Who is "Key Demographics in Retirement Risk Management" for?

^{• Researchers and graduate students studying links between population variables and retirement issues (to learn more click here)}

^{• Educators teaching about patterns of preparedness to address retirements' challenges and aspects of related capabilities (to learn more click here)}

^{• Population segmentation specialists in organizations engaged in population-segment targeting for marketing, service delivery or educational purposes (to learn more click here)}

^{• Retirement and financial planners who advise clients about strategies to meet later-life challenges (to learn more click here)}

^{• Specialists in gender issues related to retirement and who are studying or teaching about the particular challenges facing older women (to learn more click here)}

"Key Demographics in Retirement Risk Management" does the following that will interest many researchers and graduate students:

• presents in chart form estimates of the time pattern of major waves of retirement within specific cohorts, comparing the wave patterns of a Canadian cohort to those of its USA counterparts

• portrays aspects of the pattern of socio-economic differences in the recent substantial fall in pre-retirees’ confidence about achieving a satisfactory standard of living during their retirement

• examines the relative statistical importance of key factors in the recent fall of confidence concerning future life in retirement, and the persistence of some of these factors through 2011, using data from surveys sponsored by Desjardins Securité Financière (Canada), AARP and Employee Benefit Research Institute (USA)

• compares Canada to the USA regarding the extent of the fall in retirement confidence among older workers

• breaks down changes in the unemployment rate for the older-population into their component gross flows; from Unemployed or “Not in the Labour Force and Discouraged” to Employed (the proxy job offer rate), from Employed to Unemployed, from Unemployed to “Not in the Labour Force”, etc., so as to analyze intensification of pressure from unfavorable labour market conditions among older workers in the USA, drawing upon Bureau of Labour Statistics’ Current Population Survey microdata files

• evaluates the relative statistical importance of key factors that help to explain the reported decisions to delay retirement, with special attention to psychological forces linked to risk-anxiety, setting the analysis within the context of a theoretical framework that serves to guide model design and data interpretation

• analyses pre-retired persons’ usage of professional financial advisors by means of modeling three linked outcome variables: (1) needing help with financial management, (2) trusting financial advisors, and (3) using financial advisors’ services; all based on data from surveys in Canada and the USA

• analyses pre-retired persons’ usage of professional financial advisors by means of modeling three linked outcome variables: (1) needing help with financial management, (2) trusting financial advisors, and (3) using financial advisors’ services; all based on data from surveys in Canada and the USA

• extends existing theory about the key factors and the stages in processes that lead to use of the services of professional financial advisors, highlighting the influences of persons’ social networks and of personality traits that help to determine the resolution of competing priorities

• includes four key classes of explanatory variables in most of the models cited above: (1) demographic and socio-economic attributes, (2) aspects of persons’ financial positions and financial literacy, (3) proximity to the expected retirement date, and (4) psychological factors such as retirement confidence and financial self-assurance, and doing so using procedures that take their theoretical interdependencies into account while drawing upon data from both Canada and the USA

• includes four key classes of explanatory variables in most of the models cited above: (1) demographic and socio-economic attributes, (2) aspects of persons’ financial positions and financial literacy, (3) proximity to the expected retirement date, and (4) psychological factors such as retirement confidence and financial self-assurance, and doing so using procedures that take their theoretical interdependencies into account while drawing upon data from both Canada and the USA

• identifies large population segments (key demographics) with very high or very low probabilities of using professional financial advisors by taking into account dense combinations of several population attributes covering a wide range of explanatory variables

• identifies large multidimensional population segments with unusually high (or low) probabilities of doing multiple risk management activities (these segments are also called “key demographics”), based partly on a composite indicator, where the population dimensions represent important causal factors in the outcome

• demonstrates how to identify key demographics when the number of attributes needed to define these distinctive population segments is so large that routine statistical cross tabulation is unusable

• develops a strategy for estimating the sizes of the multidimensional population segments that have very high or low probabilities of doing multiple risk management activities, a problem that arises partly because routine statistical cross tabulation is unusable

• constructs a composite indicator to measure persons’ conduct of multiple retirement related risk management activities

• devises elements of a theory concerning the processes that help to determine the extent to which persons undertake retirement related risk management activities

• assesses the relative statistical importance of predictor variables in modeling survey respondents’ levels on the composite indicator, part of the basis for selecting the population dimensions to be used to identify key demographics

