Relevant bibliographies by topics / Econometrics – Statistical methods

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Econometrics – Statistical methods'

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Published: 10 March 2023

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Journal articles on the topic "Econometrics – Statistical methods"

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Bera, Anil K., and Ramu Ramanathan. "Statistical Methods in Econometrics." Journal of the American Statistical Association 89, no. 427 (September 1994): 1144. http://dx.doi.org/10.2307/2290954.

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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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Andersen, Torben G. "SIMULATION-BASED ECONOMETRIC METHODS." Econometric Theory 16, no. 1 (February 2000): 131–38. http://dx.doi.org/10.1017/s0266466600001080.

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The accessibility of high-performance computing power has always influenced theoretical and applied econometrics. Gouriéroux and Monfort begin their recent offering, Simulation-Based Econometric Methods, with a stylized three-stage classification of the history of statistical econometrics. In the first stage, lasting through the 1960's, models and estimation methods were designed to produce closed-form expressions for the estimators. This spurred thorough investigation of the standard linear model, linear simultaneous equations with the associated instrumental variable techniques, and maximum likelihood estimation within the exponential family. During the 1970's and 1980's the development of powerful numerical optimization routines led to the exploration of procedures without closed-form solutions for the estimators. During this period the general theory of nonlinear statistical inference was developed, and nonlinear micro models such as limited dependent variable models and nonlinear time series models, e.g., ARCH, were explored. The associated estimation principles included maximum likelihood (beyond the exponential family), pseudo-maximum likelihood, nonlinear least squares, and generalized method of moments. Finally, the third stage considers problems without a tractable analytic criterion function. Such problems almost invariably arise from the need to evaluate high-dimensional integrals. The idea is to circumvent the associated numerical problems by a simulation-based approach. The main requirement is therefore that the model may be simulated given the parameters and the exogenous variables. The approach delivers simulated counterparts to standard estimation procedures and has inspired the development of entirely new procedures based on the principle of indirect inference.
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Cullinane, Kevin. "Statistical and Econometric Methods for Transportation Data Analysis." Maritime Economics & Logistics 6, no. 2 (June 2004): 187–89. http://dx.doi.org/10.1057/palgrave.mel.9100102.

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Bivand, Roger, Giovanni Millo, and Gianfranco Piras. "A Review of Software for Spatial Econometrics in R." Mathematics 9, no. 11 (June 2, 2021): 1276. http://dx.doi.org/10.3390/math9111276.

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The software for spatial econometrics available in the R system for statistical computing is reviewed. The methods are illustrated in a historical perspective, highlighting the main lines of development and employing historically relevant datasets in the examples. Estimators and tests for spatial cross-sectional and panel models based either on maximum likelihood or on generalized moments methods are presented. The paper is concluded reviewing some current active lines of research in spatial econometric software methods.
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Stock, James H., and Mark W. Watson. "Twenty Years of Time Series Econometrics in Ten Pictures." Journal of Economic Perspectives 31, no. 2 (May 1, 2017): 59–86. http://dx.doi.org/10.1257/jep.31.2.59.

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This review tells the story of the past 20 years of time series econometrics through ten pictures. These pictures illustrate six broad areas of progress in time series econometrics: estimation of dynamic causal effects; estimation of dynamic structural models with optimizing agents (specifically, dynamic stochastic equilibrium models); methods for exploiting information in “big data” that are specialized to economic time series; improved methods for forecasting and for monitoring the economy; tools for modeling time variation in economic relationships; and improved methods for statistical inference. Taken together, the pictures show how 20 years of research have improved our ability to undertake our professional responsibilities. These pictures also remind us of the close connection between econometric theory and the empirical problems that motivate the theory, and of how the best econometric theory tends to arise from practical empirical problems.
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Sirisrisakulchai, Jirakom, Chon Van Le, and Uyen Pham. "On Statistics of Random Sets for Partial Identification of Econometric Structures." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28, Supp01 (August 28, 2020): 87–98. http://dx.doi.org/10.1142/s0218488520400085.

