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Interest Rates and Insurance Price Cycles
Abstract
Property liability insurance prices and profits appear to move in a six year cycle. The common explanation for the cycle amongst many industry analysts is that the insurance market is inherently unstable and that prices fail to converge on clearing levels. Our explanation is different. We identify spot equilibrium prices using the Capital Asset Pricing Model. But informational, regulatory and contractual lags preclude instantaneous adjustment. We therefore model the temporal movement of prices using a partial adjustment model in which actors form rational expectations. The actual movement of insurance prices does seem to track closely those estimated by the partial adjustment model. The cycle may be better viewed as a series of converging responses to changing spot prices.
... where LossRatio i,t is the loss ratio for company i in year t, regulation is a dummy variable encoded as 1 for 2011 to 2013 and 0 for 2014 to 2016. Interest rates can affect insurance premiums ( [3]) where premiums reflect discounting from estimated losses. To control this effect, the remaining IntRate t−1 variables are included in this model. ...
... In determining the insurance premium, all harmful factors which exist based on past experience should be more strongly considered. Level of risk will affect decisions about changes in insurance premiums and affecting the growth of the insurance premium, thus delta losses (∆Losses((∆Losses i,t−1 )(∆Losses i,t−2 )(∆Losses i,t−3 )) are included as independent variables in Equation 3. ...
... Interest rates can affect insurance premiums [3], in that premiums reflect discounts from estimated losses and interest rate rises can therefore lead to decreases in insurance premiums. In addition, insurance premiums create substantial investment funds. ...
... The recurring pattern is also observed in Asian countries as well. Subsequently, extensive insurance literature has been developed in attempting to explain the insurance underwriting cycle (Fairley, 1979;Hill, 1979;Kraus and Ross, 1982;Venezian, 1985;Cummins and Garven, 1986;Doherty and Garven, 1986;Cummins and Outreville, 1987;Berger, 1988;Doherty and Kang, 1988;Fields and Venezian, 1989;Cummins, 1990Cummins, , 1991Haley, 1993Haley, , 1995Lamm-Tennant and Weiss, 1997;Leng and Meier, 2006;Meier, 2006). ...
... As insurance premiums are computed based on the discounted future losses, any unexpected interest rate movements will induce corresponding changes in premiums, and thereby the underlying operating profits. Thus, interest rate changes could be the root of the insurance underwriting cycles (Wilson, 1981;Doherty and Kang, 1988;Smith, 1989;Fields and Venezian, 1989;Doherty and Garven, 1992;Haley, 1993;Lamm-Tennant and Weiss, 1997;Fund et al., 1998;. ...
... As insurance premiums are computed based on the future expected losses and all other economic information, one would expect underwriting profits to fluctuate randomly around an equilibrium point without consistent positive or negative returns. The discovery of the underwriting cycle has led to a substantial insurance literature being developed over the last three decades (Fairley, 1979;Hill, 1979;Kraus and Ross, 1982;Venezian, 1985;Cummins and Garven, 1986;Doherty and Garven, 1986;Cummins and Outreville, 1987;Berger, 1988;Doherty and Kang, 1988;Fields and Venezian, 1989;Cummins, 1990Cummins, , 1991Haley, 1993Haley, , 1995Lamm-Tennant and Weiss, 1997;. ...
... Price is determined by demand and supply; thus, factors affecting the demand side or supply side can have impacts on price determination. Doherty and Kang (1988) develop a structure model including both the demand side and supply side and describe underwriting cycles as a market clearing process with partial adjustment. The supply function is specified with expected excess underwriting profits, and the competitive underwriting profits are modelled by the insurance capital asset pricing model (CAPM) (Doherty & Garven, 1986;Fairley, 1979), which depends on the risk-free interest rate and capital market return. ...
... Premiums are usually thought to be the discounted present value of future costs; thus, it is not surprising to see that the interest rate, a proxy for discount rate, is negatively related with insurance price. Our findings for the property-liability line are consistent with many previous studies (Doherty & Garven, 1995;Doherty & Kang, 1988;Fields & Venezian, 1989;Haley, 1993;Lamm-Tennant & Weiss, 1997;Smith, 1989). In contrast to property-liability insurance, the price of personal accident insurance is identified as being positively correlated with rate of market return and interest rate in Table 4. ...
Non-life insurance prices may fluctuate due to economic and/or institutional factors; occasionally, the changes are cyclical. While the majority of previous studies relating to insurance price dynamics adopt data from developed economies, this paper uses data from China to provide new evidence. This study tests the long-term and short-term effects of real gross domestic product (GDP), interest rate and rate of stock market return on the prices of different lines of non-life insurance, i.e., property-liability insurance and personal accident insurance. The results indicate that the price dynamics of property-liability insurance are generally similar to those of developed countries, except for the effect of GDP, while price determination of personal accident insurance seems to be affected by a wider range of economic and institutional variables and has its own features. The price dynamics of non-life insurance in China have been identified as being connected to the country-specific economic and institutional environments.
... In the corresponding literature, there is still little research done on how the insurance premium follows from competition, and responds to changes initiated by competitors (Taylor, 1986;Daykin and Hey, 1990;Emms, 2012;Pantelous and Passalidou, 2015;Wu and Pantelous, 2017). Moreover, despite the fact that in many lines of insurance the presence of underlying cycles has been observed empirically, there is a constant endeavour to understand the dynamics of insurance premiums (Cummins and Outreville, 1987;Rantala, 1988;Doherty and Kang, 1988;Daykin et al., 1994;Winter, 1994;Cummins and Danzon, 1997;Lamm-Tennant and Weiss, 1997;Taylor, 2008;Malinovskii, 2010). ...
... Premium cycles are observed in the whole time period. Figure 5 supports the empirical evidence in the insurance literature (Cummins and Outreville, 1987;Doherty and Kang, 1988;Winter, 1994;Cummins and Danzon, 1997;Lamm-Tennant and Weiss, 1997) that premium cycles in insurance markets are caused by market competition. Although the premiums between the two insurers are not proportional, the shape of premium cycle profiles is similar. ...
