937 resultados para error correction model


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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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Research on construction prices is significant for contractors and traders. A comprehensive understanding of construction prices may influence crucial decisions in business operation and arbitrage activities. This study focuses on the cointegration relationships of regional construction prices in Australia by using a range of econometric techniques including the stationarity test, the Engle-Granger cointegration approach and error correction model. The cointegration relationships amongst the regional construction prices are detected in this study. The application of the Engle-Granger cointegration approach examines the long run equilibrium relationships within the regional markets, and the error correction models explore the short run disequilibrium relationships. Results of this study suggest that the economic system in which construction industry participants operate is characterised by a highly competitive integrated marketplace. Furthermore, the causalities and diffusion patterns among the construction price indices in six states and two territories of Australia are drawn by the cointegration analysis. These outcomes reveal a pattern of diffusion paths and network linkages among the six states and two territories, and then expose the regional price linkages.

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Studies on market convergence are well considered in the literature. However, the majority of the previous research focused on housing markets and few studies have concentrated on construction markets. Owing to a simultaneously dramatic increase in the construction prices of the sub-markets in the building construction sector in Australia, this paper aims to identify the convergence among these markets, involving house construction market, other-residential building construction market, and non-residential building construction market. To achieve it the Granger causality test and generalized response function depending on the vector error correction model with the quarterly data of Australia’s eight states from 1998 to 2010 will be applied. Based upon the econometric tests, the price diffusion patterns among these construction markets have been identified. Research on the convergences of construction markets not only helps construction firms perform well in business operations and arbitrage activities, but also provides policy makers with useful information for enacting effective construction policies for national perspectives and approaches to infrastructure planning.

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This research has contributed to literature by identifying the impacts of monetary policy and global economic turbulence on the supply side of the housing sector under a vector error correction model. The research outcomes provided policy makers with an insight to change Australia's housing shortage and declining housing affordability.

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New housing supply in Australia has been experiencing a low rate of increase in conjunction with a dramatic increase in residential construction costs since the 1990s. This study aims to estimate the relationship between new housing supply and residential construction costs with the regional heterogeneities. Based on a panel error correction model, it can be identified that there is a causal link as well as a significant correlation between new housing supply and construction costs in the Australian sub-national housing construction markets. The model developed in this research assists policy makers to better understand the nature of the supply side of the housing sector and then enact appropriate policies to improve the new housing supply in Australia.

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The main purpose of this paper is to extend the empirical research on the behavior of credit spreads on the USD denominated Malaysian bonds. We find that international political events have more influence on the changes of bond yield spreads from Malaysian USD issues than domestic events. Significant results are consistent across different issues. However, the resignation by the former Prime Minister, Dr Mahathir Mohamad, created a mixed response from the market. Using an error correction model, this study also found that the monetary policy by the US Federal Reserve has a long-term and significant impact on the behavior of the Malaysian USD issues. This study also provides further evidence that the current theoretical framework is sufficient to explain changes in the credit spread of bonds issued by the emerging market.

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Housing supply is one of important components of the housing sector. Compared with an increasingly strong housing demand, the growth rates of total housing stock in Australia have exhibited a downward trend since the end of the 1990s whilst the significant adjustments in the Australian monetary policy were being implemented. This research aims to estimate the nature of the relationship between housing supply and monetary policy by a vector error correction model. According to the empirical results, a transmission pattern comprised of the indicators associated with housing supply and monetary policy can be identified, which suggests that there is a significant interrelationship between monetary policy and the supply side of the housing sector in Australia.

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The supply of new housing in Australia has been experiencing a low increase rate since the 1990s in conjunction with an increasingly strong housing demand. On the contrary, residential construction costs across Australia?s states maintained dramatic increases simultaneously. Economic theory suggests that new housing supply is correlated to the costs of residential constructions. However, few empirical studies have focused on examining this relationship for Australian housing markets. To comprehensively investigate the relationship between the supply of new housing and residential construction costs a function for new housing supply considering the effects of regional heterogeneities is introduced in this study. By estimating a panel error correction model (ECM) applicable for quantifying the correlation with regional heterogeneities, this research identifies that a causal link and a strong correlation exist in between new housing supply and residential construction costs in Australia.

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The late-2000s global financial crisis has wrought dramatic impacts on the construction industry. However, the issue of whether the crisis influenced the behaviours of the construction industry has not been addressed yet. This research presents an econometric approach to investigating the effects of the recent global financial crisis on construction labour productivity. By employing the error correction model and panel regression methods, the direct and indirect effects of the financial crisis on the changes in Australian construction labour productivity are explored at national and state levels. Neither the direct nor the indirect effects appear statistically significant. The results indicate that the direct effect of the financial crisis drives up construction labour productivity at the national level, while the indirect effect diminishes productivity. The effects of the financial crisis on the state construction labour productivity vary from state to state. The financial crisis influenced construction labour productivity directly and significantly in the northern and eastern regions, while the direct effects appear not significant in the other states and territories. The indirect effects of the financial crisis on productivity are statistically significant in three regions: the Australian Capital Territory, the Northern Territory and Western Australia. By comparison, the model with the financial effects fails to provide more accurate simulating results. As such, this research concludes that the influence of the late-2000s financial crisis on Australian national and state construction labour productivity is limited.

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We examine the relationship between Chinese aggregate production and consumption of three main energy commodities: coal, oil and renewable energy. Both autoregressive distributed lag (ARDL) and vector error correction modeling (VECM) show that Chinese growth is led by all three energy sources. Economic growth also causes coal, oil and renewables consumption, but with negative own-price effects for coal and oil and a strong possibility of fuel substitution through positive cross-price effects. The results further show coal consumption causing pollution, while renewable energy consumption reduces emissions. No significant causation on emissions is found for oil. Hence, making coal both absolutely and relatively expensive compared to oil and renewable energy encourages shifting from coal to oil and renewable energy, thereby improving economic and environmental sustainability.