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In this paper, we emphasize and elaborate on two important and relatively new aspects in uncertainty analysis in order to increase the credibility of empirical results in statistics in general, and in econometrics in particular, namely, the problem of partial identification, and the use of random set statistics. We elaborate on the current interests in partially identified models, exemplified by econometric structures involving copulas. We spell out the rationale and the statistical methods based upon random set theory for analyzing partial identification problem towards credible econometrics.
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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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Neuburger, Hugh, and Houston H. Stokes. "Testing the Appropriateness of Statistical Methods." Financial Analysts Journal 47, no. 4 (July 1991): 83–88. http://dx.doi.org/10.2469/faj.v47.n4.83.

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Snell, Joyce, and P. Sprent. "Applied Nonparametric Statistical Methods." Journal of the Royal Statistical Society. Series A (Statistics in Society) 158, no. 2 (1995): 355. http://dx.doi.org/10.2307/2983315.

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Dissertations / Theses on the topic "Econometrics – Statistical methods"

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Huh, Ji Young. "Applications of Monte Carlo Methods in Statistical Inference Using Regression Analysis." Scholarship @ Claremont, 2015. http://scholarship.claremont.edu/cmc_theses/1160.

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This paper studies the use of Monte Carlo simulation techniques in the field of econometrics, specifically statistical inference. First, I examine several estimators by deriving properties explicitly and generate their distributions through simulations. Here, simulations are used to illustrate and support the analytical results. Then, I look at test statistics where derivations are costly because of the sensitivity of their critical values to the data generating processes. Simulations here establish significance and necessity for drawing statistical inference. Overall, the paper examines when and how simulations are needed in studying econometric theories.
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Richard, Patrick. "Sieve bootstrap unit root tests." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103285.

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We consider the use of a sieve bootstrap based on moving average (MA) and autoregressive moving average (ARMA) approximations to test the unit root hypothesis when the true Data Generating Process (DGP) is a general linear process. We provide invariance principles for these bootstrap DGPs and we prove that the resulting ADF tests are asymptotically valid. Our simulations indicate that these tests sometimes outperform those based on the usual autoregressive (AR) sieve bootstrap. We study the reasons for the failure of the AR sieve bootstrap tests and propose some solutions, including a modified version of the fast double bootstrap.
We also argue that using biased estimators to build bootstrap DGPs may result in less accurate inference. Some simulations confirm this in the case of ADF tests. We show that one can use the GLS transformation matrix to obtain equations that can be used to estimate bias in general ARMA(p,q) models. We compare the resulting bias reduced estimator to a widely used bootstrap based bias corrected estimator. Our simulations indicate that the former has better finite sample properties then the latter in the case of MA models. Finally, our simulations show that using bias corrected or bias reduced estimators to build bootstrap DGP sometimes provides accuracy gains.
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McCullough, Michael Paul. "Phase space reconstruction : methods in applied economics and econometrics /." Online access for everyone, 2008. http://www.dissertations.wsu.edu/Dissertations/Spring2008/M_McCullough_122707.pdf.

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He, Wei. "Model selection for cointegrated relationships in small samples." Thesis, Nelson Mandela Metropolitan University, 2008. http://hdl.handle.net/10948/971.

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Vector autoregression models have become widely used research tools in the analysis of macroeconomic time series. Cointegrated techniques are an essential part of empirical macroeconomic research. They infer causal long-run relationships between nonstationary variables. In this study, six information criteria were reviewed and compared. The methods focused on determining the optimum information criteria for detecting the correct lag structure of a two-variable cointegrated process.
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Koh, Jason S. H. "Comparison of the new "econophysics" approach to dealing with problems of financial to traditional econometric methods." Thesis, View thesis, 2008. http://handle.uws.edu.au:8081/1959.7/38828.

