Academic literature on the topic 'Corporations Australia Finance Econometric models'

Not so long ago, defining green energy was generally straightforward: renewables. It may not have been quite that simple, but the development of agreed-upon definitions based on science has become much more complex and contentious, even within the past year. It’s not just a highbrow debate about semantics. The standardization of criteria or a widely accepted taxonomy is critical as the focus increases on not only greenwashing, but on the actual processes and technologies enabling what were thought of as at least “greener” energy. The hammering out of definitions is needed to keep the energy transition moving forward globally. This scrutiny affects the options for companies seeking alternatives in carbon markets where the price of permits for emitting a tonne of CO2 is escalating. In early February, the price of CO2 permits in the EU reached a record high above 96 Euros ($109)/tonne CO2. Reuters reported that the carbon price has risen more than 200% since the start of 2021, partly due to high natural gas prices and the switch made to coal by some power generators. This resulted in higher emissions and increased the demand for permits. In January, the EU Platform on Sustainable Finance, comprising members from utilities, banks, nongovernmental organizations, and corporations, rejected the EU Commission’s draft sustainable finance rules which proposed labeling nuclear power and natural gas as green transition fuels. Nuclear projects permitted until 2045 were to be classified as green, but only if countries can safely dispose of the radioactive waste. Gas was to be included until 2030 with emissions thresholds specified. The EU Platform concluded that even if a gas plant stays under the emissions threshold, it “is not green at any point in its life.” Nuclear energy was acknowledged as already being part of the transitioning energy system and having near to zero greenhouse-gas emissions, but it would not meet the taxonomy’s requirement to “do not significant harm” to the environment because of the toxic waste that cannot be recycled or reused. The EU Commission’s taxonomy will be sent to the European Parliament and Council for review. Blue hydrogen was questioned as a transition fuel by a peer-reviewed study published in August 2021 in Energy Science & Engineering by coauthors from Cornell and Stanford universities. They wrote, “Far from being low-carbon, greenhouse-gas emissions from the production of blue hydrogen are quite high, particularly due to the release of fugitive methane. … Perhaps surprisingly, the greenhouse-gas footprint of blue hydrogen is more than 20% greater than burning natural gas or coal for heat and some 60% greater than burning diesel oil for heat, again with our default assumptions.” They added, “Our analysis assumes that captured carbon dioxide can be stored indefinitely, an optimistic and unproven assumption. Even if true though, the use of blue hydrogen appears difficult to justify on climate grounds.” In a study published last month in the Proceedings of the National Academy of Sciences, researchers at the University of Wisconsin-Madison combined econometric analyses, land use observations, and biophysical models to estimate the realized effects of the US Environmental Protection Agency’s Renewable Fuel Standard (RFS) mandate to partially replace petroleum-based fuels with biofuels. They found that the RFS increased corn prices by 30% and the prices of other crops by 20%, which, in turn, expanded US corn cultivation by 8.7% and total cropland by 2.4% in the years following the policy’s enactment (2008 to 2016). “These changes increased annual nationwide fertilizer use by 3 to 8%, increased water-quality degradants by 3 to 5%, and caused enough domestic land use change emissions such that the carbon intensity of corn ethanol produced under the RFS is no less than gasoline and likely at least 24% higher. These tradeoffs must be weighed alongside the benefits of biofuels as decision makers consider the future of renewable energy policies and the potential for fuels like corn ethanol to meet climate mitigation goals.” The move toward energy transition has been pivotal for our industry and many others. It could be argued that no country, business, or individual will remain unaffected by the changes in progress and yet to come. “Transition” is defined as “the process or a period of changing from one state or condition to another.” And this process will take time, effort, technology, buy-in, scientific study and verification … and consensus, which may be the most challenging piece of all. A significant announcement demonstrating the application and acceptance of a scientific taxonomy was Santos Ltd.’s recent booking of 100 million metric tons of CO2 storage capacity in the Cooper Basin in South Australia. The company believes it represents the industry’s first-ever booking to be made under SPE’s CO2 Storage Resource Management System.

