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Relevant bibliographies by topics / Econometric models

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Academic literature on the topic 'Econometric models'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Econometric models"

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Hozer, Józef, and Mariusz Doszyń. "Econometric Models of Propensities." Folia Oeconomica Stetinensia 6, no. 1 (2007): 15–25. http://dx.doi.org/10.2478/v10031-007-0008-1.

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Econometric Models of Propensities Human being is one of the most important sources of causative forces of events that assemble economical processes. Working out the effective tools that enable measurement of the impact of people on socio-economic processes is necessary in analyzing, troubleshooting and forecasting. In the article the issues of calculating propensities by means of properly specified econometrics models were presented. The definition of propensity was introduced. Questions connected with topic of propensities were presented in context of concepts promoted by Szczecin school of

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Silahtaroğlu, Yenilmez Oğuz. "Machine Learning Integration in Econometric Models." Next Generation Journal for The Young Researchers 8, no. 1 (2024): 77. http://dx.doi.org/10.62802/8c33p210.

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The integration of machine learning (ML) into econometric models represents a transformative advancement in the field of econometrics, enabling researchers to tackle complex, high-dimensional datasets while maintaining the interpretability and rigor of traditional econometric approaches. This research investigates the synergies between machine learning and econometrics, focusing on how ML techniques can enhance model flexibility, predictive accuracy, and causal inference in economic analysis. By leveraging methods such as regularization, ensemble learning, and deep learning, the study explores

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Gruszczyński, Marek. "Accounting and Econometrics: From Paweł Ciompa to Contemporary Research." Journal of Risk and Financial Management 15, no. 11 (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 accounti

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Domínguez, Manuel A., and Ignacio N. Lobato. "A SIMPLE OMNIBUS OVERIDENTIFICATION SPECIFICATION TEST FOR TIME SERIES ECONOMETRIC MODELS." Econometric Theory 31, no. 4 (2014): 891–910. http://dx.doi.org/10.1017/s0266466614000644.

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Despite their theoretical advantages, Integrated Conditional Moment (ICM) specification tests are not commonly employed in the econometrics practice. An important reason is that the employed test statistics are nonpivotal, and so critical values are not readily available. This article proposes an omnibus test in the spirit of the ICM tests of Bierens and Ploberger (1997, Econometrica 65, 1129–1151) where the test statistic is based on the minimized value of a quadratic function of the residuals of time series econometric models. The proposed test falls under the category of overidentification

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de Paula, Áureo. "Econometric Models of Network Formation." Annual Review of Economics 12, no. 1 (2020): 775–99. http://dx.doi.org/10.1146/annurev-economics-093019-113859.

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This article provides a selective review of the recent literature on econometric models of network formation. I start with a brief exposition on basic concepts and tools for the statistical description of networks; then I offer a review of dyadic models, focusing on statistical models on pairs of nodes, and I describe several developments of interest to the econometrics literature. I also present a discussion of nondyadic models in which link formation might be influenced by the presence or absence of additional links, which themselves are subject to similar influences. This argument is relate

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Bolton, Roger. "REGIONAL ECONOMETRIC MODELS*." Journal of Regional Science 25, no. 4 (1985): 495–520. http://dx.doi.org/10.1111/j.1467-9787.1985.tb00320.x.

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Ditzen, Jan, and Simon Reese. "xtnumfac: A battery of estimators for the number of common factors in time series and panel-data models." Stata Journal: Promoting communications on statistics and Stata 23, no. 2 (2023): 438–54. http://dx.doi.org/10.1177/1536867x231175305.

