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Is there really a unit root in the inflation rate? More evidence from panel data models

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  • Syed Basher
  • Joakim Westerlund

Abstract

Time series unit root evidence suggests that inflation is nonstationary. By contrast, when using more powerful panel unit root tests, Culver and Papell (1997) find that inflation is stationary. In this article, we test the robustness of this result by applying a battery of recent panel unit root tests. The results suggest that the stationarity of inflation holds even after controlling for cross-sectional dependence and structural change.

Suggested Citation

  • Syed Basher & Joakim Westerlund, 2007. "Is there really a unit root in the inflation rate? More evidence from panel data models," Applied Economics Letters, Taylor & Francis Journals, vol. 15(3), pages 161-164.
    • Handle: RePEc:taf:apeclt:v:15:y:2007:i:3:p:161-164
    DOI: 10.1080/13504850600706305
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    Cited by:

    1. Erik Hjalmarsson & Pär Österholm, 2010. "Testing for cointegration using the Johansen methodology when variables are near-integrated: size distortions and partial remedies," Empirical Economics, Springer, vol. 39(1), pages 51-76, August.
    2. Aysan, Ahmet Faruk & Disli, Mustafa, 2019. "Small business lending and credit risk: Granger causality evidence," Economic Modelling, Elsevier, vol. 83(C), pages 245-255.
    3. Su Zhou, 2013. "Nonlinearity and stationarity of inflation rates: evidence from the euro-zone countries," Applied Economics, Taylor & Francis Journals, vol. 45(7), pages 849-856, March.
    4. Imran H. Shah & Ian Corrick & Abdul Saboor, 2018. "How should Central Banks Respond to Non-neutral Inflation Expectations?," Open Economies Review, Springer, vol. 29(2), pages 321-351, April.
    5. Martin C. Arnold & Christoph Hanck, 2019. "On Combining Evidence from Heteroskedasticity Robust Panel Unit Root Tests in Pooled Regressions," JRFM, MDPI, vol. 12(3), pages 1-22, July.
    6. Ventosa-Santaularària, Daniel & Gómez, Manuel, 2006. "Inflation and Breaks: the validity of the Dickey-Fuller test," MPRA Paper 58773, University Library of Munich, Germany.
    7. Zongxin Qian, 2011. "Global Imbalance, Excess Liquidity and Financial Risk in China," Chapters, in: Wim Meeusen (ed.), The Economic Crisis and European Integration, chapter 10, Edward Elgar Publishing.
    8. Wojciech Charemza & Svetlana Makarova & Imran Shah, 2015. "Making the most of high inflation," Applied Economics, Taylor & Francis Journals, vol. 47(34-35), pages 3723-3739, July.
    9. Annette Zeilstra & Adam Elbourne, 2014. "Follow the leader? Public and private wages in the Netherlands," CPB Discussion Paper 274, CPB Netherlands Bureau for Economic Policy Analysis.
    10. Yaya OlaOluwa S., 2018. "Another Look At The Stationarity Of Inflation Rates In Oecd Countries: Application Of Structural Break-Garch-Based Unit Root Tests," Statistics in Transition New Series, Statistics Poland, vol. 19(3), pages 477-493, September.
    11. Nikos Benos & Stelios Karagiannis, 2018. "Inequality And Growth In The United States: Why Physical And Human Capital Matter," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 572-619, January.
    12. Ibhagui, Oyakhilome, 2017. "How Does Foreign Direct Investment Affect Growth in Sub-Saharan Africa? New Evidence from Non-threshold and Threshold Analysis," MPRA Paper 85784, University Library of Munich, Germany.
    13. Eijffinger, S.C.W. & Qian, Z., 2010. "Globalization and the Output-Inflation Tradeoff : New Time Series Evidence," Other publications TiSEM f4bfa96e-e080-4bb4-9714-c, Tilburg University, School of Economics and Management.
    14. Yaya, OlaOluwa S & Ogbonna, Ahamuefula & Atoi, Ngozi V, 2019. "Are inflation rates in OECD countries actually stationary during 2011-2018? Evidence based on Fourier Nonlinear Unit root tests with Break," MPRA Paper 93937, University Library of Munich, Germany.
    15. Wojciech Charemza & Svetlana Makarova & Imran Shah, 2013. "Frequent episoded of high inflation and real effects," EcoMod2013 5478, EcoMod.
    16. Costantini, Mauro & Gutierrez, Luciano, 2012. "Bootstrap innovational outlier unit root tests in dependent panels," Economics Letters, Elsevier, vol. 117(3), pages 817-819.
    17. repec:nbp:nbpbik:v:47:y:2016:i:6:p:435-462 is not listed on IDEAS
    18. Chen, Shyh-Wei & Hsu, Chi-Sheng, 2016. "Threshold, smooth transition and mean reversion in inflation: New evidence from European countries," Economic Modelling, Elsevier, vol. 53(C), pages 23-36.
    19. Krzysztof Bartosik & Jerzy Mycielski, 2016. "Dynamika płac a długotrwałe bezrobocie w polskiej gospodarce," Bank i Kredyt, Narodowy Bank Polski, vol. 47(5), pages 435-462.
    20. Ventosa-Santaulária, Daniel & Gómez-Zaldívar, Manuel, 2009. "Broken mean stationarity and the validity of the Dickey-Fuller test: the case of controlled inflation," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 29(1), May.
    21. Benos, Nikos & Karagiannis, Stelios, 2013. "Do Cross-Section Dependence and Parameter Heterogeneity Matter? Evidence on Human Capital and Productivity in Greece," MPRA Paper 53326, University Library of Munich, Germany.
    22. Paresh Kumar Narayan, 2019. "Understanding Indonesia’S City-Level Consumer Price Formation: Implications For Price Stability," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 405-422, December.
    23. Gamber, Edward N. & Smith, Julie K. & Eftimoiu, Raluca, 2015. "The dynamic relationship between core and headline inflation," Journal of Economics and Business, Elsevier, vol. 81(C), pages 38-53.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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