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Modelling labour productivity and the role of research intensity in 129 years: evidence from a new dynamic instrumental variable estimation approach

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  • Sakiru Adebola Solarin

    (Faculty of Business, Multimedia University)

  • Mufutau Opeyemi Bello

    (University of Ilorin)

Abstract

One of the areas of empirical research that has remained largely underexplored is the role of research intensity on labour productivity. To bridge this gap, this study investigates the impact of research intensity on labour productivity in 15 OECD countries using a new dynamic instrumental variable estimation approach while providing for financial development and education level as additional control variables for the 1890–2018 period. The results reveal that in most cases, research intensity, financial development, and level of education have positive impacts on labour productivity. In the model containing all the control variables and dummies, it is observed that for every 1 percentage point increase in research intensity, the labour productivity grows by 0.614 points. The results of the dummies suggest mixed evidence for the impact of World War I on labour productivity. The results further suggest that both World War II and the oil price crisis of the 1970s led to positive changes in labour productivity. For the purpose of robustness, we have also used a new Poisson pseudo maximum likelihood estimation approach to estimate the impact of research intensity on labour productivity, but the results are not materially different. The policy implications of the empirical results are detailed in the paper.

Suggested Citation

  • Sakiru Adebola Solarin & Mufutau Opeyemi Bello, 2024. "Modelling labour productivity and the role of research intensity in 129 years: evidence from a new dynamic instrumental variable estimation approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(3), pages 2619-2646, June.
  • Handle: RePEc:spr:qualqt:v:58:y:2024:i:3:d:10.1007_s11135-023-01766-w
    DOI: 10.1007/s11135-023-01766-w
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    as
    1. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    2. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2012. "A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model," Journal of Econometrics, Elsevier, vol. 170(1), pages 164-177.
    3. Markus Eberhardt & Francis Teal, 2008. "Modeling Technology and Technological Change in Manufacturing: How do Countries Differ?," CSAE Working Paper Series 2008-12, Centre for the Study of African Economies, University of Oxford.
    4. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    5. Donggyu Sul & Peter C. B. Phillips & Chi‐Young Choi, 2005. "Prewhitening Bias in HAC Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(4), pages 517-546, August.
    6. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    7. Norkutė, Milda & Sarafidis, Vasilis & Yamagata, Takashi & Cui, Guowei, 2021. "Instrumental variable estimation of dynamic linear panel data models with defactored regressors and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 220(2), pages 416-446.
    8. Pedro Carneiro & James J. Heckman & Edward J. Vytlacil, 2011. "Estimating Marginal Returns to Education," American Economic Review, American Economic Association, vol. 101(6), pages 2754-2781, October.
    9. Marcel Fafchamps & Agnes R. Quisumbing, 1999. "Human Capital, Productivity, and Labor Allocation in Rural Pakistan," Journal of Human Resources, University of Wisconsin Press, vol. 34(2), pages 369-406.
    10. Jahanger, Atif & Hossain, Mohammad Razib & Usman, Muhammad & Chukwuma Onwe, Joshua, 2023. "Recent scenario and nexus between natural resource dependence, energy use and pollution cycles in BRICS region: Does the mediating role of human capital exist?," Resources Policy, Elsevier, vol. 81(C).
    11. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    12. Kim Huynh & David Jacho-Chávez & Robert Petrunia & Marcel Voia, 2015. "A nonparametric analysis of firm size, leverage and labour productivity distribution dynamics," Empirical Economics, Springer, vol. 48(1), pages 337-360, February.
    13. Ross Levine, 1997. "Financial Development and Economic Growth: Views and Agenda," Journal of Economic Literature, American Economic Association, vol. 35(2), pages 688-726, June.
    14. Benjamin Moll, 2014. "Productivity Losses from Financial Frictions: Can Self-Financing Undo Capital Misallocation?," American Economic Review, American Economic Association, vol. 104(10), pages 3186-3221, October.
    15. Qinghua Xia & Qinwei Cao & Manqing Tan, 2020. "Basic research intensity and diversified performance: the moderating role of government support intensity," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 577-605, October.
