Skip to main content
SpringerLink
Log in

Cross-country convergence: to be or not to be, that is the question

  • Published:
Empirical Economics Aims and scope Submit manuscript

Abstract

Can we associate globalization with converging productivity levels of different countries? Are developing countries catching up? This paper provides answers to these questions by studying the convergence of labor productivity with the Penn World Table 10.0. I utilize standard \(\beta \)- and \(\sigma \)-tests and the new \(\sigma \)-test Kong et al. (J Econom 209(2):185–207, 2019) propose. Furthermore, I propose using a time-series trend test to further study the underlying process of \(\sigma \)-convergence. The tests support convergence in the country groups of OECD, EU, APEC, Europe, and Asia. Contrary to the current belief that the income gap between rich and poor countries is not closing, I find \(\sigma \)-convergence in a group that excludes only African countries. More so, even the group of all countries seems to converge from the year 2000.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

All data used (PWT10.0) is publicly available and all codes for replication are available upon request.

Notes

  1. The overall number of countries in the dataset is 183, from which 176 countries are covered with data to calculate productivity for at least one of the periods considered. See appendix A.

  2. See also Quah (1993) for slightly different definitions of convergence.

  3. Dufrenot et al. (2012) and Stengos and Yazgan (2014) extend the standard time-series approach to cover a possible long memory parameter. Stengos and Yazgan (2014) also allow for structural breaks. However, Stengos and Yazgan (2014) conclude that the standard approach is sufficient to capture the behavior of the output gaps even, while the long memory framework is information-richer.

  4. See also Lee et al. (1997) and Binder and Pesaran (1999).

  5. I also report the \(\beta \)-convergence tests. This is because, as Sala-i-Martin (1996b) and Lichtenberg (1994) point out, \(\beta \)-convergence is a necessary condition for \(\sigma \)-convergence. Furthermore, Sala-i-Martin (1996a, 1996b) argue that both concepts are interesting, whereas Bernard and Durlauf (1996) state that the cross-sectional tests are more suited to data containing transitional countries.

  6. See, for example, Madsen (2010) for empirical evidence on the possible growth mechanism.

  7. In appendix B, \(T_{1}\) refers to the original Lichtenberg’s ratio of variances test. I use the adjusted version \(T_{2}\) instead.

  8. To calculate labor productivity, I use employment rather than hours worked since this increases the number of observations notably.

  9. Most of the excluded countries are island countries in the Americas. I exclude Venezuela from the sample because the extreme decrease in GDP during 2013–2019. In this period, according to the PWT10.0 data, living standards GDP and productive capacity GDP drop 99 %, and national accounts GDP 67 %.

  10. Note that Rodrik (2013)’s claim concerns country-level convergence while the study finds that unconditional convergence exists within manufacturing industries.

  11. Overall, whether I use GDP per capita instead of labor productivity has little effect on the results. Moreover, all the main findings and conclusions in this paper stay the same.

  12. See Appendix A for countries involved in each club.

  13. To name some: Community of Sahel-Saharan States, Common Market for Eastern and Southern Africa, Southern African Development Community and Economic Community of West African States.

References

  • Aghion P, Howitt P (1992) A model of growth through creative destruction. Econometrica 60(2):323–351

    Article  Google Scholar 

  • Barro RJ (1991) Economic growth in a cross section of countries. Q J Econ 106(2):407–443

    Article  Google Scholar 

  • Barro RJ (2015) Convergence and modernisation. Econ J 125(585):911–942

    Article  Google Scholar 

  • Barro RJ, Sala-i-Martin X (1992) Convergence. J Polit Econ 100(2):223–51

    Article  Google Scholar 

  • Bartlett MS (1954) A note on the multiplying factors for various \(\chi ^{2}\) approximations. J R Stat Soc Ser B (Methodol) 16(2):296–298

    Google Scholar 

  • Baumol WJ (1986) Productivity growth, convergence, and welfare: what the long-run data show. Am Econ Rev 76(5):1072–85

    Google Scholar 

  • Bernard AB, Durlauf SN (1995) Convergence in international output. J Appl Econom 10(2):97–108

    Article  Google Scholar 

  • Bernard AB, Durlauf SN (1996) Interpreting tests of the convergence hypothesis. J Econom 71(1):161–173