In the insurance industry, the number of product-specific policies from different companies has increased significantly. The strong market competition has boosted the demand for a competitive premium. In actuarial science, scant literature still exists on how competition actually affects the calculation and the cycles of company's premiums. In this paper, we model premium dynamics via differential games, and study the insurers’ equilibrium premium dynamics in a competitive market. We apply an optimal control theory methodology to determine the open-loop Nash equilibrium premium strategies. The market power of each insurance company is characterized by a price sensitive parameter, and the business volume is affected by the solvency ratio. We study two models. Considering the average market premiums, the first model studies an exponential relation between premium strategies and volume of business. The second model initially characterizes the competition between any selected pair of insurers, and then aggregates all the paired competitions in the market. Numerical examples illustrate the premium dynamics, and show that premium cycles may exist in equilibrium.
... To the best of our knowledge, this is the first study to examine the effect of external and external capital (including reinsurance) on gross insurance prices and the underwriting cycle in a major insurance market (the UK). Second, empirical analysis of underwriting cycles is important as the return on underwriting capital is likely to have an impact on the valuation of the traded shares insurance companies (Doherty and Kang, 1988). As a result, the present study should be of interest to investors, insurance company managers, amongst others. ...
... In the literature underwriting cycles in property-liability insurance markets follow a second-order autoregressive process with an average length of between six to eight years (e.g., seeCummins and Outeville, 1987;Doherty and Kang, 1988;Niehaus and Terry, 1993;Doherty and Garven, 1995;Grace and Hotchkiss, 1995). ...
... The average rate is the arithmetic mean of all individual rates. 8 Historically rates were set too low in the early years of satellite insurance, which meant that total premium income was eroded by a few claims. Traditionally, rates have been set in reaction to claims experience rather than by statistical analysis of the launch and in-orbit record [20]. ...
... 0.2*$250 million). 8 Rates are calculated for each individual spacecraft during the underwriting process and depend on many factors, however the most important are: satellite platform and launch vehicle heritage as well as market conditions. However, capacity declined in the mid-1980s thanks to a series of losses, including the loss of the Space Shuttle Challenger in 1986 [22]. ...
The history of the satellite insurance market indicates that this market experiences crises and booms in profitability and prices that repeat in a manner suggestive of cycles. The purpose of this article is to rigorously investigate cyclicality of these and other features of the satellite insurance market and assess their volatility formally. Using data from 1968 to 2008, volatility and cyclicality are analyzed for satellite insurance market capacity, rates, and underwriting results, among other measures. The coefficient of variation for the various satellite insurance market metrics is used to assess volatility. Standard underwriting analysis is used to determine whether a cycle exists for various insurance metrics. The results indicate that some aspects of the satellite insurance market are volatile (e.g. claims) or cyclical (e.g. rates), while capacity is both volatile and cyclical.
... Cummins and Outreville (1987) study the financial pricing hypothesis by attributing such cyclical pattern to a second-order autoregressive process that includes insurance information, regulatory, and reporting lags. Studying the same hypothesis, subsequent studies by Doherty and Kang (1988) and Lamm-Tennant and Weiss (1997) also find consistent results. 6 However, in these studies it is implicitly assumed that insurers act in a risk-neutral way and that markets are perfect. ...
This paper challenges the question of existence and predictability of underwriting cycles in the U.S. property and casualty insurance industry. Using an approach in the frequency domain, we demonstrate the existence of a hidden periodic component in annual aggregated loss ratios. The data support an underwriting cycle length of 8–9 years. Going beyond previous research and studying almost 30 years of quarterly underwriting data, we can improve forecasting performance by (dis)connecting cycles and catastrophic events. Superior out-of-sample forecast results from models with intervention variables flagging the time point of catastrophic outbreaks is achieved in terms of mean squared/absolute forecast errors. We evaluate model confidence sets containing the most accurate model with a certain confidence level. The analysis suggests that reliable forecasts can be achieved net of the irregular major peaks in loss distributions that arise from natural catastrophes as well as unusual “black swan” events.
... Investment profits could augment underwriting profits. The mathematical function of underwriting profits of property-casualty insurers, in particular the cyclical nature of these profits, or the so-called [profit] underwriting and insurance cycles has been extensively studied (Venezian, 1985;Cummins & Outreville, 1987;Doherty & Kang, 1988;Gron, 1990). ...
This article derives a framework for annual financial statements of a property-casualty insurer from first principles using Adam Smith’s statement of the operation of an insurer as the point of departure. The derivation incorporates’ current standard accounting principles and regulatory requirements. In the end it will be seen that a substantial correlation exists between the final derived framework and current published statements of a modern property-casualty insurer. It remains to be seen if a similar correlation will continue to exist once the long awaited international accounting standard for insurers is finalised. The article accordingly demonstrates that Adam Smith’s statement can be used to derive a workable framework for the accounting and hence management of modern property-casualty insurers. A number of important conclusions flow from the article. Firstly the distinction between provisions and reserves must be understood and maintained failing which solvent insurers may be portrayed as being insolvent, second a new provision should be raised, a Year to Close Provision where it is unclear that existing provisions adequately cover outstanding liabilities and third the IBNR provision should be restricted to claims in the pipeline for the year under consideration.
... The first of these is graphical analysis -used mainly as a preliminary method by, for example, Helten (1977), de Witt (1979) and Lemkowska (2007). The next is spectral analysis proposed by C. Mormino (Mormino 1979) also used in the works of Venezian EC (2006) for US market, Doherty and Kang (1988), Grace and Hotchkiss (1995), Leng and Meier (2006). The most popular method is the secondorder autoregresssive model AR (2), proposed by Venezian (1985) and developed by Cummins and Outrville (1987). ...
The management team is one of the most important characteristics of a startup in the investment evaluation process. Several authors summarized and categorized the investment decision criteria concluding that the entrepreneur/team is one of the most important factors. For startupers, it is important to understand the key competencies of the management team required for a successful proposal for venture capital investment, but the empirical analysis and findings of this area have strong limitations. We defined the most important team competencies based on the literature and defined a coding system of the characteristics of the team along with several aspects and quantitatively analyzed them on the Hungarian television show called “Cápák Között” (Among Sharks). In this show, investors listen to pitches of startup entrepreneurs who seek equity investment and, after questioning the entrepreneurs, decide whether they want to invest in the company or not. In our study, we made the first step to code the most important characteristics of the management team and test the methodology of real investment decisions. We have to consider that the investors’ preferences could differ in normal business circumstances outside the TV show; however, in the show the investors made real investments in the selected companies using their own money. It is always hard when we want to analyze factors connected to personal attributes. Through this study, we made tangible some subjective factors of startup teams based on the investors’ feedback. The findings of this chapter provide a new methodology for other researchers to study the personal investment criteria.
