Changes in the Quantum of Russian Fertility During the 1980s and Early 1990s

NICHOLAS B. BARKALOV

THE BREAKUP of the Soviet Union and the subsequent economic and political crises led to a rapid and sharp fertility decline in the Russian Federation. The conventional total fertility rate, computed by Russia’s official vital statistics branch, dropped from 2.00 births per woman in 1989 to 1.37 in 1993; the estimate for 2000 of 1.17 is the lowest national TFR ever recorded. The decline was particularly unexpected, as, during the 1980s, Russian natality had increased steadily, with the TFR by decade’s end exceeding the replacement level for the first time since the early 1960s.

As always when fertility falls so fast, suspicion arises that the drop was highly influenced by fertility tempo. This is the viewpoint of some leading Russian demographers. In fact, it has been alleged that the fall was solely a consequence of the age-and-birth-interval fertility schedule distorted by the fertility rise of the 1980s. According to Anatoly Vishnevsky,

The increase in the [conventional] total fertility rate by 0.4 children occurred in 1980–87, corresponding to an advance in the timing of implementation of family formation plans, by not less than 1–2 years, on average. This was followed by a fall, easily explained, in the rate of childbearing; the family formation plans had already been accomplished, and the total fertility rate declined between 1980 and 1993 by 0.5 children per woman. Thus, canceling each other out, the “positive” and “negative” impacts of the changes in the timing of childbearing under the influence of the family policy measures of the 1980s explain virtually the entire variation in the total fertility rate during the last decade. (Vishnevsky 1997: 84, my translation)

To control for the timing effect, I undertook to measure period fertility with an advanced measurement model, the PADTFR, which derives quantum measures from annual birth probabilities according to age, parity, and time elapsed since the previous birth.

Data and methods

Data

The data set for this study is a collection of maternity histories obtained from the Russian micro census of 1994. Scherbov and van Vianen (1999: 132–133) provide a description of this micro census. The enumeration of 7.35 million persons took place in mid-February 1994. This was intended as a 5 percent sample of the population of the Russian Federation, a goal that was essentially achieved. It is known that sample selection was based on the 1989 census, although the exact method of selection was not published. While 4.99 percent of the resident population was counted, it appears that young males (aged 18–19 years) were underenumerated and that older females (aged 60+) were somewhat over-represented. Apparently there was no significant bias regarding women of reproductive age.

The 1994 micro census covered nine substantive topics in 49 questions. Two topics are of relevance to this study: general demographic characteristics of women aged 15 years and older and their maternity histories. On the latter topic questions were asked on parity (number of live births) and date of each birth.

The sample used for this study consists of 2.8 million maternity histories of women aged 15–49 and 1.9 million records of women exposed to the risk of childbearing.

The 1994 micro census portrayed a Russian population of a somewhat different composition from that provided by the 1989 census. For the individual birth cohorts that had recently completed childbearing, a discontinuity was evident between the two data sets in terms of fertility patterns (detailed in Barkalov 1999: 14). Because Russia was not a closed population, in-migration from the former Soviet republics occurred during 1989–94. On average, immigrants had a relatively higher education, a greater proportion with urban background, and lower fertility than the native population. At the same time, out-migrants had higher than average fertility.1

Period parity-progression analysis, general

To study Russia’s fertility swings, I chose parity-progression analysis rather than age-based incidence rates (ASFRs and thus conventional TFRs) for two reasons. First, parity-progression analysis allows for more accurate measurement of the quantum of fertility because parity progression is dependent on past fertility behavior. Second, parity progression analysis is a study of “distributional aspects” (Feeney and Lutz 1991) of human fertility. That is, it studies distributions by completed fertility of either actual or synthetic cohorts, with emphasis on parity-progression ratios, dispersion measures, and extensions into decomposition techniques.

A parity-progression table provides a simple representation of the general approach. The table parallels a conventional life table, substituting r, the number of children ever born, for the time parameter of decrement, x. The cohort is initiated with all women having yet to bear any children.2

Period parity-progression analysis, refined

I use period estimators of the synthetic cohort rather than cohort measures because the phenomena of interest were too recent to employ completed fertility-cohort measures. And because my interest is in examining period effects that may be attributable to conditions reflecting recent changes in Russian society, I employ refined measures in order to eliminate the influence of the past.

