Four levels of intergenerational indicators (Lili Vargha and Robert I. Gal)

Indicators of intergenerational reallocation can be calculated at the level of public programs (such as pensions or health care), more generally at the level of the general government, and in an even further generalized way at the level of the national economy. For example, the Economic Support Ratio, which captures both the effect of the age composition of the population and the age patterns of producing and consuming income by comparing the effective numbers of producers and consumers, can be defined at other levels of the reallocation system. The Fiscal Support Ratio compares the numbers of effective taxpayers and effective beneficiaries. The Pension Support Ratio repeats the same exercise with the effective numbers of contributors and pensioners.

We extend these measures by incorporating time transfers into the reallocation system. We introduce a generalized version of the support ratio, the Total Support Ratio (TSR). The TSR extends the age profile of labor income with the age profile of the value of unpaid household labor and the age profile of consumption with the age profile of the consumption of unpaid household labor. In this way, reallocation patterns in the total economy are taken into consideration. Estimates of the age profiles of produced and consumed household labor are based on the Time Use Survey. We demonstrate that the conclusions drawn from the support ratios defined at these four different levels are varying, and the projection of TSR predicts a significantly less dramatic effect of aging on society than other predictions.

We extend this generalization to other intergenerational measures, the Benefit Generosity Ratio (BGR) and the Elderly Bias of Social Spending (EBiSS), two similar indicators measuring the generational asymmetry of public expenditures along with the Lee arrow, which indicates how "old" a reallocation pattern is. We demonstrate that incorporating production and consumption of unpaid household labor largely rewrites the conclusions drawn by these indicators.

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