Is the improved financial performance after broader reforms and privatisation long-lasting and uniform across industries?
Bibliographic record
Abstract
The long-run financial performance of industries after broad reforms, including privatisation, has rarely been investigated. This study addresses this issue and examines the financial and operational performance within the Pakistani cement industry by utilising data covering two decades of the post-reform period. The study then compares the findings against four other industries from the manufacturing sector. Our empirical estimates reveal that, similar to the findings of many early studies, privatised firms improved their profitability, capacity utilisation, liquidity, solvency and leverage indicators in the short run, but recorded either a statistically significant decline or at best no change in profitability, financial prudence and capital investment over a longer post¨Creform and privatisation period. The long-run decline in profitability was also widespread across the other comparable industries. Interestingly, the improvement in liquidity and solvency indicators for privatised firms was better than for firms that had always been private in the immediate period but only lasted briefly. The one exception is labour use efficiency in terms of sales/income per employee and real sales, which indeed significantly improved over the longer post-reform/privatisation period. However, this improvement is mostly limited to the cement industry when compared against four other industries in the Pakistani manufacturing sector.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".