1 48 Yong Jian Khoo Australian National University Yong Jian Khoo graduated from the Australian National University in 2010 with a Bachelor of Actuarial Studies (with honours). He has completed the part I and II exams of the Institute of Actuaries of Australia and is working towards his fully qualified actuary status whilst working as an actuarial graduate for Prudential (Singapore). Economic cycles, financial shocks and life insurance a selected investigation of the Australian experience Yong Jian Khoo The Australian life insurance market Life insurance serves various purposes, such as mitigating the financial impact of adverse events such as death or disablement; providing a means of private savings; and for funding retirement. It can be described as the business of providing payment of sums of money at dates in the future: the payment being dependent on the satisfaction of specified conditions contingent on the death, survival or state of health of the person insured 1. Clearly, the amount of money an individual spends on life insurance varies with age, financial needs, health, budget and priorities. Currently, products that involve some form of mortality, morbidity or longevity risk can only be sold by a life insurer. There are currently 31 registered life insurers in Australia with annual premiums approximately $40 billion, and total assets under management of approximately $240 billion. Four broad categories of products exist in Australia savings products, retirement income products, risk products, and traditional products which consist of both savings and risk components. Each category of products has an important role to play in the well being of Australians, although for various reasons traditional products have become less popular in the past 25 years and are no longer sold. The popular savings vehicles are investment account and investment linked products, with some form of guarantee able to be provided on the original investment value or this amount plus interest previously credited. Various retirement products exist, with the most popular product being an allocated pension which is an account-based pension that can provide a regular income. However the income payments under this product are not guaranteed, with options around investment choice and income (withdrawal) payments but within certain limits. The policy owner bears both longevity risk and investment risk, in contrast to a lifetime immediate annuity, for example, where these risks are borne by the issuing office. Risk products have no savings component, but provide a significant proportion of total industry sales and are an important component of the life market. They can be categorised as lump sum products or income products. Lump sum risk products that pay upon death consist of term insurance and yearly renewable term (YRT), with the latter the major contributor to total risk insurance sales. YRT premiums increase with age to reflect the increasing mortal-
2 49 ity risk, and as long as regular premiums are paid, the policyholder is guaranteed the right to renew the policy without any proof of health. Lump sum risk products that pay upon ill health include total and permanent disability (TPD) and trauma. TPD provides a lump sum benefit to the policyholder in the event of total and permanent disability (the exact definition of permanent disability depends on the actual policy), whereas trauma insurance pays a lump sum benefit when the insured is diagnosed with one of a specified set of illnesses or injuries such as heart attack, stroke and cancer. Income risk products include disability income (DI) insurance, which provides benefits at regular intervals during the period of disablement for a specified period or up to a specified age. Economic cycles and the GFC Economic cycles are a type of fluctuation found in aggregate economic activity of nations that organize their work mainly in business enterprises with sequences of changes that are recurrent but not periodic 2. They can be described by movements in real Gross Domestic Product (GDP) and are divided into 4 phases: trough, expansion, boom and contraction, with troughs being the lowest points of real GDP growth and booms being the highest. GDP, however, can be volatile and subject to measurement error, and may not give a good indication of the development of the broad economy as any changes to GDP might be caused by shocks to only certain economic sector(s) 3. Various theories abound as to the cause of economic cycles, none of which seem to offer a complete explanation and considerable debate exists in the literature. The most recent slowdown in the Australian economy is closely related to what has popularly been called the Global Financial Crisis (GFC). As housing prices in the US started to fall in 2007, default rates of subprime mortgages increased. As defaults and foreclosures increased, the sellers of credit default swaps (CDS s) faced increasing pressure in fulfilling their obligations as the protection sellers. Several iconic financial institutions such as Bear Stearns, Lehman Brothers and American International Group (AIG) had more exposure to the CDS market than they could afford. The interbank lending started to dry up when Bear Stearns first showed that it was facing financial difficulty 4. The subsequent collapse of Lehman Brothers in September 2008 caused panic in financial markets which was felt in major economies around the world. The GFC has had a material impact on Australian economy. The