The Flexibility of Fertility Preferences in a Context of Uncertainty

From Ryder's (1973) “cloudy future” to Lee's (1980) “moving target,” the malleable nature of fertility preferences is widely accepted; however, tools for conceptualizing and measuring preferences have been slow to evolve. In this article, we seek to demonstrate that underpinning the number people give when asked about their ideal family size, and critical to interpreting it, is either a rigidness or a flexibility that is contextually situated and dynamic over the life course. To illustrate the difference between fixed and flexible orientations to fertility, we draw upon the metaphor of a movable feast. While some religious holidays like Christmas and All Souls Day occur annually on fixed days, others like Passover, Easter, and Pentecost change from year to year depending upon the lunar cycle or other ecclesiastical dates. From the perspective of the Gregorian calendar, movable feasts seem irregular, unpredictable, and sometimes merely seasonal. But movable feasts are no less regular than fixed feasts, nor are they of secondary importance; they differ in being governed by a distinct, flexible logic. Like many major religious feasts, some people's fertility preferences are indeed fixed, but it is the movable ones we endeavor to theorize here. Our interest in flexibility is anchored in two recent empirical and theoretical developments in the demographic literature. First, although instability in fertility preferences is higher in developing contexts than in the West (Bankole and Westoff 1995; Kodzi, Johnson, and Casterline 2010), new evidence suggests that this preference instability is not simply random noise but frequently patterned. In Malawi, for example, the setting of our present study, women change their numeric and timing preferences in response to changes in their relationships (divorce, widowhood, new marriage) and reproductive circumstances (pregnancies and child mortality) (Sennott and Yeatman 2012; Yeatman, Sennott, and Culpepper 2013). Furthermore, instability itself has predictive power with respect to short-term fertility outcomes (Kodzi et al. 2010). Second, scholars have developed more theoretically sophisticated ways of thinking about fertility. The Theory of Conjunctural Action (TCA) (Johnson-Hanks et al. 2011) critiques theories of fertility that reduce it to planned action because they rely on assumptions of clarity about a predictable, imagined future. Such an idealized view of reality is difficult or impossible to reconcile with the messiness of real lives, in which young adults lack “definite knowledge about their future family formation, education, and career paths, and so are likely to form their fertility intentions based on general social norms rather than specific desires” (Hayford 2009: 767). Fertility preferences, therefore, should only rarely be treated as a fixed statement of a feasible plan, and researchers should expect fertility behaviors to respond to contingencies, inputs, and shifts that occur at the micro and macro levels. Despite widespread agreement on these points, how can demographers go about integrating notions of flexibility into empirical research on fertility? Our interest in the nature of flexibility is further motivated by the puzzle of fertility transition in sub-Saharan Africa. The shape of the African fertility transition is distinct from the patterns of decline that characterized Latin America and Asia during the second half of the twentieth century (Bongaarts and Casterline 2013; Casterline and El-Zeini 2007). The debate about whether Africa's fertility transition is late, stalled, or simply different is ongoing (Bongaarts 2017; Bongaarts and Casterline 2013; Caldwell and Caldwell 2002; Caldwell, Orubuloye, and Caldwell 1992; Casterline and Agyei-Mensah 2017; Mbacké 1994; Moultrie, Sayi, and Timæus 2012; Shapiro and Gebreselassie 2008; Smith 2004). Despite differing in their views of the nature of the transition, scholars agree that fertility preferences play a central role in the transition and in our capacity to develop a better understanding of it. Fertility preferences are critical because, in the words of Bongaarts and Casterline (2013: 159), they “represent a key link in the chain of causation between fertility and its socioeconomic determinants.” Questions about the nature of fertility preferences raise especially challenging issues for researchers working in sub-Saharan contexts. While some researchers maintain that fertility rates in sub-Saharan Africa remain high precisely because desired fertility has remained high (Bongaarts 2006; Bongaarts and Casterline 2013; Pritchett 1994), others read the evidence differently. Günther and Harttgen (2016), for example, document that across the region realized fertility has exceeded wanted fertility by two children for more than two decades. They interpret this gap as evidence that African women are less capable of translating child preferences into outcomes than are women in other developing contexts. An extensive literature on fertility in sub-Saharan Africa attributes the observed gaps between preferences and completed fertility to “unmet contraceptive need” (Bankole and Ezeh 1999; Bongaarts 1991; Frank and Bongaarts 1991; Sedgh and Hussain 2014). Complicating this interpretation are three factors: i) the important but often neglected caution against inferring individual intentions from population rates (Johnson-Hanks 2007); ii) the weak relationship between family planning programs and fertility reduction (Günther and Harttgen 2016); and iii) new evidence that unrealized fertility is far more prevalent in this region than previously recognized. Recent estimates from individual-level analyses reveal that despite high levels of fertility in sub-Saharan Africa, as many as 46 percent of African women fall short of their ideal at the end of childbearing (Casterline and Han 2017). Other common explanations