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.     

Bank intermediation activity in a low-interest-rate environment

This paper investigates how a prolonged period of low-interest rates affects bank intermediation activity. We use data for 113 large international banks headquartered in 14 major advanced economies during the period 1994–2015. We find that low-interest rates induce banks to shift their activities from interest-generating to fee-related and trading activities. This rebalancing is stronger for low capitalised banks. Banks also moderately adjust their funding structure, away from short-term market funding towards deposits. We observe a concomitant decline in the risk-weighted asset ratio and a reduction in loan-loss provisions, which is consistent with signs of evergreening.     

Design principles of hybrid approaches in new product development: a systematic literature review

Setting the right approach for new product development (NPD) in the presence of uncertainty remains an ongoing debate in innovation management. Stage-gate systems (SGS) and agile methodology (AM) are the dominant approaches. Recently, hybrid approaches (combining SGS and AM) have been proposed. Although these hybrid approaches represent a significant development in NPD, combining them without considering their design principles might lead to contradictory and competing conceptual formulations, thus increasing the difficulty of comparison among studies. Moreover, scholars and practitioners may struggle to understand when, why and how a certain configuration of the NPD process provides the right response to different manifestations of uncertainty. The current literature faces problems regarding the clarity of design principles (e.g. flexibility and adaptability), and this has led to research gaps concerning the uncertainty contingency and outcomes of hybrid approaches. This study combines bibliometric and content analyses to identify four design parameters and principles of NPD hybrid approaches: flexibility, adaptability, velocity and integration. Our findings might help advance the development and comparison of different hybrid approaches.     

Corporate social responsibility and earnings forecasting unbiasedness

We investigate the relationship between corporate social responsibility (CSR) and I/B/E/S analysts’ earnings per share (EPS) forecasts using a large sample of US firms for 1992–2011. Based on literature findings, we decompose the CSR effect into four factors: accounting opacity, corporate governance, stakeholder risk, and overinvestment. We find that all of them significantly affect both the absolute forecast error on EPS and its standard deviation controlling for forecast horizon; number of analysts and forecasts; and year, industry, and broker house effects. Consistently with our ex ante hypotheses, overinvestment, stakeholder risk, and accounting opacity have a positive effect, increasing both dependent variables, while corporate governance quality has a negative effect. A crucial aspect of our findings is that high CSR quality in terms of the four factors (i.e., accounting transparency, high corporate governance quality, stakeholder risk mitigation, and absence of overinvestment) contributes to making earnings forecasts unbiased as unbiasedness is generally met in the subsample of the Top CSR quality companies and markedly violated in the subsample of the Bottom CSR companies. We also document that overinvestment and stakeholder risk are sufficient to produce this effect.     

INFORMATION IN THE YIELD CURVE: A MACRO‐FINANCE APPROACH

We use a macro‐finance model, incorporating macroeconomic and financial factors, to study the term premium in the US bond market. Estimating the model using Bayesian techniques, we find that a single factor explains most of the variation in bond risk premiums. Furthermore, the model‐implied risk premiums account for up to 40% of the variability of one‐ and two‐year excess returns. Using the model to decompose yield spreads into an expectations and a term premium component, we find that, although this decomposition does not seem important to forecast economic activity, it is crucial to forecast inflation for most forecasting horizons. Copyright © 2012 John Wiley & Sons, Ltd.