... The property-liability insurance business is obviously linked to the overall economic performance of the national economy (32,35), especially when it comes to interest rates that are related to insurance pricing theory (36), insurance prices should reflect investment returns by discounting expected losses, so insurance prices are the result of discounting future losses. Any change in the interest rate causes a change in the premium because the insurance company invests the premium from the time the premiums receives to the time they pay the loss. ...
The frequency and intensity of catastrophes (including natural disasters and pandemics) rise and damage the population's health, life and property more seriously. In order to protect population health and wealth via full insurance indemnity, many countries set up a public catastrophe insurance scheme (PCIS) to maintain the function of catastrophe insurance markets. Little literature discusses the smart payment way of contributions charged by PCIS. This article design a model to describe the upward trend and cyclic frequency and intensity of catastrophic events. Such characteristics also promote the business cycle of the insurance industry. We analyze the changes in catastrophic insurer's capital structures under three cases of that the volume-based charges to the PCIS may come from equity holders or policyholders or both. PCIS may entail a shift of equity capital toward minimum solvency requirements, and then adverse incentives regarding insurer's security level arise. Various numerical experiments illustrate the changes in equity position, default probabilities, or expected policyholder deficits. The results show that the payment way of contributions should be designed carefully, not only with regard to PCIS's finance balance but also the resultant incentives and effects.
... The second type of challenges are some changes in the financial system and in particular the insurance intermediation sphere, such as decreasing interest rates, tariffs, etc. There is, for example, a causality relationship between interest rates and the so-called insurance cycle (underwriting cycle) (Wilson, 1981;Doherty, 1998). For example, the global financial and economic crisis of 2008-2010 was followed by a wave of distrust of the financial system, but also by a wave of regulatory changes. ...
The history of insurance and insurance mediation in Bulgaria can be divided into four periods-from 1878 to 1946; from 1946 to 1989; from 1989 to 2007; and after the accession of Bulgaria to the EU in 2007. The most significant regulatory at the end of the penultimate period and the last period are related to the establishment of the Financial Supervision Commission (2003), the adoption of the first Insurance Code (2005) of the second, still valid new Insurance Code. The analysis shows that the legislation of insurance intermediation in Bulgaria is undergoing significant development in the direction of improvement and adaptation to evolving and complicating modern market conditions. The most significant trends that are observed are in the direction of explicitly differentiating the functions of brokers and agents; strengthening the requirements for education and qualification of the persons managing and the persons directly carrying out the activity of insurance mediation; development of the licensing and registration regime; subordination of the requirements for brokers and agents and to other categories of persons engaged in mediation (employees of the insurers themselves in direct sales, as well as intermediaries developing insurance mediation as an additional activity). After 2007, all changes are in the direction of synchronization with EU legislation and protection of consumers of insurance products. The most significant features and current challenges of the global and Bulgarian insurance market and in particular of the intermediaries working on it are related to changes in the general economic conditions. Here are added changes in the financial system, regulations, the emergence of new types of risk, changes in the insurance business (digitalization), and the cycle of the insurance market. Among the changes with the most significant impact since 2020 is COVID-19 as a new, global systemic risk with a huge impact on all economic agents and on the value of insurance estimates.
... 18 Many researchers show that combined ratios and loss ratios have an autocorrelation (Venezian 1985;Cummins and Outreville 1987;Doherty and Kang 1988;Harrington and Niehaus 2000;Meier 2006). 19 In general, if PC insurance companies prepay ΔFc more commissions to intermediaries in year t − 1, then ΔFc will be saved in year t. ...
We investigate how the 2009 regulatory change to the method of calculating combined ratios in the Chinese property–casualty insurance industry affected the relationship between commissions and combined ratios. We find that since the 2009 reform, the industry has shown a non-linear relationship between commissions and combined ratios. The relationship is negative (positive) when the combined ratio is higher (lower) than the regulatory threshold. Before 2009, this relationship was linear. Since 2009, when commissions increased, the combined ratio converges to the threshold. As the volatility of the combined ratio is positively related to the statutory capital required, this change provides incentives for insurers to decrease the combined ratio and/or its volatility as they seek to manage their commissions to approximate the threshold without jeopardising compliance with other regulatory requirements.
... Previous explanations of the insurance underwriting cycle include institutional frictions in reporting losses and biases in the forecasting of future losses (Venezian, 1985;Cummins & Outreville, 1987;Clark, 2015); capital market failures (Gron, 1994;Winter, 1994;Dicks, 2007); adverse selection and insolvency risk (Cummins & Danzon, 1987;Cagle & Harrington, 1995); unpredictable shifts in the term structure of interest rates (Doherty & Kang, 1988;Madsen, Haastrup, & Pedersen, 2005); strategic pricing and the winner's curse (Harrington, 2004;Emms, 2012) and behavioral biases in the underwriting process (Fitzwilliams, 2004). This paper differs in its explanation of such cycles, however, by avoiding the use of highly specific sources of market failure such as biased forecasting, differential costs of raising capital, adverse selection and bankruptcy costs. ...
This paper offers a novel explanation of the financial underwriting cycle in the property-liability insurance industry. By doing so it resolves that significant anomaly in asset pricing theory posed by cycles in the efficient pricing of insurance coverage. In contrast to the reliance on a variety of institutional or capital market failures underlying all previous explanations of this cycle, we directly augment the complete-markets environment of traditional asset-pricing models through the presence of a single source of risk that cannot be fully hedged through existing financial markets. We realistically interpret this source of risk as unforecastable noise in the implementation of insurance regulations. Cycles in the value of underwriting insurance coverage can arise in this simple variant of a standard complete-markets pricing model owing to the effect of such regulatory risk. We offer a sufficient condition for a stable cycle to endogenously exist in market equilibrium and illustrate this condition in the context of a representative insurance firm and a regulator pursuing a countercyclical policy with noisy implementation. Interestingly, while insurance pricing is efficient in the absence of the regulator, cyclic pricing and underwriting profitability can be induced by a countercyclical regulator policy designed to stabilize the very cycle it creates.
