Tempo and the TFR

Abstract

Tempo effects in period fertility indicators are widely regarded as a source of bias or distortion. But is this always the case? Whether tempo change results in bias depends, in the view advanced here, on the measure used, the meaning of bias/distortion, and the objective of analysis. Two ways of construing bias in period measures are suggested, and their relevance is discussed in the context of five broad purposes for measuring period fertility: describing and explaining fertility time trends, anticipating future prospects, providing input parameters for formal models, and communicating with nonspecialist audiences. Genuine timing effects are not biasing when period fertility is the explanandum but are distorting when the aim is to estimate cohort fertility. Alternatives to tempo adjustment are available that are a more defensible solution to the issue of timing change. Tempo adjustment could be more fruitfully considered a form of modeling rather than empirical measurement. The measurement of period fertility could be improved by relying more on a statistical approach and less on indicators based on stable assumptions. Future progress will depend on integrating research on measurement with substantive investigation.

Gender and fertility within the free churches in the Sundsvall region, Sweden, 1860–1921

“…Although the number of complete reproductive histories is low, as seen in Table 1, the longitudinal data combined with a reliable exit date allow us to calculate age-specific and total cohort fertility rates. For cohort TFR, the number of events (births) experienced within an age group is divided by the total exposure time "women-years at risk" (Bhrolcháin, 2011;Broström, 2014;Hinde, 1998). Marriage age is analysed using descriptive statistics, however because the birth and marriage cohorts were sampled using different methods, only internal comparisons are possible.…”

Future Fertility in Low Fertility Countries

“…The resulting tempo effect (or tempo distortion), which is the difference between the observed and hypothetical fertility in the absence of birth postponement, has become widely debated in the literature (Luy 2011;van Imhoff 2001, Schoen 2004Ní Bhrolcháin 2011) and has emerged as one of the key explanations for very low fertility levels observed in many rich societies Sobotka 2004b;Bongaarts and Sobotka 2012). A number of methods have been proposed to account for the tempo effect and compute tempo-adjusted period fertility rates (e.g., Bongaarts andFeeney 1998 andBongaarts and Sobotka 2012).…”

Ultra-low fertility in South Korea: The role of the tempo effect

“…Since then, demographers have discussed the usefulness and interpretation of tempo-adjusted indicators and developed other indicators aiming to calculate the period fertility rates free of the tempo effect and to address the shortcomings of the Bongaarts-Feeney method (e.g., Bongaarts and Feeney 2000;Kim and Schoen 2000;Zeng and Land 2001;Sobotka 2003;Schoen 2004;Ní Bhrolcháin 2011). These new indicators also addressed changing variance in fertility schedules by age and the effects of changes in the parity composition of the female population (Bongaarts and Feeney 2006;Bongaarts and Sobotka 2012;Kohler and Ortega 2002;Kohler and Philipov 2001;Pilipov and Kohler 2001;Yamaguchi and Beppu 2004).…”

“…The original Bongaarts-Feeney (1998) adjustment of period fertility was criticized by some researchers not only for its instability in time, but also for its underlying assumptions and lack of conceptual clarity (Schoen 2004;Ní Bhrolcháin 2011). Schoen (2004) advocated for the average cohort fertility (ACF), an alternative indicator of period fertility that controls for tempo changes.…”