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We begin with the outlining the motivation of this research as there are still so many unanswered research questions on our complex financial and economic systems. The philosophical background and the advances of econometrics and econophysics are discussed to provide an overview of the stochastic and nonstochastic modelling and these disciplines are set as a central theme for the thesis. This thesis investigates the effectiveness of financial econometrics models such as Gaussian, ARCH (1), GARCH (1, 1) and its extensions as compared to econophysics models such as Power Law model, Boltzmann-Gibbs (BG) and Tsallis Entropy as statistical models of volatility in US S&P500, Dow Jones and NASDAQ stock index using daily data. The data demonstrate several distinct behavioural characteristics, particularly the increased volatility during 1998 to 2004. Power Laws appear to describe the large fluctuations and other characteristics of stock price changes. Surprisingly, these Power Laws models also show significant correlations for different types and sizes of markets and for different periods and sub-periods of markets. The results show the robustness of Power Law analysis, with the Power Law exponent (0.4 to 2.4) staying within the acceptable range of significance (83% to 97%), regardless of the percentage change in the index return. However, the procedure for testing empirical data against a hypothesised power-law distribution using a simple rank-frequency plot of the data and the data binning process can turn out to be a spurious result for the distribution. As for the stochastic processes such as ARCH (1) and GARCH (1, 1) the models are explicitly confined to the conditional behaviour of the data and the unconditional behaviour has often been described via moments. In reality, it is the unconditional tail behaviour that accounts for the tail behaviour and hence, we have to convert the unconditional tail behaviour and express the models as two-dimensional stochastic difference equation using the processes of Starica (Mikosch 2000). The results show the random walk prediction successfully describes the stock movements for small price fluctuations but fails to handle large price fluctuations. The Power Law tests prove superior to the stochastic tests when stock price fluctuations are substantially divergent from the mean. One of the main points of the thesis is that these empirical phenomena are not present in the stochastic process but emerge in the non-parametric process. The main objective of the thesis is to study the relatively new field of Econophysics and put its work in perspective relative to the established if not altogether successful practice of econometric analysis of stock market volatility. One of the most exciting characteristics of Econophysics is that, as a developing field, no models as yet perfectly represent the market and there is still a lot of fundamental research to be done. Therefore, we begin to explore the application of statistical physics method particularly Tsallis entropy to give a new insights into problems traditionally associated with financial markets. The results of Tsallis entropy surpass all expectations and it is therefore one of the most robust methods of analysis. However, it is now subject to some challenge from McCauley, Bassler et. al., as they found that the stochastic dynamic process (sliding interval techniques) used in fat tail distributions is time dependent.
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Koh, Jason S. H. "Comparison of the new "econophysics" approach to dealing with problems of financial to traditional econometric methods." View thesis, 2008. http://handle.uws.edu.au:8081/1959.7/38828.

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Thesis (Ph.D.)--University of Western Sydney, 2008.
Thesis submitted to fulfil the requirements for the degree of Doctor of Philosophy in the School of Economics and Finance, College of Business, University of Western Sydney. Includes bibliography.
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Johansson, Fredrik. "Essays on measurement error and nonresponse /." Uppsala : Department of Economics, Uppsala University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7920.

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Kilinc, Ata Nurcan. "An exploration of renewable energy policies with an econometric approach." Thesis, University of Stirling, 2015. http://hdl.handle.net/1893/22196.

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This thesis focuses on the renewable energy policies for the case study countries (European Union, United States, United Kingdom, Turkey, and Nigeria) with using quantitative and qualitative analysis. The thesis adopts a three -pronged approach to address three main issues: The first paper investigates a 1990-2008 panel dataset to conduct an econometric analysis of policy instruments, such as; feed-in tariffs, quotas, tenders, and tax incentives, in promoting renewable energy deployment in 27 EU countries and 50 US states. The results suggest that renewable energy policy instruments play a significant role in encouraging renewable energy sources. Using data from 1990 to 2012 with the vector auto regression (VAR) approach for three case study countries, namely United Kingdom, Turkey, and Nigeria, the second paper focuses on how renewable energy consumption as part of total electricity consumption is affected by economic growth and electricity prices. The findings from the VAR model illustrate that the relationship between case study countries’ economic growth and renewable energy consumption is positive and economic growth in case study countries respond positively and significantly. The third paper focuses on the relationship between renewable energy policies and investment in renewables in the countries of United Kingdom and Turkey. The third paper builds upon current knowledge of renewable energy investment and develops a new conceptual framework to guide analyses of policies to support renewables. Past and current trends in the field of renewable energy investment are investigated by reviewing the literature on renewable energy investment linkage with policies, which identifies patterns and similarities in RE investment. This also includes the interview analysis with investors focusing on policies for renewable energy investment. The results from the interview and conceptual analysis show that renewable policies play a crucial role in determining investment in renewable energy sources. The findings from this thesis demonstrate that renewable energy policies increase with a growth of the renewable energy investment in the sector. Finally, the outcomes of this thesis also contribute to the energy economics literature, especially for academic and subsequent research purposes.
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Lau, Wai Kwong. "Bayesian nonparametric methods for some econometric problems /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?ISMT%202005%20LAU.

