Abstract

Nonparametric Kernel Estimation of the Impact of Tax Policy on the Demand for Private Health Insurance in Australia

Highlights

  • This paper is motivated by our attempt to answer an empirical question: how is private health insurance (PHI) take-up in Australia affected by the income threshold at which the Medicare Levy Surcharge (MLS) kicks in?

  • In Australia, individuals are liable for MLS, which is 1 per cent of their taxable income, if they do not take-up PHI and their taxable income is above certain threshold

  • 1) In 1997, the Private Health Insurance Incentives Scheme (PHIIS) was introduced, which imposes a the MLS on high-income taxpayers who do not have private insurance and provides a means-tested subsidy schedule for low-income earners who purchase; 2) In 1999, a 30% tax rebate on private insurance premium was introduced for all PHI policies and the means-tested component under PHIIS was replaced; and 3) in 2000, Life Time Health Cover (LHC), a system of entry-age ratings in which a premium surcharge of 2 percent is charged for every year that the initial purchase is delayed after age 30

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Summary

Introduction

This paper is motivated by our attempt to answer an empirical question: how is private health insurance (PHI) take-up in Australia affected by the income threshold at which the Medicare Levy Surcharge (MLS) kicks in?. We propose a new de-convolution based estimator when there are discontinuities in the regression function and the regressor is only observed with measurement errors. This is for the cases when we have information on the distribution of the measurement errors. Confidence bands are obtained from bootstrapped samples We use this estimator to estimate the take-up of PHI by single males as a function of taxable income.

A de-convolution Estimator for regression discontinuity
When the location of the discontinuity is known
When the location of the discontinuity is unknown
Choosing the bandwidths
Monte Carlo Simulations
Background
Perturbed data and the error distribution
Estimation and the results
Findings
Conclusions
Full Text
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