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Quantile regression is a statistical analysis that does not restrict attention to the conditional mean and therefore, permitting the approximation of the whole conditional distribution of a response variable. Quantile regression is a robust regression to outliers compared to mean regression models. In this paper, we demonstrate how quantile regression approach can be used to analyze the ratio of projected wealth to needs (wealth-needs ratio) during retirement. [ABSTRACT FROM AUTHOR]

Adequacy of retirement income is very important to maintain a comfortable living standard during retirement. Under a life cycle model, assets are mainly accumulated during an individual's work life to finance consumption after retirement. A generally accepted goal of retirement planning is to provide enough income during retirement to prevent the level of living from dropping much below the pre-retirement level. Retirement wealth can be defined as adequate if the total retirement income is equal or greater than the desired total retirement consumption (or needs). In this study, retirement adequacy is projected using the Malaysian Household Income Survey (HIS) 2009 data which is based on 5881 sample of households and contains information on income, demographic and socioeconomic status of each household. Besides the projection of retirement adequacy, a regression of the ratio of projected wealth to needs (or wealth-needs ratio) is performed to investigate the demographic and socioeconomic determinants of retirement adequacy in Malaysia. The results show that 69% of households in Malaysia are adequately prepared for retirement. [ABSTRACT FROM AUTHOR]