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.

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.

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.

We propose a multivariate dynamic intensity peaks‐over‐threshold model to capture extremes in multivariate return processes. The random occurrence of extremes is modeled by a multivariate dynamic intensity model, while temporal clustering of their size is captured by an autoregressive multiplicative error model. Applying the model to daily returns of three major stock indexes yields strong empirical support for a temporal clustering of both the occurrence and the size of extremes.

The concept of welfare has evolved to incorporate subjective elements. One key factor for development is social capital. Participation in organizations promotes a more active social life, with potential positive results on welfare. This work investigates this last association through the estimation of a bivariate ordered probit model by using the World Value Survey for Chile.

In this paper, we try to understand pesticide input decisions among Vietnamese rice producers by examining the production risk effects of pesticide use, applying both a lottery game and a more traditional production function approach. Production function estimates show that excessive pesticide use makes production riskier. This result is supported by the lottery approach, which signals that more risk averse farmers use less pesticide, implying that pesticide is a risk-increasing input.