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ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
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Effect of Human Capital Expenditure on the Profitability of Listed
Consumer Goods Companies in Nigeria
Ajayi, Modupe Olayinka., Oluwasesin, Olayemi Deborah
Department of Project Management, Federal University of Technology, Akure, Nigeria
DOI: https://dx.doi.org/10.47772/IJRISS.2025.910000521
Received: 24 October 2025; Accepted: 30 October 2025; Published: 18 November 2025
ABSTRACT
This study investigates the effect of human capital expenditure on the profitability of 21 consumer goods
companies listed on the Nigerian Exchange Group over the 2015–2024 period. Using panel data extracted from
audited annual reports. Results reveal a strong positive impact of T&D on ROA (β = 18.42, p < 0.001),
indicating that a one-percentage-point increase in training intensity boosts ROA by 18.42 percentage points.
Conversely, S&W negatively affects ROA (β = -1.35, p = 0.002), suggesting that wage intensity without skill
enhancement erodes profitability. The findings underscore that not all human capital spending is value-
accretive training drives strategic advantage, but salaries alone signal inefficiency. The study recommends
prioritizing T&D investments and linking salary growth to skill development to optimize long-term
profitability in Nigeria’s consumer goods sector.
Keywords: Human Capital Expenditure, Training and Development, Salaries and Wages, Profitability, Return
on Assets
INTRODUCTION
The going concern of a business depend largely on how well its managements are able to effectively harness
organizations’ resources to ensure stability of its business operations in order to prevent liquidation in the
current technologically advanced and dynamic business world. Increase adoption of technology has led to
dynamism in the ways consumer goods companies are being managed which is as a result of the important
roles it plays in the achievement of organizations’ objectives in this period of competitive business
environment. They tends towards being creative in this era of increased changes in technology by shifting to be
innovation oriented organizations where skill, knowledge and attitude is of paramount. The performance of
consumer goods companies therefore lies in its managerial capability to ensure proper navigation into the
changing business environment (Ovedje & Iserien, 2021).
These managerial capability is embedded in the intellectual asset of the organization which is its human
capital. Human capital being a viable component of an organization has been described as an instrument of
promoting competitive development among companies in that where there is human development, the
qualitative and quantitative progress of such organization is inevitable (Okere & Igba, 2023). This
irreplaceable asset of the organization plays a crucial role in driving the organization towards the achievement
of its objectives. This is because a company’s human capital is a fundamental determinant of its performance
and every other assets owned by an organization cannot function effectively without human initiatives
(Bawono, 2021). Despite the increase adoption of Artificial Intelligent, human intellect can not be
underestimated all because human reasoning is the backbone of the achievements of any technological
evolution irrespective of how vast it is including Artificial Intelligent. As a result of the increased adoption of
technology, organizations needs to focus on new pathways to thrive in the face of technological challenges by
developing human imagination to reshape their operations for sustainable development. in this age of
innovation advancement.
For organization to therefore adapt to this new pathways of development, the major competitive weapon
required is to consciously leverage on their workforce by improving largely on the recruitment of people with
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high level of intellectual competence and the readiness to be skilled. In doing this, there is need for firms to
expend on their intellectual assets to enhance their skills and competences through training and development,
compensations and also ensure a conducive working environment. All these aforementioned expenses incurred
for the improvement of employees brought about human capital expenditure.
Human capital expenditure being an unavoidable cost in having a competent workforce in an organization, can
be describe as the transformation of individual competence into highly productive human capital in monetary
values which relates to the amount spent on employee training, development and skills acquisition with the
effective input of health and moral values. (Nduka, Mark & Idayat, B.A 2024) describe such investment as
needful as it brings about the achievement of competitive advantage and other important indicators of
profitability. There is therefore the need for consumer goods companies to make informed decisions when it
comes to their stock of human capital. Consumer goods companies are firms that invested their resources to
produce items that are intended for direct use by end users with the aim of viable return on their investments.
In this present knowledge driven century, it is necessary for consumer goods companies to see human capital
as a viable component of its operations and utilize it in such a way that will not make its success to be at stake
(Ogunbiyi, Alao, Aremu & Olalere, 2023) affirms that, this can be achieved by ensuring the human capital
that will drive the economy of listed consumer goods companies be recognized as a valuable part of the total
value of an organization in order to assess the effect it has on the corporate profitability. For companies to
therefore have adequate valuation, the cost incurred must be adequately classified because some of the benefits
derived from the cost incurred on human span more than one accounting period.
For consumer goods companies and all companies at large to remain in operation for the foreseeable future, its
human capital remains the most important factor as these companies are key determinants of economic long
term growth, development and sustainable practices for Nigeria. The need for this sector to adequately bring
about innovations in their operations is highly paramount as there success has positive impact on them as an
entity and the Nigeria economic development in general while failure on the other hands is disastrous to their
going concern and economic growth of the nation. (Tatiana, 2024) in World Bank Support Forum emphasizes
the need for leaders to prioritize investment in human capital by quantifying the impact of training and
development on productivity.
Market experts, policy makers, investors, financial market participants and stakeholders perceived human
capital as the major driver of performance and growth. This is because they attach importance to the skills and
expertise of highest echelon of an organization as the stock market reacts to any change of management. Yet
this highly valued capital is not recognized in the statement of financial position as assets. (Abraham, Odobi &
Enwuchola, 2022). They treated the total cost incurred on human capital as expense in the statement of
comprehensive income. Charging the expenditure on human capital as expense in a statement of
comprehensive income was traceable to the inability of organizations to separate the expense element (salaries,
wages, commission bonus, maintenance, allowances) from the capital expenditure element (acquisition,
recruitment, training, development and retraining). This has created an obvious gap as it will affect the real
profitability of the organizations. (Ovedje & Iserien,2021).
