Measuring Subjective Survival Expectations: Do Response Scales Matter?

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Abstract

This paper analyzes the test-retest reliability of subjective survival expectations that are elicited on two widely used response scales: an 11-point scale from 0 to 10 and a full percentage scale from 0 to 100. We compare responses of the same individuals in two surveys fielded in the same month. Reliability is evaluated both at the level of reported probabilities and through a model that relates expectations to socio-demographic variables. Test-retest correlations of survival probabilities are between 0.5 and 0.7, similar to subjective well-being. Only 20% of probabilities are equal across surveys, but up to 61-77% are consistent once we account for rounding. Both scales perform similarly in terms on response rates, internal consistency and fifty-fifty answers. Models that analyze all probabilities jointly reveal similar associations between most covariates and the hazard of death in test and retest datasets. Moreover, expectations are persistent at the level of the individual and this unobserved heterogeneity is strongly correlated across surveys (r ≈ 0.8-0.9). Finally, we use a calibrated life cycle model to map survival expectations into wealth and labor supply. Though wealth accumulation is sensitive to expectations, correcting for rounding substantially improves reliability of simulated wealth profiles. Taken together this evidence suggests that the two elicitation scales yield reliable measures of expectations.
Original languageEnglish
Place of PublicationTilburg
Number of pages60
Publication statusSubmitted - 18 Mar 2019

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labor supply
life cycle
hazard
measuring
test
rate

Keywords

  • subjective expectations
  • test-retest reliability
  • life cycle model
  • rounding

Cite this

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title = "Measuring Subjective Survival Expectations: Do Response Scales Matter?",
abstract = "This paper analyzes the test-retest reliability of subjective survival expectations that are elicited on two widely used response scales: an 11-point scale from 0 to 10 and a full percentage scale from 0 to 100. We compare responses of the same individuals in two surveys fielded in the same month. Reliability is evaluated both at the level of reported probabilities and through a model that relates expectations to socio-demographic variables. Test-retest correlations of survival probabilities are between 0.5 and 0.7, similar to subjective well-being. Only 20{\%} of probabilities are equal across surveys, but up to 61-77{\%} are consistent once we account for rounding. Both scales perform similarly in terms on response rates, internal consistency and fifty-fifty answers. Models that analyze all probabilities jointly reveal similar associations between most covariates and the hazard of death in test and retest datasets. Moreover, expectations are persistent at the level of the individual and this unobserved heterogeneity is strongly correlated across surveys (r ≈ 0.8-0.9). Finally, we use a calibrated life cycle model to map survival expectations into wealth and labor supply. Though wealth accumulation is sensitive to expectations, correcting for rounding substantially improves reliability of simulated wealth profiles. Taken together this evidence suggests that the two elicitation scales yield reliable measures of expectations.",
keywords = "subjective expectations, test-retest reliability, life cycle model, rounding",
author = "{de Bresser}, Jochem",
year = "2019",
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day = "18",
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Measuring Subjective Survival Expectations : Do Response Scales Matter? / de Bresser, Jochem.

Tilburg, 2019.

Research output: Working paperOther research output

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N2 - This paper analyzes the test-retest reliability of subjective survival expectations that are elicited on two widely used response scales: an 11-point scale from 0 to 10 and a full percentage scale from 0 to 100. We compare responses of the same individuals in two surveys fielded in the same month. Reliability is evaluated both at the level of reported probabilities and through a model that relates expectations to socio-demographic variables. Test-retest correlations of survival probabilities are between 0.5 and 0.7, similar to subjective well-being. Only 20% of probabilities are equal across surveys, but up to 61-77% are consistent once we account for rounding. Both scales perform similarly in terms on response rates, internal consistency and fifty-fifty answers. Models that analyze all probabilities jointly reveal similar associations between most covariates and the hazard of death in test and retest datasets. Moreover, expectations are persistent at the level of the individual and this unobserved heterogeneity is strongly correlated across surveys (r ≈ 0.8-0.9). Finally, we use a calibrated life cycle model to map survival expectations into wealth and labor supply. Though wealth accumulation is sensitive to expectations, correcting for rounding substantially improves reliability of simulated wealth profiles. Taken together this evidence suggests that the two elicitation scales yield reliable measures of expectations.

AB - This paper analyzes the test-retest reliability of subjective survival expectations that are elicited on two widely used response scales: an 11-point scale from 0 to 10 and a full percentage scale from 0 to 100. We compare responses of the same individuals in two surveys fielded in the same month. Reliability is evaluated both at the level of reported probabilities and through a model that relates expectations to socio-demographic variables. Test-retest correlations of survival probabilities are between 0.5 and 0.7, similar to subjective well-being. Only 20% of probabilities are equal across surveys, but up to 61-77% are consistent once we account for rounding. Both scales perform similarly in terms on response rates, internal consistency and fifty-fifty answers. Models that analyze all probabilities jointly reveal similar associations between most covariates and the hazard of death in test and retest datasets. Moreover, expectations are persistent at the level of the individual and this unobserved heterogeneity is strongly correlated across surveys (r ≈ 0.8-0.9). Finally, we use a calibrated life cycle model to map survival expectations into wealth and labor supply. Though wealth accumulation is sensitive to expectations, correcting for rounding substantially improves reliability of simulated wealth profiles. Taken together this evidence suggests that the two elicitation scales yield reliable measures of expectations.

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