    16. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    17. Ujjaini Mukhopadhyay, 2021. "Differential Education Subsidy Policy and Wage Inequality Between Skilled, Semi-skilled and Unskilled Labour: A General Equilibrium Approach," Review of Development and Change, , vol. 26(1), pages 40-62, June.
    18. Jiang, Bin & Yang, Yanrong & Gao, Jiti & Hsiao, Cheng, 2021. "Recursive estimation in large panel data models: Theory and practice," Journal of Econometrics, Elsevier, vol. 224(2), pages 439-465.
    19. Misbah Tanveer Choudhry & Enrico Marelli & Marcello Signorelli, 2016. "Age dependency and labour productivity divergence," Applied Economics, Taylor & Francis Journals, vol. 48(50), pages 4823-4845, October.
    20. T. W. Swan, 1956. "ECONOMIC GROWTH and CAPITAL ACCUMULATION," The Economic Record, The Economic Society of Australia, vol. 32(2), pages 334-361, November.
    21. Ang, James B., 2010. "Financial Reforms, Patent Protection, and Knowledge Accumulation in India," World Development, Elsevier, vol. 38(8), pages 1070-1081, August.
    22. Nazlioglu, Saban & Karul, Cagin, 2017. "A panel stationarity test with gradual structural shifts: Re-investigate the international commodity price shocks," Economic Modelling, Elsevier, vol. 61(C), pages 181-192.
    23. Lanre Ibrahim, Ridwan & Bello Ajide, Kazeem & Usman, Muhammad & Kousar, Rakhshanda, 2022. "Heterogeneous effects of renewable energy and structural change on environmental pollution in Africa: Do natural resources and environmental technologies reduce pressure on the environment?," Renewable Energy, Elsevier, vol. 200(C), pages 244-256.
    24. Sebastian Kripfganz & Vasilis Sarafidis, 2021. "Instrumental-variable estimation of large-T panel-data models with common factors," Stata Journal, StataCorp LLC, vol. 21(3), pages 659-686, September.
    25. Mamun, Md. Al & Sohag, Kazi & Uddin, Gazi Salah & Shahbaz, Muhammad, 2015. "Remittance and domestic labor productivity: Evidence from remittance recipient countries," Economic Modelling, Elsevier, vol. 47(C), pages 207-218.
    26. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    27. Dinda, Soumyananda, 2004. "Environmental Kuznets Curve Hypothesis: A Survey," Ecological Economics, Elsevier, vol. 49(4), pages 431-455, August.
    28. Oleg Badunenko & Diego Romero‐Ávila, 2013. "Financial Development And The Sources Of Growth And Convergence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(2), pages 629-663, May.
    29. Guowei Cui & Vasilis Sarafidis & Takashi Yamagata, 2020. "IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude," Monash Econometrics and Business Statistics Working Papers 11/20, Monash University, Department of Econometrics and Business Statistics.
    30. Facang Zhu & Qianqian Li & Shichun Yang & Tomas Balezentis, 2021. "How ICT and R&D affect productivity? Firm level evidence for China," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 34(1), pages 3468-3486, January.
    31. Walter Enders & Junsoo Lee, 2012. "A Unit Root Test Using a Fourier Series to Approximate Smooth Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(4), pages 574-599, August.
    32. Sergio Correia & Paulo Guimarães & Tom Zylkin, 2020. "Fast Poisson estimation with high-dimensional fixed effects," Stata Journal, StataCorp LLC, vol. 20(1), pages 95-115, March.
    33. Elsie Echeverri‐Carroll & Sofia G. Ayala, 2009. "Wage differentials and the spatial concentration of high‐technology industries," Papers in Regional Science, Wiley Blackwell, vol. 88(3), pages 623-641, August.
    34. Guowei Cui & Vasilis Sarafidis & Takashi Yamagata, 2023. "IV estimation of spatial dynamic panels with interactive effects: large sample theory and an application on bank attitude towards risk," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 124-146.
    35. Yot Amornkitvikai & Charles Harvie & Piyapong Sangkaew, 2022. "The role of wages, skills development and R&D on productivity: evidence from Thai manufacturing firms," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 50(2), pages 324-342, March.
    36. Paul M. Romer, 1994. "The Origins of Endogenous Growth," Journal of Economic Perspectives, American Economic Association, vol. 8(1), pages 3-22, Winter.
    37. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
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    More about this item

    Keywords

    Research intensity; Labour productivity; Dynamic instrumental variable estimation approach; Financial development; Level of education;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • J00 - Labor and Demographic Economics - - General - - - General
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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