We propose a general framework for determining the extent of measurement error bias in OLS and IV estimators of linear models, while allowing for measurement error in the validation source. We apply this method by validating Survey of Health, Ageing and Retirement in Europe (SHARE) data with Danish administrative registers. Contrary to most validation studies, we find measurement error in income is classical, once we account for imperfect validation data. We find non-classical measurement error in schooling, causing a 38 percent amplification bias in IV estimators of the returns, with important implications for the program evaluation literature.
We assess the validity of differences in eligibility ages for early and old age pension benefits as instruments for estimating the effect of retirement on cognitive functioning. Because differences in eligibility ages across country and gender are correlated with differences in years of schooling, which affect cognitive functioning at old ages, they are invalid as instruments without controlling for schooling. We show by means of simulation and a replication study that unless the model incorporates schooling, the estimated effect of retirement is negatively biased. This explains a large part of the “mental retirement” effects which have recently been found.
Education and wealth are positively correlated for individuals approaching retirement, but the direction of the causal relationship is ambiguous in theory and has not been identified in practice. We combine administrative data on individual total wealth with a reform expanding access to lower secondary school in Denmark in the 1950s, finding that schooling increases pension annuity claims but reduces the non-pension wealth of men in their 50’s. These effects grow stronger as normal retirement age approaches. Labour market mechanisms are key, with schooling increasing job mobility, reducing housing equity, increasing leverage, and improving occupational pension benefits.
We exploit inheritance episodes to provide novel causal evidence on long-run saving dynamics. For identification, we combine a panel of administrative wealth reports with the unexpected timing of sudden parental deaths. After inheritance, net worth converges towards the path established before parental death, and convergence is faster for liquid assets. Using a generalized structural framework, we show that buffer-stock and two-asset models can fit these dynamics, but only if agents are impatient enough and have both strong precautionary and post-retirement saving motives. Relative to standard calibrations, such agents have at least 50 percent higher precautionary savings for given total wealth.
Would the value of unemployment insurance fall if more people had a buffer stock of liquid savings? Using quasi-experimental evidence from the unexpected introduction of home equity loans in Denmark, where public unemployment insurance is voluntary, we find that liquidity and insurance are substitutes. A Danish reform provided less levered homeowners with more liquidity. Using a ten-year-long panel dataset drawn from administrative registries, we find that people who obtained access to extra liquidity were less likely to sign up for unemployment insurance. The effect is concentrated among those for whom insurance has negative expected value. In this group, extra liquidity from housing equity worth one year’s income decreases insurance up-take by as much as a 0.3 percentage point fall in the risk of unemployment. Placebo tests for earlier years show no differential trends by leverage before the natural experiment. This implies that the liquidity of financial assets influences unemployment insurance uptake in the absence of public provision of insurance.
We link the Survey of Health, Ageing and Retirement in Europe (SHARE) to Danish Administrative Registers, comparing schooling, retirement status and income. We are able to retrieve administrative records for 1670 out of the original 1707 respondents from the first survey wave in 2004. We compare individual linked records in an analysis of measurement error. Overall, we find only minor non-random misclassification of schooling, but otherwise SHARE provides reliable data for socio-economic analysis of schooling, income and retirement. SHARE Denmark overestimates the proportion of individuals with higher education: the probability of misclassification is higher for lower educated, richer individuals. Labour market status is precisely reported, and misclassification probability decreases with age. Average gross household income is not statistically different in SHARE and register data, and we show that measurement error is classical.
|SHARE working paper 16:2014|