Agency embodies three types of temporalities: iteration, projectivity, and practical evaluation (Emirbayer and Mische, 1998). “Iteration” refers to actors' routine reactivation of past patterns of thought and action, “projection” entails the capacity to imagine possible future action trajectories, and “practical evaluation” is the capacity to make practical and normative judgments based on present alternatives and deliberations (Emirbayer and Mische, 1998, p. 917).³ Fertility plans are long-term in nature, where routine tends to gives way to the agency of projectivity and deliberation (Mische, 2009). Child-bearing is a life-changing decision that requires one to first imagine the future condition of parenthood (projective agency), then a choice on whether and when childbearing should occur (practice evaluative agency). In a modern contraceptive regime, childbearing tends to be intentional (Ajzen and Klobas, 2013), though not in the form of rational cost-benefit calculations. Fertility plans are truly uncertain due to the unforeseeable nature of the long-term consequences of planning or postponing childbearing (Vignoli et al., 2020a). This is because such decisions are always taken in conditions of uncertainty (which is not to say risk), and they are guided by a narrative of the future that can be more or less plausible and normatively oriented (Bazzani, forthcoming; Tavory and Eliasoph, 2013; Tuckett and Nikolic, 2017).⁴

Fertility plans “force” people to de-routinise their courses of action. Routine can be interrupted by the emergence of conflict between “different habits, or by the release of impulses” (Beckert, 2016, p. 54),⁵ wherein individuals experience uncertainty over the future that require (new) judgments, thereby allowing the deliberative process to emerge. In an uncertain situation, past experiences and expectations become relevant in an imaginative “dialogue” considering “competing possible lines of action” (Dewey, 1930, p. 190).

In the routine condition, different possible narratives of the future life-course may co-exist in a vague or undecided scenario. Parental pressure for grandchildren, peers' parenthood experiences, and personal imaginaries of children may interrupt young adults' routines and force them to problematise their daily lives, thus causing them to consider childbearing when they would not otherwise have done so. Fertility decisions force people to re-shape future life plans and establish new narrative of the future, including even postponing or abandoning fertility plans. In this sense, fertility plans are a personal space of “hyperprojectivity.” Mische (2014) developed the concept of hyperprojectivity by studying arenas of heightened, future-oriented public debate about contending futures, such as those occurring in communities, social movements, and policy arenas. We use this concept to describe a similarly high level of projective capacity taking place at the personal level of fertility plans: considering an imagined long-term future forces one to reconsider the present situation based on its strengths and weaknesses, thus potentially leading to new plans. The level of household income or expected employment stability are often considered prerequisites to parenthood (Alderotti et al., 2021). However, the specific characteristics of such prerequisites are always contingent and re-evaluated, such as in view of personal age (micro-level), the quality of the relationship with the partner (meso-level), or the availability of family policies (macro-level).

Fertility plans are the outcome of the imaginative dialogue on life-course outcomes. However, these plans cannot be reduced to either personal will or psychological forces that are the common factors operationalised in agency research. These factors include self-esteem (Cast and Burke, 2002), self-efficacy (Bandura, 1986), mastery (Pearlin and Schooler, 1978), personal control (Mirowsky and Ross, 2007), optimism for the future (Frye, 2012), and planful competence (Clausen, 1991). Indeed, while “emotions and personality traits – along with idiosyncratic personal histories, moral codes, and predispositions – influence the choices we make in emergent situations” (Hitlin and Elder, 2007, p. 178), there are also contingent situational contexts that influence courses of action. From a sociological perspective, it is crucial to understand “what kinds of contexts provoke or facilitate them [actors] toward gaining imaginative distance from those responses and thereby reformulating past patterns through the projection of alternative future trajectories” (Emirbayer and Mische, 1998, p. 1006). To this end, Hobson suggested that “situated agency is a more sociological concept capturing the relational aspects of agency, the diversity in individual situations that shape agency freedom, and the potential to convert resources into achievements” (2018:11). The concept of situated agency (Peter, 2003; Choi et al., 2019) is useful for considering the relational dimension of agency (Abbott, 2020), in that it is “always agency toward something, by means of which actors enter into a relationship with surrounding persons, places, meanings, and events” (Emirbayer and Mische, 1998, p. 973).

