SMALL-SCALE PRODUCERS OF QUALITY PRODUCTS WITH POTENTIAL OF GEOGRAPHICAL INDICATION PROTECTION IN TANZANIA
Geographical Indication (GI) adds value through product differentiation based on quality, protection of consumers through provision of certified information regarding product attributes and enhances and preserves the identity and cultural heritage of people in the region where a product is produced. Studies on potential GI products in Tanzania are yet to (be done) to show how producers may capture above mentioned benefits. This study analyses quality traits, factors and conditions with potential to increase value of Agricultural products in Tanzania through GI protection.
Are forest plantation subsidies affecting land use change and off-farm income? A farm-level analysis of Chilean small forest landowners
Forest plantations have increased rapidly in the last three decades, to a large extent due to direct and indirect financial incentives. At the farm level, forestry incentives can affect the investment decisions of small forest landowners and bring socioeconomic externalities or unintended effects associated with farm management. The purpose of this study is to assess the ex post impacts of a forestry subsidy on land use changes and off-farm income experienced by Chilean small forest landowners.
An Augmented Lagrangian algorithm for nonlinear semidefinite programming applied to the covering problem
In this work, we present an Augmented Lagrangian algorithm for nonlinear semidefinite problems (NLSDPs), which is a natural extension of its consolidated counterpart in nonlinear programming. This method works with two levels of constraints; one that is penalized and other that is kept within the subproblems. This is done to allow exploiting the subproblem structure while solving it.
A marked point process model for intraday financial returns: modeling extreme risk
Forecasting the risk of extreme losses is an important issue in the management of financial risk and has attracted a great deal of research attention. However, little attention has been paid to extreme losses in a higher frequency intraday setting. This paper proposes a novel marked point process model to capture extreme risk in intraday returns, taking into account a range of trading activity and liquidity measures. A novel approach is proposed for defining the threshold upon which extreme events are identified taking into account the diurnal patterns in intraday trading activity.