Academic literature on the topic 'Investment analysis Australia Econometric models'
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Journal articles on the topic "Investment analysis Australia Econometric models":
1
Sherris, M., L. Tedesco, and B. Zehnwirth. "Investment Returns and Inflation Models: Some Australian Evidence." British Actuarial Journal 5, no. 1 (April 1, 1999): 237–67. http://dx.doi.org/10.1017/s135732170000043x.
Abstract:
ABSTRACTThe development of stochastic investment models for actuarial and investment applications has become an important area of interest to actuaries. This paper reports the application of some techniques of modern time series and econometric analysis to Australian inflation, share market and interest rate data. It considers unit roots, cointegration and state space models. Some of the results from this analysis are not reflected in the published stochastic investment models.
2
Reddy, Wejendra, David Higgins, and Ron Wakefield. "An investigation of property-related decision practice of Australian fund managers." Journal of Property Investment & Finance 32, no. 3 (April 1, 2014): 282–305. http://dx.doi.org/10.1108/jpif-02-2014-0014.
Abstract:
Purpose – In Australia, the A$2.2 trillion managed funds industry including the large pension funds (known locally as superannuation funds) are the dominant institutional property investors. While statistical information on the level of Australian managed fund investments in property assets is widely available, comprehensive practical evidence on property asset allocation decision-making process is underdeveloped. The purpose of this research is to identify Australian fund manager's property asset allocation strategies and decision-making frameworks at strategic level. Design/methodology/approach – The research was undertaken in May-August 2011 using an in-depth semi-structured questionnaire administered by mail. The survey was targeted at 130 leading managed funds and asset consultants within Australia. Findings – The evaluation of the 79 survey respondents indicated that Australian fund manager's property allocation decision-making process is an interactive, sequential and continuous process involving multiple decision-makers (internal and external) complete with feedback loops. It involves a combination of quantitative analysis (mainly mean-variance analysis) and qualitative overlay (mainly judgement, or “gut-feeling”, and experience). In addition, the research provided evidence that the property allocation decision-making process varies depending on the size and type of managed fund. Practical implications – This research makes important contributions to both practical and academic fields. Information on strategic property allocation models and variables is not widely available, and there is little guiding theory related to the subject. Therefore, the conceptual frameworks developed from the research will help enhance academic theory and understanding in the area of property allocation decision making. Furthermore, the research provides small fund managers and industry practitioners with a platform from which to improve their own property allocation processes. Originality/value – In contrast to previous property decision-making research in Australia which has mainly focused on strategies at the property fund investment level, this research investigates the institutional property allocation decision-making process from a strategic position involving all major groups in the Australian managed funds industry.
3
Gabe, Jeremy, Spenser Robinson, Andrew Sanderford, and Robert A. Simons. "Lease structures and occupancy costs in eco-labeled buildings." Journal of Property Investment & Finance 38, no. 1 (October 4, 2019): 31–46. http://dx.doi.org/10.1108/jpif-07-2019-0098.
Abstract:
Purpose The purpose of this paper is to investigate whether energy-efficient green buildings tend to provide net lease structures over gross lease ones. It then considers whether owners benefit by trading away operational savings in a net lease structure. Design/methodology/approach Empirical models of office leasing transactions in Sydney, Australia, with wider transferability supported by analysis of office rent data in the USA. Findings Labeled green buildings are approximately four to five times more likely than non-labeled buildings to use a net lease structure. However, despite receiving operational savings, tenants in net leases pay higher total occupancy costs (TOC), benefiting owners. On average, the increase in TOC paid by tenants in a net lease is equal to or greater than savings attributed to an eco-labeled building. Practical implications A full accounting of TOC in eco-labeled buildings suggests that net lease structures provide numerous benefits to owners that offset the loss of trading away operational savings. Originality/value The principal-agent market inefficiency, or “split incentive,” is a widely cited barrier to private investment in energy-efficient building technology. Here, a uniquely broad look at rental cash flows suggests its role as a barrier is exaggerated.
