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Using historical data on energy from (Malanima 2020) and GDP from the Maddison Project Database, this paper investigates the energy-growth nexus in a less-studied region, mainly Australia and New Zealand, since 1870. The long annual series allow meaningful application of recently developed time-varying and quantile Granger causality analysis. Results indicate that there is a bi-directional Granger causal relationship between economic growth and energy, coal, and oil consumption at both ends of the distribution, and during various time periods over the past 150 years. Little evidence is found on the Granger causal relationship from gas consumption to economic growth, but some evidence on the direction from economic growth to gas consumption. The Granger causal relationships between electricity consumption and GDP change over time, but results suggest much closer links between the two in most recent decades, and big (positive and negative) changes in electricity consumption significantly Granger causes economic growth. [ABSTRACT FROM AUTHOR]

To model the price, price volatilities and their inter-relationships of the Australian wholesale spot electricity markets, the multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) models have been applied (Higgs, Energy Economics 31 (5):748–56, 2009) and these models were extended to the sophisticated GARCH-vine-copula model (Apergis et al., Energy Economics 90:104834, 2020) recently. Stochastic volatility (SV) models, as flexible alternatives to GARCH models, have demonstrated their superiority in many financial applications. However, the use of SV models in the modeling of electricity markets is still quite limited. This paper investigates existing multivariate SV models and proposes efficient SV models with bilateral Granger causality and skew error distributions, to model the price and price volatilities of three pairs of markets, selected from four regional electricity markets in Australia, which are shown to be highly correlated in the Higgs (Energy Economics 31 (5):748–56, 2009) study. Bayesian approach using Markov chain Monte Carlo (MCMC) method is adopted and models are implemented using the software OpenBUGS. Based on Deviance Information Criterion, the models with skew error distributions perform better than those with symmetric distributions. [ABSTRACT FROM AUTHOR]

This paper analyzes the relationship between interest rates, inflation expectations and inflation rates in Australia using the approach suggested by Toda and Yamamoto (1995) to test for Granger causality. The empirical evidence reported here suggests that uni-directional Granger causality is running from medium- and long-term government bond yields to short-term inflation expectations as measured by a survey among consumers. Moreover, there is bidirectional Granger causality among short-term interest rates and short-term inflation expectations among consumers. Additionally, interest rates and the sentiment data measuring inflation expectations can help to predict inflation rates. These findings are supportive for the Fisher effect and also seem to indicate that the bond market is quite efficient predicting inflation rates. Furthermore, some problems of more traditional tests of the Fisher hypothesis are discussed. In this context the role of financial deregulation in Australia is examined. Thus, the Lucas critique seems to be of some relevance testing the Fisher effect (see Lucas, 1976). [ABSTRACT FROM AUTHOR]

Despite numerous studies investigating house price diffusion between regional cities, few have considered a spillover effect among housing submarkets within a metropolitan city. This study expands upon the limited literature to examine house price diffusion of housing submarkets (namely, low-priced and high-priced submarkets) in Greater Sydney, one of the most diverse housing markets in Australia, using convergence tests, cointegration techniques, Granger causality and dynamic ordinary least square cointegration tests. The results show that a long-run relationship in house prices exists between these two submarkets in Greater Sydney. Importantly, the empirical results show that a large degree of diffusion takes place from the less prosperous submarket to the high-end submarket. This supports the equity transfer hypothesis via a filtering process in which house prices in the low-priced submarket will be transmitted into the high-priced submarket. The study also finds that the low-priced submarket is the primary reactor to changes in economic fundamentals. These findings have some profound implications for policy-makers and housing investors. [ABSTRACT FROM AUTHOR]

