Despite continuous improvement in literacy rates in India, the rate of youth unemployment has continued to be high. This is worrying, particularly in terms of how well it is being addressed through education and training and the nature of this skill mismatch. With secondary labour market indicators for 2018–2025, this study focuses on the connections between unemployment, literacy and youth employability, both individually and in combination. The analysis is based on recently released data on the labour market in India. It conducts ability and employability evaluations and follows a two-stage empirical process. Given the availability of only eight annual observations, the findings are interpreted as associations rather than causal effects. The study is an empirical approach and was conducted in two phases. First, Ordinary Least Squares regression is used to investigate the link between selected unemployment indicators and literacy indicators at the individual and at the structure level. Analyse the relationships among variables and their impact on youth employability, focusing on skill mismatch and multicollinearity patterns. Second, composite measures of unemployment and literacy are developed to look at the relationship between both. The relationship between employability and the association is examined within a parsimonious regression framework. This method can be used to allow the study to preserve the usefulness of the disaggregated indicators and to decrease dimensionality in the principal specification. The findings of this study indicate that unemployment and literacy indicators, when combined, account for a significant proportion of the variation in the results. There was some variation in youth employment levels, but it was difficult to separate out individual relationships due to multicollinearity. In the composite-index model, the unemployment index is negative. The literacy rate is associated with youth employability, and it is statistically significant at the 5% level, whereas the rate of participation in ethnic minority schools is not. The association of the index and Y is negative and statistically significant at 10%. These results relationship between the two. They do not imply a causal relationship between the two, but they are consistent with the possibility of a skill mismatch. The overall results indicated that there is a need for improvement in educational attainment, alongside a greater skills-labour market fit, if these outcomes are to change. JEL Codes: I21, J13, J24
In the modern era, efficiency and productivity are crucial for sustainable agricultural development, although they are highly sensitive to financial and climate changes. Thus, this study explores the impact of financial variability and climate change on agricultural production efficiency at the sub-national level in India from 2005 to 2019, focusing on 21 major agricultural-producing states. A two-stage approach is used: in the first stage, efficiency scores are calculated using stochastic frontier analysis with total agricultural production as the output and land, labour and fertiliser as inputs. In the second stage, regression analysis employs the feasible generalised least squares model to assess the impact of climate and financial variability. Results show that agricultural credit, electricity use for agriculture, water levels, soil wetness and social development expenditure of the state positively influence efficiency. At the same time, the effect of agricultural credit differs between low- and high-climate-vulnerability states; climate variables like temperature, droughts and floods negatively affect it. JEL Codes: D24, G21, Q54, C30
Kerala’s gender budgeting policy, since its inception in 2017–2018, has generally exhibited incremental expansion, positioning the state as one of the notable gender budgeting states. However, the Gender Budget 2025 marks a departure from this trajectory, with allocations declining for the first time. This reversal raises important concerns about the fiscal priorities of the state’s gender budgeting. Despite nearly a decade of implementation, persistent issues such as the dilution of women-exclusive schemata, static funding for flagship programmes like Kudumbashree and a continued emphasis on welfare over empowerment remain. This research note argues that Kerala’s gender budgeting remains narrowly focused on practical gender needs, with limited movement towards strategic and transformative gender needs. By situating these trends and critiques within broader trends in Union Gender Budgeting, the note calls for recalibrating the policy to align with the objectives of gender mainstreaming. JEL Codes: J16, H61, I38, H72
This article argues that though Sraffa’s fundamental equation, given by r = R (1 – w ), represents a framework of a snapshot designed to capture a moment of a dynamic empirical economy, it also provides us with a scientific tool to properly quantify and analyse economic growth due to accumulation and technical changes. JEL Codes: B24, B51, O40, O41
This article examines the club convergence of corporate environmental protection and resource management (CEPRM) expenditure across a panel of 26 Indian states from 2014–2015 to 2020–2021 using the novel Phillips–Sul (PS) (2007) approach. The results of a single steady-state analysis reveal divergence in CEPRM expenditure and indicate that states are not converging towards a single steady-state path. Meanwhile, the PS approach reveals heterogeneity among states and confirms the formation of three clubs. Each club follows a distinct steady-state path, and the estimated convergence speeds differ across groups: Club 1 has a slower rate (0.112) than Club 3, which has a faster rate (2.609), confirming the conventional convergence approach. By identifying multiple convergence paths, this analysis provides insight into CEPRM disparities and reveals uneven environmental stewardship by the corporate sector across Indian states. As a result, the findings suggest that policymakers should design tailored policies for each club to address issues related to CEPRM expenditure, thereby supporting a more balanced distribution of environmental spending across Indian states. JEL Codes: Q580, M14, C33