Rallu and Toulemon (1994: 59–94) elaborate on three parity-based measurement models. The first rests on Whelpton’s model, describing parity advances depending on current parity attained and age (PA). The second, PD, is based on Henry’s model in which an increase in parity depends on current parity and the length of the open birth interval. Rallu and Toulemon present a third model, PAD, in which birth probabilities vary with parity, age, and duration since the last birth. This last, most comprehensive measure, requires a sample size of at least 40,000 maternity histories (in contrast to 10,000 for the other two methods). With sufficient sample size, the PAD method provides a better approximation to the synthetic cohort determined by the annual conditions by eliminating many past demographic trends.3

The PADTFR index is described by Rallu and Toulemon as a “complete synthetic measure of fertility.” It results from a multi-state life table (with states identified by current parity) under the condition that no more than a single transition in parity can occur within the same integer single-year age interval. Following the usual practice of multi-state life table estimation, the data from the micro census were partitioned by single-year age intervals, current parity, and length of the open birth interval. Central birth rates were equated to their empirical counterpart, the occurrence/exposure ratio. As soon as the parameters of the model were obtained, the derivation of period parity-progression ratios and the array of other indicators was straightforward.4

Results

My estimates are presented in Tables 1 and 2 and are shown in Figures 1 and 2. According to these estimates, the fertility rise of the 1980s was significant and the fall of the early 1990s was quite sharp, although not as steep as the conventional TFR suggests. I examine below whether these measured trends could be considered to be primarily due to the effects of distortions in the timing of fertility.

TABLE 1 Period parity-progression ratios and total fertility rates, Russia, 1978–93

The parity-progression pattern of the 1980s: Context and outcomes

Indirect estimates suggest that the parity-progression ratio toward a third child, p2, was steadily declining during the 1960s and 1970s (Barkalov 1999: 25). By the census year 1979, it reached 0.255 (Table 2). My PADTFR estimates based on the 1994 Micro Census showed a slight increase for the 1980s. The ratio rose to 0.356 by 1987 (Table 1), the year fertility peaked, but then resumed a downward trend. By the census year 1989, the parityprogression ratio p2 had dropped to 0.295. During the 1980s, the prevalence of higher order births was rather low, with few women having three or more children on completion of childbearing (Figure 2).

The 1980s witnessed an overall rise in fertility, especially with regard to the probability of a second child—parity-progression ratio p1. In my view, that rise was primarily attributable to the pronatalist measures undertaken at the beginning of the decade.

Traditionally pronatalist, the Russian government’s demographic policy had been strongly parity-specific, favoring higher order births. The decree of 22 January 1981 and consequent legislative acts shifted the emphasis of the policy to include women of lower parities, by introducing numerous benefits regardless of birth order. Critical, apparently, was the introduction (on top of a long fully paid maternity leave, then 16 weeks) of a post-maternity leave providing payment until the child reached one year of age. (At the time of its introduction this payment amounted to about 40 percent of the official minimum wage.) In addition, unpaid leave with job security was granted (then until age 1.5 years). A one-time lump-sum payment, previously available starting with the birth of a third child, was increased significantly and was also extended to all parities (Barkalov 1999: 26).

TABLE 2 Changes in the period fertility quantum (parity-progression pattern), Russia: Census years

NOTES: Shown in parentheses are standard (quadratic) errors of the estimates. Parity-progression ratio for the absorbing parity, 4, is the geometric average over parities above the absorbing one. Absorbing parity is the highest parity bounding a set of transition probabilities, analogous to transient and absorbing states in mortality analysis (see Elandt-Johnson and Johnson 1980: 426; Namboodiri and Suchindran 1987: 42). Parity-progression ratios and total fertility rates are equal to those presented in Table 1.

Moreover, the state demographic policy promoted childbearing not just directly by monetary, employment, and housing benefits, by access to virtually free public child-care facilities, and by extended paid post-maternity leaves, but also indirectly by conducting a comprehensive and often welltuned campaign that emphasized the state’s role as the ultimate guarantor for children’s well-being (though not necessarily for that of their parents), and touted the psychological and social-status benefits of childbearing.

FIGURE 1 Period parity-progression ratios, Russia, 1978–93

FIGURE 2 Parity-progression pattern and final parity distribution, Russia, 1989 and 1993

Socialist society promoted uniformity in family-building behavior, encouraging commitment to legal marriage and a stable family. In particular, nonfamilial living arrangements were discouraged, and indeed such arrangements were infrequent. Importantly, however, the state’s welfare system and demographic policy, direct and indirect alike, were focused on the child rather than on the family per se. It was made clear that childbearing was welcomed even when parents’ living arrangements fell far short of the model. This could not but substantially weaken the link between fertility behavior and marriage, especially with regard to giving birth to a first child. Notably, childbearing by single mothers received special protection from the state (just short of explicit support for the mother’s social standing), even though that was not consistent with the declared state preference for marital-life values.