Also, most consumer goods companies fall short of their role in ensuring that the cost incurred on their stock
of knowledge adequately match the period in which it was incurred. This could be due to the fact that
consumer goods companies has not really dive into justifications for the place of knowledge, skill and attitude
in relation to profitability considering the technology driven era which has digitalize the economy. This study
therefore becomes needful as the rate at which organizations expend on their competent and quality staffs to
train and retrain them does not really match their rate of growth in returns. Hence, the main objective of this
study is to determine the effect of human capital expenditure(Training and Development; Wages and Salaries)
on the profitability of listed consumer goods companies.
LITERATURE REVIEW
Human capital as a concept was first developed by Sir Williams Pretty in the year 1691. The research into it
began in 1960 by Rensis Likert (Becker, 1964). (Becker, 1976) described knowledge and skills as values that
can be accumulated in different forms of education, training and development.
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Learning through Education and training is very crucial to bringing about the value and uniqueness embedded
in human. (Kwon, 2019) cited by (Ileka & Muogbo, 2020) characterized human capital as ; expandable, self
generating, transportable and shareable. The expandable and self generating characteristics of human capital
can be said to mean the possibility that the stock of knowledge increases individual human capital. While the
transportable and shareable characteristics can be likened to the ability of an individual to be able to impact the
knowledge acquired into others inform of training.
Classification of Human Capital Expenditure
The combined effort of an organization in monetary terms to bring out the best out of its employee in an
efficient and effective human capital that will drive the organization to the achievement of its objective can be
said to be human capital expenditure. The cost incurred by an organization on its employee is what it
sacrificed to achieve its aim. Such cost include Training and development, Salaries and Wages, bonuses,
contributory pension, health and welfare costs. According to (Ifrueze, 2014) cited by (Balogun & Omotoye,
2020). Expenditure on human capital are usually capital and revenue in nature. Capital expenditure is that
which provides benefits that is beyond the current accounting period such as Training and Development while
revenue expenditure is that which provides benefits during the current accounting period such as Salaries and
Wages.
Measures of Corporate Profitability
Corporate profitability is often evaluated by the use of profitability ratios. Profitability ratios measures the
operating success of a company for a given period of time and in measuring the returns of a firm in relation to
either sales, assets or shareholders equity and are usually given in percentages. (Ovedje & Iserien, 2021) .
These ratios are important for a company’s ability to obtain debt and equity financing. It also provides
information to management about specific areas of business that need attention and to access the economic
condition of a firm.
There are many different profitability ratios that measured profitability; the following are three of the most
common.
Net Profit Margin
The net profit margin measures the financial value of sales and indicate management efficiency in production
and sales of its products. Net profit margin is measured by expressing the net profit as a percentage of sales
that is, net profit divided by sales multiply by one hundred. The higher the rate of return, the more net sales are
providing income to the business. If the net profit is relatively low, it may imply management’s inability to
manage its activities efficiently. Therefore, a high ratio is more desirable. (Kinuthia, 2020).
Return On Assets
Return on assets measures the efficiency with which a firm has utilized the total funds provided by the
creditors and owners of the firm in generating profit. Therefore measuring the company’s success in using its
asset to earn a profit can be expressed as net profit divided by total assets the higher the ROA, the better for all
capital suppliers. Is the ratio of net profit to total asset. (Abraham, Odobi & Enwuchola, 2022).
Return On Owners Equity (ROE)
Return on owner’s equity is one of the important measures in financial analysis and the most widely used
measure of corporate profitability. This ratio showed the relationship between net income and common
shareholders’ investment in the company. That is how much income is earned by a company from every naira
invested by the common shareholders. It indicates how efficiently a firm has used the resources of the
shareholders’ equity (Agbi, Popoola & Edem 2020) . A low ratio may imply management is not satisfying its
function and main objective of maximizing the owners’ wealth.
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Looking at the above three measures of corporate profitability, one can conclude that corporate profitability
can be calculated in several ways . in each case a measure of profit is the numerator and the denominator
varies, that is, dividing by sales generates profit margins, dividing by shareholders equity produces return on
equity, while dividing by total assets produces return on investment.
Theoretical Review
Resourced- based Theory
The Resource-Based Theory was first propounded by Birger Wernerfelt (1984).The framework was later
expanded and popularized by Jay Barney (1991).They posits that organizational performance differences arise
from the possession and effective deployment of resources that are Valuable, Rare, Inimitable, and Organized
(VRIO). The theory explained further that incurring high labour costs in the form of salaries and wages does
not automatically yield superior performance but that superior performances can only be met when the ability
of a firm to convert compensation into enhanced motivation, commitment and productivity through
complimentary management effort such as training and development is show cased. The theory argued that
salaries and wages represent a necessary but not sufficient investment in human capital. When firms pay higher
wages without corresponding mechanisms to enhance skill utilization such as structured training, effective
supervision, or technology adoption these expenses may simply inflate operating costs without generating
proportional productivity gains. Therefore, the relationship between salaries and wages and return on assets
could be negative or neutral in the absence of complementary human resource development strategies (Youndt
& Snell, 2004).
Resource Based Theory further explained that while compensation is essential to attract and retain employees, it
enhance performance only when complemented by other value-creating human resources practices. Without
such complementary, salaries and wages may simply increase costs, thereby diluting firm profitability and
reducing ROA.
Resource-Based theory affirms that firm performance depends not merely on resource possession such as
increased compensation but on resource orchestration which means the strategic combination of salary
structures, training programs, and performance management systems that together create unique human capital
advantages. Therefore, for salaries and wages to meet the VRIO criteria to become strategically valuable, it
must be integrated with broader human resource development initiatives such as training and development
(Grant, 1996) cited by (Ogunbiyi, Alao, Aremu, & Olalere,2023).