for the fact that preferences and behaviors tend to be misaligned in sub-Saharan Africa include poor data quality (Dare and Cleland 1994), poor construct validity (Bankole 1995), and the possibility that reproductive decisions remain outside the calculus of conscious choice (Coale 1973; van de Walle 1992). To readers familiar with recent developments in the methods and materials of demography, the limits of these explanations are apparent. While concerns about data quality are valid, data availability (if not quality) has been improving, and statistical methods for treating preferences as dynamic processes have advanced considerably. Non-numeric responses to questions about fertility desires such as “Don't know” and “Up to God” have declined (Frye and Bachan 2017), suggesting that the vast majority of women think numerically about the future with respect to their families. Whereas the presence of some uncertainty about one's future is universal, most high-fertility societies are characterized by rampant uncertainty, and scholars from various disciplines have argued that flexibility is a strategic response to the many uncertainties of life in the African context. The connection between uncertainty and flexibility has been elaborated by scholars of rural livelihoods working among Kenyan pastoralists (Butt 2011), Yoruba cacao farmers (Berry 1993), and Mandara Mountain dwellers (Lev and Campbell 1987). In settings where “no condition is permanent” (Berry 1993), flexibility in everything from the selection of land and crops to the timing of labor for planting and harvest is crucial to survival in both the short and long term. Similarly, flexibility in childbearing is a strategic response to life's uncertainties. Describing the landscape of her research site, Johnson-Hanks (2005: 364) underscored the exceptionally high levels of existential and economic uncertainty. “Life in contemporary Cameroon is extremely uncertain, both in the specific sense that death often comes early and unexpectedly and also more generally: few events in everyday experience are predictable or consistent. From buses to paychecks to roadblocks to prices, common things elude standardization.” Where day-to-day life is riddled with uncertainties, being flexible about all sorts of things-including childbearing (how much and when)-is a necessity (Johnson-Hanks 2005). Posited as an alternative to rational-choice perspectives on action, the notion of “judicious opportunism” captures the ease with which individuals can withdraw from their prior intentions (intentions that were real when articulated) by seizing opportunities to reach desirable ends rather than struggling against tides to manifest a fixed and actionable plan. According to Johnson-Hanks, judicious opportunism is found not just in Cameroon but wherever the usual supports for rational choice are wobbly. And while the flexibility that judicious opportunism requires may look, on the surface, like “just waiting” or like indecision or inaction, flexibility is distinct from these responses in that it is strategic. Examples of uncertainty and its relationship to fertility abound; here we point to two additional examples-one emphasizing the existential and the other the economic. Extending the literature on insurance or replacement effects on fertility (Cain 1981; Caldwell et al. 1992; LeGrand et al. 2003; Randall and LeGrand 2003), Sandberg (2006) used network data from an agrarian community in Nepal to demonstrate that uncertainty about child survival (proxied by high levels of infant mortality within a network of conversational partners) accelerated and increased women's fertility. Using qualitative data from peri-urban Mozambique, Agadjanian (2005) looked not to the graveyard but to the market, arguing that stated fertility desires are conditional on current economic and social circumstances and that reproductive aspirations (especially at lower parities) should be treated as tentative because they are shaped by assessments of an unknowable future. While Agadjanian acknowledged the persistent poverty that characterizes much of his study population, he emphasized not the poverty itself but “the unpredictability of the economic situation” (2005: 625), including structural factors like labor market opportunities and intimate conjunctures like spousal migration and relationship strain. Because the data demands for examining preference change are high, most evidence comes from the data-rich West (Hayford 2009; Heiland, Prskawetz, and Sanderson 2008; Iacovou and Tavares 2011; Liefbroer 2009; Udry 1983); however, the evidentiary basis from Africa is growing (e.g., Kodzi et al. 2010; Yeatman et al. 2013). The roots of this literature on preference change can be found in theories about the impact of child mortality, post-hoc rationalization, and household bargaining, but new research shows that other types of events provide change as well. In our context of Malawi, a wide array of conjunctures is known to affect both the number of children a woman wants and will subsequently have and the timing of those pregnancies and births. Confirmed or suspected HIV infection, for example, leads women to accelerate their childbearing plans in order to achieve their ideal family size while still in good health (Trinitapoli and Yeatman 2011), while caregiving responsibilities for non-biological children (fostering) often lead women to reduce their numeric preferences and delay their childbearing (Bachan 2015). Labor market opportunities may lead women to adjust their timing preferences (Sennott and Yeatman 2012), while expectations that any serious relationship would be solidified through offspring mean that partnership changes in the wake of death or divorce tend to increase desired fertility (Verheijen 2013; Yeatman et al. 2013). In sum, fertility preferences are contingent and are unstable over time in ways that are patterned. What remains less clear is whether and to what