From this perspective, fertility plans are not only the direct effect of some pre-existing internal anthropological force (e.g., desire or impulse), but they are also oriented by contingent factors that shape the course of action.⁶ Personal resources (e.g., a stable partnership and the desire for children) are frequently unconverted into fertility plans and behavior due to situational hindering factors. Indeed, agency freedoms, involve more than “desire,” but embrace agency and choice and the power to act on choices (Hobson and Zimmermann, 2022). The misalignment between resources and desire (capability inputs), and actual plans and realization (agency freedom and achievements), seems to suggest the utility of considering the interplay between situational conversion factors and the long-term processes, such as the individual characteristics and structural factors explored within the literature. Indeed, this gap between desires and actual fertility plans may stem from a wide array of factors, as “unresolved tensions between choice and freedom and puzzling paradoxes mark individual agency” (Lebano and Jamieson, 2020, p. 125). Within the capability framework, conversion factors can determine whether or not individual resources and structural factors are converted into agency through a conversion process.

Recent developments have translated into a more sociological formulation of Sen's conversion factors that convert resources into agency achievement Sen (1999, 2005, 2008), considering the micro-, meso-, and macro-levels of analysis, as well as feedback processes (Hvinden and Halvorsen, 2018; Bazzani, 2022). Hobson and Zimmermann's (2022) model of future making involves a multi-dimensional relational dynamic of situated agency which can be enabled by the capability to aspire and activated through the conversion of institutional, organizational, cultural and societal resources. In our multi-dimensional framework, the three types of temporalities elaborated by Emirbayer and Mische (1998) are considered together with micro, meso, and macro level conversion factors that enable or hinder fertility agency. Figure 1 illustrates a stylised representation of the conversion processes of fertility agency with the different levels and elements involved (conversion factors), including their temporal orientation.⁷ The schema accords with the idea of multi-level structures influencing fertility and other life-course dynamics (Matysiak and Vignoli, 2010; Huinink and Kohli, 2014; Billari, 2015; Bernardi et al., 2019).

The iterative dimension of fertility agency is embedded in the elements belonging to the “shadow of the past” and the “present condition,” despite often deploying their effects on future expectations. Projectivity agency is influenced by the “shadow of the future” and synthesized in the “personal narrative of the future,” which also includes fertility decisions (practical evaluative agency; Emirbayer and Mische, 1998; Mische, 2009, 2014). The conversion processes mediate the relationship between personal resources (e.g., stable relationship, fecundity) with agency (fertility plans and behavior), and contain several elements that may be involved as conversion factors. The conversion factors are presented as a typology organized according to their level (micro, meso, and macro) and temporal orientation (past, present, and future)⁸ (Bernardi et al., 2019). Moreover, conversion factors could either “hinder” or “enable” the process. Some of the conversion factors that may influence fertility plans have already been considered within the literature. The following section introduces the most influential theories for explaining the fertility declines observed in wealthier countries, and discusses their major shortcomings.

The data employed in the analyses were taken from a survey organized by the University of Florence between June 2019 and early February 2020 – i.e., before the COVID-19 pandemic. The survey was part of a laboratory experiment dedicated to studying the influence of economic uncertainty on fertility intentions, and was planned by a multidisciplinary team of demographers, sociologists, social psychologists, and economists. The team met several times throughout the course of a year to design the questionnaire and run pilot tests. The survey protocol was approved by the Ethics Committee of the University of Florence and was then updated after the pilot, whereupon it was once again approved by the Ethics Committee. Please see Vignoli et al. (2022), Appendix 1 for further details.