Human Capital Theory
Human capital theory was originally propounded by Schultz (1961) and later developed by Becker (1964) and
Mincer (1974). The theory placed high value on the employees in the organization by describing them as
human capital. It sees problem solving abilities in human which contribute to both short and long term firm
performance and therefore rests on the assumption that formal training and developmental programs are highly
instrumental and necessary to improve the productive capacity of a population. Human capital theorists also
argue that a skilled population is a productive population in that the investment in people’s knowledge, skills
and competencies through training and development increase the productivity and efficiency of workers by
increasing the level of cognitive stock of economically productive human capability.
According to (Becker, 1964), expenditures on training and employee development constitute a form of capital
formation that improves the productive capacity of the workforce. Organizations that allocate resources toward
training and development are essentially investing in assets that appreciate over time through enhanced
employee output and innovation. (Zhou, Zhang & Montoro-Sánchez, 2018) also confirmed that human capital
investment, especially in skill development, leads to improved organizational performance through enhanced
innovation capacity, operational efficiency, and employee commitment. The study emphasized that investment
in employee training is not just an ordinary cost, but a strategic driver of organisational competitveness and
sustainable performance.
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The theoretical linkage to the expected positive effect of training and development can be framed in three
dimensions. The first is that it brings about quality output and fosters innovations which lead to proficient at
executing tasks, adapting to technological changes, creation of superior quality, adopt and leverage on new
technologies faster and contributing to operational efficiency that can command higher return on asset. The
second dimension is that training and development enhances labor productivity. Higher labour productivity as
a result of better utilization of assets allows skilled employees to use tangible and intangible assets more
efficiently, thereby increasing revenue relative to return on asset. Third, training and development reduces
employee turnover and recruitment costs. Effective training raises job satisfaction and retention thereby
lowering operational expenses and stabilizing the workforce which will eventually contribute to sustained
profitability. The above dimensions brought together, is expected improve utilization of resources and thereby
generate higher profitability levels for organizations which invest more in training and development and also
imply that positive returns should be expected in financial performance metrics such as return on asset.
Empirical Review
To empirically analyse this study, previous research work in relation to the study will have to be reviewed to
know the extent to which research has been conducted in this area of study and their various findings, results
and recommendations (Hasan ul & Naeem 2022) in their study assessed how the number of employees and
staff cost affects the financial outcomes of textile enterprises listed on the Pakistan Stock Exchange. The study
utilized an ex post facto analysis methodology and obtained data from the financial statements of 73
organizations over a five-year period from 2017 to 2021. Panel regression analysis was performed using E-
views software. The Breusch-Pagan test was employed to measure the heterosedasticity of regression errors
and then the Hausman test is utilized to determine the best approach between a fixed effect and a random effect.
The findings revealed that staff cost positively affects financial performance, whereas the number of
employees significantly negatively affects financial performance. Therefore, the study recommends investing
in employees to boost the firm’s profitability. Also, accounting standards and disclosures should be
incorporated into human resource accounting.
(John & Roseline, 2023) Viewed the influence of human capital on the profitability of companies in the
consumer goods sector in Nigeria. With a population of 21 firms in the consumer goods sector, a sample size
of 17 firms listed on the Nigerian Exchange Group Plc as of December 31, 2022 was selected using purposive
sampling techniques. To achieve the objectives, an ex-post facto research design was adopted involving
manual generation of data from the annual reports of the selected firms. The study period spanned from 2013
to the 2022 financial year. The data obtained were analysed using descriptive and inferential statistics,
specifically through simple regression techniques. The profitability of companies in the consumer goods sector
was measured by return on assets. Results revealed that human capital has a significant positive influence on
the return on assets. This result was evidenced by a beta coefficient of 0.520 and a probability value of 0.000.
It was concluded that, with adequate human capital, firms' profitability is enhanced in the long run. Since
human capital is an aspect of integrated reporting and is based on worldwide best practices, it was
recommended that human capital should be considered a main area of interest when preparing annual reports
for businesses. This is because the reports are intended for stakeholders, who are the primary resource
providers.
(Nduka, Mark & Idayat, 2024) carried out a research on the effect of human capital expenditure on financial
performance of listed consumer goods firms in Nigeria. The study aimed at determining the effect of human
capital expenditure on financial performance of listed consumer goods firms in Nigeria. The study population
consisted of twenty (20) listed consumer goods firms in Nigeria. The study used purposive sampling technique.
Secondary source of data was used in compiling its findings. The independent variable is conceptualized as
human capital expenditure, while the dependent variable is financial performance. The study concluded that
the extent of the effect of human capital expenditure on financial performance in Nigeria is very weak and
insignificant. The implication of this result is that the extent to which consumer goods firms in Nigeria embark
on human capital expenditure does not significantly and positively improve the financial performance. The
study recommended that the management of consumer goods firms in Nigeria should invest in the acquisition
of technical capacity skills needed by their employee, which has the potential of improving the financial
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performance by the company. However, the accounting treatment and disclosures of this amount still needs to
be standardized.
Being one of the variables used in determining expenditure on human capital, employees training and skill
development is one of the key human capital expenditure (Makgata & Ngwakwe 2017) evaluated the the
relationship between training and development and profitability of companies in Nigeria. The study evaluated
how productivity can be improved through investment in training and development of employee which will
result in increased profitability of the firm. The research work evaluates the relationship between employees’
training and development and profitability. The study apply quantitative approach. Correlation statistics was
used to analyse the secondary data collected over a period of 5 years. (2011- 2015) from the archives of
selected companies The profitability of a quoted company is a function of its human capital and the quality of
the human capital is also a function of Training and Development (T&D) which is cost to the organization.
Some recent researchers have argued whether the human capital cost and profitability of quoted companies are
of positive or negative relationship. (Kinuthia, 2020) analyzed the positive relationship between human capital
expenditure and profitability in that expenditure on education, training and development increased productivity
over twice the size of the wage increase in the trainee. This is because not all productivity gain brought about
by training is compensated by increase in individual remuneration, thereby making such investment remain
profitable for the organizations.
