Journal articles: 'Financial econometric'

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Gruszczyński, Marek. "Accounting and Econometrics: From Paweł Ciompa to Contemporary Research." Journal of Risk and Financial Management 15, no. 11 (November 4, 2022): 510. http://dx.doi.org/10.3390/jrfm15110510.

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This paper examines the little-known connection between econometrics and accounting invoked by Paweł Ciompa, who first introduced the term econometrics in 1910. Since then, research in accounting and in statistical (econometric) analysis has developed in parallel. It is argued that contemporary accounting research is methodologically closer to econometrics than ever before. This paper concentrates on the accounting origins of econometrics and on the econometric methodologies currently in use in accounting research, beginning with Paweł Ciompa’s introduction of the term econometrics in accounting. The major contribution of this paper is a review of the occurrence of econometric methods in five leading journals in accounting research. The author identified 246 papers, and these were examined regarding the use of econometric methods. Two-thirds of the papers used methodologies that belong to econometrics—specifically, to financial microeconometrics. The most common methods were panel data models, qualitative variables models, and causality models.

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MİXON, Franklin, and Kamal UPADHYAYA. "Scholarly Impact of Core Econometrics Journals: A Catalog and Citations-Based Ranking." International Econometric Review 13, no. 4 (July 5, 2022): 118–31. http://dx.doi.org/10.33818/ier.984141.

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With 23 core econometrics journals now in operation, this study fills a gap in the literature by cataloguing the editorial specifications of each journal, and, more importantly, assessing their impact based on citations to research published in each over the 15-year period beginning in 2001 and ending in 2015. Our investigation reveals that about one-half of all core econometrics journals publish in an online format only, while the others publish both online and in-print. About one-fourth of all core econometrics journals are affiliated with an academic organization or society, while the same number are published by either Elsevier, Springer or Wiley. In terms of our assessment, Econometrica, Journal of Econometrics and Journal of Applied Econometrics sit atop our citations index ranking, while the relatively-new Journal of Financial Econometrics breaks into the top five, and other younger journals, such as the Journal of Econometric Methods and Econometrics, also make a strong showing in what is the first academic study assessing their productivity.

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Lupekesa, Chipasha Salome Bwalya, Johannes Tshepiso Tsoku, and Lebotsa Daniel Metsileng. "Econometric Modelling of Financial Time Series." International Journal of Management, Entrepreneurship, Social Science and Humanities 5, no. 2 (December 30, 2022): 52–70. http://dx.doi.org/10.31098/ijmesh.v5i2.622.

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This paper examines the relationship between assets, capital, liabilities and liquidity in South Africa using the Johansen cointegration analysis and the GARCH model using times data for the period 02/2005 to 06/2018. The results obtained from the study suggests that the time series are integrated of order one, I(1). The findings from the Johansen cointegration test indicated that the variables have a long run cointegrating relationship. Furthermore, the results from the GARCH model revealed that the estimated model has statistically significant coefficients at 5% significance level. Additionally, results revealed that assets have a positive relationship with capital, liabilities and liquidity. This implies that a percentage increase in assets will result to a percentage increase in capital, liabilities and liquidity. The results also revealed that shocks decay quickly in the future and that the conditional variance is explosive. The diagnostic tests revealed that the estimated models show the characteristics of a well specified model. The recommendations for future studies were formulated. Keywords: ARCH model; Cointegration; Financial time series; GARCH model; VECM; Volatility

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Raji, Rahman Olanrewaju. "The Financial Stability in Developing Economy: Role of Financial Inclusion and Financial Efficiency." Quantitative Economics and Management Studies 2, no. 1 (January 11, 2021): 72–84. http://dx.doi.org/10.35877/454ri.qems269.

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This paper explores the asymmetric nexus between financial inclusion, financial efficiency and financial stability, within asymmetric and symmetric Autoregressive Distributed Lag (NARDL) framework, covering the period from 2003 to 2018, using quarterly data in Nigeria. The findings showed that symmetric technique of econometric test detects, that financial stability is augmented by better improvement in financial inclusion in short-run, while asymmetric technique observed that short-run positive effect, and negative effect likewise long-run decrease in this index heightened the level of financial stability in this economy. This study further found trade-off existence, between financial efficiency and financial stability in both symmetric and asymmetric techniques of econometric tests, which is consistent with some empirical findings. The results based on the model and empirical data indicate that, the monetary authority needs to follow prudent and adequate supervisory standard in pursuing financial inclusion, financial intermediaries should be accompanied with good institutional quality, including financial awareness that should be enhanced through financial teachings in all sectors both in the urban and rural areas of the economy.

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Городников, Кирилл, Михаил Павлов, and Александр Сус. "Influence of Mezzanine Financing on the Corporate Financial Profile." Journal of Corporate Finance Research / Корпоративные Финансы | ISSN: 2073-0438 16, no. 2 (October 18, 2022): 70–95. http://dx.doi.org/10.17323/j.jcfr.2073-0438.16.2.2022.70-95.

