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Macroeconomic Variables as Determinants of Agricultural Exports in
Nigeria
Aminat A. Amunigun, Jacob. O. Oluwoye
Department of Urban and Regional Planning Alabama A & M University Normal, Alabama 35762
United States
DOI:
https://dx.doi.org/10.47772/IJRISS.2025.910000170
Received: 30 July 2025 2025; Accepted: 07 August 2025; Published: 06 November 2025
ABSTRACT
Agricultural exports in Nigeria have been adversely affected by fluctuations in macroeconomic indicators.
Insufficient private agricultural investment and limited public expenditure directed toward the sector have
resulted in inadequate productivity and suboptimal export performance. This study investigates the
macroeconomic determinants of agricultural exports in Nigeria. A multiple regression model is specified, with
agricultural exports (as a percentage of total merchandise exports) as the dependent variable. The independent
variables are national output (economic growth rate), inflation rate, interest rate, exchange rate, and tariff rate.
The analysis employs descriptive statistics, correlation, stationarity, and cointegration tests. After confirming
the absence of multicollinearity, heterogeneity, autocorrelation, and nonstationarity in the time series data, the
variables are deemed suitable for regression analysis. The model is estimated using ordinary least squares, and
the results are interpreted at the 5% significance level. The findings indicate that all macroeconomic indicators,
except the tariff rate, significantly influence agricultural exports. It is recommended that Nigerian policymakers
reassess the effects of macroeconomic policies on the country's external balance, with particular attention to
agricultural exports.
Keywords: agricultural exports, macroeconomic variables, multiple regression, Nigeria
INTRODUCTION
Over the past three decades, the proportion of Nigeria's agricultural exports within total merchandise exports
has declined from 1.45% to 0.43% (National Bureau of Statistics, 2023). This decline underscores the need for
effective strategies to revitalize Nigeria's agricultural output to satisfy foreign demand (Voice of Nigeria, 2023).
Such strategies require a robust empirical understanding of the determinants of agricultural exports (Abdullahi
et al., 2021; Oyetade et al., 2020). Accordingly, this paper analyzes the factors influencing the volume and
direction of agricultural exports in Nigeria. Although this objective has been addressed in previous literature,
limited attention has been given to the impact of macroeconomic variables on the supply of agricultural exports
from Nigeria. This study, therefore, examines five macroeconomic variables; national output, inflation rate,
interest rate, exchange rate, and tariff rate that are primarily shaped by national policies and events, as
determinants of agricultural export volume.
The rationale for including these macro variables is hinged on the premise that there is mixed evidence of their
influence on agricultural exports. For example, while the national output positively influences the agricultural
exports (Osabohien et al., 2019), there is a crowding-out phenomenon such that the elevated interest rates result
in lower investment in goods and services, including the tradables, causing exports to fall (Nwosa, 2021). In
clear perspectives, monetary tightening (whereby the benchmark interest rates are increased) has been
persistently pursued by the Central Bank of Nigeria (CBN). Consequently, most farmers lament little access to
loanable funds (Osabohien et al., 2019). Where such loans are available, the huge borrowing costs have eroded
the intended gains from them (Nwosa, 2021). Moreover, where the interest rates are low, the political economy
is arranged to dissuade farmers from long-term focus on boosting their productivity (Akinbile et al., 2023). The
unfolding events around the CBN's Anchor Borrowers Programme offer an instance of the stifled terrain of
agricultural exports, with the CBN's policy playing a huge drag role (Akinbile et al., 2023). Furthermore,
exchange rate depreciations are generally expansionary in output and exports (Abolagba et al., 2017). This is
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because, as the domestic currency loses value against the foreign currency, it becomes cheaper for foreigners to
demand domestically produced goods, leading to a rise in exports. The effect of rising exports is rising national
output (Akinbode & Ojo, 2018). In this context, one would expect the persistent fall in the value of the naira
against the dollar to bolster Nigeria's agricultural exports. Nevertheless, available evidence does not suggest this
(Awolaja & Okedina, 2020). Falling agricultural exports have instead been associated with naira depreciations.
