The Effect of ECB Unconventional Monetary Policy on Firms’ Performance during the Global Financial Crisis
Bibliographic record
Abstract
This study aims to analyse and investigate the most important factors affecting the performance of listed firms in the Athens Stock Exchange, emphasising capital structure, size and sovereign debt rate as a proxy for firms’ borrowing rate. Yet, the most remarkable factor taken into consideration to affect firms’ profitability is the delta of ECB assets as a proxy of the ECB’s strategy during the financial crisis. Indeed, the examination of the ECB’s delta is innovative for such analysis and differentiates this study from previous ones. The survey was conducted for the period 2005–2019, and the sample consisted of 49 firms from all sectors of the economic activity, except for the financial sector, as its companies’ capital structure is subject to supervisory restrictions. Thus, the financial sector’s inclusion in the sample would affect its homogeneity. The sample is divided into two sub periods, based on the statement of ECB’s president Mario Draghi “Whatever it takes,” in 2012, expressing the ECB’s strategy for backing and boosting the Eurozone economy. The empirical approach of our analysis is based on a panel data analysis, which allows the combination of both cross-section and time series data. In addition, we develop, test and analyse four specifications of our main model, each one with a different dependent variable as a proxy for profitability. These variables are EPS (earnings per share), ROE (return on equity), ROA (return on assets) and TOBIN’s Q. Our findings lead to some very interesting conclusions, which in most cases are consistent for the specification of all the examined models. More specifically, the results show a negative influence of debt-to-equity ratio and 10-year Greek yield bond on firms’ profitability regardless of the proxy used (EPS, ROE or TOBIN’s Q), while there is a positive impact of firms’ size and the delta of ECB’s total assets on firms’ profitability. However, the soundest outcome of this study shows that the expansion of the ECB’s balance sheet and the unconventional policy does contribute to the improvement of firms’ performance and economic stability. The findings become even more impressive, considering the turning of ECB’s strategy after the implementation of the unconventional policy in 2012. Our findings are useful for policymakers of international institutions and government authorities as we propose strategies favouring economic stability and economic activity but also for managers and stakeholders who can identify the factors which determine firms’ performance in order to apply the best policies for financing, investments and growth.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".