The climate system is an excellent example of a "complex system" since there is an interplay and inter-relation of several climate variables. Variables such as the Standardized Precipitation Index (SPI) are used to indicate the drought climate condition – a negative (or positive) value of SPI would imply a dry (or wet) state in a region. It is difficult to identify the factors influencing the SPI or their inter-relations (including feedback loops). Here, we aim to study the complex dynamics that SPI has with the sea surface temperature (SST), El Niño Southern Oscillation (ENSO) (aka., NINO 3.4) and Indian Ocean Dipole (IOD), using a machine learning approach. Our findings are: (i) IOD was negatively correlated to SPI till 2008; (ii) until 2004, SST was negatively correlated with SPI; (iii) from 2005 to 2014, the SST had swung between negative and positive correlations; (iv) since 2014, we observed that the regression coefficient (δ) corresponding to SST has always been positive; (v) the SST has an upward trend, and the positive upward trend of δ implied that SPI has been positively correlated with SST in recent years; and finally, (vi) the current value of SPI has a significant positive correlation with a past SPI value with a periodicity of about 7.5 years. Examining the complex dynamics, we used a statistical machine learning approach to construct an inferential network of these climate variables, which revealed that SST and NINO 3.4 directly couples with SPI, whereas IOD indirectly couples with SPI through SST and NINO 3.4. The system also indicated that Nino 3.4 significantly negatively affects SPI. If Nino 3.4 increases (decreases), the SPI drops (increases) considerably, leading to more drought (wet) conditions. Interestingly, there was a structural change in the complex dynamics of the four climate variables of NINO 3.4, IOD, SST, and SPI, sometime in 2008. Though a simple 12-month moving average of SPI over 58 years (1961–2018) has a negative trend towards drought, the complex dynamics of SPI with other climate variables indicate a wet season for south-west Australia. [ABSTRACT FROM AUTHOR]

Few studies have examined the link between air cargo and business travel, despite there being a generally accepted understanding that these two variables are inextricably related to each other. This paper examines the relationship between air cargo and business travel at the international level and analyses how these two variables are causally related. Moreover, we break down the sample into three major Australian states (New South Wales, Queensland, and Victoria), as each possesses a distinct flavour in trade and commerce. Utilising Granger causality methods, we have found evidence that there is a direct causal relationship between business travel and air cargo in the short run, and a bi-directional relationship in periods of 12 months and longer. The nature of the Granger causality at the state-level substantially differs from state to state, suggesting that the economic landscape of Australia’s local economy has a significant impact on the air cargo and business travel relationship. [ABSTRACT FROM AUTHOR]

Based on the premise that the Internet has the potential to generate trust, this study estimates the effects of the Internet and real GDP per capita on the creation of social capital (measured by trust) for Australia for the period 1985-2013. We use ARDL bounds testing approach (Pesaran et al., 2001) to estimate the short- and long-run relationship and Granger (1969) causality test to assess the causal linkages among the variables. Findings indicate that Internet use reduces social capital in the long-run but contributes slightly to its enhancement in the short-run. There is positive significant association between the level of real GDP per capita and the stock of social capital in the long-run while the relationship in the short-run is negative and significant. No causal link is found between Internet use and social capital while a unidirectional causality running from social capital to real GDP per capita is observed. The negative association between Internet use and the formation of social capital in the long-run may occur because the trust generated through greater online interaction is outweighed by the loss in trust arising from reduced face to face interaction. [ABSTRACT FROM AUTHOR]

This study estimates the short- and long-run effects of Internet usage and economic growth on carbon dioxide (CO) emissions using annual time series macro data for Australia for the period 1985-2012. Autoregressive distributive lag (ARDL) bounds and Gregory-Hansen structural break cointegration tests are applied. ARDL estimates indicate no significant long-run relationship between Internet usage and CO emissions, which implies that the rapid growth in Internet usage is still not an environmental threat for Australia. The study further indicates that higher level of economic growth is associated with lower level of CO emissions; however, Internet usage and economic growth have no significant short-run relationship with CO emissions. Financial development has both short-run and long-run significant positive association with CO emissions. The findings offer support in favor of energy efficiency gains and a reduction in energy intensity in Australia. However, impulse response and variance decomposition analysis suggest that Internet usage, economic growth and financial development will continue to impact CO emissions in the future, and as such, this study recommends that in addition to the existing measures to combat CO emissions, Australia needs to exploit the potential of the Internet not only to reduce its own carbon footprint but also to utilize information and communication technology (ICT)-enabled emissions abatement potential to reduce emissions in various other sectors across the economy, such as, power, renewable energy especially in solar and wind energy, agriculture, transport and service. [ABSTRACT FROM AUTHOR]