• examines the degree of heterogeneity among key demographics that have very high (or very low) probabilities of conducting multiple retirement related risk management activities

• designs a survey-based composite indicator of preparedness for retirement by focusing on subjective and behavioural aspects

• examines the extent to which compositional differences between men and women explain the gender difference in population distribution over levels of the composite indicator of preparedness for retirement

> back to the main page>

"Key Demographics in Retirement Risk Management" does the following that will interest many educators:

• develops the concept of comprehensive retirement related risk management and expositing its dimensions and steps, an area where theory and empirical research are scarce and service delivery is becoming increasingly important

• extends the list of retirement related risks beyond that usually presented in the literature

• expands the scope of the concept of “longevity risk” to incorporate relevant and important non-financial dimensions

• presents in chart form estimates of the time pattern of major waves of retirement within specific cohorts, comparing the wave patterns of a Canadian cohort to those of its USA counterparts

• portrays aspects of the pattern of socio-economic differences in the recent substantial fall in pre-retirees’ confidence about achieving a satisfactory standard of living during their retirement

• highlights aspects of the risk management challenges faced by those who have little time left in their lives to recover from their losses in either earning power or financial markets

• links the fall of confidence concerning future life in retirement to rising risk-anxiety (the latter due to a convergence of psychological processes identified in the book), which is predicted to produce enhancement of the profile of risk management issues in the lives of older persons

• compares Canada to the USA regarding the extent of the fall in retirement confidence among older workers

• breaks down changes in the unemployment rate for the older-population into their component gross flows; from Unemployed or “Not in the Labour Force and Discouraged” to Employed (the proxy job offer rate), from Employed to Unemployed, from Unemployed to “Not in the Labour Force”, etc., so as to analyze intensification of pressure from unfavorable labour market conditions among older workers in the USA, drawing upon Bureau of Labour Statistics’ Current Population Survey microdata files

• evaluates the relative statistical importance of key factors that help to explain the reported decisions to delay retirement, with special attention to psychological forces linked to risk-anxiety, setting the analysis within the context of a theoretical framework that serves to guide model design and data interpretation

• analyses pre-retired persons’ usage of professional financial advisors by means of modeling three linked outcome variables: (1) needing help with financial management, (2) trusting financial advisors, and (3) using financial advisors’ services; all based on data from surveys in Canada and the USA

• analyses pre-retired persons’ usage of professional financial advisors by means of modeling three linked outcome variables: (1) needing help with financial management, (2) trusting financial advisors, and (3) using financial advisors’ services; all based on data from surveys in Canada and the USA

• extends existing theory about the key factors and the stages in processes that lead to use of the services of professional financial advisors, highlighting the influences of persons’ social networks and of personality traits that help to determine the resolution of competing priorities

• assesses the relative importance of the key predictors in modeling pre-retired persons’ expressed sense of need for professional help with financial management

• estimates the relative importance of the key predictors in modeling pre-retired persons’ expressed level of trust in professional financial advisors

• evaluates the relative importance of the key predictors in modeling in the extent of usage of professional help with financial management among pre-retired persons’ who received any sort of help (including that from sources in the social network) with financial management

• assesses the relative importance of the key predictors in modeling pre-retired persons’ expressed sense of need for professional help with financial management

• estimates the relative importance of the key predictors in modeling pre-retired persons’ expressed level of trust in professional financial advisors

• evaluates the relative importance of the key predictors in modeling in the extent of usage of professional help with financial management among pre-retired persons’ who received any sort of help (including that from sources in the social network) with financial management

• includes four key classes of explanatory variables in most of the models cited above: (1) demographic and socio-economic attributes, (2) aspects of persons’ financial positions and financial literacy, (3) proximity to the expected retirement date, and (4) psychological factors such as retirement confidence and financial self-assurance, and doing so using procedures that take their theoretical interdependencies into account while drawing upon data from both Canada and the USA

• includes four key classes of explanatory variables in most of the models cited above: (1) demographic and socio-economic attributes, (2) aspects of persons’ financial positions and financial literacy, (3) proximity to the expected retirement date, and (4) psychological factors such as retirement confidence and financial self-assurance, and doing so using procedures that take their theoretical interdependencies into account while drawing upon data from both Canada and the USA

• identifies large population segments (key demographics) with very high or very low probabilities of using professional financial advisors by taking into account dense combinations of several population attributes covering a wide range of explanatory variables