The analyzed data came from a subsample of respondents consisting of the control group (1/3 of the sample) who were not exposed to any lab treatment and only answered the survey questions. Our participants consisted of 276 respondents aged between 20–40 in stable relationships (i.e., married, cohabiting, or living apart). We ensured a balanced participation by sex, as well as between the jobless, permanently employed, and temporarily employed. The participants were recruited through the services of a specialized survey agency, which gave no information as to the content of the research (i.e., no references to family or economic aspects were made). The agency was also asked to try to ensure a distribution by education and parity that would mimic that of the national population distribution, but without imposing strict quotas. Participants were selected from panel participants available to the agency, boosted with additional participants recruited through advertisements distributed in public places, again without providing any information about the experiment's content.

We asked the participants to answer a large array of demographic, socio-economic, and psychological questions. The first part of the questionnaire was dedicated to fertility intentions, followed by open questions about the role of uncertainty in their lives and the personal narratives associated with fertility intentions (Vignoli et al., 2022). They were asked about their fertility intentions for the following 3 years (Q: “Do you intend to have a child in the next 3 years”). We focused on fertility intentions as it is the first step of fertility agency and a good predictor of subsequent behaviors. Indeed, fertility intentions “in close temporal proximity to the prospective behavior” (Ajzen and Fishbein, 1973, p. 49) are generally considered suitable predictors of actual behavior (Philipov, 2009; Spéder and Kapitány, 2009; Régnier-Loilier et al., 2011). Following recommendations from the psychology literature, we assessed fertility intentions on a scale of 0 to 10 (where 0 corresponded to “definitely not” and 10 to “definitely yes”) in order to grasp individual differences in psychological constructs with acceptable levels of precision (MacCallum et al., 2002). This choice allowed us to address both the direction and intensity of fertility intentions. The intermediate point of the scale was also included so as to capture ambivalent or neutral positions (Zammuner, 1998). We implemented the survey using the O-TREE open-source platform (Chen et al., 2016).

We analyzed the answers to two open questions about personal narratives associated with fertility intentions. The first focused on personal aspects: “When you were asked if you intend to have a child in the next 3 years on a scale from 1 to 10, you answered X. Which aspects of your personal situation were more important in deciding your answer?” The second considered the role of macro-economic factors on fertility decisions: “When you were asked if you intend to have a child in the next 3 years on a scale from 1 to 10, you answered X. Which aspects of the economic situation of your country were more important in deciding your answer?”. We refined both questions following the results of successive pilot tests to ensure their clarity and capacity for capturing the information most relevant to the research aims. Instead of using two different questions for the micro and meso conversion factors, pilot tests showed that a single open question (on their “personal situation”) was able to encourage the respondents to consider both micro and meso aspects. This strategy allowed the respondents to separately consider the micro and meso aspects while also giving them the freedom to report on one or both aspects, thereby enabling us to understand the similarities and differences of their personal narratives. While in-person interviews on family planning may be oriented toward social desirability, social norms, and interviewer expectations, we attempted to overcome these biases by collecting the answers to the open-ended questions through an anonymous form completed on a computer (Colton and Covert, 2007).

Fertility intentions for the next 3 years are part of fertility plans that are influenced by – but do not necessarily coincide with – personal imaginaries related to children. Answers about abstract ideal family size are more likely to reflect societal norms than those about personal imaginaries of family and children (Sobotka and Beaujouan, 2014). Exploring how individuals depict their family imaginaries is further complicated by social desirability and cognitive dissonance biases (Burke and Stets, 1999). Following the literature on expected happiness (Billari, 2009; Mencarini et al., 2018) and affective forecast (Wilson and Gilbert, 2003), we asked the respondents (on a scale of 0 to 10) how much happier would having a(nother) child make them. Higher values can be interpreted as the ultimate outcome of a positive family imaginary that would eventually allow one to identify the gap between family imaginaries and real fertility intentions.

Drawing distinct measures between fertility intentions and the expected happiness that having a(nother) child could bring allowed us to more closely focus on analyzing the enabling and hindering conversion factors of fertility intentions within the respondents' personal narratives. Accordingly, the analysis explored two distinct subsamples of respondents. We analyzed the enabling factors in the answers to the open questions for respondents with fertility intentions from 5 to 10 (Achieved capability group, N = 146), and the hindering factors among the respondents with fertility intentions lower than the value attributed to the expected happiness of a(nother) child (Unachieved capability group, N = 166). We assumed that this group of respondents had faced some obstacles to their fertility intentions that we hoped to explore in their answers to the open questions. The two groups partly overlapped by construction: The achieved capability group was used to code the factors enabling fertility intentions, and the unachieved capability group to code the factors hindering it. The descriptive statistics of the sample and the two subsamples can be seen in Table A1 of the Supplementary material.

