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Working Papers

climate change CEPAR

Roshen Fernando and Caterina Lepore

Abstract: This paper evaluates the global economic consequences of physical climate risks under two Shared Socioeconomic Pathways (SSP 1-2.6 and SSP 2-4.5) using firm-level evidence. Firstly, we estimate the historical sectoral productivity changes from chronic climate risks (gradual changes in temperature and precipitation) and extreme climate risks (representative of heatwaves, coldwaves, droughts, and floods). Secondly, we produce forward-looking sectoral productivity changes for a global multisectoral sample of firms. For floods, these estimates account for the productivity changes from the damage to firms’ physical capital. Thirdly, we assess the macroeconomic impact of these shocks within the global, multisectoral, intertemporal general equilibrium model: G-Cubed. The results indicate that, in the absence of additional adaptation relative to that already achieved by 2020, all the economies would experience substantial losses under the two climate scenarios, and the losses would increase with global warming. The results can be useful for policymakers and practitioners interested in conducting climate risk analysis.

Keywords: Climate change, Climate risks, Extreme events, Macroeconomic modelling



Roshen Fernando

Abstract: Medical advancements in the twenty-first century significantly contribute to increased longevity and the current global demographic trends, including population aging. While rising antimicrobial resistance (AMR) threatens the sustainability of longevity prospects, the current demographic trends also contribute to worsening AMR. We investigate the role of four demographic indicators (population growth, population aging, population density, and urbanization) in the resistance growth of seven pathogens against twelve antimicrobials in 30 countries from 2000 to 2020. We observe heterogeneous responses of different antimicrobial drug-pathogen combinations to demographic trends. We observe that the demographic trends could affect resistance growth more than antimicrobial consumption growth in some antimicrobial- drug pathogen combinations. We emphasize the importance of a broader exploration of factors affecting AMR evolution from a one-health approach and enhanced AMR surveillance, among others, to produce effective policy responses to tame AMR.

Keywords: Antimicrobial resistance, Infectious diseases, Demographic Trends, Population Growth, Population Aging, Urbanization, Econometrics, Machine Learning

cepar award

Roshen Fernando

Abstract: Antimicrobial resistance (AMR) and climate change are interrelated complex challenges to humanity. We investigate the role of physical climate risks in the resistance growth of seven pathogens against twelve antimicrobials in 30 countries from 2000 to 2020. Our empirical assessment considers both chronic (gradual changes in temperature, precipitation, and relative humidity) and extreme climate risks (representing extreme precipitation events, droughts, heatwaves, coldwaves, and storms). We observe heterogeneous responses of different antimicrobial drug-pathogen combinations to physical climate risks. We observe that the physical climate risks could affect resistance growth more than antimicrobial consumption growth in some antimicrobial-drug pathogen combinations. We also illustrate stronger effects of extreme climate risks on resistance growth compared to chronic risks in some antimicrobial-drug pathogen combinations. We emphasize the importance of a broader exploration of factors affecting AMR evolution from a one-health approach and enhanced AMR surveillance, among others, to produce effective policy responses to tame AMR.

Keywords: Antimicrobial resistance, Infectious diseases, Climate Change, Econometrics, Machine Learning


health model

Kyu Park and Michael Sherris

Abstract: With increasing numbers of Australians in or entering retirement, the modelling of functional disability and health status is critical to the insuring and financing of retirement risks for both governments and individuals. The multi-state modelling of these risks underlie projections of the population by functional disability status, the estimation of healthy life expectancy, the sustainable financing of public aged care and innovations in private long-term care insurance. Developing a model for the Australian population is challenging because of the lack of longitudinal health and mortality data for older Australians. We use the cross-sectional data in the Survey of Disability, Ageing and Carers for years 1998, 2003, 2009, 2012, 2015 and 2018, providing prevalence of functional disability and illness across 20 years, to estimate a multi-state transitions model that best explain the observed changes of prevalence in Australia. We develop and estimate for the first time an Australian model for transitions between five states (healthy, disabled but not ill, ill but not disabled, disabled and ill, and dead) using age, sex and trend factors for those aged 60 or greater. Functional disability is defined by autonomy of activities of daily living. Illness is defined by chronic illness conditions including heart problems, diabetes, lung disease, and stroke. Model estimation is done numerically. Using the fitted model, we estimate yearly transition probabilities, life expectancy of retirees and projected population distributions by functional disability and health states. We also provide a comparison of the results with previous studies.

Keywords: functional disability, activities of daily living, multiple state model, cross-sectional data, life expectancy, long-term care insurance


Financial growth

Lingfeng Lyu

Abstract: This research evaluates the Home Equity Access Scheme (HEAS) versus downsizing for older Australians, factoring in elements such as means tests, health expenditures, taxes, and home maintenance. It builds on a utility approach, considering region-specific house prices and longevity risks. Findings reveal that HEAS enhances healthy aging for healthy and mildly disabled retirees more than downsizing. This scheme benefits cash-poor but asset-rich retirees who have lower bequest motives, derive higher satisfaction from spacious homes, and prioritise long-term gratification. However, spatial disparities in housing prices and life expectancy decrease the uptake of HEAS, offering new perspectives on housing decisions among seniors in Australia.

