The top two groups in 2005 State Farm and Allstate were also the top two groups in However, their combined market share has Table 4(a) Changes in Leading Insurers' Market Share Florida , 1995, 2000, Name Rank DPW MS(%) Rank DPW MS(%) Rank DPW MS(%) Rank DPW MS(%) State Farm Group 1 1,175,850, ,296, ,718, ,427, Allstate Ins Group 2 495,663, ,641, ,679, ,329, Poe Financial Group 3 402,430, ,322, Tower Hill Ins Group 4 285,914, Nationwide Corporation 5 274,919, ,675, ,912, ,595, USAA Group 6 253,944, ,088, ,130, ,171, Liberty Mutual Group 7 172,197, ,714, ,536, ,534, St Paul Travelers Group 8 124,905, ,445, ,474, ,664, Chubb & Son Inc 9 124,290, ,324, ,015, ,874, American International Group ,271, ,442, ,557, ,771, Hartford Fire & Casualty Group ,479, ,738, ,881, ,288, ARX Holding Corp Group ,834, ,120, GeoVera Holdings Inc Group ,695, Hannover Group ,706, ,849, United Prop & Cas Ins Co ,978, ,473, Gulfstream Prop & Cas Ins Co 16 93,418, Universal Insurance Group 17 81,510, Southern Farm Bureau Casualty 18 78,785, ,636, ,734, ,781, st Century Holding Group 19 77,513, Vanguard Fire & Cas Co 20 73,489, ,630, Source: NAIC Financial Database 19

21 dropped from 50.9 percent to 29.9 percent. It is apparent that these two insurers have significantly reduced their relative presence in the Florida market (as measured by premiums). This does not mean that these insurers exposures in Florida have necessarily decreased, but the increase in their exposures has not increased at the same rate as the expansion of total exposures in the state. This development is not surprising given these insurers expressed need to limit their catastrophe exposures to what they consider more sustainable levels. It is also interesting to note that while State Farm s market share remained essentially unchanged since 2000, Allstate s share declined from 11.2 percent to 8.9 percent. This appears to be consistent with Allstate s stated intention to substantially reduce its concentration of exposures in high-risk areas to a level that it believes is more economically viable. 7 Other mid-tier insurers appear to have essentially maintained the same market shares over this period through Another significant development has been the entry/expansion of some insurers as other companies have retrenched or withdrawn from the market. Ten of the top 20 groups in 2005 entered the market after This reflects several phenomena. Two important factors were the startup of several new insurers in Florida during the 1990s and entries by other established insurers. The retrenchment or exit of some insurers created opportunities for other insurers to fill the gap. However, entry into the Florida market carries risk, especially for insurers with large portions of their portfolios in the state. This was demonstrated by the rapid rise of the 3 rd and 4 th leading groups in 2005 the Poe and Tower Hill groups. Poe was hit hard by the 2004 and 2005 storm seasons and has been placed into receivership. Tower Hill 7 See, for example, Allstate Considers More Cancellations, Tampa Tribune, May 19,

22 has been more diversified with business throughout the Southeast but it also has been stressed by the recent storm seasons. This demonstrates the drawbacks of relying heavily on local or regional insurers to fill large gaps left by larger, national insurers. Smaller insurers can bolster their capacity with extensive use of reinsurance but this comes at a cost along with some retention of risk at a primary level that may be unavoidable. Several national and regional insurers entered or increased their market presence but their market shares were still relatively modest in 2005, i.e., less than 3 percent. This may reflect a more reasonable strategy of acquiring small, digestible shares of a potentially lucrative but risky market by more broadly diversified insurers, and not going beyond this in order to limit their catastrophe risk to reasonable levels. The associated trends in market concentration from are shown in Table 4(b). The combined market share for the top 4 groups in Florida decreased steadily from 55.3 percent to 42.2 percent. This is likely to decline further in 2006 given Allstate s efforts to reduce its exposures and Poe s insolvency. The combined market shares for the top 8 and top 20 insurer groups also declined over this period but to a lesser degree and these measures contain more insurers who have experience smaller decreases in their market shares as well some insurers who have increased their market shares. The HHI decreased from 1,440 in 1992 to 776 in 2000, increased, then fell again to an alltime low of 714 in While the HHI includes all insurers in its calculation, it weights the market shares of the larger insurers more heavily so it is not surprising that it has also declined given the decrease in the market shares of the market leaders. The decline in market concentration and the relative changes for the market leaders versus the mid-tier insurers is consistent with what we would expect to see based 21

