Cause-Brand Community: Toward Consumer Citizenship

Brand communities have been proven to be successful with commercial brands. However, a review of the literature indicated that brand community has not been studied in charity organizations. To shed light on this issue, a qualitative research was conducted among stakeholders of an internationally well-known charity organization using three different techniques: in-depth interviews, netnography, and nonparticipant observation at the charity’s brandfest. The results suggest that cause-brand communities exist, sharing the same elements of commercial-brand communities, but the two have some unique characteristics, such as the existence of different stakeholders and small communities that demonstrate an extreme commitment, the promotion of consumer citizenship among them, and the lack of oppositional brand loyalty. A cause-brand community has important managerial implications as it helps build the charity’s brand equity; at the same time, a well-known brand supports the construction of the brand community.     

Measuring the dynamics of APEC output connectedness

We examine the dynamics of output connectedness of Asian Pacific Economic Cooperation (APEC) economies using time‐varying, region‐specific, generalised connectedness measures. We find that the connectedness of APEC economies with the rest of the world is quite substantial, with the 2008–09 Global Financial Crisis increasing the connectedness measures above their precrisis levels. The USA, China, and Korea are shown to be systemically important and to dominate APEC’s real activities, while outside the APEC region the roles of India and the UK are also non‐negligible. These results suggest that the majority of APEC economies are considerably open to output shocks from the dominant economies such that policymakers in APEC must be continuously conscious of headwinds originating from these sources.     

What Do Deviations from Covered Interest Parity and Higher FX Hedging Costs Mean for Asia?

Open Economies Review - Asian countries have high demand for US dollars and are sensitive to US dollar funding costs. An important, but often overlooked, component of these costs is the basis...     

Ordinaries

Journal of Bioeconomics - The Ordinaries column began in 2019 to promote a Neo-Darwinian synthesis of neoclassical and behavioral economics. This article places already-published, as well as...     

The Information Content of NAV Estimates

The Journal of Real Estate Finance and Economics - This paper investigates whether analysts’ estimates of firm fundamental value transmit unique information to security markets. Previous work...     

Externalities from Intra-Firm Trade by U.S. Multinationals

International Advances in Economic Research - The share of world trade attributed to intra-firm trade is large and fast-growing. This paper offers new information on the welfare outcome of these...     

Class structure and inequality during the industrial revolution: lessons from England's social tables, 1688–1867

This article measures the size and incomes of six major social classes across the industrial revolution using social tables for England and Wales in 1688, 1759, 1798, 1846, and 1867. Lindert and Williamson famously revised these tables, and this article extends their work in three directions. First, servants are removed from middle‐ and upper‐class households in the tables of King, Massie, and Colquhoun and tallied separately. Second, estimates are made for the same tables of the number and incomes of women and children employed in the various occupations, and, third, incomes are broken down into rents, profits, and employment income. These extensions to the tables allow variables to be computed that can be checked against independent estimates as a validation exercise. The tables are retabulated in a standardized set of six social groups to highlight the changing structure of society across the industrial revolution. Gini coefficients are computed from the social tables to measure inequality. These measures confirm that Britain traversed a ‘Kuznets curve’ in this period. Changes in overall inequality are related to the changing fortunes of the major social classes.     

Political brand image: an investigation into the operationalisation of the external orientation of David Cameron’s Conservative brand

This paper seeks to address the limited understanding of how to operationalise the external brand image of a political brand. More specifically, this research critically assesses the transfer potential of the six variables of brand image by Bosch, Venter, Han and Boshoff to deconstruct the UK Conservative Party brand from the perspective of young people aged 18–24 years during the 2010 UK General Election campaign. This research demonstrates the applicability of the six variables otherwise known as the ‘brand image framework’ to the political environment. However, the application of the brand image framework in its original conceptualisation proved problematic. Many of the brand image variables were clarified, rearticulated and simplified to address the political context. This refined conceptualisation provided an in-depth understanding of how to investigate the political brand image of David Cameron’s Conservative Party. This study addresses the paucity of research that operationalises external brand image and provides practitioners and academics within and beyond the context of political branding a mechanism to understand the external orientation of brands. This research may also be used by political and non-political brands as a basis to explore external brand image and compare its consistency with internal brand identity.     

Explaining the slow U.S. recovery: 2010–2017

This paper argues that the slow U.S. recovery after the 2008–2009 recession was due to sluggish government spending. The analysis uses a structural macroeconometric model. Conditional on government policy, the errors in predicting output for the 2009.4–2017.4 period are within what one would expect historically. Productivity and labor force participation are endogenous variables in the model, and so their behaviors in this period are a consequence of the slow growth rather than a cause.     

Modelling spatial regimes in farms technologies

We exploit the information derived from geographical coordinates to endogenously identify spatial regimes in technologies that are the result of a variety of complex, dynamic interactions among site-specific environmental variables and farmer decision making about technology, which are often not observed at the farm level. Controlling for unobserved heterogeneity is a fundamental challenge in empirical research, as failing to do so can produce model misspecification and preclude causal inference. In this article, we adopt a two-step procedure to deal with unobserved spatial heterogeneity, while accounting for spatial dependence in a cross-sectional setting. The first step of the procedure takes explicitly unobserved spatial heterogeneity into account to endogenously identify subsets of farms that follow a similar local production econometric model, i.e. spatial production regimes. The second step consists in the specification of a spatial autoregressive model with autoregressive disturbances and spatial regimes. The method is applied to two regional samples of olive growing farms in Italy. The main finding is that the identification of spatial regimes can help drawing a more detailed picture of the production environment and provide more accurate information to guide extension services and policy makers.