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Journal articles on the topic 'Econometric model'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 June 2025

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1

Kazakevičius, Vytautas, and Remigijus Leipus. "ON STATIONARITY IN THE ARCH(∞) MODEL." Econometric Theory 18, no. 1 (2002): 1–16. http://dx.doi.org/10.1017/s0266466602181011.

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We continue investigation of the ARCH(∞) model begun in Giraitis, Kokoszka, and Leipus (2000, Econometric Theory 16, 3–22). Nonrestrictive conditions for the existence of a strictly stationary solution are established. The paper generalizes the results of Nelson (1990, Econometric Theory 6, 318–334) and Bougerol and Picard (1992, Journal of Econometrics 52, 115–127) to the ARCH(∞) model.

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2

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 applications in macroeconomic forecasting, policy evaluation, and market analysis. Furthermore, it addresses the challenges of balancing interpretability with predictive performance, emphasizing the need for hybrid frameworks that merge machine learning's adaptability with econometrics' theoretical foundation. The findings demonstrate the potential of ML-enhanced econometric models to revolutionize economic research and policy-making by providing robust, data-driven insights.

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3

Ridge, Richard S., Gary A. Stern, and Ronald K. Watts. "Econometric Model Evaluation." Evaluation Review 14, no. 3 (1990): 308–14. http://dx.doi.org/10.1177/0193841x9001400306.

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4

Phillips, Peter C. B. "Econometric Model Determination." Econometrica 64, no. 4 (1996): 763. http://dx.doi.org/10.2307/2171845.

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5

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 restriction tests started by Sargan (1958, Econometrica 26, 393–415). The corresponding projection interpretation leads us to propose a straightforward wild bootstrap procedure that requires only linear regressions to estimate the critical values irrespective of the model functional form. Hence, contrary to other existing ICM tests, the critical values are easily calculated while the test preserves the admissibility property of ICM tests.

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Sabirov, Khasan Nusratovich, and Xusan Shermatov. "THE ROLE OF ECONOMIC ANALYSIS IN ECONOMIC DEVELOPMENT." Eurasian Journal of Academic Research 2, no. 2 (2022): 736–39. https://doi.org/10.5281/zenodo.6346818.

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Econometric knowledge is distinguished and formed as a result of the interdependence and development of disciplines such as economic theory, economic mathematics, economic statistics, probability theory, and mathematical statistics. Econometrics shapes its subject, purpose, and research. At the same time, the content of econometrics, its composition and scope are in constant contact with the above disciplines.

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Vassalos, Constantine. "ECONOMETRICS AND HEALTHCARE – THE MODEL OF THE GREEK NATIONAL PRIMARY HEALTHCARE NETWORK (PEDY)." PERIOPERATIVE NURSING 4, no. 3 (2015): 152–64. https://doi.org/10.5281/zenodo.44231.

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Abstract Introduction: Nowadays, the development of econometric techniques has important applications in the health sector. Econometrics facilitates the understanding of the environment where health agencies function so that they can make decisions in order to improve their performance. Moreover, the evaluation of the efficiency of health organizations contributes to the health system. This study included searching on Greek and international electronic databases by using keywords such as econometrics, health, National Health System, Social Insurance Institution, Health Centre, decision-making unit, data envelopment analysis, National Primary Healthcare Network, primary health care. In the literature, it is cited that there was a need to develop econometric techniques in relation to the existing efficiency of healthcare facilities, the administrative decision within the country’s health system, the selection of effective health interventions for planning health services, and the acceptance of administrative reform on healthcare. Econometrics was also used to evaluate the public’s acceptance of the reforms, including that of PEDY, which had been undertaken in Greece’s public health system. Econometrics produces information for managers so that they can choose the best possible strategy in financial and administrative level to reform the health system. The application of econometric techniques contributes to the economic evaluation of the health system, including the newly introduced national primary healthcare network (PEDY); identifies the factors associated with the increasing trend of demand for health services; and prepares the administration, whether centralized or regional, for future action plans in line with the health needs of the Greek population.

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8

Lombardini, Simone. "Italian regional econometric model." Papers in Regional Science 103, no. 6 (2024): 100060. http://dx.doi.org/10.1016/j.pirs.2024.100060.

