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Michael Webster and Rory C. Tarnow-Mordi

Comparisons of Income, Output, and Prices , edited by A. Heston and R. E. Lipsey, 87–107. Chicago: University of Chicago Press. Doi: https://doi.org/10.7208/chicago/9780226331126.001.0001 . De Haan, J. 2015. “A Framework for Large Scale Use of Scanner Data in the Dutch CPI.” Paper presented at the 14th meeting of the Ottawa Group, Tokyo, 20–22 May 2015. Available at: http://www.stat.go.jp/english/info/meetings/og2015/pdf/t6s11p33_pap.pdf (accessed August 2017). De Haan, J., R. Hendriks, and M. Scholz. 2016. “A Comparison of Weighted Time-Product Dummy and

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Frances Krsinich

. “Overlapping Quality Adjustment Using Online Data.” Presentation to the 2012 Economic Measurement Group, Sydney, November 21–23, Australia. Available at: https://www.business.unsw.edu.au/research-site/centreforappliedeconomicresearch-site/Documents/A.%20Cavallo%20-%20Overlapping%20Quality%20Adjustment%20Using%20Online%20Data.pdf (accessed April 2016). de Haan, J. 2015a. “The Time-Product Dummy Method and Implicit Quality Adjustment.” Unpublished draft, May 2015. de Haan, J. 2015b. “Rolling Year Time Dummy Indexes and the Choice of Splicing Method.” Paper

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Eriona Deda

References Osmani, M. (2010), Calculation of the general correlation coefficient, Vol. II. Tirana, Albania, 2010. Osmani, M. (2004), Coefficient of variation, Tirana, Albania: GEER,2004. Osmani, M. (2010) Econometric analysis with dummy variable,Vol. II. Tirana, Albania, 2010. Osmani, M (2013). Methods of econometrics with Eviews 3 programme.,Lecture, Agricultural University of Tirana, Albania 2013. Osmani, M.(2010). The multiple model of regression, Vol. II. Tirana, Albania, 2010.

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Ramona-Mihaela Bâzgan

. (2002), “An Empirical Investigation of the Dynamic Effects of Changes in Government Spending and Revenues on Output”, Quarterly Journal of Economics, Vol.117(4), pp. 1329–1368. Brooks, Ch. (2014), “Introductory Econometrics for Finance”, 3 rd Edition, Cambridge University Press, New York, USA. Duncombe, W. (2018), “Lectures notes in public budgeting and financial management”, 1 st Edition, World Scientific Publishing Co. Inc., New Jersey, USA. Enders, W. (2004), „Applied Econometric Time Series Second Edition”, Wiley. European Commission

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Janusz Ćwiklak

://grabcad.com/library/augusta-a-109-1 . [13] N109TK, EW/C2011/07/10, AAIB Bulletin, 3/2012. [14] LS-DYNA ® Keyword User’s Manual, Vol. I, Livermore Software Technology Corporation, USA 2007. [15] Allcock A. W. R., Collin D. M., The development of a dummy bird for use in bird strike research, Aeronautical Research Council, C.P. No. 1071, Ministry of Technology, United Kingdom 1969. [16] http://www.agustawestland.com/product/helicopters/aw109-power-2 . [17] http://www.dynasupport.com/tutorial/ls-dyna-users-guide/time-integration . [18] Konderla P., Metoda

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Ladislav Karrach and Elena Pivarčiová

. [6] M. Hrčková and P. Koleda. “Identifikácia objektov v obraze na základe geometrických príznakov”. Acta Facultatis Technicae, vol. 19, no. 2, pp. 13-19, 2014. [7] J. Waters. QR Codes For Dummies. London: For Dummies, 2012. [8] K. Price. QR Codes Made EZ: A Complete Guide to Creating and Implementing QR Codes. North Charleston: CreateSpace, 2014. [9] L. Karrach and E. Pivarčiová. “Data Matrix code location marked with laser on surface of metal tools”. Acta facultatis technicae, vol. 22, no. 2, pp. 29-38, 2017

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Katarzyna Śledziewska and Tinatin Akhvlediani

require the dependent variable to be an integer. Finally, PPML allows to identify the effects of time invariant factors. The latter is a very important feature for our analyses, since we aim to test the effects of several dummy variables indicating memberships in different regional agreements together with the time dummy controlling for the occurrence of crisis during the estimation period. Following the contribution of Santos Silva and Tenreyro (2006) , we analyse the trade of all the EU members with rest of the world based on the following estimation equation

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Temidayo Gabriel Apata

new equation by the substitution for u it from Eq. (10) to give the subsequent equation: (11) Q i t = α + β x i t + u i + v i t $${{Q}_{it}}=\alpha +\beta {{x}_{it}}+{{u}_{i}}+{{v}_{it}}$$ To examine all the variables that affect GDP, Q it , in a cross-sectional way, data is required that will not vary over time, and hence there is a need to introduce dummy variables (Barro et al ., 2003). In line with the works of Pham (2010) the study therefore adopted the econometric terms of the least squares dummy variable approach (LSDV) for the

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Grzegorz Kłosowski

References [1] Akarte M.M., et al. - Web Based Casting Supplier Evaluation Using Analytical Hierarchy Process [in] Journal of the Operational Research Society, Vol. 52(5), 2001, pp. 511 - 522. [2] Bottani E., Rizzi A. - An Adapted Multi-Criteria Approach to Suppliers and Products Selection - an Application Oriented to Lead-Time Reduction [in] International Journal of Production Economics, Vol. 111(2), 2008, pp. 763 - 781. [3] Bughin J., Chui M., Manyika J. - Clouds, Big Data, and Smart Assets

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Andrzej Cieślik, Jan Jakub Michałek and Iryna Gauger

revenues, fixed capital, number of employees and cost of materials of enterprises for each of KVED-2010 sectors on the basis of the unbalanced sample of enterprises for the time period of 2005–2013. Some industries were omitted from the analysis due to problems with calculating factor input shares. It was not possible to calculate the Levinsohn-Petrin input shares for the following manufacturing industries: production of ready-made garments, manufacture of leather, production of paper, manufacture of other mineral products, manufacture of transport equipment and