4
Perera, Treshani, David Higgins, and Woon-Weng Wong. "The evaluation of the Australian office market forecast accuracy." Journal of Property Investment & Finance 36, no. 3 (April 3, 2018): 259–72. http://dx.doi.org/10.1108/jpif-04-2017-0029.
Abstract:
Purpose Property market models have the overriding aim of predicting reasonable estimates of key dependent variables (demand, supply, rent, yield, vacancy and net absorption rate). These can be based on independent drivers of core property and economic activities. Accurate predictions can only be conducted when ample quantitative data are available with fewer uncertainties. However, a broad-fronted social, technical and ecological evolution can throw up sudden, unexpected shocks that result in the econometric outputs sceptical to unknown risk factors. Therefore, the purpose of this paper is to evaluate Australian office market forecast accuracy and to determine whether the forecasts capture extreme downside risk events. Design/methodology/approach This study follows a quantitative research approach, using secondary data analysis to test the accuracy of economists’ forecasts. The forecast accuracy evaluation encompasses the measurement of economic and property forecasts under the following phases: testing for the forecast accuracy; analysing outliers of forecast errors; and testing of causal relationships. Forecast accuracy measurement incorporates scale independent metrics that include Theil’s U values (U1 and U2) and mean absolute scaled error. Inter-quartile range rule is used for the outlier analysis. To find the causal relationships among variables, the time series regression methodology is utilised, including multiple regression analysis and Granger causality developed under the vector auto regression (VAR). Findings The credibility of economic and property forecasts was questionable around the period of the Global Financial Crisis (GFC); a significant man-made Black Swan event. The forecast accuracy measurement highlighted rental movement and net absorption forecast errors as the critical inaccurate predictions. These key property variables are explained by historic information and independent economic variables. However, these do not explain the changes when error time series of the variables were concerned. According to VAR estimates, all property variables have a significant causality derived from the lagged values of Australian S&P/ASX 200 (ASX) forecast errors. Therefore, lagged ASX forecast errors could be used as a warning signal to adjust property forecasts. Research limitations/implications Secondary data were obtained from the premier Australian property markets: Canberra, Sydney, Brisbane, Adelaide, Melbourne and Perth. A limited ten-year timeframe (2001-2011) was used in the ex-post analysis for the comparison of economic and property variables. Forecasts ceased from 2011, due to the discontinuity of the Australian Financial Review quarterly survey of economists; the main source of economic forecast data. Practical implications The research strongly recommended naïve forecasts for the property variables, as an input determinant in each office market forecast equation. Further, lagged forecast errors in the ASX could be used as a warning signal for the successive property forecast errors. Hence, data adjustments can be made to ensure the accuracy of the Australian office market forecasts. Originality/value The paper highlights the critical inaccuracy of the Australian office market forecasts around the GFC. In an environment of increasing incidence of unknown events, these types of risk events should not be dismissed as statistical outliers in real estate modelling. As a proactive strategy to improve office market forecasts, lagged ASX forecast errors could be used as a warning signal. This causality was mirrored in rental movements and total vacancy forecast errors. The close interdependency between rents and vacancy rates in the forecasting process and the volatility in rental cash flows reflects on direct property investment and subsequently on the ASX, is therefore justified.
5
Masouman, Ashkan, and Charles Harvie. "Forecasting, impact analysis and uncertainty propagation in regional integrated models: A case study of Australia." Environment and Planning B: Urban Analytics and City Science 47, no. 1 (April 16, 2018): 65–83. http://dx.doi.org/10.1177/2399808318767128.
Abstract:
The integration of input–output and econometric models at regional level has gained popularity for its superior performance in forecasting employment and examining the impacts of policies. There are a number of approaches to integrate the two models. This paper examines the integration of input–output with econometric modelling using two merging methodologies, namely coupling and holistic embedding. Each methodology is analysed with respect to the accuracy of its results of total and sectoral employment forecasting. Both methodologies are applied to a regional economy in Australia. The methodology which shows superior forecasting accuracy is applied to examine the significance of sectors that generate the highest number of employments relative to other sectors.