(Okere & Igba, 2023) in their investigated the relationship between Human Capital expenditure on salaries
and wages and Financial Performance of listed Manufacturing firms in Nigeria. Panel research design was
used for the study. The data used were sourced from twenty (20) listed manufacturing firms in Nigeria, quoted
on the Nigerian Stock Exchange from 2009-2018. The data extracted were analyzed using the panel data
regression analysis, descriptive method and Hausman test was used to determine the most appropriate model.
The study shows that there is a non-significant but positive relationship that exists between Human Capital
cost of salaries and wages and Financial Performance of manufacturing companies in Nigeria. Investing in
Human Capital shows a significant negative relationship with financial performance of manufacturing firms in
Nigeria. The study recommends that Companies should come up with some effective plans especially in
investing the various aspects of human capital as not only does it direct firms to attain greater performance but
also it ensures firms to remain competitive for their long term survival. This can be achieved by stipulating that
the understanding of firm performance in relation to human capitals should not be regarded as a phenomenon
that only adds ‘more zeros’ in a firm’s profits; it should be seen as an entire workforce as the most valuable
assets in order for the organization to pave ways for greater achievements via innovations and creativity.
METHODOLOGY
The study area covered all the consumer goods companies listed on the Nigeria Exchange Group. The study is
analytical in nature where panel regression was used to analyse the financial statement of the organizations
under studied. The study made use of secondary source of data gathered from the audited annual report and
financial statement of the listed consumer goods companies in Nigeria. The total consumer goods company
listed on the Nigeria Exchange Group as at 31
st
Dec., 2024 were Twenty-one(21) in number. The study
covered a period of Ten (10) years from 2015 to 2024 for it to have true representation of the sector. Variables
measured are dependent variable, Independent variables and control variables. Profitability was measured by
Return On Asset (ROA), Human Capital Expenditure (HCE) was measured using the ratio of employee-related
expenses (training and development) to total expenditure and Human Capital Expenditure (HCE) (salaries and
wages) to total expenditure. The Control Variables was measured using Asset Tangibility (AT) and
Liquidity(LIQ).
Model Specification
The econometric model for the study is specified as:
PROF_it = β0 + β1HCE_it + β2AT_it + β3LIQ_it + ε_it
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Where:
PROF_it = Profitability of firm i at time t (ROA )
HCE_it = Human Capital Expenditure (T and D , S and W)
AT_it = Asset Tangibility
LIQ_it = Liquidity
ε_it = Error term
RESULTS AND DISCUSSION
Descriptive Statistics
In the context of examining the impact of human capital expenditure on the profitability of listed consumer
goods companies in Nigeria, the descriptive statistics provide a foundational overview of the dataset,
encompassing 210 observations across a 10-year period from 2015 to 2024 for 21 firms. These statistics
illuminate the central tendencies, variability, and distributional characteristics of the variables: Return on
Assets (ROA) as the proxy for profitability (dependent variable), Salaries and Wages (S&W) and Training and
Development (T&D) as components of human capital expenditure (independent variables), and Liquidity
(LIQ) and Asset Tangibility (AT) as control variables. Here is an analysis and interpretation of each variable’s
descriptive statistics.
The mean value of Return on Assets (ROA) is 7.05, with a median of 6.50, a minimum of 0.50, and a
maximum of 18.00. This suggests that, on average, listed consumer goods companies in Nigeria generated
approximately 7% returns on their total assets during the period under review. The closeness of the mean and
median indicates a relatively balanced distribution, though the skewness (0.97) implies a moderate positive
skew meaning some firms achieved higher profitability levels compared to the industry average.
The standard deviation (3.36) reflects moderate variability in profitability among firms, showing that not all
companies achieved consistent performance. The kurtosis value of 3.89 suggests a slightly leptokurtic
distribution, meaning that extreme profitability values occurred more frequently than would be expected under
a normal distribution. The Jarque-Bera statistic (40.14, p < 0.01) confirms that ROA is not normally
distributed, implying some outliers in firm profitability performance across the study period.
The mean of Salaries and Wages is 4.95, with a median of 4.90, minimum of 3.00, and maximum of 7.50.
These values indicate that salaries and wages constitute a moderate share of total expenditure among listed
consumer goods firms. The closeness of the mean and median values again suggests a relatively symmetric
distribution, corroborated by the low skewness value (0.27). The standard deviation (1.03) indicates slight
dispersion, implying that firms’ spending on salaries and wages does not vary widely across the sector. The
kurtosis (2.20) shows a platykurtic distribution—flatter than the normal curve—indicating fewer extreme
salary and wage expenditures. The Jarque-Bera test (8.21, p = 0.016) suggests a slight deviation from
normality, meaning that while the data are close to being normally distributed, there are minor asymmetries
possibly due to firm size or differing human resource structures.
The mean of Training and Development expenditure is 0.41, with a median of 0.40, minimum of 0.10, and
maximum of 0.90. This shows that, on average, listed consumer goods companies spend less than 1% of their
total expenditure on employee training and development. This low figure indicates that Nigerian consumer
goods firms generally allocate minimal resources to human capital enhancement activities such as workshops,
skill acquisition, or professional training. The standard deviation (0.14) reveals low dispersion, suggesting
consistent under investment in training and development across firms. The positive skewness (0.73) indicates
that while most firms spend relatively little on training, a few allocate significantly higher proportions of their
budgets to it. The kurtosis (4.38) shows a leptokurtic distribution, implying that extreme values (firms that
spend much more or much less) are more common than in a normal distribution. The Jarque-Bera statistic
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(35.12, p < 0.01) confirms that the data are not normally distributed, likely due to the presence of a few firms
with substantially higher training investments.
The mean liquidity ratio is 1.38, with a median of 1.35, minimum of 0.85, and maximum of 2.00. This
indicates that, on average, listed consumer goods companies have a moderately strong ability to meet short-
term obligations, as their current assets slightly exceed current liabilities. The standard deviation (0.22) implies
low variability in liquidity levels among firms, suggesting relatively stable short-term financial health across
the sector.