... There are plenty research on the existence of the underwriting cycle. Venezian (1986), Cummins and Outreville (1987), Doherty and Kang (1988), Grace and Hotchkiss (1995), Merei (2006) studied on the underwriting cycle of the US property-liability insurance market. The main conclusion is that there is underwriting cycle in the market and LC is around 6 to 8 years. ...
... Previous explanations of the insurance underwriting cycle include institutional frictions in reporting losses and biases in the forecasting of future losses (Venezian, 1985;Cummins & Outreville, 1987;Clark, 2015); capital market failures (Gron, 1994;Winter, 1994;Dicks, 2007); adverse selection and insolvency risk (Cummins & Danzon, 1987;Cagle & Harrington, 1995); unpredictable shifts in the term structure of interest rates (Doherty & Kang, 1988;Madsen, Haastrup, & Pedersen, 2005); strategic pricing and the winner's curse (Harrington, 2004;Emms, 2012) and behavioral biases in the underwriting process (Fitzwilliams, 2004). This paper differs in its explanation of such cycles, however, by avoiding the use of highly specific sources of market failure such as biased forecasting, differential costs of raising capital, adverse selection and bankruptcy costs. ...
This paper offers a novel explanation of the underwriting cycle in the property-liability insurance industry. This explanation depends, in the context of a stochastic differential game, on the interaction between two forms of uncertainty affecting firms underwriting insurance contracts. Such firms face uncertainty both from market conditions and from regulatory policy. Underwriting reveals information about the risk of policyholders and reduces market uncertainty, while uncertainty about regulatory policy reduces the value of this information and reduces the incentive to continue underwriting. Best-reply decision rules of both a representative insurance firm and a representative regulator are combined in an asset valuation equation to illustrate the effects of these two sources of uncertainty on the value of underwriting. Under certain parametric conditions, a subgame perfect Nash equilibrium of this game will exhibit a cycle in the value of underwriting even when capital markets are complete.
... In practice, some authors found that fluctuations in non-life insurance premiums (or measures of underwriting profits 1 ) are related to the variations in the interest rate (Doherty and Kang (1988), Fields and Venezian (1989), Smith (1989), Fung et al. (1998), Choi et al. (2002), Fenn and Vencappa (2005) and Adams et al. (2006)), while other authors showed that the fluctuations in non-life insurance premiums are not related to the variations in the interest rate (Niehaus and Terry (1993), Lamm-Tennant and Weiss (1997), Chen et al. (1999) and Meier andOutreville (2006, 2010)). ...
This paper proposes an original framework based on nonlinear panel data models to study the empirical influence of the interest rate and the inflation rate on the non-life insurance premiums for fourteen developed countries over the period 1965-2008. More specifically, we apply the panel smooth transition error correction model which takes into account both the short and long-run effects of changes in economic variables on the growth rate of non-life insurance premiums and which allows the regression coefficients to vary across countries and over time. Our empirical results show that the interest rate and the inflation rate have a differentiated impact on the non-life insurance premiums depending on the value of the inflation rate. These empirical findings provide evidence of changes in insurance pricing rules. Keywords: non-life insurance premiums, interest rate, inflation rate, panel smooth transition error correction model and insurance pricing rules.
... Plusieurs études montrent qu'il existe un lien statistiquement significatif entre les mouvements à court terme des taux d'intérêt et la variabilité des résultats de l'assurance IARD. Doherty et Kang (1988) et Doherty et Garven (1992) estiment que la variabilité des taux d'intérêt entraîne des chocs externes influençant l'équilibre des prix. La sensibilité des résultats aux variations des taux d'intérêt dépend des possibilités d'accès au marché des capitaux et à la réassurance. ...
... During a hard market insurance prices increase and less coverage is available; during soft markets prices decrease and coverage is more easily available (e.g. Doherty and Kang, 1988;Lamm-Tennant and Weiss, 1997;Chen et al., 1999). In the capacity constraint theory, a loss or a negative shock causes a depletion of the capacity of insurers to grant insurance, if they wish to keep bankruptcy risk within bounds. ...
Since the financial crisis of 2008, next to banks, insurers have received increasing attention from researchers and regulators because of their crucial role in the financial system. A key point for a stable insurer is its capital structure, i.e. the choice between equity, debt and provisions in financing its operations. Based on earlier work a quickly developing literature has directly applied capital structure theories (in particular trade-off and pecking order) from corporate finance to insurers’ financing choices. Corporate finance concepts used herein however, are developed for industrial firms. In this paper we provide an overview of the literature on the capital structure of insurers, but contribute by systematically clarifying how to account for the specificities of insurers when transferring the trade-off and pecking-order logic from an industrial to an insurer context. This way, we add several new insights on an insurer's choice between equity, financial debt and provisions. In particular, we are able to explain why, as compared to industrial firms, insurers use less financial debt, and why insurers focus so strongly on self-financing. Finally, we identify multiple avenues for future research.
... Investment profits could augment underwriting profits. The mathematical function of underwriting profits of property-casualty insurers, in particular the cyclical nature of these profits, or the so-called [profit] underwriting and insurance cycles has been extensively studied (Venezian, 1985;Cummins & Outreville, 1987;Doherty & Kang, 1988;Gron, 1990). ...
This article derives a framework for annual financial statements of a property-casualty insurer from first principles using Adam Smith's statement of the operation of an insurer as the point of departure. The derivation incorporates current standard accounting principles and regulatory requirements. In the end it will be seen that a substantial correlation exists between the final derived framework and current published statements of a modern property-casualty insurer. It remains to be seen if a similar correlation will continue to exist once the long awaited international accounting standard for insurers is finalised. The article accordingly demonstrates that Adam Smith's statement can be used to derive a workable framework for the accounting and hence management of modern property-casualty insurers. A number of important conclusions flow from the article. Firstly the distinction between provisions and reserves must be understood and maintained failing which solvent insurers may be portrayed as being insolvent, second a new provision should be raised, a Year to Close Provision where it is unclear that existing provisions adequately cover outstanding liabilities and third the IBNR provision should be restricted to claims in the pipeline for the year under consideration.
