Working Papers

Ou Yang, Jongsay Yong, Yuting Zhang and Anthony Scott

Abstract: We quantify competition in Australia’s residential aged care sector and study how competition is associated with the quality of care and prices in the sector. Competition is defined three ways: the number of competitors within 10 km radius of the facility; the distance (in km) to the third closest competing facility; and Herfindahl-Hirschman index based on market share of facilities within 10 km. We further examine whether quality and price differ by ownership types (government owned, for profit and not for profit), after controlling for competition. We find that more competition is not associated with better quality or lower prices. Government-owned facilities, in comparison to for-profit and not-for-profit facilities, are found to provide higher quality in some domains but not in others yet tend to charge lower prices than other ownership types. The results indicate the possibility of market failures in aged care. Two key sources of market failures, the lack of public reporting of quality of care and price transparency, should be addressed as policy priorities before competition can work in residential aged care markets.

Keywords: Nursing home completion; Aged care quality; Aged care prices; Australia.

Salvatory R. Kessy, Michael Sherris, Andrés M. Villegas and Jonathan Ziveyi

Abstract: We present a stacked regression ensemble method that optimally combines dierent mortality models to reduce the mean squared errors of mortality rate forecasts and mitigate model selection risk. Stacked regression uses a supervised machine learning algorithm to approximate the horizon-specific weights by minimizing the cross-validation criterion for each forecasting horizon. The horizon-specific weights facilitate the development of a mortality model combination customized to each horizon. Unlike other model combination methods, stacked regression simultaneously solves model selection and estimates model combinations to improve model forecasts. Our numerical illustrations based on 44 populations from the Human Mortality Database demonstrate that stacking mortality models increases predictive accuracy. Using one-year-ahead to 15-year-ahead out-of-sample mean squared errors, we find that stacked regression improves mortality forecast accuracy by 13% - 49% and 19% - 90% over the individual mortality models for males and females, respectively. Therefore, combining the mortality rate forecasts provides lower out-of-sample point forecast errors than selecting the single best individual mortality method. Stacked regression ensemble also achieves better predictive accuracy than other model combination methods, namely Simple Model Averaging, Bayesian Model Averaging, and Model Confidence Set. Our results support the stacked regression ensemble approach over individual mortality models and other model combination methods in forecasting mortality rates. We also provide a user-friendly open-source R package, CoMoMo, that combines multiple mortality rate forecasts using dierent model combination techniques.

Keywords: Stacked regression, ensemble learning, cross-validation, model uncertainty, model combination, age-period-cohort model, mortality forecasting.

Michael Keane

Abstract: The Retirement income system in South Korea is a patchwork of different programs, none of which is particularly effective at reducing poverty among senior citizens. Program benefits are very poorly targeted, meaning a very large fraction of the elderly receive modest benefits that are generally inadequate to lift a houshold out of poverty. The consequence is that South Korea has the highest elderly poverty rate in the OECD. I will argue that a better targeted system - with more generous benefits aimed at the fewer recipients - is likely to be welfare enhancing.

However, it seems clear that elderly poverty in Korea cannot be addressed merely by reforming the retirement income system. To address the root causes of the problem, structural reforms are needed to break down Korea's dual labor market system. Under that system, a large share of workers are in informal jobs where they do not make or receive mandated retirement contributions.