Purpose – Directors play a hard-to-quantify but critical role in the success of corporations. Outside directors supplement the firm-specific knowledge of inside directors by providing expertise and monitoring. Prior research finds that outside directors who are commercial bankers can be both beneficial and costly to large, non-financial corporations. Smaller, bank-dependent corporations should benefit more than large firms from the services banker directors provide, but may also be more prone to the costs they can impose. The purpose of this paper is to investigate the influence of bank dependency on appointments of banker directors. Design/methodology/approach – The author estimates models relating the probability of a first-time banker-director appointment to proxies of bank dependency on data for a matched sample of firms with and without banker directors drawn from a size-representative sample of Compustat firms. Findings – Bank-dependent firms are less likely to appoint bankers as directors than bank-independent firms. Bank-dependent firms are also less likely to appoint bankers whose employers are firms’ creditors (i.e. affiliated bankers). Bank-dependent and bank-independent firms are indistinguishable in their probabilities of appointing unaffiliated bankers as directors. Practical implications – Bank-dependent firms with unexploited growth opportunities appear unable to ameliorate their financial constraints by having banker directors. Appointing retired bankers to boards may give firms the benefits of banker directors without the costs. Originality/value – This paper is the first to: document the prevalence of banker directors at smaller corporations; present econometric evidence on banker-director appointments at firms ranging from small to large; and identify bank dependency as a factor limiting appointments of affiliated banker directors.

Of all the sub‐sectors of the national economy, the banking industry and the property market have arguably been most severely affected by the current recession. Thus, the prevailing credit crunch in real estate finance and market conditions have implication for disposal and valuations of real estate for mortgage purposes. The study examined whether forced sale valuations of mortgage properties were a good proxy for their auction sale prices. Relevant data involving 67 auction sales of foreclosed residential property transactions together with their contemporaneous forced sale valuations were pooled together in Lagos Metropolis during the period 1994 to 2003 from sample of estate surveying and valuation/auctioneering firms, the lending institutions and the Nigeria Deport Insurance Corporation. The data obtained were analyzed with the aid of frequency distributions and multiple regression models. The study revealed, amongst others, that forced sale values are not good proxies for auction sale prices as against the conclusions of previous studies on accuracy of open market valuations either in Nigeria or other countries like UK, USA and Australia. The implications of the foregoing conclusions on the lending decisions and valuation profession in the country were further examined in the paper.

The objective of this research is to analyze the influence that monetary policies exert on the composition of the indebtedness of Brazilian corporations. From this objective, 2 hypotheses derive. The first analyzes the sample aggregate and the second directs the tests to the productive sectors. The study sample is composed of 220 companies: 84 of consumer goods, 89 of capital goods and 47 of public utility. The data collected refer to the years 2009 to 2019. The methodology used for data analysis is through panel data models, using the GMM approach. According to the results, it can be concluded - in the light of the macroeconomics of capital - that the composition of the firms' indebtedness can be determined by the market moments defined by the monetary policies, so that such influence is different depending on the sector to which the companies are located in the production chain. These results complement the literature that studies the impacts of monetary policies and macroeconomic variables on corporate finance, mainly through econometric modeling based on accounting data.

PurposeThere has been declining home ownership and increased acceptance of long-term renting in many western countries including Australia; this has created a problem when examining housing markets as there are dual demand and include both owner-occupiers and investors. The purpose of this paper is to examine the long-run relationship between house prices, housing supply and demand, and to estimate the effects of the two types of demand (i.e. owner-occupier and investor) on house prices.Design/methodology/approachThe econometric techniques for cointegration with vector error correction models are used to specify the proposed models, where the housing markets in the Australian states and territories illustrate the models.FindingsThe results highlight the regional long-run equilibrium and associated patterns in house prices, the level of new housing supply, owner-occupier demand for housing and investor demand for housing. Different types of markets were identified.Practical implicationsThe findings suggest that policies that depress the investment demand can effectively prevent the housing bubble from further building up in the Australian states. The empirical findings shed light in the strategy of maintaining levels of housing affordability in regions where owner-occupiers have been priced out of the housing market.Originality/valueThere has been declining home ownership and increased acceptance of long-term renting in many western countries including Australia; this has created a problem when examining housing markets as there are dual demand and include both owner-occupiers and investors. This research has given to the relationship between supply and dual demand, which includes owner-occupation and investment, for housing and the influence on house prices.