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In this article, we introduce a new community-contributed command, xtnumfac, for estimating the number of common factors in time-series and panel datasets using the methods of Bai and Ng (2002, Econometrica 70: 191–221), Ahn and Horenstein (2013, Econometrica 81: 1203–1227), Onatski (2010, Review of Economics and Statistics 92: 1004–1016), and Gagliardini, Ossola, and Scaillet (2019, Journal of Econometrics 212: 503–521). Common factors are usually unobserved or unobservable. In time series, they influence all predictors, while in paneldata models, they influence all cross-sectional units at d

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Dokumacı, Melis. "AI-Driven Econometric Models for Legal Issues." Human Computer Interaction 8, no. 1 (2024): 137. https://doi.org/10.62802/btfvze98.

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Artificial intelligence (AI) is reshaping the landscape of econometric modeling, offering innovative tools to address complex legal issues involving predictive analysis, resource allocation, and policy evaluation. This research explores the application of AI-driven econometric models to legal challenges, focusing on areas such as contract enforcement, intellectual property disputes, and regulatory compliance. By integrating machine learning with traditional econometric techniques, these models enhance the precision and adaptability of legal forecasts and decision-making processes. Key methodol

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Maziarz, Mariusz. "‘Emerging contrary result’ phenomenon and scientific realism." Panoeconomicus, no. 00 (2020): 24. http://dx.doi.org/10.2298/pan171218024m.

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The article is aimed at reconsidering the question if the project of econometrics can be read in line with scientific realism. Previously, the methodological literature focused on the philosophy of econometrics, voices criticizing realist interpretations of econometrics were raised. The criticism was aimed at showing that econometric models lack robustness. The use of slightly different methods leads to obtaining different and often contrary models what supposedly undermine the project of econometrics. In this article, I aim at offering a new argument in defence of the current practice of the

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Garcia d'Acuña, Eduardo. "Econometric models for planning." CEPAL Review 1990, no. 41 (1990): 193–98. http://dx.doi.org/10.18356/75fb3d71-en.

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Dissertations / Theses on the topic "Econometric models"

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Fahs, Faysal Habib. "Essays in the estimation of systems of limited dependent variables with application to demand systems." Online access for everyone, 2008. http://www.dissertations.wsu.edu/Dissertations/Summer2008/F_Fahs_072508.pdf.

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Conradie, Tiaan. "The South African economy and internationally fuelled business cycles: an econometric analysis." Thesis, Nelson Mandela Metropolitan University, 2015. http://hdl.handle.net/10948/4354.

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The objective of this study is to understand the dynamics of international monetary policy and the relationship that exists between larger more developed economies and smaller less developed economies within a policy context. The 2008 financial crisis has caused intense revival of Austrian economics due to the monetary nature of the recession caused as a subsequent effect of the stock/housing market collapse that occurred in 2007. One factor of the 2008 financial crisis that created intense concern was the extent to which the slowdown in economic activity was able to be transmitted across inte

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Vilela, Lucas Pimentel. "Hypothesis testing in econometric models." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/18249.

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Submitted by Lucas Pimentel Vilela (lucaspimentelvilela@gmail.com) on 2017-05-04T01:19:37Z No. of bitstreams: 1 Hypothesis Testing in Econometric Models - Vilela 2017.pdf: 2079231 bytes, checksum: d0387462f36ab4ab7e5d33163bb68416 (MD5)<br>Approved for entry into archive by Maria Almeida (maria.socorro@fgv.br) on 2017-05-15T19:31:43Z (GMT) No. of bitstreams: 1 Hypothesis Testing in Econometric Models - Vilela 2017.pdf: 2079231 bytes, checksum: d0387462f36ab4ab7e5d33163bb68416 (MD5)<br>Made available in DSpace on 2017-05-15T19:32:18Z (GMT). No. of bitstreams: 1 Hypothesis Testing in Economet

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Castelli, Francesca <1982&gt. "Econometric models of financial risks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amsdottorato.unibo.it/4274/1/Castelli_Francesca_tesi.pdf.

