Abstract
In this chapter we review the literature on the origins and implications of family structure in historical perspective with a focus on Italian provinces. Furthermore, we present newly collected data on three of the main features of family structure: the female mean age at marriage, the female celibacy rate, and the fraction of illegitimate births. Data are collected at the provincial level for 1871. The analysis of the data allows us to confirm and quantify the geographic differentiation in family patterns across the country. We also illustrate the links between family structure and a set of socioeconomic outcomes, in the short, medium, and long run.
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Notes
- 1.
In the demographic literature, delayed marriage and high celibacy are also referred to as “Malthusian preventive checks” on fertility, that is, behaviors aimed at controlling reproduction, consciously or not, which differ from the “positive checks,” namely, mortality by famine, wars, or diseases (Malthus 1798). An implication of the “preventive checks” is the possibility of high illegitimacy rates.
- 2.
Todd obtains his classification by applying the “regressive method” due to Bloch (1949). Starting with contemporaneous census data for Western Europe, mostly collected for the 1950s and 1960s, he goes back to historical data. By comparison he can establish strong persistence of the observed family types back to the Middle Age. Outside Europe, Todd also classifies three additional family types, i.e., the endogamous community, anomic, and African families.
- 3.
We refer to the literature cited by Dennison and Ogilvie (2014) for further details.
- 4.
The latter are Belluno, Padua, Rovigo, Treviso, Udine, Venice, Verona, and Vicenza.
- 5.
The maps do not include the area in the North corresponding to Trentino, which was not part of the Kingdom of Italy in 1871 but entered afterward. See the Appendix for definitions and sources of variables.
- 6.
Todd (1984) also proposes an alternative classification criterion based on the relationship between husband and wife as captured by the degree of feminism, which is at its highest under matrilineality, at its lowest under patrilineality, and at an intermediate level under bilaterality. A family system is considered matrilinear if it assigns a prominent social role to the kinship of the wife.
- 7.
Italy exhibits rich variation in family types also in an international comparison. For instance, Spain exhibits only two family types: the stem in the North and the egalitarian nuclear in the South, while England presents the egalitarian nuclear family in the East and the incomplete stem in the West.
- 8.
- 9.
Data on male mean age at marriage (again adjusted to exclude marriages where the bride is older than 45) reveal that the relevant range for men is between 27 and 32, with a limited age difference between grooms and brides ranging from 2 to 5.
- 10.
To account for female age at marriage, Bertocchi and Bozzano (2015) propose an alternative measure based on data from Barbagli (1987) on the percentage of women married below the age of 15 in 1872–1875. The original source is DIRSTAT (1877). However, information is available only at the regional level. Consistent with the variables presented here, on average women marry before age 15 years in only 3% of the regions, even though the figure is as high as 13% in the case of Sicily.
- 11.
As an alternative measure, Livi Bacci (1980) employs the celibacy rate for women between age 50 and 54.
- 12.
More recently Voigtlander and Voth (2013) specify that high celibacy rates range between 10 and 30% depending on time and place.
- 13.
Rome entered the unified Kingdom of Italy in 1871 but the datum is missing for this year in MAIC (1874).
- 14.
Campa et al. (2011) employ a measure of the gender gap in literacy in 1911 as an instrument for gender culture, which is in turn shown to affect the present gender gap in employment.
- 15.
In the literature on gender inequality, early age at marriage for girls is widely recognized as a good measure of female agency and subordination of women in society. Additional information is provided by the spousal age gap and by male age at marriage. According to our data, male age at marriage is highly correlated with female age at marriage (70%), while spousal age gap is poorly correlated (30%).
- 16.
Turning to family types, height is correlated negatively with the presence of the egalitarian nuclear family type with early marriage and positively with that of the incomplete stem family type. Literacy is negatively correlated with the egalitarian nuclear family with early marriage and positively with the egalitarian nuclear family with late marriage. Female to male literacy is negatively linked to the egalitarian nuclear family with early marriage. The crude birth rate in 1871 is correlated positively with the incomplete stem family type and negatively with the communitarian family, while the same variable in 1881 is positively correlated with the egalitarian nuclear family with early marriage and negatively with the communitarian family. These correlations are not reported in Table 6.2 for simplicity.
- 17.
We refer to the Appendix for sources and further details on the variables included in this analysis.
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Acknowledgments
We would like to thank three reviewers for their comments and suggestions. Generous financial support from Fondazione Cassa Risparmio di Modena and the Italian University Ministry is gratefully acknowledged.
