Explaining UK wage inequality in the past globalisation period, 1880–1913

Abstract

The current era of globalisation has witnessed a rising premium paid to skilled workers resulting in increasing wage inequality in most OECD countries. This pattern differs from that observed during the past globalisation period (1880–1913), in which wage inequality decreased in most of the Old World countries. The present debate over wage inequality focuses on the implications of globalisation, technological change, the role of labour market institutions and education. Similar factors were at work in the past globalisation process. In order to disentangle the main factors that contribute to wage inequality, we calibrate a general equilibrium model for the UK economy in the past globalisation period. The results show that a trade shock and a skilled-biased technology shock increased wage inequality. However, education and emigration had a more significant impact and led to a decrease in wage inequality.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

Notes

  1. 1.

    In addition to already mentioned references see also, for example Taylor and Williamson 1997, Harley 2002 and Voigtländer and Voth 2006.

  2. 2.

    Unfortunately, calibration does not allow us to offer confidence intervals for the results.

  3. 3.

    As Kehoe (1996) points out, one can think of these variables as price indices, which are naturally set to one in the base case. Only one of these prices (or a combination of some prices) can be considered the numeraire. That means that all prices change after a shock except the numeraire. Thus, the problem is defined in terms of relative prices.

  4. 4.

    Although the exports of mining and quarrying were very important (due mainly to exports of coal) the UK imported other mining and quarrying products such as iron ore, copper, lead, or petroleum. The trade statistics did not show exactly whether the sector was net exporter or importer. We have estimated it and obtained that the mining and quarrying sector in 1880 and 1900 was a net importer.

  5. 5.

    Later on, we will check the robustness of the results when a Hicksian technology shock is considered.

  6. 6.

    Note that our measure of capital also does include land.

  7. 7.

    The wage inequality for “Transport and Railways” sub-sector in 1906 was 1.57 and the average for the industrial sector was 1.58.

  8. 8.

    Following the same procedure that for the industrial sector, we have obtained that in the service sector the 71.5% of the labour force was unskilled. Although in this sector there were some high skilled sub-sectors such as “Insurance, banking and finance” (with the 69.3% of skilled workers) or the “Professional services” (with the 74.4% of skilled workers), they only represented a very small portion of the total labour force of the service sector (the two sectors represented only the 11.78% of total labour force in the service sector in 1911). However, the majority sectors such as “Miscellaneous” (pubs, hotels, domestic service, etc.) and “Distributive trades” (both sectors represented the 61.3% of the total labour force in the service sector) were unskilled labour sectors (with the 83.2 and the 81.6% of unskilled workers on their total labour force respectively).

References

  1. Abrego L, Whalley J (2000) The choice of structural model in trade-wages decompositions. Rev Int Econ 9(3):462–477. doi:10.1111/1467-9396.00235

    Article  Google Scholar 

  2. Abrego L, Whalley J (2003) Good market responses to trade shocks and trade and wages decompositions. Can J Econ 36(3):747–757. doi:10.1111/1540-5982.t01-2-00011

    Article  Google Scholar 

  3. Aghion P, Howitt P (2002) Wage inequality and the New World economy. Oxf Rev Econ Policy 18(3):306–323. doi:10.1093/oxrep/18.3.306

    Article  Google Scholar 

  4. Aghion P, Howitt P, Violante GL (2002) General purpose technology and wage inequality. J Econ Growth 7(4):315–345. doi:10.1023/A:1020875717066

    Article  Google Scholar 

  5. Anderson E (2001) Globalisation and wage inequalities, 1870–1970. Eur Rev Econ Hist 5(1):91–118. doi:10.1017/S1361491601000041

    Article  Google Scholar 

  6. Atkinson AB (2002) Top incomes in the United Kingdom over the twentieth century, discussion papers in economic and social history, University of Oxford, no. 43, January