Open question data (which has been typically unused in most previous studies in the field) has the advantage that the analyst has access to the respondents' ideas in their own words. This opens up possibilities of using content analysis to search for subtler patterns within the responses compared with closed questions (Fielding et al., 2013). In order to analyse these patterns, we used an inductive approach to identify the relevant factors without assuming a predetermined set of variables (Boyatzis, 1998). We analyzed the answers to the two open questions using MAXQDA-2020 software, and coded them according to the content analysis approach (Züll, 2016) for both the achieved and unachieved capability groups. We anonymised the answers prior to the analysis. In particular, the interview coding sought to capture the different conversion factors that people felt were relevant in their fertility decision-making processes. We used an iterative process that started with a round of open coding. All of the transcripts were read, whereupon we highlighted recurring themes and reflected on emergent issues in a series of memos. This process generated a list of initial codes that we then used in a second review of each transcript. Initial ideas and themes were refined in the context of this second review. Double coding of randomized subsamples of the materials was conducted by a second coder to assess the reliability of the coding procedures. Differences in coder agreement were minimal and resolved via discussion. Once done, the refinements involved both splitting categories into those with finer distinctions and combining categories as deeper themes became apparent (Fielding et al., 2013). In the next step, we grouped the different factors according to the varying micro, meso, and macro levels of the conversion factors (Figure 1). We interpreted the presence of the different self-reported factors related to fertility plans as a signal of their influencing capacity within the conversion process of fertility agency. Thus, as an application of the inductive method, we generated a table setting out the numbers or proportions of responses that referred to each of the conversion factors identified in the data (Sandelowski, 2001; Fielding et al., 2013).

The answers to the two open questions shed light on the personal narratives associated with fertility agency, which represent agency's projective and deliberative side (Emirbayer and Mische, 1998). However, there may well be conversion factors that are part of the iterative side of agency of which people are either simply unaware, or follow a “silent” reduction and production of possibilities (i.e., “manifest in automatic rather than deliberative cognition,” DiMaggio, 1997, p. 269–71). While these types of conversion factors are “structural” and influence the fertility decision-making process, they are not readily apparent when directly analyzing personal narratives. Indeed, people may be unaware of their influence or dismissive of their relevance. We conducted the analysis of the role of structural conversion factors on personal narratives with a convergent analysis with the data-based integration of answers to the open and closed questions (Fielding, 2012; Morgan, 2014; Kuckartz and Rädiker, 2019). Once the thematic coding had been completed and checked, we analyzed the distribution of the patterns of responses by using the code frequencies across different groups of respondents with cross-tabulation functions. This allowed us to generate tables based on selected combinations of thematic codes and attributes (‘quantitative analysis of code frequencies broken down by groups' Kuckartz and Rädiker, 2019, p. 179; Fielding et al., 2013; see also Sandelowski, 2001; Kuckartz, 2014, p. 140–142; Guetterman et al., 2015; Hesse-Biber et al., 2015, p. 5–7). We used the answers to closed questions on working conditions, education level, sex, religiosity, and the number of children to observe the different distribution of the conversion factors among those groups.⁹

To grasp the effects of unemployment or temporary job contracts on fertility plans, we classified the respondents according to their employment condition (1 = employed with a permanent contract; 2 = employed with a temporary contract; 3 = jobless). Regarding education's impact on fertility, we distinguished the respondents' education levels between low (1 = elementary, junior high school, and short vocational courses), medium (2 = high school), and high (3 = tertiary or higher). The respondents' religious affiliation was classified by distinguishing between those who felt themselves as belonging to a specific religion and those who did not. The overwhelming number of religious respondents (88%) declared themselves to be Catholics. We conducted the analysis for first-birth, second-birth, and higher-order parity separately, and divided the respondents between the childless and parents with one, two, and three children for the unachieved capability subsample. Due to their limited number, we did not consider respondents with two or three children (four and five respondents, respectively) as being part of the achieved capability subsample.