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Appendix
Appendix
6.1.1 Description of Variables
6.1.1.1 (A) Family Structure Data
Female mean age at marriage
We collect data from MAIC (1872, vol. 2) on the age of all brides who got married in 1871. Data are available by age group as follows: below 20, 20–24, 25–29, 30–44, 45–59, and over 60.
Share of brides aged 20 or less
We compute the percentage of brides aged 20 or less over the total number of marriages in 1871. Data are from MAIC (1872, vol. 2).
Female celibacy rate (over age 50)
Census 1871 provides detailed information on the marital status of the population disaggregated by gender and by year of age. For each province, we collect data on the age-specific marital status and calculate our indicator as the number of female celibates aged 50 or more over the total number of women in the same age range. The source is MAIC (1872, vol. 2).
Illegitimacy rate
This indicator is calculated from life statistics in 1871 (MAIC 1874). Births are disaggregated into legitimate, illegitimate, and “esposti” (i.e., abandoned infants). In this work the illegitimacy rate is calculated taking into account both out-of-wedlock births and abandoned infants over the total number of births in the same year. For Rome (and Comarca) data refers to 1872 (MAIC 1875).
Nuclearity
We define a dummy variable taking value 1 if the province was dominated by nuclear residential habits, 0 if by complex ones. Information is from Todd (1990).
Family types
These variables are taken from Bertocchi and Bozzano (2015), who adapt the classification proposed by Todd (1990) to the Italian specific regional differentiation following Hajnal (1982), Barbagli (1987), and Del Panta et al. (1996). Provinces are coded according to a set of four dummies, one for each family type, i.e., egalitarian nuclear with late marriage, incomplete stem, communitarian, and egalitarian nuclear family with early marriage.
6.1.1.2 (B) 1871 and 1881 Data
Height
Since historical data about income or wealth for Italian provinces are not available, we employ heights as a proxy. Data on heights refer to the mean height of military conscripts aged 20 at the provincial level and are taken from A’Hearn and Vecchi (2011, Table S3). We employ data referring to 1871 and 1881.
Industrialization
Data on industrialization at the provincial level are taken from Ciccarelli and Fenoaltea (2013, Table 2). The variable is a provincial index of relative industrialization calculated on the basis of census data as the share of industrial value added, excluding construction, over the share of the male population over age 15. We employ data referring to 1871 and 1881.
Human capital
We collect data on literacy, female literacy, and male literacy for population aged 20 or more, both for 1871 and 1881, from the censuses (MAIC 1872, 1883). We also obtain a measure of equality in human capital accumulation as the female to male ratio of literacy rates in both years: this measure ranges between 0 (perfect inequality) and 1 (perfect equality) and is therefore increasing in gender equality.
Crude birth rate
Our fertility measure is the standard one. We collect data on total births in 1871 and 1881 for each province, and we calculate the crude birth rate as the number of live births (legitimates, illegitimate, and “esposti”) per 1000 inhabitants. The source is MAIC (1874, 1882; for Rome, MAIC 1875).
6.1.1.3 (C) 2001 Data
Income
We use the natural logarithm of total value added per capita in 2001 (Italian lira, constant prices, base year 2000). The source is Istituto Guglielmo Tagliacarne (2011).
Labor market variables
We employ two variables taken from Bozzano (2017). The first refers to the female to male ratio of the labor force participation rate, defined as female labor force participation rate over male labor force participation rate. The second is the female to male ratio in economic leadership, defined as the share of women who are in charge of enterprises or in top managerial positions over the share of men employed in the same positions. Both variables are elaborated from the 2001 census and take values between 0 (perfect inequality between women and men) and 1 (perfect equality), so that they increase in gender equality.
Education variables
We employ variables taken from Bertocchi and Bozzano (2015), who collected data on female and male secondary and tertiary attainment for 2001 from the national census (ISTAT 2009) and computed female to male ratios. Both variables are weighted by female and male population aged 19 or more. The first variable is defined as the ratio between females with at least a high school diploma over female population over age 19 and males with at least a high school diploma over male population over age 19. Likewise, the second variable is the ratio between females with a university degree over female population over age 19 and males with a university degree over male population over age 19.
Fertility rate
This variable is defined as the average number of children per women aged 15–49 (i.e., total fertility rate net of immigration fertility rate) and measured in 2001 (ISTAT 2009).
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Bertocchi, G., Bozzano, M. (2019). Origins and Implications of Family Structure Across Italian Provinces in Historical Perspective. In: Diebolt, C., Rijpma, A., Carmichael, S., Dilli, S., Störmer, C. (eds) Cliometrics of the Family. Studies in Economic History. Springer, Cham. https://doi.org/10.1007/978-3-319-99480-2_6
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