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The Hiring of Labour for Field Cultivation: A Study in the Brahmaputra Valley of Northeast India
International Journal of Rural Management, Volume 19, Issue 2, Page 274-297, August 2023.
On the basis of household-level data, the present study examines the hiring of farm labour in the Brahmaputra Valley of Assam in the north-eastern part of India. By adopting a multi-stage sampling technique, the primary data were collected from 237 randomly selected field crop cultivating households located in the lower, upper and central parts of the Brahmaputra Valley. The hiring of labour for field cultivation is extensive among the sample farm households of all size groups, but it varies across locations and activities. There are three forms of farm labour hiring, among which the hiring of labour on daily basis is common and pre-dominant. The wage of farm labourers is not same across activities, sex and locations. The estimation of independent double hurdle model depicts the farm size, type of cultivator and age of head of the household as the common factors that affect both the adoption and the extent of hiring of farm labour. The availability of family labour is another factor that affects the extent of hiring of farm labour.
On the basis of household-level data, the present study examines the hiring of farm labour in the Brahmaputra Valley of Assam in the north-eastern part of India. By adopting a multi-stage sampling technique, the primary data were collected from 237 randomly selected field crop cultivating households located in the lower, upper and central parts of the Brahmaputra Valley. The hiring of labour for field cultivation is extensive among the sample farm households of all size groups, but it varies across locations and activities. There are three forms of farm labour hiring, among which the hiring of labour on daily basis is common and pre-dominant. The wage of farm labourers is not same across activities, sex and locations. The estimation of independent double hurdle model depicts the farm size, type of cultivator and age of head of the household as the common factors that affect both the adoption and the extent of hiring of farm labour. The availability of family labour is another factor that affects the extent of hiring of farm labour.
Examining stereotypes in a dynamic social order: the stereotype content model in India
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Foreign Institutional Ownership and Its Impact on Investment Efficiency in Manufacturing Firms: Evidence from Indian Capital Market
Business Perspectives and Research, Ahead of Print.
This article explores the impact of foreign institutional investor’s (FII) ownership on the investment efficiency of Indian manufacturing firms. In this article, unbalanced panel data is used, in total, 21,214 firm-year observations of 1,205 companies listed in Centre for Monitoring Indian Economy (CMIE) COSPI (CMIE Overall Share Price Index) are taken into account. The data range is from 2001 to 2019. This research article considers investment-investment opportunities sensitivity as the proxy for investment efficiency, where investment opportunities are measured Tobin’s Q. As per our findings FII’s ownership impacts investment efficiency in a negative way. It is further found that this inverse relationship between FII’s ownership and investment efficiency is more pronounced in resource abundant firms, compared to the resource constrained firms. In this study both fixed as well as random effect models are developed incorporating robust standard error, additionally system generalized method of moments (GMM) model as well as two step Heckman model are also used to check the robustness of the findings.This study adds to the existing literature as a pioneering study on impact of FII’s ownership on firm’s investment efficiency in the context of India, a large emerging market economy.
This article explores the impact of foreign institutional investor’s (FII) ownership on the investment efficiency of Indian manufacturing firms. In this article, unbalanced panel data is used, in total, 21,214 firm-year observations of 1,205 companies listed in Centre for Monitoring Indian Economy (CMIE) COSPI (CMIE Overall Share Price Index) are taken into account. The data range is from 2001 to 2019. This research article considers investment-investment opportunities sensitivity as the proxy for investment efficiency, where investment opportunities are measured Tobin’s Q. As per our findings FII’s ownership impacts investment efficiency in a negative way. It is further found that this inverse relationship between FII’s ownership and investment efficiency is more pronounced in resource abundant firms, compared to the resource constrained firms. In this study both fixed as well as random effect models are developed incorporating robust standard error, additionally system generalized method of moments (GMM) model as well as two step Heckman model are also used to check the robustness of the findings.This study adds to the existing literature as a pioneering study on impact of FII’s ownership on firm’s investment efficiency in the context of India, a large emerging market economy.
The impact of place-based policy: evidence from a multiple synthetic control analysis of the northeastern revitalization program in China
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Price Discovery in the Presence of Embedded Location Options: The Evidence from Chana Contracts in India
Business Perspectives and Research, Ahead of Print.