Also, rising inflation in Nigeria could incentivize the country's agricultural exports to increase. Again, this
remains to be validated empirically. Finally, the Nigerian government is known to practice a protective trade
policy for its agricultural industries, implying that the movements of tariff rates might shed light on the
movement of agricultural exports. Taking these factors together, this study analyses the macroeconomic
determinants of agricultural exports in Nigeria.
LITERATURE REVIEW
Extensive evidence in the literature identifies agricultural exports as a key determinant of economic growth.
However, this study examines the reverse relationship. Akinkunmi (2017), in an analysis of Nigeria's economic
growth and its determinants, identified output growth as a benchmark variable intersecting with other
macroeconomic indicators. The study linked developments in Nigeria's agricultural sector to the sector's
significant contribution to GDP, suggesting that economic growth tends to benefit its primary drivers.
Consequently, since agricultural exports do not lead Nigeria's economic growth, the agricultural sector derives
limited benefits from overall economic expansion (Akinkunmi, 2017). During the 2016 recession, which
disrupted many economic activities, agriculture was identified as the most resilient sector. Although agriculture
contributes approximately a quarter to Nigeria's GDP, economic growth does not significantly enhance
agricultural exports (Akinkunmi, 2017). This observation was later supported by Osabohien et al. (2019) and
Abdullahi et al. (2021). Okafor and Isibor (2021) further examined the effects of exchange rate, inflation rate,
and interest rate on the development of Nigeria's agricultural sector, with a focus on exports. Using annual time
series secondary data and ordinary least squares (OLS) analysis, they found that the exchange rate had a positive
effect on agricultural exports, while inflation had a significant negative impact. Interest rates were found to be
insignificant. Based on these results, Okafor and Isibor (2021) recommended that monetary authorities
implement policies to reduce inflationary pressures. These findings align with those of Udah et al. (2015), who
investigated the role of monetary instruments and infrastructure in agricultural development. However, Udah et
al. (2015) emphasized the importance of agricultural credit and monetary expansion to boost productivity and
exports, contrasting with Okafor and Isibor's (2021) recommendations. Oriavwote and Eshenake (2017)
employed error correction modelling (ECM) and Granger-causality techniques to assess the impact of
agricultural productivity and the exchange rate on exports. Their results indicated that agricultural output is the
primary driver of agricultural exports, suggesting that policies aimed at enhancing exports should focus on
increasing output. Furthermore, agricultural output can serve as a significant source of economic growth, as it
constitutes a component of national output. Additionally, Oriavwote and Eshenake (2017) found that exchange
rate depreciation can stimulate agricultural exports.
According to the authors, exchange rate depreciations (or devaluations) expand the exporting country's trade
openness and encourage foreign importers of the locally made goods. This argument is supported by the extant
theoretical propositions of the J-curve hypothesis (Trofimov, 2020). Similar results have been reported by David
et al. (2014) using the time series data that were sourced from the Ghanaian economy. The effect of trade
openness and tariff rate on agricultural exports was brought into the limelight by Tsaurai (2022) in their analysis
of the growth of the agricultural sector in the middle-income countries in Africa (inclusive of Nigeria), with
financial development included as the intervening variable. The analysis was carried out under the dynamic
generalized methods of moments (GMM) approach. According to Tsaurai (2022), the dynamic GMM and the
pooled OLS results indicated that the influence of economic growth on agricultural sector growth was
significantly negative. Also, fixed, random, and pooled effects showed that trade openness and tariffs on the
growth of the agriculture sector were significantly positive. This was facilitated by the growing financial
development in the sampled African countries (Tsaurai, 2022). More recently, Okuduwor et al. (2023) assessed
the significance of tariffs and trade openness as the factors linking agricultural exports to economic growth.
