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North and south: long-run social mobility in England and attitudes toward welfare

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Abstract

In this paper, we examine the long-run social mobility experience in England. We present evidence for surprisingly constant levels of social mobility over the period 1550–1749, despite huge structural changes. Examining regional differences, we show that the North of England exhibited higher rates of social mobility than the South. We link this to the hypothesis that historically high levels of social mobility can lead to a culture of non-acceptance of redistribution and welfare provision. Taking advantage of the fact that welfare provision was determined at the local level at the time, we are able to compare social mobility rates and welfare spending within a single country. Consistent with the hypothesis, we find evidence for historically higher levels of social mobility as well as lower welfare spending and less acceptance of redistribution in the North.

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Fig. 1
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Source: Marshall (1834)

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Notes

  1. We have also run the analysis excluding Gainsborough, and though not significant because we lose a lot of observations, our results are otherwise unaffected.

  2. And indeed relatively highly skilled (see for example Abramitzky 2009).

  3. See Xie and Killewald (2013) for a discussion on potential biases in the data used in Long and Ferrie (2013a). See also Long and Ferrie’s reply (2013b).

  4. This was made very much easier by the availability of the Stata program for performing the analysis in the appendix of Altham and Ferrie (2007).

  5. One could also argue that people will only be able to observe social mobility not adjusted for occupational structures and that this should matter for the formation of the sort of beliefs and attitudes toward welfare we discuss in the following section. In our case, differences between the North and the South are in fact larger when comparing unadjusted mobility.

  6. The method has been criticized for not being able to decompose total mobility into structural and exchange mobility (Hout and Guest 2013). We choose this method to be able to compare our results to those of Long and Ferrie (2013a) and due to the advantages of the method, discussed above and in Long and Ferrie (2013a, b).

  7. Note that M’ uses marginal frequencies adjusted to the period 1850–1880, but this measure does not give a significance level. D(X,I) gives a significance level, but measures the difference of the mobility matrix in one period to independence and is thus not adjusted to the period 1850–1880. The choice of the base period does therefore not affect significance levels here.

  8. The difference is statistically insignificant according to the Altham statistics for the different periods.

  9. Results for other countries and other time periods suggest considerable diversity across time and space. Long and Ferrie (2013a) find an Altham statistic of around 12 for the US in the late nineteenth century, increasing to almost 21 one century later. Modalsli (2015) finds an Altham statistic of around 22 for Norway in the period 1960–1980. At the other extreme, it is around 100 in India for cohorts after the Second World War (Azam 2013).

  10. The size of the intergenerational elasticity of earnings is dependent on the standard deviations in the earnings distributions of fathers and sons, i.e., the earnings inequality. It has therefore been suggested to look at the intergenerational correlation (see Blanden et al. 2004), which adjusts for the ratio of the standard deviations. In general, the intergenerational correlation will be larger than the intergenerational elasticity when inequality increases from fathers to sons. Here, we are interested in differences between North and South rather than the absolute size of the association between fathers’ and sons’ earnings. We therefore estimate the intergenerational elasticity, also for easier comparison with previous studies.

  11. It should be noted here that including the southwest of England, Devon and Cornwall, which also had low levels of Poor Law spending, in the ‘North’ makes no difference to our results, since there are few observations from Devon, and none from Cornwall.

  12. ‘Crop suitability index (class) for low input level rain-fed cereals’, from GAEZ, Global Agro-Ecological Zones, at the Food and Agriculture Organization of the United Nations.

  13. See http://www.europeanvaluestudy.eu for a full list of the questions.

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Acknowledgements

We would like to thank Gregory Clark, Nicholas Crafts, Carl-Johan Dalgaard, Marc Klemp, Andreea-Alexandra Maerean, Karl Gunnar Persson, Ulrich Pfister, Eric Schneider, Jacob Weisdorf as well as participants at seminars and conferences for their help and suggestions. Thanks also to the Cambridge Group for allowing us to use the family reconstitution data.

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Authors and Affiliations

  1. University of Southern Denmark, Odense, Denmark

    Nina Boberg-Fazlić & Paul Sharp

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  1. Nina Boberg-Fazlić
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Correspondence to Paul Sharp.

Appendix

Appendix

See Figs. 4 and 5 and Tables 7, 8, 9, 10, 11 and 12.

Fig. 4
figure 4

Source: Marshall (1834)

Relief spending per recipient by county, 1803.

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Fig. 5
figure 5

Source: Marshall (1834)

Number of poor relief recipients by county, 1803.

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Table 7 Frequencies of observations by occupational group and location
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Table 8 Examples of occupations in the four groups
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Table 9 Mobility tables, intergenerational occupational mobility in Northern England, 100-year periods
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Table 10 Mobility tables, intergenerational occupational mobility in Southern England, 100-year periods
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Table 11 Components of d(North,I), d(South,I) and d(South,North), pre-1650
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Table 12 Components of d(North,I), d(South,I) and d(South,North), 1650–1749
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We have coded all the occupations in the dataset according to the HISCO classification scheme. HISCO, the historical version of the ISCO scheme, gives a code to each occupation based on the duties and tasks performed in the occupation. These are then grouped together into different “social classes” according to the degree of supervision exercised and whether the occupation was manual or non-manual. This scheme is called HISCLASS and gives a total of 12 “social classes”, with class 12 being the lowest and class 1 the highest. For more details on HISCO and HISCLASS, see also van Leeuwen et al. (2002) and van Leeuwen and Maas (2011).

Whenever the specific occupation/HISCO code in our data is not available in one of Williamson’s wage groups we assign an average of one or several, similar wage groups to the occupation according to the HISCLASS it is in. We do this according to the following scheme: Table 13.

Table 13 Link from HISCLASS to Williamson wage groups
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Boberg-Fazlić, N., Sharp, P. North and south: long-run social mobility in England and attitudes toward welfare. Cliometrica 12, 251–276 (2018). https://doi.org/10.1007/s11698-017-0160-2

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