Dual incentives in earnings management: Threshold meeting and tax-motivated profit suppression

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Type of the article: Theoretical Article

Abstract
A common assumption in corporate finance is that firms maximize profits. However, in countries with weak tax administration and limited contract enforcement, firms may understate reported pre-tax earnings to reduce tax liabilities through evasion. This paper revisits the canonical threshold-based earnings management framework and extends it by incorporating an additional (often illegal) incentive to reduce corporate income payments. Simulation results indicate that manipulation does not significantly change when latent earnings are negative. In contrast, when latent earnings are moderately positive, firms combine legal earnings management with illegal underreporting to reduce reported earnings for two purposes: (i) to shift earnings forward to increase the likelihood of meeting next-period benchmark and (ii) to lower current tax payments. At higher earnings levels, both channels plateau as manipulation costs, marginal legal costs, and detection risk increase. Using distributional (histogram-based) diagnostics, discontinuity tests, and a Probit regression model, we find that Ukrainian companies in 2024 were more focused on reducing taxable income than on beating the zero-earnings benchmark. Excess mass is concentrated in the first positive bin, and it is associated with a higher effective tax rate and lower discretionary accruals. Overall, the results suggest that in weak-enforcement settings, tax-motivated earnings suppression can dominate classic threshold-beating incentives.

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    • Figure 1. Earnings manipulation
    • Figure 2. Simulated distribution of reported earnings: extended scenario
    • Figure 3. Histogram of reported earnings (deflated by total assets): empirical distribution
    • Figure A1. Probability of detection
    • Figure A2. Simulated distribution of reported earnings: baseline scenario
    • Table 1. Median financial indicators
    • Table 2. Regression results
    • Table B1. Modified Jones regression
    • Conceptualization
      Roman Semko
    • Data curation
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    • Formal Analysis
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    • Writing – original draft
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