ANALYSIS OF SUPPLY RESPONSE AND TREND OF GINGER PRODUCTION IN BENUE AND KADUNA STATES, NIGERIA

Abstract

This study analysed supply response and trend of ginger production in Benue and Kaduna States Nigeria. A multistage sampling technique was employed. Cross sectional data from 359 respondents were collected through structured questionnaire and time series data from 1979 to 2018 were also used for the study. Simple descriptive statistics, Autoregressive Distribution Lag Model (ARDL) and the grafted polynomial model were employed for the study. Male (80.5%) dominated ginger farming. (83.3%) were married with an average household size of 8 persons. (62.4%) attained the level of secondary education at an average age of 31 years. Ginger farmers were well experienced in their farm practices with an average farm size of 1.0 ha. The result of the ARDL model revealed that ginger output responded positively to land area and price change at 1% significant level in the long run with a coefficient of 0.316 and 1.452. Ginger productivity dprod(-1) and dprod(-2) were significant at 1% and positively influenced the productivity of ginger in the short run. The coefficients of the current (0.381), first (0.2598) and second (1.0256) lag of land area positively affect ginger production at 1% significant level in the short run. The short run coefficients for the current price (1.8518) and first lag of price (1.2059) positively influenced ginger production at 1% significant level. However, ginger production was negatively influenced by price in the second previous years at 10% significant level. The estimate of the error correction term (ECT) has a coefficient of -0.884, -0.929 and -0.124 in Benue, Kaduna and the pooled sample respectively. This implies that nearly 88%, 92% and 12% of any disequilibrium level of ginger production during the previous years will be corrected in the subsequent years in Benue, Kaduna and the States combined respectively. The observed trend in ginger production indicated that ginger output stood between the ranges of 180,000 to 200,000 metric tonnes from 1980 to 1984 and maintains a slow rise from 1985 to 1990. However, between 1999 and 2000 there was a structurer break and a sharp drop in ginger production. Ginger production increases from 455,660.55 to 503,001.12 metric tonnes between 2009 and 2010 and reaches a peak of 594,502.52 metric tonnes in 2015. However ginger production fell sharply from 56,000 to 27,000 metric tonnes between 2017 and 2018. These changes occurred either as a result of price variation or government agricultural policies. The result of the ex-ante and ex-post forecast of the Quadratic-Quadratic-Linear function for the pooled sample predicted a fall in ginger output in the future with a root mean square error(RMSE), mean absolute error(MAE) and mean absolute percentage error(MAPE) of 65658.12, 49729.86 and 16.386 respectively. Inadequate rainfall, high, weed infestation, disease incidence, high cost of seedlings, inadequate improved seed variety, inadequate loan and credit, inadequate market extension service are serious constraint militating against ginger production in the study area. Since the Quadratic-quadratic-linear function predicted a possible fall in ginger production in the near future, it is recommended that credit facilities and farm inputs should be made available in the study area, ginger farmers should be sensitized through adequate extension services on modern production techniques and adaptation strategies to climate change constraints. Government should regulate the price of ginger as a potential export commodity. The land tenure act should be more flexible to give more access to land for ginger production. ii