23 Table 4(b) Homeowners Insurance Market Concentration Florida: Year CR4 CR8 CR20 HHI % 70.9% 85.2% 1, % 71.6% 86.6% 1, % 71.9% 86.7% 1, % 72.2% 87.4% 1, % 71.5% 87.0% 1, % 63.8% 82.9% 1, % 64.9% 83.1% % 62.7% 80.0% % 61.2% 78.7% % 60.1% 78.4% % 59.2% 79.6% % 59.9% 81.7% % 61.4% 83.8% % 60.0% 78.7% 714 Source: NAIC Financial Database on our discussion of the impact of catastrophe risk on insurers cost functions and exposure management. One s view of whether this decline in concentration is good or bad depend on one s perspective. Normally, economists associate lower concentration with greater competition but the situation in Florida s homeowners insurance market is peculiar. While insurers may be competing to maintain a sustainable market share, many are not currently seeking to increase their market share through price and product competition. Also, homeowners who have been dropped or rejected by their preferred insurer would not view this as a favorable development. State Farm and Allstate have maintained larger shares of other markets because of characteristics that consumers apparently prefer. On the other hand, less concentration implies that there is a greater dispersion of exposures among carriers in Florida which could be viewed as a positive development in terms of greater diversification of risk. In markets subject to high levels of catastrophe 22

24 risk, lower concentration levels may be a necessary condition to allow insurers to maintain their catastrophe risk at manageable levels. Another caveat to the observation about market de-concentration in Florida is the movement of exposures from national carriers to smaller state or regional insurers that are not pooling risk across a wide base of countrywide exposures. One aspect of this phenomenon is the movement of exposures to Florida-only companies within the national groups to increase the transparency of their Florida performance. If the smaller state and regional insurers are making good use of reinsurance to spread their catastrophe exposure, then the positive objective of broader risk diversification would still be achieved. Single-state companies within national groups can receive support from their affiliates in the event of large losses, but as we explain below, these national groups cannot engage in sustained cross-subsidies of their Florida insureds. These are aspects of market structure trends that warrants more investigation. Some homeowners also must find new carriers to underwrite their coverage and others may be forced into residual market mechanisms, at least for a period of time. D. Insurer Exposure Patterns Insurers statewide market shares (based on premiums) tells one part of the story on changes in the structure of Florida s homeowners insurance market. Another important part of the story is the distribution of insurers shares of exposures (the amount of insurance coverage) in different areas in the state hurricane risk varies significantly among these areas so this aspect of market structure is important in terms of how insurers are managing their catastrophe risk as well as the associated implications for homeowners. 23

25 We were able to obtain data on insurers exposures by county by year/quarter from the Florida Office of Insurance Regulation (FLOIR). These data are reported by insurers to the FLOIR under its QUASR system. To make the data compilation more manageable, we requested and obtained data for first quarter of every year from This is sufficient to allow us to track trends and major changes in the distribution of insurers exposures at a county level. Tables 5(a) and 5(b) compare the company level HHI (based on amount of insured homeowners property) by county between 1997 and Tables 5(c) and 5(d) make the same comparisons at a group level. Table 6(a)-6(b) compares the market shares of the 10 leading insurers in Dade County in 1997 and 2006 at a company and group level. We see two important developments from these data. The first is decreased concentration in the higher risk counties (along the coasts). The second thing we see is that the leading insurers in the state have decreased their shares of exposures in the highest risk counties. This is evident in both the company level data and the group level data. We also see from Table 5 that new insurers have moved in to underwrite a significant proportion of exposures in Dade County. These are understandable developments as the leading insurers have had to reduce their catastrophe exposure to more manageable levels that do not impose excessive financial risks. Another observation is that the start-up insurers that formed in the mid-1990s had been forced to write a large share of portfolios in high risk areas as they took policies out of the residual market mechanism (see Grace, Klein, and Liu, 2006). However, when the 3-year requirement on retaining these policies expired, the majority of these insurers dropped a significant portion of these higher risk exposures and these exposures returned 24