extent strategic flexibility i) varies with perceptions and experiences of uncertainty, ii) may help account for the high levels of preference instability observed in sub-Saharan Africa, and iii) helps explain a unique pattern of fertility-related behaviors and outcomes. Reflecting on his experience directing the US National Fertility Study (NFS), Ryder likened the task of asking American respondents to identify their optimal reproductive target to “asking the respondent to perform a complex conceptual experiment: ‘If everything else in your life were to remain the same, except for your parity, what would you choose for your parity?’” He continued, “I suspect that respondents, faced with this challenge, can scarcely avoid thinking of other things they would like to change in addition to the number of children, such as their health, or their housing, or perhaps their husband, unless, of course, they reject the game altogether and converge on their actual experience” (Ryder 1973: 504). When researchers ask questions such as “If you could have exactly the number of children you want, what number would that be?,” women almost always answer clearly, providing a single number. However, underpinning these numbers are processes that are messy to model but central to understanding fertility preferences and what they do (and do not) tell us. During the heyday of research on fertility preferences, several scholars sought to supplement best-practice measures of ideal family size (IFS) with new constructs that could tap, prospectively, an underlying structure that would tell us more. For example, Coombs advanced both theory and measurement related to fertility preferences, employing the metaphor of preferences unfolding around a personal ideal (the target). She codified this metaphor in a set of preference scales that were part of a broader endeavor to generate more valid, sensitive, and refined measures of preferences: “[I]f we are to explore in more precise fashion than heretofore the antecedents and correlates of preferences, measures beyond global statements about preferred numbers provide valuable tools” (Coombs 1974: 609). Coombs-authored preference scales force respondents to move a beyond their initial target to reveal underlying preferences. To describe her “unfolding theory” of fertility, Coombs began with an exercise that moved respondents to either end of a constrained spectrum of ideal family size: “‘If you couldn't have ___ (number given) would you rather have __ (lower number) or __ (higher number)?’ and so on until the respondent chose zero or six” (1974: 588-89). Today, the most widespread adaptation of the Coombs scale forces respondents to choose second and third preferences, which enables analysts to identify women's underlying preference for a small or a large family but masks variability in movement up and down the IFS spectrum by constraining the amount of variation within each sample to two shifts per person. Concerned primarily with the instability of fertility preferences over the life course, Morgan (1981) built upon Coombs's insights, offering a simple but elegant alternative. Leveraging changes in preferences observed among American women from the National Fertility Studies conducted in 1965 and 1970, he insisted: “This uncertainty is not ‘noise’ in the data that should be ignored, discarded, or removed by some post hoc coding procedure. Rather, it is a real phenomenon inherently part of fertility decision making” (Morgan 1981: 268). The 1965 NFS asked those respondents who indicated their intention to have more children, “Do you think you might later change your minds and decide not to have another child?” And it asked respondents who indicated the intention to stop, “Do you think you might later decide to have another child?” Learning that 7 percent did not know their intentions to begin with, 13 percent were uncertain of their intention to stop, and 50 percent were uncertain of their stated intention to have more, Morgan commented that these high levels of inconsistency between intentions and behaviors were “not surprising” (p. 280). Morgan's work pointed to flexibility as an inherent part of fertility intentions, worthy of further theoretical and empirical attention. But despite the fact that these two simple questions actually did, to some extent, index individuals’ willingness to revise their preferences, such questions are rarely used by researchers today and are seldom asked outside of the West. Like Coombs, we believe that a structure underlies each person's stated ideal. However, rather than conceptualizing this structure numerically, as a type of statistical uncertainty, we focus on the level of flexibility that characterizes individual preferences. By flexibility we mean the extent to which preferences are designed to shift in the wake of the evolving contingencies. We posit that flexibility is measurable and intrinsically linked to fertility preferences and that measuring the prevalence of and variation in flexibility can increase understanding of fertility processes broadly. When viewing world fertility patterns from a fixed-feasts perspective, an unacceptably large proportion of fertility preferences appear unstable, invalid, unpredictable, and untrustworthy; we argue here that for large portions of the world's population, this instability is not an anomaly to be corrected for, but, like movable feasts, an essential aspect of their nature. The data for our study come from Tsogolo la Thanzi (TLT), a longitudinal study conducted in Balaka, Malawi designed to examine how, in the context of a generalized AIDS epidemic, young adults navigate the sometimes incompatible goals of enjoying sexual relationships, bearing children, and avoiding HIV infection. Balaka is a bustling township located in Malawi's southern region at the crossroads between a major road linking the country's political capital (Lilongwe) with its cultural capital (Zomba) and the rail