Abstract
Primarily, the study examined the determinants of rice import demand in Nigeria by assessing the short run and long run dynamic model relationships among the determinants, trends and extent of causality among per capita income, population, exchange rate and price of rice imports were equally examined, using data obtained from the Central Bank of Nigeria (CBN) and National Bureau of statistics (NBS) over the period 1961 to 2013. Data obtained showed the perceived determinants of imports demand for rice in Nigeria were local rice production, rice import price, rice consumption, per capita income, and exchange rate, price of local rice, domestic stock variation, maize price, meat price and demographic development. The short run dynamic model result showed that rice consumption, price of meat, price of maize, local rice quantity, demography development and stock variance are statistically significant at 5%. The significance of the coefficient of the error correction term confirmed theappropriateness of the error correction approach which also showed that ignoring the long run relationship is detrimental. The result however, revealed that rice import demand increases significantly with increasing rice consumption, increasing price of meat, increasing price of maize (keeping that for imported rice unchanged) and increasing demography development. Rice import price, per capita income, price of local rice and exchange rate had no significant effects on rice import demand. The study therefore recommends that locally-produced rice should be intensively improved.
 Keywords: demography, determinants, Error correction mechanism, rice import demand
Highlights
The study examined the determinants of rice import demand in Nigeria by assessing the short run and long run dynamic model relationships among the determinants, trends and extent of causality among per capita income, population, exchange rate and price of rice imports were examined, using data obtained from the Central Bank of Nigeria (CBN) and National Bureau of statistics (NBS) over the period 1961 to 2013
This study pattern its model in line with Shehu and Aliyu (2007) which happen to be the most appropriate for this study. They employed the simple import demand model as developed by Khan (1974). This involves a cointegration and error correction modelling, using the Ordinary Least Squares regression (OLS) estimation technique, which were based on the simple linear relationship between rice imports as dependent variables and rice import price, per capita income, exchange rate, volume of local rice, price of local rice, total rice consumption, domestic stock variation, price of pseudo substitute, price of complement, demographic development and consumer price index as independent variables; the model specified a linear relationship between rice imports quantity (RMQ) as dependent variable, and Rice Import Price (RMP), Rice Consumption (RC), Per Capita Income (PCI), Exchange-Rate (EXG), Local Rice quantity (LRQ), Price of Local Rice (LRP), Domestic Stock Variation (DSV),Maize Price (MaP), Meat Price (MeP) and Demographic Development (DD)
The signs of the coefficient of rice import price, per capita GDP, rice consumption, demography development, price of meat and price of maize are found to be positive while the signs of the coefficient of local rice quantity, local rice price, exchange rate, and domestic stock variance are negative
Summary
Data for this study were secondary in nature and were sourced from Food and Agriculture Organization (FAO) and World Development Indicator (WDI). While “U” (the error term) was introduced to take care of variables not included in the model but affect rice import, equation (1) transforms to: f(RMP, RC, PCI, EXG, LRQ, LRP, DSV, MaP, MeP, DD). Βo, , , , , , , , , and are the elasticities of Rice Import Price (RMP), Rice Consumption (RC), Per Capita Income (PCI), Exchange-Rate (EXG), Local Rice quantity (LRQ), Price of Local Rice (LRP), Domestic Stock Variation (DSV),Maize Price (MaP), Meat Price (MeP), and Demographic Development (DD). In the event of a long run relationship among the variables, equation (3) transforms into an error correction model specified as: exchange rate was relatively low and constant, rice import was very low. Either equation (3) (if there is no long run relationship among the variables) or equation (10) (in the event of a long run relationship among the variables) shall be estimated
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