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The goal of this dissertation is to use statistical tools to analyze specific financial risks that have played dominant roles in the US financial crisis of 2008-2009. The first risk relates to the level of aggregate stress in the financial markets. I estimate the impact of financial stress on economic activity and monetary policy using structural VAR analysis. The second set of risks concerns the US housing market. There are in fact two prominent risks associated with a US mortgage, as borrowers can both prepay or default on a mortgage. I test the existence of unobservable heterogeneity in

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Castelli, Francesca <1982&gt. "Econometric models of financial risks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amsdottorato.unibo.it/4274/.

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The goal of this dissertation is to use statistical tools to analyze specific financial risks that have played dominant roles in the US financial crisis of 2008-2009. The first risk relates to the level of aggregate stress in the financial markets. I estimate the impact of financial stress on economic activity and monetary policy using structural VAR analysis. The second set of risks concerns the US housing market. There are in fact two prominent risks associated with a US mortgage, as borrowers can both prepay or default on a mortgage. I test the existence of unobservable heterogeneity in

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Billah, Baki 1965. "Model selection for time series forecasting models." Monash University, Dept. of Econometrics and Business Statistics, 2001. http://arrow.monash.edu.au/hdl/1959.1/8840.

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Spurway, Kayleigh Fay Nanette. "A study of the Consumption Capital Asset Pricing Model's appilcability across four countries." Thesis, Rhodes University, 2014. http://hdl.handle.net/10962/d1013016.

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Historically, the Consumption Capital Asset Pricing Method (C-CAPM) has performed poorly in that estimated parameters are implausible, model restrictions are often rejected and inferences appear to be very sensitive to the choice of economic agents' preferences. In this study, we estimate and test the C-CAPM with Constant Relative Risk Aversion (CRRA) using time series data from Germany, South Africa, Britain and America during relatively short time periods with the latest available data sets. Hansen's GMM approach is applied to estimate the parameters arising from this model. In general, esti

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Paraskevopoulos, Ioannis. "Econometric models applied to production theory." Thesis, Queen Mary, University of London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.392498.

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McGarry, Joanne S. "Seasonality in continuous time econometric models." Thesis, University of Essex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313064.

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Gualdani, C. "Econometric analysis of network formation models." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/1566643/.

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This dissertation addresses topics in the econometrics of network formation models. Chapter 1 provides a review of the literature. Statistical models focus on the specification of the probability distribution of the network. Examples include models in which nodes are born sequentially and meet existing vertices according to random meetings and network-based meetings. Within this group of models, special attention is reserved to the milestone work by Jackson and Rogers (2007): after having discussed and replicated the main results of the paper, an extension of the original model is examined and

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Books on the topic "Econometric models"

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Intriligator, Michael D. Econometric models, techniques, andapplications. 2nd ed. Prentice-Hall International, 1996.

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Nevezhin, Yuriy. Research of econometric models: collection of laboratory works. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1882574.

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The textbook is a collection of laboratory works on the sections "Study of linear econometric models", "Study of nonlinear econometric models", "Time series". Each work includes theoretical and practical parts (tasks with a possible solution). There are also tasks for independent work on each topic being studied. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students studying in the field of Economics, for the purpose of practical study of the sections of the discipline "Econometrics" (bachelors) or "Econometric

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Congress, Econometric Society World. Advances in econometrics. Cambridge University Press, 1987.

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Congress, Econometric Society World. Advances in econometrics: Fifth World Congress. Cambridge University Press, 1994.

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Congress, Econometric Society World. Advances in econometrics: Fifth World Congress. Cambridge University Press, 1987.

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Gruber, Josef, ed. Econometric Decision Models. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-51675-7.

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1948-, Fischer Joachim, ed. Macro-econometric models. 2nd ed. Avebury, 1992.

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K, Puttaswamaiah, ed. Econometric models: Techniques and applications. Indus, 1994.

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Pötscher, Benedikt M., and Ingmar R. Prucha. Dynamic Nonlinear Econometric Models. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-662-03486-6.

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1963-, Franses Philip Hans, and Montgomery A, eds. Econometric models in marketing. JAI, 2002.