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Due to global changes in the global economy, the importance of financing and building an optimal capital structure is increasing. Rapid changes in the exogenous environment and the investment climate lead companies to revise their financing strategies. Currently, there are many financial instruments that provide cash inflow, but have certain restrictions. The tool that allows to eliminate them is the mezzanine. However, the existing literature on mezzanine financing does not fully cover this financing method. The novelty of this research lies in determining the financial profile of the borrower company that utilizes mezzanine financing, and in studying the impact of the mezzanine on the market value of a company’s equity and its value. Econometric analysis confirms that mezzanine financing is more often chosen by companies with a less attractive financial profile, based on ROA, EBITDA – CapEx cash flow, and beta. In addition, the interconnection between a company’s life cycle and its desire to attract a mezzanine loan is revealed. Econometric and empirical analysis allow us to conclude that the market situation, managerial methods within the company and the operational strategy increase the chances of the effective use of the mezzanine.

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Lee, Bong-Soo, and Terence C. Mills. "The Econometric Modelling of Financial Time Series." Journal of Finance 50, no. 1 (March 1995): 387. http://dx.doi.org/10.2307/2329254.

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Walden, Andrew, and T. C. Mills. "The Econometric Modelling of Financial Time Series." Journal of the Royal Statistical Society. Series A (Statistics in Society) 157, no. 3 (1994): 508. http://dx.doi.org/10.2307/2983542.

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Hylleberg, Svend, and Terence C. Mills. "The Econometric Modelling of Financial Time Series." Economic Journal 105, no. 431 (July 1995): 1038. http://dx.doi.org/10.2307/2235181.

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9

Pedroni, Peter. "The Econometric Modelling of Financial Time Series." Journal of the American Statistical Association 96, no. 453 (March 2001): 339–55. http://dx.doi.org/10.1198/jasa.2001.s376.

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Franses, P. H. B. F. "The Econometric Modelling of Financial Time Series." International Journal of Forecasting 16, no. 3 (July 2000): 426–27. http://dx.doi.org/10.1016/s0169-2070(00)00046-7.

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Meade, Nigel. "The econometric modelling of financial time series." International Journal of Forecasting 10, no. 1 (June 1994): 165–66. http://dx.doi.org/10.1016/0169-2070(94)90060-4.

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Chang, Chia-Lin, and Michael McAleer. "Econometric analysis of financial derivatives: An overview." Journal of Econometrics 187, no. 2 (August 2015): 403–7. http://dx.doi.org/10.1016/j.jeconom.2015.02.026.

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13

Bettin, Giulia, Riccardo Lucchetti, and Alberto Zazzaro. "Financial development and remittances: Micro-econometric evidence." Economics Letters 115, no. 2 (May 2012): 184–86. http://dx.doi.org/10.1016/j.econlet.2011.12.026.

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Joudar, Fadoua, Zouheir Msatfa, Olaya Metwalli, Maha Mouabid, and Brahim Dinar. "Islamic Financial Stability Factors: An Econometric Evidence." Economies 11, no. 3 (March 2, 2023): 79. http://dx.doi.org/10.3390/economies11030079.

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This study empirically examines the internal and external factors of Islamic banks’ financial stability during the time frame from 2006 to 2017 in the Middle Eastern and North African (MENA) region. The stability of Islamic banks was determined by the Z-score, which is one of the most well-known financial stability indicators. Using multiple regression analysis, it is shown that capital adequacy ratio and liquidity positively impact the Z-score of Islamic banks, whilst size, governance and level of concentration have a negative impact. This study recommends raising the capital and the liquidity level of Islamic banks as it helps to promote the financial stability of Islamic banks.

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Erra, Kamal Sai Sadharma, and Debashis Acharya. "Financial inclusion across major Indian states: some spatial panel econometric evidence." International Journal of Social Economics 48, no. 3 (January 8, 2021): 419–36. http://dx.doi.org/10.1108/ijse-06-2020-0392.

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PurposeThis paper aims to test for spatial convergence in financial inclusion across major Indian states and union territories.Design/methodology/approachAfter initially building an Index of Financial Inclusion (IFI) for major Indian states between 2003 and 2016, exploratory spatial data analysis (ESDA) is employed to draw inferences about mean and variance of IFI. The paper then seeks to confirm the ESDA results through spatial panel regression techniques. Finally, spatial results are correlated with results from aspatial convergence measures.FindingsThe study finds that there is no evidence of spatial convergence in financial inclusion over the study period, suggesting that those states that were relatively less financially included remained so through the study period. The study also asserts the relevance of certain important determinants, namely, per capita income, infrastructure, industrialization and gender.Research limitations/implicationsThis study has two limitations. First, only banking institutions are considered in measuring financial inclusion. Second, due to lack of a consistent indicator of gender participation across states, we had to employ sex ratio as a proxy.Practical implicationsThe study suggests that policies to expand financial inclusion in Indian states, especially those with low inclusion levels are likely to benefit neighbouring states also, thereby accelerating the financial inclusion drive across states.Originality/valueThe study is a first in the Indian context to estimate the spatial dependence of financial inclusion and provides relevant implications for policymakers and bankers to target financial inclusion schemes in backward states.