This study estimates the short- and long-run effects of the Internet usage and economic growth on electricity consumption using annual time series macro data for Australia for the period 1985–2012. ARDL bounds test for cointegration and Granger causality test for causal link are applied. Results from ARDL estimates indicate that the Internet use and economic growth stimulate electricity consumption in Australia. Internet usage and economic growth have no significant short-run relationship with electricity consumption. Multivariate Granger causality test confirms unidirectional causal link running from Internet usage to economic growth and electricity consumption. The findings are robust across different econometric specifications. The findings imply that Australia is yet to achieve electricity efficiency gains from ICT expansion and that it may pursue energy conservation policy without any adverse effect on its economy. Australia needs to promote its existing carbon capture and storage facilities, significantly boost investment in the renewable energy sector, in particular, in solar energy and build nuclear power plants for electricity generation to reduce CO 2 emissions. Also promoting green IT and IT for green might be potential means to curb environmental damage from Internet usage. A coordination between ICT policy, energy policy and growth policy is also recommended. [ABSTRACT FROM AUTHOR]

Purpose – Investment in Australia’s property market, whether directly or indirectly through Australian real estate investment trusts (A-REITs), grew remarkably since the 1990s. The degree of segregation between the property market and other financial assets, such as shares and bonds, can influence the diversification benefits within multi-asset portfolios. This raises the question of whether direct and indirect property investments are substitutable. Establishing how information transmits between asset classes and impacts the predictability of returns is of interest to investors. The paper aims to discuss these issues. Design/methodology/approach – The authors study the linkages between direct and indirect Australian property sectors from 1985 to 2013, with shares and bonds. This paper employs an Autoregressive Fractionally Integrated Moving Average (ARFIMA) process to de-smooth a valuation-based direct property index. The authors establish directional lead-lag relationships between markets using bi-variate Granger causality tests. Johansen cointegration tests are carried out to examine how direct and indirect property markets adjust to an equilibrium long-term relationship and short-term deviations from such a relationship with other asset classes. Findings – The authors find the use of appraisal-based property data creates a smoothing bias which masks the extent of how information is transmitted between the indirect property sector, stock and bond markets, and influences returns. The authors demonstrate that an ARFIMA process accounting for a smoothing bias up to lags of four quarters can overcome the overstatement of the smoothing bias from traditional AR models, after individually appraised constituent properties are aggregated into an overall index. The results show that direct property adjusts to information transmitted from market-traded A-REITs and stocks. Practical implications – The study shows direct property investments and A-REITs are substitutible in a multi-asset portfolio in the long and short term. Originality/value – The authors apply an ARFIMA(p,d,q) model to de-smooth Australian property returns, as proposed by Bond and Hwang (2007). The authors expect the findings will contribute to the discussion on whether direct property and REITs are substitutes in a multi-asset portfolio. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to address a key issue fundamental to the operation of land and housing markets, that is, the relationship between land and house prices. The study identifies possible causation between established house and vacant allotment prices using the metropolitan area of Adelaide, Australia as a case study. Design/methodology/approach – A key outcome of the study is the construction of a Site Adjusted Land Price Index against which a Quality Adjusted House Price Index is compared. Findings – The results show that there is a lagged effect of land prices on house prices and that this is significant at an interval of eight lag periods. The results also imply that the lead lag relationship between established house and vacant allotment prices is not unidirectional. This suggests that, while a change in house prices leads to a change in land prices in the short-run, the long-run position is for increasing land prices to lead to a delayed increase in house prices. Research limitations/implications – Rising house prices do not simply and solely reflect a shortage of land. There are suggested effects both immediate from house to land and delayed from land to house, particularly in a rising market. Originality/value – The lead lag relationships of both indexes are tested using Granger causality estimates to assess whether theoretical Ricardian concepts still hold in a modern urban land market. [ABSTRACT FROM AUTHOR]