  7. Bagge G, Lundberg E, Svennilson I (1933) Wages in Sweden 1860–1930. Sockholm Economic Studies, Stockholm

    Google Scholar 

  8. Betrán C, Pons MA (2004) Skilled and unskilled labour wage differentials and economic integration, 1870–1930. Eur Rev Econ Hist 8(1):29–60. doi:10.1017/S1361491604001042

    Article  Google Scholar 

  9. Bowley AL (1937) Wages and income in the UK since 1860. Cambridge University Press, Cambridge

    Google Scholar 

  10. Card D, Di Nardo JE (2002) Skill-biased technological change and rising wage inequality: some problems and puzzles. J Labor Econ 20(4):733–783. doi:10.1086/342055

    Article  Google Scholar 

  11. Card D, Lemieux T, Ridde WC (2003) Unionization and wage inequality: a comparative study of the US, the UK and Canada. NBER, WP 9473

  12. Chandler AD (1996) Scale and scope: the dynamics of industrial capitalism. Belknap Press of Harvard University Press, Cambridge

    Google Scholar 

  13. David P (1991) Computer and dynamo: the modern productivity paradox in a not too distant mirror, in technology and productivity: the challenge for economic policy. OCDE, Paris

    Google Scholar 

  14. Federico G, O’Rourke KH (2000) Much ado about nothing? Italian trade policy in the late nineteenth century. In: Pamuk S, Williamson JG (eds) The Mediterranean response to globalisation before 1950. Routledge, London, pp 269–296

    Google Scholar 

  15. Feenstra RC (2000) The impact of international trade on wages. The University of Chicago Press, Chicago

    Google Scholar 

  16. Feinstein CH (1972) National income, expenditure and output of the UK 1855–1965. The University Press, Cambridge

    Google Scholar 

  17. Flora P (1973) Historical processes of social mobilization: urbanization and literacy, 1850–1965. In: Eisenstadt SN, Rokkan S (1973) Building states and nations. Models and Data Resources, Vol I. Sage, London, pp 213–258

  18. Flora P (1987) State, economy, and society in Western Europe, 1815–1975: a data handbook in two volumes. Campus Verlag, Frankfurtam Main

    Google Scholar 

  19. Goldin C, Katz LF (1996) Technology, skill, and the wage structure: insights from the past. Am Econ Rev LXXXVI:252–257

    Google Scholar 

  20. Goldin C, Katz LF (1998) The origins of technology-skill complementarity. Q J Econ (August):694–732

  21. Goldin C, Katz LF (2001) The legacy of US educational leadership: notes on distribution and economic growth in the 20th century. Am Econ Rev 91(2):18–23

    Google Scholar 

  22. Goldin C, Katz LF (2008) The race between education and technology. Harvard University Press, Cambridge

    Google Scholar 

  23. Goslin, A. and Lemieux, T. (2001) Labour market reforms and changes in wage inequality in the UK and the US, NBER, WP, pp 8413

  24. Hadass YS, Williamson JG (2001) Terms of trade shocks and economic performance 1870–1940: Prebisch and Singer revisited. Econ Dev Cult Change 51(3):629–656. doi:10.1086/375259

    Article  Google Scholar 

  25. Harley CK (2002) Computational general equilibrium models in economic history and an analysis of British capitalist agriculture. Eur Rev Econ Hist 6(2):165–191. doi:10.1017/S1361491602000072

    Article  Google Scholar 

  26. Harley CK, Crafts NFR (2000) Simulating the two views of the British industrial revolution. J Econ Hist 60(3):819–841. doi:10.1017/S0022050700000346

    Article  Google Scholar 

  27. Hatton TJ (2004) Emigration from the UK, 1870–1913 and 1950–1998. Eur Rev Econ Hist 8(2):149–171. doi:10.1017/S1361491604001121

    Article  Google Scholar 

  28. Hatton TJ, Williamson JG (1998) The age of mass migration: causes and economic impact. Oxford University Press, New York

    Google Scholar 

  29. Hobsbawm EJ (1985) The ‘New Unionism’ reconsidered. In: Mommsen WJ, Husung HG (eds) The development of trade unionism in Great Britain and Germany. George Allen and Unwin, London, pp 1880–1914