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Fan, Jianqing, Kunpeng Li, and Yuan Liao. "Recent Developments in Factor Models and Applications in Econometric Learning." Annual Review of Financial Economics 13, no. 1 (November 1, 2021): 401–30. http://dx.doi.org/10.1146/annurev-financial-091420-011735.

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This article provides a selective overview of the recent developments in factor models and their applications in econometric learning. We focus on the perspective of the low-rank structure of factor models and particularly draw attention to estimating the model from the low-rank recovery point of view. Our survey mainly consists of three parts. The first part is a review of new factor estimations based on modern techniques for recovering low-rank structures of high-dimensional models. The second part discusses statistical inferences of several factor-augmented models and their applications in statistical learning models. The final part summarizes new developments dealing with unbalanced panels from the matrix completion perspective.

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Magiera, Frank T. "Risk and Volatility: Econometric Models and Financial Practice." CFA Digest 35, no. 1 (February 2005): 82–83. http://dx.doi.org/10.2469/dig.v35.n1.1639.

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18

Engle, Robert. "Risk and Volatility: Econometric Models and Financial Practice." American Economic Review 94, no. 3 (May 1, 2004): 405–20. http://dx.doi.org/10.1257/0002828041464597.

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19

GREEN, CHRISTOPHER J., and ERIC KIERNAN. "MULTICOLLINEARITY AND MEASUREMENT ERROR IN ECONOMETRIC FINANCIAL MODELLING." Manchester School 57, no. 4 (December 1989): 357–69. http://dx.doi.org/10.1111/j.1467-9957.1989.tb00822.x.

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Barassi, Marco R. "Evaluating Econometric Forecasts of Economic and Financial Variables." Economic Journal 116, no. 509 (February 1, 2006): F164—F165. http://dx.doi.org/10.1111/j.1468-0297.2006.01069_6.x.

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Jawadi, Fredj. "INTRODUCTION TO TIME-VARYING MODELING WITH MACROECONOMIC AND FINANCIAL DATA." Macroeconomic Dynamics 16, S2 (April 12, 2012): 167–75. http://dx.doi.org/10.1017/s136510051100071x.

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The dynamics of macroeconomic and financial series has evolved swiftly and asymmetrically since the end of the 1970s, and their statistical properties have also changed over time, suggesting complex relationships between economic and financial variables. The transformations can be explained by considerable changes in householder's behavior, market structures, and economic systems and by the alternation of exogenous shocks and financial crises that have affected the economic cycle, with significant evidence of time variation in the major economic variables. Hence, there is a need for new econometric protocols to take such changes into consideration. The introduction of ARMA (autoregressive moving average models) by Box and Jenkins (1970) led to the development of time-series econometrics, which had a major impact on the conceptual analysis of economic and financial data. This type of modeling offered a transition from a static setup to a new modeling process that reproduces the time-varying features of macroeconomic and financial series. However, the ARMA modeling system retains the constancy of the first and second moments, limits the phases of a cycle to symmetrical instances, and only reproduces the dynamics of stationary variables. It thus fails to adequately reproduce the nonstationary relationships between major economic and financial variables. Abrupt changes in economies and financial systems have given evidence of nonstationary series whose statistical properties are also time-varying, making it necessary to develop new econometric tools to capture the time variation of economic and financial series in the mean and in the variance, and to apprehend their dynamics in the short and long term. Among the most important and influential studies in the 1980s' econometrics literature were therefore those that dealt with the introduction of the ARCH (autoregressive conditional heteroskedasticity) model by Engle (1982) and the cointegration theory by Engle and Granger (1987). The ARCH model, which focuses on the time-varying features of volatility structure, was a major breakthrough, as it highlighted the importance of the second moment of time series, while the cointegration framework enabled the short- and long-term dynamics of nonstationary variables to be modeled.

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Tsaurai, Kunofiwa. "Financial development and growth in Hungary." Risk Governance and Control: Financial Markets and Institutions 5, no. 3 (2015): 205–13. http://dx.doi.org/10.22495/rgcv5i3c2art6.

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This study investigated the relationship between financial development and economic growth in Hungary using a case study approach. Majority of previous studies on the same or similar topic have so far used regression and or econometric methodologies to examine the nature of the relationship between financial development and economic growth. Not a single study the author is aware of used a case study approach to discuss the relationship between the two variables. It is against this background that the author decided to use the case study approach that allows the author to really deepen an understanding of the relationship between the two variables in Hungary. Apart from being narrowly focused on regression or econometric approaches, previous studies on the same or similar topic in Hungary excluded a broad range of financial development variables. The current study departs from these previous studies as it used a case study approach and taken into account a broad range of financial development variables. From the trend analysis done in section 3, it appears that the relationship between financial development and growth in Hungary during the period under study is not clear. A definite and clear cut conclusion could not be reached about the relationship between the two variables in Hungary hence the use of econometric data analysis approaches in conjuction with the case study approach is recommended.