We interpreted the results of the analysis of the distribution of codes among different groups of respondents as the presence of different/similar conversion factors in personal narratives associated with fertility intentions (Kuckartz and Rädiker, 2019).¹⁰ In some cases, we observed unexpected results in the distribution patterns of the conversion factors among groups. In such cases, we developed qualitative insights on specific subsamples.

At the micro-level, the most frequently reported hindering factors were perceptions and expectations concerning the economic situation and imaginaries related to children and family (Table 1, column 1). Indeed, economic factors were reported in half of the coded segments. Among the hindering economic factors cited, the respondents mentioned precarious jobs, low-income levels, joblessness, as well as uncertainty and generic economic troubles. Precarious jobs refer to various types of working conditions, from seasonal work with temporary contracts (“Mainly my work situation, working seasonally I cannot ensure security in the first place for me, in secundis for my future children” female, 30) to self-employment with a relatively developed career. Uncertainty and generic economic troubles often refer to – without specifying an exact meaning – an “uncertain personal economic situation” or “employment situation.”

Interestingly, the economic hindering factors were not only reported by the jobless or the temporarily employed, but also (albeit less frequently) by those with permanent work contracts (Table 1, column 5). Despite the absence of precarious employment, these respondents reported sharing a common feeling of progressive deterioration of working conditions. “The working environment is too precarious, the economic condition is very important to be able to guarantee a future for our children” (male, 43, permanently employed). Moreover, some stably-employed respondents reported low-income levels. “The situation in the world of work whereby workers' salaries do not follow the trend in the cost of living and the consequent increases in the cost of all accessory and essential goods” (male, 32, permanently employed).

The distribution of the economic hindering factors among different education levels followed an unexpected increasing pattern for highly-educated respondents (Table 1, columns 6, 7, and 8). While we may have expected that high education levels would correspond with better employment conditions (which, in turn, would not represent an obstacle to fertility intentions), the distribution pattern of economic factors suggests their salience also for the highly-educated subgroup. This is because high levels of education do not always correspond with better working conditions. “In the historical period in which we find ourselves, we young precarious people, with difficulties in creating a stable position, find it difficult to set ourselves such goals. We need to think more about surviving in the current world of work than we do about having a child” (male, 34, high education). Some respondents began professional careers which often require years of work before a stable income is granted. “I work, I am a practicing attorney and the path is very long if you want to go freelance. The earnings are very random” (female, 32, high education). Indeed, this low-income obstacle was also shared by respondents with jobs requiring high levels of education. “Bha, last year when I worked as an educator in a cooperative I earned 6 euros net per hour, how the fuck do you raise a child with a salary like that?” (male, 27, high education).

While it is obvious that the economic cost of children increases in line with their number, the reported salience of economic hindering factors for having another child, conversely, decreased after one child, and much more significantly after two (Table 1, columns 11, 12, 13, and 14). The types of reported concerns were similar across different parities and regarding both the precarious job condition and the low-income level (Table A2). Different hypotheses can be advanced for this unexpected phenomenon. For instance, we could speculate that families with one or two children were selected among those with greater economic resources. We calculated the mean monthly salary of the respondents, but found it to be relatively similar across the different groups, thereby not supporting the selection hypothesis.¹¹ Alternatively, we may also hypothesize that childless people have unrealistic expectations of the cost of raising a child. The perceived capacity of coping with the economic and personal burdens of childrearing may increase with the parenthood experience together with the decreasing salience of the economic aspects. However, it seems reasonable to argue that the experience of parenthood changes the attributed salience of different aspects of people's lives, including the economic prerequisites. “With our first daughter, we were conditioned by our and our country's economic situation. We put it off for several years hoping for a better time, but since she is here, now 3 years old, there could not be a better time” (female, 34).