    Google Scholar 

  30. Hunt EH (1973) Regional wage variation in Britain 1850–1914. Clarendon Press, Oxford

    Google Scholar 

  31. Kehoe TJ (1996) Social accounting matrices and applied general equilibrium models. Federal Reserve Bank of Minneapolis, Working Paper 563

  32. Kehoe P, Kehoe T (1994) A primer on static applied general equilibrium models. Fed Reserve Bank Minneap Q Rev 18(2):2–16

    Google Scholar 

  33. King RG, Rebelo ST (2000) Resuscitating real business cycles. NBER, Working Paper Series, 7345

  34. Lee DS (1999) Wage inequality in the US during the 1980s: rising dispersion or falling minimum wage? Q J Econ 114:977–1023. doi:10.1162/003355399556197

    Article  Google Scholar 

  35. Lindert PH (1986) Unequal English wealth since 1670. J Polit Econ 94(6):1127–1162. doi:10.1086/261427

    Article  Google Scholar 

  36. Lindert PH, Williamson JG (1983) Reinterpreting Britain’s social tables, 1688–1913. Explor Econ Hist 20:94–109. doi:10.1016/0014-4983(83)90044-X

    Article  Google Scholar 

  37. Machin S, Van Reen J (1998) Technology and changes in skill structure: evidence from seven OECD Countries. Q J Econ (November):1215–1244. doi:10.1162/003355398555883

  38. Mitchell BR (1990) British historical statistics. Cambridge University Press, Cambridge

  39. Mitchell BR (1998) International historical statistics: Europe, 1750–1993. Mcmillan, Basigstoke

    Google Scholar 

  40. Mathews RCO, Feinstein CH, Odling-Smee JC (1982) British economic growth, 1856–1973. Oxford University Press, Oxford

    Google Scholar 

  41. Nakamura E (2005) Deconstructing the success of RBC. Harvard University, Mimeo

    Google Scholar 

  42. O’Rourke K (1997) The European grain invasion, 1870–1913. J Econ Hist 57(4):775–801

    Article  Google Scholar 

  43. O’Rourke KH, Williamson JG (1994) Late nineteenth century Anglo-American factor-price convergence: were Heckscher and Ohlin right? J Econ Hist 54:892–916

    Article  Google Scholar 

  44. O’Rourke KH, Williamson JG (1999) Globalization and history. The evolution of a nineteenth-century Atlantic economy. The MIT press, Cambridge

    Google Scholar 

  45. O’Rourke KH, Williamson JG, Hatton TJ (1994) Mass migration, commodity market integration and real wage convergence. The latte-nineteenth-century Atlantic economy. In: Hatton TJ, Williamson JG (eds) Migration and the international labour market. Routledge, London, pp 1850–1939

    Google Scholar 

  46. O’Rourke KH, Taylor A, Williamson JG (1996) Factor price convergence in the late nineteenth century. Int Econ Rev 37(3):499–530. doi:10.2307/2527439

    Article  Google Scholar 

  47. Pollard S (1999) The new unionism in Britain: its economic background. In: Pollard S (ed) Labour history and labour movement in Britain. Ashgate, Aldershot

    Google Scholar 

  48. Rosenberg N (1976) Perspectives on technology. Cambridge University Press, Cambridge

    Google Scholar 

  49. Routh G (1980) Occupation and pay in Great Britain 1906–1979. The MacMillan Press, London

    Google Scholar 

  50. Rutherford TF (1998) Economic equilibrium modelling with GAMS. An introduction to GAMS/MCP and GAMS/MPSGE. Draft monograph, Department of Economics, University of Colorado

  51. Shoven JB, Whalley J (1992) Applying general equilibrium. Cambridge University Press, Cambridge

    Google Scholar 

  52. Slaughter MJ (1998) International trade and labour-market outcomes: results, questions, and policy options. Econ J 108:1452–1462. doi:10.1111/1468-0297.00353