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Chen, Shu-Heng, Chia-Ling Chang, and Ye-Rong Du. "Agent-based economic models and econometrics." Knowledge Engineering Review 27, no. 2 (April 26, 2012): 187–219. http://dx.doi.org/10.1017/s0269888912000136.

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AbstractThis paper reviews the development of agent-based (computational) economics (ACE) from an econometrics viewpoint. The review comprises three stages, characterizing the past, the present, and the future of this development. The first two stages can be interpreted as an attempt to build the econometric foundation of ACE, and, through that, enrich its empirical content. The second stage may then invoke a reverse reflection on the possible agent-based foundation of econometrics. While ACE modeling has been applied to different branches of economics, the one, and probably the only one, which is able to provide evidence of this three-stage development is finance or financial economics. We will, therefore, focus our review only on the literature of agent-based computational finance, or, more specifically, the agent-based modeling of financial markets.

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Fedotova, M. A., T. V. Tazihina, and A. S. Maltsev. "QUANTITATIVE METHODS OF FINANCIAL STABILITY DEPENDENCE ON THE COMPANY VALUE." Strategic decisions and risk management, no. 2 (October 25, 2014): 52–62. http://dx.doi.org/10.17747/2078-8886-2014-2-52-62.

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The topics related to the financial stability assessment and market valuation of a business have received a detailed coverage in contemporary literature. However no approaches in meth-odology have been elaborated that would enable the quantitative assessment of the degree to which the financial stability indices and the market value of the company are linked together. Therefore, the econometric modelling of the dependence assessment between the cost factors and financial stability indicators poses a task relevant to present-day challenges.The authors of the article present the proof that the company value is an integral indicator, which can replace the broad range of absolute and relative financial stability ratios in the assessment of the financial stability of a business.Based on the econometric data analysis of the leading Russian and global energy companies that meet the profitability, financial stability and maturity criteria, the article proves the practical application of Modigliani—Miller theory as compared to D. Duran traditional theory of capital structure. The econometric regression correlations and the analysis of their statistical significance bring the con clusion of the ambiguity in the correlation between the Cost of Capital and Financial Leverage.

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Misha, Ergys. "Regular Econometric Model of Taylor for Albania." European Journal of Economics and Business Studies 5, no. 1 (August 30, 2016): 123. http://dx.doi.org/10.26417/ejes.v5i1.p123-133.

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The Taylor’s Rule Central Banks is applying widely today from Central Banks for design the monetary policy and for determination of interest rates. The purpose of this paper is to assess monetary policy rule in Albania, in view of an inflation targeting regime. In the first version of the Model, the Taylor’s Rule assumes that base interest rate of the monetary policy varies depending on the change of (1) the inflation rate and (2) economic growth (Output Gap).Through this paper it is proposed changing the objective of the Bank of Albania by adding a new objective, that of "financial stability", along with the “price stability”. This means that it is necessary to reassess the Taylor’s Rule by modifying it with incorporation of indicators of financial stability. In the case of Albania, we consider that there is no regular market of financial assets in the absence of the Stock Exchange. For this reason, we will rely on the credit developmet - as a way to measure the financial cycle in the economy. In this case, the base rate of monetary policy will be changed throught: (1) Targeting Inflation Rate, (2) Nominal Targeting of Economic Growth, and (3) Targeting the Gap of the Ratio Credit/GDP (mitigating the boom cycle, if the gap is positive, and the contractiocycle if the gap is negative).The research data show that, it is necessary that the Bank of Albania should also include in its objective maintaining the financial stability. In this way, the contribution expected from the inclusion of credit gap indicators in Taylor’s Rule, will be higher and sustainable in time.

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Japaridze, David, and Giga Jojua. "Development of an Optimal Econometric Model for Assessing the Financial Sustainability of a Large Electricity Company and its Forecasting Approbation in Georgia." Works of Georgian Technical University, no. 1(523) (March 25, 2022): 151–62. http://dx.doi.org/10.36073/1512-0996-2022-1-151-162.

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An optimal econometric model for assessing the financial stability of a large electric power company has been developed based on the in-depth analysis, which takes into account all possible factors affecting financial stability. The types of factors are established by correlation analysis. The model is universal in nature, its application is possible in assessing the financial stability of any enterprise. For the purpose of practical implementation of the optimal econometric model for assessing financial stability, a predictive approbation was carried out using the example of the Georgian State Electricity System and JSC Telasi. As a result, problems in the management of financial stability were identified and ways to solve them were outlined.

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Oxley, Les, and Peter C. B. Phillips. "ECONOMETRIC SOCIETY INTENSIVE WORKSHOP FOR YOUNG SCHOLARS." Econometric Theory 17, no. 6 (December 2001): 1161–63. http://dx.doi.org/10.1017/s0266466601176073.