Australian All Ordinaries Index dropped 55% between November 2007 and March The unemployment rate (seasonally adjusted) increased from 4.0% in February 2008 to 5.8% in June Several major corporations failed such as Allco, Babcock & Brown, and ABC Learning. However, the impact of the GFC on the Australian economy was much less severe than the impact on other economies, such as the US and many European nations. Australia weathered the GFC mainly due to the strength of its financial system and strong demand for commodities from Asian countries, especially China 6. Investigation A selected investigation was carried out into several facets of the life insurance industry in Australia. Where possible the impact of the GFC is discussed in light of broader insights about the more general impact of economic cycles, for the sake of context and additional insight into GFC-specific impacts. The main focus is on the demand for life insurance in the context of historical trends and existing theoretical perspectives, and also on changes to asset allocations given the significant fall in equity markets. Brief discussions of lapse rate and mortality / morbidity dynamics are also presented. Historical economic data was sourced from the Reserve Bank of Australia (RBA), the Australian Bureau of Statistics (ABS), and the World Bank (WB). The data includes inflation (as measured by the consumer price index (CPI)), unemployment rates, real GDP growth, real GDP per capita, and real interest rates. Annual reports for twelve life insurance companies (or their subsidiaries) in Australia were sourced 7. These companies represent more than 90% of the Australia life insurance industry, so the intent was that since those companies made up majority of the life insurance industry, impacts on those companies infer impacts across the industry. All companies investigated have at least four annual reports covering 2006 to They cover the period just before the GFC and during the GFC. Additional aggregate information across the industry was sourced from APRA. Life insurance demand Theoretical perspectives Economic variables such as personal income, inflation, interest rates and unemployment have been identified by various researchers to influence the demand for life insurance. In many cases however, the findings have not been conclusive 8. Many studies find income to be an important determinant of life insurance consumption 9 while two main explanations exist for an increase in demand for life insurance with income 10 : It is reasonable to assume that life insurance is a normal good; its consumption should increase as income increases and various life insurance products can be considered an option to absorb subsequent surplus funds; Personal income can be viewed as an opportunity cost of dying. Debt levels may also increase with income level. Thus, life insurance policies can be used to reduce the financial impact of an adverse event (such as death or disablement) to the policyholders and their dependents. Many studies find income to be an important determinant of life insurance consumption.
3 50 Figure 1: Life insurance penetration and life insurance density Source: APRA (2008a, 2008b, 2009a, 2009b, 2009c, 2009d, 2010) Life insurance penetration rates and density generally increased from 1980 up to 1999/2000, then dropped between 1999 and 2005 before rising again. Some studies 11 demonstrate a negative relationship between inflation and the demand for life insurance, even where some policies are inflation-linked 12. High inflation can erode the real value of the benefit payment(s) or protection and reduce the expected return from life insurance policies. The impact of inflation on life insurance demand varies with the product type, as it is possible that policyholders would give up savings products first, rather than risk products. Ambiguity exists however, in that if life insurance is viewed as a necessary consumption, policyholders may increase life insurance consumption to ensure they are adequately insured, but on the other hand, people may buy less life insurance as inflation will erode its real value. In Australia, inflation rates have historically been positively correlated with nominal interest rates due to the monetary policy agenda set by the RBA. Hence, as life insurance demand is expected to be affected negatively by inflation rates, the same relationship would be expected between life insurance demand and interest rates. Various studies show a negative relationship between unemployment and life insurance demand. However the level of individual savings is also important here, where an individual with high levels of savings would be able to survive longer periods of unemployment and hence better manage the financial impact of being unemployed. Historical analysis Various measures have been used as a proxy for life insurance demand 13. Two such measures are life insurance penetration 14, and life insurance density 15. Consistent with past studies, these were used as proxies for life insurance demand 16. Figure 1 shows the life insurance penetration rate and life insurance density in Australia from 1980 to Life insurance penetration rates and density generally increased from 1980 up to 1999/2000, then dropped between 1999 and 2005 before rising again. The divergence in experience of life insurance penetration and life insurance density after 2000 is due to the life insurance premiums growing at slower rates 17 than nominal GDP but at faster rates than