route that ferries goods between Salima and Blantyre. The common refrain “In Balaka, every day is market day” attests to the vibrancy of this rapidly growing trading other of the setting in which we examine young fertility goals in the context of broader First, the economic Balaka are Despite the southern Malawi is than the of the The southern region lower levels of and higher levels of poverty than the and central 2010). of Balaka are is just and in only percent of to Second, of the southern region has the country's most AIDS in percent of the population in the southern region with to percent in the central and 7 percent in the region In perspective, might be as but HIV prevalence in Malawi's southern at percent in has to percent but remains as high as prevalence in Recent for include a decline in new to and mortality Despite these however, the has widespread a proportion of the population is of their current HIV and about future is for the vast majority of young adults and 2010; and Yeatman 2011; 2004). the transition to women around for the time about a year and give to their child about a year that et al. 2009; and 2009; 2007). The of data for between and simple random sample of respondents from a of to year in within a of The a of rural and peri-urban around the trading respondents in their and a time for an to the research to the market, and were in where their responses could not be by family and at the time of an and by not up were percent of and respondents completed a of data were from this of women through with at the response at In a of data from the sample of an percent response The of all measures and the of the sample at respondents in from to with a mean of in within the is by a of from the of of respondents been or were percent of the sample at and percent of women a or child about half the sample no children, while others or children at In to van de respondents from three young women in Balaka no numeric responses to questions about ideal family two to respond to our about IFS by a number. family size from to children, with a mean of By percent at child and mean Our two key measures of fertility preferences are ideal family size numeric and ideal time to timing To we often do not have exactly the number of children they to you could have exactly the number of children you want, how many children would you to for ideal time to from as to or more these we to the flexibility of preferences. asked each respondent how would respond to each of events and with that occur in Malawi death of a relationship would her preference for the number of children stated or the the her desired timing no Questions in the flexibility were asked during the and in factors including household from the household goods and and the calculus of conscious in three i) a of respondents were asked to simple ii) a of planning for the future at do you think about or for your with and iii) a of agreement with the statement on children, they just and measures designed to existential uncertainty. The women who in their and childbearing a or the death of a The second experience of death in the network by the number of in the The third each sense of mortality an in which respondents are a of and asked to shift from to another the number of the a will occur within a time the will zero it will and a We the of HIV the the number of that how likely it is that you will within a has been used in a of cultural contexts to generate assessments of child mortality, HIV and mortality and 2011; and 2009; and 2011; and Yeatman we the extent to which preferences, and outcomes by level of We by the relationship between flexibility at and observed instability in IFS over the We further whether flexibility fertility-related behaviors of and outcomes and we flexibility in this of women a dynamic view of flexibility with a dynamic view of fertility preferences us to between explanations and perspectives on flexibility that view it as part of a to a more on the of which respondents indicated in whether and how they would adjust their fertility preferences. We our into three factors (the in the economic and family respondents indicated movement in fertility preferences on of the for both their desired number of children and the desired timing of While percent of young women in Balaka no movement in their numeric preferences for any of the percent a change for every of the to respect to timing preferences, percent no and percent movement in response to every condition we of flexibility among women in Balaka, shows from most fixed to most Tsogolo la For 13 in including all of the economic (e.g., the new to the of children more a in the of and most related to family such as the or death of a less than 50 percent of the sample that they would respond by their fertility in number or Our data provide no evidence of preferences of although more than of women a clear for a household by they would more children they only or only few however, appear to change for a majority of the the that numeric and timing changes for the are two AIDS for or your to and two for which AIDS is of a and children a The other most condition is one's respect to timing preferences, are the only that lead a of respondents to they would accelerate their all other tend to While percent of women that they would children they of an percent that they would have their children as a for the relationship or children with HIV and 2012; and Yeatman To we respondents who from those who a likely change or for each to of For each we responses to all to her level of flexibility in a simple The analyses that primarily on this which from to we such as a examining numeric flexibility only or a in which the flexibility is into in In over percent of the sample indicated some with almost percent more than likely changes in response to the questions about the ways in which flexibility is patterned. flexibility level to social it the of we for other fertility-related

