Modelling the impact of maize and sorghum production on Nigeria’s economic growth: An ARDL approach

Introduction

According to (Praburaj, et al., 2018; Pawlak and Kołodziejczak, 2020) [12,19] , agriculture is directly proportional to economic growth, development and industrialization, most especially among the developing nations of the world including Nigeria. Mgbakor et al. (2014) [20] , also said that no relevant development can take place in a developing country without the proper building of the agricultural sector as this will bring about adequacy in food production and decline in the governments' annual spending on food importation. It has been revealed that over 80% of the farmers in Nigeria are persistent farmers who cultivate few hectares of land, plant crops, and harvest but yet play a crucial role in the country's food security and yet remain poor (FAO, 2015; Mgbenka and Mbah, 2016) [21,22] . According to MA Zubair, S.O Adams, and KS Aniagolu (2022) [8] , the Nigerian government should make local products better to meet international needs so as to minimize total imports. Maize is an essential staple food crop in Nigeria where it plays a major role in the food basket of the country (Anderson et al., 2017) [23] . Maize is an important cereal crop occupying second place after rice in the diet of most households in Nigeria. It is a high yielding crop with so many uses ranging from food source in the human diet, a principal ingredient in livestock feed production and raw material to many agro-allied industries. In addition, maize is also employed in beer and starch production (IITA, 2007; Ogunniyi, 2011) [24,11] . Maize is majorly where carbohydrate is gotten from and also other nutrient elements like minerals, protein, vitamin B and iron. For there to be an invigorate rise of Nigeria's economy through an expansion in human limit improvement, the government need to increment monetary designation to the power area and instructive (SO Adams, MA Zubair, TG Olatunde-Aiydun, 2022) [8] . According to (Sadiq et al., 2013) [14] , human food needs and livestock feeds has caused a competitive demand for maize in Nigeria. Sorghum is one of the principal cereal crops mostly grown in Nigeria, and a very essential staple food but now is being replaced by other crops such as barley, wheat, rice and maize for the people. Tashkalma et al. (2010) [18] , submitted that this crop is one of the main source of energy and is the fifth major crop grown for human consumption in the world being surpassed only by corn, rice, and barley.

Materials and Methods

The study will utilize a quantitative approach to model the impact of maize and sorghum production on Nigeria's economic growth. The study will adopt an econometric technique to examine the relationships between maize and sorghum production and economic growth over time. The study employed a well-known approach by Pesaran et al. known as the Autoregressive Distributed Lag (ARDL) model.

Data collection

This study employs a secondary source of data. The yearly time series data are collected from the National Bureau of Statistics (NBS) covering 1960-2024.

Model specification

This study will focus on an ARDL model that captures the relationships between maize and sorghum production and economic growth. The autoregressive distributed lag (ARDL) model suggested by (Pesaran, Shin, 1999) and (Pesaran et al., 2001) [25,26] is adopted here. The agricultural products for this study are maize (MZ) and sorghum (SM).

The representation of the model specification is as follows: EG=𝜙(MZ,SM);𝜙 1 ,𝜙 2 <0

Model I: ARDL Model for Economic Growth (EG) and Maize (MZ)

Model II: ARDL Model for Economic Growth (EG) and Sorghum (SM)

. 3.2 reveals that the optimal lag lengths selected by the Akaike Information Criterion (AIC) are 10 lags for dmaize, 2 lags for dsorghum, and 1 lag for dgdp. This suggests that the dynamics of MAIZE prices require a longer memory compared to SORGHUM and GDP. The key result is the ECM(-1) coefficient, which indicates the speed at which the system returns to equilibrium after a shock. If the ECM(-1) coefficient is significant and negative, it implies that there is a short-run relationship between the variables, and the system adjusts towards the long-run equilibrium. In this case, the ECM(-1) coefficient is -1.120, and it is statistically significant with a p-value of 0.000145 (less than 0.01), indicating that there is indeed short-run adjustment in the relationship between maize production and economic growth. This suggests that the residuals are independent over time, satisfying an important assumption for time series regression.

Model III: ARDL Model for all Variables

Results and Discussions

Similarly, the Breusch-Pagan test for heteroskedasticity yields a Chi²(6) statistic of 10.625 with a p-value of 0.1007, indicating that the null hypothesis of homoskedasticity cannot be rejected. Therefore, the residuals exhibit constant variance, implying that the model does not suffer from heteroskedasticity problems. However, the Shapiro-Wilk test for normality reports a W statistic of 0.9582 with a p-value of 0.0385, which is below the 5% threshold. This result suggests that the residuals are not normally distributed. Although normality is desirable for small-sample inference, its violation does not necessarily invalidate the model, especially in large samples where the Central Limit Theorem provides some robustness. The Ramsey RESET test, used to detect model misspecification, produces an F-statistic of 3.6685 with a pvalue of 0.0323. Since the p-value is less than 0.05, there is evidence that the model may be misspecified, potentially due to omitted variables or an incorrect functional form. This indicates the need for caution when interpreting the model's results and suggests that further model refinement may be necessary. Finally, the ARDL Bounds Test for cointegration shows an F-statistic of 32.99, which is substantially higher than the critical values at the 1%, 5%, and 10% levels. This strongly confirms the presence of a long-run equilibrium relationship between the variables, justifying the use of the ARDL approach in this study. is positive but very small, with a marginally significant tvalue. This suggests that short-run fluctuations in GDP have a small but significant effect on changes in sorghum production. The lagged coefficients (Y.1 and Y.2 for past sorghum production) show a significant negative effect on the current economic growth, indicating that the effects of past agricultural performance may persist and hinder economic growth in the short run. The significant negative relationship between lagged sorghum production and GDP implies that changes in sorghum production from the previous periods may still have a lingering impact on economic performance. The long-run coefficients reveal that in the long term, an increase in sorghum production positively influences GDP. This suggests that over time, higher sorghum production contributes to economic growth. The long-run relationship between GDP and sorghum production (coefficient = -1.238) indicates that, over time, GDP has a negative effect on sorghum production. This could reflect structural shifts in the economy as GDP grows, potentially leading to a decline in agricultural sector reliance. 2 indicates that the model is generally stable over the sample period. The residuals fluctuate within the critical bounds at the 5% significance level, suggesting that the model's parameters remain stable over time. There is no clear evidence of structural breaks or instability, supporting the reliability of the ARDL model's estimates for both short-run and long-run analysis.

Conclusion

The study has provided valuable insights into the impact of maize and sorghum production on Nigeria's economic growth. Based on the results obtained, I therefore concludes that there is indeed short-run adjustment in the relationship between maize production and economic growth. There exist the presence of a long-run cointegration relationship among the variables maize production and economic growth. There is a short-run fluctuations in GDP which has a small but significant effect on changes in sorghum production. In the long-run, there is an increase in sorghum production that positively influences GDP, but over time, GDP has a negative effect on sorghum production.

Recommendations

Based on the findings of the study, the following recommendations are made; 1. Further research should be conducted to examine the impact of other agricultural commodities on economic growth in Nigeria. 2. Policymakers should provide support to maize and sorghum farmers, including access to credit, extension services, and market information 3. The government and private sector should increase investment in agriculture to improve productivity and efficiency. 4. Policymakers should formulate policies that promote the development of maize and sorghum subsectors.

Acknowledgement

AcknowledgementI acknowledge God Almighty for His infinite mercy to complete this research work.

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