population growth. The amount of money spent on life insurance per capita (as measured by life insurance density) increased by a factor of 16 between 1980 and Many events and trends have contributed to the changes in life insurance demand from 1980 to 2008, including but not limited to a greater role played by self-employed brokers and agents from the 1980 s 18 ; the stock market crash of 1987 and the recession of the early 1990 s; the introduction of the Superannuation Guarantee Charge which boosted the savings business, both in the life insurance industry and the wider financial sector; deregulation and demutualization of the life insurance industry 19 ; a series of mergers and acquisitions amongst life insurance companies 20 ; the greater role played by banks where now all four major Australian banks have their own life insurance arm; the impact of the Financial Services Reform Act 2001 and the establishment of APRA in 1998; and the removal of tax benefits for life insurers in July 2000 as a result of a review of business taxation 21. Under more formal correlation tests, it was found that both life insurance penetration and density is significantly positively correlated with real GDP per capita. There is also a negative and significant correlation between inflation rates and life insurance penetration and density. Both of these findings support the studies stated earlier. The relationship with unemployment is mixed, with life insurance density (but not life insurance penetration) having a significant negative correlation. In other words, the Australian experience seems to indicate that as real incomes rise, so does the demand for life insurance (probably heavily influenced by increases in savings products); as inflation rises, there is a negative impact on life insurance demand; and as unemployment rises, the impact is more un-
4 51 certain. Impact of the GFC Increased attention on risk business has been mentioned by various sources 22. This increased focus was and is probably due to increased awareness and perception of need in the community, increased focus from life insurers in this area, a shift in attention from advisors, as well as the more obvious decreased demand for savings and investment products. In terms of the total life insurance industry, figure 2 shows the annual net premiums and net policy payments from 1998 to The spike in the annual net premiums in 2008 was the result of changes to the superannuation system in 2007 and is viewed as a one-off event 23. The annual net premiums for the year to 31 March 2010 reduced slightly. However, considering the magnitude of the GFC, the fall was not significant. This could be due to offsetting effects of rising unemployment rates, falling inflation rates and a slight reduction in real GDP per capita in Lapse, mortality and morbidity rates Data was not sourced for an analysis of lapse, mortality and morbidity rates. Brief overviews of expected impacts, and findings from ready sources such as annual reports (where applicable) are given below. Figure 2: Annual Net Premiums and Net Policy Payments for Year to 31 March (total life insurance business) Source: APRA (2008c, 2010) Figure 3: Asset allocation for non-investment linked products Lapse rates Two main hypotheses address the relationship between economic conditions and lapse rates: The Emergency Fund Hypothesis (EFH) that policyholders use cash surrender values from their policies as emergency funds in the time of financial distress. Therefore lapse rates are expected to increase during recessions as some policyholders may become unemployed and face financial distress 25. The impact would again differ by product however clearly with no cash value, risk products would not be impacted by the EFH. The Interest Rate Hypothesis (IRH) that interest rates act as an opportunity cost for owning life insurance policies so that when interest rates rise, lapse rates will increase. There were some minor changes in the assumed voluntary discontinuance in 2008 and 2009 in some life insurers. As the changes were not consistent across all life insurers, it is not expected that these changes were a consequence of the GFC, but more of a reflection of differences in the particular experience of life insurers over time. Alternatively, this observation could be the result of opposing impact of the EFH and the IRH. During the GFC, the unemployment rate increased while interest rates dropped 26. While the EFH suggests lapse rates could increase, the IRH suggests a reduction in lapse rates. Hence the overall impact is ambiguous. Mortality Many studies have investigated the impact of economic variables such as unemployment rates and short term interest rates on mortality 27. The results are mixed, and sometimes differ depending on whether the mortality in question is that of an insured group, or the general population. Source: APRA (2010) During unfavourable economic conditions, it is expected that there will be higher rates of claim incidence as well as longer claim durations with disability income (DI) policies. Morbidity During unfavourable economic conditions, it is expected that there will be higher rates of claim incidence as well as longer claim durations with disability income (DI) policies. Studies highlight positive relationships between unemployment and incidence rates as well as unemployment and claim durations in the Australian context. That is, the higher the rate of unemployment, the higher the incidence and durations of DI claims 28.
