Economic Targeting of Agricultural Beneficial Management Practices to Address Phosphorus Runoff in Manitoba

The mechanisms used to deliver agricultural beneficial management practices (BMPs) can influence the performance of these policies. Research has suggested that agri‐environmental instruments targeted based on specific economic or environmental characteristics can improve policy performance. Using a case study approach, we evaluate the relative performance of different mechanisms to target subsidized water retention pond BMPs to reduce phosphorus (P) runoff in an agriculture dominated subwatershed within the Lake Winnipeg watershed in southern Manitoba. The water retention pond BMPs were targeted based on estimated establishment costs (cost targeting), total phosphorus removal from surface water (benefit targeting), and pond‐specific benefit–cost ratios. The targeting was simulated using predictions of retention pond‐specific P removal from an adapted hydrology model and site‐specific pond construction and land opportunity costs assembled in a geographic information system database. Targeting of water retention pond BMPs has an impact on the cost effectiveness of the policy delivery with benefit–cost targeting being the most cost‐effective approach. Water retention ponds providing higher P removal at lower cost were smaller in size and on land previously used for the production of lower value crops. Le ciblage économique des pratiques de gestion bénéfiques en agriculture pour remédier au ruissellement du phosphore au Manitoba Les mécanismes utilisés pour livrer des pratiques de gestion bénéfiques (PGB) peuvent influencer la performance de ces politiques. Des études suggèrent que le ciblage d'instruments agroenvironnementaux basé sur des caractéristiques économiques ou environnementales précises peut améliorer la performance des politiques. Au moyen d'études de cas, nous évaluons la performance relative de divers mécanismes pour cibler les PGB des bassins de rétention d'eau subventionnés pour réduire le ruissellement de phosphore (P) dans un sous‐bassin du bassin du Lac Winnipeg au sud du Manitoba. Les PGB du bassin de rétention des eaux ont été ciblées en fonction des coûts estimés d'établissement (ciblage des coûts), de l′élimination totale du phosphore de la surface de l'eau (ciblage des bénéfices), et des ratios avantages‐coûts liés au bassin. Le ciblage fut simulé au moyen de prédictions du taux de suppression de P spécifique à chaque bassin de rétention obtenues à partir d'une adaptation d'un modèle hydrologique et d'une base de données d'un système d'information géographique (SIG) contenant les sites de chaque bassin de rétention et le coût d'opportunité du terrain. Le ciblage des PGB des bassins de rétention d'eau a un impact sur la rentabilité de la mise en ?uvre de politiques, le ciblage coût‐avantages étant l'approche la plus rentable. Les bassins de rétention d'eau ayant le plus haut taux d'élimination de P à moindre coût s'avéraient plus petits et sur des terrains ayant servi, auparavant, à la production de cultures de moindre valeur.     

The Relationship Between Consumer-Brand Identification and Brand Extension

The present research aims at examining the role of consumer-brand identification (CBI) in attitude toward brand extension regarding the congruency between the values of consumers and brands. In this way, the benefits of CBI to consumers and brand managers are outlined. This research has been conducted through designing a survey and collecting data through a questionnaire. For data mining and investigating the model, the SEM approach is implemented. According to the findings, high levels of CBI lead to positive attitudes toward the brand extension, and that value congruity positively impacts this relationship. The results outline that CBI impacts fit and tie in separate ways, so that CBI effect on fit is more substantial. Furthermore, according to the results, in comparison to the role of tie, the role of fit is more significant in predicting attitudes toward brand extension. The sample from university students is appropriate for testing theory, but limits generalizing the results of the research. In addition, this research has studied one product category and is limited in this perspective. The findings have remarkable recommendations for implementing brand extension as they emphasize the role of perceived fit. Moreover, by reexamining CBI in a less known market, the research has outlined its positive outcomes for firms. This research has used perceived tie in a brand extension context and, similar to perceived fit, has implemented it as another factor to predict attitude toward brand extension. In addition, this research is unique, as it has investigated CBI in a new context.     

Dynamic linkages among equity markets in the Middle East and North African countries

The relaxation of security laws and regulations in emerging markets in the Middle East and North Africa (MENA) provides abundant opportunities for foreign investors. These markets exhibit high-expected returns and substantial volatility. In this paper, we investigate the lead/lag relationship between the MENA countries and regions. We find no market causality or spillover from one country to another in the North Africa region. Our results for the Levant region reveal that there are linkages between stock markets in this region. The results for the Gulf Cooperation Council (GCC) region show that there is more interaction and linkage in the GCC region than in the North Africa and Levant regions. An unexpected result is that UAE's stock market leads all the markets in this region. Finally, we investigate linkages among the three regions. We find that GCC influences the other two regions.     

Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH-class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH-M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.     

Sustainable resource use,economic development,and public regulation

The role of production technology for sustainable economic growth and resource management in the multispecies renewable resources industries is a neglected issue, particularly in complex tropical ecosystems. Given the still rudimentary understanding of biological interactions among species, even in most temperate ecosystems, the importance of under-standing the technological and economic interactions is heightened for sustainable economic growth and public regulation. This paper evaluates these interactions for the multiproduct gill net fisheries of Peninsular Malaysia. Standard price and quantity controls may have little promise. Gear regulations, a policy of constant escapement, and managing the entire mix of species as a single stock for economic rather than biomass yield appear the most promising management tools given the limited regulatory options.     

Some general results for moments in bivariate distributions

The purpose of this paper is to present a closed formula to compute the moments of a general function from the knowledge of its bivariate survival function. The result is derived by utilizing an integration by parts formula for two variables, which is not readily available in the literature. Many of the existing results are obtained as special cases. Finally, two examples are presented to illustrate the results. In both the examples, mixed moments as well as moments for the series system and parallel system are obtained. The integration by parts formula in two variables, derived here, is of interest in its own right and we hope that it will be useful in other investigations. The integration by parts formula in two variables is derived as a special case of a general formula in n variables.     

A fuzzy goal programming approach to analyse sustainable development goals of India

Energy policy, environmental planning and economic development play a key role in sustainable development. Sustainable development requires suitable and strategic policies satisfying multiple and conflicting objectives. Fuzzy goal programming (FGP) is a well-known approach in multi-criteria decision-making for its practical application. In this article, a FGP approach is proposed to analyse environmental, energy and sustainability goals of India by the year 2030 with reference to the key economic sectors of India. The presented model analyses the improvement opportunities, requirement of efforts and implementation of the sustainable development plans. Numerical illustration is also provided for validation and application of the proposed model.     

Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High-Dimension Regime

In this study, we suggest pretest and shrinkage methods based on the generalised ridge regression estimation that is suitable for both multicollinear and high-dimensional problems. We review and develop theoretical results for some of the shrinkage estimators. The relative performance of the shrinkage estimators to some penalty methods is compared and assessed by both simulation and real-data analysis. We show that the suggested methods can be accounted as good competitors to regularisation techniques, by means of a mean squared error of estimation and prediction error. A thorough comparison of pretest and shrinkage estimators based on the maximum likelihood method to the penalty methods. In this paper, we extend the comparison outlined in his work using the least squares method for the generalised ridge regression.     

Vicarious warfare and dynamic efficiency of companies in the aerospace and defence industry

This study explores the economic performance that vicarious warfare can bring for the aerospace and defence industry. First, this study measures the performance of 22 companies using a nonradial dynamic data envelopment analysis model from 2011 to 2017. Second, this study evaluates whether vicarious warfare can influence the performance. The efficiency analysis suggests rooms for improvements meanwhile, the projection analysis suggests that market value should be significantly increased, and the number of employees should be reduced significantly. The regression analysis suggests that the number of times a country takes a side in wars would positively affect the efficiency of companies.     

Corporate commitment to climate change action,carbon risk exposure,and a firm's debt financing policy

Motivated by the rising consensus that corporate engagement in climate change actions holds the key for society's transition into environmentally resilient economy, the study examines whether a firm's commitment to climate change action and its carbon risk exposure shape the firm's debt financing policy. Based on insights drawn from signaling, corporate reputation, and agency theories, we develop models that link corporate commitment to climate change actions and a firm's carbon risk exposure with its debt financing decisions. Using data drawn from S&P 500 companies, for years 2015 to 2019, we find a robust evidence that firms that engage in higher levels of commitment to climate change actions issue a higher proportion of debt with longer terms to maturity, even after controlling for their carbon risk exposure. However, we do not find a robust evidence corroborating an association between firms' carbon risk exposure and their debt financing policy. These findings are consistent with arguments that high-commitment firms enjoy positive reputation, better credit rating, and reduced agency and information asymmetry costs, allowing them to gain easier access to long-term debt markets.