Among perceptions and expectations, inadequate housing conditions for hosting a(nother) child and hardships in work-family conciliation were often reported. Regarding the latter, people reported that they expected to be unable to successfully meet their children's needs or have sufficient time to work. Conciliation problems were associated both with the need for career development and the absence of flexibility in the working schedule. “I wish I had achieved a more stable and better paid position, lack of flexibility regarding working hours – I am not allowed to work remotely” (male, 31). In some cases, school timetables did not coincide with parents' working hours. “I already have two children, no help (not even financial) close other than my husband. The management is all in my hands. At the slightest hitch, there is a problem. School hours do not coincide with work hours. My contract was not renewed when it expired after returning from my second maternity leave” (female, 33).

Imaginaries related to children and family were frequently cited as hindering factors to fertility intentions. Reported hindering imaginaries refer to expected parental duties and the fulfillment of personal aspirations outside of the family. Table 2 displays these categories along with the respondents' exemplary quotations. The most common categories which emerged were the desire for self-realization and freedom as obstacles to deciding to have a(nother) child. The respondents believed that having a(nother) child would not only reduce their time for self-realization and travel, but also limit time for couple activities or career developments. This argument – which accords with SDT theory – contrasts the presence of children with self-fulfillment and champions the latter.

The desire for self-realization and freedom was not an exclusive feature of highly-educated, career-oriented respondents, but was also observed in those with lower levels of education (Table 1, columns 6 and 7). Moreover, the desire for self-realization as an obstacle to fertility intentions almost disappeared after the arrival of the first child (Table 1, columns 12, 13, and 14). Despite the expectation that the presence of one child should reduce the time for personal activities and increase fears of further reductions in the case of an additional one, this fear decreases in importance after the first child. As with the presence of economic obstacles across parities, this trend seems counterintuitive: The experience of parenthood shapes personal perceptions that directly contrast the objective condition and its subjective perception.

The second most common group of categories was imaginaries of intensive parenting (Hays, 1996; Gauthier et al., 2020). Those imaginaries view the presence of children as an enormous responsibility due to the vast quantities of time and effort required to nurture and educate them. Childrearing is often referred to as a “full-time job” that requires enormous amounts of engagement. These frightened imaginaries of parenthood may also manifest themselves as guilt over not being able to provide “everything a child deserves”, both in economic and non-economic terms. Finally, for some respondents, these feelings of inadequacy were not limited to certain life standards, but also to their whole personal identities, where they spoke of “inadequate personal maturity.”

Certain meso-level conversion factors also emerged. They mostly referred to the presence of other children and the characteristics of their relationships with their partners. The partner characteristics reported as obstacles to fertility intentions referred mostly to the partner's job (specifically regarding unemployment or difficult work-family conciliation). “The current state of my relationship and the work situation of my partner, who is often away on business. Before having a child, I want to make sure I can create the best possible family environment around him or her” (male, 34).

Despite the fact that the open question analyzed thus far concerned personal situational factors, some respondents reported macro-level factors. However, we were able to more accurately analyse macro-economic hindering factors with the answers to the open question on macro-economic aspects.

Table 3 shows the codes and frequencies of the macro-economic hindering factors to fertility intentions for the unachieved capability group. The most common group of factors related to economic issues, while the second concerned (the lack of) policies. The respondents cited a general feeling of insecurity and distrust over the country's future economic situation as an obstacle to fertility plans. “Currently, in my country, the economic situation is definitely devastating. There are no positive aspects today to push a couple to have children. Unfortunately, if you are lucky, you can find a temporary job that often – because of the “system” – is not renewed and then you have to start from zero” (female, 26). Regarding economics, the most reported factors were low incomes, precarious jobs or the lack of job opportunities, and generic economic uncertainty (Table 3, columns 1–4). Moreover, the respondents also reported feeling a progressive deterioration of working conditions and rising levels of insecurity. “Everything, there is no more security in anything, nor on the workplace and then on an income, nor at the level of aid from the state, the situation is becoming drastic to say the least” (male, 33). Precarious labor conditions also prohibit people from being granted a mortgage, which is a situation that can be overcome only with the support of affluent families of origin. “The progressive reduction of the most basic social rights: It is now impossible to find a decent permanent job, to obtain a mortgage, to have even a minimum economic security if one does not already come from a wealthy family” (female, 29). In terms of the distribution of the macro-economic hindering factors across different parities (Table 3, columns 5–8), there was a similar distribution of the economic factors related to the personal situation described above (Table 1, columns 11–14). We found that the salience of macro-economic hindering factors decreased with the rise of the number of children.