6
Stavytskyy, Andriy, and Daria Martynovych. "THE ECONOMETRIC MODELING OF UKRAINIAN MACROECONOMIC TENDENCIES." Ekonomika 91, no. 1 (January 1, 2012): 79–92. http://dx.doi.org/10.15388/ekon.2012.0.906.
Abstract:
Econometric models are widely used in economic policies of many states. They help to build a great variety of econometric systems for every country and take into account the specifics of each economy.In this article, the structural macroeconomic models that describe the main aspects of the economic policy were applied. The interdependence between the level of inflation, the value of investment, savings, consumption, export and import transactions, taxes on the foreign trade were defined based on the analysis of the key macroeconomic parameters of Ukraine. After investigating all economic indicators, they were transformed into stationary time series for a correct use in the model. In addition, heteroscedasticity and autocorrelation of residuals were excluded in all econometric equations.As a result, the research shows that a large share of black economy leads to a rather high level of inflation in the state, because its value is primarily determined by expectations of the population under such circumstances. The paper indicates that the further export growth leads to a lower consumption growth and also to a lower growth of savings. Such a situation indicates an insufficient development of the domestic market. Investment growth has been fund not to be directly linked to consumption increase and economic development in general. Unfortunately, the main sources of investment in Ukraine are the funds of enterprises and foreign sources. The analysis shows a need to encourage public involvement into investment processes. For example, the creation of public–private partnerships is especially useful while implementing infrastructural projects.
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ZEUG-ŻEBRO, Katarzyna. "Spatial modeling of investment activity of enterprises in service sector." Scientific Papers of Silesian University of Technology. Organization and Management Series 2021, no. 150 (2021): 357–68. http://dx.doi.org/10.29119/1641-3466.2021.150.27.
Abstract:
Purpose: Due to the visible disproportions, the problem of innovation is increasingly often perceived regionally. These inequalities result from the concentration of knowledge, resources and the amount of expenditure on innovation in a few regions. The aim of the paper is to study the spatial dependence between Polish voivodships in terms of expenditure on innovative activities in enterprises in the service sector. Design/methodology/approach: For the selected variable conditioning the innovative activity of the enterprise, a classical econometric model will be built and the necessity to include the spatial factor in the modeling process will be verified. For this purpose, two spatial models will be considered: the spatial error model and spatial lag model. Findings: During the study, the hypothesis on the legitimacy of introducing spatial relationships to the econometric model describing the shaping of the amount of expenditure on innovative activities in enterprises in the service sector in Polish voivodeships was verified. The hypothesis has been verified positively – there are spatial relationships between the examined objects. Research limitations/implications: The need to take into account the spatial factor in the econometric model results in taking into account spatial estimation methods. The research used selected spatial models. Due to the limitations resulting from the availability of source data, the analysis was conducted only for voivodships in selected years. The analysis should be further deepened, e.g., by even more precise identification of the models and taking into account other neighborhood matrices - only the first-order neighborhood matrix was included in the study. Practical implications: Modeling the phenomenon of innovation. Social implications: An essential condition influencing the innovative activity of enterprises is their environment. It is the regional factors that largely influence innovation and faster development of enterprises. Originality/value: Introducing spatial relationships to the econometric model of outlays on innovative activities of enterprises in the service sector.
8
Vidales, María, and Carmelo García-Pérez. "Financing sources and social development: an empirical analysis." Social Responsibility Journal 15, no. 5 (August 5, 2019): 640–57. http://dx.doi.org/10.1108/srj-06-2018-0149.
