Journal articles: 'Econometric modelling'

1

Phillips, Peter C. B., and A. R. Bergstrom. "Continuous Time Econometric Modelling." Economica 59, no. 235 (August 1992): 373. http://dx.doi.org/10.2307/2554608.

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Bertholon, H., A. Monfort, and F. Pegoraro. "Econometric Asset Pricing Modelling." Journal of Financial Econometrics 6, no. 4 (July 17, 2008): 407–58. http://dx.doi.org/10.1093/jjfinec/nbn011.

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3

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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4

Farkhod, Mulaydinov. "Econometric Modelling of the Innovation Process in Uzbekistan." International Journal of Psychosocial Rehabilitation 24, no. 02 (February 20, 2020): 359–67. http://dx.doi.org/10.37200/ijpr/v24i2/pr200343.

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5

Rees, Hedley, and Aris Spanos. "Statistical Foundations of Econometric Modelling." Economic Journal 98, no. 389 (March 1988): 202. http://dx.doi.org/10.2307/2233530.

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Rowley, J. C. R., and Aris Spanos. "Statistical Foundations of Econometric Modelling." Economica 55, no. 217 (February 1988): 145. http://dx.doi.org/10.2307/2554269.

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7

Wegge, Leon L., and Aris Spanos. "Statistical Foundations of Econometric Modelling." Journal of the American Statistical Association 85, no. 409 (March 1990): 255. http://dx.doi.org/10.2307/2289558.

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Głowicka-Wołoszyn, Romana, Izabela Kurzawa, and Andrzej Wołoszyn. "Econometric Modelling of the Demand." Ekonomiczne Problemy Turystyki 33 (2016): 43–54. http://dx.doi.org/10.18276/ept.2016.1.33-04.

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Aschheim, Joseph, and George S. Tavlas. "Econometric modelling of partial adjustment." Economic Modelling 5, no. 1 (January 1988): 2–8. http://dx.doi.org/10.1016/s0264-9993(98)90002-5.

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10

Davidson, James. "Econometric Modelling: Techniques and Applications,." International Journal of Forecasting 17, no. 2 (April 2001): 302–3. http://dx.doi.org/10.1016/s0169-2070(01)00086-3.

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11

Hendry, David F., and Jurgen A. Doornik. "MODELLING LINEAR DYNAMIC ECONOMETRIC SYSTEMS." Scottish Journal of Political Economy 41, no. 1 (February 1994): 1–33. http://dx.doi.org/10.1111/j.1467-9485.1994.tb01107.x.

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12

Ray, W. D., Ian B. MacNeil, and Gary J. Umphrey. "Time Series and Econometric Modelling." Journal of the Royal Statistical Society. Series A (General) 150, no. 4 (1987): 401. http://dx.doi.org/10.2307/2982052.

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13

Mittnik, Stefan. "Macroeconomic dynamics and econometric modelling." European Journal of Operational Research 30, no. 3 (June 1987): 258–61. http://dx.doi.org/10.1016/0377-2217(87)90068-3.

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14

Powell, Alan A. "Integrating econometric and environmetric modelling." Environmetrics 6, no. 5 (September 1995): 429–37. http://dx.doi.org/10.1002/env.3170060503.

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15

Mosconi, Rocco, and Paolo Paruolo. "A Conversation with Søren Johansen." Econometrics 10, no. 2 (April 13, 2022): 21. http://dx.doi.org/10.3390/econometrics10020021.

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This article was prepared for the Special Issue “Celebrated Econometricians: Katarina Juselius and Søren Johansen” of Econometrics. It is based on material recorded on 30 October 2018 in Copenhagen. It explores Søren Johansen’s research, and discusses inter alia the following issues: estimation and inference for nonstationary time series of the I(1), I(2) and fractional cointegration types; survival analysis; statistical modelling; likelihood; econometric methodology; the teaching and practice of Statistics and Econometrics.