Purpose The purpose of this paper is to investigate the relationship of financial ratios and non-financial factors of successful and failed corporations in the USA. Specifically, the authors provide evidence on whether financial ratios and non-financial factors can be jointly included as indicators to improve the predictive capacity of organisational success or failure in different countries and sectors. Design/methodology/approach The paper utilises a mixed method exploratory case study focussing on listed corporations in the US and Australian manufacturing, agriculture, finance and property sectors. Findings The financial ratio findings demonstrate that (with the exception of the failed Australian manufacturing sector) the integrated multi-measure (IMM) ratio approach consistently provides a higher classification rate for the failed and successful groups than those provided by an individual measure. In all cases the IMM method scored higher for US companies (with the exception of the failed Australian property sector). The findings also show that irrespective of the country location or sector, non-financial factors such as board composition and managements’ involvement in organisational strategy impact on a corporation’s success or failure. Practical implications The findings reveal that non-financial factors occur prior to financial ratios when attempting to predict organisational success or failure and the IMM approach enables a more thorough examination of the predictive ability of financial ratios for US and Australian organisations. This intuitively indicates that when combined with financial ratios, non-financial factors may be a useful predictor of corporate success or failure across countries and sectors. Originality/value Sound internal processes and the identification of both financial ratios and non-financial factors can be utilised to improve the reliability of financial failure models, enable corrective and preventative steps to be implemented by management and potentially reduce the costs of failure for US and Australian organisations.

Traditional financial theories see capital structure as a result of mainly financial, tax and growth factors (Modigliani & Miller, 1958). But corporate governance theories (Jensen & Meckling, 1976) and business strategy theories (Barton & Gordon, 1988) suggest that ownership structure and ownership concentration, product diversification and asset specificity may also influence capital structure. Focusing on the examination of the determinants of capital structure in Chinese listed companies, this research goes beyond financial factors and considered business strategy and corporate governance approaches, and their impact on capital structure, in a transitioning Chinese context where institutions, expertise and regulatory processes are different to, but converging on, Western approaches. A panel data set of 1,098 Chinese listed companies for the period of 1991 to 2000 was collected from published sources, and conventional and innovative econometric methodologies were used to model a range of relationships between capital structure and its financial and non-financial determinants. The statistical approaches used in this study included Ordinary Least Squares Model and also Linear Mixed Model, which is a powerful tool to examine panel data where independence of explanatory variables is not assumed. The analysis also involved Hox’s model building procedures to measure model fit. The capital structure of listed companies in both the Shenzhen Stock Exchange and the Shanghai Securities Exchange is positively related to a firm’s tax rate, growth and capital intensity and negatively related to a firm’s profit and size. Other financial factors such as tangibility, risk and duration are non-significant. The capital structure of listed companies, particularly in the Shenzhen Stock Exchange, is positively related to product diversification and negatively related to asset specificity. The capital structure of listed companies in the Shanghai Securities Exchange is positively related to government ownership and ownership concentration of the largest shareholder and negatively related to legal person ownership and ownership concentration of the ten largest shareholders. The data and modelling support financial and non-financial determinants of capital structure. In particular, information asymmetry, business diversity and asset specificity have a significant impact on capital structure. In addition the empirical work in the study supports agency cost explanations of debt and equity. Finally the research demonstrates that the two main financial markets in China, Shenzhen and Shanghai, have operated differently but are converging towards a common norm. The research contributes to the general field of capital structure and provides valuable insights into the nature of the Chinese firm and the evolution of the Chinese financial system.
Doctor of Philosophy