    Article  Google Scholar 

  53. Taylor A, Williamson JG (1997) Convergence in the age of mass migration. Eur Rev Econ Hist 1:27–63

    Article  Google Scholar 

  54. Voigtländer N, Voth H-J (2006) Why England? Demographic factors, structural change and physical capital accumulation during the industrial revolution. J Econ Growth 11:319–361. doi:10.1007/s10887-006-9007-6

    Article  Google Scholar 

  55. Wälde K (2000) Egalitarian and elitist education systems as the basis for international differences in wage inequality. Eur J Polit Econ 16:445–468. doi:10.1016/S0176-2680(99)00055-5

    Article  Google Scholar 

  56. Williamson JG (1976) The sources of American inequality, 1896–1948. Rev Econ Stat 58(4):387–397. doi:10.2307/1935870

    Article  Google Scholar 

  57. Williamson JG (1990) The impact of the Corn Laws just prior to repeal. Explor Econ Hist 27(2):123–156. doi:10.1016/0014-4983(90)90007-L

    Article  Google Scholar 

  58. Williamson JG (2008) Globalization and the Great Divergence: terms of trade and volatility in the poor periphery NBER Working Paper W13841, pp 1782–1913

  59. Wood A (1998) Globalisation and the rise in labour market inequalities. Econ J 108:1463–1482. doi:10.1111/1468-0297.00354-

    Article  Google Scholar 

Download references

Acknowledgments

Concha Betrán and María A. Pons acknowledge financial support from CICYT Grant SEJ2004-07402. Financial support from CICYT Grant SEJ2005-01365, GV/2007/268 Fundación Rafael del Pino and EFRD is gratefully acknowledged by Javier Ferri. Preliminary versions of this paper were presented at the Sixth Conference of the European Historical Economics Society, the European Social History Society Congress in Amsterdam, IX Encuentro de Economía Aplicada, 18th Annual Conference of the European Association of Labour Economists, XXXI Simposio de Analisis Economico, and the 8th Global Conference on Business and Economics. Thanks to all the participants for their comments and suggestions. A previous version of the paper has been published as a working paper in FUNCAS, num. 352/2007. Finally, we are very grateful for the relevant and constructive comments made by a referee.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Maria A. Pons.

Appendices

Appendix 1: Parameters, variables and equations

See Tables 9, 10, 11

Table 9 Parameters of the model
Table 10 Exogenous variables
Table 11 Endogenous variables

A1.1 Production functions

Each sector produces using capital and a composite of skilled and unskilled labour:

$$ X_{j} = \alpha_{j}^{x} \left[ {\delta_{j}^{x} K_{j}^{{\upsilon_{j}^{x} }} + \left( {1 - \delta_{j}^{x} } \right)L_{j}^{{\upsilon_{j}^{x} }} } \right]^{{\frac{1}{{\upsilon_{j}^{x} }}}} $$

where = 1, 2 stands for the skilled (1) and unskilled (2) sector. The composite of labour for each sector takes the form:

$$ L_{j} = \alpha_{j}^{l} \left[ {\delta_{j}^{l} \left( {\beta^{\text{s}} S_{j} } \right)^{{\upsilon_{j}^{l} }} + \left( {1 - \delta_{j}^{l} } \right)\left( {\beta^{\text{u}} U_{j} } \right)^{{\upsilon_{j}^{l} }} } \right]^{{\frac{1}{{\upsilon_{j}^{l} }}}} $$

There is a utility function defined over domestic and imported goods:

$$ W = \alpha^{w} \left[ {\delta^{w} X_{1}^{{\upsilon^{w} }} + (1 - \delta^{w} )Y^{{\upsilon^{w} }} } \right]^{{\frac{1}{{\upsilon^{w} }}}} $$

where Y is a composite of the domestic produced unskilled good and an equivalent imported good (Armington assumption):

$$ Y = \alpha^{y} \left[ {\delta^{y} X_{2}^{{\upsilon^{y} }} + \left( {1 - \delta^{y} } \right)M_{2}^{{\upsilon^{y} }} } \right]^{{\frac{1}{{\upsilon^{y} }}}} $$

The model is composed of the following equations determined by zero profit conditions, market clearing conditions, income balance and the macroeconomic closure rule.

