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India’s international trade in services benefited immensely from the change in policy stance from import substitution to export promotion in the post-1991 period. Services trade received a further boost when India became signatory to the World Trade Organization (WTO) in 1995. This article aims to estimate the income and price elasticities of India’s services trade during the post-WTO period, using the autoregressive distributed lag (ARDL) approach to cointegration, for the time period starting from 1996–97 Q1 (Quarter 1) to 2011–12 Q4 (Quarter 4). This study finds that the long-run income elasticity of services export is quite high and statistically significant, when the gross domestic product (GDP) of the Organisation for Economic Co-operation and Development countries is taken as proxy for GDP of importing countries. However, the price elasticity of services export is found to be statistically insignificant. In case of services import, both the income and price elasticities of demand are found to be statistically significant, and services import is found to be more responsive to income than relative prices. The implications of the empirical findings for India’s current account deficit are also explored.

India’s working-age group has been over 60 per cent of its population for over two decades, with a record high of 66 per cent in 2018. The gross domestic savings (GDS), yet, plummeted during the previous decade, recording a low of 29.34 per cent in 2018. This is a divergence from the demographic theories which indicate that a rising working-age population will increase savings. Past research on India’s demographic transitioning implications on economic growth and demographic dividend focused on the working-age group. This article brings in a new dimension to existing studies and analyses savings trends by examining working-age youth, and the millennials within this subgroup, in particular. By considering data from between 1980 and 2017, the article investigates the influence of these two demographic variables on the GDS, along with key macroeconomic variables. The estimation techniques applied are the autoregressive distributed lag (ARDL) cointegration technique and the vector error correction model (ECM). The results indicate that the millennial youth’s influence on GDS is statistically significant. Though the long-term influence of the millennial youth working-age group indicates a positive effect on GDS, the adverse impact reflected in the short run may be pointing towards the future financial sustainability of this segment. Although youth savings are expected to be the lowest in the working-age segment, the significant fall in the youth ratio of employment-to-population in the 20–29 years segment, especially since 2005 onwards, raises the thrust for youth policies that can unravel the millennial savings conundrum and thereby pave the way for India’s demographic dividend.

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