Under the perceived stability of the socialist state, and given a wellestablished pronatalist environment, few women failed to become mothers. Nevertheless, progression to parities over one was not assured. The psychological gains from childbearing were not perceived to depend significantly on the number of children. Parental well-being actually declined with advancing parity (and age) as negative experiences from dealing with problems of child rearing mounted—not the least since the incidence of separation and divorce among couples with children was rising (described in UNDP 1997).

The level of childlessness in Russia, which had always been very low, declined further during the 1980s, approaching the biological limit of about 5 percent by 1989 (Table 2). However, giving birth to a second child showed greater (statistical) uncertainty in decisionmaking. The lifetime probability of having a second child rose significantly. The parity-progression ratio p1 increased from about 0.678 in 1979, to 0.754 in 1989, with a peak of 0.790 in 1987. The decomposition formula (Barkalov 1999: 53) attributes 67.3 percent of the change in total fertility (PADTFR) 1979–89 to the greater probability of the birth of a second child. By contrast, the probability of having a first child, p0, changed far less, accounting for only 22.1 percent of the overall (PADTFR) change in the fertility level (Table 1). Judging from the implied distribution by final parity, a two-child family was then the most prevalent. Its share reached 50.4 percent by the census year 1989 (Figure 2).

On the whole, the parity-progression pattern became slightly more homogeneous during the 1980s: the Gini mean difference in the final number of children between two randomly chosen women declined. Women who became mothers increased their lifetime fertility slightly less than all women. But in this period, the average number of siblings changed even less (Table 2).

The conventional (solely age-based) total fertility rates were somewhat overestimated in the 1980s (Table 1). Some tempo effects were operative: the interval between first and second births grew shorter, and the age at first birth declined. Computed conventionally for 1989, the lifetime probability of having a first birth, p0, exceeded 1.0 owing to the tempo effect. In essence, tempo effects were present, but of minor magnitude. In the larger picture, the change in the quantum of fertility was of major magnitude.

The fertility decline of the early 1990s: Context and outcomes

Numerous social, economic, and political forces resulted in the fall of the “Iron Curtain” in most socialist countries around 1990. The early 1990s brought about the demise of the socialist state in Russia. With the collapse of Soviet power, Russia lost overnight half of its population and about onefourth of its territory (US Census Bureau 2005), including areas rich in minerals (e.g., Central Asia) and agricultural resources (e.g., the Southern Caucuses), as well as a large part of the ancient Russian heartland (e.g., Ukraine). As noted by many observers, with the dissolution of the Soviet state the Russian people and the country’s economy suffered the worst setbacks during peacetime of any industrialized country in history. The national economy had already been in a crisis. With the dissolution of the state came misdirected technical assistance from foreign advisers and drastic economic decisions that provided “shock therapy.”5

The price liberalization of 1992 was launched with monopolistic economic structures still in place, unleashing hyper-inflationary pressure. In 1992 consumer and producer prices rose over 2,500 percent for the year; monthly inflation continued in double digits for several years. This inflation set in motion a number of mechanisms6 resulting in a drop in per capita income (in real terms) to 40 percent of its 1991 equivalent; expanded poverty (the main trade union body concluded that 80 percent of the population had fallen below the poverty line); great income inequality;7 the loss of lifetime savings by most people; and quite importantly, the disappearance of general as well as child support benefits.

With the collapse of the Soviet Union in late December 1991, Russians discovered that the entire fabric of social security that they had taken for granted for three generations was disintegrating. Those losses included: guaranteed lifetime employment and re-employment; protective labor laws that, for instance, on top of unlimited fully paid sick leave, gave annual multi-week fully paid vacations, and generous retirement benefits at no perceived out-of-pocket cost to working people; free housing and merely symbolically priced utilities; free education up to graduate school; and free health services (including doctors’ house calls).

These radical changes in personal and household well-being had major demographic ramifications. Male life expectancy had been increasing slowly over the preceding 30 years. The increase was one-tenth of that experienced globally during 1959–88. In the six year span 1988–94, life expectancy for all in Russia, and for males in particular, dropped sharply. Male life expectancy at birth fell by over seven years—from 64.8 to 57.5 years (Bennett, Bloom, and Ivanov 1998: 1922). The decrease in male life expectancy in this time period was linked to increased mortality among working- age males (see, e.g., Notzon et al. 1998)—a pattern with likely effects on fertility and, particularly, on family plans and formation. Increased mortality and morbidity resulted from “traditional” infections and parasitic diseases, such as typhus (which had virtually disappeared a hundred years ago), accidents (both industrial and domestic), and violent crimes. Tuberculosis showed a resurgence. The prevalence of sexually and intravenously transmitted diseases also rose markedly. And many of the male deaths were attributed to psychological stress and inability to adapt to the conditions that followed from the “shock therapy” reforms.