The skewness (0.31) and kurtosis (2.89) values show that liquidity is approximately normally distributed, with
a slightly right-skewed and mesokurtic pattern. The Jarque-Bera statistic (3.54, p = 0.17) shows an
insignificant probability value, indicating that the liquidity variable is normally distributed. This normality
suggests that liquidity management practices among the sampled firms are relatively consistent and do not
vary dramatically.
Asset Tangibility has a mean of 53.36, a median of 53.75, a minimum of 30.00, and a maximum of 77.50.
These figures indicate that, on average, fixed assets constitute about 53% of total assets for the sampled
companies, reflecting the capital-intensive nature of consumer goods production. The standard deviation
(10.95) indicates substantial variation, suggesting that while some firms are heavily asset-based, others
maintain a more flexible, less capital-intensive structure. The skewness (0.06) shows near symmetry, while the
kurtosis (2.09) suggests a platykurtic distribution, indicating that extreme values are less frequent. The Jarque-
Bera test (7.41, p = 0.0247) reveals that the variable slightly deviates from normality. However, the near-
symmetry and low dispersion indicate that most firms in the sector share similar asset structures.
Overall, the descriptive statistics reveal that profitability (ROA) and human capital expenditure (S&W and
T&D) vary across listed consumer goods firms, although liquidity and asset tangibility are relatively stable.
The data exhibit mild departures from normality, with most variables showing positive skewness suggesting
that a few firms perform better or invest more than the average. Notably, the low mean for training and
development underscores limited investment in employee capacity-building, which may have implications for
long-term profitability and productivity within Nigeria’s consumer goods sector.
Table 1: Descriptive Statistics
ROA
S&W
T&D
LIQ
AT
Mean
7.045238
4.945238
0.409762
1.375381
53.36429
Median
6.500000
4.900000
0.400000
1.350000
53.75000
Maximum
18.00000
7.500000
0.900000
2.000000
77.50000
Minimum
0.500000
3.000000
0.100000
0.850000
30.00000
Std. Dev.
3.355664
1.031977
0.140901
0.215984
10.95180
Skewness
0.974734
0.271029
0.726036
0.313513
0.060629
Kurtosis
3.887115
2.196962
4.380325
2.891601
2.088078
Jarque-Bera
40.13971
8.213590
35.12086
3.542990
7.405168
Probability
0.000000
0.016460
0.000000
0.170079
0.024660
Sum
1479.500
1038.500
86.05000
288.8300
11206.50
Sum Sq. Dev.
2353.440
222.5802
4.149288
9.749620
25067.88
Observations
210
210
210
210
210
Source: Researcher’s Computation (2025)
Test of Variables
In table 2, this section conducts essential pre-estimation and post-estimation tests to ensure the reliability and
validity of the research findings. Pre-estimation tests like the unit root test and correlation analysis check for
data stationarity and multicollinearity, while post-estimation tests such as the Hausman and heteroscedasticity
tests confirm model robustness and address variance inconsistencies.
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Unit Root Test
The ADF test statistic for ROA is 76.8281 with a corresponding p-value of 0.0000, indicating statistical
significance at the 1% level. This result implies that the null hypothesis of a unit root is rejected. Therefore,
ROA is stationary at first difference, denoted as I(1). This means that after first differencing, the profitability
of firms, as measured by Return on Assets, exhibits a stable mean and variance over time. The stationarity of
ROA ensures that the profitability trends across the sampled firms are consistent enough to allow meaningful
analysis of the influence of human capital expenditure. For Salaries and Wages, the test statistic is 69.6190
with a p-value of 0.0000, which is also significant at the 1% level. This suggests that the series is stationary
after first referencing, implying that fluctuations in salary and wage expenditures stabilize over time. In
practical terms, this means that although salary and wage levels may vary across firms and years, their growth
or change rate tends to revert to a stable mean. Thus, S&W is integrated of order one, I(1), confirming its
suitability for inclusion in the panel regression model. The Training and Development variable records an ADF
statistic of 109.562 with a p-value of 0.0000, confirming strong statistical significance. Like the other
variables, T&D is stationary at first difference, i.e., I(1). This result indicates that variations in firms’ training
and development expenditures are not random but trend around a consistent long-term mean after first
differencing. The implication is that although some firms may periodically increase or reduce spending on
training, the overall pattern of investment in employee development across the sector remains stable over time.
The Liquidity ratio shows an ADF statistic of 79.6442 with a p-value of 0.0018, which is also significant at the
1% level. This means that liquidity is stationary at first difference, denoted as I(1). Therefore, short-term
solvency or the ability of firms to meet current liabilities using current assets remains stable after differencing.
This stability suggests that listed consumer goods companies generally maintain a consistent liquidity policy
over the years, despite occasional fluctuations due to market or operational factors. Asset Tangibility records a
test statistic of 61.3188 and a p-value of 0.0031, indicating significance at the 1% level. The result shows that
AT is stationary at first difference (I(1)), meaning that the proportion of fixed assets to total assets in consumer
goods firms stabilizes after initial variation. This finding suggests that while companies might adjust their asset
structures occasionally due to expansion, divestment, or revaluation, the overall ratio remains stable in the long
run.
The results of the unit root test indicate that all variables—ROA, S&W, T&D, LIQ, and AT are stationary at
first difference, I(1). This uniform order of integration is desirable for panel data econometric analysis because
it allows for meaningful long-run relationship testing (such as co-integration) and ensures that the regression
estimates are valid and non-spurious. The presence of stationarity at first difference implies that while the raw
series of the variables may exhibit trends or random walks over time, their difference forms are stable and
reliable for further statistical estimation. ADF test confirms that all the variables possess the required statistical
properties for panel regression analysis. This validates the appropriateness of using a first-difference
transformation or other panel estimation techniques, such as Fixed Effects or Random Effects Models, in
examining the effect of human capital expenditure on profitability among listed consumer goods companies in
Nigeria.