A1.2 Zero profit conditions

Perfect competition and free entry imply that firms do not have extraordinary profits.

$$ \begin{aligned} P_{{_{j} }} & = \left( {\alpha_{j}^{x} } \right)^{ - 1} \left[ {\left( {\delta_{j}^{x} } \right)^{{\eta_{j}^{x} }} P_{K}^{{\left( {1 - \eta_{j}^{x} } \right)}} + \left( {1 - \delta_{j}^{x} } \right)^{{\eta_{j}^{x} }} P_{{L_{j} }}^{{\left( {1 - \eta_{j}^{x} } \right)}} } \right]^{{\frac{1}{{\left( {1 - \eta_{j}^{x} } \right)}}}} \\ P_{{L_{j} }} & = \left( {\alpha_{j}^{l} } \right)^{ - 1} \left[ {\left( {\delta_{j}^{l} } \right)^{{\eta_{j}^{l} }} \left( {\frac{{W_{\text{s}} }}{{\beta^{\text{s}} }}} \right)^{{\left( {1 - \eta_{j}^{l} } \right)}} + \left( {1 - \delta_{j}^{l} } \right)^{{\eta_{j}^{l} }} \left( {\frac{{W_{\text{u}} }}{{\beta^{\text{u}} }}} \right)^{{\left( {1 - \eta_{j}^{l} } \right)}} } \right]^{{\frac{1}{{\left( {1 - \eta_{j}^{l} } \right)}}}} \\ P_{W} & = \left( {\alpha^{w} } \right)^{ - 1} \left[ {\left( {\delta^{w} } \right)^{{\eta^{w} }} P_{1}^{{\left( {1 - \eta^{w} } \right)}} + \left( {1 - \delta^{w} } \right)^{{\eta^{w} }} P_{Y}^{{\left( {1 - \eta^{w} } \right)}} } \right]^{{\frac{1}{{\left( {1 - \eta^{w} } \right)}}}} \\ P_{Y} & = (\alpha^{y} )^{ - 1} \left[ {\left( {\delta^{y} } \right)^{{\eta^{y} }} P_{2}^{{\left( {1 - \eta^{y} } \right)}} + \left( {1 - \delta^{y} } \right)^{{\eta^{y} }} P_{{F_{2} }}^{{\left( {1 - \eta^{y} } \right)}} } \right]^{{\frac{1}{{\left( {1 - \eta^{y} } \right)}}}} \\ P_{1} & = \overline{{P_{{E_{1} }} }} P_{\text{FX}} \\ P_{F2} & = \overline{{P_{{M_{2} }} }} P_{\text{FX}} \\ \end{aligned} $$

where unitary revenue is on the left hand side of the equations and unitary cost on the right.

A1.3 Market clearing conditions

These conditions imply that demand equals supply for each good and factor.