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This inaugural Workshop for Young Scholars was arranged under the auspices of and with financial support from the Econometric Society and the Econometric Society Australasian Standing Committee (ESASC). Twenty-five scholars met for two days in Hamilton, New Zealand immediately following the Econometric Society Australasian Meeting which was held in Auckland over July 6–8. (A report by Les Oxley on these Econometric Society Meetings, entitled “2001 Econometric Society Australasian Meeting: Auckland,” will appear in the Journal of Economic Surveys (2001), vol. 15.) The Waikato Young Scholars Workshop represented the culmination of 18 months of planning and organization following an initiative from the Executive of the Econometric Society to encourage special projects by regional committees.

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Amin, Yasir, and Abdul Jalil. "Remittances and Financial Inclusion: Micro-econometric Evidences from Pakistan." Asian Journal of Economics, Business and Accounting 8, no. 4 (November 5, 2018): 1–13. http://dx.doi.org/10.9734/ajeba/2018/44990.

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Sun, Lixin. "On the People’s Bank of China’s Financial Strength and Policy Outcomes." Journal of Central Banking Theory and Practice 9, no. 3 (September 1, 2020): 135–61. http://dx.doi.org/10.2478/jcbtp-2020-0041.

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AbstractThis paper measures the financial strength of the People’s Bank of China from the perspective of balance sheets, and then examine empirically whether its financial strength influences its policy commitments given its financial conditions. The econometric results suggest that, first, the financial strength of the People’s Bank of China does affect its policy performance, although the effects are weak and overall results lack robustness with respect to the econometric technique and the choice of alternative measures of financial strength. Second, alternative financial strength indicator plays different role in helping the People’s Bank of China achieve its alternative policy objectives. Therefore, maintaining benign financial conditions and a resilient balance sheet are necessary pre-conditions for the People’s Bank of China to achieve desirable policy outcomes. Third, the People’s Bank of China’s current standalone finance is healthy under our stressing tests, despite certain concerns attained.

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Stengos, Thanasis. "Nonparametric Econometric Methods and Applications." Journal of Risk and Financial Management 12, no. 4 (November 30, 2019): 180. http://dx.doi.org/10.3390/jrfm12040180.

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An area of very active research in econometrics over the last 30 years has been that of non- and semi-parametric methods. These methods have provided ways to complement more-traditional parametric approaches in terms of robust alternatives, as well as preliminary data analysis. The present Special Issue collects a number of new contributions, both theoretical and empirical that cover a wide spectrum of areas such as financial economics, microeconomics, macroeconomics, labor economics, and economic growth as well as statistical theory and methodology.

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Zhou, Huan, Shaojian Qu, Qinglu Yuan, and Shilei Wang. "Spatial Effects and Nonlinear Analysis of Energy Consumption, Financial Development, and Economic Growth in China." Energies 13, no. 18 (September 22, 2020): 4982. http://dx.doi.org/10.3390/en13184982.

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Energy consumption is of great significance to the sustainable development of the economy. Due to the spatial heterogeneity of low-carbon growth in regional economies, the relationship between energy consumption and economic growth is complicated. However, a few researches have been published about spatial spillover effects and non-linearity of energy consumption and financial development on regional economic growth in China. Based on the panel data of 30 provinces in China from 2007 to 2017, this paper analyzes the spatial spillover effects and threshold effects of energy consumption and financial development on regional economic growth by using spatial and nonlinear econometric methods. The main conclusions are as follows. Spatial econometric methods show that financial development and energy consumption are two factors of production input to promote China’s economic growth. Meanwhile, energy consumption and financial development have spillover effects on regional economic growth. Additionally, the nonlinear econometric method finds that with increasing financial development, the impact of energy consumption on economic growth is segmented. Therefore, relevant policies should be implemented to enhance the role of finance in energy consumption to promote low-carbon growth of China’s economy.

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Campbell, John Y., Andrew W. Lo, A. Craig MacKinlay, and Robert F. Whitelaw. "THE ECONOMETRICS OF FINANCIAL MARKETS." Macroeconomic Dynamics 2, no. 4 (December 1998): 559–62. http://dx.doi.org/10.1017/s1365100598009092.

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This book is an ambitious effort by three well-known and well-respected scholars to fill an acknowledged void in the literature—a text covering the burgeoning field of empirical finance. As the authors note in the preface, there are several excellent books covering financial theory at a level suitable for a Ph.D. class or as a reference for academics and practitioners, but there is little or nothing similar that covers econometric methods and applications. Perhaps the closest existing text is the recent addition to the Wiley Series in Financial and Quantitative Analysis. written by Cuthbertson (1996). The major difference between the books is that Cuthbertson focuses exclusively on asset pricing in the stock, bond, and foreign exchange markets, whereas Campbell, Lo, and MacKinlay (henceforth CLM) consider empirical applications throughout the field of finance, including corporate finance, derivatives markets, and market microstructure. The level of anticipation preceding publication can be partly measured by the fact that at least three reviews (including this one) have appeared since the book arrived. Moreover, in their reviews, both Harvey (1998) and Tiso (1998) comment on the need for such a text, a sentiment that has been echoed by numerous finance academics.