Taken together, these setbacks could not but affect reproductive behavior. Although the social welfare measures of the 1980s were still in place in the early 1990s, their impact had to be judged against substantially diminished overall money incomes and increased insecurity. Undoubtedly, the connotation of demographic policy was also altered. No longer were policy measures presented as encouraging childbearing. Instead, the government provided erratic welfare support for women and children and promoted freely chosen reproductive behavior (Barkalov 1999: 27). Women found themselves in greater insecurity, enduring unpaid wages, loss of many child benefits, and loss of housing and utility subsidies.

It is no wonder that fertility fell sharply—by one-fourth, or by an average of more than one-half child per woman, in four years. Childlessness increased to about 10 percent (Tables 1 and 2). Even more striking was the drop in the probability of the birth of a second child. Actually, the parityprogression ratio p1 began to decline between 1987 and 1988, with the launch of the “perestroika” campaign. By 1993, it had fallen below 0.5 (Tables 1 and 2). The one-child family became the most prevalent (45.5 percent), followed by the two-child family (37.2 percent), which had been prominent in the 1980s (Figure 2). The homogeneity of the completed parity distribution increased substantially (Table 2 and Figure 2). The lifetime probability of a third birth p2 had resumed its declining trend and fell as low as 0.165 by 1993. Maternal fertility declined less than total fertility, reflecting the increase in childlessness.

Once again, the component contributing most to the change was the parity-progression ratio to a second birth, p1. It accounted for about 60 percent of the overall fertility decline (PADTFR), while the incidence of childlessness remained moderate by Western standards.

The conventional TFR overestimated the changes in quantum. A longer birth interval to the second child, and older age at first birth had created a parity composition different from that of the synthetic cohort, which resulted in a lower TFR than the true period measure, obtained with the PADTFR. Hence, as in the 1980s, a tempo effect was present, but it was of minor magnitude in comparison to the major actual fertility decline.

Conclusion

The age–parity–birth interval standardized indicators presented above strongly suggest that the Russian fertility changes in the 1980s and 1990s were due far more to a quantum effect than to a tempo effect. In 20 years, the issue can be definitely settled when all cohorts involved have completed their childbearing years.

Notes

The author, N. B. Barkalov, died shortly after submitting the first draft of this article. His wife, Sharon Kirmeyer, of the Centers for Disease Control and Prevention, made the subsequent revisions.

1 The reader will note that the fertility increase of the 1980s quoted from A. G. Vishnevsky does not correspond to the conventional rates contained in Table 1. As a standard practice for comparing outcomes of paritybased measures, it is necessary to remove exogenous demographic influences (such as the selective migration noted above). Therefore, this study includes a series of conventionally calculated TFRs based solely on the 1994 micro census. A partition was established by age (single-year intervals) alone. The reduced numbers of births, specific to age- and birth-order, were equated to the respective age-specific fertility rates. The rates for the most recent years coincided well with official statistics. The discussion can hence proceed without the major disturbance factor of inter-censal migration.

2 The principal parity-progression functions and their life table counterparts are: lr [~lx], the parity attainment proportion; dr [~dx], the proportion at parity r at completed fertility; pr [~px], the parity-progression ratio; and hr [~ex], the expected number of children after r.

3 The refined period-progression methods have their own precise but arduously calculated measures of tempo: mean age at transitionand mean age at birth of children, described by Rallu and Touleman (1994: 71–72); mean closed birth interval (Barkalov 2004: 35); and quantum-tempo separation via fertility timing paths proposed for cohorts by Edelfsen (1981) and applied to period methods (see Barkalov 2004: 37–38). While it would be interesting to introduce into the discussion a quantum–tempo analysis in the manner of Bongaarts and Feeney (1998), its grounding in age-based incidence rates would introduce confusion in interpretation. For one thing, the mean age of childbearing at various parities varies substantially depending on whether the computation is carried out by conventional or by period-parity methods (Barkalov 2004: 77).

4 In addition to the parity-progression life table measures enumerated in note 2, other distributional measures may be calculated: The maternal TFR follows the observation that countries’ total fertility rates vary substantially owing to the proportion childless in a cohort. This rate is the mean number of children ever born to women who become mothers (Feeney and Lutz 1991). Empirical departures of this measure from the simple TFR may range from 0.0 to 1.0.