... To avoid this controversy without ignoring the existence of cycles altogether, this analysis makes use of an empirical result first reported by Doherty and Kang (1988). They demonstrate that a partial-adjustment representation of insurance supply is adequate to explain the "cyclical" fluctuations in aggregate insurance data, once interest rate fluctuations are accounted for. ...
This article investigates whether regulatory lag affects the character of unit prices (inverse loss ratios) in regulated private passenger automobile insurance markets. The analysis is developed in the context of a simple model of a regulated insurance market. The model predicts that regulatory lag will increase the intertemporal dependence of unit prices in regulated markets. The model is estimated using data from auto liability insurance markets in 35 states over the period 1975-1986. The estimation results support the view that regulatory lag is significant for most firms in most regulated states.
... In their work, they also assert that the underwriting margin should be negatively correlated with interest rates. Financial pricing models utilizing a discounted cash flow approach and the capital asset pricing model point to changing interest rates as an important factor in the behavior of the underwriting cycle (Cummins (1990), Doherty and Kang (1988)). ...
... other things being equal. This prediction is consistent with Doherty and Kang (1988) who suggest that fluctuations in interest rates create insurance pricing cycles.5 The intuition is that higher interest rates generate greater investment income, which lowers premiums and vice versa. ...
Using industry and by-line data, we examine the causes of insurance cycles in a vector autoregressive model. Some of the important findings are summarized below. First, the uncertainty variable explains significant portions of forecast errors of premiums. Second, the significant factors that determine premiums are different for different lines. Third, investment incomes in general are more important for long-tail lines than short-tail lines. Evidence on the response of premiums to shocks suggests that all one-time shocks to variables tend to be relatively permanent. The overall results seem to imply that no single hypothesis is able to explain the insurance cycle.
... Evidence that general insurance premiums and profit margins fluctuate cyclically has been found in a number of studies, mainly drawing on US data (Venezian, 1985;Cummins and Outreville, 1987;Doherty and Kang, 1988;Winter, 1994). Cummins and Outreville (1987) also review the evidence on premiums and underwriting profits from other countries, and show it to be consistent in most cases with a second order autoregressive process and a cycle length between 6-8 years. 2 Much of the stimulus for work in this area stemmed from concern over the US "liability insurance crisis" of the mid to late 1980's, in which aggregate general insurance premiums increased at over 70% per annum in 1985 and 1986, and limitations on the availability of insurance were widely reported. ...
... For examples, seeSmith and Gahin (1983);Venezian (1985);Cummins and Outreville (1987);Doherty and Kang (1988);Grace and Hotchkiss (1995); Lamm-Tennant andWeiss (1997);Chen et al. (1999);Harrington et al. (2008) and Berry-Stolzle and Born (2012). ...
This research analyses whether underwriting cycles are present in an important but often overlooked line of insurance, satellite insurance. Unlike previous underwriting cycle studies, this study uses rates-on-line and capacity devoted to satellite insurance as well as loss ratios to determine the applicability of cycles. The sample period encompasses virtually the entire history of the satellite insurance industry, 1968–2010. The results indicate that cycles are present in the minimum and average rates-on-line and in capacity, but not the loss ratio. Regression analysis is carried out on the rate-on-line and capacity variables, and the regression results support the rational expectations/institutional intervention hypothesis and the capacity constraint (capital shock) hypothesis.
... For loss-shock and resultant capacity constraint theories, see Gron (1994), Winter (1988Winter ( , 1991Winter ( and 1994 and Cummins and Danzon (1997). For interest rate theories, see Doherty and Kang (1988) and Doherty and Garven (1995). For under-pricing and irrational insurer behavior theories, see Harrington and Danzon (1994) and Harrington (2004). ...
This study performs a time series analysis to explore the effects of property casualty insurance underwriting cycles on stock and mutual insurers' asset risk taking. It is well documented that underwriting costs and insolvency risks faced by insurers are greater in hard markets while lower in soft markets. To achieve optimal risk portfolios, insurers may take on more asset risks in soft markets and discharge them in hard markets. Moreover, we expect stock companies would be more reactive to underwriting cycles than are mutual companies given greater risk-taking capacity and better managerial-incentive-control mechanism of the stock companies. Our result confirms these conjectures. While stock companies are found actively responding to the underwriting cycle, mutual companies appear to be indolent. Another interesting finding is that property casualty insurers, both mutual and stock companies, do not actively respond to capital market signals.
... We control for the underwriting cycle using the mean and variance of historical lending interest rates in each country in a given year. Doherty and Kang (1988), Gron (1994), and Doherty and Garven (1995) argue that fluctuations in interest rates create insurance pricing cycles. Fung et al. (1998) find that interest rates (mean and variance) are able to explain the variation in premium rates. ...
We investigate how investor protection, government quality, and contract enforcement affect risk taking and performance of insurance companies from around the world. We find that better investor protection results in less risk taking, as do higher quality government and greater contract enforceability. However, we find only limited evidence that these factors influence firm performance. We conclude that better overall operating environments result in less risk taking by insurers without the concomitant decline in performance. These results imply that better investor protection environments benefit policyholders and outside stockholders by preventing corporate insiders from expropriating wealth from policyholders and outside stockholders.
The risk appetite of insurance companies fluctuates over time in a quasi cyclical fashion. When their capitalization is high (low), companies choose portfolios with a high (small) share of risky assets. We show that this phenomenon has the same source as the underwriting cycle, namely recapitalization costs. We build a dynamic stochastic general equilibrium model of the insurance sector where financial frictions prevent companies from maintaining a target leverage. Portfolio decisions of insurers fluctuate with their aggregate capitalization. The model rationalizes two apparently disjoint pieces of evidence: long-standing empirical evidence on underwriting cycles and more recent evidence on the fluctuations of insurance companies’ risk appetite.