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Book chapters on the topic "Econometric models"

1

Dubé, Jean, and Diègo Legros. "Spatial Econometric Models." In Spatial Econometrics Using Microdata. John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119008651.ch4.

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LeSage, James P., and R. Kelley Pace. "Spatial Econometric Models." In Handbook of Applied Spatial Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03647-7_18.

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Asteriou, Dimitrios, and Stephen G. Hall. "Dynamic Econometric Models." In Applied Econometrics. Macmillan Education UK, 2016. http://dx.doi.org/10.1057/978-1-137-41547-9_10.

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Jiao, Xiaoying, and Jason Li Chen. "Spatiotemporal econometric models." In Econometric Modelling and Forecasting of Tourism Demand. Routledge, 2022. http://dx.doi.org/10.4324/9781003269366-6.

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Zong, Ping. "Dynamic Econometric Models." In The Art and Science of Econometrics. Routledge, 2022. http://dx.doi.org/10.4324/9781003273905-7.

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Mizen, Paul. "Econometric methods." In Buffer Stock Models and the Demand for Money. Macmillan Education UK, 1994. http://dx.doi.org/10.1007/978-1-349-23660-2_4.

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Italianer, Alexander. "Econometric Specification." In Theory and Practice of International Trade Linkage Models. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4472-5_6.

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LeSage, James P., and R. Kelley Pace. "Interpreting Spatial Econometric Models." In Handbook of Regional Science. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-642-36203-3_91-1.

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Pace, R. Kelley, and James P. LeSage. "Spatial Econometric Models, Prediction." In Encyclopedia of GIS. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23519-6_1266-2.

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Pace, R. Kelley, and James P. LeSage. "Spatial Econometric Models, Prediction." In Encyclopedia of GIS. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-17885-1_1266.

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Conference papers on the topic "Econometric models"

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Cedolin, Michele, and Mujde Erol Genevois. "Cash Demand Prediction Problem using Econometric and Computational Intelligence Forecasting Models." In 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2024. http://dx.doi.org/10.1109/codit62066.2024.10708473.

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Ivanyuk, Vera, Anatoly Tsvirkun, David Petrosov, Alexander Voronov, Pavel Tereliansky, and Natalia Shchukina. "Econometric Model of the Indicator for Identifying Crisis Situations." In 2024 17th International Conference on Management of Large-Scale System Development (MLSD). IEEE, 2024. http://dx.doi.org/10.1109/mlsd61779.2024.10739537.

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Demianchuk, Maryna, Natalia Maslii, and Valerijs Skribans. "GRP Econometric Models for Regions of Ukraine." In the 2019 10th International Conference. ACM Press, 2019. http://dx.doi.org/10.1145/3345035.3345056.

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Lippi, Marco. "Aggregation and dynamics in one-equation econometric models." In 1986 25th IEEE Conference on Decision and Control. IEEE, 1986. http://dx.doi.org/10.1109/cdc.1986.267526.

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Islamov, Bakhtiyor, Munisa Turdibaeva, and Asomiddin Yusupov. "METHODOLOGICAL ISSUES OF ECONOMETRIC ESTIMATING EXPORT GRAVITY MODELS." In ICFNDS '22: The 6th International Conference on Future Networks & Distributed Systems. ACM, 2022. http://dx.doi.org/10.1145/3584202.3584244.

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Ivanyuk, Vera. "Econometric Forecasting Models Based on Forecast Combination Methods." In 2018 Eleventh International Conference "Management of large-scale system development" (MLSD 2018). IEEE, 2018. http://dx.doi.org/10.1109/mlsd.2018.8551825.

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Пугачева, Ольга. "Use of econometric models for solvency analysis and estimation of probability of bankruptcy of the enterprise." In International Scientific Conference “30 Years of Economic Reforms in the Republic of Moldova: Economic Progress via Innovation and Competitiveness”. Academy of Economic Studies of Moldova, 2022. http://dx.doi.org/10.53486/9789975155663.01.