5 52 The financial and non-financial risk can be borne by the shareholders, policyholders or both. Asset allocations Non investment linked Figure 3 shows the asset allocation for non-investment linked products from 2008 to the first quarter of The asset allocations for non-investment linked policies are usually decided by the life insurers as they bear the investment risk. A high proportion is invested in debt securities and cash which reflects the more conservative strategy required to meet guarantees with these products. During the GFC, fluctuations in the holdings of equities, cash and deposits and debt securities are evident. There was a material increase of about 10% in cash and deposits held. It could be that life insurers became more conservative and held more cash to withstand the impact of substantial investment losses and to provide for any guarantee embedded in certain products. The drop of nearly 50% in the proportion of assets held in equities is not surprising given the Australian equity market dropped by a similar percentage. Investment linked Figure 4 shows the allocation for assets backing investment linked policyholder liabilities from 2008 to the first quarter of In contrast to non-investment linked policies, significantly more assets were invested in equities. This is because the asset allocations for investment linked policies are generally at the discretion of the policyholders as they bear the investment risk, and this allocation likely reflects the relatively high risk tolerance and long time horizon of policyholders. As can be seen above, there were relatively little changes in asset allocations for investment linked products compared to non-investment linked products, with only a slight drop in the overall proportion of funds held as equities. This is surprising, given the magnitude of the drop in the Australian equity market, but may be attributable to the risk profile and time horizons of these investors. It may also be due to policyholders not wanting to realise losses, not having trusted alternatives with a long term view, or being faced with costs associated with changing asset allocations which may have discouraged policyholder action in this regard. Profit Nature of profit for life insurance Life insurance profit (excluding tax) is defined as: where P = Premium income, I = Investment earnings, C = Claim payments, E = expenses and ΔR = changes in reserves. The major impact on life insurance profit is the claims experience. An unexpected improvement in mortality or morbidity rates will benefit the life insurer as less claims need to be paid out. For DI insurance, the benefit payments depend on both the incidence rate of policyholders becoming disabled and the duration which they remain disabled. For retirement products such as an annuity where benefit payments are contingent on survival, an unexpected improvement in mortality rates will be detrimental to the life insurer. Investment returns determine the return on life office funds. As some policies assume a minimum investment return within the pricing structure, these can be critically important. The expenses of a policy include initial expenses, maintenance or ongoing expenses, investment expenses and termination expenses. Expense levels vary significantly depending on the product. For example, a risk policy incurs costs associated with underwriting that an investment-linked policy does not have. An unexpected rise in expenses or inflationary growth of expenses will reduce the profitability and vice versa. Unexpected increases in policy lapse rates are detrimental for a life office for various reasons. A life insurer might not be able to recoup its initial expenses, resulting in a loss. Also, healthier policyholders are more likely to lapse their policies first leading to adverse selection, which gives an unexpected increase in mortality rates for the remaining policyholders. Changes in reserves held have a direct impact on profit in a given year. The higher the level of reserves held, the less the available funds to be distributed as profit. The financial and non-financial risk can be borne by the shareholders, policyholders or both. Bearing risk simply means that when a profit or loss arises, the profit or loss is attributed to the party bearing the risk. For risk products, shareholders bear the financial and non-financial risk (such as mortality and lapse risk) and policyholders do not share in the profits or losses arising from these policies. In contrast, the financial risk of investment linked savings products are generally borne by policyholders as profits or losses arising from changes in the value of the assets are attributed to them, however shareholders still bear the non-financial risks. For example, if policyholders lapse earlier than expected, any resultant losses are attributable to the shareholders. Impact of the GFC The most obvious and intuitive outcome of an event of the nature of the GFC was a decrease in profit due to large investment losses, even though large investment losses were attributed to the policyholders through investment linked savings products. The negative impact on profit was apparent from most annual reports over the 2008 year and also in the aggregate industry information provided below. Figure 5 shows the quarterly aggregate net profits after tax for the Australian life insurance industry from June 2008 to March 2010.
