Back to Appendix C: Social Security Dependence and Standards of LivingFrom Planning for the Future
p. 89-94, published 2002
The data shown on pages 52 and 53 were garnered from questions commissioned by the Kentucky Long-Term Policy Research Center and included in the Fall 2001 Kentucky Survey of the general adult population. The survey is conducted by the University of Kentucky Survey Research Center. Kentucky households were selected for this survey using random-digit dialing, a procedure giving every residential telephone line in Kentucky an equal probability of being called. Calls were made between February 21 and March 22, 2002. The sample includes noninstitutionalized Kentuckians aged 18 and older. Of the 2,589 calls made, 1,037 interviews were completed, yielding a response rate of 40.1 percent. The margin of error is approximately ±3 percentage points at the 95 percent confidence level. Table D.1 shows some sample characteristics.
Table D1: Sample Characteristics for the Fall 2001 Kentucky Survey
All respondents were asked about their satisfaction with the availability and affordability of high-quality elder-care services in their communities regardless of whether they had personally used or sought information about these services for themselves or someone else. Tables D.2 and D.3 show the crosstabulation between the satisfaction levels and personal use. These tables reveal that although the majority of the sample had no personal experience with elder-care services in their communities, many were still able to express satisfaction levels regarding their availability and affordability. Approximately two thirds of those with no personal experience expressed an opinion of satisfaction with both aspects of services. All sample respondents who chose “don’t know” or “refuse to answer” were excluded from the analytical results presented in this report, the majority of which were those with no personal experience with elder-care services. Approximately a quarter of the total sample chose these answers when asked about either aspect of elder-care services.
The estimated percentages presented here are based on the effect of each factor on the level of satisfaction with the availability and affordability of services while holding the other socioeconomic and demographic factors constant. We used a multivariate probit model to estimate the relationship between the dependent variables and several independent variables. The dependent variable in the first model is the respondent’s self-assessment of his or her satisfaction with the availability of elder-care services, while the second model focused on the affordability aspect. The actual questions are: Would you describe yourself as a) extremely satisfied, b) somewhat satisfied, c) somewhat dissatisfied, or d) extremely dissatisfied with the 1) AVAILABILITY and 2) AFFORDABILITY of high-quality elder-care services in your community? The question was asked twice, the first question asked about availability and the second question asked about affordability and choices “a” through “d” are the possible answers to each question. Those who answered “don’t know” or “refuse to answer” were excluded from the sample. We collapsed the dependent variables into two categories so that “extremely satisfied” or “somewhat satisfied” with the availability or affordability of elder-care services equals one and “somewhat dissatisfied” or “extremely dissatisfied” with the availability and affordability of elder-care services equals zero. The independent variables are listed below:
ELDSERVE — This dichotomous variable equals 1 if the respondent has used or inquired about elder-care services for himself or herself or someone else. Otherwise the variable equals 0.
HSGRAD — The survey respondents were asked to please circle the last grade in school you completed. HSGRAD equals 1 if they circled “graduated high school” or “GED.” Otherwise the variable equals zero.
SOMEPSE — The survey respondents were asked to please circle the last grade in school you completed. SOMEPSE equals 1 if they circled “1 or 2 years college, no degree,” “graduated junior or community college,” “vocational/technical degree,” or “3 or 4 years of college, no degree.” Otherwise the variable equals zero.
BAORMORE — The survey respondents were asked to please circle the last grade in school you completed. BAORMORE equals 1 if they circled “Bachelor’s degree,” “Some graduate school work,” or “Graduate degree (ex: MA, MS, Ph.D., JD).” Otherwise the variable equals zero. The comparison group includes all those individuals with educational attainment levels less than a high school diploma or equivalent.
URBAN — This dichotomous variable is equal to 1 if the individual lives in an urban county and 0 for a rural county.
OVER65 — This dichotomous variable is equal to 1 if the individual is 65 years old or older and 0 if the individual is 64 years old or younger.
BTWN2540, BTWN4070, GT70K, MISINC — These dichotomous variables reflect if the individual’s annual household income from all sources before taxes is in the second, third, or fourth quartile. The first quartile is left out of the model and is therefore the comparison group. It includes individuals with yearly household incomes less than $25,000. The variable equals 1 if the individual’s income falls in the quartile (or is missing in the case of MISINC) and 0 if it does not. The variable BTWN2540 is 1 if the individual’s income is between $25,000 and $40,000. The variable BTWN4070 is equal to 1 if the individual’s income is between $40,000 and $70,000. The variable GT70K is equal to 1 if the individual’s income is greater than $70,000. The variable MISINC is equal to 1 if the individual’s income is missing.
MALE — This dichotomous variable is equal to 1 for males and 0 for females.
WHITE — This dichotomous variable is equal to 1 if the individual is white, non-Hispanic and equal to 0 otherwise.
Two probit models were used to estimate the relationship between the independent variables and the likelihood that an individual would be “extremely satisfied” or “somewhat satisfied” with the availability and affordability of elder-care services in his or her community. Table D.4 presents the parameter estimates for each model.
The two models predicting satisfaction with availability and affordability of elder-care services were relatively equivalent in their explanatory power. The likelihood ratio (LR) statistics for the models were highly significant at the 0.01 level, thus rejecting the hypothesis that all the estimated coefficients of the independent variables in these models were equal to zero. Thus, the independent variables were jointly significant in explaining individual satisfaction levels with each aspect of high-quality elder-care services in his or her community. The goodness-of-fit measures were also equivalent at approximately 0.07 for each model. We found a slightly higher predictability level for the model explaining satisfaction with the availability of elder-care services, however. The first model predicted approximately 71 percent of the dependent variables correctly, while the model of affordability predicted approximately 58 percent correctly.
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Back to Appendix C: Social Security Dependence and Standards of Living
