ISSN (Print) - 0012-9976 | ISSN (Online) - 2349-8846

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Short- and Long-run Dynamics of Total Fertility Rate in West Bengal

An ARDL Bounds Co-integration Approach

Despite India achieving sub-replacement fertility and projecting stable future population growth, there exist significant variations in the total fertility rate among its states. One such state, West Bengal, exhibits a concerning TFR of 1.4, posing a threat to sustainable population growth. This research paper aims to identify the determinants contributing to the declining TFR in West Bengal. Our study reveals that while per capita income has long-term implications for TFR, it does not have a short-term effect. Conversely, the total population significantly impacts TFR in both the short and long run. The share of the primary sector in the state’s domestic product is found to be inconsequential in shaping TFR.

The total fertility rate (TFR) is a crucial indicator that reflects population dynamics within a region. When the TFR reaches 2.1, it is considered replacement fertility, signifying a level at which a population replaces itself from one generation to the next without significant long-term growth or decline (Smallwood and Chamberlain 2005). Both high and low fertility rates present challenges for a region. A high fertility rate, when combined with other favourable indicators, can lead to a population boom. Conversely, a low fertility rate, coupled with other favourable demographic indicators, can result in a shrinking population. The concern regarding low fertility rates gained prominence in the later part of the 20th century when Europe experienced remarkably low TFRs.

Currently, the world is witnessing a dramatic reduction in fertility rates (Bloom 2011). India too has witnessed a decline in its TFR over the past decade. From a very high fertility rate of 4.5 in 1981, it has now dropped below the replacement fertility rate to 2.05 (Office of the Registrar General and Census Commissioner 2022). Numerous factors contribute to the decline in fertility rates in India and globally, including sex bias (Das Gupta and Bhat 1997; Ghosh and Ghosh 2020; Ghosh et al 2020), urbanisation (White et al 2008), increasing literacy (Liu and Raftery 2020), biological factors (Levine et al 2023), and economic growth (Heer 1968).

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Updated On : 18th Jan, 2024
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