Abstract
This chapter presents the methodology used to construct the new estimates of regional GDP in Spain, breaking down the territory into NUTS3 and NUTS2 regions (provinces and autonomous communities respectively) and dividing sectors homogeneously into five production areas: agriculture, mining, manufacturing and public utilities, construction and services. Taken as a whole in combination with data on regional population, this information provides a picture of regional inequality in per-capita income in Spain over the long term, starting from the early stages of modern economic growth. This new quantitative evidence enables to point out some of the stylized facts observed in the regional distribution of economic activity in Spain that will guide the analysis over the course of the book.
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- 1.
For the nineteenth century and the first third of the twentieth, the only data available are those provided by Álvarez Llano (1986), who reports the distribution of GDP by autonomous community (NUTS2) for six different points in time. However, the fact that the exact method the author used to calculate these figures is unknown undermines their reliability. Among others, Carreras (1990), Martín (1992), Germán Zubero et al. (2001) and Domínguez (2002) have based their analyses of regional inequality in Spain on this dataset.
- 2.
- 3.
See Eurostat.
- 4.
These data series were compiled by researchers who played an active part in designing the national accounts and are therefore methodologically comparable.
- 5.
- 6.
There would also be a need for historical data series of national GDP broken down by sector, since these are the basis for the territorial distribution of economic activity.
- 7.
- 8.
Although the estimation of purchasing power parities and regional deflators for the 155 years analysed lies outside the scope of this study, in Chap. 4, in order to test the robustness of the results, we provide a comparison between the evolution of regional inequality estimated with national deflators and the evolution that would be recorded if territorial price differences were taken into account.
- 9.
Although today there are 50 provinces in Spain, initially the Canary Islands (two provinces) were a single province and appear as such in statistics for the nineteenth and early twentieth centuries. In 1927 they were split into the two provinces we know today, bringing the total up to 50.
- 10.
To some extent this is an anomaly in the context of Europe, since most countries have seen changes in their internal and external borders over the course of history. An extreme example would be the changes that took place after the First World War (1914–1918).
- 11.
In some regions the Spanish language coexists alongside the local language (mainly Catalan, Basque or Galician). It is from these regions that demands have traditionally been made for a more federal view of the state, although this is not exclusively the case, as can be seen from the cantonalist movements in Murcia and Andalusia in the 1870s.
- 12.
This would refer to Andalusia, Aragon, the Balearic Islands, the Canary Islands, Catalonia, Valencia, Galicia and the Basque Country, all recognized as “historical nationalities”.
- 13.
This is relevant because we are carrying out a historical analysis and sometimes refer to the autonomous communities in periods that predate their creation. The regions’ historical continuity makes this reasonable.
- 14.
The various different NUTS divisions in Spain are listed in Table A1 of the Appendix.
- 15.
For the 1880 estimation we use the closest available wage data, which are for 1887.
- 16.
We have taken the 1915 values for 1910 and the 1931 values for 1930.
- 17.
The year when more precise records of the mining workforce were first given in the population census (Foro Hispánico de Cultura 1957).
- 18.
- 19.
- 20.
“Jornales de los obreros de la construcción de carreteras durante el año 1860 en reales de vellón”, Madrazo (1984, p. 208).
- 21.
We use a simple average given that no data on active population in each occupation are available and the average cannot therefore be weighted.
- 22.
Gipuzkoa, Lugo, Ourense, Oviedo, Bizkaia and Zamora.
- 23.
To test this result we take wages for 1897, the nearest date available. In that year the industrial wage in Navarre was 3 per cent higher than the Spanish average weighted by the industrial population. If we apply this percentage to the Spanish value for 1860, the figure obtained almost exactly matches the figure we calculated at the start.
- 24.
- 25.
Simpson (1995), pp. 190 and 199 respectively.
- 26.
The coverage provided by the wages dataset is far from perfect, which meant we had to make some assumptions. First, that the wages series, while not homogeneous over time, is representative of industry. And second, as regards the use of nominal wages, that there will be a bias given that price levels vary between regions (Geary and Stark 2002, pp. 933–934).
- 27.
The years consulted are 1856, 1878–1979, 1890, 1893 and 1900.
- 28.
Due to lack of data, only seven industry sectors are considered for 1913 and 1929 (food, textiles and footwear, metal, chemicals, paper, wood and cork, and ceramic).
- 29.
The use of this source to construct factor shares and then apply them retrospectively means assuming that the intensity of factor use in 1958 is a good proxy for previous years. This assumption has also been made in previous estimations of industrial production indices for Spain (Carreras 1983; Prados de la Escosura 2003).
- 30.
Given that no fiscal information is available, we assume a labour share similar to the Spanish total for the Basque Country provinces and Navarre.
- 31.
The lack of data for 1870 means we have had to obtain the provincial shares for manufacturing by interpolating the values for 1860 and 1880.
- 32.
Since Herranz’s (2008) dataset only applies from 1870 onwards, the data for 1860 were based on urban population alone.
- 33.
Wages were taken from the sources mentioned for the other economic sectors and from Rosés and Sánchez-Alonso (2004). For 1870 (given that no population census was published), the provincial values for the service sector were obtained as an average of 1860 and 1880.
- 34.
Table A1 in the Appendix shows the NUTS1, NUTS2 and NUTS3 regions in Spain with the nomenclature currently used by Eurostat, which reproduces the official administrative nomenclature used in Spain. This nomenclature, however, is in Spanish and in some cases involves rather lengthy names (e.g. Comunidad Foral de Navarra, Principado de Asturias, Región de Murcia, Comunidad Valenciana). To simplify things we use shorter (and sometimes anglicized) versions throughout the main text when referring to the autonomous communities (i.e. Navarre, Asturias, Murcia, Valencia, etc.). The official denominations and equivalent versions we use in the text can be found in Table A2 in the Appendix.
- 35.
The joint GDP share of these five autonomous communities in this case would have been around 55%, to a large degree due to the high participation of Andalusia in the mid-nineteenth century.
- 36.
Within this group, Asturias and Cantabria are those that have probably experienced the most ups and downs in the course of their history.
- 37.
In fact these four regions that represented 31.2% of the population in 1860 represent only 15.3% today.
- 38.
The coefficient of variation, which measures the relationship between the statistical average and the standard deviation, takes on values between 0 and 1. A value of 0 would indicate an absence of dispersion or inequality, and the more it increases, the more it reflects inequality.
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Díez-Minguela, A., Martinez-Galarraga, J., Tirado-Fabregat, D.A. (2018). Methodology, Sources and New Evidence. In: Regional Inequality in Spain. Palgrave Studies in Economic History. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-96110-1_3
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