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9

Forchini, G. "OPTIMAL SIMILAR TESTS FOR STRUCTURAL CHANGE FOR THE LINEAR REGRESSION MODEL." Econometric Theory 18, no. 4 (2002): 853–67. http://dx.doi.org/10.1017/s0266466602184027.

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This paper analyzes similar tests for structural change for the normal linear regression model in finite samples. Using the approach of Wald (1943, American Mathematical Society Transactions 54, 426–482), Hillier (1987, Econometric Theory 3, 1–44), Andrews and Ploberger (1994, Econometrica 62, 1382–1414), and Andrews, Lee, and Ploberger (1996, Journal of Econometrics 70, 9–36), we characterize a class of optimal similar tests for the existence of (possibly multiple) changepoints at unknown times. We extend the analysis of Andrews et al. (1996) by deriving weighted optimal similar tests for the case where the error variance is not known. We also show that when the sample size is large, the tests of Andrews et al. constructed by replacing the error variance with an estimate are equivalent to the optimal test derived in this paper. Power comparisons are provided by a small simulation study.

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10

Rancan, Antonella. "Econometric modelling in Italy: From economic planning to academic research." HISTORY OF ECONOMIC THOUGHT AND POLICY, no. 1 (November 2021): 63–82. http://dx.doi.org/10.3280/spe2021-001003.

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The paper deals with the introduction and acceptance of econometric model-ling as a tool to conduct economic policy analysis in Italy in the Post War. A re-search practice first applied in public and private institutions other than universi-ties. It is argued that economic planning and policymakers' needs of empirical es-timations, simulations and forecasts played an important role in supporting quan-titative research, at the time when economics was still conceived as a theoretical discipline. Sylos Labini's (1967) econometric model, the Modellaccio (1970-75), the University of Bologna model (1976) were the first examples of econometric modelling activities within academia. Only since the late 1980s, also due to a gen-erational change, econometrics is fully accepted and introduced in economics cur-ricula with the discipline that aligned to international standards.

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11

LeSage, James P., and Olivier Parent. "Bayesian Model Averaging for Spatial Econometric Models." Geographical Analysis 39, no. 3 (2007): 241–67. http://dx.doi.org/10.1111/j.1538-4632.2007.00703.x.

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12

Chung, Joseph H. "Introduction." L'Actualité économique 51, no. 4 (2009): 505–9. http://dx.doi.org/10.7202/800641ar.

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Abstract One of the most significant post-war development in economics has been the contribution of econometrics to the refinement of techniques of analysis. Econometrics is now an integral part of economics teaching in most of the known universities throughout the world and large econometric models are being used for economic policies in industrialized countries. The CANDIDE model (Canadian Disaggregated Inter-Departmental Econometric Model) is a medium-term policy oriented model and an indication of some degree of maturity in the Art of model building in CANADA. The purpose of this special issue of L'Actualité Économique is to initiate undergraduate students in economics as well as the interested public to the model, to show how the model can be applied and finally to discuss some of its deficiencies. It is hoped that this special issue will be a useful tool for the teaching of econometrics in Canada. It has three parts. The first part comprising three papers, explains the nature and the characteristics of the model. The second part through five papers shows various applications of the model. Finally, in the third part, seven papers discuss some of the deficiencies of the major blocks of the model1. 1 Only the first two parts are included in this issue. The third part will be published in the next issue.

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Chen, Wenhui. "Discussion on Collaborative Teaching of Econometrics in the Field of Environmental Economics." Journal of Contemporary Educational Research 7, no. 11 (2023): 154–59. http://dx.doi.org/10.26689/jcer.v7i11.5590.

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To capitalize on the synergies between the Econometrics course and the Environmental Economics major, this paper aims to enhance students’ability to conduct empirical analysis and practical application using econometric models. It also seeks to promote collaborative teaching through case studies and model research. The primary focus is on the hot research issues within the field of environmental economics, utilizing the econometric model as a vehicle for instruction. To achieve this, the paper proposes the development of a comprehensive case library specific to environmental economics. This resource will serve to optimize the case teaching approach, incorporating the use of econometric software, and fostering interactive teaching models between educators and students. By implementing these strategies, the paper outlines a path and mode for collaborative teaching that effectively bridges the gap between conometrics and environmental economics.

