We propose a parsimonious stochastic model of reported earnings that links misreporting to performance shocks. Our main analytical prediction is that misreporting leads to a negative second-order autocorrelation in the residuals from a regression of current earnings on lagged earnings. We also propose a stylized dynamic model of earnings manipulation and demonstrate that both earnings smoothing and target-beating considerations result in the same predictions of negative second-order autocorrelations. Empirically, we find that the distribution of this measure is asymmetric around zero with 27% of the firms having significantly negative estimates. Using this measure, we specify a methodology to estimate the intensity of misreporting and to create estimates of unmanipulated earnings. Our estimates of unmanipulated earnings are more correlated with contemporaneous returns and have higher volatility than reported earnings. With respect to economic magnitude, we find that, in absolute terms, median misreporting is 0.7% of total assets. Moreover, firms in our sample subject to SEC AAERs have significantly higher estimates of manipulation intensity.

We investigate the experience of companies listing and raising capital on the AIM, which is privately regulated and relies on Nominated Advisors who compete for listings and provide regulatory oversight. AIM firms underperform newly listed firms on traditionally regulated exchanges based on post-listing returns and failure rates, comparable to firms listing on the unregulated US Pink Sheets, and exhibit abnormally high pre-listing accruals and post-listing reversals. “High quality” auditors and Nomads partially mitigate underperformance, suggesting that AIM firms have limited ability to bond through more stringent oversight. Underperformance is particularly pronounced for firms with higher proportions of retail investors.