Controlling agricultural product price volatility: An empirical analysis from Cameroon

doi:10.1016/j.regsus.2025.100215

Abstract

Abstract:

Motivated by a significant impact of price volatility on food security and economic stability in Cameroon, this study aims to understand the factors influencing agricultural product price volatility (APPV) and formulate effective policies for mitigating its negative impact and promoting sustainable economic growth. Specifically, this research used the autoregressive distributed lag-error correction model (ARDL-ECM) to analyse the impact of agricultural productivity, agricultural product imports, population, temperature variation, gross domestic product (GDP) per capita, and government expenditure on APPV based on the annual data from 2000 to 2021. The ARDL-ECM estimation results revealed that agricultural productivity (β=4.901), agricultural product imports (β=1.012), population (β=13.635), and GDP per capita (β=2.794) were positively related to APPV, while temperature variation (β= -0.990) and government expenditure (β= -8.585) were negatively related to APPV in the long term. However, temperature variation had a positive relationship with APPV in the short term. Moreover, the Granger causality test showed that there were bidirectional causality of APPV with agricultural productivity and agricultural product imports, and unidirectional causality of APPV with population, temperature variation, GDP per capita, and government expenditure. The findings highlight the importance of public policies in stabilizing agricultural product prices by investing in agricultural research, improving access to agricultural inputs, strengthening farmer capacities, implementing climate adaptation measures, and enhancing rural infrastructure. These policies can reduce APPV, improve food security, and promote inclusive economic growth in Cameroon.

Key words: Agricultural product price volatility (APPV), Autoregressive distributed lag-error correction model (ARDL-ECM), Food security, Agricultural productivity, Climate change

Ivette Gnitedem KEUBENG, George Achu MULUH, Vatis Christian KEMEZANG. Controlling agricultural product price volatility: An empirical analysis from Cameroon[J]. Regional Sustainability, 2025, 6(2): 100215.

Figures/Tables 10

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References 61

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Variable	Abbreviation	Unit	Period	Source
Agricultural product price volatility	APPV	-	2000-2021	FAOSTAT (2024)
Agricultural productivity	AP	-	2000-2021	USDA ERS (2023)
Agricultural product imports	API	10⁹ USD	2000-2021	FAOSTAT (2024)
Population	POP	10⁷ persons	2000-2021	WDI (2024)
Temperature variation	TV	°C	2000-2021	FAOSTAT (2024)
Gross domestic product (GDP) per capita	GDP	USD/person	2000-2021	WDI (2024)
Government expenditure	GOVT	10⁹ USD	2000-2021	WDI (2024)

Variable	Mean	Standard deviation	Minimum	Maximum
APPV	1.085	0.489	0.220	2.600
AP	88.727	11.163	70.006	104.652
API (×10⁹ USD)	0.853	0.183	0.562	1.186
TV (°C)	0.872	0.283	0.230	1.290
GDP (USD/person)	1311.289	97.242	1137.625	1454.564
POP (×10⁷ persons)	2.050	0.380	1.510	2.720
GOVT (×10⁹ USD)	3.090	1.010	1.620	4.580

	lnAPPV	lnAP	lnAPI	lnPOP	lnTV	lnGDP	lnGOVT
lnAPPV	1.000
lnAP	0.461^**	1.000
lnAP	(0.031)
lnAPI	0.256	0.652^***	1.000
lnAPI	(0.250)	(0.001)
lnPOP	0.419^*	0.874^***	0.415^*	1.000
lnPOP	(0.052)	(0.000)	(0.055)
lnTV	-0.101	0.396^*	0.169	0.528^**	1.000
lnTV	(0.656)	(0.068)	(0.452)	(0.012)
lnGDP	0.359	0.736^***	0.388^*	0.769^***	0.608^***	1.000
lnGDP	(0.101)	(0.000)	(0.074)	(0.000)	(0.003)
lnGOVT	0.396^*	0.720^***	0.519^**	0.686^***	0.481^**	0.755^***	1.000
lnGOVT	(0.068)	(0.000)	(0.013)	(0.000)	(0.023)	(0.000)

Variable	ADF unit root test		PP unit root test		Stationary
Variable	I(0)	I(1)	I(0)	I(1)	Stationary
lnAPPV	-3.199^**	-	-3.190^**	-	I(0)
lnAPPV	(0.020)	-	(0.021)	-	I(0)
lnAP	-0.825	-3.496^***	-0.838	-3.473^***	I(1)
lnAP	(0.812)	(0.008)	(0.808)	(0.009)	I(1)
lnAPI	-2.182	-3.989^***	-1.755	-3.578^***	I(1)
lnAPI	(0.213)	(0.002)	(0.403)	(0.006)	I(1)
lnTV	-4.799^***	-	-2.651^*	-5.473^***	I(0)
lnTV	(0.000)	-	(0.083)	(0.000)	I(0)
lnGDP	-1.873	-3.123^**	-1.737	-3.098^**	I(1)
lnGDP	(0.345)	(0.025)	(0.412)	(0.027)	I(1)
lnGOVT	-1.907	-3.681^***	-1.806	-3.741^***	I(1)
lnGOVT	(0.329)	(0.004)	(0.378)	(0.004)	I(1)
lnPOP	-1.130	-3.958^***	0.954	-3.714^***	I(1)
lnPOP	(0.703)	(0.002)	(0.994)	(0.004)	I(1)

	Critical value						P-value
	10% significance level		5% significance level		1% significance level		P-value
	Lower bound	Upper bound	Lower bound	Upper bound	Lower bound	Upper bound	Lower bound	Upper bound
F-value	2.746	4.237	3.462	5.249	5.411	7.972	0.004	0.021
t-value	-2.523	-3.963	-2.956	-4.527	-3.900	-5.770	0.000	0.004
Decision	Reject		Reject		Inconclusive		-
F-statistic	6.644
t-statistic	-6.527