Forecasting Labour Productivity Growth In Norway for the Period 2012-2021 Using Arima Models

• Autorzy: Pirooz Samavati
• Języki publikacji: EN

Abstrakty

EN

There appeared to be a change in labour productivity growth in Norway (a fall in the growth rate) in the middle of the 2000s, followed by a slight recovery at the end of the period under consideration (1971-2011). The 2007-2009 financial and economic crisis in Norway (which resulted from the banking crisis) caused an even greater drop in labour productivity growth to the extent that it in 2008 it reached its lowest point over the last three decades. After 2008, labour productivity growth started to increase. In this paper, in order to forecast time-series labour productivity growth in Norway for the period 2012-2021, the ARIMA model is fitted to Norwegian time-series labour productivity growth data obtained in the period 1971-2011. Using the Box-Jenkins model selection methodology, ARIMA (1, 1, 1) with no constant is selected as an appropriate model. As the selected ARIMA model indicates, labour productivity growth in Norway shall continue to increase very slowly and will ultimately reach a non-zero constant in the forecast period (2012-2021) following its recovery after 2008. Long-term forecasts for time-series labour productivity growth in Norway using ARIMA (1, 1, 1) with no constant will also reach a non-zero constant. Initially, it might be concluded that slow technological development as a result of the 2007-2009 financial and economic crisis could explain the slowdown in the recovery of labour productivity growth both in the forecast period (2012-2021) and over the longer term. However, due to the fact that the 2007-2009 financial and economic crisis has changed the underlying process which Norwegian labour productivity growth rate followed in the immediately preceding period, and that a technological revolution, which can be considered as a contributing factor, also took place in that period, it seems unlikely that a single labour productivity growth time series will be rich enough to describe the variation in the data. From the data and the analysis performed, it seems plausible to conclude that the crisis has changed the underlying process determining the labour productivity growth rate in Norway (at least in the short term), and therefore forecasts based on such models are rather unreliable. (original abstract)

Słowa kluczowe

EN

Labour efficiency; Economic crisis; Financial crisis

PL

Wydajność pracy; Kryzys gospodarczy; Kryzys finansowy

• Czasopismo: Wroclaw Review of Law, Administration & Economics
• Rocznik: 2013
• Tom: 3
• Numer: nr 1
• Strony: 126--147