Abstract:
PurposeThe purpose of this paper is to analyse, from an empirical point of view, the importance of each of the main sources of funding in developing countries (foreign direct investment, official development assistance, external debt and remittances) in achieving sustainable, social and inclusive development.Design/methodology/approachThe methodology followed to achieve this purpose is the construction of three econometric models. The general model incorporates as a dependent variable the Human Development Index (HDI) and, as explanatory variables, the four sources of funding indicated above, as well as three exogenous variables (human capital, corruption and natural resources). This model is complemented by two extensions that aim to analyse the behaviour of explanatory variables in reducing inequalities and improving each of the HDI components.FindingsThe results of the estimations of the econometric models show that foreign direct investment and remittances are the sources of funding with the greatest impact on achieving development. Moreover, official development assistance while not making a positive contribution to the achievement of development as a whole, could be adequate to reduce inequalities.Originality/valueThe added value of this paper consists in carrying out a joint analysis of these four sources of funding because previous researches focussed the attention on some of them, drawing partial conclusions. The conclusion of this study is that the four sources of funding analysed can be considered complementary to promote sustainable and inclusive development, although foreign direct investment has a much more important role.
9
Balash, Vladimir, Olga Balash, Alexey Faizliev, and Elena Chistopolskaya. "Economic Growth Patterns: Spatial Econometric Analysis for Russian Regions." Information 11, no. 6 (May 29, 2020): 289. http://dx.doi.org/10.3390/info11060289.
Abstract:
In this article, we analyze the σ - and β -convergence, using the data of the socio-economic development of Russian areas, and discover the role of spatial autocorrelation in regional economic development. We are considering 80 areas of the Russian Federation for the period of 2010–2017. Moran coefficients were used to estimate spatial autocorrelation. We compare the Moran scatterplots for GDP per capita and GDP growth rates per capita in 2017 and in 2014. We study the impact on raising investment in leading capital and the costs of technological innovation. We evaluate a wide range of specifications of spatial econometric models for all kinds of weight matrices. We combine standard geographical proximity with specialization proximity to assess whether they are substitutes or additions to converging economic growth rates. The weight matrix of the neighborhood and specialization similarities are used. The weight matrix of specialization similarities of the regional economies is based on data on the structure of tax payments in 82 industries. The specialization structure of the region’s economy is related to its location. Clusters obtained by matrices of specialization proximity are well separable from each other in space. The connectivity within clusters and the boundaries between them become more apparent over time. It is shown that according to the results of estimation of conditional β -convergence models, the models of 2010–2014 and 2014–2017 differ significantly. There is a statistically significant β -convergence for the period 2010–2014. There is also the presence of spatial autocorrelation. Based on the results of valuation models constructed from data after 2014, it can be concluded that the coefficient estimates for the explanatory variables are not significantly different from zero, and accordingly there is no tendency towards regional convergence in terms of economic development. The results obtained in the work are stable for the proposed models and spatial weight matrices. Territorial proximity is a more important factor than the similarity of specialization for explanation the economic growth rates of Russian regions.
10
Mahmoudi, Saeid, Nasser Nasiri, and Saeid Hajihassaniasl. "Investigating the Factors Affecting Foreign Direct Investment in Selected Muslim Countries: A Panel Data Approach." Turkish Journal of Islamic Economics 8, no. 1 (February 15, 2021): 153–75. http://dx.doi.org/10.26414/a132.
Abstract:
This paper attempts to test the effects of foreign direct investment on selected Islamic countries by using spatial econometric analysis. For this purpose, foreign direct participation and investment data from selected countries were used as panel data between 2000-2013 years period. The foreign direct investment equation is estimated using static (fixed and random effects) and dynamic (Generalized Method of Moments) methods as panel data in both conventional and spatial econometric models. The results of the estimated model show the existence of spatial correlations between selected countries and hence the use of this type of estimation is justified. On the other hand, the variables of degree of openness of the economy and economic security have a positive and significant effect on attracting foreign direct investment in the studied countries while inflation rate, economic growth and human capital solely have no significant effect on foreign direct investment in these countries.