• constructs a composite indicator to measure persons’ conduct of multiple retirement related risk management activities

• devises elements of a theory concerning the processes that help to determine the extent to which persons undertake retirement related risk management activities

• assesses the relative statistical importance of predictor variables in modeling survey respondents’ levels on the composite indicator, part of the basis for selecting the population dimensions to be used to identify key demographics

• examines the degree of heterogeneity among key demographics that have very high (or very low) probabilities of conducting multiple retirement related risk management activities

• highlights the relative weights of selected target groups, such as women and immigrants, among the low-performing key demographics

• identifies population segments within which the gender difference in preparedness to address later-life challenges widens markedly, highlighting implications of the special situations of immigrant women and widows

• designs a survey-based composite indicator of preparedness for retirement by focusing on subjective and behavioural aspects

• examines the extent to which compositional differences between men and women explain the gender difference in population distribution over levels of the composite indicator of preparedness for retirement

> back to the main page>

"Key Demographics in Retirement Risk Management" does the following that will interest many specialists in population/market segmentation:

• presents in chart form estimates of the time pattern of major waves of retirement within specific cohorts, comparing the wave patterns of a Canadian cohort to those of its USA counterparts

• portrays aspects of the pattern of socio-economic differences in the recent substantial fall in pre-retirees’ confidence about achieving a satisfactory standard of living during their retirement

• highlights aspects of the risk management challenges faced by those who have little time left in their lives to recover from their losses in either earning power or financial markets

• examines the relative statistical importance of key factors in the recent fall of confidence concerning future life in retirement, and the persistence of some of these factors through 2011, using data from surveys sponsored by Desjardins Securité Financière (Canada), AARP and Employee Benefit Research Institute (USA)

• links the fall of confidence concerning future life in retirement to rising risk-anxiety (the latter due to a convergence of psychological processes identified in the book), which is predicted to produce enhancement of the profile of risk management issues in the lives of older persons

• evaluates the relative statistical importance of key factors that help to explain the reported decisions to delay retirement, with special attention to psychological forces linked to risk-anxiety, setting the analysis within the context of a theoretical framework that serves to guide model design and data interpretation

• analyses pre-retired persons’ usage of professional financial advisors by means of modeling three linked outcome variables: (1) needing help with financial management, (2) trusting financial advisors, and (3) using financial advisors’ services; all based on data from surveys in Canada and the USA

• assesses the relative importance of the key predictors in modeling pre-retired persons’ expressed sense of need for professional help with financial management

• estimates the relative importance of the key predictors in modeling pre-retired persons’ expressed level of trust in professional financial advisors

• evaluates the relative importance of the key predictors in modeling in the extent of usage of professional help with financial management among pre-retired persons’ who received any sort of help (including that from sources in the social network) with financial management

• includes four key classes of explanatory variables in most of the models cited above: (1) demographic and socio-economic attributes, (2) aspects of persons’ financial positions and financial literacy, (3) proximity to the expected retirement date, and (4) psychological factors such as retirement confidence and financial self-assurance, and doing so using procedures that take their theoretical interdependencies into account while drawing upon data from both Canada and the USA

• identifies large population segments (key demographics) with very high or very low probabilities of using professional financial advisors by taking into account dense combinations of several population attributes covering a wide range of explanatory variables

• raises key questions that emerge concerning preparedness to meet unusual financial challenges that may be encountered among low net worth persons whose income replacement rates surpass policy targets — levels of knowledge and skill needed to navigate treacherous “financial rapids” associated with catastrophic illness or family breakdown may be in short supply among such persons

• identifies large multidimensional population segments with unusually high (or low) probabilities of doing multiple risk management activities (these segments are also called “key demographics”), based partly on a composite indicator, where the population dimensions represent important causal factors in the outcome

• demonstrates how to identify key demographics when the number of attributes needed to define these distinctive population segments is so large that routine statistical cross tabulation is unusable

• develops a strategy for estimating the sizes of the multidimensional population segments that have very high or low probabilities of doing multiple risk management activities, a problem that arises partly because routine statistical cross tabulation is unusable

• constructs a composite indicator to measure persons’ conduct of multiple retirement related risk management activities

• assesses the relative statistical importance of predictor variables in modeling survey respondents’ levels on the composite indicator, part of the basis for selecting the population dimensions to be used to identify key demographics.