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Yuandong, G., W. Tao, Y. Wen, and W. Xiaohua. "A spatial econometric study on effects of fiscal and financial supports for agriculture in China." Agricultural Economics (Zemědělská ekonomika) 59, No. 7 (July 19, 2013): 315–32. http://dx.doi.org/10.17221/126/2012-agricecon.

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Since the reform and opening-up, the disparity between Chinese rural economy and the overall national economic development has already become the key constraint for further development of the national economy. In order to increase the farmers’ income and to promote rural economic development, the efforts of China’s budgetary and financial policies to support agriculture have been strengthened year by year. However, it lacks an accurate and effective assessment to evaluate the effects of China’s fiscal and financial policies supports for agriculture. This paper proposes to estimate and measure the effects of China’s fiscal and financial supports for agriculture utilizing the Chinese provincial panel data on the basis of the latest spatial panel econometric method. The results show that since China intensified the fiscal and financial support in 2004, the direct effects of fiscal and financial supports for agriculture have improved, but the spatial spillover effects have turned from positive to negative.  

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Sukharev, Oleg, and Ekaterina Voronchikhina. "Financial and non-financial investments: comparative econometric analysis of the impact on economic dynamics." Quantitative Finance and Economics 4, no. 3 (2020): 382–411. http://dx.doi.org/10.3934/qfe.2020018.

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Duguleana, Constantin, Liliana Duguleana, Camelia Mirela Baba, and Cristina Drumea. "Recovery after Demerger: Evidence from Romanian Companies." Sustainability 14, no. 3 (January 20, 2022): 1151. http://dx.doi.org/10.3390/su14031151.

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The paper follows the demerger phenomenon in Romania in order to find out whether companies regain their economic performance after reorganization. The research is based on four samples of companies, divided into 2012, 2013, 2014, and 2015, that recorded their financial indicators in the period from 2005–2019. Using the financial indicators of companies that demerged in the same year, we analyzed the economic performances before and after the demergers, using statistical and econometric methods. The model with the fixed effects of the cross sections proved to be the most suitable for each panel, both for the entire analyzed period and for the two subperiods: ante and post demerger. The subperiod models are better than the panel econometric models for the entire period. The results show that all of the Romanian companies recovered after the demergers, and also to what extents. The validities of the econometric models confirm the sustainability of the economic activities after the demergers. This paper provides a study methodology and econometric models to investigate the demerger phenomenon among Romanian companies.

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Khan, Imran, Atiq ur Rehman, and Saud Ahmad Khan. "Financial Development and Economic Growth an Advanced Econometric Modeling Approach." Global Economics Review VI, no. II (June 30, 2021): 160–72. http://dx.doi.org/10.31703/ger.2021(vi-ii).13.

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Financial development is essential for economic growth for all economies. In the current study, we examine the importance of financial development on economic growth for different countries using advanced econometric techniques of model selection. We use Auto metrics, Elastic Net,and Extreme Bound Analysis to retain the variables that affect the economic growth by using the data (1980-2019) on 32 countries from different regions. We used an advanced approach (retention frequency) to investigate the relationship between financial development and economic growth. The results show that financial development is a significant retention frequency in the case of Asian, European, and American countries directly and indirectly. For in-sample forecasting, we use root mean square error (RMSE) and mean square prediction error (MSPE). Extreme Bound Analysis presents a superior predictive performance interms of the lowest RMSE and MPSE that are 1.03 and 0.05,respectively.

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Ece, Arslan, and Güven Sayılgan. "Macroeconomic Determinants of Financial Distress in Turkey: An Econometric Analysis." Australasian Business, Accounting & Finance Journal 14, no. 5 (2020): 86–107. http://dx.doi.org/10.14453/aabfj.v14i5.6.

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Purpose The purpose of this paper is to investigate the possible links between macroeconomic factors and financial distress in Turkey. Design/methodology/approach Based on the 2009/1-2016/2 quarterly data of macroeconomic factors and the number of filings for bankruptcy postponement, econometric models are developed using forward stepwise regression and classical regression methods to determine the factors influencing financial distress. A vector error correction model is also developed using macroeconomic factors found significant in both methods to investigate the interactions of financial distress with them. Findings In the stepwise regression implementation, performed with 16 independent variables, statistically significant variables entered into the model are industrial production index with negative sign as expected and the unemployment rate with negative sign against the expectations. In the classical regression implementation, performed with 7 independent variables, statistically significant variables are ex ante real interest rate with positive sign and gross domestic product with negative sign as expected and money supply with negative sign against the expectations. The impulse response graphics of a vector error correction model involving bankruptcy postponement, industrial production index and nominal interest rate indicates that bankruptcy postponement is influenced by the shocks both in itself and in industrial production index. Originality/value This is the first study in Turkey investigates macroeconomic determinants of financial distress.