6 53 YRT modelling Cashflows under a YRT policy were approximated and projected to illustrate the resilience of this product to external factors such as associated with the GFC. YRT was chosen because it is the most popular risk product in Australia due to its flexibility and lower premiums compared to a comparable term insurance. From the perspective of life insurers, YRT is an attractive product as premiums can be revised in the light of ongoing experience. Adopting a series of reasonable pricing assumptions (from a range of sources) relating to expenses, mortality and selection effects, lapses, new business demographic profile, and profit, gave rise to premium rates gave rise that were consistent with industry norms. Implications of the GFC that were then considered include: An overall increase in the cost of capital due to a reduction in its availability 29 ; Negative impacts on investment returns; An increase in sales volumes as a result of the increase in awareness and interest in risk insurance, which in turn can help reduce the fixed expenses of an insurer which are typically allocated across all policies in some manner; A reduction in lapse rates as life insurance may be needed the most during a significant economic downturn, and the low premium rates combined with no surrender value make policyholders less likely to lapse their YRT policies; An unexpected increase in future inflation 30. The first two factors are expected to adversely affect the profit margin on YRT business, and/or present a case for life insurers to raise premiums, though clearly the actual responses taken by life insurers would depend on customer responses and wider market reactions to the same circumstances. The third and fourth points would be expected to offset these adverse impacts in some manner. Two factors worth highlighting here are the investment earnings, which will have only a minor impact on YRT because the cash flows and reserves are small. The impact would differ for traditional and term insurance because life insurers hold larger reserves for these policies. Furthermore, an increase in inflation can actually increase the profit margin. This is due to the option for policyholders to increase the sum insured with inflation, which gives rise to a higher premium, which contributes towards the recoupment of initial expenses. However the extent to which inflationary pressure on an insurer s expenses differs to the inflation increase on sums insured, and also the extent to which the proportion of policyholders exercising their right to increase their sum insured differs to that expected, can have a detrimental effect on profit margins (and hence pressure on premiums). Nevertheless, it appears the case that the inflation option provides good protection for life insurers offering YRT. The results of the projections demonstrated that indeed, there is little reason to see YRT profit and/or premiums being substantially impacted. A 10% increase in sales and 10% decrease in lapses would be sufficient to offset a 20% rise in the cost of capital and a fall in investment earnings to 3% p.a. Sufficient here means that to maintain the same profit margin as before, premiums would not have to change. Whilst this can only be illustrative at best, and heavily dependent on the assumptions adopted, nevertheless the nature and structure Figure 4: Asset allocation for investment linked products Source: APRA (2008c; 2010) Figure 5: Investment revenue and net profit/loss after tax Source: APRA (2008a, 2008b, 2009a, 2009b, 2009c, 2009d, 2010) From the perspective of life insurers, YRT is an attractive product as premiums can be revised in the light of ongoing experience.