Dissertations / Theses on the topic "Investment analysis Australia Econometric models":
1
Eadie, Edward Norman. "Small resource stock share price behaviour and prediction." Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09CM/09cme11.pdf.
2
Enzinger, Sharn Emma 1973. "The economic impact of greenhouse policy upon the Australian electricity industry : an applied general equilibrium analysis." Monash University, Centre of Policy Studies, 2001. http://arrow.monash.edu.au/hdl/1959.1/8383.
3
Galagedera, Don U. A. "Investment performance appraisal and asset pricing models." Monash University, Dept. of Econometrics and Business Statistics, 2003. http://arrow.monash.edu.au/hdl/1959.1/5780.
4
Chen, Hongqing. "An Empirical Study on the Jump-diffusion Two-beta Asset Pricing Model." PDXScholar, 1996. https://pdxscholar.library.pdx.edu/open_access_etds/1325.
Abstract:
This dissertation focuses on testing and exploring the usage of the jump-diffusion two-beta asset pricing model. Daily and monthly security returns from both NYSE and AMEX are employed to form various samples for the empirical study. The maximum likelihood estimation is employed to estimate parameters of the jump-diffusion processes. A thorough study on the existence of jump-diffusion processes is carried out with the likelihood ratio test. The probability of existence of the jump process is introduced as an indicator of "switching" between the diffusion process and the jump process. This new empirical method marks a contribution to future studies on the jump-diffusion process. It also makes the jump-diffusion two-beta asset pricing model operational for financial analyses. Hypothesis tests focus on the specifications of the new model as well as the distinction between it and the conventional capital asset pricing model. Both parametric and non-parametric tests are carried out in this study. Comparing with previous models on the risk-return relationship, such as the capital asset pricing model, the arbitrage pricing theory and various multi-factor models, the jump-diffusion two-beta asset pricing model is simple and intuitive. It possesses more explanatory power when the jump process is dominant. This characteristic makes it a better model in explaining the January effect. Extra effort is put in the study of the January Effect due to the importance of the phenomenon. Empirical findings from this study agree with the model in that the systematic risk of an asset is the weighted average of both jump and diffusion betas. It is also found that the systematic risk of the conventional CAPM does not equal the weighted average of jump and diffusion betas.
5
Wong, Siu-kei, and 黃紹基. "The performance of property companies in Hong Kong: a style analysis approach." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B26720401.
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"Study on forward premium puzzle." Thesis, 2007. http://library.cuhk.edu.hk/record=b6074212.
Abstract:
Existing literature reports a puzzle about the forward foreign exchange rate premium over the spot foreign exchange rate. The premium is often negatively correlated with subsequent changes in the spot rate, which is considered to defy economic intuition and possibly violate market efficiency. Rational explanations include non-stationary risk premia and econometric misspecifications, and the puzzle as a guide to profitable trading. Actually, the puzzle consists of three aspects of anomalies: volatility, persistence, and unbiasedness. The puzzle has not yet solved fully thus far.In the latter part of the thesis, we try to explore the behavioral aspects of the investors in the foreign currency markets (spot and forward markets). We discuss asset prices in an economy where investors derive direct utility from their consumption and adjust their utility based on the concept of habit formation and "catching up with Joneses", therefore explaining thus far the formidable unbiasedness anomaly to a certain extent. Simulation results exhibit properties similar to what has been observed in historical data.
This thesis suggests firstly that there may be no real puzzle. A simple model fits the data. Starting from examining the relations between the excess return of speculation in foreign currency forward markets and the change rates of the return rate on equity (stock) portfolio and the change rate of futures price on stock index as well as foreign currencies where the stock markets and futures market are active, publicly traded, and highly transparent markets, the source of the risk premia in the future change in spot rate has been analyzed in detail. We believe that the panel data analysis is in place for the puzzle based on its nature. In this thesis we find that the future change in spot foreign exchange rate correlate with both forward premium and especially the change rate in stock index or the change rate of futures settlement price on the stock index or on the currencies, which implies that the investors compare and employ the profitable opportunities across financial markets not just act in only one market such as just foreign exchange forward market, thus maximizing the utility or efficiency of their funds. In addition, the change rate of futures price has rather impacts on the excess return of speculation in forward currency markets, thus establishing the relation between OTC markets and publicly traded markets of foreign exchange.