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14

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 economists devoted to the empirical branch of macroeconomics. To do so, I apply M?ki?s (2009) model of representation to three case studies of contradictory pairs of econometric models and argue that contrary results are not necessarily a drawback of econometrics. Instead, the seemingly contradictory pairs of models are useful in various contexts constituted by their purpose and audience.

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15

Franjo, Štiblar, Oplotnik Žan, and Vukotić Veselin. "Montenegrin Quarterly Macroeconomic Econometric Model." Prague Economic Papers 15, no. 2 (2006): 156–71. http://dx.doi.org/10.18267/j.pep.282.

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16

Lady, George M., and Carlisle E. Moody. "Econometric Modeling and Model Falsification." Advances in Pure Mathematics 09, no. 09 (2019): 762–76. http://dx.doi.org/10.4236/apm.2019.99036.

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17

Bidabad, Bijan. "A Small Macro-Econometric Model." American Finance & Banking Review 4, no. 1 (2019): 22–31. http://dx.doi.org/10.46281/amfbr.v4i1.287.

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Different sizes of macro-econometric models are used for different policy purposes. In this paper, we introduce a small macro-econometric model that includes macro-aggregates variables that can be solved dynamically and be used as a sample model to be estimated for other countries.

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18

Witt, Christine A., and Stephen F. Witt. "Appraising An Econometric Forecasting Model." Journal of Travel Research 28, no. 3 (1990): 30–34. http://dx.doi.org/10.1177/004728759002800305.

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19

Shishido, Shuntaro, Fumimasa Hamada, Sei Kuribayashi, Mitsuo Yamada, and Mikio Suga. "Symposium of Macro Econometric Model." Input-Output Analysis 18, no. 1-2 (2010): 3–23. http://dx.doi.org/10.11107/papaios.18.1-2_3.

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20

Petersen, C. E., and A. Cividini. "Vectorization and Econometric Model Simulation." IFAC Proceedings Volumes 22, no. 5 (1989): 569–75. http://dx.doi.org/10.1016/s1474-6670(17)53506-5.

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21

Bechtold, Brigitte H. "A methodologist's econometric model selection." International Advances in Economic Research 1, no. 2 (1995): 119–28. http://dx.doi.org/10.1007/bf02295966.

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22

Petersen, Christian E., and Andrea Cividini. "Vectorization and econometric model simulation." Computer Science in Economics and Management 2, no. 2 (1989): 103–17. http://dx.doi.org/10.1007/bf00435828.

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23

Bezverkhyi, Kostiantyn. "Econometric model for quality evaluation of integrated reporting." Herald of Ternopil National Economic University, no. 3(89) (October 10, 2018): 96–104. http://dx.doi.org/10.35774/visnyk2018.03.096.

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The article considers the issues of evaluating the quality of integrated reporting in economic entities through using an econometric model. It is proved that the econometric model developed for monitoring the quality of integrated reporting is an effective tool for evaluation. Therefore, the subject matter of the article is an econometric model for quality evaluation of integrated reporting, and the study object is the quality of integrated reporting. Accordingly, the research objective is to develop an econometric model for quality evaluation of integrated reporting. The achievement of the objective requires solving the following tasks: 1) to establish a criterion for developing an econometric model for quality evaluation of integrated reporting; 2) to analyse changes of indicators, which affect the quality of integrated reporting; 3) to develop a correlation matrix for the connection of criteria included in integrated reporting; 4) to determine how indicators, which are included in integrated reporting, affect its quality; to analyse the outcomes of developing an econometric model for quality evaluation of integrated reporting. The proposed methods used for developing an econometric model for quality evaluation of integrated reporting in economic entities are as follows: analysis, synthesis, induction, deduction, abstraction, idealization, generalization, and modeling. The theoretical framework and further elaboration of practical steps towards quality evaluation of integrated reporting through using an econometric model is relevant and important for users of such reporting. The results of international annual competitions on quality evaluation of integrated reporting in European economic entities and enterprises of South Africa are presented. Introducing an econometric model for quality evaluation of integrated reporting is of particular importance for countries in transition. The study proposes approaches for quality evaluation of integrated reporting through using an econometric model. The obtained findings serve as a guide for setting new standards of integrated reporting in entities. In entities, the findings might be used to prepare, submit and make public reporting. In conclusion, the paper outlines future prospects which are aimed at using three more criteria for developing an econometric model of quality evaluation of integrated reporting, namely: 1) disclosure of information on performance in sustainable development; 2) compliance with the recommendations of the International Integrated Reporting Council; 3) interaction between interested parties.