Their results were similar to those of Tsaurai (2022). However, while the former employed GMM techniques on
the panel time series data, the latter performed the ARDL analysis on the single-country time series data. Aside
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from this, the two studies were the same regarding the objectives, variables, and conclusions. Previously, Ebi
and Ape (2014) evaluated the supply response of seven agricultural export commodities from Nigeria between
1970 and 2010. An econometric analysis, which the ECM anchored, was employed to estimate export supply
behaviors of the seven commodities, including cocoa, benniseed, rubber, palm oil, groundnut, cottonseed, and
soybeans. The authors found that the response of export supply to changes in relative price was positive and
significant for five commodities, except cocoa and soybeans. Also, output growth and more investment credit
to the agricultural sector positively and significantly influence the export supply of the commodities. Other
identified supply factors were the road network transporting agricultural produce and communication,
facilitating trade. Mesike et al. (2010) had earlier made similar conclusions.
MATERIALS AND METHODS
This research is designed with an ex-post facto approach so that the determinants of Nigeria's agricultural exports
are analysed and discussed. These determinants are specifically related to the macro and trade variables such as
the national output, inflation rate, interest rate, exchange rate, and tariff rate. A multiple regression model was
adopted to guide the analytical framework in capturing these variables' individual and joint impact. The baseline
model is specified as: Where AGREXP is agricultural exports, NATOUT is national output (which is proxied by
the gross domestic product), INFRATE is inflation rate, INTRATE is interest rate, EXCRATE is exchange rate,
and TARRAT is tariff rate. In econometric terms, the model is specified as: Where the AGREXP is the dependent
variable and other variables are independent variables. The variables retain their earlier definitions. The
parameters – measure the changes in the dependent variable when the independent variables change by one unit.
The parameter is the constant of the model. is the error term which is normally distributed with zero mean (its
value converges to zero) and constant variance – this is important to produce unbiased, efficient estimates. The
analytical technique began with cleaning the data in a spreadsheet. After this, the descriptive statistics of the
variables were discussed. This was followed by a correlational analysis to explore the inter-relationships among
the variables. Then the regression model was analysed using the ordinary least squares (OLS) technique. The
annual time series data on these variables were sourced from the World Development Indicators of the World
Bank. The data covered the 30 years 1992-2022. The unit of measurement of all the variables is percentage,
except the national output in billions of dollars.
RESULTS AND DISCUSSION
Descriptive Analysis
The descriptive statistics of the variables are presented in Table 1. The average value of agricultural exports (as
a fraction of total export of goods and services) over the sample period is 0.96% ± 1.68%. Only about 1% of
total merchandise exports are traceable to the agricultural sector. This development is partly blamed on the
Nigerian government's switch from agricultural to oil exports in the 1970s. The standard deviation is noteworthy
as it indicates a wide spread in the sample distribution. This is further supported by the wide gap between the
minimum value (0.01%) and the maximum value (7.27%) of agricultural exports. These statistics suggest that
the supply of agricultural exports from Nigeria is prone to high volatility. The mean national output of the
Nigerian economy is $326billion. A perspective is generated on this value if it is noted that Nigeria is the largest
economy in Africa. While the standard deviation ($ 141billion) is considerably low, the maximum value of $535
billion relates that the recent performance of the Nigerian economy is rather unimpressive – the economy
recently witnessed periods of recessions and slow growth.
