Economic links and the wealth effects of layoff announcements along the supply chain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This paper investigates the effects of layoff announcement by customers on the valuation and operating performance of their supply chain partners. Design/methodology/approach The authors collect corporate layoff announcements from 8-K filings submitted by US publicly-traded firms from 2004 to 2017. Using event study methodology, they examine the information externality of corporate layoffs on announcing firms' suppliers. Findings Results show that suppliers, on average, experience a negative stock price reaction around their major customers' layoff announcements. The negative price effect is exacerbated when industry rivals of layoff-announcing customers also suffer from negative intra-industry contagion effects. Additionally, supply chain spillover effects are asymmetric, with only “bad news” layoff announcements causing significant value implications for suppliers, but not “good news” announcements. Supplier firms also reduce their investments in and sales dependence on layoff-announcing customers in subsequent years. Practical implications This study shows that layoff decisions, often aimed at improving firms' efficiency and effectiveness, create uncertainty for the suppliers' operation and cause negative value implications on firms' upstream partners. Findings should be useful to corporate decision-makers in making layoff decisions. Originality/value This paper is one of the first to address the value implications of corporate layoffs on announcing firms' suppliers. It provides a more comprehensive picture of the economy-wide impact of achieving efficiency through employee layoffs.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 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 it