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Unit Root Testing in a Central Bank

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  • Lavan Mahadeva and Paul Robinson

Abstract

Central bank economists have to understand and forecast macroeconomic time series. A serious problem that they face is that those series are often trended or a.ected by persistent innovations to the process. To try to get round this problem, or at least to understand its possible e.ects, it is common to test whether series are stationary. These tests are often called unit-root tests.1 In this handbook we discuss such testing. A model-builder should use appropriate econometric techniques. In order to choose between alternative estimators, the model-builder needs to think carefully about the relevant theory and the available data. But economic theory is rarely unambiguous in its implications for the data generating process. Subjecting the data to pre-estimation testing can help to gauge the relevance of different theories and possible data problems.

Suggested Citation

  • Lavan Mahadeva and Paul Robinson, 2004. "Unit Root Testing in a Central Bank," Handbooks, Centre for Central Banking Studies, Bank of England, number 22, April.
  • Handle: RePEc:ccb:hbooks:22
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    References listed on IDEAS

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    7. Korap, Levent, 2008. "Determinants of reserve money demand: a multivariate co-integrating approach," MPRA Paper 25525, University Library of Munich, Germany.
    8. Yaser Abolghasemi & Stanko Dimitrov, 2021. "Determining the causality between U.S. presidential prediction markets and global financial markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4534-4556, July.
    9. Lili Guo & Sihang Guo & Mengqian Tang & Mengying Su & Houjian Li, 2022. "Financial Support for Agriculture, Chemical Fertilizer Use, and Carbon Emissions from Agricultural Production in China," IJERPH, MDPI, vol. 19(12), pages 1-19, June.
    10. Abdul Aziz, Muhammad & Widodo, Tri, 2017. "Exchange Market Pressure: Evidences from ASEAN Inflation Targeting Countries," MPRA Paper 80919, University Library of Munich, Germany.
    11. Levent Korap, 2009. "Parasal Buyume ve Tuketici Enflasyonu Degisim Orani Arasindaki Nedensellik Iliskisi Uzerine Bir Deneme: Turkiye Ornegi," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 9(1), pages 56-74, May.
    12. H. Levent Korap & Ozgur Aslan, 2010. "Re-examination of the long-run purchasing power parity: further evidence from Turkey," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3559-3564.
    13. J. F. M. De Jong & M. Ferdinandusse & J. Funda, 2018. "Public capital in the 21st century: as productive as ever?," Applied Economics, Taylor & Francis Journals, vol. 50(51), pages 5543-5560, November.
    14. Levent, Korap, 2007. "Testing causal relationships between energy consumption, real income and prices: evidence from Turkey," MPRA Paper 21834, University Library of Munich, Germany.
    15. Portes, Richard & Palladini, Giorgia, 2011. "Sovereign CDS and Bond Pricing Dynamics in the Euro-area," CEPR Discussion Papers 8651, C.E.P.R. Discussion Papers.
    16. Levent, Korap, 2008. "Modeling Turkish M2 broad money demand: a portfolio-based approach using implications for monetary policy," MPRA Paper 19703, University Library of Munich, Germany.
    17. Amarasekara, Chandranath, 2005. "Interest Rate Pass-through in Sri Lanka," MPRA Paper 64865, University Library of Munich, Germany.
    18. Khatibu Kazungu, 2019. "The Nexus between Government Expenditure and Revenue in Tanzania," Asian Journal of Economic Modelling, Asian Economic and Social Society, vol. 7(4), pages 158-170, December.
    19. Solarin, Sakiru Adebola & Ozturk, Ilhan, 2016. "The relationship between natural gas consumption and economic growth in OPEC members," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1348-1356.
    20. Kamer Ainur M. AIVAZ & Ion Danut I. JUGANARU & Mariana C. JUGANARU, 2016. "The Anticipation Of The Number Of Tourists Arrived In Mamaia Using The Type Of Models Arima," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 7, pages 93-108, June.

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    More about this item

    Keywords

    Unit; Root; Testing; Central Bank;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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