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• Covid-19 and Childlessness among Women in the United States

  Open Access•H Hummer•Population and Development Review•2024

  Añadir item

• Fertility Desires and Contraceptive Transition

  Open Access•Sara Yeatman, Christie Sennott•Population and Development Review•2024

  Añadir item

• Fertility Intentions During the Covid-19 Pandemic

  Open Access•L J Marteleto, Neha Kumar et al.•Population and Development Review•2024

  Añadir item

• Change in Fertility Intentions in the First Year of Covid-19

  Open Access•Linnea A Zimmerman, Cary Karp et al.•Population and Development Review•2024

  Añadir item

• Housework, Gender Role Attitudes, and Couples' Fertility Intentions

  Open Access•Barbara S Okun, Liat Raz‐yurovich et al.•Population and Development Review•2019

  Añadir item

• Periods of high uncertainty

  Open Access•Elena Vakulenko, Dmitriy Gorskiy et al.•Demographic Research•2025

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• Advanced or postponed motherhood? Migrants' and natives' gap between ideal and actual age at first birth in Spain

  Open Access•Xiana Bueno, Mariona Lozano et al.•Demographic Research•2023

  Añadir item

• Accuracy of wives' proxy reports of husbands' fertility preferences in sub-Saharan Africa

  Open Access•Dana Sarnak, Dana O Sarnak et al.•Demographic Research•2022

  Añadir item

• An investigation of Jordan's fertility stall and resumed decline

  Open Access•C Krafft, Elizabeth Kula et al.•Demographic Research•2021

  Añadir item

• Women's health decline following (some) unintended births

  Open Access•Sara Yeatman, Emily Smith-Greenaway•Demographic Research•2021

  Añadir item

• Visualizing Young Men's Fertility Desires

  Open Access•J Trinitapoli, Abdallah Chilungo et al.•Socius Sociological Research for…•2022

  Añadir item

• Motherhood myths and mystiques

  Open Access•H Hummer•Journal of Marriage and the Family•2024

  Añadir item

• The Paradox of Planning

  Open Access•Catherine Bolten, Richard Marcantonio•African Studies Review•2021

  Añadir item

• Understanding Family Change and Variation

  Open Access•Jennifer Johnson‐Hanks, Jennifer A Johnson-Hanks et al.•Understanding Family Change and…•2011

  Añadir item

• Plotting Regression Coefficients and other Estimates

  Open Access•Ben Jann•The Stata Journal: Promoting…•2014

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• No Condition Is Permanent

  Sara S Berry, Sara Berry•No Condition Is Permanent•1993

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• Will HIV become a major determinant of fertility in Sub‐Saharan Africa

  Sarah Gregson, Simon Gregson•The Journal of Development Studies•1994

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• Stability and Change in Fertility Preferences Among Young Women in Malawi

  Christie Sennott, Sara Yeatman•International Perspectives on…•2012

  Añadir item

• Measuring subjective expectations in developing countries

  Open Access•Adeline Delavande, Xavier Giné et al.•Journal of Development Economics•2011

  Añadir item

• Reproductive Strategies and Decisions in Senegal

  Open Access•Sara Randall, Thomas Legrand•Population (English Edition•2003

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• The temporal dimension in farming systems research

  Open Access•Larry Lev, David J Campbell•Journal of Rural Studies•1987

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• Changes in Family Size Intentions Across Young Adulthood

  Open Access•Aart C Liefbroer•European Journal of Population /…•2009

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• Are Individuals’ Desired Family Sizes Stable? Evidence from West German Panel Data

