Fertility Intentions in Italy: An Update from the 2017 Trustlab Data

Arnstein Aassve, Bocconi University
Francesco Mattioli, Bocconi University
Letizia Mencarini, Bocconi University

In this paper we present an analysis of fertility intentions in Italy. We draw on a newly created survey, Trustlab Italy, which was implemented in September 2017. The analysis is based on a representative sample of Italian men and women with 1100 respondents. This sample is supplemented by a booster sample of 400 women aged 18 to 45. For all respondents we have information about the number of children, their partnership status, the number of siblings and the number of children those siblings have - in addition to their age. One neat feature of the Trustlab survey, is that we have information about the municipality where the respondents live. We link our sample with municipality data drawn from ISTAT. There are more than 8000 municipalities in Italy for which ISTAT provides a range of information. For instance, we are able to control for both the TFR in the municipality, economic activity, and childcare coverage. Currently, the last available data on fertility intentions in Italy comes from 2009. One important contribution of this paper is simply to provide an update of the pattern of fertility intentions in Italy. But we are also able to provide additional insights to the Theory of Planned Behaviour, which is the framework fertility intentions are usually framed. For instance, the municipality data adds to the measure of perceived control. In addition, we have a wealth of information about the individual herself, such the personality traits and objective measures of trust, which may matter for the subjective attitude towards children.

In this paper we present an analysis of fertility intentions in Italy. We draw on a newly created survey, Trustlab Italy, which was implemented in September 2017. The analysis is based on a representative sample of Italian men and women with 1100 respondents. This sample is supplemented by a booster sample of 400 women aged 18 to 45. For all respondents we have information about the number of children, their partnership status, the number of siblings and the number of children those siblings have - in addition to their age. One neat feature of the Trustlab survey, is that we have information about the municipality where the respondents live. We link our sample with municipality data drawn from ISTAT. There are more than 8000 municipalities in Italy for which ISTAT provides a range of information. For instance, we are able to control for both the TFR in the municipality, economic activity, and childcare coverage. Currently, the last available data on fertility intentions in Italy comes from 2009. One important contribution of this paper is simply to provide an update of the pattern of fertility intentions in Italy, to assess to which extent the last decade rich of global and local phenomena have had an impact on the low-fertility Italian context. But we are also able to provide additional insights to the Theory of Planned Behaviour, which is the framework fertility intentions are usually framed. For instance, the municipality data adds to the measure of perceived control. In addition, we have a wealth of information about the individual herself, such the personality traits and objective measures of trust, which may matter for the subjective attitude towards children. Drawing on recent evidence establishing that trust matters in determining fertility differentials across countries, the Italian version of Trustlab enables us to study whether and to what extent experimental measures of trust influence fertility through individuals’ fertility intentions – a missing, though relevant, link, so far. The micro-level analysis of the Italian sample allows us to consider the institutional context neutral, thus leaving the results free from noise related to cross-country institutional gaps, which are also relevant explanatory factors of fertility. The rich set of control variables makes it possible to disentangle the impact of a wide range of theoretically valid determinants of fertility intentions. We would be able to isolate the influence of many key factors such as the importance of having being raised and/or living in large versus small households, whether the respondent is or not the firstborn among her siblings, at which parity these factors start or stop being relevant for fertility intentions, whether fertility at the municipality level correlates with the respondents’ intended number of children and what the difference between municipality and respondent’s fertility is due to. The framework provided by the Theory of Planned Behaviour allows us to empirically study whether and how fertility intentions affect actual fertility, and what discrepancies between them are driven by. Moreover, these data let us put into the frame of fertility intentions the role played by psychological forces, captured through questions on personality traits derived from established and validated BIG 5 questionnaires.

Presented in Session 1069: Data and Methods