$$ \begin{aligned} X_{1} - E_{1} & = \left( {\alpha^{w} } \right)^{ - 1} \left[ {\left( {\delta^{w} } \right) + \left( {1 - \delta^{w} } \right)\left( {\frac{{\delta^{w} P_{Y} }}{{\left( {1 - \delta^{w} } \right)P_{1} }}} \right)^{{\left( {1 - \eta^{w} } \right)}} } \right]^{{\frac{{\eta^{w} }}{{\left( {1 - \eta^{w} } \right)}}}} W \\ Y & = \left( {\alpha^{w} } \right)^{ - 1} \left[ {\left( {\delta^{w} } \right)\left( {\frac{{\left( {1 - \delta^{w} } \right)P_{1} }}{{\delta^{w} P_{Y} }}} \right)^{{\left( {1 - \eta^{w} } \right)}} + \left( {1 - \delta^{w} } \right)} \right]^{{\frac{{\eta^{w} }}{{\left( {1 - \eta^{w} } \right)}}}} W \\ X_{2} & = \left( {\alpha^{y} } \right)^{ - 1} \left[ {\left( {\delta^{y} } \right) + \left( {1 - \delta^{y} } \right)\left( {\frac{{\delta^{y} P_{{F_{2} }} }}{{\left( {1 - \delta^{y} } \right)P_{2} }}} \right)^{{\left( {1 - \eta^{y} } \right)}} } \right]^{{\frac{{\eta^{y} }}{{\left( {1 - \eta^{y} } \right)}}}} Y \\ M_{2} & = \left( {\alpha^{y} } \right)^{ - 1} \left[ {\left( {\delta^{y} } \right)\left( {\frac{{\left( {1 - \delta^{y} } \right)P_{2} }}{{\delta^{y} P_{{F_{2} }} }}} \right)^{{\left( {1 - \eta^{y} } \right)}} + \left( {1 - \delta^{y} } \right)} \right]^{{\frac{{\eta^{y} }}{{\left( {1 - \eta^{y} } \right)}}}} Y \\ W & = \frac{I}{{P_{W} }} \\ \end{aligned} $$
$$ \begin{aligned} \overline{K} & = \mathop \sum \limits_{j = 1}^{2} \left[ {\left( {\alpha_{j}^{x} } \right)^{ - 1} \left[ {\left( {\delta_{j}^{x} } \right) + \left( {1 - \delta_{j}^{x} } \right)\left( {\frac{{\delta_{j}^{x} P_{{L_{j} }} }}{{\left( {1 - \delta_{j}^{x} } \right)P_{\text{K}} }}} \right)^{{\left( {1 - \eta_{j}^{x} } \right)}} } \right]^{{\frac{{\eta_{j}^{x} }}{{\left( {1 - \eta_{j}^{x} } \right)}}}} X_{j} } \right] \\ L_{1} + L_{2} & = \mathop \sum \limits_{j = 1}^{2} \left[ {\left( {\alpha_{j}^{x} } \right)^{ - 1} \left[ {\left( {\delta_{j}^{x} } \right)\left( {\frac{{\left( {1 - \delta_{j}^{x} } \right)P_{\text{K}} }}{{\delta_{j}^{x} P_{{L_{j} }} }}} \right)^{{\left( {1 - \eta_{j}^{x} } \right)}} + \left( {1 - \delta_{j}^{x} } \right)} \right]^{{\frac{{\eta_{j}^{x} }}{{\left( {1 - \eta_{j}^{x} } \right)}}}} X_{j} } \right] \\ \overline{U} & = \mathop \sum \limits_{j = 1}^{2} \left[ {\left( {\alpha_{j}^{l} } \right)^{ - 1} \left( {\frac{1}{{\beta^{\text{u}} }}} \right)\left[ {\left( {\delta_{j}^{l} } \right)\left( {\frac{{\left( {1 - \delta_{j}^{l} } \right)\beta^{\text{u}} W_{\text{s}} }}{{\delta_{j}^{l} \beta^{\text{s}} W_{\text{u}} }}} \right)^{{\left( {1 - \eta_{j}^{l} } \right)}} + \left( {1 - \delta_{j}^{l} } \right)} \right]^{{\frac{{\eta_{j}^{l} }}{{\left( {1 - \eta_{j}^{l} } \right)}}}} L_{j} } \right] \\ \overline{S} & = \mathop \sum \limits_{j = 1}^{2} \left[ {\left( {\alpha_{j}^{l} } \right)^{ - 1} \left( {\frac{1}{{\beta^{\text{s}} }}} \right)\left[ {\left( {\delta_{j}^{l} } \right) + \left( {1 - \delta_{j}^{l} } \right)\left( {\frac{{\delta_{j}^{l} \beta^{\text{s}} W_{\text{u}} }}{{\left( {1 - \delta_{j}^{l} } \right)\beta^{\text{u}} W_{\text{s}} }}} \right)^{{\left( {1 - \eta_{j}^{l} } \right)}} } \right]^{{\frac{{\eta_{j}^{l} }}{{\left( {1 - \eta_{j}^{l} } \right)}}}} L_{j} } \right] \\ \end{aligned} $$

Supply is on the left hand side while the right captures demand. The equation W = I/P W represents the budget constraint, P W being the minimum cost at a given commodity prices of buying one unit of utility (the expenditure function) and I the total income of the representative household (see definition in the below equation).

