The relationship between investment intensity and profitability measures from the perspective of foreign investors

The study investigates whether non-GAAP profitability measures—EBITDA and EBIT—serve as reliable indicators of investment intensity among nonfinancial firms in GCC countries and which measure foreign investors prefer when making investment decisions. Against the backdrop of GCC economic diversification from oil and gas and the strategic emphasis on developing capital-intensive nonfinancial sectors, the research addresses two questions: (1) Are EBITDA and/or EBIT good indicators of investment intensity in GCC economies? (2) Do foreign investors prefer EBITDA and/or EBIT when deciding investment intensity? The work is motivated by mixed evidence on profitability–investment links and by investor preference for non-GAAP measures thought to be more value-relevant across jurisdictions.

The review differentiates investment intensity from capital intensity and summarizes measures used in prior studies (e.g., change in tangible assets plus depreciation; fixed assets to total assets; growth of fixed assets). Prior evidence on the profitability–investment link is mixed, with studies finding both positive and negative associations. Many prior works rely on GAAP-based profitability metrics (ROA, ROE, net profit), while investors increasingly use non-GAAP measures. EBITDA is highlighted as a proxy for operating cash flow and a comparable, financing- and tax-neutral measure; EBIT removes interest and taxes but includes depreciation effects. Hypotheses: H1 (null): No association exists between EBITDA and investment intensity. H2: A positive association exists between EBIT and investment intensity. The study also explores foreign investors’ preference between EBITDA and EBIT via interaction with foreign ownership.

Design: Panel study of 205 nonfinancial listed firms across GCC markets (KSA, Oman, Bahrain, UAE, Kuwait, Qatar) from 2010–2019, yielding 2050 firm-year observations. Data source: S&P Capital IQ. Financial firms are excluded; 2008–2009 are omitted due to the financial crisis. Variables: Independent variables: EBITDA (earnings before interest, tax, depreciation, amortization) and EBIT (earnings before interest and tax), as reported in Capital IQ. Dependent variable: Investment intensity (INV), measured as total fixed assets at year-end minus total fixed assets at year-begin plus depreciation/amortization (change in tangible assets plus depreciation). Controls: firm size (total debt), firm age (years since establishment), leverage (total debt/total assets), profitability growth, sales growth, and growth of market share price (growth in closing price). Model: Baseline panel regression of INV on EBITDA, EBIT, and controls. Estimation strategy addresses panel data issues: OLS diagnostics include skewness/kurtosis normality tests, VIF for multicollinearity, Breusch–Pagan/Cook–Weisberg for heteroskedasticity, and Durbin–Watson for autocorrelation (DW=1.415 indicates autocorrelation). Given heteroskedasticity and autocorrelation, Feasible GLS (FGLS) is used. Hausman test (Prob>chi2=0.923) supports Random Effects GLS as the primary specification. Robustness checks include Dynamic Panel Data (DPD, one-step GMM with lagged instruments L(2/.) for EBITDA and EBIT) to handle unobserved heterogeneity and endogeneity, and Dynamic OLS (DOLS) to address endogeneity and serial correlation. An additional GLS model tests interactions of profitability measures with foreign investment (FI), defined as the fraction of shares held by foreign investors.

Descriptive and diagnostics: - Mean EBITDA=1.437, EBIT=1.291; mean INV=36.845. VIF values <10 indicate no multicollinearity concerns; skewness/kurtosis suggest approximate normality. Breusch–Pagan heteroskedasticity present (chi2=177.37, p<0.001); Durbin–Watson=1.415 indicates autocorrelation. - Correlations: EBITDA–INV positive and significant (r=0.279, p<0.01); EBIT–INV positive but smaller (r=0.121, p<0.01). Main regression results (Table 8): - FGLS: EBITDA coef=80.790 (p=0.002); EBIT coef=-10.792 (p=0.590, ns). Controls: LEV positive (165.610, p<0.001); AG negative (-47.812, p=0.006); Size S negative (-23.028, p<0.001); GRO not significant. - GLS Random Effects (primary): EBITDA coef=84.316 (p<0.001); EBIT coef=-22.771 (p=0.046). Controls: S positive (14.694, p=0.027); GRO positive (2.153, p=0.017); LEV (40.501, p=0.082, ns); AG (4.035, p=0.783, ns). Model fit: R2≈0.3173; model significant (Prob>chi2=0.000). - DPD (one-step GMM, robust): EBITDA coef=177.934 (p<0.001); EBIT coef=-46.202 (p<0.001). Controls: LEV positive (85.148, p<0.001); S positive (19.283, p=0.019); AG not significant; GRO not significant. Wald chi2=440.33. - DOLS: EBITDA coef=267.013 (p<0.001); EBIT coef=-58.975 (p=0.204, ns). Controls: LEV positive (174.613, p=0.004); AG negative (-310.245, p<0.001); S and GRO not significant. R2=0.25041. Foreign investor interactions (Table 9): - EBITDA*FI coef=0.00124 (p=0.001), positive and significant. - EBIT*FI coef=-0.00135 (p=0.001), negative and significant. Overall: EBITDA consistently shows a positive and significant association with investment intensity across all estimators. EBIT is negative and significant in GLS-RE and DPD, and negative but not significant in DOLS. Interaction results indicate foreign investors favor EBITDA (positive) and avoid EBIT (negative) as guides for investment intensity decisions.

Findings directly address the research questions. EBITDA, a non-GAAP proxy closer to operating cash flow and less affected by cross-country tax and accounting differences, robustly predicts higher investment intensity in GCC nonfinancial firms. EBIT, which includes depreciation and amortization effects, provides a weaker and often negative signal, likely due to high depreciation burdens in capital-intensive GCC firms reducing EBIT comparability across industries and countries. Interaction analysis shows foreign investors’ decisions on investment intensity align positively with EBITDA and negatively with EBIT, indicating a preference for EBITDA when evaluating operating capacity and cash-generating ability. Control effects suggest leverage is associated with greater investment intensity (risk–return balancing), while firm size and age present mixed effects across models. These results reinforce the value relevance of non-GAAP metrics in emerging markets’ capital allocation and guide regulators and market participants toward emphasizing EBITDA disclosures for better resource allocation.

The study provides GCC-wide evidence that EBITDA positively and significantly relates to investment intensity, while EBIT is negatively related or not significant, indicating that EBITDA is a superior indicator for investment decisions in capital-intensive, diversified nonfinancial sectors. Foreign investors’ preferences also favor EBITDA over EBIT when determining investment intensity. Contributions include extending the literature on non-GAAP performance measures’ relevance to investment behavior in emerging markets and informing policy on disclosure practices. Practical implications: regulators and policymakers should ensure high-quality, standardized EBITDA/EBIT reporting to enhance market confidence and capital allocation; managers should provide transparent non-GAAP metrics alongside GAAP measures to support investor decision-making. Future research could test alternative measures of investment intensity, explore causal dynamics between investment intensity and profitability, and examine generalizability beyond the GCC.

- Measurement scope: Investment intensity is proxied solely by change in tangible assets plus depreciation; alternative measures may yield different insights. - Data source and variables: Reliance on firm financial reports and specific non-GAAP variables may introduce measurement differences across firms. - Causality: The study examines associations and does not establish causal directions between profitability measures and investment intensity (reverse causality possible). - External validity: Findings are specific to GCC nonfinancial firms and may not generalize to other regions or sectors.