Tan Yue.
"January 2007."
Adviser: Jia He.
Source: Dissertation Abstracts International, Volume: 68-09, Section: A, page: 4006.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2007.
Includes bibliographical references.
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstract in English and Chinese.
School code: 1307.
7
Mahembe, Edmore. "Foreign direct investment inflows and economic growth in SADC countries : a panel data approach." Diss., 2014. http://hdl.handle.net/10500/14232.
Abstract:
This dissertation examines the causal relationship between inward foreign direct investment (FDI)
and economic growth (GDP) in SADC countries. The study investigates, within a panel data
context, whether causation is short-term, long-term or both; and explores whether the causal
relationship between the two variables differs according to income level. The study covered a
panel of 15 SADC countries over the period 1980-2012. In order to assess whether the causal
relationship between FDI inflows and economic growth is dependent on the level of income, the
study divided the SADC countries into two groups, namely, the low-income and the middleincome
countries. The study used the recently developed panel data analysis methods to examine
this causal relationship. It adopted a three stage approach, which consists of panel unit root, panel
cointegration and Granger causality to examine the dynamic causal relationship between the two
variables. Panel unit root results show that both variables in the two SADC country groups were
integrated of order one. Panel cointegration tests showed that the variables for low-income
country group were not cointegrated, while the variables for the middle-income countries were
cointegrated. Since the low-income country group panels were not cointegrated, Grangercausality tests were conducted within a VAR framework, while causality tests for the middleincome
country group were conducted within an ECM framework. Panel Granger causality results
for the low-income countries showed no evidence of causality in either direction. However, for
the middle-income countries’ panel, there was evidence of a unidirectional causal flow from GDP
to FDI in both the long- and short- run. The study concludes that the FDI-led growth hypothesis
does not apply to SADC countries. The results imply that the recent high economic growth rates
recorded in the SADC region, especially middle-income countries, have been attracting FDI. In
other words, it is economic growth that drives FDI inflows into the SADC region, and not vice
versa. These findings have profound policy implications for the SADC region at large and
individual countries.Economics
MCOM (Economics)
Books on the topic "Investment analysis Australia Econometric models":
1
Humavindu, Michael. An econometric analysis of fixed investment in Namibia. Windhoek, Namibia: Directorate of Environmental Affairs, Ministry of Environment and Tourism, 2002.
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Carlstrom, Charles T. Investment and interest rate policy: A discrete time analysis. [Cleveland, Ohio]: Federal Reserve Bank of Cleveland, 2004.
3
Milopoulos, Christos. Investment behaviour under uncertainty: An econometric analysis of Swedish panel data. Gothenburg: Nationalekonomiska institutionen, Handelshögskolan vid Göteborgs universitet, 1993.
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Alexander, Gordon J. Portfolio analysis. 3rd ed. Englewood Cliffs, N.J: Prentice-Hall, 1986.
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Gilchrist, Simon. Putty-clay and investment: A business cycle analysis. Cambridge, MA: National Bureau of Economic Research, 1998.
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Gilchrist, Simon. Investment during the Korean financial crisis: A structural econometric analysis. Cambridge, MA: National Bureau of Economic Research, 2007.
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Gilchrist, Simon. Investment during the Korean financial crisis: A structural econometric analysis. Cambridge, Mass: National Bureau of Economic Research, 2007.
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Odada, J. E. O. Demand for investment in Namibia: An empirical analysis. Windhoek, Namibia: University of Namibia, Multi-Disciplinary Research and Consultancy Centre, Social Sciences Division, 2000.
