Abstract
In this paper, we analyze time-varying predictability of labor productivity for growth in income (and consumption) inequality of the United Kingdom (UK) based on a high-frequency (quarterly) data set over 1975:Q1 to 2016:Q1. Results indicate that the growth rate of an index of labor productivity has a strong predictive power on growth rate of income (and consumption) inequality in the UK. Interestingly, the strength of the predictive power is found to be higher towards the end of the sample period in the wake of the global financial crisis. In addition, based on time-varying impulse response function analysis, we find that inequality and labor productivity growth rates are in general negatively associated over our sample period, barring a short-lived positive impact initially.
Similar content being viewed by others
Notes
The data is downloadable from: https://discover.ukdataservice.ac.uk/series/?sn=200016 and https://discover.ukdataservice.ac.uk/series/?sn=2000028.
We would like to thank Professor Haroon Mumtaz for kindly sharing the inequality data.
The data is available for download from: https://fred.stlouisfed.org/series/ULQELP01GBQ661S.
Again, the constant parameter-based Granger causality test could not detect causality running from GI1 to GLP even at the 10% level of significance, though ExpW, MeanW, and SupLR tests all overwhelmingly rejected the null of no time-varying predictability at the highest level of significance, but the Nyblom test statistic could not do so event at the 10% level of significance. Complete details of these results are available upon request from the authors.
This line of reasoning is further corroborated by the Bayesian Markov-switching quantile regression model (see, Yamaka et al. (2019) for further technical details) in Table 2 in the Appendix of the paper, with the results highlighting the importance of accounting for regime-changes in standard quantile regression models, when trying to deduce the correct inference, i.e., the negative relationship between GI1 and GLP, especially when inequality growth is conditionally high. Note the quantile regression model involves two lags of GLP with and without regime-switching across two states of low (indicated by regime-0) and high (indicated by regime-1)-GI1 states.
References
Arestis, P. (2018). Importance of tackling income inequality and relevant economic policies. In: Arestis, P., Sawyer M.C. (eds) Inequality: trends, causes, consequences, relevant policies, annual edition of International Papers in Political Economy, Palgrave Macmillan.
Arestis, P. (2020). Productivity and inequality in the UK: a political economy perspective. Review of Evolutionary Political Economy, 1, 183–197.
Atkinson, A. B. (2015). Inequality: what can be done? Cambridge: Harvard University Press.
Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1–22.
Barnett, A., Chiu, A., Franklin, J., & Sebastiá-Barriel, M. (2014). The productivity puzzle: a firm-level investigation into employment behaviour and resource allocation over the crisis. Bank of England Working Paper No. 495.
Berg A.G., & Ostry, J.D. (2011). Inequality and unsustainable growth: two sides of the same coin? IMF Staff Discussion Note 11/08. International Monetary Fund, Washington, DC. Available at: http://www.imf.org/external/pubs/ft/sdn/2011/sdn1108.pdf.
Blundell, R., Crawford, C., & Jin, C. (2013). What can wages and employment tell us about the UK’s productivity puzzle? Economic Journal, 124, 377–407.
Castle J., &Hendry, D. (2014). The real wage–productivity nexus. 13 January 2014. Available at: https://scholar.google.co.uk/scholar?q=Castle,+J.+and+Hendry,+D.+(2014),+%E2%80%9CThe+Real+Wage%E2%80%93Productivity+Nexus%E2%80%9D,+13+January+2014&hl=en&as_sdt=0&as_vis=1&oi=scholart.
Del Negro, M., & Primiceri, G. (2015). Time varying structural vector autoregressions and Monetary policy: A corrigendum. Review of Economic Studies, 82(4), 1342–1345.
Dickey, D. A., & Fuller, W. A. (1979). Distributions of the estimators for autoregressive time series with a unit root. Journal of American Statistical Association, 74(366), 427–481.
Disney, R., Jin, W., & Miller, H. (2013). The productivity puzzles. In C. Emmerson, P. Johnson and H. Miller (eds.), The IFS green budget, February 2013.
Dorling, D. (2015). Income inequality in the UK: Comparisons with five large Western European countries and the USA. Applied Geography, 61, 24–34.
Elliot, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64, 813–836.
Felstead, A., Gallie, D., Green, F., & Henseke, G. (2018). Productivity in Britain: the workers’ perspective. First findings from the skills and employment survey 2017. Available at: https://www.cardiff.ac.uk/research/explore/find-a-project/view/626669.
Haldane, A. (2017). Productivity puzzles. Speech given at the London School of Economics, 20 March. Available at: https://www.bankofengland.co.uk/speech/2017/productivity-puzzles.
Haldane, A. (2018). The UK’s productivity problem: hub no spokes. Speech given at the Academy of Social Sciences Annual Lecture, London, 28 June 2018. Available at: https://www.bankofengland.co.uk/speech/2018/andy-haldane-academy-of-social-sciences-annual-lecture-2018.