A1.4 Income balance

The following equation defines total income as revenues from total capital endowment, skilled and unskilled labour endowments and current trade deficit.

$$ I = P_{\text{K}} \overline{K} + W_{\text{s}} \overline{S} + W_{\text{u}} \overline{U} + P_{\text{FX}} \overline{\text{CTD}} $$

A1.5 Macro closure rule

This rule reflects the fact that the current trade deficit is constant.

$$ P_{1} E_{1} - P_{{F_{2} }} M_{2} = P_{\text{FX}} \overline{\text{CTD}} $$

Equations from (A1.2) to (A1.5) determine a model with 19 equations that is solved for 19 endogenous variables (see Table 11 above).

A1.6 Calibration with added restrictions

Up to what degree match the model solution other data than wage premium? To answer this question two changes in calibration are included with respect to exact calibration in which only information for the wage premium is considered. First, we allow for Hicks neutral technology change in sector X 2 as captured by ∆α x2 in addition to the unskilled-biased technological change (∆βu) used in the exact calibration procedure. Second, we choose βu and α x2 for 1880 in order to minimize a criterion function. In particular we choose the sum of squared deviation of model-predicted wage and production ratios (with a hat in the expression below) with respect to the actual values in 1880 (the variables without hat):

$$ \begin{gathered} \min \left( {\Upomega \left( {\frac{{W_{\text{s}}^{1880} }}{{W_{\text{u}}^{1880} }} - \frac{{\hat{W}_{\text{s}}^{1880} }}{{\hat{W}_{\text{u}}^{1880} }}} \right)^{2} + (1 - \Upomega )\left( {\frac{{X_{1}^{1880} }}{{X_{2}^{1880} }} - \frac{{\hat{X}_{1}^{1880} }}{{\hat{X}_{2}^{1880} }}} \right)^{2} } \right) \hfill \\ {\text{w}} . {\text{r}} . {\text{t}}\quad \beta_{\text{u}}^{1880} ,\alpha_{2}^{x,1880} \hfill \\ \end{gathered} $$

where Ω = 0.5. This particular form implies the same weight for the wage premium and production deviations. Thus, the exact calibration procedure can be considered a special case where both Ω = 1 (in this case we reply exactly the wage premium variation) or Ω = 0 in which case we would replicate exactly variation in production ratios. We solve the above optimization problem numerically creating a grid of values for βu and α x2 , and solve the model for all the possible combinations of values of βu and α x2 , taking the combination that minimize the objective function.

According to our results, the minimum value for this function is 0.004 that is reached for a value of β 1880u  = 0.600 and α x,18802  = 1.230.

Appendix 2: Data

A2.1 Data for wage inequality in the past

For France, the UK, Italy and Spain see Betrán and Pons (2004). For Sweden, we have calculated from Bagge et al. (1933).

A2.2 Data for the UK

Employment

Skilled workers:

Skilled manual workers.

Unskilled workers:

Semi-skilled and unskilled manual workers. Males and females for industry and males for agriculture. (in thousands).

Sectors:

Industry (manufacturing, building, gas, electricity and water, mining and quarrying) and agriculture. We have not considered the service sector.

Years:

1911 (census year).

We have used employment of manual workers by industry elaborated by Routh (1980). These data are elaborated from the Census of Population to obtain a homogeneous classification. As we need data by industry for skilled, semi-skilled and unskilled manual workers and the data elaborated by Routh (1980) only refer to 1951, we have calculated the proportions of skilled manual workers, semi-skilled and unskilled manual workers and non-manual workers in the labour force for each industry in 1951 and we have considered that these proportions are the same as in 1911.