Traditional financial theories see capital structure as a result of mainly financial, tax and growth factors (Modigliani & Miller, 1958). But corporate governance theories (Jensen & Meckling, 1976) and business strategy theories (Barton & Gordon, 1988) suggest that ownership structure and ownership concentration, product diversification and asset specificity may also influence capital structure. Focusing on the examination of the determinants of capital structure in Chinese listed companies, this research goes beyond financial factors and considered business strategy and corporate governance approaches, and their impact on capital structure, in a transitioning Chinese context where institutions, expertise and regulatory processes are different to, but converging on, Western approaches. A panel data set of 1,098 Chinese listed companies for the period of 1991 to 2000 was collected from published sources, and conventional and innovative econometric methodologies were used to model a range of relationships between capital structure and its financial and non-financial determinants. The statistical approaches used in this study included Ordinary Least Squares Model and also Linear Mixed Model, which is a powerful tool to examine panel data where independence of explanatory variables is not assumed. The analysis also involved Hox’s model building procedures to measure model fit. The capital structure of listed companies in both the Shenzhen Stock Exchange and the Shanghai Securities Exchange is positively related to a firm’s tax rate, growth and capital intensity and negatively related to a firm’s profit and size. Other financial factors such as tangibility, risk and duration are non-significant. The capital structure of listed companies, particularly in the Shenzhen Stock Exchange, is positively related to product diversification and negatively related to asset specificity. The capital structure of listed companies in the Shanghai Securities Exchange is positively related to government ownership and ownership concentration of the largest shareholder and negatively related to legal person ownership and ownership concentration of the ten largest shareholders. The data and modelling support financial and non-financial determinants of capital structure. In particular, information asymmetry, business diversity and asset specificity have a significant impact on capital structure. In addition the empirical work in the study supports agency cost explanations of debt and equity. Finally the research demonstrates that the two main financial markets in China, Shenzhen and Shanghai, have operated differently but are converging towards a common norm. The research contributes to the general field of capital structure and provides valuable insights into the nature of the Chinese firm and the evolution of the Chinese financial system.
Doctor of Philosophy

[Truncated abstract] This thesis examines competing asset-pricing models in Australia with the goal of establishing the model which best explains cross-sectional stock returns. The research employs Australian equity data over the period 1980-2001, with the major analyses covering the more recent period 1990-2001. The study first documents that existing asset-pricing models namely the capital asset pricing model (CAPM) and domestic Fama-French three-factor model fail to meet the widely applied Merton?s zero-intercept criterion for a well-specified pricing model. This study instead documents that the US three-factor model provides the best description of Australian stock returns. The three US Fama-French factors are statistically significant for the majority of portfolios consisting of large stocks. However, no significant coefficients are found for portfolios in the smallest size quintile. This result initially suggests that the largest firms in the Australian market are globally integrated with the US market while the smallest firms are not. Therefore, the evidence at this point implies domestic segmentation in the Australian market. This is an unsatisfying outcome, considering that the goal of this research is to establish the pricing model that best describes portfolio returns. Given pervasive evidence that liquidity is strongly related to stock returns, the second part of the major analyses derives and incorporates this potentially priced factor to the specified pricing models ... This study also introduces a methodology for individual security analysis, which implements the portfolio analysis, in this part of analyses. The technique makes use of visual impressions conveyed by the histogram plots of coefficients' p-values. A statistically significant coefficient will have its p-values concentrated at below a 5% level of significance; a histogram of p-values will not have a uniform distribution ... The final stage of this study employs daily return data as an examination of what is indeed the best pricing model as well as to provide a robustness check on monthly return results. The daily result indicates that all three US Fama-French factors, namely the US market, size and book-to-market factors as well as LIQT are statistically significant, while the Australian three-factor model only exhibits one significant market factor. This study has discovered that it is in fact the US three-factor model with LIQT and not the domestic model, which qualifies for the criterion of a well-specified asset-pricing model and that it best describes Australian stock returns.

This study deals with the estimation of the optimal hedge ratios using various econometric models. Most of the recent papers have demonstrated that the conventional ordinary least squares (OLS) method of estimating constant hedge ratios is inappropriate, other more complicated models however seem to produce no more efficient hedge ratios. Using daily AOIs and SPI futures on the Australian market, optimal hedge ratios are calculated from four different models: the OLS regression model, the bivariate vector autoaggressive model (BVAR), the error-correction model (ECM) and the multivariate diagonal Vcc GARCH Model. The performance of each hedge ratio is then compared. The hedging effectiveness is measured in terms of ex-post and ex-ante risk-return traHe-off at various forcasting horizons. It is generally found that the GARCH time varying hedge ratios provide the greatest portfolio risk reduction, particularly for longer hedging horizons, but hey so not generate the highest portfolio return.