The lack of family policies and childcare services was cited by over one-third of the respondents. They referred both to the need for economic support for couples with children and the high cost, or complete lack of, childcare services. “The lack of services to families. The lack or high cost of day-care centers. Poor economic support for families and high taxes that have a very negative impact on family income” (male, 34). The references to lack of family policies were equally distributed among different parities, with a slight increase among respondents with two children (Table 3, columns 5–8). Some respondents reported how family policies are still dependent on the support of the family of origin. Indeed, as one respondent remarked: “Certainly, the subsidies for families in our country are not adequate to the needs. The real welfare is that of the maternal and paternal grandparents, still living and healthy, who give a big hand to the whole family system. Even this morning in order to take this test, one of the two children stayed at their grandparents' house. If I had had to find a babysitter, I would not have taken this test” (male, 31).

As with those of the personal situation, we also performed the analysis of the distribution of the macro-economic hindering factors across different groups of respondents for working conditions, education level, religiosity, and sex. The results (available upon request) showed no particularly different distribution of factors among these different groups.

We analyzed the enabling factors to fertility intentions within the sub-sample of respondents with a high level of fertility intentions (5–10). As with hindering factors, the economic factors were also prominent, but as enabling factors. While a precarious job was regarded as a significant obstacle, the presence of a stable job has the same, though beneficial, salience for positive fertility intentions (Table 4, columns 1 and 2). A stable job was considered necessary as it “enables [one] to support a family” (male, 37). A stable job with a sufficient income level is the economic prerequisite of childbearing. This was reported across different levels of education (Table 4, columns 6–8) and sex, with slightly higher male levels of importance to the presence of a positive economic situation (Table 4, columns 9 and 10).

Imaginaries are prominent drivers of fertility intentions. Table 5 reports the different dimensions and exemplary quotations of children and family imaginaries enabling fertility intentions. We classified them into three different groups: Imaginaries of children as a means, children as an end, and family as an end. Children as a means was the most reported group of imaginaries. Here, children were viewed as a means toward self-realization, the fulfillment of the couple/family, the joy of nurturing and educating children, a contribution to society, and a means to satisfy grandparents. Children as an end refers to children as the greatest joy, something always wanted, or the consequence of love. In the same vein, family as an end imaginaries see a family with children as a valuable outcome of the life-course. Both the children and family as an end imaginaries locate family and children as life goals which require no further justification.

Enabling imaginaries were distributed across different working conditions and education levels, with a slight predominance among the unemployed (Table 4, column 3), or less educated respondents (Table 4, column 6). Imaginaries were more often reported by religious than irreligious respondents (Table 4, columns 9 and 10), but they were differentiated by sex (Table 4, columns 11 and 12), or parity (Table 4, columns 13 and 14).

The quality of the relationship with the partner was the most reported meso-level enabling factor. “The serene and stable relationship I have with my partner” (female, 29). This factor was reported mostly by irreligious respondents, women, and the childless (Table 4, columns 9–14). The relationship with the partner and the children as an end imaginaries were more frequently reported by irreligious and religious respondents, respectively. One possible interpretation of this difference is that irreligious respondents afforded a greater salience to the quality of family relationships due to the absence of religious family goals. The partner's fertility intentions as enabling factors were reported only by men (Table 4 columns 11 and 12), while the support of the family of origin was reported more often by women (Table 4 columns 13 and 14).

We searched for the macro-economic enabling factors for fertility intentions in the answers to the related open question for the achieved capability group of respondents. However, we found no evidence of such country macro-economic enabling factors. Indeed, all the reported macro-economic factors were considered as obstacles.