New Paradigm for International Insurance Comparison: With an Application to Comparison of Seven Insu

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New Paradigm for International Insurance
ComparisonWith an Application to Comparison of
Seven Insurance Markets

• Wei Zheng, Peking University
• Yongdong Liu, China Academy of Sciences
• Yiting Deng, Peking University

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Outline

• 1. Introduction
• 2. Comparison of Insurance Growth Level
• 3. Comparison of Insurance Growth Structure
• 4. Economic and Institutional Factors in
  Insurance Growth
• 5. Conclusion

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1. Introduction

• Commonly used methods for international insurance
  comparison
• premium income method
• insurance density method
• insurance penetration method
• Limitations of the above methods
• They fail to take into consideration the
  relationship between insurance penetration and
  economic development stage
• A new paradigm is proposed
• BRIP comparison of Insurance Growth Level
• Trichotomy comparison of Insurance Growth
  Structure

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1. Introduction

• Application to seven markets
• U.S.
• Japan
• U.K.
• Brazil
• Russia
• India
• China
• Sometimes we also refer to data of OECD average,
  BRIC average and world average.

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2. Comparison of Insurance Growth Level

• 2.1 New Method BRIP
• 2.2 Ordinary model of insurance growth
• 2.3 Comparison of Ranking Results under the New
  Method and the Traditional Methods

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2.1 New Method BRIP

• Benchmark Ratio of Insurance Penetration
• benchmark penetration refers to the world
  average insurance penetration at a countrys
  economic level
• actual penetration refers to a countrys actual
  penetration
• The central idea here is to measure the
  benchmark-adjusted insurance growth level
  instead of a traditional one.
• The difficulty is how to get the benchmark
  penetration.

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2.2 Ordinary model of insurance growth

• Carter Dickinson (1992) and Enz (2000)
  developed a logistic model to depict the
  relationship between insurance penetration and
  GDP per capita.
• Y insurance penetration
• X GDP per capita
• C1, C2, C3 three parameters
• e residual
• This paper uses the data of 95 countries
  (regions) over the past 27 years (1980-2006) as
  the sample.

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Estimates of Ordinary Growth Model
The Robust t-statistics is in parentheses. The
term of means the level of significance is
1.
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Regression Curves of Ordinary Growth Model
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Why use BRIP ?

• The international insurance comparison will make
  more sense only when it is based on the
  comparable benchmark-adjusted insurance growth
  level.
• BRIP is such a benchmark adjustment to
  insurance penetration.
• So, BRIP represents a more reasonable indicator
  for the international insurance comparison.

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Whats the economic implications of BRIP ?

• BRIP 1 the countrys actual penetration is
  equal to the world average penetration at that
  countrys economic development stage
• BRIP lt 1 the actual penetration is less than the
  average
• BRIP gt 1 the actual penetration is greater than
  the average
• There is a positive correlation between the BRIP
  and the relative insurance growth level of that
  country.

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2.3 Comparison of Ranking Results (2006)
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To sum it up,

• We should have a new recognition for the
  insurance growth level of each country
• the benchmark-adjusted insurance growth level of
  the emerging countries is not as low as what
  traditional methods indicate
• the benchmark-adjusted insurance growth level of
  the developed countries is not as high as what
  traditional methods imply
• Put it in another way, for the year 2006, the
  ranking of the growth potential of the seven
  countries would be like this (from large to
  small) Russia, Brazil, China, US, Japan, India
  and UK

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3. Comparison of Insurance Growth Structure

• 3.1 Introduction to Trichotomy
• 3.2 Adjusted model of insurance growth
• 3.3 Comparison of Growth Structure

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3.1 Introduction to Trichotomy

• Insurance growth can be decomposed into three
  parts
• Regular growth
• Insurance growth accompanying the economic growth
  assuming the insurance penetration is unchanged
• Deepening growth
• Insurance growth brought about by the increase of
  insurance penetration induced by economic growth
• Institutional growth
• The remaining part of the growth, which is
  brought about by the institutional factors after
  the economic factors have been deducted

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Trichotomy of Insurance Growth Structure
Adjusted Growth Curve of World Insurance
Penetration
D
C
B
A
GDP per Capita
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Trichotomy of Insurance Growth Structure
Adjusted Growth Curve of World Insurance
Penetration
D
C
B
A
GDP per Capita
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Trichotomy of Insurance Growth Structure
Adjusted Growth Curve of World Insurance
Penetration
D
C
B
A
GDP per Capita
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3.2 Adjusted model of insurance growth

• Y insurance penetration
• X GDP per capita
• C1, C2, and C3 three parameters
• Di(i1,94) country dummy with respect to
  country i
• ?i(i1,94) coefficient for Di
• e residual