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Ragusa, Giuseppe. "Essays on moment conditions models econometrics /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3170252.

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Books on the topic "Econometrics – Statistical methods"

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Ramanathan, Ramu. Statistical methods in econometrics. San Diego: Academic Press, 1993.

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Statistical methods in econometrics. San Diego: Academic Press, 1993.

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S, Maddala G., Rao C. Radhakrishna 1920-, and Vinod Hrishikesh D. 1939-, eds. Econometrics. Amsterdam: North-Holland, 1993.

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Economic Statistics and Econometrics. 2nd ed. New York: Macmillan, 1990.

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Economic statistics and econometrics. 3rd ed. Englewood Cliffs, NJ: Prentice Hall, 1995.

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Economic statistics and econometrics. 2nd ed. New York: Macmillan, 1988.

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Aman, Ullah, ed. Nonparametric econometrics. Cambridge: Cambridge University Press, 1999.

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Pagan, A. R. Nonparametric Econometrics. Cambridge, U.K.: Cambridge University Press, 1999.

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C, Porter Dawn, ed. Essentials of econometrics. 4th ed. New York: McGraw-Hill/Irwin, 2010.

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Gujarati, Damodar N. Essentials of econometrics. New York: McGraw-Hill, 1992.

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Book chapters on the topic "Econometrics – Statistical methods"

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Loan, Nguyen Thi, Le Dinh Hac, and Nguyen Viet Hong Anh. "Application of Statistical Methods for Tax Inspection of Enterprises: A Case Study in Vietnam." In Econometrics for Financial Applications, 648–55. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-73150-6_51.

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Perfilieva, Irina. "Fuzzy-Based Methods in Data Analysis with the Focus on Dimensionality Reduction." In Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas, 179–92. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45619-1_14.

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Novák, Vilém, and Viktor Pavliska. "Time Series: How Unusual Local Behavior Can Be Recognized Using Fuzzy Modeling Methods." In Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas, 157–77. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45619-1_13.

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Lee, Cheng-Few, Hong-Yi Chen, and John Lee. "Alternative Methods to Derive Option Pricing Models." In Financial Econometrics, Mathematics and Statistics, 541–69. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9429-8_21.

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Lee, Cheng-Few, Hong-Yi Chen, and John Lee. "Alternative Methods to Deal with Measurement Error." In Financial Econometrics, Mathematics and Statistics, 181–210. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9429-8_7.

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Chen, Li-jiun, and Cheng-der Fuh. "Statistics Methods Applied in Employee Stock Options." In Handbook of Financial Econometrics and Statistics, 841–72. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-7750-1_30.

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Meinl, Thomas, and Edward W. Sun. "Methods of Denoising Financial Data." In Handbook of Financial Econometrics and Statistics, 519–38. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-7750-1_18.

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Do, Van Huyen, Thibault Laurent, and Anne Vanhems. "Guidelines on Areal Interpolation Methods." In Advances in Contemporary Statistics and Econometrics, 385–407. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73249-3_20.

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Manzi, Cecilia, and Federica Piersimoni. "Statistical Systems in Agriculture." In Spatial Econometric Methods in Agricultural Economics Using R, 108–21. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9780429155628-6.