We have also used the proportion of skilled on semi-skilled and unskilled manual workers to classify industries in skilled and unskilled sectors. The skilled industries are those that display an above average proportion and the unskilled industries a below average proportion.

Classification of sectors in decreasing order:

Skilled sectors:

(1) leather, (2) wood, (3) building, (4) vehicles, (5) paper printing, (6) textiles, (7) engineering, shipbuilding and electric, (8) other manufacturing, (9) metal goods and instruments, (10) metal manufacture and (11) cement, ceramic and glass.

Unskilled sectors:

(12) mining and quarrying, (13) clothing, (14) gas, electricity and water, (15) food, drink, tobacco, (16) chemicals and (17) agriculture.

Source:

Routh (1980).

Production

We have obtained the data of production for the different industries for 1924. We have taken the production data from Gross Domestic product at factor cost (million pounds) for 1924 elaborated by Feinstein (1972), Table 9, p. T26 and the share of value added in manufacturing for 1924 in Mathews et al. (1982), chap. 4, p. 239. To obtain the data for the year 1913 we have used the index of production of each industry and agriculture, forestry and fishing elaborated by Feinstein (1972).

We have used the above classification of skilled and unskilled sectors to obtain the skilled and unskilled production for the skilled and unskilled sectors.

Capital

The rents of capital are estimated for each sector as a residual obtained from the difference between the value of the production and the income from labour.

Trade

Exports (£m):

Mitchell (1990, p.481).

Source:

Mitchell (1990).

Terms of trade:

Prices of exports on prices of imports in percentages.

Imports (£m):

Mitchell (1990, p.475–476)

Source:

Feinstein (1976).

Average wage

We have calculated an annual average wage for the year 1913 (in pounds), weighted by the participation of each group of workers in the total number of manual workers. We have used the data from Routh (1980, p.99) for 1911 and for obtaining the data for 1913 we use the Index of Money Wages from Bowley (1937).

Education

Literacy:

The percentage of the population over 10–12 years old able to read and write. Source: Flora (1973), in Eisenstadt and Rokkanpp, p. 213–258, 245.

School-enrolment ratio:

Primary school enrolment as a percentage of the population aged 5–14 years old. Calculated from Flora (1987), pp. 78, 559, 624.

Other variables

Migration:

To calculate the impact of emigration in the labour market, we consider that emigration reduced the unskilled labour force by 16% in 1911 following O’Rourke, Williamson and Hatton (1994, p. 208).

Population:

Total population (in thousands) from Mitchell (1998).

Labour force:

We have used the data for the labour force in 1913 elaborated by Routh (1980) which is homogenous with the data of 1951 Census. To calculate the labour force in 1880 we have used the increase in the labour force in the considered sectors from 1880 to 1913 from Mitchell (1998, p. 104)

The growth rate of capital stock:

We have considered the growth of the total gross stock of capital at 1900 prices between 1880 and 1913 from Mitchell (1990, p.864). As in our model, capital involves land and capital, in order to identify productive capital and land accumulation separately we use the percentage which represents the rents of land on GDP in 1841 (from Harley and Crafts 2000) and extrapolate to the year 1913 using the rate of growth of the rents of land and buildings calculated by Feinstein (1972). According to our estimation, the rents of land represented 15% of the production of agriculture (A) and industry (I) in 1913. As the participation of the total rents of capital on GDP (A + I) according to the social accounting matrix was 58.2%, we use the ratio (58.2 − 15)/58.2 to correct the shock in capital of Table 3.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Betrán, C., Ferri, J. & Pons, M.A. Explaining UK wage inequality in the past globalisation period, 1880–1913. Cliometrica 4, 19–50 (2010). https://doi.org/10.1007/s11698-009-0038-z

Download citation

Keywords

  • Wage inequality
  • Globalisation
  • Technological change
  • General equilibrium

JEL Classification

  • N30
  • C68
  • J31