David L. Eckles

The Patient Protection and Affordable Care Act (ACA) requires that insurers spend a minimum amount of their premium revenue on policyholder benefits. The Act specifies enforcement via a combination of insurer self-reporting, government examinations, and payment of policyholder rebates in cases where insurers fail to meet the required spending amount. We find that insurers' reported estimates are consistently overstated in situations in which more accurate estimates would have triggered rebate payments; publicly traded insurers (particularly those exhibiting poor financial reporting quality) exhibit the strongest evidence of strategic over-estimating. In aggregate, we estimate that approximately 14 percent of insurers engage in strategic over-estimates, and that insurer over-estimates resulted in hundreds of millions of dollars in underpaid policyholder rebates. Our study illustrates how a combination of regulatory design choices and lax oversight can weaken the effectiveness of accounting-based regulation and have substantial economic consequences.

A rich body of academic research has addressed the question of earnings management in the property-casualty insurance industry via manipulation of loss reserve estimates. This study analyzes the variability of reserve estimates at different development horizons to determine whether the predominant practice of relying on five years of development is appropriate. We examine two common measures of reserve estimation error, calendar year development and accident year development, and compare and contrast the two approaches. We also consider the appropriateness of the common practice of aggregating lines of business. After examining reserve development patterns for each of the major lines of business, we conclude that the appropriate development horizon to adequately establish ultimate liability may be longer than the current maximum reported horizon of 10 years found in Schedule P for most lines of business, including the aggregate reserves. Although longer-term development horizons are necessary to establish insurers’ ultimate liability, relatively short-term development horizons may be more appropriate when attempting to identify deliberate manipulations or to assess solvency risk, where the short-term variations are the primary object of interest. Ultimately, this article investigates the degree to which methodology originally developed for estimating loss reserve errors is appropriate today, in particular, relative to current data availability.

We estimate the effects on county‐wide housing development in Florida of community‐level participation in the National Flood Insurance Program using panel data methods and observed variation in the timing of the decision to join the program. We find that program participation “increased” housing starts and permits in noncoastal counties, while coastal counties with average flood zone acreage saw significant “declines” in housing activity. We conjecture that loss‐mitigating regulatory costs, an obligation of obtaining insurance, might explain these findings.

Loss reserves are a discretionary tool for managing insurer earnings, with more accurate and/or less volatile reserve errors resulting in higher accruals quality. We investigate whether accruals quality is related to insurer financial strength ratings. Specifically, we use insurer loss reserve errors as a measure of the quality of accruals and examine whether overall accruals quality, as well as a decomposition into innate and discretionary accruals quality, is related to insurer financial strength ratings. We find that firms with lower‐quality (noisier) accruals receive lower financial strength ratings from A.M. Best. This result holds for both innate and discretionary accruals. Overall, we provide the first evidence that the quality of accounting information is a significant factor in ratings of insurance firms.

We use the theories of optimal stochastic control and engineering process control to analyze the well-known phenomenon of insurance underwriting cycles in continuous time. We show in a continuous time framework that underwriting cycles can be explained with a model where premiums are set rationally, but where there are various reporting and regulatory lags. We find that the observed cycle length depends on the length of these underlying lags. Our result can be seen as consistent with previous empirical work showing underwriting cycles varying across countries and lines of insurance. In the event that no lags exist, our result is also consistent with more recent literature suggesting that insurance cycles may not exist.