This research questions whether technical trading rules can help predict stock price movements for a sample of stocks selected from four equity markets from the Asia-Pacific region: Australia, Malaysia, Hong Kong and Thailand for the period 1989-2008. The research is split into two stages. Stage-1 of the research tests the predictability of technical trading rules against a buyand- hold strategy. The variable moving average (VMA), fixed moving average (FMA) and the trading range break (TRB) trading rules are applied to this research. Economic predictability of these rules is examined by comparing returns conditional on a trading rule buy (sell) signal against an unconditional buy-and-hold return. Any existence of excess returns can thus be established. This follows with a statistical analysis of returns using a traditional t-test methodology. Traditional statistical tests assume normally distributed returns with independent observations and a non-changing distribution across time. In Stage-2 of this research a bootstrap checks whether features such as non-normality, time-varying moments and serial correlation bias test statistics. The bootstrap involves assumptions regarding the underlying returns generating process (RGP) and allows returns conditional on a trading rule buy (sell) signal from the original stock price series to be compared with conditional returns simulated from four common null models: RW, AR (1), GARCH-M and E-GARCH models. Simulated p-values are calculated in conjunction with simulated distributions and are applied in lieu of the theoretical normal distribution. Given this process it is possible to infer as to whether non-linear dependencies in returns can be captured by any of the three trading rules. Given the null model output standard t-test outcomes of predictability of technical trading rules may be diminished and/or eliminated. Conclusions are drawn as to the predictability and profitability of the VMA, FMA and TRB trading rules when applied to the chosen stock samples. Findings of this research indicate returns conditional on technical trading rules exceed unconditional buy-and-hold returns for all stocks. Thai sample output indicates strong support in favour of the predictability of standard test results supporting the use of technical trading rules. Output for Australia, Hong Kong and Malaysia indicates that previous standard t-test outcomes of predictability may be diminished and/or eliminated. This implies that the underlying RGP may be characterised by underlying features of some/all of the stochastic models.

This thesis provides more precise characterisation of patterns, causes and consequences of takeover activity in Australia over three decades spanning from 1972 to 2004. The first contribution of the thesis is to characterise the time series behaviour of takeover activity. It is found that linear models do not adequately capture the structure of merger activity; a non-linear two-state Markov switching model works better. A key contribution of the thesis is, therefore, to propose an approach of combining a State-Space model with the Markov switching regime model in describing takeover activity. Experimental results based on our approach show an improvement over other existing approaches. We find four waves, one in the 1980s, two in the 1990s, and one in the 2000s, with an expected duration of each wave state of approximately two years. The second contribution is an investigation of the extent to which financial and macro-economic factors predict takeover activity after controlling for the probability of takeover waves. A main finding is that while stock market boom periods are empirically associated with takeover waves, the underlying driver is interest rate level. A low interest rate environment is associated with higher aggregate takeover activity. This relationship is consistent with Shleifer and Vishny (1992)'s liquidity argument that takeover waves are symptoms of lower cost of capital. Replicating the analysis to the biggest takeover market in the world, the US, reveals a remarkable consistency of results. In short, the Australian findings are not idiosyncratic. Finally, the implications for target and bidder firm shareholders are explored via investigation of takeover bid premiums and long-term abnormal returns separately between the wave and non-wave periods. This represents the third contribution to the literature of takeover waves. Findings reveal that target shareholders earn abnormally positive returns in takeover bids and bid premiums are slightly lower in the wave periods. Analysis of the returns to bidding firm shareholders suggests that the lower premiums earned by target shareholders in the wave periods may simply reflect lower total economic gains, at the margin, to takeovers made in the wave periods. It is found that bidding firms earn normal post-takeover returns (relative to a portfolio of firms matched in size and survival) if their bids are made in the non-wave periods. However, bidders who announce their takeover bids during the wave periods exhibit significant under-performance. For mergers that took place within waves, there is no difference in bid premiums and nor is there a difference in the long-run returns of bidders involved in the first half and second half of the waves. We find that none of theories of merger waves (managerial, mis-valuation and neoclassical) can fully account for the Australian takeover waves and their effects. Instead, our results suggest that a combination of these theories may provide better explanation. Given that normal returns are observed for acquiring firms, taken as a whole, we are more likely to uphold the neoclassical argument for merger activity. However, the evidence is not entirely consistent with neo-classical rational models, the under-performance effect during the wave states is consistent with the herding behaviour by firms.