Keywords: Home Equity Release, Reverse Mortgage, Downsizing, Healthy Ageing, Utility Approach.


Ageing data

Lingfeng Lyu

Abstract: This paper presents a tri-level hierarchical approach to house price modelling at the postcode level, which is considered the most granular geographical scale, incorporating macroeconomic influences from the national level and integrating data from the largest sub-state level (SA4). By employing a Risk Premium - Principal Component Analysis (RP-PCA) for SA4-level risk factors and combining these with national-level risk factors, a vector autoregressive (VAR) model is developed. This geographically conditional multi-factor model with a hierarchical structure offers enhanced short-term prediction accuracy while maintaining long-term forecasting capabilities. The model’s predictive accuracy is further enhanced by introducing an empirical copula to describe the dependence structure of one-step residuals across various suburbs. This methodology grants a dynamic and granular view of housing price trends in Australia. Key determinants like interest rate shifts, GDP growth, and exchange rate variances play a crucial role, particularly in urban areas in metropolitan cities. The analysis of economic and demographic factors on the SA4 level indicates that elements such as home debt increments, wage fluctuations, and population shifts are pivotal in shaping housing prices, underscoring the significance of a granular regional analysis.

Keywords: House price modelling, Hierarchical framework, Macroeconomic variables, Risk Premium - Principal Component Analysis (RP-PCA)



Tess Stafford, Xiaoyun Zhang and Katja Hanewald

Abstract: We study the effect of rural-urban migration on the well-being of older adults that re- main in rural communities in China, a country that is experiencing extensive rural-urban migration and rapid population aging. We exploit China’s historic “sent-down youth” program which temporarily relocated millions of urban youth to rural villages and created lasting social ties between sending cities and receiving villages. These ties, coupled with present-day variation in urban growth, create exogenous variation in present-day rural-urban migration rates, allowing us to uncover causal effects of migration. Results suggest that migration negatively affects the physical, cognitive, and emotional health of older adults that remain behind. (JEL I12, I15, J24, J61, O15, O18, R23)




Ricky Kanabar, Satu Nivalainen and Noora Järnefelt

Abstract: Using rich Finnish population level registers, we examine the impact of fusing a flexible early retirement pathway with a more stringent pathway, without changing eligibility conditions, so- called ‘relabelling’, on individual application behaviour. Our findings show that among affected cohorts the likelihood of applying for (successfully claiming) disability-related early retirement declined by 1.8 (1.5) percentage points equivalent to a relative drop of approximately 37% (39%) following the reform. Individuals with below tertiary level education and stronger lifetime labour market attachment exhibit a stronger behavioural response to the reform. We find tentative evidence of programme substitution to early retirement pathways designed to keep individuals in the labour market albeit on a part time basis. Our findings suggest that social norms and lack of awareness associated with early retirement pathways can strongly influence application behaviour even when eligibility conditions remain unchanged, offering policymakers novel ways to extend working lives.

Keywords: Retirement, disability, pensions, Finland, regression discontinuity.


Doreen Kabuche

Doreen Kabuche, Michael Sherris, Andrés M. Villegas and Jonathan Ziveyi


Abstract: Mortality risk sharing pools such as pooled annuity funds and tontines provide an attractive and effective solution for managing longevity risk. They have been widely studied in the literature. However, such arrangements are not optimal for individuals in need of long-term care (LTC) insurance. Enhancing the design of pooled annuities and tontines factoring in LTC can aid in reducing the cost of LTC insurance. This paper presents a matrix-based approach for pooling mortality risk across heterogeneous individuals classified by functional disability states and chronic illness statuses. Based on multi-state models of functional disability and health statuses, we demonstrate how individuals with different health risks can share mortality risk in a pooled annuity design. A multi-state pool is formed by pooling annuitants vulnerable to longevity and LTC risks, determining the associated actuarially fair benefits based on individuals’ health states. We provide a general structure for setting up a pooled annuity product that can be applied even for complex multi-state models. An extensive analysis is also carried out to illustrate our approach with numerical examples using US Health and Retirement Study (HRS) data. From the numerical illustrations, there is an increasing trend in the expected annuity benefits with higher upsides for individuals in poor health than those in good health, especially when systematic trends and uncertainty are considered in pricing. Smaller pool sizes and higher mortality credits among ill and disabled individuals due to higher death probabilities are the two main factors for the increased benefits in dependency.


Keywords: long-term care insurance, pooled annuity, multi-state models, functional disability, health status.