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Krishna, Kala. Trade, investment, and growth: Nexus, analysis, and prognosis. Cambridge, MA: National Bureau of Economic Research, 1998.
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Stambaugh, Robert F. Analyzing investments whose histories differ in length. Cambridge, MA: National Bureau of Economic Research, 1997.
Book chapters on the topic "Investment analysis Australia Econometric models":
1
Bhowmik, Debesh. "Econometric Analysis of India's Foreign Direct Investment Inflows." In Foreign Direct Investments (FDIs) and Opportunities for Developing Economies in the World Market, 248–75. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3026-8.ch012.
Abstract:
In this chapter, the author explains the trend lines, random walk, stationary, structural breaks, and volatility of FDI inflows in India during 1971-2015. Both log linear and exponential trends are significant. FDI inflows are stationary and showed four structural breaks in 1985, 1994, 2000, and 2006. The author found the relation among FDI inflows, growth rate, interest rate, inflation rate, exchange rate, fiscal deficit, external debt, and trade openness with the help of Granger causality, Johansen cointegration test, and vector error correction models. Trace statistic has four cointegrating equations, and Max Eigen statistic has three cointegrating equations. The speed of the vector error correction process is more or less slow except for change in interest rate and change in inflation rate, which are significant where VECM is stable and diverging. Limitations and future scope of research is added. Policy recommendations are also included.
2
Muet, Pierre-Alain. "Econometric models of investment: a comparative study on annual data* *Originally published as “Modèles économetriques de l'investissement: une étude comparative sur données annuelles,” Annates de l'INSEE 35:85–133, 1979." In Contributions to Economic Analysis, 43–90. Elsevier, 1990. http://dx.doi.org/10.1016/b978-0-444-88105-2.50008-4.
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"Model and Model-Driven Methodology." In Post-Keynesian Empirical Research and the Debate on Financial Market Development, 115–57. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6018-2.ch006.
Abstract:
This chapter specifies the empirical model used in the study, which is a Kaleckian post-Keynesian model, as an alternative to mainstream neoclassical theory. Having discussed the theory of financial intermediation in chapter two and commonality between post-Keynesian models of growth and endogenous growth theory in chapter three, this chapter postulates that financial development influences economic growth through different channels including investment, savings, and productivity growth. Later in the chapter, data characteristics, including stationarity, cointegration, and causality are reviewed. The chapter closes with a discussion about the main econometric modelling implemented in this research, including structural autoregressive modelling, impulse response analysis, and the variance decomposition method.
4
McDaid, David, Brendan Kennelly, Susan Ahern, and Brendan McElroy. "An economic perspective on suicide across the five continents." In Oxford Textbook of Suicidology and Suicide Prevention, edited by Danuta Wasserman and Camilla Wasserman, 409–20. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780198834441.003.0049.
Abstract:
In considering suicide prevention measures, it is important to consider potential economic risk factors, and the costs and consequences of suicide. We provide an overview of some areas where economics has played a role in the analysis of suicide and prevention strategies. Evidence on the wide-ranging socioeconomic costs and consequences of suicide is provided, including a reflection on the development of economic theories on individual motivations for suicide. Evidence from econometric models at cross-country and single country levels on the links between suicide and socioeconomic risk factors is reviewed. Cost-effectiveness is used as part of decision-making processes in health and other sectors. In respect to suicide prevention there is growing evidence of cost-effective measures. Incorporating economic analyses into future effectiveness studies is likely to help strengthen the case for investment in suicide prevention. There is also scope to look at the economic implications of interventions already shown to be effective.
Conference papers on the topic "Investment analysis Australia Econometric models":
1
Koşan, Naime İrem, and Sudi Apak. "Trade Openness and Macroeconomic Policy in OECD Countries." In International Conference on Eurasian Economies. Eurasian Economists Association, 2015. http://dx.doi.org/10.36880/c06.01373.