  Open Access•Frank Heiland, Alexia Prskawetz et al.•European Journal of Population /…•2008

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• Fraught with Ambivalence

  Open Access•Victor Agadjanian•Population Research and Policy…•2005

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• Unmet need for couples

  Open Access•Akinrinola Bankole, Alex Chika Ezeh et al.•Population Research and Policy…•1999

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• Do couples make fertility plans one birth at a time

  Open Access•J Richard Udry•Demography•1983

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• Men matter

  Open Access•F Nii-Amoo Dodoo, F Nii‐amoo Dodoo•Demography•1998

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• Desired Fertility and Number of Children Born Across Time and Space

  Open Access•Isabel Günther, Kenneth Harttgen•Demography•2016

  Añadir item

• A critique of the national fertility study

  Open Access•Norman B Ryder•Demography•1973

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• Fertility transition, conscious choice, and numeracy

  Open Access•Etienne Van De Walle•Demography•1992

  Añadir item

• Intention and Uncertainty at Later Stages of Childbearing

  Open Access•S Philip Morgan•Demography•1981

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• The estimation of Unwanted Fertility

  Open Access•John B Casterline, Laila O El‐Zeini et al.•Demography•2007

  Añadir item

• Differential Survival in Europe and the United States

  Open Access•Adeline Delavande, Susann Rohwedder•Demography•2011

  Añadir item

• Young Women’s Dynamic Family Size Preferences in the Context of Transitioning Fertility

  Open Access•Sara Yeatman, Christie Sennott et al.•Demography•2013

  Añadir item

• The Measurement of Family Size Preferences and Subsequent Fertility

  Open Access•Lolagene C Coombs•Demography•1974

  Añadir item

• The influence of network mortality experience on nonnumeric response concerning expected family size

  Open Access•John Sandberg•Demography•2005

  Añadir item

• The evolution of fertility expectations over the life course

  Open Access•Sarah R Hayford•Demography•2009

  Añadir item

• Now or Never

  Open Access•Sarah R Hayford, Victor Agadjanian et al.•Studies in Family Planning•2012

  Añadir item

• HIV Infection and Fertility Preferences in Rural Malawi

  Open Access•Sara Yeatman•Studies in Family Planning•2009

  Añadir item

• Fertility Levels, Trends, and Differentials in Sub-Saharan Africa in the 1980s and 1990s

  Dudley Kirk, Devin Kirk et al.•Studies in Family Planning•1998

  Añadir item

• The Relationship between Partners' Family‐Size Preferences in Southern Malawi

  Open Access•Sara Yeatman, Christie Sennott•Studies in Family Planning•2014

  Añadir item

• An Economic Framework for Fertility Analysis

  Richard A Easterlin•Studies in Family Planning•1975

  Añadir item

• Reasons for Contraceptive Nonuse among Women Having Unmet Need for Contraception in Developing Countries

  Open Access•Gilda Sedgh, Rubina Hussain•Studies in Family Planning•2014

  Añadir item

• Reproductive Preferences and Fertility Trends in Post-transition Thailand

  John Knodel, Vipan Prachuabmoh Ruffolo et al.•Studies in Family Planning•1996

  Añadir item

• The Causes of Stalling Fertility Transitions

  Open Access•John Bongaarts•Studies in Family Planning•2006

  Añadir item

• Africa

  Open Access•John C Caldwell, Pat Caldwell•Studies in Family Planning•2002

  Añadir item

• Navigating the Aids Epidemic in Rural Malawi

  Open Access•Susan Watkins, Susan Cotts Watkins•Population and Development Review•2004

  Añadir item

• Coping with Uncertainty and Variability

  Open Access•Bilal Butt•Human Ecology•2011

  Añadir item

• Natural Intentions

  Jennifer Johnson‐hank, Jennifer Johnson‐Hanks•American Journal of Sociology•2007

  Añadir item

• Infant Mortality, Social Networks, and Subsequent Fertility

  Open Access•John Sandberg•American Sociological Review•2006

  Añadir item

• Fertility Desires and the Course of Fertility Decline in sub-Saharan Africa

  Open Access•John B Casterline, Samuel Agyei‐mensah•Population and Development Review•2017

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• Preference scales for number and sex of Children

  Clyde H Coombs, Lolagene C Coombs et al.•Population Studies•1975

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• On the Social Control of Human Reproduction