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Mohammad, Naim Azimi. "Rationalizing an Econometric Test Model: An Empirical Investigation of ARCH Family Models." Journal of Research in Business, Economics and Management 5, no. 4 (2016): 625–34. https://doi.org/10.5281/zenodo.3965517.

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Selecting an appropriate econometric testing model is of high value to scholars of this field. The central focus of this paper is to empirically investigate the rationality and appropriateness of an econometric testing model for time series macroeconomic variables that exhibit clustering volatility. We test the India’s Producer Price Index (PPI) covering the period January 01, 1947 to October 30, 2015 arranged on monthly basis by using the ARCH family models. The empirical investigation and statistical analysis show that among ARCH, GARCH, TARCH, PARCH and EGARCH models, the most rationale and appropriate testing model for PPI and as such variables that share common nature is the GARCH model as its statisitical result displays lower values for AIC, SIC and HIC that positively correspond with theoretical foundation of the econometric literature and satisfy the philosophical requirements.  

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25

Shabani, Zeinab, Shahin Rafiee, and Hossein Mobli. "Econometric Model on Energy Input and Yield in Carnation Flower." Journal of Agricultural Science and Applications 01, no. 01 (2012): 8–12. http://dx.doi.org/10.14511/jasa.2012.010102.

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26

Larocca, Roger. "Reconciling Conflicting Gauss-Markov Conditions in the Classical Linear Regression Model." Political Analysis 13, no. 2 (2005): 188–207. http://dx.doi.org/10.1093/pan/mpi011.

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This article reconciles conflicting accounts of Gauss-Markov conditions, which specify when ordinary least squares (OLS) estimators are also best linear unbiased (BLU) estimators. We show that exogeneity constraints that are commonly assumed in econometric treatments of the Gauss-Markov theorem are unnecessary for OLS estimates of the classical linear regression model to be BLU. We also generalize a set of necessary and sufficient conditions first established by McElroy (1967, Journal of the American Statistical Association 62:1302–1304), but not yet generally recognized in the econometric literature, that are appropriate for many political science applications. McElroy's conditions relax the traditional Gauss-Markov restriction on autocorrelation in the errors to allow a type of correlation, exchangeability, that has two desirable characteristics: (1) exchangeable data occur in a potentially important class of political science models, and (2) the form of autocorrelation that occurs in exchangeable data has a ready intuition. We thus show that a common class of sample selection models that does not satisfy the Gauss-Markov conditions specified in econometrics textbooks is, in fact, BLU under OLS estimation.

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27

Cassing, S., and F. Giarratani. "A Simulation-Oriented Regional Econometric Model." Environment and Planning A: Economy and Space 18, no. 12 (1986): 1611–28. http://dx.doi.org/10.1068/a181611.

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This paper concerns the structure and application of an econometric model of the Pittsburgh region. A distinction is drawn between forecasting models and those to be used for policy simulation. With this in mind, a simulation-oriented model based on annual data is specified and applied.

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28

Dritsakis, Nikolaos, and Spiros Athanasiadis. "An Econometric Model of Tourist Demand." Journal of Hospitality & Leisure Marketing 7, no. 2 (2000): 39–49. http://dx.doi.org/10.1300/j150v07n02_03.

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29

International Monetary Fund. "MULTIMOD: A Multi-Region Econometric Model." IMF Working Papers 88, no. 23 (1988): 1. http://dx.doi.org/10.5089/9781451921014.001.

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30

Wiśniewski, Jerzy Witold. "Empirical Econometric Model of an Enterprise." Folia Oeconomica Stetinensia 16, no. 1 (2016): 232–47. http://dx.doi.org/10.1515/foli-2016-0015.

