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Working Papers

Content pensioners enjoying a stroll

George Kudrna, Philip O'Keefe and John Piggott

Abstract: This paper reviews the current state of knowledge about pension policy and pension policy formulation in emerging economies undergoing demographic transition, and, with this background, indicated possible directions for future policy development. The countries we consider are primarily located in East and Southeast Asia, a region which is home to more than 30% of the world's population, and are characterised by increasing life expectancy, falling and /or low fertility ratios, immature social protection policy structures, high rates of informal employment, and in many cases, high rates of co-residency.

These features point to the relevance of strands of research which do not normally sit together in thinking about the evidence base for pension policy formulation and its impacts. They include fiscal implications; impacts on economic growth and intergenerational affordability; the relationship between alternative pension models and labour market (in)formality; the role of public benefits in the context of multi-generation households and intergenerational transfers; and the limitations of pension administration for older people who have worked in the informal sector for most or all of their lives.

The paper documents what we know about these various aspects of the issue and identifies knowledge gaps. On the basis of the evidence we do have, we indicate policy reform directions, in particular regarding development of social pensions directed to older people who have worked in the informal sector.


Roshen Fernando, Weifeng Liu and Warwick J McKibbin

Abstract: This study assesses the global economic consequences of climate-related risk in three broad areas: (1) the macroeconomic impacts of physical climate risk due to chronic climate change associated with global temperature increases and climate-related extreme shocks; (2) the macroeconomic effects of climate policies designed to transition to net zero emissions by 2050 (transition risk); and (3) the potential macroeconomic consequences of changes in risk premia in financial markets associated with increasing concern over climate events.

We consider four widely used climate scenarios (Representative Concentration Pathways, or RCP), and identify the physical damage functions due to chronic climate risks. The chronic climate risks include sea-level rise, crop yield changes, heat-induced impacts on labor, and increased incidence of diseases. We also estimate the future incidence of climate-related extreme events, including droughts, floods, heat waves, cold waves, storms and wildfires, based on climate variable projections under the climate scenarios.

After translating physical climate shocks into economic shocks to labor force and sectoral productivity, we investigate the macroeconomic consequences under the climate scenarios using the G-Cubed model. The results demonstrate that physical climate risk is likely to cause large economic losses in all RCP scenarios, both through chronic climate change and extreme climate shocks.

We then explore the impact of country-specific economy-wide carbon taxes as a representative policy action to drive the global economy to achieve net-zero emissions by mid-century. Transition risks vary according to the ambition and the design of policies to reduce emissions. The results demonstrate that there can be potentially significant costs associated with policies to reduce emissions, and the costs differ across sectors and across countries.

We also address whether changes in climate risk perceptions can significantly impact the real economy through changes in risk premia in financial markets. We calculate shocks to financial risk premia based on relationships between historical climate shocks and changes in financial market risk premia. We apply these shocks to risk premia under the RCP scenarios and find that the cost of rising risk premia can be of a magnitude consistent with historical experience. The cost appears to be smaller than the economic costs of changes in physical climate risk and transition risk.

Keywords: Climate change, Extreme events, Climate shocks, Climate risk, Macroeconomics, DSGE, CGE, G-Cubed

Aged care

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.



Population ageing data

Dajung Jun and Matt Sutton

Abstract: Good health is a fundamental aspect of quality of life. Although there are measures of poverty in several aspects of life, there is no established measure of health poverty. We use data on 30,005 adults from the Household, Income and Labor Dynamics in Australia (HILDA) to track trends in health poverty in Australia over 18 years from 2001 to 2018.

We define health poverty as dying within one year or reporting the lowest levels of health in any of the six health domains of the Short-Form Six Dimension (SF-6D). We show how rates of health poverty have changed over time for the population as a whole and for sub-groups of the population defined by gender, age, indigenous status, rurality and State of residence.

The proportion of the adult population experiencing health poverty in any one of the dimensions was 41% in 2001, falling to 36% in 2009 and then rising to 42% in 2018. The level of health poverty was higher for women than for men (42% vs. 36%), for older age groups (37% among 15 to 29-year-olds vs. 49% among those aged 60 years and over), for indigenous people (52% vs. 39%) and in South Australia (41% vs. 39%— the average rate of all the other states).

