Financial flexibility and the impact of the global financial crisis
Bibliographic record
Abstract
Purpose The purpose of this study is to gain some insights into how managers perceive and achieve financial flexibility and its value in coping with the 2008 global financial crisis. The study focuses on the following questions: What are the sources and measures of financial flexibility? Do financially flexible firms suffer a lower impact from the crisis? Is financial flexibility related to business flexibility? and Is financial flexibility important for the firm's capital structure decision? Design/methodology/approach This paper employs two methods: a questionnaire survey and interviews with chief financial officers (CFOs). The results are used to examine the relation between the firm's financial flexibility level and the impact of the global financial crisis on its liquidity, investments, capital structure and business operations. The results are used to analyze the robustness of different financial flexibility measures constructed from the survey data to identify an appropriate financial flexibility measure. Findings The main finding is that firms with high financial flexibility suffer lower impact from the crisis. The results show that firms with greater internal financing are likely to have lower leverage, higher cash ratios, and suffer a lower impact from the crisis on their business operations. The analysis indicates that an index based on the firm's leverage, liquidity, and operating ratios, similar to the Altman Z‐score, might be a better financial flexibility measure than long‐term debt ratio. The evidence also suggests that financial flexibility is a part of the firm's business strategy and is important for its capital structure decisions. Originality/value A major challenge for researchers is how to measure the firm's financial flexibility level, as it is unobservable and difficult to quantify. The innovation of this paper is to directly ask managers about the firm's financial flexibility, from both internal and external financing, construct several financial flexibility variables based on the survey data, and examine their correlations with the global financial crisis impact, to identify a robust financial flexibility measure. The research also provides unique data to investigate the value of financial flexibility during a severe credit crisis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".