The presence of embedded location options in agricultural commodity futures contracts allows for several additional deliverable locations in addition to the reference location for the delivery of the underlying asset using location specific adjustments to futures settlement prices. Price discovery contribution assessment in this context needs to be done simultaneously across futures and cash markets in all these deliverable locations in contrast to present bivariate studies in the Indian context, which only consider futures and the cash market at reference location. We assess price discovery contributions across all the deliverable cash markets and the most liquid futures contract for Chana (Gram/Chickpea) in India. We find that while futures lead price discovery as expected, the cash market at the reference location plays almost no role in price discovery with cash markets at additional deliverable locations playing a larger than expected role. We interpret these results as arising from large values of location options for Chana due to inappropriate specifications of deliverable asset locations and associated premiums and discounts. These results provide evidence that exchanges and regulators need to monitor option values and optimize delivery specifications of futures contracts so that they perform their functions of price discovery and risk transfer well.
The presence of embedded location options in agricultural commodity futures contracts allows for several additional deliverable locations in addition to the reference location for the delivery of the underlying asset using location specific adjustments to futures settlement prices. Price discovery contribution assessment in this context needs to be done simultaneously across futures and cash markets in all these deliverable locations in contrast to present bivariate studies in the Indian context, which only consider futures and the cash market at reference location. We assess price discovery contributions across all the deliverable cash markets and the most liquid futures contract for Chana (Gram/Chickpea) in India. We find that while futures lead price discovery as expected, the cash market at the reference location plays almost no role in price discovery with cash markets at additional deliverable locations playing a larger than expected role. We interpret these results as arising from large values of location options for Chana due to inappropriate specifications of deliverable asset locations and associated premiums and discounts. These results provide evidence that exchanges and regulators need to monitor option values and optimize delivery specifications of futures contracts so that they perform their functions of price discovery and risk transfer well.
An integrative framework for supply chain rating: from financial-based to ESG-based rating models
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Gender ideology and fertility: evidence for a curvilinear hypothesis
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Rising and thriving in the post COVID-19 era: a case study of COSMAX, a leader of the Korean cosmetic industry
Exploring the Effects of Firm-Specific Factors on Financing Preferences of Listed SMEs in India
Business Perspectives and Research, Ahead of Print.
Small and medium-sized enterprises (SMEs) are the driving force for the robust socioeconomic growth of a country. The study primarily aims to empirically evaluate the impact of certain firm-specific factors on the financing preferences of the listed SMEs with specific reference to India. It attempts to examine their financing practices and also investigates if they follow the order explained under various theories of finance. The sample consists of 134 listed SMEs on NSE as well as BSE SME exchange. They have been studied for the period from 2014 to 2019. The sample and the time period of the study differentiates it from the existing studies in the domain. It concludes that though majority of the variables included in the model are statistically significant, there is a possibility of influence of other micro-level variables or macro-level economic factors on the financing decisions of the listed SMEs. It is also revealed that for their financial needs, SMEs prefer short-term spontaneous sources, that is, payables and provisions, then accumulated profits followed by short-term borrowings and in last opt for the long-term debt. The study also found that there is no single theory that can completely explain the financing behavior of the listed SMEs. Moreover, it is also observed that no additional benefit is available for SMEs out of listing in India.
Small and medium-sized enterprises (SMEs) are the driving force for the robust socioeconomic growth of a country. The study primarily aims to empirically evaluate the impact of certain firm-specific factors on the financing preferences of the listed SMEs with specific reference to India. It attempts to examine their financing practices and also investigates if they follow the order explained under various theories of finance. The sample consists of 134 listed SMEs on NSE as well as BSE SME exchange. They have been studied for the period from 2014 to 2019. The sample and the time period of the study differentiates it from the existing studies in the domain. It concludes that though majority of the variables included in the model are statistically significant, there is a possibility of influence of other micro-level variables or macro-level economic factors on the financing decisions of the listed SMEs. It is also revealed that for their financial needs, SMEs prefer short-term spontaneous sources, that is, payables and provisions, then accumulated profits followed by short-term borrowings and in last opt for the long-term debt. The study also found that there is no single theory that can completely explain the financing behavior of the listed SMEs. Moreover, it is also observed that no additional benefit is available for SMEs out of listing in India.