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Abstract This work will present an empirical econometric model describing an enterprise within the category of medium-sized companies (according to European Union classification). The company, code-named ENERGY, carries out a manufacturing, commercial, and service business activity. The statistical data used was in the form of quarterly time series, containing 24 statistical observations from the years 2008–2013. A hypothetical model of the enterprise is a system of interdependent equations. The econometric model is composed of seven stochastic equations. The empirical model is missing the equation describing investments in the enterprise. It results from the fact, that during the years 2008–2013 the company suffered meagre investments. Investment output equation, therefore, does not provide any relevant systemic information for the management, since most statistical information in the time series assumes zero values. An empirical model of the company ENERGY is a system of interdependent equations, with statistically significant feedback between labour efficiency (EFEMP) and the average pay per 1 employee (APAY). Additionally, there is recurrence of the relationships between the fixed assets (FIXAS), employment volume (EMP), and the size of the net sales income (SNET). The empirical equations of the model are characterized by a description accuracy of individual endogenous variables. The model also has good decision-making and forecasting qualities.

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31

WANG, STANLEY D. H., and CHRISTOPHER B. KELLOGG. "An Econometric Model for American Lobster." Marine Resource Economics 5, no. 1 (1988): 61–70. http://dx.doi.org/10.1086/mre.5.1.42871965.

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32

Gilli, Manfred, and Giorgio Pauletto. "Econometric Model Simulation On Parallel Computers." International Journal of Supercomputing Applications 7, no. 3 (1993): 254–64. http://dx.doi.org/10.1177/109434209300700306.

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33

Niedercorn, John H., and John F. Kain. "AN ECONOMETRIC MODEL OF METROPOLITAN DEVELOPMENT." Papers in Regional Science 11, no. 1 (2005): 123–43. http://dx.doi.org/10.1111/j.1435-5597.1963.tb01894.x.

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34

Anderson, Evan E., and Yu-Min Chen. "Microcomputer software evaluation: An econometric model." Decision Support Systems 19, no. 2 (1997): 75–92. http://dx.doi.org/10.1016/s0167-9236(96)00042-5.

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35

Dinenis, Elias, Sean Holly, Paul Levine, and Peter Smith. "The London Business School econometric model." Economic Modelling 6, no. 3 (1989): 243–351. http://dx.doi.org/10.1016/0264-9993(89)90026-6.

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36

Mátyás, László. "The Gravity Model: Some Econometric Considerations." World Economy 21, no. 3 (1998): 397–401. http://dx.doi.org/10.1111/1467-9701.00136.

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37

Granato, Jim. "An Agenda For Econometric Model Building." Political Analysis 3 (1991): 123–54. http://dx.doi.org/10.1093/pan/3.1.123.

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This article addresses the lack of cohesion in econometric model building. This incoherence contributes to model building based on statistical criteria—correcting residuals—and not theoretical criteria. The models we build, therefore, are not valid replications of theory. To deal with this problem, an agenda for model building is outlined and discussed. Drawing on the methodological approaches of Hendry, Qin, and Favero (1989), Hendry and Richard (1982, 1983), Sargan (1964), and Spanos (1986), this agenda incorporates a “general to simple” modeling philosophy, a battery of diagnostic tests, reduction theory, and the development of models that include short-term and long-term parameters. A comparison is made between a model based on this agenda and a model based on corrected residuals. The findings show that the agenda-based model outperforms the residual correction model.

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Cicinelli, Claudio, Andrea Cossio, Francesco Nucci, Ottavio Ricchi, and Cristian Tegami. "The Italian Treasury Econometric Model (ITEM)." Economic Modelling 27, no. 1 (2010): 125–33. http://dx.doi.org/10.1016/j.econmod.2009.08.001.

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Fair, Ray C. "Properties of a multicountry econometric model." Journal of Policy Modeling 9, no. 1 (1987): 83–123. http://dx.doi.org/10.1016/0161-8938(87)90005-6.

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40

Li, Qi. "Consistent model specification tests for time series econometric models." Journal of Econometrics 92, no. 1 (1999): 101–47. http://dx.doi.org/10.1016/s0304-4076(98)00087-6.