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Lee, Cheng-Few, Hong-Yi Chen, and John Lee. "Nonparametric Method for European Option Bounds." In Financial Econometrics, Mathematics and Statistics, 623–42. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9429-8_24.

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Conference papers on the topic "Econometrics – Statistical methods"

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Franz, Marina, and Zulfia Ibragimova. "Measuring inequality of opportunity: approaches, methods, results." In Multivariate statistical analysis, econometrics and simulation of real processes. Proceedings of Xth International School-Seminar. CEMI RAS, 2020. http://dx.doi.org/10.33276/978-5-8211-0786-2-66-68.

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Svensson, Elisabeth. "Experiencing the complexity of reality before graduation." In Next Steps in Statistics Education. IASE international Association for Statistical Education, 2009. http://dx.doi.org/10.52041/srap.09202.

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The curriculum for undergraduate students offers not only basic statistics courses but also optional courses regarding statistical methods for times series, modelling, epidemiology, econometrics and other topics potentially useful in a statistician’s career. This means that the students believe that they will get a comprehensive statistical toolbox for solving a variety of real life problems after graduation. But can they use the tools in a complex reality? The aim is to present the use of inter-disciplinary statistical problem solving courses for introducing the complexity of reality to statistics students before graduation. Experiences of the discordance between students’ theoretical and practical skills regarding statistical description, analysis and understanding will be given.
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Trofimova, Natalia. "Analysis of social capital functioning in two-level systems based on the application of MCA methods." In Multivariate statistical analysis, econometrics and simulation of real processes. Proceedings of Xth International School-Seminar. CEMI RAS, 2020. http://dx.doi.org/10.33276/978-5-8211-0786-2-139-140.

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Isaeva, Marta. "Planning machine experiments based on the Bayesian method." In Multivariate statistical analysis, econometrics and simulation of real processes. Proceedings of Xth International School-Seminar. CEMI RAS, 2020. http://dx.doi.org/10.33276/978-5-8211-0786-2-69-70.

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Saidova, Markhabo. "Current Obstacles of Business Development in Uzbekistan." In International Conference on Eurasian Economies. Eurasian Economists Association, 2018. http://dx.doi.org/10.36880/c10.02167.

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This article refers to the theoretical and practical aspects of business, its development paths and strategy selection in Uzbek economy, the statistical analyses through methods of observation, collection of statistical data, classification, tabulation; and also diagrams and graphs frequently used in presenting data, dynamic changes, comparison and prognosis of indicators of the development of business, including the ways of improvement of private sector through solve the problems in the formation of economy as well as the perspectives of development of business in Uzbekistan. There are also given econometric modeling and forecasting of business development in GDP through analytical method in dynamic lines, OLS method taking into account the share of business in the number of employed in the volume of production of agricultural products, exports of the Republic of Uzbekistan.
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Nocoń, Aleksandra, and Irena Pyka. "EFFECTIVENESS OF RISK CAPITAL (OWN FUNDS) IN THE POLISH BANKING SECTOR IN THE YEARS OF 2002–2016." In Business and Management 2018. VGTU Technika, 2018. http://dx.doi.org/10.3846/bm.2018.02.

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The analysis of effectiveness of risk capital in the Polish banking sector have become the main aim of the study. In the article, statistical and econometric methods were used, based on a linear regres-sion model of net profit in relation to the value of own funds of the banking sector in Poland in the years of 2002–2016. Next, through the quartile method, there were estimated the relations between effectiveness and a level of risk capital of the largest banks in Poland. Conducted research were aimed to verify the research hypothesis stating that in the Polish banking sector there is a positive cor-relation between net profit and banks’ own funds, which constitute an essential component of bank risk capital.
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Ziankova, Larysa, Sergey Yashin, Vladislav Frolov, Yuliya Popova, and Yuliya Chemodanova. "Unemployment and employment management in the context of digitalization of anti-crisis regulation." In Human resource management within the framework of realisation of national development goals and strategic objectives. Dela Press Publishing House, 2022. http://dx.doi.org/10.56199/dpcsebm.fonc8076.