  Ron Lesthaeghe•Population and Development Review•1980

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• Aiming at a moving target

  Ronald D Lee•Population Studies•1980

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• Risk and Insurance

  Mead Cain•Population and Development Review•1981

  Añadir item

• Sex, money, and premarital partnerships in southern Malawi

  Open Access•Michelle Poulin•Social Science & Medicine•2007

  Añadir item

• Uncertainty and Fertility in a Generalized Aids Epidemic

  Open Access•J Trinitapoli, Sara Yeatman•American Sociological Review•2011

  Añadir item

• Social Structure and Fertility

  Kingsley Davis, Judith Blake•Economic Development and Cultural…•1956

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• Birth intervals, postponement, and fertility decline in Africa

  Tom A Moultrie, Takudzwa S Sayi et al.•Population Studies•2012

  Añadir item

• Desired Fertility and Fertility Behaviour among the Yoruba of Nigeria

  Akinrinola Bankole•Population Studies•1995

  Añadir item

• The demography of words

  M Frye, Lauren Bachan•Population Studies•2017

  Añadir item

• Contradictions in Nigeria's Fertility Transition

  Open Access•Daniel Jordan Smith•Population and Development Review•2004

  Añadir item

• Yearning, Learning, and Conceding

  Open Access•Maria Iacovou, 忠信 合屋 et al.•Population and Development Review•2011

  Añadir item

• Fertility Transition

  Open Access•John Bongaarts, John B Casterline et al.•Population and Development Review•2013

  Añadir item

• Desired Fertility and the Impact of Population Policies

  Lant Pritchett, Lant H Pritchett•Population and Development Review•1994

  Añadir item

• On Postponement and Birth Intervals

  Open Access•Ian M Timaeus, Tom A Moultrie•Population and Development Review•2008

  Añadir item

• Africa's Unique Fertility Transition

  Open Access•John Bongaarts•Population and Development Review•2017

  Añadir item

• Mass Education as a Determinant of the Timing of Fertility Decline

  John C Caldwell•Population and Development Review•1980

  Añadir item

• Fertility Decline in Africa

  John C Caldwell, I O Orubuloye et al.•Population and Development Review•1992

  Añadir item

• The Proximate Determinants of Fertility in Sub-Saharan Africa

  John Bongaarts, Odile Frank et al.•Population and Development Review•1984

  Añadir item

• Reproductive Mishaps and Western Contraception

  Caroline Bledsoe, Fatoumatta Banja et al.•Population and Development Review•1998

  Añadir item

• A Framework for Analyzing the Proximate Determinants of Fertility

  John Bongaarts•Population and Development Review•1978

  Añadir item

• Reassessing the Insurance Effect

  Open Access•Thomas Legrand, Todd Koppenhaver et al.•Population and Development Review•2003

  Añadir item

• The KAP-Gap and the Unmet Need for Contraception

  John Bongaarts•Population and Development Review•1991

  Añadir item

• Family Planning Programs and Fertility Transition in sub-Saharan Africa

  Cheikh Mbacke, National Research Council•Population and Development Review•1994

  Añadir item

• Stratégies reproductives et prise de décision au Sénégal

  Open Access•Sara Randall, Thomas Legrand et al.•Population•2003

  Añadir item

• Unrealized fertility

  Open Access•John B Casterline, John Casterline et al.•Demographic Research•2017

  Añadir item

• Asking God about the date you will die

  Open Access•A Kaler, Susan Watkins•Demographic Research•2010

  Añadir item

• Examining the predictive value of fertility preferences among Ghanaian women

  Open Access•Ivy Kodzi, David Read Johnson et al.•Demographic Research•2010

  Añadir item

• Subjective expectations in the context of HIV/Aids in Malawi

  Open Access•Adeline Delavande, Hans‐peter Kohler et al.•Demographic Research•2009

  Añadir item

• Concepts and Operationalisation of Reproductive Decisions Implementation in Austria, Germany and Switzerland

  Open Access•Dimiter Philipov, L Bernardi•Comparative Population Studies•2012

  Añadir item

• Marital Aspirations, Sexual Behaviors, and HIV/Aids in Rural Malawi

  Open Access•Shelley Clark, Michelle Poulin et al.•Journal of Marriage and the Family•2009

  Añadir item

• When the Future Decides

  Jennifer Johnson‐hank, Jennifer Johnson‐Hanks•Current Anthropology•2005

  Añadir item