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Barna, Marta Yuriivna, and Yuriy Bohdanovych Myronov. "ECONOMETRIC MODELLING OF TOURIST FLOWS DYNAMICS." SCIENTIFIC BULLETIN OF POLISSIA 1, no. 4(12) (2017): 165–70. http://dx.doi.org/10.25140/2410-9576-2017-1-4(12)-165-170.

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17

Keuzenkamp, Hugo A., and Michael McAleer. "Simplicity, Scientific Inference and Econometric Modelling." Economic Journal 105, no. 428 (January 1995): 1. http://dx.doi.org/10.2307/2235317.

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18

Tendziagolskytė, Dalia, and Rimantas Rudzkis. "Econometric Modelling of Lithuanian Labour Market." Lietuvos statistikos darbai 53, no. 1 (December 20, 2014): 40–52. http://dx.doi.org/10.15388/ljs.2014.13893.

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Lithuanian labour market indicators, such as the total number of employees, the number of employees in the private and public sectors, the number of the unemployed, labour force, employment and unemployment rates, the relative number of employees, average monthly gross income are analysed in the paper. The experience of foreign countries and Lithuania in creating labour market models and econometric methodology has been examined. As a result, a new model of the Lithuanian labour market is produced, comprising ﬁve regressive equations, which are part of the recursive SVAR model, and four identities, which are part of balance equations. According to the logic of economic and other research, relevant connections in the economy have been specified, unknown parameters of equations have been estimated. Finally, forecasts of endogenous indicators for 2014 have been provided, and results have been compared with the projections of the main labour market indicators for 2014−2017, published by the Ministry of Finance. Calculations have been made using a statistical package Gretl.

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19

Conte, Anna, and Peter G. Moffatt. "The econometric modelling of social preferences." Theory and Decision 76, no. 1 (June 1, 2012): 119–45. http://dx.doi.org/10.1007/s11238-012-9309-4.

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20

Byers, David. "Econometric modelling of agricultural commodity markets." International Journal of Forecasting 7, no. 2 (August 1991): 248–49. http://dx.doi.org/10.1016/0169-2070(91)90064-3.

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21

Thomson, K. J. "Econometric modelling of agricultural commodity markets." Agricultural Systems 35, no. 3 (January 1991): 353. http://dx.doi.org/10.1016/0308-521x(91)90164-6.

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22

Conyon, M. J., S. I. Peck, and G. Sadler. "Econometric modelling of UK executive compensation." Managerial Finance 26, no. 9 (September 2000): 3–20. http://dx.doi.org/10.1108/03074350010766846.

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23

Dineen, Chris. "Progressive econometric modelling (PERM): A review." Journal of Applied Econometrics 6, no. 2 (April 1991): 213–17. http://dx.doi.org/10.1002/jae.3950060209.

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24

Paelinck, Jean H. P. "On aggregation in spatial econometric modelling." Journal of Geographical Systems 2, no. 2 (July 6, 2000): 157–65. http://dx.doi.org/10.1007/pl00011452.

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25

Dharmapala, Dhammika, and Michael McAleer. "Prediction and accommodation in econometric modelling." Environmetrics 6, no. 5 (September 1995): 551–56. http://dx.doi.org/10.1002/env.3170060522.

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26

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

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

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27

Zellner, Arnold. "Time-series analysis, forecasting and econometric modelling: The structural econometric modelling, time-series analysis (SEMTSA) approach." Journal of Forecasting 13, no. 2 (March 1994): 215–33. http://dx.doi.org/10.1002/for.3980130212.

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28

Qayyum, Unbreen. "Wojciech W. Charemza andDerekF. Deadman. NewDirections in Econometric Practice, General to Specific Modelling,Cointegration and Vector Auto Regression. Cheltenham, U.K.: Edward Elgar Publishing Limited. 1997. Pages 360. £28.00 (Paperback)." Pakistan Development Review 54, no. 1 (March 1, 2015): 73–75. http://dx.doi.org/10.30541/v54i1pp.73-75.