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41

Skoruks, Dmitrijs, and Maija Šenfelde. "ECONOMETRIC METHODOLOGY OF MONOPOLIZATION PROCESS EVALUATION." Business, Management and Education 12, no. 1 (2014): 47–59. http://dx.doi.org/10.3846/bme.2014.04.

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The research “Econometric Methodology of Monopolization Process Evaluation” gives a perspective description of monopolization process’ nature, occurrence source, development procedure and internal conjuncture specifics, as well as providing an example of modern econometrical method application within a unified framework of market competition analysis for the purpose of conducting a quantitative competition evaluation on an industry level for practical use in both private and public sectors. The main question of the aforementioned research is the definition and quantitative analysis of monopolization effects in modern day globalized markets, while constructing an empirical model of the econometric analysis, based on the use of international historical experience of monopoly formations standings, with the goal of introducing a further development scheme for the use of both econometrical and statistical instruments in line with the forecasting and business research need of enterprises and regulatory functions of the public sector. The current research uses a vast variety of monopolization evaluation ratios and their econometrical updates on companies that are involved in the study procedure in order to detect and scallar measure their market monopolizing potential, based on the implemented acquired market positions, turnover shares and competition policies.

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Phillips, P. C. B. "Partially Identified Econometric Models." Econometric Theory 5, no. 2 (1989): 181–240. http://dx.doi.org/10.1017/s0266466600012408.

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This paper studies a class of models where full identification is not necessarily assumed. We term such models partially identified. It is argued that partially identified systems are of practical importance since empirical investigators frequently proceed under conditions that are best described as apparent identification. One objective of the paper is to explore the properties of conventional statistical procedures in the context of identification failure. Our analysis concentrates on two major types of partially identified model: the classic simultaneous equations model under rank condition failures; and time series spurious regressions. Both types serve to illustrate the extensions that are needed to conventional asymptotic theory if the theory is to accommodate partially identified systems. In many of the cases studied, the limit distributions fall within the class of compound normal distributions. They are simply represented as covariance matrix or scalar mixtures of normals. This includes time series spurious regressions, where representations in terms of functionals of vector Brownian motion are more conventional in recent research following earlier work by the author.

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Kwilosz, Tadeusz, and Bogdan Filar. "Ekonometryczny model zużycia paliw ciekłych." Nafta-Gaz 75, no. 7 (2019): 404–12. http://dx.doi.org/10.18668/ng.2019.07.04.

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Al-Juwari, Munadhil, Khalil Hameed Radhi, and Amer Omran AI-Mamouri. "Analytical Explanations of the Concept of the Fixed Term and the Random Error Term in Econometric Models." International Journal of Religion 5, no. 8 (2024): 1037–45. http://dx.doi.org/10.61707/jk5d4748.

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The error term or disturbance term plays an important role in the econometric model, and there are several reasons for including it in the econometric model, including issues related to measurement problems, the omission of variables from the econometric model, or for contingency reasons or related to abnormal human behavior from the general rule, or for inaccurate description of the models or inaccurate preparation of the data. The fixed term or intercept also has different meanings in the econometric model, such as the mathematical meaning, the econometric meaning, the fixed term without meaning, or the fixed term with a negative sign, and others.

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Abdunazarova, Shakhnoza. "ANALYSIS OF ECONOMETRIC MODELING STEPS." TECHNICAL SCIENCE RESEARCH IN UZBEKISTAN 2, no. 9 (2024): 29–31. https://doi.org/10.5281/zenodo.13895176.

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This article investigates the main stages of econometric modeling, their unique characteristics in various fields and the economy, as well as the sequence and content of the stages of economic-mathematical modeling

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Cho, Jin Seo, and Halbert White. "DIRECTIONALLY DIFFERENTIABLE ECONOMETRIC MODELS." Econometric Theory 34, no. 5 (2017): 1101–31. http://dx.doi.org/10.1017/s0266466617000354.

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The current article examines the limit distribution of the quasi-maximum likelihood estimator obtained from a directionally differentiable quasi-likelihood function and represents its limit distribution as a functional of a Gaussian stochastic process indexed by direction. In this way, the standard analysis that assumes a differentiable quasi-likelihood function is treated as a special case of our analysis. We also examine and redefine the standard quasi-likelihood ratio, Wald, and Lagrange multiplier test statistics so that their null limit behaviors are regular under our model framework.

