Has international borrowing or lending driven Australia's net capital inflow?

Over the recent decades the most significant global imbalances have been between Asia-Pacific economies, with most attention directed to the imbalances of the largest economies, China, Japan and the United States. In contrast, this paper examines how external account imbalances and real long term interest rates are determined in smaller open economies. It first derives the proposition that external imbalances and long term interest rates move together whenever saving-investment shocks are predominantly domestically sourced, but move oppositely when saving-investment shocks mainly emanate abroad. It then shows that in the case of Australia, an Asia-Pacific economy that has borrowed heavily from abroad since the mid 1980's, rising net capital inflow has had a statistically significant negative impact on domestic real interest rates. This suggests that over that time net international lending rather than net foreign borrowing was mainly responsible for the variation in its external imbalance and real interest rates.

Sectoral analysis on capital structure determinants among the Malaysia listed firms

This study highlights the sensitivity of capital structure determinants in each sector within the ensembles of Malaysia Listed Companies. Based on pooled OLS, fixed effect and Generalized Method of Moments analysis, the findings revealed that capital structure determinants vary across sectors due to its nature or characteristics.

'Everybody has settled in so well': How migrants make connections and build social capital in Geelong

Australian and Victorian Government policies encourage settlement in regional areas for international migrants, refugees and internal migrants. Migrants to regional areas are diverse in terms of their area or country of origin, skills and occupation, family status and other demographic characteristics. The regional cities to which they migrate are also varied in terms of their community resources, social and cultural capital. The objective shared by all of these cities is for migrants to engage successfully with their new communities. Just how this occurs is the subject of debate and a lack of clarity. This therefore calls for a sound, theoretically informed understanding of how employers and community groups (formal and informal) can effectively assist migrants to make social connections in regional cities, and practical strategies which respond to these insights. The well-established social determinants of health tell us that the more socially included, connected and stable workforce and their families are, the better will be their physical and mental health and wellbeing.

Online social capital : mood, topical and psycholinguistic analysis

Social media provides rich sources of personal information and community interaction which can be linked to aspect of mental health. In this paper we investigate manifest properties of textual messages, including latent topics, psycholinguistic features, and authors' mood, of a large corpus of blog posts, to analyze the aspect of social capital in social media communities. Using data collected from Live Journal, we find that bloggers with lower social capital have fewer positive moods and more negative moods than those with higher social capital. It is also found that people with low social capital have more random mood swings over time than the people with high social capital. Significant differences are found between low and high social capital groups when characterized by a set of latent topics and psycholinguistic features derived from blogposts, suggesting discriminative features, proved to be useful for classification tasks. Good prediction is achieved when classifying among social capital groups using topic and linguistic features, with linguistic features are found to have greater predictive power than latent topics. The significance of our work lies in the importance of online social capital to potential construction of automatic healthcare monitoring systems. We further establish the link between mood and social capital in online communities, suggesting the foundation of new systems to monitor online mental well-being.

Connectivity, online social capital, and mood : a Bayesian nonparametric analysis

Social capital indicative of community interaction and support is intrinsically linked to mental health. Increasing online presence is now the norm. Whilst social capital and its impact on social networks has been examined, its underlying connection to emotional response such as mood, has not been investigated. This paper studies this phenomena, revisiting the concept of “online social capital†in social media communities using measurable aspects of social participation and social support. We establish the link between online capital derived from social media and mood, demonstrating results for different cohorts of social capital and social connectivity. We use novel Bayesian nonparametric factor analysis to extract the shared and individual factors in mood transition across groups of users of different levels of connectivity, quantifying patterns and degree of mood transitions. Using more than 1.6 million users from Live Journal, we show quantitatively that groups with lower social capital have fewer positive moods and more negative moods, than groups with higher social capital. We show similar effects in mood transitions. We establish a framework of how social media can be used as a barometer for mood. The significance lies in the importance of online social capital to mental well-being in overall. In establishing the link between mood and social capital in online communities, this work may suggest the foundation of new systems to monitor online mental well-being.

A panel error correction approach to explore spatial correlation patterns of the dominant housing market in Australian capital cities

Purpose - A panel error correction model has been developed to investigate the spatial correlation patterns among house prices. This paper aims to identify a dominant housing market in the ripple down process. Design/methodology/approach - Seemingly unrelated regression estimators are adapted to deal with the contemporary correlations and heterogeneity across cities. Impulse response functions are subsequently implemented to simulate the spatial correlation patterns. The newly developed approach is then applied to the Australian capital city house price indices. Findings - The results suggest that Melbourne should be recognised as the dominant housing market. Four levels were classified within the Australian house price interconnections, namely: Melbourne; Adelaide, Canberra, Perth and Sydney; Brisbane and Hobart; and Darwin. Originality/value - This research develops a panel regression framework in addressing the spatial correlation patterns of house prices across cities. The ripple-down process of house price dynamics across cities was explored by capturing both the contemporary correlations and heterogeneity, and by identifying the dominant housing market.

Making connections in a regional city: social capital and the primary social contract

Government policy in many countries encourages migration to regional centres to relieve pressure on major cities and to boost economic development. Migrants are more likely to remain in a new location if they have meaningful work and establish social connections there. This article explores how organisations and groups in a regional city provide newcomers with access to social capital resources which migrants can use to forge social connections. Past research has shown that migrants require a mix of linking, bridging and bonding social capital to form an effective primary social contract with their new home. This research suggests that regional cities – such as Geelong, Victoria – which are proactive in assembling diverse social capital resources and making them accessible to migrants, are more likely not only to receive more newcomers but also more likely to retain migrants and a skilled workforce. The findings have relevance to other regional centres.