Variables & measurement

A variable is defensible when another researcher can reproduce it.

Good operationalisation connects a construct to theory, a suitable proxy, consistent source data and an interpretation that respects the limits of the measure.

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Operationalisation advisory: A formula is not automatically a defensible operationalisation. The researcher must also justify why the measure fits the construct, study population, reporting environment, data availability and analytical model.

Measurement principles that apply to every ratio

  • Keep numerator and denominator definitions consistent across every firm and year.
  • Do not mix Group and Company financial-statement figures within a firm-year ratio.
  • Consider average balance-sheet values instead of closing balances where theory and data permit.
  • Investigate negative or near-zero denominators; they can make a ratio economically misleading.
  • Do not treat “total debt” and “total liabilities” as automatically interchangeable.
  • Document the statement, note, currency unit and transformation used for every extracted item.
  • Write definitions precisely enough for another researcher to reproduce the dataset from the methodology chapter.

Prof. Enyi P. Enyi's operational break-even and relative solvency models

Developed by Prof. Enyi Patrick Enyi of Babcock University, this family of models offers a firm-based alternative to Altman-type discriminant scores. The foundation is operational break-even theory (Enyi, 2005): a firm reaches its operational break-even point at the stage of activity where cumulative contribution margin on recovered outputs equals the total cumulative production, marketing and administrative costs and losses of the learning period. The measures below derive from a firm's own financial statements using turnover, profit before tax and working-capital items.

Attribution: These operationalisations are presented to recognise Prof. Enyi's scholarship and help researchers discover, apply and properly cite the original work. Researchers should consult and cite the relevant source rather than treating this page as a substitute for the published research.

Earning capacity: mark-up rate (m)

T is turnover or total operating income and P is profit before tax, so T − P is total operating cost inclusive of interest and depreciation. The mark-up rate measures the firm's ability to recover operating costs with a margin. A negative m indicates that the firm is eating into capital and may be prone to distress (Enyi, 2008).

Operational break-even point (OBEP)

OBEP expresses how many operating cycles the firm needs to recover its costs; a lower value indicates greater operational efficiency. Enyi, Nweze, Adebawojo and Olalere (2026) extend this into a break-even-based cash conversion cycle: CCC-B = OBEP × stock-up period, using an assumed 30-day stock-up period.

Working capital required at break-even (WCR)

WCR estimates the working capital a firm needs to sustain operations at its operational break-even point. The constant 104 embeds the model's cycle assumption of two times 52 weekly operating cycles.

Enyi's relative solvency ratio (RSR)

a is current assets and l is current liabilities, so a − l is available working capital. RSR measures working-capital availability relative to the firm's own operational needs and productive efficiency rather than an industry-average benchmark.

RSR valueInterpretation under the model
Above 1.0Available working capital exceeds the operational requirement.
Below 1.0Working capital is inadequate for the firm's operational scale.
Negative (a < l)The firm is technically insolvent by definition under the model.

Source trail: cite Enyi (2005) for operational break-even theory, Enyi (2008) for the RSR model, and Enyi (2018; 2021) for later validation and restatement.

Going concern ratio (GCR) and corporate financial stability (CFS)

A is total assets, L is total liabilities excluding shareholders' funds, B is the book value of ordinary shares and n is par value per share. GCR values the unencumbered worth of the firm due to equity holders, while CFS combines it geometrically with earning capacity. Enyi (2018) interprets CFS values of 1.0 and above as strong going concern, 0.5 to below 1.0 as minor problems, 0 to below 0.5 as major instability, and below 0 as absence of going concern.

The Altman Z-score family

Model-selection warning: There is no single Altman equation suitable for every firm. The correct version depends on whether the sample contains publicly listed manufacturers, private manufacturers, non-manufacturers or firms being assessed under the Emerging Market Score calibration.

A. Original Altman Z-score

Suitable context: publicly listed manufacturing firms.

WC
Working capital.
TA
Total assets.
RE
Retained earnings.
EBIT
Earnings before interest and taxes.
MVE
Market value of equity.
TL
Book value of total liabilities.
S
Sales or revenue.
  • Z > 2.99: Safe zone.
  • 1.81 ≤ Z ≤ 2.99: Grey zone.
  • Z < 1.81: Distress zone.

B. Revised Z′ score

Suitable context: primarily private manufacturing firms; book value of equity replaces market value.

BVE is the book value of equity. Other components retain the definitions above.

  • Z′ > 2.90: Safe or non-bankruptcy zone.
  • 1.23 ≤ Z′ ≤ 2.90: Grey zone.
  • Z′ < 1.23: Distress or bankruptcy-risk zone.

C. Z″ score

Suitable context: non-manufacturing firms and applications where the sales-to-assets component is intentionally removed.

  • Z″ > 2.60: Safe zone.
  • 1.10 ≤ Z″ ≤ 2.60: Grey zone.
  • Z″ < 1.10: Distress zone.