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Zhao, Xuemei, and Guofeng Yu. "Data-Driven Spatial Econometric Analysis Model for Regional Tourism Development." Mathematical Problems in Engineering 2021 (May 8, 2021): 1–7. http://dx.doi.org/10.1155/2021/6631833.

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Taking 16 cities in Anhui province as research units, based on the research perspective of spatial econometrics, using spatial autocorrelation analysis, this paper investigates the spatial correlation of regional tourism industry in Anhui province, indicating that regional per capita tourism income in Anhui province has obvious positive spatial autocorrelation and relatively obvious local spatial cluster characteristics. To further explore the influence factors of the development level of the regional tourism industry in Anhui and construct the spatial econometric model, the model results show that the Anhui tourism industry development has been accompanied by spatial agglomeration process, per capita GDP, the number of star-rated hotels, fixed assets investment, and employment in the tertiary industry which play a significant role for tourism development. Finally, some countermeasures and suggestions are put forward to promote the development of regional tourism in Anhui province.

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Kim, Dong-sup, and Seungwoo Shin. "THE ECONOMIC EXPLAINABILITY OF MACHINE LEARNING AND STANDARD ECONOMETRIC MODELS-AN APPLICATION TO THE U.S. MORTGAGE DEFAULT RISK." International Journal of Strategic Property Management 25, no. 5 (2021): 396–412. http://dx.doi.org/10.3846/ijspm.2021.15129.

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This study aims to bridge the gap between two perspectives of explainability−machine learning and engineering, and economics and standard econometrics−by applying three marginal measurements. The existing real estate literature has primarily used econometric models to analyze the factors that affect the default risk of mortgage loans. However, in this study, we estimate a default risk model using a machine learning-based approach with the help of a U.S. securitized mortgage loan database. Moreover, we compare the economic explainability of the models by calculating the marginal effect and marginal importance of individual risk factors using both econometric and machine learning approaches. Machine learning-based models are quite effective in terms of predictive power; however, the general perception is that they do not efficiently explain the causal relationships within them. This study utilizes the concepts of marginal effects and marginal importance to compare the explanatory power of individual input variables in various models. This can simultaneously help improve the explainability of machine learning techniques and enhance the performance of standard econometric methods.

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Hall, S. G., and S. G. B. Henry. "Rational Expectations in an Econometric Model: Niesr Model 8∗." National Institute Economic Review 114 (November 1985): 58–68. http://dx.doi.org/10.1177/002795018511400105.

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This article summarises research on the role of forward-looking behaviour in important sectors of a macro-econometric model. It is based on the work of a number of researchers at the National Institute over the last two years. Important changes are introduced into many central equations in the model We argue that on grounds of both the underlying theory and the plausibility of the empirical results, this work is a significant advance in explaining dynamic macro-economic behaviour.

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Doszyń, Mariusz. "Econometric Support of a Mass Valuation Process." Folia Oeconomica Stetinensia 20, no. 1 (2020): 81–94. http://dx.doi.org/10.2478/foli-2020-0005.

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AbstractResearch background: The issues undertaken in the paper include the specification of an econometric model in real estate mass appraisal. Advantages and disadvantages of using econometric models in real estate mass appraisal are discussed.Purpose: The issue of aiding the valuation process with an econometric model based on the Szczecin algorithm of real estate mass appraisal is discussed in the paper. Such problems like multicollinearity, lack of coincidence and nonmonotonic influence of attributes are pointed out. Also, potential solutions to these problems are mentioned. Moreover, the paper features a discussion of cases in which econometric appraisal is not sufficient.Research methodology: The base for constructing an econometric model is the so-called Szczecin algorithm of real estate mass appraisal. Based on the algorithm, the econometric model was created to enable determining the impact of real estate attributes and location on their value.Results: problems related with specification, estimation and verification of the real estate mass appraisal econometric model are discussed in an empirical example.Novelty: A non-linear model is proposed, which features explanatory variables introduced into the model, and by taking into consideration the scale of their measurement. The proposed model, by introducing dummy variables, also account for the impact of a location, which significantly improves the fit to empirical values.

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