984 resultados para Capital cities


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Local climate is a critical element in the design of energy efficient buildings. In this paper, ten years of historical weather data in Australia's eight capital cities were profiled and analysed to characterize the variations of climatic variables in Australia. The method of descriptive statistics was employed. Either the pattern of cumulative distribution and/or the profile of percentage distribution are presented. It was found that although weather variables vary with different locations, there is often a good, nearly linear relation between a weather variable and its cumulative percentage for the majority of middle part of the cumulative curves. By comparing the slopes of these distribution profiles, it may be possible to determine the relative range of changes of the particular weather variables for a given city. The implications of these distribution profiles of key weather variables on energy efficient building design are also discussed.

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Hanoi promotes itself both as a place for foreign investment in urban development and as the 'cradle of Vietnamese civilisation'. Special status is given to places of national heritage significance, and policy makers and planners face challenges of balancing heritage conservation and modern development. By contrast, the former capital, Hue, continues to decline economically relative to other Vietnamese cities and is discovering value in its imperial heritage as a 'vector for development'. These Vietnamese capital cities demonstrate that heritage conservation is a key consideration in government efforts to improve the position of their constituencies in the newly-shaping global and national economic systems.

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The ripple effect of house prices within metropolitan areas has recently been recognised by researchers. However, it is very difficult to formulate and measure this effect using conventional house price theories particularly in consideration of the spatial locations of cities. Based on econometrics principles of the cointegration test and the error correction model, this research develops an innovative approach to quantitatively examine the diffusion patterns of house prices in mega-cities of a country. Taking Australia's eight capital cities as an example, the proposed approach is validated in terms of an empirical study. The results show that a 1-1-2-4 diffusion pattern exists within these cities. Sydney is on the top tier with Melbourne in the second; Perth and Adelaide are in the third level and the other four cities lie on the bottom. This research may be applied to predict the regional housing market behavior in a country.

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The ripple effect of house prices within metropolitan areas has recently been recognised by researchers. However, it is very difficult to formulate and measure this effect using conventional house price theories particularly in consideration of the spatial locations of cities. Based on econometrics principles of the cointegration test and the error correction model, this research develops an innovative approach to quantitatively examine the diffusion patterns of house prices in mega-cities of a country. Taking Australia's eight capital cities as an example, the proposed approach is validated in terms of an empirical study. The results show that a 1-1-2-4 diffusion pattern exists within these cities. Sydney is on the top tier with Melbourne in the second; Perth and Adelaide are in the third level and the other four cities lie on the bottom. This research may be applied to predict the regional housing market behavior in a country.

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Prior research supports the proposition that house price diffusion shows a ripple effect along the spatial dimension. That is, house price changes in one region would reflect in subsequent house price changes in other regions, showing certain linkages among regions. Using the vector autoregression model and the impulse response function, this study investigates house price diffusion among Australia's state capital cities, examining the response of one market to the innovation of other markets and determining the lagged terms for the maximum absolute value of the other markets' responses. The results show that the most important subnational markets in Australia do not point to Sydney, rather towards Canberra and Hobart, while the Darwin market plays a role of buffer. The safest markets are Sydney and Melbourne. This study helps to predict house price movement trends in eight capital cities.

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The study described in this paper focuses on testing the short-run and
long-run relationships between house price and consumer price indices in Australia’s capital cities from 1998 to 2008. The autoregressive distributed lag model is adopted to obtain the estimates of the short-run relationships, while the error correction model is used to investigate the long-run relationships. The t-statistic is used to compute the significance of these relationships. The research results give no evidence that house price indices are correlated with consumer price indices in the short run. However, the long-run relationships between house and consumer price indices exist in most of the cities.

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This paper investigates the existence of house price bubbles in Australia's eight capital cities in recent years by using quantitative analyses including Johansen cointegration test, Granger causality test, impulse response and Chow forecast test. While interactions between house prices and market fundamentals are discussed in long-run and causal estimations, shocks from the market fundamentals to house prices are investigated in generalized impulse response analyses. Findings from estimating house price bubbles for eight capital cities suggest that there was an obvious house price bubble in Perth, while a slight house price bubble occurred in Sydney. In contrast, house prices in Adelaide and Darwin can be explained very well by market fundamentals, while house prices in Melbourne, Brisbane, Hobart and Canberra were undervalued in the study period.

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House prices in the Australian capital cities have been increasing over the last two decades. An over 10% average annual increase arises in the capital cities. In Melbourne, Brisbane and Perth, the house prices increased by more than 15% annually, while the house prices in Darwin increased by even higher at about 21%. It is surprising that, after a decrease in 2008, the house prices in the Australian capital cities show a strong recovery in their last financial year’s increase. How to read the house prices in cities across a country has been an issue of public interest since the late 1980s. Various models were developed to investigate the behaviours of house prices over time or space. A spatio-temporal model, introduced in recent literature, appears advantages in accounting for the spatial effects on house prices. However, the decay of temporal effects and temporal dynamics of the spatial effects cannot be addressed by the spatio-temporal model. This research will suggest a three-part decomposition framework in reading urban house price behaviours. Based on the spatio-temporal model, a time weighted spatio-temporal model is developed. This new model assumes that an urban house price movement should be decomposed by urban characterised factors, time correlated factors and space correlated factors. A time weighted is constructed to capture the temporal decay of the time correlated effects, while a spatio-temporal weight is constructed to account for the timevaried space correlated effects. The house prices of the Australian capital cities are investigated by using the time weighted spatio-temporal model. The empirical findings suggest that the housing markets should be clustered by their geographic locations. The rest parts of this paper are organised as follows. The following section will present a principle for reading urban house prices. The next section will outline the methodologies modelling the time weighted spatio-temporal model. The subsequent section will report the relative data and empirical results, while the final section will generate the conclusions.

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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.

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Motivated by a novel stylized fact { countries with isolated capital cities display worse quality of governance { we provide a framework of endogenous institutional choice based on the idea that elites are constrained by the threat of rebellion, and that this threat is rendered less e ective by distance from the seat of political power. In established democracies, the threat of insurgencies is not a binding constraint, and the model predicts no correlation between isolated capitals and misgovernance. In contrast, a correlation emerges in equilibrium in the case of autocracies. Causality runs both ways: broader power sharing (associated with better governance) means that any rents have to be shared more broadly, hence the elite has less of an incentive to protect its position by isolating the capital city; conversely, a more isolated capital city allows the elite to appropriate a larger share of output, so the costs of better governance for the elite, in terms of rents that would have to be shared, are larger. We show evidence that this pattern holds true robustly in the data. We also show that isolated capitals are associated with less power sharing, a larger income premium enjoyed by capital city inhabitants, and lower levels of military spending by ruling elites, as predicted by the theory.

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Capital cities that are not the economic centers of their nations – so-called secondary capital cities (SSCs) – tend to be overlooked in the field of political science. Consequentially, there is a lack of research and resulting theory describing their local economy and their public policies. This paper analyzes how SCCs try to develop and position themselves through the formulation of locational policies. By linking three different theoretical strands – the Regional Innovation System (RIS) approach, the concept of locational policies, and the regime perspective – this paper aims for constructing a framework to study the economic and political dynamics in SCCs.

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Capital cities that are not the economic centers of their nations – so-called secondary capital cities (SSCs) – tend to be overlooked in the field of political science. Consequentially, there is a lack of research and resulting theory describing their political economy. This paper proposes a comparative research framework which analyzes how external pressures are influencing the relevant policy makers in the process of (re)positioning the SCC.