26 to the residual market or were picked up by other entrants like the Poe and Tower groups. This action by the startups is understandable because they probably realized that they were holding a ticking time bomb and could not continue to hold a number of high-risk exposures without continuing to expose themselves to an excessive level of Table 5(a) Homeowners Exposure Company Level HHIs by County in 1997 & 2006 County HHI 1997 HHI 2006 Change County HHI 1997 HHI 2006 Change Alachua 1,340 1, Lake 1,419 1, Baker 1,553 2, Lee 1, Bay 1, Leon 1,319 1, Bradford 1,346 2, Levy 1, Brevard 2,221 1, Liberty 964 1, Broward 2, ,458 Madison 1,121 1, Calhoun 1,240 1, Manatee 1, Charlotte 1,791 1, Marion 1,030 1, Citrus 1,541 1, Martin Clay 1,578 1,573-5 Monroe 1,836 2, Collier 1, Nassau 1, Columbia 1,619 1, Okaloosa 1,615 1, Dade 2, ,596 Okeechobee 1,966 2, Desoto 2,197 2, Orange 1,588 1, Dixie 1,793 1, Osceola 2,102 1, Duval 1,605 1, Palm Beach 1, ,254 Escambia 1,754 1, Pasco 1,370 1, Flagler 1, Pinellas 1, Franklin Polk 1,995 1, Gadsden Putnam 1,278 2, Gilchrist 866 1, Santa Rosa 1,622 1, Glades 1,920 2, Sarasota 1, Gulf Seminole 1,664 1, Hamilton 1,185 1, St. Johns 1,341 1, Hardee 1,655 2, St. Lucie 1, Hendry 2,459 2, Sumter 1,022 1, Hernando 1,439 1, Suwannee 1,074 1, Highlands 1,701 1, Taylor 2,903 3, Hillsborough 1, Union 1,148 1, Holmes 1, Volusia 2,113 1, Indian River 1, Wakulla Jackson 1,083 1, Walton 1, Jefferson 1,251 2,399 1,147 Washington 1,093 1, Lafayette 1,535 1, Total 1, Source: data from FLOIR; authors' calculations 25

27 Table 5(b) Homeowners Exposure Company Level HHIs by County in 1997 & 2006 Counties Ranked in Descending Order of HHI Rank County HHI Rank County HHI Rank County HHI Rank County HHI 1 Taylor 2, Hernando 1,439 1 Taylor 3, Hamilton 1,153 2 Hendry 2, Lake 1,419 2 Desoto 2, Alachua 1,151 3 Dade 2, Flagler 1,409 3 Hendry 2, Osceola 1,142 4 Broward 2, Pasco 1,370 4 Monroe 2, Charlotte 1,139 5 Brevard 2, Bradford 1,346 5 Hardee 2, Citrus 1,105 6 Desoto 2, St. Johns 1,341 6 Glades 2, Liberty 1,087 7 Volusia 2, Alachua 1,340 7 Baker 2, Orange 1,068 8 Osceola 2, Sarasota 1,327 8 Jefferson 2, Pasco 1,060 9 Polk 1, Leon 1,319 9 Putnam 2, Marion 1, Okeechobee 1, Putnam 1, Okeechobee 2, Santa Rosa 1, Glades 1, Jefferson 1, Bradford 2, Washington 1, Palm Beach 1, Calhoun 1, Columbia 1, Gadsden Monroe 1, Bay 1, Volusia 1, Lee Dixie 1, Hamilton 1, Duval 1, Levy Charlotte 1, Union 1, Hernando 1, Pinellas Escambia 1, Nassau 1, Jackson 1, Broward Highlands 1, Madison 1, Lafayette 1, Walton Pinellas 1, Levy 1, Sumter 1, Sarasota Seminole 1, Washington 1, Polk 1, Indian River St. Lucie 1, Jackson 1, Clay 1, Holmes Hardee 1, Suwannee 1, Madison 1, Nassau Santa Rosa 1, Manatee 1, Dixie 1, Flagler Columbia 1, Walton 1, Leon 1, St. Lucie Lee 1, Marion 1, Highlands 1, Dade Okaloosa 1, Holmes 1, Calhoun 1, Manatee Duval 1, Sumter 1, St. Johns 1, Collier Orange 1, Martin Suwannee 1, Hillsborough Clay 1, Liberty Union 1, Bay Baker 1, Gilchrist Seminole 1, Gulf Citrus 1, Gulf Escambia 1, Martin Lafayette 1, Franklin Brevard 1, Franklin Indian River 1, Gadsden Lake 1, Wakulla Collier 1, Wakulla Okaloosa 1, Palm Beach Hillsborough 1,493 Total 1, Gilchrist 1,169 Total 876 Source: data from FLOIR; authors' calculations 26