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The article is devoted to the study of the relationship between the level of employment, unemployment and the dynamics of GDP in the framework of cyclical nature studies of the Belarus national economy, the possibility of digitalization within economic cycle crisis phase anticipation and hence forecasting the unemployment dynamics. The study used a comparative analysis of the employment level statistical base and the dynamics of real GDP growth rates over the last 2 crises based on STATISTICA 10. The non-linear forecast of the employment level in Belarus for 2022 was also made using the Eviews 10 application software packages. The methodological basis for the choice of IT tools was the need to take into account cyclical, seasonal, delayed and prolonged reaction of the labor market to changes in the commodity market. Therefore, polynomial autoregression with distributed lag (PDL) was chosen from econometric methods. The comparative analysis of the employment level statistical base and the dynamics of real GDP growth rates over the last 2 crises showed that the dynamics of the employment level behaves as an acyclic indicator. As a result, an algorithm is proposed for setting a task for programmers when creating a management platform for the labor market and linking it with other parameters of public administration system digitization. The actions proposed will allow to plan the item of consolidated state budget expenditures for the payment of unemployment benefits more accurately and to form the targets of state employment assistance programs.
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Żurek, J., J. Ziółkowski, and A. Borucka. "A method for determination of combat vehicles availability by means of statistic and econometric analysis." In The 2nd International Conference on Engineering Sciences and Technologies. CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742: CRC Press, 2017. http://dx.doi.org/10.1201/9781315210469-371.

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Subotić, Slobodan, Goran Mitrović, and Vladimir Marković. "FINANCIAL LEASING IN THE FUNCTION OF ECONOMIC DEVELOPMENT OF BOSNIA AND HERZEGOVINA (STATISTICAL APPROACH)." In Fourth International Scientific Conference ITEMA Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2020. http://dx.doi.org/10.31410/itema.s.p.2020.81.

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The leasing institution is typical for countries with developed market economies, although it keeps gaining more and more importance in transition countries. Therefore, the research in this paper is focused on the financial leasing market in Bosnia and Herzegovina, as one of the countries undergoing transition process. Its basic features have been assessed, together with determining turnover over the observed ten-year period, both in Bosnia and Herzegovina as a whole and in its respective entities. The research aims to establish to what extent has financial leasing contributed to the development of the small and medium enterprise (SME) sector and the economic development of Bosnia and Herzegovina. Modern statistical methods have been applied to analyze the connection and interdependence of leasing and certain macroeconomic indicators in Bosnia and Herzegovina. For the purpose and in the context of this research, the following indicators, such as the values of leasing, gross domestic product, export, import, and foreign direct investments related to the period from 2009 to 2018 are presented in the respective tables and charts. The analysis is based on the application of descriptive and econometric statistical methods of correlation and regression, as well as on the following statistical packages: IBM SPSS ver. 21, Microsoft XLSTAT. A particular, dedicated segment of the analysis refers to determining the impact of financial leasing on the level of SME investment to classic bank loans. That is, to what extent is financial leasing in the function of investment decision-making of small and medium enterprises in Bosnia and Herzegovina.
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Apak, Sudi, and Ali Osman Serdar Citak. "The Short and Long Term Quantitative Analysis of Supply-Demand Equilibrium of Gold as a Financial Asset and Empirical Testing of Gold Price Function." In International Conference on Eurasian Economies. Eurasian Economists Association, 2016. http://dx.doi.org/10.36880/c07.01462.

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Abstract:
In order to analyze gold as a financial asset requires evaluation both technical features of precious metals and financial markets in the analytical framework. The aim of this study is to analyze the demand and supply functions of gold under the market conditions which are dominated by bullion banks and central bank in both short and long terms. Finally, as first step the mathematical infrastructure of gold price function analyzed and as second step gold price function has been estimated by using econometrical methods. In this study, the one period lagged data of gold price in US dollar and return of US treasury bonds have used for estimating of the model and reached statistically significant results.
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