Earnings management in response to political costs : an investigation of Australian gold mining firms
Bibliographic record
Abstract
Earnings from gold mining in Australia remained tax-exempt for almost seven decades until 1 January 1991. Devaluation of the Australian dollar against the U.S. currency toward the end of 1976 and significant increases of gold prices in the international market in 1979 and 1980 led to a boom in the Australian gold mining industry in 1980s. The rapid success and prosperity against the backdrop of its tax-exempt status brought the industry under intense political scrutiny in the mid- to late- 1980s. In June 1985, the federal government revealed its intention to impose income tax on gold mining. Eventually, the removal of the tax-exempt status of the industry and introduction of income tax on gold mining were announced in May 1988, and implemented from 1 January 1991. This thesis investigates whether the politicalisation of its tax-exempt status and the imposition of income tax induced the Australian gold mining industry to manage earnings. It is argued that the political scrutiny of the industry and the introduction of income tax caused significant increases in the political costs of the industry during the period from mid-1980s to early-1990s, and gold mining firms, in tum, engaged in earnings management to mitigate those political costs. In addition, it is argued that political costs in this industry vary systematically with industry-specific factors such as gold price and firm-specific factors such as gold reserves. Earnings management is tested by employing an accrual-based model that segregates non-discretionary accruals from total accruals on the basis of the firms' economic circumstances. The sample for this study comes from 45 Australian gold mining firms for the years 1976-1991. Empirical results provide evidence that is consistent with significant downward earnings management during the period from June 1986 to May 1988 to mitigate political costs associated with the introduction of income tax, and during the year 1991 to reduce the magnitude of wealth transfers via income tax. A control sample of Canadian gold mining firms does not exhibit similar evidence of earnings management during the same periods. The empirical results for the hypotheses are not sensitive to the scaling variable used or to the correlation of the partitioning variables with measures of earnings performance. In addition, significant results indicating earnings management could not be replicated during out-of-sample non-event years. No evidence of upward earnings management, however, was obtained during the period from June 1988 to December 1990, a period in which gold mining firms were expected to have incentives to manage earnings upward. This suggests that accounting incentives to manage earnings may appeal to firms only in the absence of opportunities to increase earnings via operating-investment decisions. Of the two factors identified, only gold reserves held by the sample firms appear to be a significant factor in explaining cross-sectional variation in the sample firms' political sensitivity. Gold reserves can also explain the firms' choice with respect to the submission to the federal tax inquiry during the period from December 1985 to August 1986. This thesis contributes to and extends the positive accounting theory literature on earnings management and political costs. Earnings management affects the reliability of financial statement information. Hence, studies on earnings management have implications for a number of stakeholders of the firm including holders of debt and equity capital, accounting standard setters, auditors, financial analysts, and capital market regulators. Moreover, this study has implications for tax policy-makers as earnings management associated with tax policy changes affects revenue estimates as well as estimates of effects of tax law changes. By documenting earnings management in the Australian gold mining industry, this study extends the knowledge on motives and extent of earnings management, and adds to the scanty evidence of earnings management in Australian and non-U.S. reporting environments. Further, unlike most of the prior studies on political costs, it investigates political costs in an industry other than the traditionally considered politically sensitive oil and chemical industries. Thus, it provides fresh evidence on accounting responses to political costs in a non-U.S. regulatory framework.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".