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Oh, Kok-Boon, and Sardar M N Islam. "A financial econometric analysis of E-Commerce stock price predictability." Social and Management Research Journal 9, no. 2 (December 3, 2012): 59. http://dx.doi.org/10.24191/smrj.v9i2.5217.

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The predictability of stock price changes has been a contentious issue in finance for a long period of time. Using the Australian e-commerce financial data for determining the equity value of e-commerce firms, this paper provides an empirical analysis of the issue of predictability of stock prices. The factors contributing to the predictability of equity prices in the e-commerce markets are identified, analyzed and the issues and implications are discussed and explained. This paper presents new approaches to econometric specification, estimation and testing in relation to e-commerce stock predictability including stationarity tests, co-integration modeling and analyses. The policy implications of the empirical findings are stated. The empirical findings of the Australian study are extrapolated and inferences are made for other countries.

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Stella, Peter, and Ulrich H. Klueh. "Central Bank Financial Strength and Policy Performance: An Econometric Evaluation." IMF Working Papers 08, no. 176 (2008): 1. http://dx.doi.org/10.5089/9781451870343.001.

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Lv, Zhike, and ShaSha Li. "How financial development affects CO2 emissions: A spatial econometric analysis." Journal of Environmental Management 277 (January 2021): 111397. http://dx.doi.org/10.1016/j.jenvman.2020.111397.

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Brownlees, C. T., and G. M. Gallo. "Financial econometric analysis at ultra-high frequency: Data handling concerns." Computational Statistics & Data Analysis 51, no. 4 (December 2006): 2232–45. http://dx.doi.org/10.1016/j.csda.2006.09.030.

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Fedorova, E., and I. Lukasevich. "Forecasting Financial Crises by Using Key Indicators in Developing Countries." Voprosy Ekonomiki, no. 12 (December 20, 2011): 35–45. http://dx.doi.org/10.32609/0042-8736-2011-12-35-45.

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This paper presents the method of forecasting financial crises in developing countries based on a list of crisis indicators. It helps find critical indicators and the combination of key indicators using modern econometric modeling.

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Kim, Chang-Jin, James Morley, and Jeremy Piger. "INTRODUCTION TO “SPECIAL ISSUE ON THE EMPIRICAL ANALYSIS OF BUSINESS CYCLES, FINANCIAL MARKETS, AND INFLATION: ESSAYS IN HONOR OF CHARLES NELSON”." Macroeconomic Dynamics 19, no. 4 (December 16, 2013): 723–27. http://dx.doi.org/10.1017/s1365100513000643.

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Time series analysis of macroeconomic and financial variables requires a deep understanding of many econometric pitfalls if an empirical researcher hopes to avoid making spurious inferences. This understanding is the hallmark of Charles Nelson's research over four decades and it develops out of a healthy skepticism about “conventional wisdom,” yet a pragmatic belief that, despite the econometric hurdles, it is possible to learn from data. The papers in this special issue build on Charles Nelson's research legacy to address many important empirical questions related to business cycles, financial markets, and inflation, always with respect for the data, but wary of spurious inferences.

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Duguleană, Constantin, and Liliana Duguleană. "FINANCIAL PROFITABILITY OF DEMERGED COMPANIES." SERIES V - ECONOMIC SCIENCES 14(63), no. 2 (December 15, 2021): 173–82. http://dx.doi.org/10.31926/but.es.2021.14.63.2.20.

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The paper presents a complete analysis of the evolution of the profitability of some Romanian companies that decided to demerge in 2013. The sample of companies was analyzed with statistical and econometric methods of panel data, in the sub-periods before and after demerger: 2005-2013 and 2014-2019. The main objective of research was to find out if the organizational management strategy was beneficial for obtainingbetter economic and financial performance. The research results were extended to the population to characterize the financial situation of all Romanian companies in the same situation as those in the sample

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Hlongwane, Tshembhani M., and Johannes P. S. Sheefeni. "Examining the Effect of Financial Markets Shocks on Financial Stability in South Africa." International Journal of Economics and Financial Issues 12, no. 6 (November 23, 2022): 30–37. http://dx.doi.org/10.32479/ijefi.13452.

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The paper analyzed the impact of financial market shocks on financial market stability. The goal was achieved by employing quarterly time-series data spanning from 2003:Q1 to 2020:Q4. The study used various econometric techniques such as stationarity, determining optimal lag length, cointegration analysis, estimating a vector error correction model, impulse response functions and forecast error variance decomposition. Following this, the long run relationship amongst the variables was established. The findings revealed that inflation has a negative impact on financial stability in both the short and long run. Lastly, it was only the shocks in economic activities that was found to have a significant impact on financial stability.

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Dzuba, Sergey, and Denis Krylov. "Cluster Analysis of Financial Strategies of Companies." Mathematics 9, no. 24 (December 10, 2021): 3192. http://dx.doi.org/10.3390/math9243192.

