Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach

Sarbapriya Ray

doi:doi:10.11648/j.ajtab.20220804.11

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Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach

Sarbapriya Ray

Published in American Journal of Theoretical and Applied Business (Volume 8, Issue 4)

Received: 8 October 2022 Accepted: 7 November 2022 Published: 23 November 2022

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Abstract

In a thickly populated country like India where there are abundant skilled and unkilled labour forces, economic growth along the path of GDP growth can be augmented when the number of workers increases in production process providing opportunity for employment or when each worker produces more. Competitiveness, standard of living and also economic growth of a country are connected with labour productivity growth. That is why, labour productivity growth is construed as one of the essential instruments of economic growth in general and industrial progress in particular. In view of this, the article explores the direction of causal link between labour productivity growth and economic growth via GDP growth in India. By adopting the techniques of unit–root tests (ADF, PP and KPSS), and Toda and Yamamoto long–run dynamic Granger causality test, the causal connection between the above two variables has been investigated using annual data for the period 1990 to 2018. The findings suggests that there exist bidirectional causality between labor productivity and economic growth indicating that labour productivity is a vital cause of economic growth and economic growth via GDP growth enhances labour productivity in India. The study concludes with a note of optimism that the policy makers in India should be cautious enough in implementing its economic policies towards healthy sustainable economic development and strengthening labour productivity as well as employment generation.

Published in	American Journal of Theoretical and Applied Business (Volume 8, Issue 4)
DOI	10.11648/j.ajtab.20220804.11
Page(s)	62-71
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Labor Productivity, Economic Growth, Toda Yamamoto, Causality Analysis, India