Table 2: Unit Root Test [ADF Test with Intercept Only]
Variable
P-Value
Order of Integration
Decision
ROA
0.0000
I(1)
Stationary
S&W
0.0000
I(1)
Stationary
T&D
0.0000
I(1)
Stationary
LIQ
0.0018
I(1)
Stationary
AT
0.0031
I(1)
Stationary
Source: Researcher’s computation (2025)
Correlation Matrix
The correlation coefficient between ROA and T&D is 0.898, which is positive and highly significant at the 1%
level (p < 0.01). This strong correlation suggests that increases in expenditure on training and development are
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associated with higher profitability among listed consumer goods firms. The relationship implies that
investment in employee capacity-building, skills acquisition, and professional development translates to
enhanced productivity, efficiency, and ultimately, improved firm performance. This result supports the
theoretical premise that human capital development contributes meaningfully to a firm’s value creation and
profitability. The correlation between ROA and S&W is 0.750, also positive and significant at the 1% level (p
< 0.01). This indicates a strong direct relationship between employee remuneration and profitability. The
implication is that firms that invest adequately in compensating their employees through competitive salaries
and wages tend to achieve better financial performance. Proper remuneration likely motivates employees,
enhances job satisfaction, and reduces turnover, which collectively improve operational efficiency and
profitability. This finding aligns with the view that salaries and wages are not merely expenses but strategic
investments in human capital that yield financial returns.
The correlation coefficient between ROA and AT is 0.073, which is positive but not statistically significant (p
= 0.290). This suggests a very weak relationship between asset tangibility and profitability. The lack of
significance indicates that the proportion of fixed assets in total assets does not have a notable effect on
profitability among listed consumer goods firms. This may be because profitability is more driven by efficient
use of both tangible and intangible resources, particularly human capital, rather than merely holding large
physical assets.
The correlation between ROA and LIQ is 0.563, which is positive and significant at the 1% level (p < 0.01).
This moderately strong relationship implies that firms with higher liquidity levels that is, those capable of
meeting short-term obligations tend to be more profitable. Adequate liquidity ensures smooth operations,
reduces financial distress risk, and provides flexibility to seize investment opportunities, all of which enhance
profitability. However, excessively high liquidity may suggest underutilized assets, so the optimal balance is
key for sustainable profitability. The correlation between T&D and S&W is 0.913, which is very strong and
significant at the 1% level (p < 0.01). This indicates that firms that spend more on training and development
also tend to spend more on salaries and wages. The relationship suggests that both variables complement each
other as components of human capital expenditure. Firms that prioritize employee compensation are also likely
to invest in their professional growth, reflecting a holistic human resource strategy aimed at maximizing
productivity and profitability. The correlation coefficient between T&D and AT is 0.202, significant at the 1%
level (p = 0.003). Although the relationship is relatively weak, its positive sign indicates that firms with higher
tangible assets may allocate slightly more resources toward training and development. This may be due to the
need for skilled personnel to manage and operate tangible production assets effectively in capital-intensive
consumer goods companies.
The relationship between S&W and AT is 0.236, significant at the 1% level (p = 0.001). This weak positive
relationship suggests that firms with larger tangible assets also tend to have higher salary expenses, possibly
due to the need for more technical or operational staff to manage these assets. However, the relatively low
magnitude of correlation implies that while the relationship exists, it is not a dominant factor in determining
wage expenditure. The correlation between AT and LIQ is -0.341, which is negative and significant at the 1%
level (p < 0.01). This indicates an inverse relationship between asset tangibility and liquidity. In other words,
firms with higher proportions of fixed assets tend to have lower liquidity. This result is logical, as heavy
investment in tangible assets such as machinery and buildings reduces the proportion of current assets
available for meeting short-term obligations. This finding suggests that capital-intensive firms might face more
liquidity constraints compared to those with lighter asset structures.
The correlation between T&D and LIQ is 0.485, which is positive and significant at the 1% level (p < 0.01).
This moderate positive relationship indicates that firms with healthier liquidity positions are more likely to
allocate funds for training and development activities. It implies that liquidity strength enhances a firm’s
ability to invest in human capital, reflecting a connection between financial flexibility and employee
development initiatives. Overall, the correlation results reveal that human capital expenditure variables (T&D
and S&W) exhibit strong positive and significant relationships with profitability (ROA), indicating that firms
that invest more in their workforce tend to perform better financially. The control variables liquidity and asset
tangibility also show meaningful but weaker relationships with profitability, suggesting that while financial
and structural factors play roles, human capital remains a more critical determinant of firm performance.
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Table 3: Correlation Statistics
ROA
T&D
S&W
AT
LIQ
ROA
1
210
T&D
.898
**
1
.000
210
210
S&W
.750
**
.913
**
1
.000
.000
210
210
210
AT
.073
.202
**
.236
**
1
.290
.003
.001
210
210
210
210
LIQ
.563
**
.485
**
.466
**
-.341
**
1
.000
.000
.000
.000
210
210
210
210
210
Source: Researcher’s Computation (2025)
Multicollinearity Analysis
The results from the VIF test indicate that moderate multicollinearity exists between the two human capital
expenditure variables (T&D and S&W), while Asset Tangibility (AT) and Liquidity (LIQ) do not present any
multicollinearity concern. The VIF values of 6.183 and 6.251 for T&D and S&W respectively are slightly
above the acceptable limit of 5, implying that their effects on profitability may overlap to some degree. This
finding is consistent with theoretical expectations, as both variables represent different but related aspects of
human capital investment. However, since none of the variables exceeds the critical VIF threshold of 10, the
level of multicollinearity can be considered tolerable and not severe enough to distort the regression estimates.
The results therefore validate the continued use of all variables in the model, provided that the potential
interrelationship between T&D and S&W is acknowledged in interpreting the regression outcomes.