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Measuring the value of companies and assessing their risk often relies on econometric methods that consider companies as a set of objects under study, homogeneous in the sense of their use of financial strategies. This paper shows that cluster analysis methods can divide companies into classes according to financial strategies that they employ. This indicates that homogeneity can be considered within these classes, while between-class companies should rather be perceived as heterogeneous. The clustering of companies has to be performed on quite a dense set of strategies, which requires a combination of formal and heuristic methods. To divide companies into classes, we used financial coefficients characterizing strategies for the 2030 largest non-financial companies within the time period from 2006 to 2018. As a result, a stable division into seven clusters/strategies was obtained. We revealed that some strategies were more characteristic for the companies of high-tech economy, while others were typical for the companies in basic industries. The dynamics of clusters is characterized by an increase in the share of risky strategies. A good meaningful interpretation of the resulting clustering confirms its consistency. The identified clusters can be used as dummy variables in econometric studies of companies to improve the quality of the results.

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Karakara, Alhassan Abdul-Wakeel, Joshua Sebu, and Isaac Dasmani. "Financial literacy, financial distress and socioeconomic characteristics of individuals in Ghana." African Journal of Economic and Management Studies 13, no. 1 (October 27, 2021): 29–48. http://dx.doi.org/10.1108/ajems-03-2021-0101.

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PurposePersonal financial stress-free living is desired by many, which dwells on sound financial literacy (including financial behaviour, financial knowledge and financial attitude). Many individuals do not make optimal savings and investment decisions. The realisation that these choices may well lead to low living standards has also increased economic anxiety, especially in Sub-Sahara African countries, including Ghana. Thus, this study underscores the link between financial literacy and financial distress in Ghana. It establishes whether persons that are financially literate escape financial distress in their life.Design/methodology/approachThe paper engages nationally representative survey data and adopts a positivist research approach with logistic regression analysis to establish the likelihood of financial literate persons experiencing financial distress.FindingsThis study establishes that financially literate individuals are 2.4% less likely to experience financial distress. Socioeconomic characteristics greatly influence the probability of one experiencing financial hardship. It submits that policy can be directed towards improving financial habits (financial literacy) to enhance individuals' financial behaviour to lessen personal financial distress.Originality/valueNot much attention has been paid to whether financial literacy has a nexus with financial distress. Few studies (not on Sub-Saharan Africa) that have looked at this are done, neglecting a sensitivity analysis of socioeconomic characteristics in establishing the relations. However, this current study dwells on econometric analysis to establish the margin or extend to which a financially literate person may or may not escape financial distress given his/her socioeconomic characteristics.

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POLYUSHKO, Yu N. "FINANCIAL STRATEGY MATRIX: THEORY AND PRACTICE." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 1, no. 8 (2020): 29–34. http://dx.doi.org/10.36871/ek.up.p.r.2020.08.01.004.

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The article discusses various scenarios that arise when developing a financial strategy of an enterprise. The author uses a practical example to reveal the General mechanisms for applying financial strategy models. All this makes it possible to determine the choice of the most preferable scenario for the enterprise in specific economic conditions. The empirical basis of the research is the data of a modern enterprise. The analysis was performed using a specialized econometric package of MS Excel, as well as tabular and graphical methods.

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Escribano-Navas, María, and German Gemar. "Gender and Bankruptcy: A Hotel Survival Econometric Analysis." Sustainability 13, no. 12 (June 15, 2021): 6782. http://dx.doi.org/10.3390/su13126782.

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This study’s objective was to understand how chief executive officers’ (CEOs) gender affects hotel businesses’ survival. Female managers’ influence has already been examined in other sectors, but researchers have not studied women CEOs’ role in hotel management and survival. A sample of 2615 Spanish hotel companies was examined during the period 2005–2018 for how their survival was affected by the variables of financial aspects, years of experience and the principal hotel executive’s gender. An econometrics-based survival analysis was conducted using a single complementary log-log model and panel data. The results indicate that some financial variables, such as sales, working capital to total assets ratio and each company’s experience, influence hotel businesses’ survival. The main finding was that women CEOs increase hotels’ survival rate. This CEO gender study is a novelty in the literature on hotel survival.

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Siddik, Md Nur Alam, Tanveer Ahsan, and Sajal Kabiraj. "Does Financial Permeation Promote Economic Growth? Some Econometric Evidence From Asian Countries." SAGE Open 9, no. 3 (July 2019): 215824401986581. http://dx.doi.org/10.1177/2158244019865811.

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This study endeavors to explore whether financial permeation stimulates economic growth in Asian region. To answer this, we collect data of 24 Asian economies for the duration of 2004 to 2016 and apply panel unit root, Granger causality, and regression techniques. The regression results controlled for country and time effects reveal that various indicators of financial permeation have substantial positive impact on the economic growth of Asian economies. Based on the findings of Granger causality, we find that financial permeation as well as economic openness has mutual causalities with economic growth. Therefore, it seems rational to conclude that financial permeation has positive impact on the economic growth in Asian economies. We also find a negative impact of financial crisis (2007-2008) on economic growth of Asian countries.

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Journal articles on the topic 'Financial econometric'

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