Hayes, K.J., Nieswiadomy, M., Slottje, D.J., Redfearn, M., & Wolff, E.N. (1994). Productivity and Income Inequality Growth Rates in the United States. Chapter 10 Contributions to Economic Analysis, 223, 299–327.
Johansen, S. (1996). Likelihood-based inference in cointegrated vector autoregressive models. New York, NY: Oxford University Press.
Johansen, S. (2008). A representation theory for a class of vector autoregressive models for fractional processes. Econometric Theory, 24, 651–676.
Johansen, S., & Nielsen, M. Ø. (2010). Likelihood inference for a nonstationary fractional autoregressive model. Journal of Econometrics, 158, 51–66.
Johansen, S., & Nielsen, M. Ø. (2012). Likelihood inference for a fractionally cointegrated vector autoregressive model. Econometrica, 80, 2667–2732.
Korinek, A., & Kreamer, A. (2013). The redistributive effects of financial deregulation. NBER Working Paper No. 19572.
Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of Econometrics, 54, 159–178.
Lanier, J. (2013). Who Owns the Future? United States: Simon & Schuster.
Lloyd-Ellis, H. (2003). On the Impact of Inequality on Productivity Growth in the Short and Long Term: A Synthesis. Canadian Public Policy, 29, Supplement: The Linkages between Economic Growth and Inequality, S65-S86.
Mason, G., O’Mahony, M., & Riley, R. (2018). What is holding back UK productivity? Lessons from decades of measurement. National Institute Economic Review, 246, R24–R35.
McCafferty, I. (2018). Changing times, changing norms. Speech Given at the City Lecture OMFIF, London. Available at: www.bankofengland.co.uk/speeches.
Mo, P. H. (2000). Income Inequality and Economic Growth. KYKLOS, 53(3), 293–316.
Mumtaz, H., & Theophilopoulou, A. (2017). The impact of monetary policy on inequality in the UK. An empirical analysis. European Economic Review, 98, 410–423.
Ng, S., & Perron, P. (2001). Lag length selection and the construction of unit root tests with good size and power. Econometrica, 69, 519–1554.
OECD. (2015). The Future of Productivity. OECD Publishing.
Patterson, P. (2012). The productivity conundrum, explanations and preliminary analysis”, Office for National Statistics (ONS). Available at: http://www.ons.gov.uk/ons/dcp171766_283259.pdf.
Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75, 335–346.
Pierdzioch, C., Gupta, R., Hassani, H., & Silva, E. S. (2019). Forecasting changes of economic inequality: A boosting approach. The Social Science Journal. https://doi.org/10.1016/j.soscij.2019.09.001.
Piketty, T. (2014). Capital in the Twenty-First Century. Cambridge, Massachusetts, Harvard University Press (Translated by A. Goldhammer).
Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies, 72, 821–852.
Ramos, G. (2014). Inclusive growth: Making it happen. OECD Yearbook.
Ravallion, M. (2018). Inequality and globalisation: a review essay. Journal of Economic Literature, 56(2), 620–642.
Rifkin, J. (1995). The End of Work: The Decline of the Global Labor Force and the Dawn of the Post-Market Era. United States: Putnam Publishing Group.
Rossi, B., & Wang, Y. (2019). VAR-based Granger-Causality Test in the presence of instabilities. Stata Journal, 19(4), 883–899.
Shi, S., Phillips, P. C. B., & Hurn, S. (2018). Change detection and the causal impact of the yield curve. Journal of Time Series Analysis, 39(6), 966–987.
Shi, S., Hurn, S., & Phillips, P.C.B. (2020). Causal Change Detection in Possibly Integrated Systems: Revisiting the Money-Income Relationship. Journal of Financial Econometrics, 2020, 18(1), 158–180.
Tenreyro, S. (2018). The fall in productivity growth: causes and implications. Speech given at the Preston lecture theatre, 15 January 2018. Queen Mary University of London. Available at: www.banofengland.co.uk/speeches.
Û. Redistribution, inequality and growth. IMF Staff Discussion Note No. 14/02.
Yamaka, W., Rakpho, P., & Sriboonchittac, S. (2019). Bayesian Markov Switching Quantile Regression with Unknown Quantile tau: Application to Stock Exchange of Thailand (SET). Thai Journal of Mathematics, Special Issue (2019): Structural Change Modeling and Optimization in Econometrics 2018, pp 1–13.
Acknowledgements
We would like to thank two anonymous referees for many helpful comments. However, any remaining errors are solely ours. David Gabauer would like to acknowledge that this research has been partly funded by BMK, BMDW and the Province of Upper Austria in the frame of the COMET Programme managed by FFG.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Gabauer, D., Gupta, R., Nel, J. et al. Time-Varying Predictability of Labor Productivity on Inequality in United Kingdom. Soc Indic Res 155, 771–788 (2021). https://doi.org/10.1007/s11205-021-02622-w
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11205-021-02622-w