D. Emerging Market Score

Suitable context: credit-risk assessment using the Emerging Market Score calibration.

The constant 3.25 belongs to the Emerging Market Score calibration. It should not be added when a study intends to calculate the ordinary Z″ distress score.

Interpretation warning: The ordinary Z″ safe, grey and distress thresholds should not automatically be applied to the Emerging Market Score. The EMS was calibrated for credit-rating equivalence and should be interpreted according to the selected EMS framework.

Altman model comparison

ModelTarget population or useVariables retainedCut-offs
Original ZPublicly listed manufacturersWC/TA, RE/TA, EBIT/TA, MVE/TL, S/TASafe > 2.99; grey 1.81–2.99; distress < 1.81
Z′Private manufacturersWC/TA, RE/TA, EBIT/TA, BVE/TL, S/TASafe > 2.90; grey 1.23–2.90; distress < 1.23
Z″Non-manufacturers; sales term removedWC/TA, RE/TA, EBIT/TA, BVE/TLSafe > 2.60; grey 1.10–2.60; distress < 1.10
EMSEmerging-market credit-rating calibrationZ″ variables plus constant 3.25Use the selected EMS credit-rating framework; do not import ordinary Z″ zones automatically

Common financial variables

Return on assets

ROA =Profit measureTotal assets
Construct measuredProfitability relative to the asset base.
Suitable contextOperating or overall performance studies where the numerator is theoretically justified.
Risky useSwitching between profit after tax, profit before tax and EBIT across observations.
Data sourceStatement of profit or loss and statement of financial position.
InterpretationHigher values indicate more profit per unit of assets, subject to industry and accounting differences.
Extraction problemMixing Group profit with Company-only assets or using closing assets where average assets are required.

Leverage

Leverage =Total debtTotal assets
Construct measuredReliance on debt financing.
Suitable contextCapital-structure, risk and performance research with a clearly defined debt concept.
Risky useSubstituting total liabilities for interest-bearing debt without explanation.
Data sourceBorrowing notes and statement of financial position.
InterpretationHigher values generally indicate greater debt exposure, not automatically poor performance.
Extraction problemOmitting lease liabilities or double-counting current portions of long-term borrowings.

Simplified Tobin’s Q proxy

Q proxy =Market capitalisation + Total liabilitiesTotal assets
Construct measuredA market-based approximation of firm valuation relative to recorded assets.
Suitable contextListed-firm studies that explicitly justify and cite the simplified proxy.
Risky useCalling the proxy the original replacement-cost formulation of Tobin’s Q.
Data sourceYear-end share price, shares outstanding and audited financial statements.
InterpretationValues above one are often read as market valuation exceeding the accounting asset base, subject to proxy limits.
Extraction problemUsing inconsistent dates for market capitalisation and financial-statement balances.

Return on equity

ROE =Profit after taxShareholders’ equity
Construct measuredAccounting return attributable to the equity base.
Suitable contextShareholder-return studies where equity remains economically meaningful.
Risky useInterpreting extreme values caused by very small or negative equity as superior performance.
Data sourceStatement of profit or loss and statement of financial position.
InterpretationRead together with leverage, equity sign and industry context.
Extraction problemFailing to identify restatements, non-controlling interests or average-equity requirements.

Extraction and reproducibility controls

Correct control

Record entity level, year, statement, note, line item, unit, currency, restatement status, transformation and reviewer check.

Common error

Copy a figure into the dataset without preserving where it came from or why it satisfies the variable definition.

  • Create a variable dictionary before extraction begins.
  • Lock the numerator and denominator definitions before collecting the full panel.
  • Use one entity level within each ratio and document any justified exception.
  • Flag missing, negative, restated and unusually large values for review rather than silently replacing them.
  • Preserve source-page references or traceable links to each annual report.
  • Run independent spot checks and reconcile calculated ratios to published comparatives where possible.

Core supporting references

Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x

Enyi, E. P. (2005). Applying relative solvency to working capital management – the break-even approach. SSRN. https://ssrn.com/abstract=744364

Enyi, E. P. (2008). A comparative analysis of the effectiveness of three solvency management models. SSRN. https://ssrn.com/abstract=1138357

Enyi, E. P. (2018). Going concern, earning capacity and corporate financial stability. International Journal of Development and Sustainability, 7(1), 179–207.

Enyi, E. (2021). Corporate survival monitoring mechanism and discriminant analysis using operational breakeven point and relative solvency ratio. Academia Letters, Article 2, 1–10.

Enyi, E. P., Nweze, E. O., Adebawojo, O., & Olalere, M. D. (2026). Working capital management and cash conversion cycle – thinking outside the box with new insights. Economics and Business Quarterly Reviews, 9(1), 90–99. https://doi.org/10.31014/aior.1992.09.01.707

Later model variants and calibrations should be cited to the exact source used by the study. A DOI should be included only after it has been independently verified.

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