Preston (1976) transformed mothers’ cohorts by parity into the number of children born to their mothers. This switches the perspective to the children, making it possible to estimate the mean number of siblings. Obviously, there are on average more siblings than would be suggested by mothers’ average fertility rate, due to overrepresentation of births from large families.

The Gini mean difference, derived directly from parity-progression ratios, measures heterogeneity (or concentration) of the parity distribution. It gives half of the mean difference of completed fertility between two women. This provides a simple indicator to evaluate populations in terms of their parity dispersions. As shown, fertility levels have undergone significant changes in the past decades. To evaluate the impact of changing parity-progression ratios on a new overall fertility level, Barkalov (1999: 52–53) adapted Pollard’s (1988) decomposition technique to discrete analysis. Applying this decomposition, the difference between two total fertility rates is attributed to shares corresponding to each parityprogression ratio.

5 “The attempted ‘shock therapy’ reforms launched in January 1992 ushered in a period of economic decline of unprecedented proportions, after several years of stagnation and relatively modest decline” (UNDP 1997: 12).

6 For a detailed discussion of these economic outcomes, see UNDP (1997), which states the following:

The growth [of poverty and inequality] has had many causes. They include the slump in national income and production, the process of unemployment in its various guises, the non-payment or partial payment of contractual wages and state transfers, the erosion of enterprise benefits, the inadequate development of a system of social protection, and the very high level of price inflation, which contributed to wiping out savings. (UNDP 1997: 21)

7 Of the 36 countries of Europe in the mid-1990s (including countries of the European portion of the former Soviet Union), Russia had the greatest income inequality, as reflected by: — the highest Gini index (i.e., furthest from perfect equality): 48.7; — the smallest income share to the poorest 20% of the population (4.4 percent); and — the highest income share to the richest 20 percent (53.7 percent). (World Bank 2002)

References

• Barkalov, Nicholas B. 1999. “The fertility decline in Russia, 1989–1996: A view with period parity-progression ratios,” Genus 55(3-4): 11–60.
• ———. 2004. Parity: A Brief Introduction to Formal Demographic Fertility Analysis. Research Triangle Park, NC: Research Triangle Institute; and Moscow: TEIS.
• Bennett, Neil G., David E. Bloom, and Serguey F. Ivanov. 1998. “Demographic implications of the Russian mortality crisis,” World Development 26(11): 1921–1937.
• Bongaarts, John and Griffith Feeney. 1998. “On the quantum and tempo of fertility,” Population and Development Review 24(2): 271–291.
• Edelfsen, I. E. 1981. “An investigation of the timing pattern of childbearing,” Population Studies 35(3): 375–385.
• Elandt-Johnson, Regina C. and Norman L. Johnson. 1980. Survival Models and Data Analysis. New York: Wiley.
• Feeney, Griffith and Wolfgang Lutz. 1991. “Distribution analysis of period fertility,” in W. Lutz (ed.), Future Demographic Trends in Europe and North America: What Can We Assume Today? London: Academic Press, pp. 169–195.
• Namboodiri, N. Krishnan and C. M. Suchindran. 1987. Life Table Techniques and Their Applications. Orlando: Academic Press.
• Notzon, F. C. et al. 1998. “Causes of declining life expectancy in Russia,” Journal of the American Medical Association 279(10): 793–800.
• Pollard, John H. 1988. “On the decomposition of changes in expectation of life and differentials in life expectancy,” Demography 25(2): 265–276.
• Preston, Samuel H. 1976. “Family sizes of children and family sizes of women,” Demography 13(1): 105–114.
• Rallu, Jean-Louis and Laurent Toulemon. 1994. “Period fertility measures: The construction of different indices and their application to France, 1946–89,” Population: An English Selection 6: 59–94.
• Scherbov, Sergei and Harrie van Vianen. 1999. “Marital and fertility careers of Russian women born between 1910 and 1934,” Population and Development Review 25(1): 129–143. United Nations Development Programme (UNDP). 1997. Human Development Report 1996. Russian Federation. Moscow: Academia.
• United States Census Bureau. 2005. International Data Base. Accessed July 2005, «http://www. census.gov».
• Vishnevsky, Anatoly G. (ed.). 1997. The Population of Russia, 1996. Moscow. (In Russian.) World Bank. 2002. World Development Indicators, 2002. Washington, DC: World Bank.

(c) POPULATION AND DEVELOPMENT REVIEW 31(3): 545–556 (SEPTEMBER 2005) Uploaded with the permission of the Editor

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