Use of Derivatives and Analysts’ Forecasts: New Evidence from Non‐financial Brazilian Companies

This study investigates whether market analysts’ forecasts are influenced by the presence of derivative financial instruments in listed firms. From a sample of firms comprising 1173 derivative users and 7797 non‐users for the 2006–14 period, the results indicate the existence of less error behaviour (bias) on earnings per share forecasts for derivative user firms compared to non‐user firms. This finding suggests that these instruments may be used to protect businesses and provide greater stability in the results of companies that use them. The presence of derivative financial instruments is increasing among listed firms, and management can use them for hedging or speculation (thus mitigating or increasing risk). The literature contains few studies on this issue, and the general understanding relies on the assumption that derivative financial instruments provide relevant information for decision making.     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

The anticipated and concurring effects of the EMU: exchange rate volatility, institutions and growth

Reduced exchange rate volatility and higher and less heterogeneous quality of institutional rules and macroeconomic policies are two of the main (anticipated and concurring) effects expected from a currency union.In this paper, we measure the magnitude of these two effects for the Eurozone countries looking at real effective exchange rates (REER) and at different indicators of quality of institutional rules and macroeconomic policies (QIRMP). We find that the first effect is much stronger than the second when we compare relative changes for Eurozone countries and the rest of the world in the relevant period.We further evaluate the impact of both effects on economic growth on a larger sample of countries. Our findings show that both have significant impact on levels (more robust) and on rates of growth (weaker) of per capita GDP.     

Using technology to improve the management of development impacts on biodiversity

The mitigation hierarchy (MH) is a prominent tool to help businesses achieve no net loss or net gain outcomes for biodiversity. Technological innovations offer benefits for business biodiversity management, yet the range and continued evolution of technologies creates a complex landscape that can be difficult to navigate. Using literature review, online surveys, and semi-structured interviews, we assess technologies that can improve application of the MH. We identify six categories (mobile survey, fixed survey, remote sensing, blockchain, data analysis, and enabling technologies) with high feasibility and/or relevance to (i) aid direct implementation of mitigation measures and (ii) enhance biodiversity surveys and monitoring, which feed into the design of interventions including avoidance and minimization measures. At the interface between development and biodiversity impacts, opportunities lie in businesses investing in technologies, capitalizing on synergies between technology groups, collaborating with conservation organizations to enhance institutional capacity, and developing practical solutions suited for widespread use.     

Cross-country differences in monetary policy execution and money market rates’ volatility

Volatility patterns in overnight interest rates display differences across industrial countries that existing models—designed to replicate the features of individual countries’ markets—cannot account for. This paper presents an equilibrium model of the overnight interbank market that matches cross-country differences in patterns in interest volatility by incorporating differences in how central banks manage liquidity in response to shocks. Our model is consistent with central banks’ practice of rationing access to marginal facilities when the objective of stabilizing short-term interest rates conflicts with another high-frequency objective, such as an exchange rate target.     

Consumption and Portfolio Choice over the Life Cycle

This article solves a realistically calibrated life cycle modelof consumption and portfolio choice with non-tradable laborincome and borrowing constraints. Since labor income substitutesfor riskless asset holdings, the optimal share invested in equitiesis roughly decreasing over life. We compute a measure of theimportance of human capital for investment behavior. We findthat ignoring labor income generates large utility costs, whilethe cost of ignoring only its risk is an order of magnitudesmaller, except when we allow for a disastrous labor incomeshock. Moreover, we study the implications of introducing endogenousborrowing constraints in this incomplete-markets setting.     

Do economic integration agreements affect trade predictability? A group effect analysis

Recent theoretical findings in the trade literature suggest that economic integration agreements (EIAs) not only increase the level of trade but also make it more stable and predictable. This paper proposes a Hausman–Taylor quantile regression approach to identify the causal effect of EIA membership on trade predictability. The proposed methodology accounts for group effects in the gravity equation and is computationally efficient. Our results corroborate the theoretical findings that EIAs make trade more stable and predictable and this conclusion is even stronger for deeper EIAs.