O13 - Economic Development: Agriculture; Natural Resources; Energy; Environment; Other Primary ProductsReturn

Renewable power generation, especially wind power and solar power, is experiencing a strong expansion worldwide and especially in Germany. With high shares of these methods of power generation, energy storage is needed to enable a demand-oriented power supply even with weather-related fluctuations in generation. Against the background of a power supply based entirely on wind and solar power, the question arises as to what total costs arise with the inclusion of storage systems, which is the subject of this article. The calculation model uses hourly resolved real data of German electricity generation from the years 2012 to 2018 to determine the required storage capacities. The electricity generation costs used range between 0.02 and 0.10 EUR/kW/h. The costs for the considered energy storages are calculated based on the Levelised Cost of Storage (LCOS) metric. It is concluded that in an electricity supply system based on wind and solar power, it is not the electricity generation that causes the greatest costs, but the storage. With electricity generation costs of 0.06 EUR/kW/h, the total system costs are in a range of 0.19 to 0.28 EUR/kW/h. This means that, in terms of costs, energy storage is more significant than electricity generation.

This article evaluates the production possibilities of the electricity sector in selected EU countries. The estimates for production functions are based on the financial data of individual companies in the selected sector. The analysis was based on a linearized version of the two-factor Cobb-Douglas production function, which was subsequently modified to compare productivity results by company size and country. The countries were selected based on the results of a cluster analysis. The cluster analysis was performed using aggregated data on the shares of energy sources in production in the electricity sector. The results show that companies from countries with a high share of renewables (such as Denmark) perform the worst in terms of total productivity. Furthermore, it was found that large companies have significantly higher productivity when compared to their smaller competitors.

This study investigates the impact of agricultural financing and agricultural output growth on employment generation in Nigeria from 1981 to 2017. The study adopts the framework of the Auto Regressive Distributed Lag (ARDL) Model for analysis. The empirical results show that while agricultural financing increases employment generation in both the short run and long run, the lag of agricultural output growth increases employment generation mainly in the short run. Other variables found to have significant effect on employment generation were price and agricultural output while labor force population, wages and aggregate expenditure were insignificant. The study concludes that policy makers should endeavor to see that every fund allocated for a specific agricultural schemes and interventions should be fully utilized for its purpose. To increase employment opportunities, there should be careful monitoring of the implementation of each scheme and policy to realize their specific objectives.