Table 1: Descriptive statistics of the variables
AGREXP
NATOUT
INFRAT
INTRAT
EXCRAT
TARRAT
Mean
0.96
3.26E+11
18.59
18.49
155.43
22.72
Maximum
7.27
5.35E+11
72.84
31.65
425.98
92.88
Minimum
0.01
1.55E+11
5.39
11.48
17.30
11.95
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Standard Deviation
1.68
1.41E+11
16.49
3.94
114.75
15.56
Skewness
2.81
0.11
2.11
1.19
0.82
3.07
Source: Author’s Data Analysis (2025)
The inflation rate is currently averaged at 18.59% ± 16.49%. This describes Nigeria as having inflationary
pressures. Unlike many advanced economies where inflation is targeted at 2%, the Nigerian policymakers have
not particularly considered high prices of consumer goods and services as an important macroeconomic problem
– this assertion is linked with the deviation of the CBN from its hitherto target of a single-digit inflation. Yet,
the standard deviation of 16.49% points to inflation being characterized by large fluctuations in Nigeria. The
interest rate shares the same mean value as the inflation rate, but with a lower standard deviation (3.94%). The
average exchange rate is N155/$1. For anyone conversant with macroeconomic events in Nigeria, the exchange
rate currently tilts around N1000/$1 in the unofficial parallel markets. However, this current event is not captured
in this study for two reasons. First, the end-year of the time series used for the empirical analysis is 2022, when
the exchange rate was at its maximum (N425/$1). Second, no official source has reported the aggregated
exchange rates in the country until this paper was sent for publication. Nigeria also pursues an unstable trade
policy. This is reflected by the standard deviation of the tariff rate (15.56%) being close to its mean value
(22.72%). The tariff rate on the import of raw materials and primary inputs is included in this study because the
literature has established that the tariff regime is a driver of the importing country's exports. In practice, countries
institutionalize the tariff regime in response to the trade policy mechanisms that other countries have pursued
(Okuduwor et al., 2023). All the variables are skewed to the right, meaning they have positive trends. As they
have been growing over time, this result has disparate interpretations. While the growth of agricultural exports
and national output is desirable because it indicates impressive performance of the economy, the growth of the
inflation rate, interest rate, exchange rate, and tariff rate is unwelcome due to their contractionary impact on
economic activity. For example, higher inflation or interest rates diverts resources from productive purposes.
Similarly, a higher tariff rate may result in a counterreaction leading to lower foreign demand for domestic
goods.
Correlation Analysis
As reported in Table 2, the correlation coefficients among the variables are pro-intuitive. Agricultural exports
and national output are positively correlated at 0.17. This follows the theoretical argument that exported output
is first produced at home and counted as part of the domestic GDP. Also, domestic inflation and agricultural
exports are negatively associated at -0.06. When the consumer price index of a country is elevated, demand for
the country's exports is depressed. This agrees with the extant submission in the literature (for example, Udah
et al., 2015; Ebi & Ape, 2014; Mesike et al., 2010). The negative link between tariff rate and agricultural exports
(-0.18) is similarly explained by the fact that tariffs make domestic goods more expensive, resulting in lower
exports. Nevertheless, the negative relationship between the exchange rate and agricultural exports is
counterintuitive. Given that exchange rate is quoted as naira (N) per dollar ($) in this paper, one would interpret
an increase as naira depreciation and a decrease as naira appreciation against the dollar. In the standard economic
analysis, an exchange rate depreciation makes exports cheaper, leading to higher demand for exports. Thus, the
persistent fall in the value of the naira against the dollar is expected to be positively correlated with the
agricultural exports (Bawa et al., 2018), but this was not the case, as given in Table 2. The subsequent section
will generate More informed empirical arguments on this relationship. The coefficients among the other
variables satisfy the theoretical links and intuitive arguments.
Table 2: Correlation coefficients among the variables
AGREXP
NATOUT
INFRAT
INTRAT
EXCRAT
TARRAT
AGREXP
1.00
NATOUT
0.17
1.00
INFRAT
-0.06
-0.44
1.00
INTRAT
-0.11
-0.72
0.51
1.00
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EXCRAT
-0.08
0.88
-0.38
-0.68
1.00
TARRAT
-0.19
-0.61
0.75
0.49
-0.48
1.00
Source: Author’s Data Analysis (2025)
Stationarity Analysis
A stationarity analysis was conducted to determine the likelihood of mean reversion in the variables included in
the present study. This analysis was hinged on Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests.