The six domains of health are: physical function, role function, social function, pain, mental health, and vitality. Most (51%) people experiencing health poverty reported poverty in more than one of the six dimensions. Poverty in role functioning was the most commonly reported domain. Lack of vitality and role functioning were the domains most commonly reported as the only deficit causing an individual to be in health poverty, by 24% and 39% respectively of individuals experiencing health poverty. These domains were also the main reasons for higher rates of poverty over time and between women and men. Poor mental health and role functioning were the main reasons for higher health poverty amongst Indigenous people.

The analysis shows which groups in Australia experience health poverty and in which aspects of their lives. We hope that this framework, together with regular monitoring and evaluation, could be used by Australian Governments to target and minimize health poverty.


health model

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.


Rob Bauer, Inka Eberhardt, and Paul Smeets

Abstract: To understand what motivates individuals to look at their pension situation and take adequate savings decisions, we conduct two field experiments with 226,946 and 257,433 pension fund participants. We find peer-information statements do not increase the rate at which individuals check their pension information, but lottery-type financial incentives do. Offering a few large prizes rather than many small prizes is most effective. However, the uptake of pension information does not lead to improved pension knowledge nor to increased self-reported savings three weeks after our intervention.

Mike Sherris CEPAR

Dilan SriDaran, Michael Sherris, Andrés M. Villegas and Jonathan Ziveyi

Abstract: Given the rapid reductions in human mortality observed over recent decades and the uncertainty associated with their future evolution, there have been a large number of mortality projection models proposed by actuaries and demographers in recent years. However, many of these suer from being overly complex, thereby producing spurious forecasts, particularly over long horizons and for small, noisy datasets. In this paper, we exploit statistical learning tools, namely group regularisation and cross validation, to provide a robust framework to construct such discrete- time mortality models by automatically selecting the most appropriate functions to best describe and forecast particular datasets. Most importantly, this approach produces bespoke models using a trade-o between complexity (to draw as much insight as possible from limited datasets) and parsimony (to prevent overfitting to noise), with this trade-o designed to have specific regard to the forecasting horizon of interest. This is illustrated using both empirical data from the Human Mortality Database and simulated data, using code that has been made available within a user-friendly open-source R package StMoMo.

Keywords: Mortality projection, regularisation, cross validation, Age-period-cohort model 




Seda Peksevim

Foreword: Today, people’s greatest financial concern is no longer paying their short-term bills or credit-card debt. According to the new study by Zurich Insurance Group and the University of Oxford (2019), ‘retirement security is the top financial worry’ for workers in 14 out of 16 countries. Likewise, recent surveys on old-age income suggest that nearly half of the respondents from different parts of the world do not feel secure about having a comfortable retirement (AARP Foundation, 2018; Credit Suisse, 2020).

While a lack of retirement savings has turned out to be a global phenomenon, most studies cover the design of pension systems in developed countries, which face relatively few challenges compared to developing ones. Moreover, from a handful of papers on developing regions, there is a tendency to discuss pension- related issues in the context of specific countries or topics. To this end, this study aims to provide an overall and detailed picture of the public and private pension systems in the developing world, including the present challenges and future directions.

The first part of the paper presents an overview of public pensions in developing countries. It illustrates the impact of ageing on sustainability and the adequacy of pay-as-you-go plans, along with some suggestions for the future of state pensions. In the second part, the paper focuses on private pension systems in the developing world and discusses the reasons for low pension savings with respect to the issues of coverage, contribution, and investment performance. This section also concludes by proposing certain recommendations for private pensions in the light of financial as well as behavioural and technological developments.

This work was made possible by the invaluable research support from the Pensions Scholarship Trust and IPE Magazine. Special thanks are due to Prof. Metin Ercan and Prof. Vedat Akgiray for their encouragement and guidance in my doctoral studies on pensions. I am also grateful to many researchers and colleagues from different parts of the world, notably Prof. Olivia Mitchell, Prof. Christopher Sier, Prof. Umut Çetin, Dr. Oğuz Karahan, Yaşar Kemal Peştreli, Joseph Mariathasan, Ziga Vizintin, Wojciech Sieczkowski, and Manfred Jormakka, for their fruitful discussion and valuable suggestions.




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.