Twórcy

autor

Pirooz Samavati

• Wroclaw University

Bibliografia

• Akaike H., A new lookat the statistical model identification (1974) (6) "IEEE Transactions on Automatic Control" 19, 716-723 <http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1100705&abstractAccess=no&userType=inst>accessed 18 November 2013.
• Brockwell P.J., Davis R. A., Introduction to Time Series and Forecasting (Second edition,Springer -Verlag, New York 2002) 238-250, 273-320 <http://www.masys.url.tw/Download/2002-Brockwell-Introduction Time Series and Forecasting.pdf>accessed 18 November 2013.
• Box G. E. P., Pierce D. A., Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models (1970) "Journal of the American Statistical Association" 65, 1509-1526 <http://www.stat.purdue.edu/~mlevins/STAT598K_2012/Box_Pierce_1970.pdf >accessed 18 November 2013.
• Box G. E. P., Cox D. R., Ananalysis of transformations (1964) (B) JRSS 26, 211-246<http://fisher.osu.edu/~schroeder.9/AMIS900/Box1964.pdf>accessed 18 November 2013.
• Box G. E. P., Jenkins G. M., Reinsel G. C., Time Series Analysis: Forecasting and Control (3rd ed.Englewood Cliffs, NJ: Prentice-Hall 1994) 32-33, 66, 68, 70-75, 188, 314-315, 547<http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470272848.html>accessed 18November 2013.
• Burnham K.P., Anderson D. R. ?, Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2nd ed. Springer-Verlag 2002) Chapter 7<http://www.mun.ca/biology/quant/ModelSelectionMultimodelInference.pdf >accessed 18 November 2013.
• Cowpertwait P.S.P., Metcalfe A. V., Introductory Time Series with R (Springer-Verlag, New York 2009) 121-128, 137-140 <http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-88697-8>accessed 18 November 2013.
• Chambers J., Cleveland W., Kleiner B., Tukey P., Graphical Methods for Data Analysis (Wadsworth& Brooks/Cole, Pacific Grove, CA 1983) <http://stat.belllabs.com/wsc/papersbooks.pdf>accessed 18 November 2013.
• Coghlan A., A Little Book of R For Time Series (Release 0.1. University College Cork, Cork, Ireland 2011) 13-65<http://stamash.org/hub/wp-content/uploads/2012/09/TimeSeries.pdf>accessed 18 November 2013.
• Dickey D. A., WA Fuller WA, Distribution of the estimators for autoregressive time series with a unit root (1979) "Journal of the American Statistical Association" 74, 427-431 <http://www.deu.edu.tr/userweb/onder.hanedar/dosyalar/1979.pdf >accessed 18 November 2013.
• Data is extracted from OECD statistics<http:// stats.oecd.org/>accessed 18November 2013.
• Data isextracted from OECD statistics<http:// stats.oecd.org>accessed 18November 2013.
• Freeman R., Labour Productivity Indicators (2008) OECD Statistics Directorate, Division of Structural Economic Statistics, 5-15 <http://www.oecd.org/std/labour-stats/41354425.pdf >accessed 18 November 2013.
• Grytten Ola, The EconomicHistory of Norway (2008) EH.Net Encyclopedia, edited by RobertWhaples. March 16, 2008 <http://eh.net/encyclopedia/article/grytten.norway>accessed 18November 2013.
• Hagelund K., Productivity growth in Norway 1948-2008 (2009) Special adviser, Economics Department, Norges Bank, Economic bulletin 2, 4-15 <http://www.norgesbank.no/Upload/77502/EN/Hele BUL.pdf>accessed 18 November 2013.
• Hamilton J. D., Time Series Analysis (Princeton University Press New Jersey 1994) 514-528<http://press.princeton.edu/titles/5386.html>accessed 18 November 2013.
• Hyndman R. J., Athanasopoulos G., Forecasting: principles and practice (An online textbook, MonashUniversity 2012) Section 8: ARIMA models, Non-seasonal ARIMA models<https://www.otexts.org/fpp/8/5 >accessed 18 November 2013.
• Hyndman R. J., Athanasopoulos G., Forecasting: principles and practice (An online text book, Monash University 2012) Section 8: ARIMA models<http://otexts.com/fpp>accessed 18 November 2013.
• IMF Executive Board Concludes 2011 Article IV Consultation with Norway, Public Information Notice (PIN)No. 12/9, February 2, 2012 <http://www.imf.org/external/np/sec/pn/2012/pn1209.htm>accessed18 November 2013.
• Kaldor N., Causes of the Slow Growth in the United Kingdom (Cambridge: Cambridge University Press 1966) 289.
• Kennedy C., Inducedbias in innovation and the theory of distribution (1964) in "Economic Journal", Vol. 74, 541-547 <http://www.jstor.org/stable/2228295?origin=JSTORbelow-page >accessed 18 November 2013.
• Kleiber C., Zeileis A., Applied Econometrics with R (Springer -Verlag, New York 2008)<http://uosis.mif.vu.lt/~rlapinskas/20122013/Ekonometrija 3k/KleibZeil - AER.pdf>accessed 18 November 2013.
• Kwiatkowski D., Phillips PCB, Schmidt P., Shin Y., Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root (1992) "Journal of Econometrics" 54, 159-178<http://www.ccee.edu.uy/ensenian/catmetec/material/KPSS.pdf >accessed 18 November 2013.
• Labour productivity growth data in Norway extracted in January 2013 from OECD. Stat<http://stats.oecd.org/>accessed 18 November 2013.
• McCombie J.S.L., Pugno M., Soro B., Introduction (In MP McCombie, B Soro (eds), Productivity Growth and Economic Performance, Palgrave Macmillan, London 2002) 1-27.
• Said S. E., Dickey D. A., Testing for Unit Roots in Autoregressive-Moving Average Models of Unknown Order (1984) (3) Biometrika 71, 599-607. doi:10.1093/biomet/71.3.599<http://www.ssc.wisc.edu/~bhansen/718/SaidDickey1984.pdf>accessed 18 November 2013.
• Scarpetta S., Tressel T., Boosting Productivity via Innovation and Adoption of New Technologies: Any Role for Labour Market Institutions? (2004)World Bank Policy Research Working Paper, no. 3273 <http://ideas.repec.org/p/wbk/wbrwps/3273.html>accessed 18 November 2013.
• Shapiro S.S., Wilk M. B., Ananalysis of variance test for normality (completesamples) (1965) (3-4) "Biometrika" 52, 591-611. doi:10.1093/biomet/52.3-4.591 <http://sci2s.ugr.es/keel/pdf/algorithm/articulo/shapiro1965.pdf >accessed 18 November 2013.
• Schmookler J., Invention and economic growth (Harvard University Press, Cambridge, Massachussets 1966)181-204 http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=8326359 accessed 18 November 2013.
• Shumway R. H., Stoffer D. S., Time Series AnalysisandIts Applications: With R Examples (Springer Texts in Statistics 2010, 3rd ed. 2011) XII, chapter 3, 83-154 <http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-36276-2>accessed 18 November 2013.
• The R Project for Statistical Computing <http://www.r-project.org/>accessed 18 November2013.
• Verdoorn J. P., On the Factors Determining the Growth of Labour Productivity (1949) (in L. Pasinetti (ed.). Italian Economic Papers 59, Vol. II, Oxford: Oxford University Press 1993) 3-10.
• Van Geenhuizen M., Trzmielak D. M., Gibson D. V., Urbaniak M.,Value-Added Partnering and Innovation in a Changing World (Purdue University Press 2009) 358-362 <http://www.thepress.purdue.edu/titles/format/9781557535139>accessed 18 November 2013.
• Vergeer R., Kleinknecht A., Jobs versus Productivity? The causal link from wages to labour productivity growth (2007) TU Delft, The Netherlands, 2-6 http://www.fep.up.pt/conferencias/eaepe2007/Papers and abstracts_CD/Vergeer.pdf accessed 18 November 2013.