The use of dual tests was focused on ascertaining consistency in the stationarity properties of the variables. In
the context of this study, a series is said to be stationary if it has constant mean, constant variance, and constant
covariance (Traore & Diop, 2022). Nevertheless, following Traore and Diop (2022), constancy in mean is
enough to indicate constancy in variance and covariance. Furthermore, the PP test captures both constancy in
mean and variance, providing toolbox for verifying the ADF stationarity report mainly identifies constancy in
mean (Fowler et al., 2024). The statistical ADF and PP values were obtained at constant and linear trend
specifications. These are contained in Table 3. The corresponding critical values are presented in Table 4.
Comparing statistical and critical values shows that all variables are stationary at levels. That is, they are all I
(0). This stationarity provides credence to use OLS as an appropriate estimation technique in the present study.
According to Fowler et al. (2024), time-series variables integrated of order 0 tend to exhibit the same
characteristics in the short and long run. By implication, the short-run properties of variables discussed in this
study are extended over the long run. In other words, there is no deviation of behaviour between the short run
and the long run, suggesting that using short-run models such as the autoregressive distributed lag (ARDL)
model or error correction model (ECM) in this study is superfluous.
Table 3: ADF and PP Statistics
ADF statistic
PP statistic
Order of integration
AGREXP
-4.2345
-4.4592
I(0)
AGREXP (-1)
-8.5433
-8.6592
NATOUT
-4.4590
-4.4409
I(0)
NATOUT (-1)
-9.4562
-9.4021
INFRAT
-4.7458
-4.6672
I(0)
INFRAT (-1)
-8.6439
-8.4722
INTRAT
-4.1295
-4.0098
I(0)
INTRAT (-1)
-9.4981
-9.4881
EXCRAT
-5.7632
-5.0879
I(0)
EXCRAT (-1)
-10.3208
-10.1125
TARRAT
-4.7766
-5.5587
I(0)
TARRAT (-1)
-9.5883
-10.4344
Source: Author’s Data Analysis (2025)
Cointegration Test
The Johansen cointegration test further strengthened the description of the variable's stability properties. As
Yussuf (2022) discussed, cointegration is invoked to establish a long-run relationship among all variables in the
model. In this study, while the zero-order integration reported in the preceding section is an indicator of strong
long-run convergence among the variables, the computed cointegration test strengthens this indication. This
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result is presented in Table 5. With the Johansen (statistical) values being greater than critical values only at
none and at most one specification, it was obtained that there are two cointegration equations. This is consistent
between the eigenvalue and trace statistical values. Thus, reliable long-run relationships exist in the time series
estimated in this study.
Table 4: Asymptotic Critical Values of ADF and PP
Level of significance
Form of test
Levels
First differences
1%
ADF
-4.2528
-4.2627
PP
-4.2529
-4.2627
5%
ADF
-3.5485
-3.5530
PP
-3.5485
-3.5530
10%
ADF
-3.2071
-3.2096
PP
-3.2071
-3.2096
Source: Author’s Data Analysis (2025)
Table 5: The Johansen cointegration test
Hypothesized number of cointegrating equations
Eigenvalue
Trace statistic
Critical value
p-value
None
0.85
115.56
40.17
0.00
At most 1
0.82
52.88
24.28
0.00
At most 2
0.24
8.34
12.32
0.33
At most 3
-0.12
0.66
4.13
0.61
Source: Author’s Data Analysis (2025)
Regression Analysis
The regression coefficients are telling. As summarized in Table 6, an increase in the national output by $1 billion
leads to an increase in agricultural exports by about 0.017%. This result echoes the assertion that a pathway to
bolster the export of agricultural output in Nigeria is through growth trajectories of the national economy. After
all, the agricultural sector is one of the most significant components of Nigeria's GDP, currently sharing around
25% of the overall economic activity. Since agricultural raw materials exported are locally produced, the logic
is that an expansion of the national output will necessarily improve agricultural exports. This submission
supports the earlier findings in the literature (such as Abdullahi et al., 2021; Osabohien et al., 2019; Akinkunmi,
2017). However, it was found that a rise in inflation by 1% would lead to an increase in agricultural exports by
0.012%. Like the behavior of the national output, the inflation rate has an expansionary effect on the volume of
exported agricultural goods. This result can be justified by the reasoning that prices of 10 agricultural raw
materials are relatively low on the world market, implying that foreign importers might shrug off the news that
Nigeria's inflation rate has increased. It is the case that, no matter the rise in agricultural exports, their prices are
still low on the world markets. In addition, Nigeria is not an example of hyperinflation, so foreign importers
might be less worried about buying Nigeria-made agricultural goods and services.