The moderate multicollinearity observed between the two components of human capital expenditure suggests
that training and development and salaries and wages are closely linked in driving profitability among
consumer goods firms. Firms that invest in improving employee skills also tend to offer competitive
compensation packages, reflecting an integrated human capital strategy. From a managerial perspective, this
highlights that both forms of human capital investment work synergistically to enhance productivity and
profitability rather than functioning as isolated factors.
Table 4: Variance Inflation Factor Test of Variables
Variable
Tolerance
VIF
T&D
.162
6.183
S&W
.160
6.251
AT
.681
1.468
LIQ
.550
1.818
Source: Researcher’s computation (2025)
Regression Analysis
The panel-corrected standard error (PCSE) regression with fixed effects represents the cornerstone of the
econometric analysis examining how human capital expenditure influences profitability. The model
demonstrates exceptional explanatory power, with an R² of 0.9941 and an adjusted R² of 0.9933, indicating
that approximately 99.3% of the variation in ROA is explained by the included variables and firm-specific
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intercepts. The F-statistic of 1297.08 (p = 0.0000) confirms the joint significance of all regressors at the
highest level. These metrics underscore the model’s strong fit, particularly when firm-level fixed effects absorb
time-invariant differences such as brand equity, management quality, or geographic advantages. The Hausman
test (χ² = 22.39, p = 0.00002) strongly rejects the null hypothesis that random effects are consistent, justifying
the use of fixed effects. This implies that unobserved firm-specific factors are correlated with the regressors,
and failing to control for them would bias estimates. The Likelihood Ratio (LR) test for heteroskedasticity
(193.23, p = 0.0000) confirms the presence of groupwise heteroskedasticity, validating the use of PCSE over
standard OLS, which would produce inefficient and biased standard errors. Thus, the reported standard errors
(in parentheses) and p-values (denoted by {}) are robust to cross-sectional dependence and time-varying
variances, enhancing the reliability of inference.
The coefficient of T&D is positive, highly significant, and economically large. A one-percentage-point
increase in T&D expenditure as a share of total expenditure is associated with an 18.42 percentage point
increase in ROA, holding all else constant. This effect is not only statistically robust but also practically
transformative. Given that the mean T&D ratio is only 0.41% (from descriptive statistics), even modest
increases say, from 0.4% to 0.6% would theoretically boost ROA by over 3.7 percentage points, a substantial
leap in a sector averaging 7% ROA. This finding provides strong empirical support for human capital theory,
particularly the knowledge-based view of the firm. Investments in training enhance employee skills,
adaptability, and innovation, translating into operational efficiency, product quality, and market responsiveness
key drivers in Nigeria’s competitive consumer goods landscape. The magnitude suggests that T&D acts as a
strategic lever, amplifying asset productivity far beyond its cost.
Surprisingly, the coefficient of S&W is negative and statistically significant at the 1% level. A one-percentage-
point increase in S&W ratio is associated with a 1.35 percentage point decrease in ROA. This counterintuitive
result challenges efficiency wage theory and appears to contradict the strong positive bivariate correlation (r =
0.750). However, multicollinearity diagnostics provide the key to reconciliation. Despite VIFs of ~6.2 for both
T&D and S&W, the fixed effects model combined with PCSE successfully parses their joint influence. The
negative S&W coefficient likely reflects a suppression effect: when T&D is controlled for, higher salary
intensity (without corresponding skill enhancement) signals cost inefficiency or overstaffing. Firms paying
high wages but underinvesting in training may suffer from low productivity per employee, eroding
profitability. In contrast, the positive T&D effect dominates when both are included, suggesting that training is
the value-adding component, while salaries alone may represent a drag unless paired with skill development.
The coefficient of LIQ is positive and highly significant, indicating that a one-unit increase in the current ratio
(e.g., from 1.3 to 2.3) is associated with an 8.14 percentage point rise in ROA. This powerful effect
underscores liquidity’s role as a financial enabler. Firms with stronger working capital positions can seize
growth opportunities, manage supply chain disruptions, and avoid costly short-term borrowing all critical in
Nigeria’s volatile economic environment. Liquidity also likely facilitates human capital investment, acting as a
mediating channel between financial health and profitability. The coefficient of AT is negative and significant
at the 5% level. A one-percentage-point increase in fixed assets to total assets reduces ROA by 0.039
percentage points. Though small in magnitude, this suggests that over-reliance on tangible assets may hinder
profitability in this sector. Consumer goods firms competing on speed, branding, and flexibility may find
heavy fixed asset bases inflexible and capital-intensive, tying up resources that could be deployed more
productively elsewhere (e.g., marketing or R&D). This aligns with the weak correlation between AT and ROA
(r = 0.073, insignificant). Constant negative intercept, significant within the fixed effects framework, reflects
the baseline ROA when all regressors are zero adjusted for firm-specific effects. Its interpretation is limited but
confirms the model’s structural validity.
Table 5: Panel-Corrected Standard Error Regression Results
Variable
Fixed Effect Model
C
-2.935671*
(0.603235)
{0.0000)
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T&D
18.42254
(2.730993)
{0.0000}
S&W
-1.350215 *
(0.421910)
{0.0016}
AT
-0.039063
(0.015486)
{0.0125}
LIQ
8.138665
(0.716848)
{0.0000}
R
2
0.994092
Adjusted R
2
0.993326
F-statistic
1297.080
Prob(F-stat)
0.000000
Heteroskedasticity LR Test
193.2301
Prob(Heteroskedasticity)
0.000000
Hausman Test
22.390139
Prob(Hausman Test)
0.00002
Source: Researcher’s computation (2025) * sig @ 5%, *( ) standard error { } p-values.
