Prospective trends in the development of the agricultural sector: Through thorns to innovations

The principal directions and trends in the development of the agricultural sector under the conditions of the world’s economic crisis are considered in the article. The specification of priority directions of economic growth for the efficient use of resources and increasing competitiveness based on innovation factors is validated.     

Will African Agriculture Survive Climate Change?

Measurement of the likely magnitude of the economic impact ofclimate change on African agriculture has been a challenge.Using data from a survey of more than 9,000 farmers across 11African countries, a cross-sectional approach estimates howfarm net revenues are affected by climate change compared withcurrent mean temperature. Revenues fall with warming for drylandcrops (temperature elasticity of –1.9) and livestock (–5.4),whereas revenues rise for irrigated crops (elasticity of 0.5),which are located in relatively cool parts of Africa and arebuffered by irrigation from the effects of warming. At first,warming has little net aggregate effect as the gains for irrigatedcrops offset the losses for dryland crops and livestock. Warming,however, will likely reduce dryland farm income immedia-tely.The final effects will also depend on changes in precipitation,because revenues from all farm types increase with precipitation.Because irrigated farms are less sensitive to climate, wherewater is available, irrigation is a practical adaptation toclimate change in Africa.     

The information content of implied volatilities and model-free volatility expectations: Evidence from options written on individual stocks

We measure the volatility information content of stock options for individual firms using option prices for 149 US firms and the S&P 100 index. We use ARCH and regression models to compare volatility forecasts defined by historical stock returns, at-the-money implied volatilities and model-free volatility expectations for every firm. For 1-day-ahead estimation, a historical ARCH model outperforms both of the volatility estimates extracted from option prices for 36% of the firms, but the option forecasts are nearly always more informative for those firms that have the more actively traded options. When the prediction horizon extends until the expiry date of the options, the option forecasts are more informative than the historical volatility for 85% of the firms. However, at-the-money implied volatilities generally outperform the model-free volatility expectations.