This paper seeks to determine whether tourism has promoted economic growth in Australia during the last two decades. Specifically, it uses Granger Causality analysis to explore the relationship between (i) tourism expenditure and gross domestic product and (ii) tourism expenditure and expenditure on other factors known to be associated with tourism demand. According to the results, there is a bi-causal link between tourism and economic growth, indicating the possible existence of tourism-led endogenous growth. The results also suggest that food expenditure (specifically expenditure in restaurants, cafés and takeaways) may be the key to growth in the tourism sector. Evidently, expenditure in this sector may facilitate the growth of other industries through the local market, thus kickstarting a system of endogenous growth via tourism. [ABSTRACT FROM AUTHOR]

This article presents an analysis of real wages, inflation and labour productivity interrelationships using cointegration, Granger causality and, most importantly, structural change tests. Applications of tests to Australian data over the 1965 to 2007 period corroborate the presence of a structural break in 1985 and show that a 1% increase in manufacturing sector real wages led to an increase in manufacturing sector productivity of between 0.5% and 0.8%. Comparable estimates for the effect of inflation on manufacturing sector productivity have limited statistical significance. Granger causality test results suggest that real wages and inflation both Granger cause productivity in the long run. [ABSTRACT FROM PUBLISHER]

This article investigates the nature of the causal linkage between stock markets and foreign exchange markets in Australia, Canada, Japan, Switzerland, and UK from January 1992 to December 2005. Recently developed cointegration tests are employed and no evidence of a long-run relationship between the variables is found. Three variations of the Granger causality test are carried out and causality from exchange rates to stock prices is found for Canada, Switzerland, and UK; weak causality in the other direction is found only for Switzerland. The Hiemstra-Jones test is used to examine possible non-linear causality and the results indicate causality from stock prices to exchange rates in Japan and weak causality of the reverse direction in Switzerland. [ABSTRACT FROM AUTHOR]

Binswanger (2000) concluded that traditional links between stock market performance and two major macroeconomic indicators, production and GDP, broke down in the most recent US bull market. Australia's stock market also took off in the early 1980s and the objective of the present paper is to contribute to the literature on the connection between the stock market and real economic activity, using Australian data. The study finds that, unlike the US, the links between stock prices and industrial production or GDP remained strong during the high-growth phase in Australia. However, this relationship breaks down in periods of slower economic growth with contradictory empirical results for different macroeconomic indicators. The paper concludes that increasing globalisation is the most plausible explanation for this phenomenon. [ABSTRACT FROM AUTHOR]

The focus of this paper is to test the cointegrating and Granger-causal relationships between Australian short-run interest rate securities and those of the UK, US, Japan, Hong Kong, Singapore and New Zealand. A relatively new methodology known as Long Run Structural Model (LRSM) (Pesaran and Shin, 2002) followed by vector error-correction model, generalized variance decompositions, generalized impulse response, and persistence profile have been used. The findings tend to suggest that Australia's short-term interest rates are cointegrated with those of its major trading partners. The results of this paper indicate that the ability of Australian policy makers to target and manipulate domestic interest rates may be limited and that they should look to the policy decisions of the US and Japan in particular when setting domestic policy. [ABSTRACT FROM AUTHOR]

Weekend effects have been well known in many financial markets. Australia however displays its effect on Tuesdays rather than on Mondays. In this study, we investigate on the possible linkage between the US Monday and Australian Tuesday returns. We document that the Tuesday effect in Australia is one-way Granger caused by the weekend effect in the US conditional on the weekend effects in the UK and Japanese markets. Furthermore, in the post-1987 period where the US Monday returns are positively significant, the Australian Tuesday return also turns out to be positive. This latter finding provides further evidence that the anomaly in Australia is induced by the weekend effect in the US. [ABSTRACT FROM AUTHOR]