ARC 2009 Yunjie (Winnie) Household’s Life Insurance Demand - Sun a Multivariate Two Part Model Welcome! Introduction Data Edward (Jed) W. Frees Statistical Models Yunjie (Winnie) Sun Conclusion The End! School of Business, University of Wisconsin-Madison July 30, 2009 1 / 19
Outline ARC 2009 Yunjie (Winnie) Sun Welcome! Introduction Introduction 1 Data Statistical Data 2 Models Conclusion Statistical Models 3 The End! Conclusion 4 2 / 19
Introduction Objective ARC 2009 To understand characteristics of a household that drive life insurance demand Yunjie (Winnie) with more sophisticated analytical techniques Sun Welcome! Data Introduction Data 2004 Survey of Consumer Finance Statistical Build on the work of Lin and Grace (2007) by using covariates that they Models developed Conclusion Model features The End! Two part Model Frequency model - Whether or not to have life insurance Severity model - The amount of insurance a household demands given they decide to have life insurance Multivariate Model Term life insurance Whole life insurance Important finding Demand of term and whole life insurance are substitutes in frequency and complements in severity. 3 / 19
Introduction Objective ARC 2009 To understand characteristics of a household that drive life insurance demand Yunjie (Winnie) with more sophisticated analytical techniques Sun Welcome! Data Introduction Data 2004 Survey of Consumer Finance Statistical Build on the work of Lin and Grace (2007) by using covariates that they Models developed Conclusion Model features The End! Two part Model Frequency model - Whether or not to have life insurance Severity model - The amount of insurance a household demands given they decide to have life insurance Multivariate Model Term life insurance Whole life insurance Important finding Demand of term and whole life insurance are substitutes in frequency and complements in severity. 3 / 19
Introduction Objective ARC 2009 To understand characteristics of a household that drive life insurance demand Yunjie (Winnie) with more sophisticated analytical techniques Sun Welcome! Data Introduction Data 2004 Survey of Consumer Finance Statistical Build on the work of Lin and Grace (2007) by using covariates that they Models developed Conclusion Model features The End! Two part Model Frequency model - Whether or not to have life insurance Severity model - The amount of insurance a household demands given they decide to have life insurance Multivariate Model Term life insurance Whole life insurance Important finding Demand of term and whole life insurance are substitutes in frequency and complements in severity. 3 / 19
Introduction Objective ARC 2009 To understand characteristics of a household that drive life insurance demand Yunjie (Winnie) with more sophisticated analytical techniques Sun Welcome! Data Introduction Data 2004 Survey of Consumer Finance Statistical Build on the work of Lin and Grace (2007) by using covariates that they Models developed Conclusion Model features The End! Two part Model Frequency model - Whether or not to have life insurance Severity model - The amount of insurance a household demands given they decide to have life insurance Multivariate Model Term life insurance Whole life insurance Important finding Demand of term and whole life insurance are substitutes in frequency and complements in severity. 3 / 19
Motivation ARC 2009 Yunjie (Winnie) Sun Life insurance demand literature: How much life insurance protection a household would seek given their Welcome! economic and demographic structure (see Goldsmith (1983), Burnett and Palmer (1984) and Lin and Grace (2007)) Introduction Tobit and OLS are widely applied. Data Term and Whole life insurance are substitutes. Statistical Models Two part model Conclusion Analogous to decision making process The End! Allow for different explanatory variables for frequency and severity models respectively Multivariate models Model two dependent variables simultaneously Examine the substitutes or complements effect of term and whole life insurance 4 / 19
Motivation ARC 2009 Yunjie (Winnie) Sun Life insurance demand literature: How much life insurance protection a household would seek given their Welcome! economic and demographic structure (see Goldsmith (1983), Burnett and Palmer (1984) and Lin and Grace (2007)) Introduction Tobit and OLS are widely applied. Data Term and Whole life insurance are substitutes. Statistical Models Two part model Conclusion Analogous to decision making process The End! Allow for different explanatory variables for frequency and severity models respectively Multivariate models Model two dependent variables simultaneously Examine the substitutes or complements effect of term and whole life insurance 4 / 19
