The Impact of State Taxes on Self-Insurance: Closing remarks

5. Closing remarks
In summary, this paper finds self-insurance of property-casualty risks increases in state taxes. Tests are conducted assessing the relation between a state’s property-casualty insured losses and its tax levy on the insurance industry. As expected, a negative relation holds for nonautomobile coverage and automobile physical damage coverage. Similar relations are detected for workers’ compensation benefit payments. These findings are consistent with consumers opting to self-insure rather than bear the incidence of higher insurer taxes. Continue reading

The Impact of State Taxes on Self-Insurance: NOPRIVATE

North Dakota and Wyoming are excluded from the analysis because they prohibit selfinsurance, and Texas is excluded because 1993 was the first year that it permitted self-insurance. For the 47 remaining states, the percentage of workers’ compensation not covered through selfinsurance ranges from 54 percent to 92 percent with a mean (median) of 77 (79) percent and a standard deviation of 9 percent. A categorical variable (NOPRIVATE) is added to the explanatory variables to identify the four states (Nevada, Ohio, Washington, and West Virginia) that restrict coverage to self-insurance or state funds. Continue reading

The Impact of State Taxes on Self-Insurance: Workers’ compensation

4.6 Workers’ compensation
The preceding section shows that the results hold when premiums are employed as the dependent variable capturing insurance coverage. This section extends the robustness checks by employing a different dependent variable to test the relation between taxes and self-insurance of a specific line of property-casualty insurance, workers’ compensation. Workers’ compensation is essentially mandatory for all employers. Most states permit businesses to cover workers’ compensation through private insurance, government funds, or self-insurance (assuming the business can show sufficient wherewithal). Continue reading

The Impact of State Taxes on Self-Insurance: Sensitivity tests

The Impact of State Taxes on Self-Insurance: Sensitivity tests4.5. Sensitivity tests
The automobile regression results were subjected to same sensitivity tests applied to the non-automobile lines. Again, findings are robust to alternative specifications and control variables. Results are insensitive to estimating the automobile regression equations in log-linear expression. Conclusions are qualitatively unaltered when the regression variables, other than TAX, WEALTH, and COMPULSORY, are scaled by population. The TAX coefficients remain negative and significantly less than zero in the automobile physical regression. They also are more negative than the TAX coefficients in the automobile liability regressions, which are never significantly different from zero. Also, results again hold when rank regressions are employed. Continue reading

The Impact of State Taxes on Self-Insurance: TAX coefficients

In addition, the TAX coefficients for the physical coverage regressions are significantly less than the TAX coefficients for the automobile liability coverage regressions. In fact, the liability TAX coefficients are always positive, though not significantly different from zero. These findings are consistent with consumers being insensitive to upward adjustments in the cost of liability insurance because, unlike physical insurance, liability coverage is a necessary condition to operate an automobile. Within the liability and physical groupings, the regression coefficient estimates on the control variables are stable across years. However, the coefficients are in the predicted direction and significant more often for the liability regressions. Population is always positive and highly significant for both liability and physical coverage. Wealth, population density, and thefts are always significantly positive in the liability regressions, but significantly different from zero in the physical regressions only once (density in 1993). Catastrophic damage never has explanatory power in either set of regressions, which is not surprising because catastrophes only account for a tiny fraction of all automobile claims. Continue reading

The Impact of State Taxes on Self-Insurance: AutomobUe msurance

The Impact of State Taxes on Self-Insurance: AutomobUe msuranceTo test both the alternative explanation and the hypothesis that the relation between selfinsurance and state insurer taxes varies with the elasticity of demand, equation (1) is reestimated twice, once with the natural logarithm of liability insured losses as the dependent variable and once with the natural logarithm of physical insured losses as the dependent variable. An inverse relation between physical losses and state taxes will be interpreted as contrary to the alternative explanation and support for the original inference that self-insurance is increasing in state taxes. A finding that the relation between liability losses and taxes is less negative than the relation between physical losses and taxes is consistent with the demand curve being more inelastic for liability insurance. Greater inelasticity for liability insurance is expected to impede a shift to self-insurance in response to higher state taxes. Continue reading

The Impact of State Taxes on Self-Insurance: Alternative explanation

4.3 Alternative explanation
The results in this section also are consistent with an alternative explanation. Recall that Petroni and Shackelford (1999) report a disproportionate amount of premiums from multistate policies is reported as earned in low premium tax states. Suppose insurers also shift the losses associated with those premiums. Shifting the losses would not affect the premium tax liability, but perhaps it could mask the manipulation of the premiums. If the losses are shifted, then more insured losses are reported (though not necessary incurred) in low-tax states. If so, the relation between losses and taxes reported above is not evidence of taxes increasing self-insurance, but simply another manifestation of the premium tax avoidance found in Petroni and Shackelford (1999).
To test this alternative explanation requires investigating a line where manipulation of premiums is not expected. The following section examines such a setting, automobile insurance coverage. Continue reading

The Impact of State Taxes on Self-Insurance: Sensitivity tests

The Impact of State Taxes on Self-Insurance: Sensitivity testsOne control variable whose coefficient is significantly different from zero is the maximum statutory state corporate income tax rate. An attraction of purchasing coverage for business risks is that the insured party can deduct premiums against its income taxes. Business losses arising under self-insurance also are deductible. Losses under self-insurance, however, are deducted when incurred while premiums are deducted when paid. Moreover, because selfinsurance excludes insurer profits, it provides a smaller tax deduction than purchased coverage. Continue reading

The Impact of State Taxes on Self-Insurance: Empirical Results

4.2. Sensitivity tests
The findings in this study are robust to alternative specifications and control variables. Specifically, results are insensitive to estimating equation (1) in log-linear expression. Conclusions are qualitatively unaltered when the regression variables expressed in levels are scaled by population. The TAX coefficients remain negative and significantly less than zero. As expected, the adjusted R2 in the scaled models are smaller, ranging from 18 percent to 42 percent. Results also hold when equation (1) is estimated using rank regressions. Continue reading

The Impact of State Taxes on Self-Insurance: Univariate Analysis

The Impact of State Taxes on Self-Insurance: Univariate Analysis3.7. Univariate Analysis
Table 2 presents Pearson correlation coefficient estimates for each of the regression variables using 1993 data expressed in natural logarithms. The correlation coefficient estimate between TAX and LOSS is negative and highly significant; however, so is the correlation between TAX and POP. Because LOSS and POP are highly positively correlated, inferences about the relation between taxes and coverage must be deferred until the multivariate analysis is completed. Correlations are qualitatively similar in 1994 and 1995. Continue reading