References

[1]	Alani, J. (2012), Effects of Productivity Growth on Employment Generation, Capital Accumulation and Economic Growth in Uganda. International Journal of Trade, Economics and Finance, vol. 3 (3), pp. 170-175.
[2]	Ahmed, E. M. (2011), Measuring the Effects of Labour Productivity on ASEAN5 Plus3 Economic Growth, Journal of Business Management and Economics, vol. 2 (2), pp. 69-74.
[3]	Auzina-Emsina, A. (2014), Labour Productivity, Economic Growth and Global Competitiveness in Post-crisis Period. Procedia-Social and Behavioral Sciences, vol. 156, pp. 317-321.
[4]	Baily, M. N., Bartelsman, E. J., & Haltiwanger, J. (1996), Labor Productivity: Structural Change and Cyclical Dynamics. Cambridge: NBER Working Paper. No. 5503. http://dx.doi.org/10.3386/w5503
[5]	Brooks, C (2019), Introductory Econometrics for Finance, Cambridge: Cambridge University Press.
[6]	Cui, D., Wei, X., Wu, D., Cui, N., & Nijkamp, P. (2019), Leisure time and labor productivity: a new economic view rooted from sociological perspective. Economics: The Open-Access, Open-Assessment E-Journal, vol. 13, pp. 1-24.
[7]	Dickey, David A., and Wayne A. Fuller (1979), Distribution of the estimators for autoregressive time series with a unit root, Journal of the American Statistical Association, vol. 74, pp. 427–31.
[8]	Dritsaki, C (2017), Toda-Yamamoto Causality Test between Inflation and Nominal Interest Rates: Evidence from Three Countries of Europe, International Journal of Economics and Financial Issues, vol. 7, pp. 120–29.
[9]	Engle, R. F. and Granger C. W. J., (1987), “Cointegration and Error Correction: Representation, Estimation and Testing,” Econometrica, vol. 55, pp. 251-276.
[10]	Enders W. (2004), Advanced Econometric Time Series (Second Edition), New York: Willey.
[11]	Gujarati, D. (1995), Basic Econometrics. (3rd Ed.). McGraw-hill: New York.
[12]	Highfill, K. (2002), “The Economic Impacts of Increased Labour Productivity: A REMI Analysis of Increased Output in Missouri’s Chemical Sector.” Department of Economic Development, Missouri Economic Research and Information Centre, MO USA.
[13]	Jajri, I., & Ismail, R. (2010). Impact of Labour Quality on Labour Productivity and Economic Growth. African Journal of Business Management, vol. 4 (4), pp. 486-495.
[14]	Johansen, S., and Juselius, K., (1990), “Maximum Likelihood Estimation and Inference on Cointegration – with Applications to the Demand for Money,” Oxford Bulletin of Economics and Statistics, vol. 52, pp. 169-210.
[15]	Jorgenson, D. W. (1991). Productivity and Economic Growth. InE. R. Berndt, &J. E. Triplett (Eds.), NBER Studies in Income and Wealth (pp. 19-118). Chicago: Univ. of Chicago Press.
[16]	Kwiatkowski. D, Phillips. P, C. B., Schmidt, P. Shin, Y (1992), Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root, Journal of Econometrics, vol. 54, pp. 159–178.
[17]	Karaalp-Orhan, H. S. (2016), Human Capital, Labor Productivity And Economic Growth: The Bounds And Causality Tests For Turkey. In ICPESS (International Congress on Politic, Economic and Social Studies) (No. 1).
[18]	Krugman, Paul (1994), Defining and measuring productivity, The Age of Diminishing Expectations., Cambridge, M. A: MIT Press.
[19]	McCullough, E. B. (2017), Labor productivity and employment gaps in Sub-Saharan Africa. Food Policy, vol. 67, pp. 133–152.
[20]	Nachega, J. C., & Fontaine, T. (2006). Economic Growth and Total Factor Productivity in Niger. IMF Working Paper WP/06/208, pp. 1-30.
[21]	Phillips, P. C., and P. Perron (1988), Testing for a unit root in time series regression. Biometrika, vol. 75, pp. 335–46.
[22]	Rudolf, B., & Zurlinden, M. (2010). Productivity and Economic Growth in Switzerland 1991-2006. Swiss journal of Economics and Statistics, vol. 146 (3), pp. 577-600.
[23]	Rambaldi, A. N. and Doran, H. (1996), “Testing for Granger noncausality in cointegrated systems made easy”, Working Paper in Econometrics and Applied Statistics No. 88, Department of Econometrics, University of New England, Armidale.
[24]	Saraçoğlu, D. Ş., Memiş, E., Voyvoda, E., & Kızılırmak, B. (2018), Changes in Global Trade Patterns and Women’s Employment in Manufacturing, 1995–2011, Feminist Economics, vol. 24 (3), pp. 1–28.
[25]	Su, B., & Heshmati, A. (2011). Development and Sources of Labor Productivity in Chinese Provinces. IZA Discussion Paper, (No 6263), 1-30. Retrieved from http://ftp.iza.org/dp6263.pdf
[26]	Szirmai, A., &Verspagen, B. (2015), Manufacturing and economic growth in developing countries, 1950-2005. Structural Change and Economic Dynamics, vol. 34, pp. 46–59.
[27]	Shirazi, N., S., Manap, T., A. (2005), “Export-Led Growth Hypothesis: Further Econometric Evidence from South Asia,” The Developing Economies, XLIII-4, December, pp. 472–88.
[28]	Tabari, N. A. Y., & Reza, M. (2012), Technology and Education Effects on Labor Productivity in the Agricultural Sector in Iran. European Journal of Experimental Biology, 2 (4), 1265-1272.
[29]	Tejani, S., & Milberg, W. (2016), Global Defeminization? Industrial Upgrading and Manufacturing Employment in Developing Countries. Feminist Economics, vol. 22 (2), pp. 24–54.
[30]	Toda, H. Y., and P. C. Phillips (1993), Vector auto regressions and causality, Econometrica, Journal of the Econometric Society, vol. 61, pp. 1367–93.
[31]	Taylor, T., Greenlaw, S. A., Dodge, E & Sonenshine, R. (2016), Principles of Economics. US: Rice University, Open Stax.
[32]	Toda, H. Y., Yamamoto, T, (1995), “Statistical Inference in Vector Autoregressions with Possibly Integrated Processes,” Journal of Econometrics, vol. 66, pp. 225–250.
[33]	Wagner, J. (2010). Entry, Exit and Productivity: Empirical Results for German Manufacturing Industries. German Economic Review, vol. 11 (1), pp. 78–85.
[34]	Yıldırım, K., Koyuncu, C., & Koyuncu, J. (2009), Does Temperature Affect Labor Productivity: Cross-Country Evidence. Applied Econometrics and International Development, vol. 9 (1), pp. 29-38.
[35]	Yao, Y. (2016). Higher education expansion, economic reform and labor productivity (No. 5357). Victoria University of Wellington, School of Economics and Finance.
[36]	Wu, H. X. (2013), “Measuring Industry Level Employment, Output and Labour Productivity in the Chinese Economy, 1987-2008.” Economic Review, vol. 64 (1), pp. 42-61.
[37]	Haraguchi, N., et al. (2017), The Importance of Manufacturing in Economic Development: Has This Changed? World Dev., http://dx.doi.org/10.1016/j. worlddev.2016.12.013.