7 54 This investigation suggests that it is also due to the mix of products which either limit excessive risk to the insurer, or share the risk with the policyholder. of YRT policies gives confidence that the premiums charged can remain relatively consistent and smooth over time. This is despite the impact of external forces upon a life insurance company such as those associated with the GFC. Notes 1. Carr et al., (2009). 2. Burns and Mitchell (1946). 3. Gillitzer, Kearns & Richards (2005). 4. Markowitz (2009). 5. ABS (2010). 6. Dobbie (2009). 7. AMP, NAB, ANZ, Westpac, CBA, AXA, Suncorp Life and Super, Asteron Life, Suncorp-Metway, Macquarie Life/Macquarie Group, Tower Australia and Challenger Financial Services Group. However a limitation was that the annual reports of ANZ, Westpac, CBA, Macquarie Group and Challenger Financial Services Group contain very little information on their life insurance business. 8. Zietz (2003). 9. Truett and Truett (1990), Browne and Kim (1993), Outreville (1996), Beck and Webb (2003), Hwang and Greenford (2005), and Li et al. (2007). 10. Lenten and Rulli (2006). 11. Babbel (1981), Browne and Kim (1993), Beck and Webb (2003) and Li et al. (2007) 12. Babbel (1981). However, this study was on the Brazilian life insurance market where hyperinflation occurred during the sample period. 13. Zietz (2003). 14. Life insurance penetration is defined as the ratio of premium volume to GDP. 15. Life insurance density is defined as premiums per capita. It measures the average amount spent on life insurance per each individual of a country. Hwang and Greenford (2005) and Li et al. (2007) use life insurance density as a proxy for life insurance consumption. 16. Data for life insurance penetration and life insurance premium is available in annual terms from 1980 to 2008 from the Swiss Re Sigma database (thanks to Professor Garry Twite of the Australian National University for providing this data) and population data from the International Monetary Fund (IMF) website. Correlation tests between life insurance penetration/life insurance density and the relevant economic variables were then conducted, in line with Hwang & Greenford (2005) and Beck & Webb (2003) who used correlation when dealing with similar economic variables. 17. Between 2000 and 2008 life insurance premiums grew on average 3.8% p.a., nominal GDP grew on average 7.2% p.a., and the Australian population grew on average 1.4% p.a. Summary Overall, although there were some impacts on the profitability and financial positions of life insurers, the Australian life insurance industry appears to have been resilient considering the magnitude of the GFC and the impact on the wider economy. This is likely due to effective regulatory standards, adequate levels of reserves, and strong financial positions of life insurers before the GFC. This investigation suggests that it is also due to the mix of products which either limit excessive risk to the insurer, or share the risk with the policyholder. The predominance of investment linked savings products meant that significant investment losses were attributed to policyholders. The structure of the most popular risk product (YRT) allows insurers to revise future premiums which enables ongoing management of emerging risks, and the impact of poor investment returns are not a significant component of the product s viability. From the perspective of the life insurance advisor, it is perhaps the case that even with an event of the size and significance of the GFC, no golden goose exists to promote widespread awareness and interest in what life insurance can offer across all life stages (increased interest in risk products notwithstanding). It is nevertheless valid that many prospective policyholders may be more motivated when economic times are tough (such as during the GFC) to reconsider their life insurance coverage in some form. It is a good advisor however who can stress the need for adequate coverage when times are good. In the Australian context, the advisor can point to the evidence which shows that the policyholder can have high confidence in the fidelity of the life insurance market to meet their policyholder obligations, and in the case of YRT, to do so with some confidence that premiums will remain stable over time. The key it seems