28 Table 5(c) Homeowners Exposure Group Level HHIs by County in 1997 & 2006 County HHI 1997 HHI 2006 Change County HHI 1997 HHI 2006 Change Alachua 1,451 1, Lake 1,611 1, Baker 1,960 2, Lee 1,710 1, Bay 1, Leon 1,414 1, Bradford 1,678 2, Levy 1,304 1, Brevard 2,354 1,351-1,003 Liberty 1,456 1, Broward 2,408 1,255-1,153 Madison 1,645 1, Calhoun 1,491 1, Manatee 1, Charlotte 1,896 1, Marion 1,236 1, Citrus 1,695 1, Martin 1, Clay 1,726 1, Monroe 2,553 2,561 8 Collier 1, Nassau 1, Columbia 1,751 1, Okaloosa 1,789 1, Dade 2, ,588 Okeechobee 2,035 2, Desoto 2,375 2, Orange 1,689 1, Dixie 1,994 1, Osceola 2,244 1,234-1,010 Duval 1,738 1, Palm Beach 1, ,108 Escambia 1,862 1, Pasco 1,495 1, Flagler 1, Pinellas 1, Franklin 1, Polk 2,079 1, Gadsden 1,030 1, Putnam 1,604 2, Gilchrist 1,208 1, Santa Rosa 1,762 1, Glades 2,117 2, Sarasota 1,424 1, Gulf 1, Seminole 1,774 1, Hamilton 1,643 1, St. Johns 1,510 1, Hardee 1,996 2, St. Lucie 1, Hendry 2,561 2, Sumter 1,234 1, Hernando 1,630 1, Suwannee 1,518 1, Highlands 1,890 1, Taylor 3,161 3, Hillsborough 1, Union 1,569 1, Holmes 1,314 1, Volusia 2,274 1, Indian River 1, Wakulla Jackson 1,314 1, Walton 1,339 1, Jefferson 1,686 2, Washington 1,267 1, Lafayette 2,599 2, Total 1, Source: data from FLOIR; authors' calculations 27

29 Table 5(d) Homeowners Exposure Group Level HHIs by County in 1997 & 2006 Counties Ranked in Descending Order of HHI Rank County HHI Rank County HHI Rank County HHI Rank County HHI 1 Taylor 3, Hamilton 1,643 1 Taylor 3, Escambia 1,391 2 Lafayette 2, Hernando 1,630 2 Desoto 2, Brevard 1,351 3 Hendry 2, Indian River 1,627 3 Hendry 2, Lake 1,331 4 Monroe 2, Flagler 1,620 4 Baker 2, Santa Rosa 1,258 5 Dade 2, Lake 1,611 5 Hardee 2, Alachua 1,257 6 Broward 2, Putnam 1,604 6 Monroe 2, Broward 1,255 7 Desoto 2, Collier 1,574 7 Glades 2, Osceola 1,234 8 Brevard 2, Union 1,569 8 Lafayette 2, Charlotte 1,224 9 Volusia 2, Hillsborough 1,560 9 Jefferson 2, Walton 1, Osceola 2, Gulf 1, Putnam 2, Washington 1, Glades 2, Suwannee 1, Bradford 2, Orange 1, Polk 2, St. Johns 1, Okeechobee 2, Pasco 1, Okeechobee 2, Pasco 1, Sumter 1, Marion 1, Hardee 1, Calhoun 1, Columbia 1, Gadsden 1, Dixie 1, Liberty 1, Madison 1, Levy 1, Baker 1, Alachua 1, Volusia 1, Holmes 1, Palm Beach 1, Sarasota 1, Duval 1, Lee 1, Charlotte 1, Bay 1, Jackson 1, Sarasota 1, Highlands 1, Leon 1, Hernando 1, Franklin Escambia 1, Nassau 1, Clay 1, Flagler Okaloosa 1, Walton 1, Polk 1, Pinellas Seminole 1, Jackson 1, Union 1, Nassau Pinellas 1, Holmes 1, Suwannee 1, Bay St. Lucie 1, Levy 1, Dixie 1, Indian River Santa Rosa 1, Washington 1, Calhoun 1, St. Lucie Columbia 1, Marion 1, St. Johns 1, Manatee Duval 1, Sumter 1, Highlands 1, Gulf Clay 1, Gilchrist 1, Liberty 1, Dade Lee 1, Franklin 1, Leon 1, Collier Citrus 1, Manatee 1, Citrus 1, Hillsborough Orange 1, Martin 1, Okaloosa 1, Palm Beach Jefferson 1, Gadsden 1, Hamilton 1, Martin Bradford 1, Wakulla Gilchrist 1, Wakulla Madison 1,645 Total 1, Seminole 1,394 Total 963 Source: data from FLOIR; authors' calculations 28