This study aims to develop autoregressive integrated moving average (ARIMA) models to predict the solar, wind, spot and options pricing over the next 2 years, with historical data being used in a univariate manner to understand market behaviour in terms of trends. The assessment is made in the context of the Australian National Electricity Market (ANEM). The ARIMA models predict the future values of the monthly solar, wind, spot and options prices for various Australian states using time-series data from January 2006 to March 2018. The results show increases from 30.46% to 40.42% for the spot electricity prices and from 14.80% to 15.13% for the options electricity prices in the ANEM with a 2-year horizon. The results further show that wind prices are expected to increase by an average of 5.43%. However, the results also show that the average solar electricity prices will decrease by 67.7%.

The present study employed various qualitative techniques to investigate the nature and influence of policies and regulations concerning solar and wind pricing on the Australian electricity spot and options markets. The analysis was based on data gathered through interviews conducted with energy managers, chief executive officers and other significant personnel from the Australian electricity industry. The interviewees' responses regarding the solar and wind policies of relevance to the Australian electricity markets were examined, and the thick and in-depth content data derived from the interviews were used to examine how their views and personal politics influenced pricing within the electricity markets. The results suggest that renewable energy policies lower the electricity prices, reduce the risks for investors and also result in larger deployment mechanisms.

Water is highly critical for the existence of humans and other living organisms as well as for all sorts of life. Agriculture needs water to produce crops and manufacturing industries need it for producing products and services. Water is immensely critical for energy production and needed in the balance and sustainability of ecosystem. There has been a considerable rainfall variations that impacted water availability in Somalia and Ethiopia. Equally, temperature variations have also played a major role in the everyday life of Somalis and Ethiopians. Together the rainfall fluctuations and temperature variations have been attributed to climate change. The effects of these issues on people movements away from rural to urban have had little attention in recent times. This paper addresses the impact of climate change variables on rural -urban migration in both Somalia and Ethiopia. More specifically, we use time series analysis to examine the interactions between the rural-urban migration, rainfall and temperature. We model the multivariate data using ARIMA and VAR models; this is to first conduct univariate analyses for the purpose of predictions, and secondly to understand the nature of interactions and dependencies by conducting multivariate VAR analysis. This study determines the most appropriate ARIMA models of rural migration, urban migration rainfall and temperature of Somalia and Ethiopia as presented in Table 2. Both ARIMA and VAR analyses have produced relatively good models that are statistically significant and perform well in making short term predictions; a 10 year period of annual forecast of rural and urban migration as well as rainfall and temperature of Somalia and Ethiopia were carried out. Then univariate and multivariate analyses have showed that climate change factors such as "rainfall" and "temperature" variations have a combined granger effect on people migration in both rural and urban areas in both countries; in fact temperature variations have a significant impact (5% and 10%) on urban and rural migrations respectively. Climate change effects appear to be driving the migration from rural to urban. This is also compounding the international migration out of the African continent that is noted in Europe, Asia and even Australia.