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ighly acclaimed and endorsed by leading econometricians, the book “New Directions in Econometric Practice” is not new among the econometrics and statisticians. It is more of a textbook for students of econometrics and statistics at various levels.It impressively attempts to addressthe main objective of explaining ‘how to practice econometrics’. It provides an accessibleand user-friendly approach to a new approach and methodology presented by David Hendry in his book,‘Dynamic Econometrics’. The book under review provides a practical and hands-on illustration ofHendry’s approach, enabling students to use it for themselves inreal world time-series econometric problems. The second edition of thebook attempts to address the shortfalls identified by some reviewers in the first edition. By providing practical guidelines in terms of empirical illustration of each technique,using DHSY’s suggested aggregated timeseries consumption function on PC-Gives (8.1 Professional), it opens new trails ofresearch. The book is primarily designed for providing an intuitive understanding of recent developments in econometrics to nonspecialist econometricians and is widely adopted by teachers, students and practitioners alike

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29

Enescu, Adrian Gabriel, Andreea Georgiana Petroșan, and Gheorghița Dincă. "THE IMPLICATION OF DEMOGRAPHICS ON THE ROMANIAN PENSION SYSTEM." SERIES V - ECONOMIC SCIENCES 14(63), no. 2 (December 15, 2021): 85–94. http://dx.doi.org/10.31926/but.es.2021.14.63.2.10.

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This paper aims to analyse the influence of the demographical factors on the short-term sustainability of the pension system from Romania. The data used for econometric modelling consisted of panel data for the period 2009-2019 for 8 European Union member states, together with time series data for autoregressive modelling. The following econometrical models were used: random-effects GLS regression and Box-Jenkins (ARIMA). The results emphasize an increasing demographical pressure on the Romanian pension system and the need of pension system reform.

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30

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

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31

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

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32

Davidson, James, and C. W. J. Granger. "Modelling Economic Series: Readings in Econometric Methodology." Economica 58, no. 231 (August 1991): 405. http://dx.doi.org/10.2307/2554825.

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33

Godfrey, Leslie, and David F. Hendry. "PC-GIVE: An Interactive Econometric Modelling System." Economic Journal 100, no. 399 (March 1990): 303. http://dx.doi.org/10.2307/2233641.

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34

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

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35

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

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36

Hendry, David F. "Econometric Modelling: The ‘Consumption Function’ In Retrospect." Scottish Journal of Political Economy 60, no. 5 (October 2, 2013): 495–522. http://dx.doi.org/10.1111/sjpe.12021.

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37

Watkins, Clinton, and Michael McAleer. "Econometric modelling of non-ferrous metal prices." Journal of Economic Surveys 18, no. 5 (December 2004): 651–701. http://dx.doi.org/10.1111/j.1467-6419.2004.00233.x.

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38

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

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39

Oxley, L. T. "An expert systems approach to econometric modelling." Mathematics and Computers in Simulation 39, no. 3-4 (November 1995): 379–83. http://dx.doi.org/10.1016/0378-4754(94)00087-x.

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40

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

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41

Hendry, David F. "ECONOMETRIC MODELLING WITH COINTEGRATED VARIABLES: AN OVERVIEW." Oxford Bulletin of Economics and Statistics 48, no. 3 (May 1, 2009): 201–12. http://dx.doi.org/10.1111/j.1468-0084.1986.mp48003001.x.

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42

Kim, H. Youn. "The econometric modelling of aggregate consumer behaviour." European Economic Review 32, no. 4 (April 1988): 1013–17. http://dx.doi.org/10.1016/0014-2921(88)90058-x.

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43

Smith, Clare, Stephen Hall, and Nick Mabey. "Econometric modelling of international carbon tax regimes." Energy Economics 17, no. 2 (April 1995): 133–46. http://dx.doi.org/10.1016/0140-9883(95)00009-j.

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44

Hayo, Bernd. "Simplicity in econometric modelling: some methodological considerations." Journal of Economic Methodology 5, no. 2 (December 1998): 247–61. http://dx.doi.org/10.1080/13501789800000015.

