This study investigates the relationship between Nigeria's external debt and economic growth, between 1975 and 2006. The choice of period was guided by data availability and the the escalation of Nigeria's external debt. Econometric evidence revealed stationarity of the variables at their first difference while the Johansen cointegration approach also confirms the existence of one cointegrating relationship at the 1 percent and 5 percent level of significance. In addition, error correction estimates revealed that external debt has negative relationship with economic growth in Nigeria. For example, a one per cent increase in external debt resulted in a decrease of 0.027 per cent in Gross Domestic Product, while a 1 per cent increase in total debt service resulted to 0.034 per cent (decrease) in Gross Domestic Product. These relationships were both found to be significant at the ten per cent level. In addition, the pairwise Granger Causality test revealed that uni-directional causality exists between external debt service payment and economic growth at the 10 percent level of significance. Also, external debt was found to granger cause external debt service payment at the 1 percent level of significance. Statistical interdependence was however found between external debt and economic growth. In order to ameliorate the negative influence of external debt on economic growth, debt accumulation for projects must be matched with the timing of repayment. Nigeria must be concerned about the absorptive capacity. Consideration about low debt to GDP, low debt service/GDP capacity ratios should guide future debt negotiations. Finally the portfolio of debt must be diversified in terms of sources and types to avoid harmful concentration and a reoccurrence to the past.

This study examined the impact of some macroeconomic variables and power supply on the performance of the Nigerian manufacturing sector, using ex-post facto research design. Secondary data were sourced from Central Bank of Nigeria (CBN) statistical bulletin (2009) and other publications. The main findings of the study were that power supply had positive and significant impact on capacity utilization while inflation rate and interest rate had negative impact on capacity utilization. However, the impact of interest rate was significant at 5% level while lending rate was insignificant. Time series data were analysed with the aid of e-views 5.0 econometric computer package using least square multiple regression technique. The regression model explained 88.54% of the variation in capacity utilization, after correcting for linearity, normality, auto-correlation and heteroscedascity. The study recommended that the ongoing privatisation of Power Holding Company of Nigeria should be pursued with vigour and that the policy thrust of single digit inflation and lending rates by CBN should be sustained. The government should also put in place monetary and fiscal policies to create an enabling environment for the manufacturing sector, thereby giving a boost to the economy as a whole.

The telecommunication industry is one of the service industries that is most affected by the problem of subscribers' churn. Although several techniques have been used to predict customer churn in developed countries, many of those studies used secondary data which are not readily available in Nigeria for researchers. This study investigates how Markov chains help in modelling and predicting the customer churn and retention rate in the Nigerian mobile telecommunication industry. The data generated through the survey were input in the Windows-based Quantitative System for Business (WinQSB) for analysis. The results reveal that in the study area MTN has the highest retention rate (86.11%), followed by GLO (70.51%), Airtel (67%), and Etisalat (67.5%). This result particular and survival in general.

Stock market returns are predictable from a variety of financial and macroeconomic variables and have long been an attraction for equity investors. Recently increasing attention has shifted on the market index as a method of measuring a section of the stock market. The stock market index is regarded as an important indicator by the investing public at large and can be used as a benchmark by which investor or fund manager compares the returns of their own portfolio.In this study, attempts are made to model the Nigerian stock market index using a structural model. The procedure is based on the relationship between the state space and the autoregressive moving average (ARMA) model. The time series procedure from S-PLUS software is used in the analysis. The result obtained shows that the Nigerian stock market price index is an autoregressive model (AR) of order 1. It is also found that the AIC is at minimum at lag 1which corresponds to the same model identified for the series by using the sample ACF and PACF.