Renewable and nonrenewable energy production and economic growth in sub-Saharan Africa: a hidden cointegration analysis

The objective of this article is to investigate the hypothesis of asymmetric effects between economic growth and renewable and nonrenewable energy production. To this end, both the linear cointegration and the hidden cointegration methodology are employed, with the latter allowing a straightforward delimitation of the data in an economically sensible way. We test for the presence of hidden cointegration across 12 sub-Saharan African countries spanning the period 1971–2011. The empirical results confirm the growth hypothesis for a subset of countries, suggesting that their growth could be adversely affected by conservation policies, while for a second subgroup of countries they confirm the conservation hypothesis, indicating that conservation policies could enhance the growth process in these countries. The differentiation of the results could be captured entirely by the linear approach, indicating that the lack of cointegration between renewable energy production and economic growth found in previous studies may be due to failures to properly delimit the nonlinearity property in the data.     

Modelling the National Greenhouse and Energy Reporting System's Energy Consumption Under‐Coverage

The new data source for the Australian Energy Statistics, the National Greenhouse and Energy Reporting System, does not require businesses using less than 200 terajoules to report their energy consumption. This results in a data gap in the total industry energy consumption. To estimate the gap, this study models business energy consumption using data from the Australian Bureau of Statistics' 2008–09 Energy, Water and Environment Survey and data from the 2008 to 2009 business activity statement unit record estimates. The article discusses the modelling approaches and methodological issues associated with the estimation of the National Greenhouse and Energy Reporting System's energy consumption under‐coverage. It provides estimation results and suggestions for future research, based on available data.

     

Factors Influencing Young Consumers’ Acceptance of Genetically Modified Food in India

We analyzed the determinants of acceptance of genetically modified food (GMF) by using the probit model. In this study, we found that around 41% of the students are willing to buy GMF, and acceptance of GMF is less in female respondents than male respondents. The findings indicate that in India, benefit perception of GMF outweighed the risk perception. We also found that respondents’ trust in international organizations for truthful information has a positive and significant influence on acceptance of GMF.     

The Gravity Model Analysis of Bangladesh's Trade: A Panel Data Approach

The article applies generalized gravity models to analyze Bangladesh's bilateral trade pattern using the panel data estimation technique. The results reveal that Bangladesh's trade is positively determined by the size of the economies, per capita gross domestic product differential and openness of the trading countries. Bangladesh's exports are positively determined by its income, partner countries' total import demand and openness, but negatively determined by partner countries' income and domestic inflation. Bangladesh's imports are positively determined by income of trading countries and degree of openness of the partner countries and negatively determined by partner countries' inflation. Transportation costs affect Bangladesh's trade negatively.     

Leveraging Virtual Attribute Experience in Video Games to Improve Brand Recall and Learning

This article extends the concept of virtual direct experience (VDE) from a product to an attribute as video gamers can virtually experience an attribute within a gaming environment. Using a 2 (VAE: present versus absent) x 2 (order of brand presentation: first or second) between subjects experimental design, we find that associating a brand with virtual attribute experience (VAE) by exposing consumers to the brand name and the virtual experience simultaneously has a positive effect on brand recall, brand extension acceptance, overall attitude, and purchase intention. In addition, our results demonstrate a significant interaction between VAE and telepresence on brand recall.     

Contextual and Competitive Interference: Inhibition or Facilitation?

Existing literature has found two sources of advertising interference, competitive and contextual, that decrease the effectiveness of an ad in a cluttered environment. However, to date, the negative impact of competitive and contextual interference has been examined independently. This research explores advertising effectiveness when these sources exist concurrently. Contrary to the supposition concerning the additive effects of both sources of interference when simultaneously present, our findings indicate that viewing ads for the same product category with similar executional elements leads to the dissipation of interference effects (Study 1). Consistent with the process rationale, when a product-brand cue (versus a picture cue) is provided, this novel effect disappears (Study 2). The implications of these findings for advertising are highlighted in the discussion section.     

Maximizing Profits for a Multi-Category Catalog Retailer

It is a common trend in the retail industry for catalog retailers to mail multiple catalogs, each promoting different product categories. The existing catalog mailing models do not address the issue of optimizing multi-category catalog mailing. We address this research gap by introducing a model that integrates the when and what components of a customer's purchase decision into the how much component (number of catalogs) of a firm's cross-selling strategy. In addition to comparing the impact of category-specific versus full product catalogs in generating sales in a specific category, the study also finds relative impacts of various category-specific catalogs. We jointly estimate the probability of purchase and purchase amounts in multiple product categories by using multivariate proportional hazard model (MVPHM) and a regression based purchase amount model in a Hierarchical Bayesian framework. The model accounts for unobserved heterogeneity, and uses a control function (CF) approach to account for endogeneity in catalog mailing. The results from the Genetic Algorithm (GA) based optimization suggest that the catalog mailing policy as per the proposed model would be able to generate 38.4 percent more customer lifetime value (CLV) from a sample of 10 percent of the households as compared to the current catalog mailing policy of the retailer by reallocation of the catalogs across customers and mailing periods based on their propensity to buy.     

Adoption of weather‐index insurance: learning from willingness to pay among a panel of households in rural Ethiopia

In this article we examine which farmers would be early entrants into weather‐index insurance markets in Ethiopia, were such markets to develop on a large scale. We do this by examining the determinants of willingness to pay for weather insurance among 1,400 Ethiopian households that have been tracked for 15 years as part of the Ethiopian Rural household Survey. This provides both historical and current information with which to assess the determinants of demand. We find that educated, wealthier individuals are more likely to purchase insurance. Risk aversion is associated with low insurance take‐up suggesting that models of technology adoption can inform the purchase and spread of weather index insurance. We also assess how willingness to pay varied as two key characteristics of the contract were varied and found that basis risk reduces demand for insurance particularly when the price of the contract is high, and that provision of insurance through groups is preferred by female headed households and individuals with lower levels of education.