Family firm performance during a time of economic instability : Evidence from the Covid-19 pandemic in Sweden
Bibliographic record
Abstract
This paper investigates how family ownership affects firm performance among Swedish publicly listed firms during the Covid-19 pandemic. The period of interest is the second quarter of 2020 which is argued to be the period of the largest impact on the economy from the Covid-19 pandemic. During this period, we hypothesize that firm performance is influenced by family ownership due to agency conflicts. Our findings suggest that family firms with a present founding family member in the management outperform other firms in general. However, firm performance is not affected by family ownership during the Covid-19 period. We also consider different aspects of family ownership such as the level of stake controlled by the family, and whether the family firm uses a dual-class share system. Inconsistent with our hypotheses, our results show that a moderate stake controlled by the family is not associated with higher performance, and family firms that use the dual-class share system do not suffer in performance. Overall, our findings indicate that the Covid-19 pandemic did not impact firm performance contrary to our expectations. Lastly, this paper highlights an issue of sensitivity in the results depending on the family firm definition and the chosen measure for firm performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".