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Sarbapriya Ray. (2022). Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach. American Journal of Theoretical and Applied Business, 8(4), 62-71. https://doi.org/10.11648/j.ajtab.20220804.11

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ACS Style

Sarbapriya Ray. Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach. Am. J. Theor. Appl. Bus. 2022, 8(4), 62-71. doi: 10.11648/j.ajtab.20220804.11

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AMA Style

Sarbapriya Ray. Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach. Am J Theor Appl Bus. 2022;8(4):62-71. doi: 10.11648/j.ajtab.20220804.11

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@article{10.11648/j.ajtab.20220804.11,
  author = {Sarbapriya Ray},
  title = {Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach},
  journal = {American Journal of Theoretical and Applied Business},
  volume = {8},
  number = {4},
  pages = {62-71},
  doi = {10.11648/j.ajtab.20220804.11},
  url = {https://doi.org/10.11648/j.ajtab.20220804.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtab.20220804.11},
  abstract = {In a thickly populated country like India where there are abundant skilled and unkilled labour forces, economic growth along the path of GDP growth can be augmented when the number of workers increases in production process providing opportunity for employment or when each worker produces more. Competitiveness, standard of living and also economic growth of a country are connected with labour productivity growth. That is why, labour productivity growth is construed as one of the essential instruments of economic growth in general and industrial progress in particular. In view of this, the article explores the direction of causal link between labour productivity growth and economic growth via GDP growth in India. By adopting the techniques of unit–root tests (ADF, PP and KPSS), and Toda and Yamamoto long–run dynamic Granger causality test, the causal connection between the above two variables has been investigated using annual data for the period 1990 to 2018. The findings suggests that there exist bidirectional causality between labor productivity and economic growth indicating that labour productivity is a vital cause of economic growth and economic growth via GDP growth enhances labour productivity in India. The study concludes with a note of optimism that the policy makers in India should be cautious enough in implementing its economic policies towards healthy sustainable economic development and strengthening labour productivity as well as employment generation.},
 year = {2022}
}

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TY  - JOUR
T1  - Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach
AU  - Sarbapriya Ray
Y1  - 2022/11/23
PY  - 2022
N1  - https://doi.org/10.11648/j.ajtab.20220804.11
DO  - 10.11648/j.ajtab.20220804.11
T2  - American Journal of Theoretical and Applied Business
JF  - American Journal of Theoretical and Applied Business
JO  - American Journal of Theoretical and Applied Business
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PB  - Science Publishing Group
SN  - 2469-7842
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AB  - In a thickly populated country like India where there are abundant skilled and unkilled labour forces, economic growth along the path of GDP growth can be augmented when the number of workers increases in production process providing opportunity for employment or when each worker produces more. Competitiveness, standard of living and also economic growth of a country are connected with labour productivity growth. That is why, labour productivity growth is construed as one of the essential instruments of economic growth in general and industrial progress in particular. In view of this, the article explores the direction of causal link between labour productivity growth and economic growth via GDP growth in India. By adopting the techniques of unit–root tests (ADF, PP and KPSS), and Toda and Yamamoto long–run dynamic Granger causality test, the causal connection between the above two variables has been investigated using annual data for the period 1990 to 2018. The findings suggests that there exist bidirectional causality between labor productivity and economic growth indicating that labour productivity is a vital cause of economic growth and economic growth via GDP growth enhances labour productivity in India. The study concludes with a note of optimism that the policy makers in India should be cautious enough in implementing its economic policies towards healthy sustainable economic development and strengthening labour productivity as well as employment generation.
VL  - 8
IS  - 4
ER  -