Motivation ARC 2009 Yunjie (Winnie) Sun Life insurance demand literature: How much life insurance protection a household would seek given their Welcome! economic and demographic structure (see Goldsmith (1983), Burnett and Palmer (1984) and Lin and Grace (2007)) Introduction Tobit and OLS are widely applied. Data Term and Whole life insurance are substitutes. Statistical Models Two part model Conclusion Analogous to decision making process The End! Allow for different explanatory variables for frequency and severity models respectively Multivariate models Model two dependent variables simultaneously Examine the substitutes or complements effect of term and whole life insurance 4 / 19
Data ARC 2009 Yunjie (Winnie) Sun Survey of Consumer Finances (SCF) data Welcome! A triennial survey of U.S. families conducted by the Federal Reserve Introduction Data About 4000 household level ("primary economic unit") observations Statistical during each survey period Models Conclusion A probability sample of the U.S. population The End! Extensive demographic and economic characteristics of the households as well as their behavioral aspects such as the motive to leave a bequest Limitations Life insurance information is aggregate. No information about when the life insurance was purchased. 5 / 19
Data ARC 2150 married couples of age range from 20 to 64 (2004 SCF data) 2009 Dependent variable Yunjie (Winnie) Frequency Part (2150 observations) Sun Term life insurance indicator (65.86%) Whole life insurance indicator (33.40%) Welcome! *19.72% have both types of insurance Introduction Severity Part (1710 observations—Life insurance purchasers subsample) Data Face amount of term life insurance (Median $270,000) Statistical Net Amount at Risk (NAR) of whole life insurance (Median $202,500) Models * Positively correlated Conclusion The End! Histogram of Face Value of Term Histogram of NAR of Whole 400 250 200 300 Frequency Frequency 150 200 100 100 50 0 0 0e+00 1e+06 2e+06 3e+06 4e+06 5e+06 6e+06 0e+00 2e+06 4e+06 6e+06 8e+06 Term Whole 6 / 19
Explanatory Variable ARC 2009 We build on the work of Lin and Grace (2007) by using covariates that they Yunjie (Winnie) developed. Sun Welcome! Financial Vulnerability Index (IMPACT) Introduction Measures the adverse financial impact in terms of living standard decline Data upon the death of one member of the household on the rest Statistical Models Conclusion The End! 7 / 19
Explanatory Variable ARC 2009 We build on the work of Lin and Grace (2007) by using covariates that they Yunjie (Winnie) developed. Sun Welcome! Financial Vulnerability Index (IMPACT) Introduction Measures the adverse financial impact in terms of living standard decline Data upon the death of one member of the household on the rest Statistical Models Assets Conclusion Cash and cash equivalents, mutual funds, stocks, bonds, annuities, The End! individual retirement accounts, real estate, and other assets 7 / 19
Explanatory Variable ARC 2009 We build on the work of Lin and Grace (2007) by using covariates that they Yunjie (Winnie) developed. Sun Welcome! Financial Vulnerability Index (IMPACT) Introduction Measures the adverse financial impact in terms of living standard decline Data upon the death of one member of the household on the rest Statistical Models Assets Conclusion Cash and cash equivalents, mutual funds, stocks, bonds, annuities, The End! individual retirement accounts, real estate, and other assets Debts 7 / 19
Explanatory Variable ARC 2009 We build on the work of Lin and Grace (2007) by using covariates that they Yunjie (Winnie) developed. Sun Welcome! Financial Vulnerability Index (IMPACT) Introduction Measures the adverse financial impact in terms of living standard decline Data upon the death of one member of the household on the rest Statistical Models Assets Conclusion Cash and cash equivalents, mutual funds, stocks, bonds, annuities, The End! individual retirement accounts, real estate, and other assets Debts Age 7 / 19
Explanatory Variable ARC 2009 We build on the work of Lin and Grace (2007) by using covariates that they Yunjie (Winnie) developed. Sun Welcome! Financial Vulnerability Index (IMPACT) Introduction Measures the adverse financial impact in terms of living standard decline Data upon the death of one member of the household on the rest Statistical Models Assets Conclusion Cash and cash equivalents, mutual funds, stocks, bonds, annuities, The End! individual retirement accounts, real estate, and other assets Debts Age Education 7 / 19
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