Examining the Supply Response and Production Trends of Ginger in Benue and Kaduna States, Nigeria.

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Examining the Supply Response and Production Trends of Ginger in Benue and Kaduna States, Nigeria.


This study presents an analysis of the supply response and trends in ginger production in Benue and Kaduna States, Nigeria. A multistage sampling technique was utilized, collecting cross-sectional data from 359 respondents through structured questionnaires, along with time series data spanning from 1979 to 2018. Descriptive statistics, the Autoregressive Distribution Lag Model (ARDL), and the grafted polynomial model were employed in the study.

The findings revealed that ginger farming was predominantly carried out by males (80.5%), with a majority (83.3%) of them being married, and an average household size of 8 persons. Approximately 62.4% of ginger farmers attained secondary education at an average age of 31 years. The farmers exhibited considerable experience in their practices, with an average farm size of 1.0 hectare.

The results from the ARDL model indicated that ginger output responded positively to changes in land area and price at the 1% significant level in the long run, with coefficients of 0.316 and 1.452, respectively. In the short run, ginger productivity dprod(-1) and dprod(-2) significantly and positively influenced ginger productivity, with coefficients significant at the 1% level. The current land area, as well as its first and second lags, also had positive effects on ginger production in the short run, with coefficients significant at the 1% level. Similarly, the current price and its first lag positively influenced ginger production at the 1% significant level, while the second lag of price negatively affected production at the 10% significant level. The error correction term (ECT) estimates had coefficients of -0.884, -0.929, and -0.124 in Benue, Kaduna, and the pooled sample, respectively, implying that approximately 88%, 92%, and 12% of any disequilibrium level of ginger production during previous years would be corrected in subsequent years.

The observed trend in ginger production showed fluctuations between 1980 and 1984, maintaining a slow rise from 1985 to 1990, experiencing a structural break and sharp drop between 1999 and 2000, and witnessing significant increases and declines between 2009 and 2018. These variations were attributed to price fluctuations and government agricultural policies. The Quadratic-Quadratic-Linear function’s ex-ante and ex-post forecasts for the pooled sample predicted a future decline in ginger output, with root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) of 65,658.12, 49,729.86, and 16.386, respectively.

Inadequate rainfall, weed infestation, disease incidence, high cost of seedlings, lack of improved seed varieties, insufficient access to credit and loans, and inadequate market extension services were identified as significant constraints impeding ginger production in the study area. Considering the predicted decline in ginger production, it is recommended that credit facilities and farm inputs should be made readily available, and ginger farmers should be equipped with modern production techniques and climate change adaptation strategies through effective extension services. Additionally, government regulation of ginger prices as a potential export commodity and flexible land tenure policies to enhance land access for ginger production are proposed.

Examining the Supply Response and Production Trends of Ginger in Benue and Kaduna States, Nigeria.

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