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Author Information

Sarbapriya Ray

Department of Commerce, Vivekananda College, Under University of Calcutta, Kolkata, India

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Sarbapriya Ray. (2022). Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach. American Journal of Theoretical and Applied Business, 8(4), 62-71. https://doi.org/10.11648/j.ajtab.20220804.11

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ACS Style

Sarbapriya Ray. Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach. Am. J. Theor. Appl. Bus. 2022, 8(4), 62-71. doi: 10.11648/j.ajtab.20220804.11

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AMA Style

Sarbapriya Ray. Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach. Am J Theor Appl Bus. 2022;8(4):62-71. doi: 10.11648/j.ajtab.20220804.11

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@article{10.11648/j.ajtab.20220804.11,
  author = {Sarbapriya Ray},
  title = {Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach},
  journal = {American Journal of Theoretical and Applied Business},
  volume = {8},
  number = {4},
  pages = {62-71},
  doi = {10.11648/j.ajtab.20220804.11},
  url = {https://doi.org/10.11648/j.ajtab.20220804.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtab.20220804.11},
  abstract = {In a thickly populated country like India where there are abundant skilled and unkilled labour forces, economic growth along the path of GDP growth can be augmented when the number of workers increases in production process providing opportunity for employment or when each worker produces more. Competitiveness, standard of living and also economic growth of a country are connected with labour productivity growth. That is why, labour productivity growth is construed as one of the essential instruments of economic growth in general and industrial progress in particular. In view of this, the article explores the direction of causal link between labour productivity growth and economic growth via GDP growth in India. By adopting the techniques of unit–root tests (ADF, PP and KPSS), and Toda and Yamamoto long–run dynamic Granger causality test, the causal connection between the above two variables has been investigated using annual data for the period 1990 to 2018. The findings suggests that there exist bidirectional causality between labor productivity and economic growth indicating that labour productivity is a vital cause of economic growth and economic growth via GDP growth enhances labour productivity in India. The study concludes with a note of optimism that the policy makers in India should be cautious enough in implementing its economic policies towards healthy sustainable economic development and strengthening labour productivity as well as employment generation.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Unraveling Labour Productivity Growth and Economic Growth Nexus in India: A Toda-Yamamoto Dynamic Granger Causality Approach
AU  - Sarbapriya Ray
Y1  - 2022/11/23
PY  - 2022
N1  - https://doi.org/10.11648/j.ajtab.20220804.11
DO  - 10.11648/j.ajtab.20220804.11
T2  - American Journal of Theoretical and Applied Business
JF  - American Journal of Theoretical and Applied Business
JO  - American Journal of Theoretical and Applied Business
SP  - 62
EP  - 71
PB  - Science Publishing Group
SN  - 2469-7842
UR  - https://doi.org/10.11648/j.ajtab.20220804.11
AB  - In a thickly populated country like India where there are abundant skilled and unkilled labour forces, economic growth along the path of GDP growth can be augmented when the number of workers increases in production process providing opportunity for employment or when each worker produces more. Competitiveness, standard of living and also economic growth of a country are connected with labour productivity growth. That is why, labour productivity growth is construed as one of the essential instruments of economic growth in general and industrial progress in particular. In view of this, the article explores the direction of causal link between labour productivity growth and economic growth via GDP growth in India. By adopting the techniques of unit–root tests (ADF, PP and KPSS), and Toda and Yamamoto long–run dynamic Granger causality test, the causal connection between the above two variables has been investigated using annual data for the period 1990 to 2018. The findings suggests that there exist bidirectional causality between labor productivity and economic growth indicating that labour productivity is a vital cause of economic growth and economic growth via GDP growth enhances labour productivity in India. The study concludes with a note of optimism that the policy makers in India should be cautious enough in implementing its economic policies towards healthy sustainable economic development and strengthening labour productivity as well as employment generation.
VL  - 8
IS  - 4
ER  -

Copy | Download