India’s Age Structure Transition, Sectoral Labor Productivities, and Economic Growth: Evidence and Implications Based on National Transfer Accounts

Abstract

Using the new methodology of National Transfer Accounts, this paper quantifies the economic impacts of age structure transition and productivity growth rate on India's economic growth over the period 2005-2050 by formal and informal sectors. Growth effects are captured by the first demographic dividend (FDD) and distinguished by sector-specific (a) productivity age profiles, (b) relative and absolute labor productivity growth rates, and (c) population distribution for the benchmark year during 2004-2005. Empirical results show that in the presence of these sector-specific differences, growth effects are higher and the sources of lower and slower FDD are attributable to lower productivity levels, growth rates of productivity, and growth rate of effective number of producers in informal sector. Further, throughout, growth effects of productivity are found to be stronger than the age structure transition. Sensitivity results show that growth effects can be remarkably higher at an annual rate of 17 % if benchmark output can be doubled in the informal sector, or FDD can be sustained up to 2050 if India's productivity profile in formal (and informal) sector has a comparable shape with that of Japan/ USA (and Philippines/Indonesia/Nigeria). Overall implications show that stronger policy efforts are required for improvement in productivity levels and growth in informal sector to maximize long-run economic growth through FDD. These new results and implications may be of relevance for formulation of age-structure and informal sector related growth promotion policies in other developing countries of Asia, Latin America and Africa.

Accounting for Growth Effects of Age Structure Transition through Public Education Expenditure: New Macroeconomic Evidence from India

“…Thus, both size and patterns of public spending policies on education by levels of education matter for India’s long-term growth due to age structure transition effects. The above approach, results and implications add to the existing knowledge in the FDD studies on India, such as, Narayana (2015).…”

Nexus between demographic dividend and economic growth: A systematic review with bibliometric exploration

“…The authors find that during the low-growth era of 1991-1999, when the Philippines witnessed its first demographic dividend, demographic conditions improved in urban regions compared to those in rural areas and among the middle and upper classes compared to those in poor household groups. Using the same NTA technique, Narayana (2015) constructed estimates of the empirical links between India's demographic structure, labour productivity by sector, and economic growth. In this example, the author observes that the influence of the demographic dividend differs not only by area, as Abrigo et al (2016) concluded but also by the formal-informal economic sector.…”

“…In this example, the author observes that the influence of the demographic dividend differs not only by area, as Abrigo et al (2016) concluded but also by the formal-informal economic sector. Narayana (2015Narayana ( ) used 2004Narayana ( -2005 base data to predict the effects of the demographic dividend from 2005 to 2050 and concluded that the beneficial shadow of a high ratio of the younger generation (the first demographic dividend) will last until 2045. Sectoral productivity and growth, on the other hand, are critical to enjoying rewards.…”

Impact of Age–Structure Transition on India’s Current Account Balance: An Empirical Analysis

“…Numerous studies have focused on the impact of changes in a country’s age structure on its macroeconomic variables such as fiscal indicators (Lee & Edwards, 2002; Narayana, 2014), economic growth (Bloom & Williamson, 1998; Bloom, Canning, Fink, & Findley, 2007; Mason, 1988; Narayana, 2015a, 2015b), savings, investments and capital flows (Domeij & Floden, 2006; Feroli, 2003; Higgins, 1998; Leff, 1969; Lindh, 1999; Mason, Lee, & Jiang, 2016).…”