Insurance business (underwriting) cycles are typical of non-life insurance. The cycle consists of phases of low and high prices of insurance products and indicators of financial condition. According to theory, underwriting cycles are long, in developed countries – even 8–10 years. On the Polish market, up to now, the cycle survey has been limited by the time horizon of available data (unified data since 1999). Currently, the scope of data is much longer, which allows to compare the results of earlier studies (from 2010 to 2013) with newer ones, to check whether the cycle lengths have reached values similar to observed in developed markets. Knowledge of these cycles can support the risk management process of an insurance company. The purpose of the research is to analyse the occurrence of underwriting cycles in liability insurance on the Polish market (cumulated data for insurance companies operating on the Polish market), as they are particularly sensitive to changes in legal regulations (numerous on the Polish market in 2007–2012). It will be examined whether the cycles occur and, if so, what their length is. The study will use the second-order autoregressive model AR(2). Model coefficients are estimated by least squares method. The study confirmed the presence of cycles for groups: 10 (MTPL insurance), 5–6-year cycles confirmed in most of the ratios analysed; 11 (third-party liability insurance, arising out of the possession and use of aircraft), no cycles found except combined ratio; 12 (insurance of civil liability for sea and inland navigation), cycles observed in claims, profitability and combined ratio; and 13 (general third-party liability insurance not included in groups 10–12) of the non-life insurance sector, cycles observed only in dynamics ratios.
The objective of this paper is to compare alternative models of insurance pricing as theories of the property‐liability underwriting cycle. The existing literature has focused on comparing two models, the financial pricing and capacity constraint models. However, these are not the only relevant models. We show that six alternative models imply the same general form of the pricing equation. We apply the model to data on stock property‐liability insurers for the period 1935‐1997. We find that the actuarial model and the capacity constraint hypothesis are the only theoretical models that are consistent with the data.
This study explores the existence of inefficiencies in catastrophe (CAT) bond secondary markets by investigating the impact of sponsor characteristics on the CAT bond premium. We show that the CAT bond market does not satisfy the demand for catastrophe risk transfer efficiently by revealing a significant effect of sponsor-related factors on the CAT bond premium. This inefficiency is particularly surprising given that a CAT bond isolates the insured risk from other sponsor-related risks through a special purpose vehicle. Remarkably, this inefficiency is even present among non-indemnity CAT bonds, which determine the payout through a mechanism that is exogenous to the sponsor. Our findings also reveal that sponsor-related pricing inefficiencies vary over time and are more relevant during hard and neutral phases compared to soft market phases. Among the sponsor-related determinants of the CAT bond premium are the sponsor's tenure, market coverage, rating, credit default swap spread, and his ability to issue innovative “on the run” CAT bonds.
Insurance is critical to the fabric of modern societies and economies, but the insurance industry continues to suffer deep cycles and periodic crises. These have a great socio-economic cost as insurance cover can become prohibitively expensive or unavailable, damaging livelihoods, property, belongings and employment. These phenomena are poorly understood. A set of socio-anthropological and behavioural hypotheses have recently been posited. We investigate these explanations by means of an agent-based simulation model. The model is parameterized on actual property insurance industry data and is carefully validated. Our main result is that simple behaviour and interaction at the individual level can result in complex cyclical industry-wide behaviour. Heterogeneity and interaction at a micro level must therefore be understood if cycles and crises in the insurance industry are to be managed and prevented.
The aim of this chapter is to identify the areas where insurance companies’ investment policies influence risk management in the public sector and financial system stability in the European Union countries and to analyse the model of their investment portfolio allocation. The significance of the insurance sector for the public one is examined in the context of the so-called critical functions: (1) fulfilment of the function of insurance coverage; and (2) the mechanisms of long-term allocation of capital. The importance of insurance institutions both for the stability of the public sector and the whole economic system arises from the fact that these institutions perform the critical—from the perspective of society as well as the economy—function of insurance coverage which allows the management of risk and ensures continuity of operation. The capability of ensuring infallible fulfilment of insurance coverage constitutes a synthetic indicator of the stability of the socio-economic system. Performance of the functions of critical importance for the stability of the public sector by the insurance sector is also concerned with the mechanism of long-term allocation of capital, especially in the case of life insurance companies, which is invested in the financial market and in the real economy. The investment activities of insurance companies have an impact on the stability of the public sector, in particular: (1) by investing in instruments issued by the government, which is of particular systemic importance in the context of debt crisis in many EU member states; (2) by influencing the situation on the stock and bond markets, e.g. creating speculative bubbles, assets fire sale; (3) by transforming capital into investment in the real economy sector—an effect on the real economy through over-rating some sectors at the expense of others, thus determining the cost of capital. Activity of insurance companies on the market of public debt is of immense importance for risk management in the public sector.
A BSTRACT
We examine changes in workers’ compensation laws from 2003 to 2011 and their effect on insurer performance as measured by loss ratios and claim costs. We study changes to: length of temporary total loss indemnity, penalties on employees who do not comply with rehabilitation efforts, employer or employee choice of physician, and limits on attorney fees. We find differential effects among these reforms with the most robust being changes to limits on temporary total indemnity and penalties for workers who do not comply with rehabilitation efforts. We measure one effect of the political environment and find that appointing authority over the workers’ compensation board or committee significantly affects loss costs. Lastly, we find evidence of regulatory capture in workers’ compensation.
Using cross-state panel data of the U.S. personal auto insurance premiums from 2007 to 2012, this study provides evidence that consumer purchases of insurance were reduced by more than expected from losses of risk exposure during and after the subprime mortgage crisis. Analyses show that the credit crunch of auto loans and a deterioration of net worth in housing resulting from the bursting housing bubble contributed to the reduced consumption of auto insurance. This result is robust even after controlling for associated factors, such as the insurance price, personal spending on vehicles, and general consumption. These findings provide evidence for a real effect of the financial crisis.
It is the conventional wisdom of the insurance industry the world over that the industry is subject to an underwriting cycle. By this is meant that the industry’s profit exhibits cyclical behaviour over time. In this context “profit” usually means total operating profit rather than just the underwriting profit component, though in the present paper it will not be necessary to focus on this distinction to any great extent.
The starting point of this chapter is the flow of resources generated by the operations of the insurance business. The concept employed for the purpose is the ratio analysis, which is a way of expressing and displaying performance measurement, based on the periodic accounting statements. The chapter will present the key ratios and measures commonly applied in financial analysis for expressing the business performance of insurance companies.
The demand for and supply of liability insurance arise from the legal liability of individuals and corporations for injuries caused to third parties. Tort liability rules and liability insurance markets have attracted substantial attention in recent years. This paper introduces the literature on the demand for and supply of liability insurance. The focus is on issues that distinguish liability from first party insurance. Particular emphasis is given to the relationships between liability law, liability insurance, and risk reduction.
