Madhabendra Sinha

Determinants of Farmers’ Decision-Making to Accept Crop Insurance: A Multinomial Logit Model Approach

With the developing trends of commercialization of agriculture, the magnitude of loss due to unfavorable eventualities is increasing and the farmers committed suicides. Burdwan district of West Bengal, India, becomes news headline because of farmer suicide. This study tries to underscore the elements which impact marginal farmers’ decision to accept Pradhan Mantri Fasal Bima Yojona (PMFBY). We collect primary data from 701 farmers in the study over period of from February 2017 to October 2017. Seven estimators, namely education, age, cultivating land area, self-help groups (SHGs), marital condition, gender, and income, are considered, and multinomial logistic regression was used to analyze the data. Results show that gender coefficient is negative which indicates female farmer are prone to agro insurance (access to PMFBY) than male farmers. Results indicate that farmers’ PMFBY and income are significant to the situation that one applies if others apply and get benefit.

FDI and Industry in Developed and Developing Countries: A Comparative Dynamic Panel Analysis

The paper investigates the sector-specific dynamic impacts of FDI inflow on industrial productivity on a comparative basis between developed and developing countries. Different studies observe both positive and negative impacts of FDI on economic growth. However, the existing evidences have not cleared the sector-wise impact of FDI, particularly in industrial sector separately in developing and developed economies. We explore and compare the dynamic relationship between FDI and industrial performances in two groups of countries using data from UNCTAD and World Bank over the period of 1970–2015 in the dynamic panel framework. The stochastic properties of variables are looked into by carrying out various panel unit root tests followed by the GMM estimation. Empirical findings imply that FDI inflows significantly promote industrial growth in both groups of countries; however, the relationship is bi-directional in developing countries and the degree of influence is higher in developed nations.

Foreign Exchange Rate and Agricultural Performances: A Time Series Exercise for India

The paper attempts to investigate and analyze the causal linkage between movements of foreign exchange rate and agricultural performances in terms of production and export empirically in India. Agricultural is described as the backbone of India, contributed largest but continuously declining share of national income. Indian agricultural exports, contribute a significant share of total exports, an important earner of foreign exchange. So foreign exchange rate can have a relationship with worldwide exports and well as output of India’s agricultural and allied commodities. In this context, the current paper explores the underlying long-term causal relationships among India’s foreign exchange rate and productions of exports of agricultural and allied commodities to fill gaps in the available literature. Yearly data on agricultural exports is calculated from DGCIS, Government of India over the period 1970–2015. Reserve Bank of India provides the yearly data on foreign exchange rate and data on GDP of agricultural and allied activities is collected from CSO, Government of India over the same period. The stochastic properties of variables are checked by applying ADF and PP unit root tests. Johansen cointegration test is employed followed by vector error correction mechanism (VECM) to find the long run dynamics. Our findings imply unidirectional long run causality between agricultural exports and India’s foreign exchange rate.