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Estimates of Adjusted Growth Model
The Robust t-statistics is in parentheses. The
term of means the level of significance is
1.
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Regression Curves of Adjusted Growth Model
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3.3 Comparison of Growth Structure
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To sum it up,

• In developed countries, the insurance growth is
  mainly driven by the economic factors (including
  regular and deepening factors)
• In emerging countries, the insurance growth is
  largely driven by the institutional factors

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4. Economic and Institutional Factors in
Insurance Growth

• 4.1 Comparison of Two Growth Models
• 4.2 Discussion on Institutional Factors
• 4.3 Discussion on Developed and Emerging Countries

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4.1 Comparison of Two Growth Models

• Ordinary growth model
• combines both the economic factors and
  institutional factors that influence the
  insurance growth
• Adjusted growth model
• separates the country-specific institutional
  influences and the common economic influences

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Comparison of Two Models for Life Insurance
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Comparison of Two Models for Non-Life Insurance
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Comparison of Two Models for Insurance Industry
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Comparison of Two Models for Insurance Industry

• In the figure
• Ordinary growth curve combines both economic and
  institutional factors
• Adjusted growth curve reflects only pure
  economic factors
• When GDP per capita is low, the ordinary curve is
  higher than the adjusted curve, which indicates
  that institutional factors facilitate the growth
  of the insurance industry to some degree.
• When GDP per capita is high, the ordinary curve
  is obviously lower than the adjusted curve, which
  indicates that institutional factors markedly
  restrain the growth of the insurance industry.

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4.2 Discussion on Institutional Factors

• Major institutions
• social security system (systematic institution)
• dominantly affects the life insurance
• legal system (systematic institution)
• dominantly affects the non-life insurance, with
  its most typical components being the compulsory
  insurance and liability insurance
• culture (non-systematic institution)
• religion (non-systematic institution)

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Effects of institutional factors on life insurance

• Relationship between life insurance and social
  security
• usually substitutable
• the better developed the social security system
  is, the more the life insurance growth is
  restricted
• Relationship between social security and GDP per
  capita
• usually positive correlation
• low GDP per capita countries social security
  system is usually under-developed
• high GDP per capita countries social security
  system is usually well-developed
• Thus, as the GDP per capita increases (with the
  improvement of social security system), the
  negative effects of institutional factors on life
  insurance would gradually increase.

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Effects of institutional factors on non-life
insurance

• Relationship between non-life insurance and
  certain legal policies
• usually complementary
• the more compulsory insurance and liability
  insurance are implemented, the more growth
  opportunities will be created for the non-life
  insurance
• Relationship between certain legal policies and
  GDP per capita
• usually no direct relation
• the governments decision of whether to adopt
  those legal policies (the compulsory insurance
  and liability insurance) is mainly based on the
  consideration of social policy (such as equity
  and justice), and generally is not related to GDP
  per capita
• Thus, no matter how large GDP per capita is,
  institutional factors will always bring positive
  effects to the growth of non-life insurance.

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Effects of institutional factors on insurance
industry

• When GDP per capita is low
• institutions have some positive effects on both
  the life insurance and the non-life insurance
• with its net effects on the insurance industry
  being positive
• When GDP per capita is high
• institutions have remarkably negative effects on
  the life insurance and some positive effects on
  the non-life insurance
• with its net effects on the insurance industry
  being negative, and the negative effects are
  notable

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4.3 Discussion on Developed and Emerging Countries

• For the emerging countries
• institutional factors facilitate the growth of
  the insurance industry to some degree
• For the developed countries
• institutional factors notably restrain the growth
  of the insurance industry
• It could also imply that as the economy develops,
  the contribution of the institutional factors to
  the insurance growth would gradually decrease,
  and the economic factors would play a more active
  role in driving the insurance growth.

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4.3 Discussion on Developed and Emerging Countries

• This implication suggests that, for those
  emerging countries, after the insurance industry
  having experienced a period of taking-off, its
  growth will gradually change from being driven
  by both economic and institutional factors to
  being driven mainly by economic factors.
• Following this judgment, it is extremely
  important for the insurance industry in the
  emerging countries to upgrade its growth strategy
  from the extensive developing pattern to a
  refined and sustainable developing pattern, for
  the former one will lose its foundation for
  surviving.

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5. Conclusion

• 1. We should have a new recognition for the
  insurance growth level of each country.
• BRIP gives a different and probably more
  reasonable answer
• 2. The insurance growth in developed countries is
  mainly driven by the economic factors, while that
  in emerging countries is largely driven by the
  institutional factors.
• 3. As the economy develops, the contribution of
  the institutional factors to the insurance growth
  would gradually decrease, and the economic
  factors would play a more active role in driving
  the insurance growth.

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