This chapter reviews the literature on underwriting cycles and volatility in property-casualty insurance prices and profits. It provides a conceptual framework for assessing unexplained and possibly cyclical variation. It summarizes time series evidence of whether underwriting results follow a second-order autoregressive process and illustrates these findings using US property-casualty insurance market data during 1955–2009. The chapter then considers (1) evidence of whether underwriting results are stationary or cointegrated with macroeconomic factors, (2) theoretical and empirical work on the effects of shocks to capital on insurance supply, and (3) research on the extent and causes of price reductions during soft markets.
This paper re-examines the evidence in favour of the existence of underwriting cycles in property and casualty insurance and their economical significance. Using a meta-analysis of published papers in the area of insurance economics, we show that the evidence supporting the existence of underwriting cycles is misleading. There is, in fact, little evidence in favour of insurance cycles with a linear autoregressive character. This means that any cyclicality in firm profitability in the property and casualty insurance industry is not predictable in a classical econometric framework. It follows that pricing in the property and casualty insurance industry is not incompatible with that of a competitive market. © 2015 The International Association for the Study of Insurance Economics.
The presence of an underwriting profit cycle in property / liability insurance has become a stylized fact. Models of this "underwriting cycle" imply that the insurance market is governed by two regimes, as capacity is constrained ol not. We apply the smooth transition regression model to insurance industry data for 1934-1993 to test for a regime shift We find a rapid shift between two distinct regimes with different dynamics. When capacity is trot restricted Me find no evidence of a cycle. The cycle is present in periods when capacity is restricted immediately following World War II and after 1968, The underwriting cycle appears to be a recent phenomenon. (JEL G22, C32).
Time series causality tests are used to examine hypotheses about the determinants of insurance premiums and causes of the underwriting cycle. The evidence supports the hypothesis that underwriting cycles are partially due to costly external capital as predicted by Winter (1989), Cummins and Danzon (1992), and Gron (1992).
This article presents evidence that 90-day Treasury bill rates and underwriting margins for stock property-liability insurers were negatively related and cointegrated over the period 1930-1989. These results imply that underwriting margins fluctuated around a long-term equilibrium relationship with interest rates in a way that is consistent with financial models of insurance prices.
The underwriting cycle—the periodic swing in underwriting profitability in the insurance industry—has received considerable research attention. Studies have focused on causes of the cycle, whether there is truly a cycle, and the relationship between insurance company failure rates and the cycle. Little, if any, research, however, has focused on changes in underwriting practices over the course of the underwriting cycle. The current study considers three aspects of insurers’ underwriting strategy: (i) product concentration, (ii) geographic concentration, and (iii) focus on states with caps on general damages. Our analyses of the NAIC data show that all three aspects display trends that run opposite that of the combined ratio in medical malpractice insurance. During soft markets, which are characterised by low prices, low underwriting profitability and high loss ratios, insurers employ a looser underwriting strategy with lower product and geographic concentration, and less focus on safer states. We observe the use of a tighter underwriting strategy during hard markets, when loss ratios are low and prices and profitability are high. On the basis of observed associations between loss ratios and underwriting strategy, we also indirectly test the capital constraint theory and the risky debt theory. Our empirical results show that weakened capital bases at the firm level are associated with tighter underwriting.
This article reinvestigates the presence and the causes of the underwriting cycle in the French property–liability insurance industry as displayed by the combined ratio for the 1963–2008 period. The question is still a timely issue if we refer to regulation issues and the recent proposals in the Solvency framework to take into account the fluctuations of the profitability in specifying the solvency capital requirement. In the literature, two approaches are traditionally adopted to investigate the underwriting cycle. The first one refers to an endogenous characterization of the cyclical properties from an AR(2) model. The second one claims that the cycle in the property–liability insurance has exogenous sources related to the financial markets and the general economy. In this article, we reconcile the two approaches by using a smooth transition regression model. This model shows that the AR(2) model is relevant in a first regime where the capacity constraint is binding. In contrast, the fluctuations in the combined ratio are positively influenced by the lagged stock market return in a second regime where the capacity is not constrained, as for the most recent period. Moreover, we find that the current capacity is related to the lagged inflation rate in the latter case. These results confirm the idea that the European rules regarding the solvency capital requirement for insurance companies should take into account the state of the economy and the financial markets.
This study examines the effect of tort reform on medical malpractice insurers with an emphasis on the effect of cap levels on noneconomic damages. While previous research finds that caps on noneconomic damages have a beneficial effect on insurer performance, these studies do not evaluate the effects of caps of varying size. Examining insurer data from 1997 to 2007, we test whether cap levels matter. We find that insurer performance generally improves when the cap is set at $250,000, but caps exceeding $250,000 are not associated with improved performance, as they are possibly not binding on award amounts.
An insurance company entering the property and liability insurance market at the high point of the insurance cycle may decide to slash premiums to gain an advantageous market share. Such aggressive intrusion may call forth a concerted industry response, producing a severe decline in the insurance market price. This can ruin some companies, and agrees with the observation that the insurance cycles are correlated with clustered insolvencies. This paper addresses a quantitative analysis of competition-originated cycles; it explores an interplay of rational aggressive and defensive strategies in the multi-period Lundberg-type controlled risk model.
U.S. property–liability insurance markets have displayed insurance cycles, with their swings in underwriting profits, for nearly a century. Various hypotheses have been developed to explain these fluctuations, as follows: financial pricing hypothesis, capacity constraint hypothesis, financial quality hypothesis, option pricing approach and economic pricing hypothesis. Consistent with previous studies despite of examining whether variables possess unit roots, performing an ARDL bound test on underwriting profits from 1950 to 2009 demonstrates that the economic pricing hypothesis may be the most suitable model for explaining historical insurance pricing. An evident cyclical pattern in underwriting profits is explained as dynamic feed back to the long-term equilibrium. Considerable evidence suggests that the supply effect of risk-averse insurance companies has dominated U.S. insurance markets during the last half century.