DISCUSSION OF FINDINGS
The strongly positive and economically significant effect of T&D on ROA (β = 18.42, p < 0.001) aligns
unequivocally with theoretical expectations and several prior studies. (Makgata & Ngwakwe, 2017) found a
positive correlation between T&D and profitability, arguing that enhanced employee skills drive productivity
and consequently financial performance. Similarly, (Kinuthia, 2020) demonstrated that training investments
yield productivity gains exceeding wage increases, creating a net profitability surplus for firms. The current
study’s magnitude—where a one-percentage-point increase in T&D expenditure ratio boosts ROA by over 18
percentage points far exceeds typical effect sizes but is plausible given the low baseline T&D intensity (mean
= 0.41%). This suggests that Nigerian consumer goods firms operate in a human capital-constrained
environment, where marginal investments in skill development generate outsized returns due to diminishing
marginal costs of inefficiency. The result also resonates with (John & Roseline, 2023) who reported a
significant positive influence of aggregated human capital on ROA (β = 0.520, p < 0.001) in a similar sector
and sample frame. However, the current study’s disaggregation of T&D from S&W reveals that training is the
primary driver of this positive effect, a refinement absent in John & Roseline ‘s composite measure.
In contrast, the negative and significant effect of S&W on ROA (β = -1.35, p = 0.0016) presents a striking
divergence from several studies and initial bivariate correlations (r = 0.750). (Hasan ul & Naeem, 2022) found
that staff cost positively affects financial performance in Pakistan’s textile sector, while (Okere & Igba 2023)
reported a non-significant but positive relationship between salaries and wages and financial performance in
Nigerian manufacturing firms. (Nduka, Mark & Idayat, 2024), using a similar consumer goods sample,
concluded that overall human capital expenditure has a weak and insignificant effect on performance. These
discrepancies are reconciled through the lens of multicollinearity and model specification. The current study’s
inclusion of both T&D and S&W in a multivariate fixed effects framework coupled with PCSE to address
heteroskedasticity successfully isolates the conditional effect of salaries. When T&D is controlled for, higher
S&W intensity reflects cost inefficiency, overstaffing, or wage inflation without skill complimentary, eroding
profitability. This suppression effect explains why S&W appears beneficial in bivariate or aggregated models
but detrimental when training is accounted for. (Hasan ul & Naeem 2022) positive staff cost effect may thus
capture firms where high wages are paired with skill development, while Okere & Igba, s non-significance
reflects manufacturing’s different labor dynamics (e.g., lower skill intensity).
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The negative coefficient on Asset Tangibility (AT) (β = -0.039, p = 0.0125) and strongly positive effect of
Liquidity (LIQ) (β = 8.14, p < 0.001) further contextualize the findings. The liquidity result supports (Hasan ul
& Naeem, 2023), who implicitly link financial flexibility to human capital deployment. High liquidity enables
sustained T&D investment even during economic shocks (e.g., Nigeria’s 2020 recession), amplifying its
profitability impact. The negative AT effect suggests that capital-intensive structures constrain agility in a
sector where consumer preferences shift rapidly, reinforcing the primacy of human over physical capital.
Critically, Nduka, Mark & Idayat, despite using nearly identical data (20 firms, 2010s–2020s) found human
capital expenditure insignificant. This contradiction likely stems from aggregation bias: combining T&D and
S&W into a single variable masks their opposing effects. The current study’s disaggregation, supported by VIF
diagnostics (6.18 and 6.25), demonstrates that lumping human capital components obscures critical
heterogeneity. Similarly, Hasan ul & Naeem ’s finding that number of employees negatively affects
performance aligns with the current S&W result: both suggest that scale without skill erodes efficiency.
The policy and managerial implications are sharpened by these comparisons. While (Nduka, Mark & Idayat,
2024). and (Okere & Igba, 2023) recommend technical skill acquisition, the current findings provide
quantitative urgency: a 0.2 percentage point increase in T&D could offset a 2.7 percentage point S&W
increase in profitability drag. (John & Roseline 2023) call for human capital disclosure in integrated
reporting is validated, but the results demand granular reporting of T&D versus compensation to guide investor
scrutiny. The current analysis resolves apparent contradictions in the literature by demonstrating that not all
human capital expenditure is created equal. Training and development emerges as a high-yield strategic asset,
while salaries and wages, in isolation, function as a cost liability. This dichotomy unobserved in aggregated
studies underscores the necessity of disaggregated modelling in human capital research. In Nigerian consumer
goods firms, the path to sustained profitability lies not in wage escalation but in targeted, measurable
investments in workforce capability, supported by liquidity and unencumbered by excessive fixed asset
burdens.
CONCLUSION AND RECOMMENDATIONS
This study concludes that human capital expenditure significantly influences profitability, but critically, not all
components contribute equally. T&D strongly enhances ROA, while S&W diminishes it in isolation. The
results reconcile apparent contradictions in prior literature by showing that aggregation masks opposing effects
training creates value, but wages without skill enhancement represent inefficiency. In Nigeria’s consumer
goods sector, strategic investment in workforce capability, supported by financial flexibility, is the true driver
of sustainable profitability.
Hence, it is recommended that given the exceptionally high return on T&D (18.42 percentage points in ROA
per percentage point of expenditure), management should reallocate budgetary resources from general wage
increases to structured, measurable training programs. Firms should implement skill gap assessments, technical
and leadership development initiatives, and digital transformation training to maximize productivity gains. A
modest increase in T&D intensity from the current mean of 0.41% to 0.6% could yield over 3.7 percentage
points in ROA, far outweighing the cost.
There is need for the accounting profession to reinvent itself. This is because of the inherent deficiencies of
conventional accounting which as failed to recognize the knowledge acquired by organization as non-current
assets. Therefore there is need for more elaborate platform of financial reporting that could capture knowledge
and other intellectual capital components.
Also, Managements of consumer goods companies should come up with an enabling organisation structure for
qualified, experienced and skilled employees to fully utilise their potentials and thus reallocate funds from
wages to training in the area of product differenciation, E-commerce delivery services, logistics for higher
production and delivery of finished goods. This will enable the organisation to achieve higher profitability.
Because the higher the human capital efficiency, the greater the profitability.
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