Table 6: Regression estimates
Dependent variable: AGREXP
Independent variable
Coefficient estimate
Standard error
t-statistic
NATOUT
1.17E-11
3.87E-12
3.026*
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INFRAT
0.012
0.026
0.468*
INTRAT
-0.03
0.051
2.534*
EXCRAT
-0.02
0.005
2.767*
TARRAT
-0.01
0.029
1.463**
R-squared = 0.668;
Adjusted R-squared = 0.489;
F-stat =37.18;
Log-likelihood = 54.78
* Implies the coefficient estimate is significant at 5%
** implies the coefficient estimate is not significant at 5%
Source: Author’s Data Analysis (2025)
In contrast, increases in other independent variables (interest rate, exchange rate, and tariff rate) hurt agricultural
exports. Particularly, when the interest rate increases by 1%, agricultural exports are down by about 0.03%. This
result re-establishes the theoretical impact of changes in the interest rate on the real sector. When the central
bank increases the benchmark interest rate (or the federal funds rate), domestic investment crowds out because
the borrowing costs for investment purposes would inadvertently increase. Moreover, a similar increase in the
exchange rate reduces the agricultural exports by 0.02%. When the increase is in the tariff rate, the exports are
down by 0.01%. It follows that changes in macroeconomic variables determine the volume of agricultural
exports in Nigeria. While national output and inflation rate have expansionary effects, interest, exchange, and
tariff rates have contractionary effects on agricultural exports. As suggested by the t-statistics, the independent
variables are statistically significant at 5% except for the tariff rate. The R-squared shows that all the variables
jointly account for about 66.8% of the variation in the agricultural exports. While this is noteworthy, it
demonstrates that other determinants of agricultural exports differ from those included in this study. The F-stat
(37.18) indicates that the independent variables are jointly significant in having an exact impact on agricultural
exports. Finally, the log likelihood (54.78) shows that the coefficient estimates are typically distributed, such
that the mean values are valid for most of the series in the population sample. This confirms that the estimated
model represents a good fit of the population sample.
CONCLUSION AND RECOMMENDATION
This Study Revalidates the Macroeconomic Determinants of Agricultural Exports in Nigeria by Specifying and
Estimating a Multiple Regression Model That Includes five Macroeconomic Aggregates: National Output,
Inflation Rate, Interest Rate, Exchange Rate, and Tariff Rate. The Findings Indicate that these Macroeconomic
Indicators Have Not Been Effectively Leveraged by Nigerian Policymakers to Enhance Agricultural Exports.
Although GDP Demonstrates Expansionary Effects on Agricultural Exports, The Current Structure of The
Nigerian Economy Prioritizes the oil and Service Sectors Over Agriculture. The Oil Sector Contributes
Approximately 10% To Nigeria's GDP But Accounts for Nearly 90% of Total Exports, While the Service Sector
Represents Up To 55% Of Overall Economic Output. Without A Strategic Shift in Government Focus Toward
the Agricultural Sector, Significant Improvement in Agricultural Exports is Unlikely. Therefore, It Is
Recommended That the Nigerian Government Diversify Its Revenue Sources to Include Agricultural Export
Gains. Historical Evidence Shows That Agriculture Was the Foundation of The Nigerian Economy During the
First Decade of Independence (1960-1970). Rather Than Maintaining a Mono-Cultural Focus on The Oil Sector,
Policymakers Should Encourage Both Domestic and Foreign Investment in Agriculture. This Approach Offers
the Most Effective Means of Strengthening the Country's External Balance and Increasing Agricultural Exports.
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