India and China have the largest farm‐household populations in the world—populations that are also among the poorest. Among the many factors that affect farm livelihoods, access to credit has been identified as a significant barrier preventing the escape from poverty. While there has been significant research on credit constraints in developing countries, there is surprisingly little information pertaining to the actual impacts of credit constraints on household well‐being. The objective of this paper is to investigate the impacts of credit constraints on various factors affecting farm households, such as physical and human capital formation, agricultural inputs applications, consumption smoothing, and wage‐seeking behavior using direct elicitation. This paper contributes to the literature and policy debates by comparing the effects of credit constraints in China and India as surveyed in 2008–2009. The analytical results and data demonstrate that binding credit constraints adversely affect a broad range of production and livelihood choices. We empirically show that credit constraints negatively affect food consumption, farm input applications, and health and educational attainments.

Purpose The purpose of this paper is to efficiently assist the decision makers in evaluating and selecting the most appropriate third-party logistics (3PL) provider from environmental sustainability perspective using a two-phase model based on data envelopment analysis (DEA) and analytic network process (ANP). Design/methodology/approach The study uses an integrated approach of DEA and ANP as an evaluation and selection methodology to select an efficient and requisite 3PL. The integrated model is a sound technique for 3PL evaluation and selection. DEA effectively screens the maximally efficient 3PLs, whereas ANP easily performs the cumbersome process of weighting diverse criteria and ranks various alternatives according to their performance on the basis of these criteria. This study lists the prominent evaluation and selection criteria taking into consideration the environmental sustainability. Finally, a real-life industrial application is presented to demonstrate the proposed method. Findings The current research work is devoted to the emerging research topic of environmental sustainability in logistics industry and supply chain management. The results of study indicate that eco-efficient transportation and 3PLs lead better transportation planning, better inventory and warehouse management, lower inventory cost and sustainable supply chain operations. Also, the applied approach enables the decision makers to better understand the complex relationships of the relevant criteria in the decision-making process. Research limitations/implications This study does not investigate the relationships between environmental performances and differentiation advantage from the perspective of 3PLs. Also, sensitivity analysis is not performed. Practical implications The developed integrated model enables decision analysts to better understand the complete evaluation process of 3PL evaluation and selection considering environmental sustainability perspective. Furthermore, the developed approach provides a more flexible, simple, accurate, effective, and systematic decision support tool for 3PL evaluation and selection. Originality/value The current study is first of its kind to use the integrated approach in evaluation and selection of 3PLs from environmental sustainability perspective considering the inter-dependencies among the evaluation and selection criteria.

In this paper I attempt to understand the empirics of human capital (schooling attainment here) and economic growth under the framework of neoclassical growth model and later endogenizing the technological progress as a function of stock value of human capital. Various econometric methodologies have been used to overcome estimation problems involved here - such as omitted variable bias, endogeneity of independent variables, and weak instruments problem. I used panel data method, Difference GMM method, and System GMM method respectively to overcome the above problems. In all the above estimation methodologies, the positive and significant effect of human capital is not observed. The paper concludes with the observations that significance of human capital may be understated, because of (i) inappropriate specification of human capital production function, (ii) inappropriate estimation methodologies, (iii) not controlling for variables related to governance, institutions, etc. Hence further research works on these points may help in appropriately estimating the significance of human capital in growth empirics.

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