Abstract:
Trade openness has been subject to an important issue many studies in literature. It allows us to analyze potential trade as a percentage of gross domestic product. Total value of international trade in goods and services shows the countries’ integration into the world economy. Generally, small countries are more integrated because of their dependency on imports. On the other hand, there many variables which effects trade integration. Our study focuses on to analyze the effects on trade openness and make inferences for OECD countries.
In this paper we aim to examine the relationship between trade openness and macro-economic indicators in OECD countries. To analyze the relationship, we used panel data regression analysis. Data obtained from World Bank, The Heritage Foundation and United Nations Conference on Trade and Development (UNCTAD). The panel data covers 2000-2013 periods and 33 countries. The analysis made through the Stata econometric packet program. We predicted pooled, fixed effects and random effects panel data models and analyzed them.
It has been found that gross domestic savings, investment freedom, and unemployment rate are statistically significant. The results found in this paper show that investment freedom and gross domestic savings have positive effect on trade openness as we expected. On the other hand, unemployment rate has positive effect on trade openness. These findings have important policy implications for OECD countries. Our interpretation of these findings is that, integration to world economy has generally positive effects for macroeconomic factors in OECD countries, but it should be limited.
Reports on the topic "Investment analysis Australia Econometric models":
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de Caritat, Patrice, Brent McInnes, and Stephen Rowins. Towards a heavy mineral map of the Australian continent: a feasibility study. Geoscience Australia, 2020. http://dx.doi.org/10.11636/record.2020.031.
Abstract:
Heavy minerals (HMs) are minerals with a specific gravity greater than 2.9 g/cm3. They are commonly highly resistant to physical and chemical weathering, and therefore persist in sediments as lasting indicators of the (former) presence of the rocks they formed in. The presence/absence of certain HMs, their associations with other HMs, their concentration levels, and the geochemical patterns they form in maps or 3D models can be indicative of geological processes that contributed to their formation. Furthermore trace element and isotopic analyses of HMs have been used to vector to mineralisation or constrain timing of geological processes. The positive role of HMs in mineral exploration is well established in other countries, but comparatively little understood in Australia. Here we present the results of a pilot project that was designed to establish, test and assess a workflow to produce a HM map (or atlas of maps) and dataset for Australia. This would represent a critical step in the ability to detect anomalous HM patterns as it would establish the background HM characteristics (i.e., unrelated to mineralisation). Further the extremely rich dataset produced would be a valuable input into any future machine learning/big data-based prospectivity analysis. The pilot project consisted in selecting ten sites from the National Geochemical Survey of Australia (NGSA) and separating and analysing the HM contents from the 75-430 µm grain-size fraction of the top (0-10 cm depth) sediment samples. A workflow was established and tested based on the density separation of the HM-rich phase by combining a shake table and the use of dense liquids. The automated mineralogy quantification was performed on a TESCAN® Integrated Mineral Analyser (TIMA) that identified and mapped thousands of grains in a matter of minutes for each sample. The results indicated that: (1) the NGSA samples are appropriate for HM analysis; (2) over 40 HMs were effectively identified and quantified using TIMA automated quantitative mineralogy; (3) the resultant HMs’ mineralogy is consistent with the samples’ bulk geochemistry and regional geological setting; and (4) the HM makeup of the NGSA samples varied across the country, as shown by the mineral mounts and preliminary maps. Based on these observations, HM mapping of the continent using NGSA samples will likely result in coherent and interpretable geological patterns relating to bedrock lithology, metamorphic grade, degree of alteration and mineralisation. It could assist in geological investigations especially where outcrop is minimal, challenging to correctly attribute due to extensive weathering, or simply difficult to access. It is believed that a continental-scale HM atlas for Australia could assist in derisking mineral exploration and lead to investment, e.g., via tenement uptake, exploration, discovery and ultimately exploitation. As some HMs are hosts for technology critical elements such as rare earth elements, their systematic and internally consistent quantification and mapping could lead to resource discovery essential for a more sustainable, lower-carbon economy.