    Article  MathSciNet  Google Scholar 

  • Bernardini Papalia R, Bertarelli S (2013) Nonlinearities in economic growth and club convergence. Empir Econ 44(3):1171–1202

    Article  Google Scholar 

  • Binder M, Pesaran MH (1999) Stochastic growth models and their econometric implications. J Econ Growth 4(2):139–183

    Article  Google Scholar 

  • Brynjolfsson E, Rock D, Syverson C (2021) The productivity j-curve: how intangibles complement general purpose technologies. Am Econ J Macroecon 13(1):333–72

    Article  Google Scholar 

  • Carree M, Klomp L (1997) Testing the convergence hypothesis: a comment. Rev Econ Stat 79(4):683–686

    Article  Google Scholar 

  • Comin D, Hobijn B (2010) An exploration of technology diffusion. Am Econ Rev 100(5):2031–59

    Article  Google Scholar 

  • Comin DA, Gonzalez JQ, Schmitz TG, Trigari A (2020) Measuring TFP: the role of profits, adjustment costs, and capacity utilization. NBER Working Paper Series 28008

  • Desdoigts A (1999) Patterns of economic development and the formation of clubs. J Econ Growth 4(3):305–30

    Article  Google Scholar 

  • Dickey DA, Fuller WAF (1979) Distribution of the estimators for autoregressive time series with a unit root. J Am Stat Assoc 74(366a):427–431

    Article  MathSciNet  Google Scholar 

  • Dobson S, Ramlogan C, Strobl E (2006) Why do rates of \(\beta \)-convergence differ? A meta-regression analysis. Scot J Polit Econ 53(2):153–173

    Article  Google Scholar 

  • Dufrenot G, Mignon V, Naccache T (2012) Testing catching-up between the developing countries: “growth resistance’’ and sometimes “growth tragedy’’. Bull Econ Res 64(4):470–508

    Article  Google Scholar 

  • Durlauf SN, Johnson PA (1995) Multiple regimes and cross-country growth behaviour. J Appl Econom 10(4):365–384

    Article  Google Scholar 

  • Egger P, Pfaffermayr M (2009) On testing conditional sigma-convergence. Oxf Bull Econ Stat 71(4):453–473

    Article  Google Scholar 

  • Elliott G, Rothenberg TJ, Stock JH (1996) Efficient tests for an autoregressive unit root. Econometrica 64(4):813–836

    Article  MathSciNet  Google Scholar 

  • Feenstra RC, Inklaar R, Timmer MP (2015) The next generation of the Penn world table. Am Econ Rev 105(10):3150–3182

    Article  Google Scholar 

  • Friedman M (1992) Do old fallacies ever die? J Econ Lit 30(4):2129–2132

    MathSciNet  Google Scholar 

  • Galor O (2005) Chapter 4 from stagnation to growth: unified growth theory. Volume 1 of Handbook of Economic Growth, pp 171 – 293. Elsevier

  • Harvey DI, Leybourne SJ, Taylor AR (2007) A simple, robust and powerful test of the trend hypothesis. J Econom 141(2):1302–1330

    Article  MathSciNet  Google Scholar 

  • Harvey DI, Leybourne SJ, Taylor AR (2012) Testing for unit roots in the presence of uncertainty over both the trend and initial condition. J Econom 169(2):188–195

    Article  MathSciNet  Google Scholar 

  • Howitt P (2000) Endogenous growth and cross-country income differences. Am Econ Rev 90(4):829–846

    Article  Google Scholar 

  • Howitt P, Mayer-Foulkes D (2005) R &d, implementation, and stagnation: a Schumpeterian theory of convergence clubs. J Money Credit Bank 37(1):147–177

    Article  Google Scholar 

  • Islam N (1995) Growth empirics: a panel data approach. Q J Econ 110(4):1127–1170

    Article  Google Scholar 

  • Johansen S (1991) Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica 59(6):1551–1580

    Article  MathSciNet  Google Scholar 

  • Johnson P, Papageorgiou C (2020) What remains of cross-country convergence? J Econ Lit 58(1):129–75

    Article  Google Scholar 

  • Kong J, Phillips PC, Sul D (2019) Weak \(\upsigma \)-convergence: theory and applications. J Econom 209(2):185–207