is that prospective and existing policyholders know or be encouraged to think about their risk appetite and then be prepared to plan accordingly. The role of the advisor is crucial in this advisory and implementation process. fs This paper was co-authored by Aaron Bruhn and Dr Bronwen Whiting. Bruhn is a lecturer in Actuarial Studies at the Australian National University. He previously worked as an actuary in the New Zealand life insurance industry as well as the public service. He is a fellow of the Institute of Actuaries of Australia and of the New Zealand Society of Actuaries. Dr Whiting is a lecturer in Statistics at the Australian National University. She has a PhD from the Australian National University, and has a particular interest in statistical applications to actuarial issues. fs 18. Lenten and Rulli (2006). 19. The percentage of assets held by mutual life insurance companies dropped from 58% in 1985 to 0% in 2000 (Lenten and Rulli, 2006). 20. Indeed, 58 life insurers in 1990 (Keneley, 2001) shrank to 46 in 1998 (APRA, 1998) and 32 in 2009 (APRA, 2009). 21. Carr et al. (2009). 22. Fourie (2010), NMG (2010), and Tower Australia (2008, 2009). 23. The changes provided tax incentive for certain policyholders to switch from superannuation contracts to allocated pension/annuity products. This caused large inflows and outflows between different products (APRA, 2008). 24. As discussed, unemployment and inflation are expected to have negative relationships with life insurance demand while real GDP per capita is expected to have a positive relationship with life insurance demand. Real GDP per capita reduced in However, overall, real GDP per capita increased from 2007 to Outreville (1990), Kuo et al. (2003). 26. The yield on 90 days bank accepted bill dropped from 6.43% in January 2007 to a low of 3.1% in April Brenner (1979), Brenner & Mooney (1983), Ruhm (2000), Laporte (2004), Tapia Granados (2005), and Hayes (2009). 28. Carr et al. (2009), Schriek and Lewis (2010), Service and Ferris (2001). 29. The GFC decreased the availability of capital at a time when additional capital was needed by companies affected by the GFC (Yan, 2008). The increase in demand combined with a decrease in supply would push up the price of capital. 30. As the Australia economy recovers from the GFC, there is speculation that high levels of inflation may eventuate due to the nature of government responses to the GFC (Collings, 2009). Factors supporting this possibility include (i) high levels of capacity utilization; (ii) strong demand for commodities may give rise to further investment in mining at a faster rate than expected; and (iii) the global recovery has been stronger than expected (RBA, 2010).
8 55 References ABS (Australian Bureau of Statistics) 2010, Labour Force, Australia, February 2010, Australian Bureau of Statistics, Canberra. APRA (Australian Prudential Regulation Authority) 1998, APRA Half Yearly Life Insurance Financial Bulletin June 1998, Australian Prudential Regulation APRA (Australian Prudential Regulation Authority) 2008a, APRA Quarterly Life Insurance Performance September 2008, Australian Prudential Regulation APRA (Australian Prudential Regulation Authority) 2008b, APRA Quarterly Life Insurance Performance December 2008, Australian Prudential Regulation APRA (Australian Prudential Regulation Authority) 2008c, APRA Life Insurance Trends March 2008, Australian Prudential Regulation APRA (Australian Prudential Regulation Authority) 2009a, APRA Quarterly Life Insurance Performance March 2009, Australian Prudential Regulation APRA (Australian Prudential Regulation Authority) 2009b, APRA Quarterly Life Insurance Performance June 2009, Australian Prudential Regulation APRA (Australian Prudential Regulation Authority) 2009c, APRA Quarterly Life Insurance Performance September 2009, Australian Prudential Regulation APRA (Australian Prudential Regulation Authority) 2009d, APRA Quarterly Life Insurance Performance December 2009, Australian Prudential Regulation APRA (Australian Prudential Regulation Authority) 2010, APRA Quarterly Life Insurance Performance March 2010, Australian Prudential Regulation Babbel, DF 1981, Inflation, indexation, and life insurance sales in Brazil, Journal of Risk and Insurance, vol. 48, no. 1, pp Beck, T and Webb, I 2003, Economic, demographic, and