> back to the main page>

Demographics in Retirement Risk Management" does the following that will interest many retirement and financial planners:

• develops the concept of comprehensive retirement related risk management and expositing its dimensions and steps, an area where theory and empirical research are scarce and service delivery is becoming increasingly important

• extends the list of retirement related risks beyond that usually presented in the literature

• expands the scope of the concept of “longevity risk” to incorporate relevant and important non-financial dimensions

• highlights aspects of the risk management challenges faced by those who have little time left in their lives to recover from their losses in either earning power or financial markets

• examines the relative statistical importance of key factors in the recent fall of confidence concerning future life in retirement, and the persistence of some of these factors through 2011, using data from surveys sponsored by Desjardins Securité Financière (Canada), AARP and Employee Benefit Research Institute (USA)

• links the fall of confidence concerning future life in retirement to rising risk-anxiety (the latter due to a convergence of psychological processes identified in the book), which is predicted to produce enhancement of the profile of risk management issues in the lives of older persons

• analyses pre-retired persons’ usage of professional financial advisors by means of modeling three linked outcome variables: (1) needing help with financial management, (2) trusting financial advisors, and (3) using financial advisors’ services; all based on data from surveys in Canada and the USA

• assesses the relative importance of the key predictors in modeling pre-retired persons’ expressed sense of need for professional help with financial management

• estimates the relative importance of the key predictors in modeling pre-retired persons’ expressed level of trust in professional financial advisors

• evaluates the relative importance of the key predictors in modeling in the extent of usage of professional help with financial management among pre-retired persons’ who received any sort of help (including that from sources in the social network) with financial management

• includes four key classes of explanatory variables in most of the models cited above: (1) demographic and socio-economic attributes, (2) aspects of persons’ financial positions and financial literacy, (3) proximity to the expected retirement date, and (4) psychological factors such as retirement confidence and financial self-assurance, and doing so using procedures that take their theoretical interdependencies into account while drawing upon data from both Canada and the USA

• identifies large population segments (key demographics) with very high or very low probabilities of using professional financial advisors by taking into account dense combinations of several population attributes covering a wide range of explanatory variables

• highlights the pattern of the gender difference in usage of professional financial advisors in view of older women’s greater exposure to economic aspects of longevity risks (these have non-economic as well as economic dimensions, as explained in the book)

• discusses implications of the findings for strategy in marketing to high net worth persons

• raises key questions that emerge concerning preparedness to meet unusual financial challenges that may be encountered among low net worth persons whose income replacement rates surpass policy targets — levels of knowledge and skill needed to navigate treacherous “financial rapids” associated with catastrophic illness or family breakdown may be in short supply among such persons

• highlights the relative weights of selected target groups, such as women and immigrants, among the low-performing key demographics

• identifies population segments within which the gender difference in preparedness to address later-life challenges widens markedly, highlighting implications of the special situations of immigrant women and

> back to the main page>

"Key Demographics in Retirement Risk Management" does the following that will interest many specialists in gender issues:

• develops the concept of comprehensive retirement related risk management and expositing its dimensions and steps, an area where theory and empirical research are scarce and service delivery is becoming increasingly important

• extends the list of retirement related risks beyond that usually presented in the literature

• expands the scope of the concept of “longevity risk” to incorporate relevant and important non-financial dimensions

• highlights aspects of the risk management challenges faced by those who have little time left in their lives to recover from their losses in either earning power or financial markets

• links the fall of confidence concerning future life in retirement to rising risk-anxiety (the latter due to a convergence of psychological processes identified in the book), which is predicted to produce enhancement of the profile of risk management issues in the lives of older persons

• highlights the pattern of the gender difference in usage of professional financial advisors in view of older women’s greater exposure to economic aspects of longevity risks (these have non-economic as well as economic dimensions, as explained in the book)

• highlights the relative weights of selected target groups, such as women and immigrants, among the low-performing key demographics

• identifies population segments within which the gender difference in preparedness to address later-life challenges widens markedly, highlighting implications of the special situations of immigrant women and widows

• designs a survey-based composite indicator of preparedness for retirement by focusing on subjective and behavioural aspects

• examines the extent to which compositional differences between men and women explain the gender difference in population distribution over levels of the composite indicator of preparedness for retirement

> back to the main page>

(c) 2012 Leroy O. Stone. All rights reserved.