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The article is devoted to the analysis of modern approaches to assessing the solvency and probability of bankruptcy of the enterprise using econometric models. An example of building an econometric model based on the national methodology for analyzing the solvency of a business entity is given

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Khylko, I. I., and K. O. Yatsenko. "YIELD FORECASTING MODELS AS A MEANS OF ENSURING FOOD SECURITY STABILITY." In FOOD SECURITY OF UKRAINE IN THE CONDITIONS OF POST-WAR RECOVERY: GLOBAL AND NATIONAL DIMENSIONS. MYKOLAIV NATIONAL AGRARIAN UNIVERSITY, 2025. https://doi.org/10.31521/978-617-7149-86-5-84.

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The paper deals with the issues of food security in Ukraine. Yield forecasting models as a means of ensuring the stability of food supply are analyzed. Particular attention is paid to the econometric analysis of the impact of factors on food security, the application of the relevant econometric model and the digital transformation of the agro-industrial complex in the context of global instability.

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Kovalchuk, Olha, Mykola Shynkaryk, and Mariia Masonkova. "Econometric Models for Estimating the Financial Effect of Cybercrimes." In 2021 11th International Conference on Advanced Computer Information Technologies (ACIT). IEEE, 2021. http://dx.doi.org/10.1109/acit52158.2021.9548490.

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Sedlak, Otilija, Jelena Birovljev, Zoran Ciric, Jelica Eremic, and Ivana Ciric. "ANALYSIS OF COMPETITIVENESS OF HIGHER EDUCATION WITH ECONOMETRIC MODELS." In International Conference on Education and New Learning Technologies. IATED, 2016. http://dx.doi.org/10.21125/edulearn.2016.1121.

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Reports on the topic "Econometric models"

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de Paula, Áureo. Econometric Models of Network Formation. The IFS, 2020. http://dx.doi.org/10.1920/wp.cem.2020.420.

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Hansen, Lars Peter, John Heaton, and Erzo G. J. Luttmer. Econometric Evaluation of Asset Pricing Models. National Bureau of Economic Research, 1993. http://dx.doi.org/10.3386/t0145.

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Lo, Andrew, A. Craig MacKinlay, and June Zhang. Econometric Models of Limit-Order Executions. National Bureau of Economic Research, 1997. http://dx.doi.org/10.3386/w6257.

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Chetverikov, Denis. Testing regression monotonicity in econometric models. Institute for Fiscal Studies, 2012. http://dx.doi.org/10.1920/wp.cem.2012.3512.

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Chernozhukov, Victor, Christian Hansen, and Alexandre Belloni. Inference for high-dimensional sparse econometric models. Institute for Fiscal Studies, 2011. http://dx.doi.org/10.1920/wp.cem.2011.4111.

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Ludwig, Jens, Sendhil Mullainathan, and Ashesh Rambachan. Large Language Models: An Applied Econometric Framework. National Bureau of Economic Research, 2025. https://doi.org/10.3386/w33344.

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Kaczmarek, Tomasz. Input Data for the Model Determined Based on Econometric Models. Publishing House of the University of Agriculture in Krakow, 2024. http://dx.doi.org/10.15576/repourk/2024.1.05.

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Mullahy, John. Multivariate Fractional Regression Estimation of Econometric Share Models. National Bureau of Economic Research, 2010. http://dx.doi.org/10.3386/w16354.

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Heckman, James, and Christopher Taber. Econometric Mixture Models and More General Models for Unobservables in Duration Analysis. National Bureau of Economic Research, 1994. http://dx.doi.org/10.3386/t0157.

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Diebold, Francis, and Til Schuermann. Exact Maximum Likelihood Estimation of Observation-Driven Econometric Models. National Bureau of Economic Research, 1996. http://dx.doi.org/10.3386/t0194.

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