institutional determinants of life insurance consumption across countries, The World Bank Economic Review, vol. 17, no. 1, pp Brenner, M 1979, Mortality and the national economy: a review, and the experience of England and Wales , The Lancet, vol. 314, no. 8142, pp Brenner, M and Mooney, A 1983, Unemployment and health in the context of economic change, Social Science and Medicine, vol. 17, no. 16, pp Browne, M and Kim, K 1993, An international analysis of life insurance demand, The Journal of Risk and Insurance, vol. 60, no. 4, pp Burns, Arthur F. and Mitchell, Wesley C. 1946, Measuring Business Cycles, The National Bureau of Economic Research, Cambridge, Massachusetts. Carr et al. 2009, The Practice of Life Insurance in Australia (2009 Ed), The Institute of Actuaries of Australia, Sydney. Collings, S 2009, Discount rates, inflation and risk margins, GI in a GFC World: General Insurance Impacts of the Global Financial Crisis, The Institute of Actuaries of Australia, Sydney. Dobbie, P 2009, How Australia ducked the crisis, Bnet.com. Available at: <http://www.bnet.com/article/how-australia-ducked-the-crisis/352693> [accessed 18 October 2010]. Fourie, P 2010, Insights into the Australia Life Insurance Sector, Australian Journal of Financial Planning, vol. 5, no. 1, pp Gillitzer, C, Kearns, J and Richards A 2005, The Australian business cycle: A coincident indicator approach, RBA Research Discussion Papers, Reserve Bank of Australia, Sydney. Hayes, G 2009, Stochastic Solvency Testing in Life Insurance, School of Finance, Actuarial Studies and Applied Statistics, PhD thesis, The Australian National University, ANU Digital Theses Collection. Available at: < dspace.anu.edu.au/handle/1885/49286> [Accessed on 22 March 2010]. Hwang, T and Greenford, B 2005, A cross-section analysis of the determinants of life insurance consumption in Mainland China, Hong Kong, and Taiwan, Risk Management and Insurance Review, vol. 8, no. 1, pp Keneley, M 2001, The evolution of the Australian life insurance industry, Accounting, Business & Financial History, 11: 2, pp Kuo, W, Tsai, C and Chen, W 2003, An empirical study on the lapse rate: The cointegration approach, Journal of Risk and Insurance, vol. 70, no. 3, pp Laporte, A 2004, Do economic cycles have a permanent effect on population health? Revisiting the Brenner hypothesis, Health Economics, vol. 13, pp Lenten, L and Rulli, D 2006, A time-series analysis of the demand for life insurance companies in Australia: An unobserved components approach, Australian Journal of Management, vol. 31, no. 1, pp Li, D, Moshirian, F, Nguyen, P and Wee T 2007, The demand for life insurance in OECD countries, The Journal of Risk and Insurance, vol. 74, no. 3, pp Markowitz, H 2009, Proposals concerning the current financial crisis, Financial Analysts Journal, vol. 65, no. 1, pp NMG 2010, Insights report: Life risk Australia 2010, NMG Financial Services Consulting. Outreville, JF 1990, Whole-life insurance lapse rates and the emergency fund hypothesis, Insurance: Mathematics and Economics, vol. 9, no. 4, pp Outreville, JF 1996, Life insurance markets in developing countries, The Journal of Risk and Insurance, vol. 63, no. 2, pp RBA (Reserve Bank of Australia) 2010, Statement on Monetary Policy, August Ruhm, C 2000, Are recessions good for your health? Quarterly Journal of Economics, vol. 115, no. 2, pp Schriek, KA and Lewis, PL 2010, The link between disability experience and economic conditions in South Africa, International Congress of Actuaries Service, D and Ferris, K 2001, Disability experience and economic correlations, IAAust Biennial Convention 2001, The Institute of Actuaries of Australia, Sydney. Tapia Granados, J 2005, Increasing mortality during the expansion of the US economy, , International Journal of Epidemiology, vol. 34, no. 6, pp Tower Australia 2008, Annual Report Tower Australia 2009, Annual Report Truett, DB and Truett, LJ 1990, The demand for life insurance in Mexico and the United States: A comparative study, The Journal of Risk and Insurance, vol. 57, no. 2, pp Zietz, EN 2003, An examination of the demand for life insurance, Risk Management and Insurance Review, vol. 6, no. 2, pp Yan, T 2008, The impact of the GFC on the Chinese and Australian economies, Australian China Connections Nov/Dec 2008 Issue.