This paper empirically assesses the relationship between Deposit Insurance Funds (DIF) and the quality of risk assets of listed Deposit Money Banks (DMBs) in Nigeria. The entire fifteen listed DMBs in the country as of 31st December, 2017 were focused on and the secondary data were subsequently sourced from the yearly financials of the Nigeria Deposit Insurance Corporation (NDIC) for a 29-year period covering from 1989 to 2017. The Auto-Regressive Distributed Lag (ARDL) and the Vector Error Correction (VEC) estimation techniques were the basis of estimating the relationship between the variables of interest in this study. Evidence from our analyses indicates that the volume of total deposits and total loans and advances of DMBs have long run negative and statistically significant relationship with DIF. Conversely, the quality of risk assets of DMBs exhibits a positive and insignificant relationship with the target reserve ratio of DMBs. The study thus recommends that regulatory agencies in the banking sector (CBN and NDIC), amongst others, collaborate with listed DMBs to diversify and manage their risk assets by strategically intensifying the implementation of existing measures aimed at minimising incidences of loan default and the alarming levels of non-performing loans in the portfolio of Nigerian DMBs.

This paper presents a study to determine demand for electricity in city of Yazd, Iran over the period of 1998-2008. Using vector error correction model (VECM) based on seasonal information, the study determines that electricity has no elasticity in short term in household expenditure. Therefore, government policy on increasing price of electricity will not influence demand. However, electricity maintains elasticity over the long-term period and an increase on price of electricity could motivate consumers to reduce their consumption by purchasing energy efficient facilities. Therefore, any governmental strategy to increase price may have positive impact on economy. The study also detects a positive and meaningful relationship between temperature and electricity consumption.