Current Issue

Vol. 54,  No. 2,  2024

Dynamics of Gender Wage Differentials in Urban Labour Market: An Investigation in Uttar Pradesh

Nomita P. Kumar ¹, Kavita Baliyan ¹, Achala Srivastava ¹ and Geeta Rani^2
1Giri Institute of Development Studies, Lucknow, India and ²R.G. (PG) College, Meerut, India

Abstract: This paper has dealt with comprehensive empirical analysis based on gender wage gaps among regular wage workers in urban Uttar Pradesh in India and explored the significance of gender bias in explaining the wage gap between men and women in the urban workforce of Uttar Pradesh. We have utilized unit-level data from the NSSO 2011-12 and Periodic Labour Force Survey (PLFS) 2020-21 to quantify the wage gap and explore its implications on gender-based differences in earnings. Our results indicate that the ‘sticky floor effect’ persists in absolute magnitudes, leading significantly to larger wage disparities between low-income workers and high-income workers. The magnitude of this effect is strongly pronounced among women than men, indicating that women at the lower end of the income spectrum experience marked discrimination. The analysis has revealed that approximately 75% in 2020-21 of the wage disparities stem from the ‘coefficient’ portion or gender bias. The empirical findings of our study suggest some policy intervention in reducing the gender wage gap among urban regular salaried workers.

Key Words: Urban labour market, Gender discrimination, Wage gap.

Growth-Employment Nexus in India: A Simulation Exercise

Dipa Mukherjee¹ and Rajarshi Majumder ^2
1Narasinha Dutt College, Howrah, West Bengal, India and ²University of Burdwan, Bardhaman, West Bengal, India

Abstract: In this paper, we explore and compare the roles of three factors—namely, growth, employment elasticity, and sectoral distribution—in explaining the sluggish employment growth in India in recent decades using a simulation cum decomposition method. It transpires from our analysis that the incremental employment would have been highest if the technology were similar in all the major states, followed closely by that if the sectoral structure of their economies were similar. In both cases, employment in 2021 would have been more than 11 per cent higher than what it actually was. But, removal of regional disparity in economic growth would have raised employment by less than 5 per cent. A more labour-intensive technology and more output from secondary sector would have created substantial additional employment.

Key Words:

Married Female Labour Force Participation in Maharashtra: Insights from The PLFS Dataset

Surabhi Sharma, Anurag Asawa and Santoshi Rajguru
Gokhale Institute of Politics and Economics, Pune, India

Abstract: Female labour force participation (FLFP) has been low in India and worldwide. The situation looks grim when we probe the contribution of married females in the labour force. In India, although married female participation in the labour force has increased, it is abysmal compared to married male participation in the labour force. Several studies have suggested various deterrents which stop married females from participating in the labour force. The present study attempts to identify the determinants that influence the decision of married females. Demography, social and religious background, and status of married females are vital in their decision-making. Relationships with the head of household, family size, count of children and age of a child, level of education, and income of husband are a few factors that are probed by utilising unit-level data (of Maharashtra) from Periodic Labour Force Surveys (PLFS) covering the years 2017-18, 2018-19, 2019-20 and 2020-21. Married Hindu females in urban areas of Maharashtra are more likely to work than other religious groups, barring Buddhists. Females with young children are less likely to participate in the labour force but intend to join as the child’s age increases. Education also plays interesting role.

Key Words: Female, Married, Workforce participation, Social groups, Religion, Education.

Revisiting The Macroeconomic Determinants of The USD/INR Exchange Rate: A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis

Manbhanjan Mishra ¹ and Hansa Jain ^2
1Reserve Bank of India, Ahmedabad, Gujarat, India and ²Mahatma Gandhi Kashi Vidyapith, Varanasi, Uttar Pradesh, India

Abstract: The Exchange Rate (ER) plays a substantial role in the decision-making of the economic agents. The study seeks to find out the macroeconomic determinants of USDINR ER by considering both the monetary and real sectors. The study uses Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL (NARDL) models to find out the nonlinear impact of the various economic variables on the ER. The study also uses the Cumulative Dynamic Multiplier (CDM) method to find out the shock evolution of a unit change in the independent variables on USDINR ER. It is observed that ER is primarily impacted by Broad Money (M3), foreign exchange reserves, stock index (Nifty 50), GDP and Foreign Institutional Investment flows.

Key words:Exchange rate, Co-integration, Error correction model, NARDL, Cumulative dynamic multiplier.

Monetary Poverty and Multidimensional Poverty in Hilly Region of Manipur: A Static and Dynamic Comparative Analysis

S. Solomon¹ and Utpal Kumar De ^2
1Tamenglong College, Tamenglong, Manipur, India and ²North-Eastern Hill University, Shillong, Meghalaya, India

Abstract: With agriculture as the main occupation and large proportions of the population living subsistence lifestyles in rural areas, consumption poverty may not reflect the true nature of poverty in rural hilly areas. This paper examines the static and dynamic approaches of poverty measurement across household. Based on these estimates, we examine the degree of synergies and overlaps among different measures of poverty. While the static measures of monetary poverty (MP) and multidimensional poverty (MDP) identify households who are poor at a point of time, the ex-ante (dynamic) vulnerability to monetary poverty (VMP) measure is used to identify vulnerable households. Using a cross-sectional survey of 500 households in rural hilly areas of Manipur, India, it is observed that in majority of the cases vulnerable households are identified correctly by both the static and ex-ante measures of vulnerability to poverty. We also find large inclusion errors in ex-post measures of poverty. The significant conclusion drawn here is that it recommends using multiple measures of poverty while designing context-specific programmes for alleviating and preventing poverty. The results also demonstrate that estimates of vulnerability to poverty exceeds that of head count poverty in both the monetary and multidimensional poverty measures with vulnerability stemming more from excess fluctuation in predicted wellbeing rather than a particularly low expected level of wellbeing.

Key words:Monetary poverty, Vulnerability, Multidimensional poverty, Multidimensional poverty index, FGLS model, Manipur.

Impact of Climate Change on Tea Production in India: An Econometric Analysis

Jeet Saha, Zafar Iqubal and Kanak Kanti Bagchi
University of North Bengal, Siliguri, West Bengal, India

Abstract: Major previous studies examining the impact of climate change on tea production have primarily assumed a linear relationship. However, laboratory experiments conducted in controlled environments have revealed that different levels of increased carbon dioxide (CO2) in the atmosphere can affect tea output differently. No prior study, through time series data and econometric tools, aimed to verify this asymmetric effect of CO2 on tea output empirically. This study attempts to fill this research gap through a time series analysis. We employ a multiple-threshold NARDL model to determine how minor to extreme changes in CO2 in the atmosphere can cause varying impacts on tea production in India. Our findings align with laboratory research, indicating a ‘fertilization effect’ of carbon on tea plants, and this effect is found to vary across different CO2 levels in the atmosphere.

Key words:Climate change, Tea production, Carbon fertilization, Climate change and agriculture, Time series econometrics.