It has long been recognized that taxing a commodity that generates negative externalities can be used to reduce the consumption of that commodity. A variant involves the imposition of revenue neutrality but that may alter the tax rate required to meet a consumption reduction target. We explore the relationships among the commodity tax rate, the demand and supply elasticities, and the revenue offsets by calibrating a theoretical consumer equilibrium model and then recalibrating it with alternative parameter configurations. For each configuration we simulate equilibrium for three policy scenarios: no neutrality, neutrality achieved by subsidizing other commodities, and neutrality achieved by income transfer.
Measures of retirement that take a cohort perspective are appealing since retirement patterns may change, and it would be useful to have consistent measures that would make it possible to compare retirement patterns over time and between countries or regions. We propose and implement two measures. One is based on administrative income tax records and relates to actual cohorts; the other is based on a time-series of cross sectional labour force surveys and relates to pseudo-cohorts. We conclude that while the tax-based observations for actual cohorts provide a richer data set for analysis, the estimated measures of retirement and transition from work to retirement based on the two data sets are quite similar.
Consumer-related policy decisions often require analysis of aggregate responses or mean elasticities. However, in practice these mean elasticities are seldom used. Mean elasticities can be approximated using aggregate data, but that introduces aggregation bias for full and compensated price elasticities, though interestingly not for expenditure elasticities. The biases corresponding to incorrect approximations of mean elasticities depend on the type of data (micro or aggregate), the type and rank of the model, and generalized measures of income inequality. These biases are distinct from the biases (already noted in the literature) when using aggregate data to estimate micro elasticites at mean income.
We derive transition probability matrices for chronic health conditions using survey prevalence data. Matrices are constructed for successive age groups and the sequence represents the “age dynamics” of the health conditions for a stationary population – the probabilities of acquiring the conditions, of moving from one chronic conditions state to another, and of dying. One can simulate the life path of a cohort under the initial probabilities, and again under altered probabilities to explore the effects of eliminating a particular condition or reducing its mortality probabilities. We report the results of such simulations and note the general applicability of the methods.