Modelling The Dynamic Relationship Between Rainfall and Temperature Time Series Data In Niger State, Nigeria.

Vector Autoregression (VAR) has some very attractive features and has provided a valuable tool for analysing dynamics among time series processes. This paper examined the dynamic relationship between rainfall and temperature time series data in Niger State, Nigeria, collected from the Meteorological station, NCRI, Badeggi, Niger State, Nigeria which spanned from January 1981 to December 2010. The VAR model favoured VAR at lag 8 which indicated bi-directional causation from rainfall to temperature and from temperature to rainfall. The Impulse Response Functions and the Forecast Error Variance Decomposition were further used to interpret the VAR model. We concluded that modelling rainfall and temperature together in Niger State will further improved the forecast of rainfall and temperature respectively. Keywords: Rainfall; Temperature; Modelling; Meteorological data; Time series; Vector Autoregression (VAR)

Short Communique: Identifying local names for adopted improved rice varieties in Nigeria

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Estimation of Actual and Potential Adoption Rates and Determinants of NERICA Rice Varieties in Nigeria

The article uses the Average Treatment Effect (ATE) to estimate the population potential adoption rates of New Rice for Africa (NERICA) varieties in Nigeria when awareness of the new varieties and access to their seed are not constrained to farmers. It thus extends previous works in the literature which have focused on estimating potential adoption rates when only awareness of the technology is not a constraint to farmers. The adoption gaps due to lack of awareness and access to seed, and the determinants of adoption are estimated as well. Results show that NERICA adoption rate in Nigeria would have been up to 54% if the whole population were aware and up to 62% if they had access to NERICA variety seed. The actually observed 19% adoption rate implies a population adoption gap of 35% and 43% due to lack of awareness and access to NERICA seed respectively. It is also inferred from these results that when awareness is not a constraint, about 8% of the population will fail to adopt NERICA because of lack of access to its seed. Also famers with secondary education and farmers with access to extension services are more likely to adopt NERICA than farmers without