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45

Tsolakis, S. D., C. Cridland, and H. E. Haralambides. "Econometric Modelling of Second-hand Ship Prices." Maritime Economics & Logistics 5, no. 4 (December 2003): 347–77. http://dx.doi.org/10.1057/palgrave.mel.9100086.

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46

Shouhong Wang. "Nonparametric econometric modelling: A neural network approach." European Journal of Operational Research 89, no. 3 (March 1996): 581–92. http://dx.doi.org/10.1016/0377-2217(94)00282-7.

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47

Olejnik, Alicja Anna, and Agata Żółtaszek. "Spatial Econometric Approach to Modelling of Selected Western Diseases." Acta Universitatis Lodziensis. Folia Oeconomica 6, no. 332 (February 2, 2018): 39–50. http://dx.doi.org/10.18778/0208-6018.332.03.

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For years now, developed countries face an epidemic of high blood pressure, diabetes and high cholesterol, risk factors related to heart and circulatory disease, and a suite of psychological disorders ranging from depression, anxiety, to compulsive behaviours. These health risks have traditionally been associated with affluence, however by 2008 there is no clear link between national income and these diseases. E.g. according to Danaei, there was no relationship between national income and blood pressure in men, and in women blood pressure was even higher in poorer countries. This paper provides an in depth analysis of this correlation, applying spatial econometrics tools. The spatial aspect of the prevalence of western diseases does not seem to be obvious and, to our knowledge, is not widely explored in the literature. In particular, the paper investigates the spatial processes of selected diseases of affluence in regions of the European Union. The research covers 261 NUTS 2 regions for the period 2003–2010. This study provides the spatial analysis of circulatory and mental health disorders. In our opinion, the presented spatial econometric approach may constitute an important contribution to the field of epidemiology.

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48

Rudzkis, R., and E. Mačiulaitytė. "Econometrical Modelling of Profit Tax Revenue." Nonlinear Analysis: Modelling and Control 12, no. 1 (January 25, 2007): 95–112. http://dx.doi.org/10.15388/na.2007.12.1.14724.

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The aim of this article is to present a forecast of budget revenue from the profit tax using econometric models. The set of applied models has to be reduced to very simple models due to short time series used. Therefore, the profit tax regression analysis is made in two stages. In the first stage, econometric modelling of profit tax revenue with the main profit indicators (called the profit tax base) is performed on the basis of information on profit tax regulation and its changes. In the second stage, algorithms of forecasting the profit tax base are formed when the main macroeconomic indicators of Lithuanian economy are used as regressors. Crossvalidation was applied to estimate the accuracy of these algorithms.

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49

Wan Yaacob, Wan Fairos, and Wan Zakiyatussariroh Wan Husin. "Modelling Malaysian Road Accident Deaths : An Econometric Approach." Social and Management Research Journal 3, no. 1 (June 1, 2006): 99. http://dx.doi.org/10.24191/smrj.v3i1.5105.

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A number of methods have been proposed for dealing with road accident death model. This paper uses econometric regression models to develop the road accident death model. By using this approach, this paper attempts to establish a statistical model to describe the relationship between the total road accident deaths and a range ofexplanatory macroeconomic variables. The macroeconomic factors used in the model include population, the number of registered vehicles, road length, technique of data coverage, system of data recording and Gross Domestic Product. The results suggest that the POp, ROADL, VEH and DR do not have any impact on road accident deaths. In contrast, the GDP and Technique of data Coverage were found to be highly significant (P < 0.05) in explaining the road accident deaths.

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Yaacob, Wan Fairos Wan, and Wan Zakiyatussariroh Wan Husin. "Modelling Malaysian road accident deaths : an econometric approach." Social and Management Research Journal 3, no. 1 (June 1, 2006): 99–112. http://dx.doi.org/10.24191/smrj2006.3.3.7.

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Journal articles on the topic 'Econometric modelling'

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