Speculative efficiency often requires that future changes in a series cannot be forecast. In contrast, series with a cyclical component would seem to be forecastable with decreases, possibly relative to a trend, during the upper part of the cycle and increases during the lower part. On the basis of autoregressive model (AR) estimates, it is considered that there is strong evidence of cycles in insurance underwriting performance as measured by the premium‐to‐loss ratio. Indeed, a large literature attempts to explain this documented cyclicality. First, we show that the parameter estimates from AR models do not lead to any such inference and that in the contrary, the evidence in the data is consistent with no cyclicality at all. Second, we show that a number of different filters lead to the same conclusion: that there is no evidence of in‐sample or out‐of‐sample predictability in annual insurance underwriting performance in the United States.
This paper examines insurance pricing and its regulation in the context of efficient capital markets. Starting with an aggregated model and generalizing results reported recently in the literature about "proper" underwriting profit, the paper turns to disaggregation of the model with m insurance lines. The main result is that no unique set of rates exists that regulators may impose to avoid disturbing market equilibrium. Preliminary empirical evidence presented shows that the "systematic risk" of underwriting profits approaches zero in most lines. Thus an intuitive solution for underwriting profit rates in these lines equal to minus the riskless interest rate, is reasonable.
The conflicting results from previous studies of economies of scale might arise partly from the choice of output measure. This paper discusses conceptual and econometric problems arising from the use of premium income as a proxy for output. This output measure is not independent of the firm's pricing policy and its use implies potentially serious problems of simultaneous equation bias and errors in variables. It is argued that a delivery-based output measure is theoretically superior and will encounter less severe econometric problems. Cost functions estimated with the delivery-based measure do reveal significant scale economies in the Canadian property-liability insurance industry.
This paper examines auto liability loss reserve levels of nine large property-liability insurers from 1955-1974. These data are compared to previous empirical studies of auto liability reserves. Several statistical tests are used to determine if insurers manage loss reserve levels to smooth underwriting results. Auto liability underwriting returns adjusted for fully developed losses are tested for normality. Finally, a comparison is made between the results of direct writers and those of independent agency insurers.
The underwriting beta is an important parameter in the application of financial theory to property-liability insurance pricing and rate regulation. This paper presents the results of using quarterly profit data to estimate underwriting betas for 14 property-liability insurers. Sensitivity of the estimates to alternative model specifications, market return series, and estimation periods is examined. The results imply that underwriting betas may have been subject to significant instability during the 1970s. This finding suggests extreme caution if underwriting betas are to be used to establish fair profit margins in rate regulation. Possible reasons for instability in the estimated underwriting betas are discussed.
Insurers and rating bureaus often use regression of past costs, or of loss ratios, on time as a way of estimating future rate requirements. A model of this process suggests that the rates set by such methods would create a quasi-cyclical pattern of underwriting profit margins. The details of the forecasting method determine the characteristics of the cylical pattern, so different lines may have different periods or different phases. Empirical data on major lines of property and liability insurance are consistent with the hypothesis that ratemaking methods contribute to the fluctuations of underwriting profit margins.
Virtually all western countries regulate the reserves of insurance firms, even when they do not directly regulate the premiums charged. The justification for such reserve requirements is usually based on consumer ignorance; it is alleged to be costly if not impossible for a typical consumer of insurance to determine the level of reserves held by insurance firms from which he buys; consequently, consumers would often be unprepared for insurer default.1) But even if one accepts the premise of consumer ignorance, the premise only implies that reserves regulation may be useful.
DISSERTATION (PH.D.)--THE UNIVERSITY OF MICHIGAN Dissertation Abstracts International,
Thesis (Ph.D.)--University of Michigan, 1977. Bibliography: p. 191-194. Chair: W. Allen Spivey
Capital market equilibrium rates of return on equity for property-liability insurers and underwriting profit margins by line that are consistent with these are derived by using the capital asset pricing model and measurements of cash flows by line. The profit solutions depend on the cash flows and systematic risks of the lines and on the yield of risk-free securities, but not on company investment portfolios. Recent historical profit margins by line are shown to be much closer to the solutions derived than to the traditional profit margin factors routinely included in rate filings in almost every state.
There has been substantial interest in the question of how (and whether) to allow for investment income in setting rates for property-liability insurers. In a sense this interest is premature, since the fair (i.e., competitive) total profit for an insurance firm has not been defined except by unsupported rules of thumb. This article uses the capital asset pricing model to determine the competitive insurance premium and profit rate. Fair profit rates for real lines of insurance are then calculated and compared with actual profit rates. The comparison suggests that rule-of-thumb profit rates used in regulation are above the level that would occur in a competitive insurance market.
The primary aim of the paper is to place current methodological discussions in macroeconometric modeling contrasting the ‘theory first’ versus the ‘data first’ perspectives in the context of a broader methodological framework with a view to constructively appraise them. In particular, the paper focuses on Colander’s argument in his paper “Economists, Incentives, Judgement, and the European CVAR Approach to Macroeconometrics” contrasting two different perspectives in Europe and the US that are currently dominating empirical macroeconometric modeling and delves deeper into their methodological/philosophical underpinnings. It is argued that the key to establishing a constructive dialogue between them is provided by a better understanding of the role of data in modern statistical inference, and how that relates to the centuries old issue of the realisticness of economic theories.
ABSTRACTA discrete‐time option‐pricing model is used to derive the “fair” rate of return for the property‐liability insurance firm. The rationale for the use of this model is that the financial claims of shareholders, policyholders, and tax authorities can be modeled as European options written on the income generated by the insurer's asset portfolio. This portfolio consists mostly of traded financial assets and is therefore relatively easy to value. By setting the value of the shareholders' option equal to the initial surplus, an implicit solution for the fair insurance price may be derived. Unlike previous insurance regulatory models, this approach addresses the ruin probability of the insurer, as well as nonlinear tax effects.
Single period and dynamic valuation models in continuous time, under certainty and uncertainty, are developed for a property‐liability insurance contract to determine the “fair” (competitive) premium and underwriting profit. The intertemporal stochastic model assumes that the claim frequency and the price index of claim settlements are functions of a set of underlying state variables which follow a multivariate Wiener process. The competitive premium is shown to be proportional to the claim frequency and the price index for claim settlements at the time the policy is issued. The factor of proportionality varies directly with the claim settlement rate and the length of coverage, and inversely with the risk‐adjusted real interest rate on the dollar‐valued claim rate.
Loss reserve deficiencies and underwriting results, Best's Review, Property and Casualty ed
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The underwriting cycle and investment income
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