<p>Jobless growth and unemployment are not just things of the past but are still some of the biggest challenges faced by nations even today. The generation of employment is considered the most important step towards the rise in the growth of both developed and developing nations. Hence, this study analyses the role of economic growth on unemployment using the Autoregressive Distributed Lags (ARDL) and Nonlinear Autoregressive Distributed Lags (NARDL) mechanics for the period 1990 to 2019. In this study, Okun’s Law and its validation for India, an emerging economy, are also examined empirically. The results obtained from the ARDL study revealed that unemployment was positively affected by gross domestic product, openness of trade, and growth rate of population, while negatively affected by school enrolment ratio (at the tertiary level), in the short run. In the long run, unemployment was positively affected by gross domestic product (GDP) and negatively affected by the school enrolment ratio. Similar to the case of ARDL in NARDL as well, gross domestic product had an unfavourable effect on unemployment. GDP showed a positive relation with unemployment when given positive (GDP +) and negative shocks (GDP-), both in the short and in the long run. The coefficient of GDP is closer to 2–3 per cent, but it is positive for both ARDL and NARDL, showing a positive relation with unemployment, hence indicating the absence of Okun’s law in India. The Granger Causality Test concluded “unidirectional causalities” from GDP and school enrolment ratio towards unemployment and unemployment towards trade openness. Furthermore, “bidirectional causality” was also observed between population growth rate and unemployment. Strategies such as the inclusion of domestic and foreign investments, improvement in education and healthcare, and on-the-job programs with targeted training could pave the way for improved competition and better job opportunities in the labour market and a more balanced growth trajectory for the nation.</p>