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.     

Trade unions vs. statistical discrimination: Theory and application to post-apartheid South Africa

A simple model of statistical discrimination is analyzed, which captures some stylized facts of the South African labor market. It shows that this type of discrimination disappears when the wage rates are determined by efficient bargaining between a representative firm and a union, with endogenous membership. This may explain why the wage gap between Black and White workers in post-apartheid South Africa is smaller among unionized workers than among non-unionized ones.     

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.     

Assessing the Impact of District Primary Education Program in India

We examine the impact of India's District Primary Education Program (DPEP) introduced in the mid‐1990s. We exploit the fact that the DPEP was targeted towards primary school age children and was introduced in phases to different districts in India, and many of the districts never got the program to implement a difference‐in‐difference strategy to find the causal impact of the program on probability of attended primary school, probability of completed primary education and years of schooling. We find that the DPEP program increased the probability of attended primary school and completed primary school by about 2 percentage points. Similarly, the program increased the years of schooling by 0.16 years.     

Tax Rebate and Dividend Payout in Bangladesh

The purpose of this paper is to examine the effects of the introduction of 20% tax rebate in 2002 for certain firms on the dividend policy of firms potentially qualifying for this rebate in Bangladesh. A balanced panel data set of 63 non-financial firms of Bangladesh for 14 （1998-2011） years from the Dhaka stock exchange is used for this purpose Newey-West estimator is used to estimate a logit model and the specified model uses binary values of 0 and 1 to identify if it met the tax rebate threshold. The explanatory variables are finn size, log of market value to face value ratio and profitability. A dummy variable was used to separate the pre-rebate period （2003 and before） from post-rebate period （after 2003）. The dummy variable turned out to be insignificant indicating that introduction of the tax rebate had no impact on dividend policy of qualifying firms.     

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.