    Article  MathSciNet  Google Scholar 

  • Kwiatkowski D, Phillips PC, 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? J Econom 54(1):159–178

    Article  Google Scholar 

  • Lee K, Pesaran MH, Smith R (1997) Growth and convergence in a multi-country empirical stochastic Solow model. J Appl Econom 12(4):357–392

    Article  Google Scholar 

  • Lichtenberg FR (1994) Testing the convergence hypothesis. Rev Econ Stat 76(3):576–579

    Article  Google Scholar 

  • Madsen JB (2010) The anatomy of growth in the OECD since 1870. J Monet Econ 57(6):753–767

    Article  ADS  Google Scholar 

  • Madsen JB, Timol I (2011) Long-run convergence in manufacturing and innovation-based models. Rev Econ Stat 93(4):1155–1171

    Article  Google Scholar 

  • Mankiw NG, Romer D, Weil DN (1992) A contribution to the empirics of economic growth. Q J Econ 107(2):407–437

    Article  Google Scholar 

  • Morrison DF (2005) Multivariate Statistical Methods, 4th edn. Duxbury Press, Pacific Grove

    Google Scholar 

  • Moss E, Nunn R, Shambaugh J (2020) The slowdown in productivity growth and policies that can restore it. The Hamilton Project, Brookings Institution, Washington, DC

  • Newey WK, West K (1994) Automatic lag selection in covariance matrix estimation. Rev Econ Stud 61(4):631–653

    Article  MathSciNet  Google Scholar 

  • Pesaran MH (2007) A pair-wise approach to testing for output and growth convergence. J Econom 138(1):312–355

    Article  MathSciNet  Google Scholar 

  • Quah DT (1993) Galton’s fallacy and tests of the convergence hypothesis. Scand J Econ 95(4):427–443

    Article  Google Scholar 

  • Quah DT (1996) Empirics for economic growth and convergence. Eur Econ Rev 40(6):1353–1375

    Article  Google Scholar 

  • Quah DT (1997) Empirics for growth and distribution: stratification, polarization, and convergence clubs. J Econ Growth 2(1):27–59

    Article  Google Scholar 

  • Rodrik D (2013) Unconditional convergence in manufacturing. Q J Econ 128(1):165–204

    Article  Google Scholar 

  • Sala-i-Martin X (1996) The classical approach to convergence analysis. Econ J 106(437):1019–1036

    Article  Google Scholar 

  • Sala-i-Martin X (1996) Regional cohesion: evidence and theories of regional growth and convergence. Eur Econ Rev 40(6):1325–1352

    Article  Google Scholar 

  • Solow RM (1956) A contribution to the theory of economic growth. Q J Econ 70(1):65–94

    Article  Google Scholar 

  • Stengos T, Yazgan ME (2014) Persistence in convergence. Macroecon Dyn 18(4):753–782

    Article  Google Scholar 

  • Summers R, Heston A (1988) A new set of international comparisons of real product and price levels estimates for 130 countries, 1950–1985. Rev Income Wealth 34(1):1–25

    Article  Google Scholar 

  • Swan TW (1956) Economic growth and capital accumulation. Econ Rec 32(2):334–361

    Article  Google Scholar 

  • White H (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48(4):817–38

    Article  MathSciNet  Google Scholar 

  • Yang Y, Wang S (2017) Two simple tests of the trend hypothesis under time-varying variance. Econ Lett 156(C):123–128

    Article  MathSciNet  Google Scholar 

Download references

Funding

This work was supported by Palkansaajasäätiö.

Author information

Author notes

  1. Sakari Lähdemäki

    Present address: ETLA Economic Research, Arkadiankatu 23B, 00100, Helsinki, Finland

Authors and Affiliations

  1. Labour Institute for Economic Research, Arkadiankatu 7, 00100, Helsinki, Finland

    Sakari Lähdemäki

Authors
  1. Sakari Lähdemäki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sakari Lähdemäki.

Ethics declarations

Conflict of interest

The author has no competing interests to declare that are relevant to the content of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

I gratefully acknowledge the funding provided by Palkansaajasäätiö.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file 1 (pdf 179 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lähdemäki, S. Cross-country convergence: to be or not to be, that is the question. Empir Econ (2024). https://doi.org/10.1007/s00181-024-02561-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00181-024-02561-8

Keywords

JEL Classification

Search

Navigation