Agricultural Growth Diagnostics: Identifying the Binding Constraints and Policy Remedies for Bihar, India

Agriculture plays a significant role in economic development of underdeveloped regions. Multiple factors influence the performance of agricultural sector but a few of these have a strong bearing on its growth. This study develops a growth diagnostics framework for agricultural sector in Bihar, located in eastern India, to identify the most binding constraints. The study results show that poor functioning of agricultural markets and low-level of crop diversification are the important reasons for low agricultural growth in Bihar. Rise in price instability of agricultural produces indicates a weak price transmission across the markets even after repealing the Agricultural Produce Market Committee Act. Poor market linkages and non-functioning producer collectives at village-level affect the farmers’ motivation for undertaking crop diversification. Hence, policy suggestions to overcome these binding constraints include the state provisioning of basic market infrastructure to attract private investment in agricultural marketing, strengthening the Farmer Producer Organisations, and framing a comprehensive policy on crop diversification.

Existence and Uniqueness of Solutions to Dynamic Models with Occasionally Binding Constraints

Occasionally binding constraints (OBCs) like the zero lower bound (ZLB) can lead to multiple equilibria, and so to belief-driven recessions. To aid in finding policies that avoid this, we derive existence and uniqueness conditions for otherwise linear models with OBCs. Our main result gives necessary and sufficient conditions for such models to have a unique (“determinate”) perfect foresight solution returning to a given steady state, for any initial condition. While standard New Keynesian models have multiple perfect-foresight paths eventually escaping the ZLB, price level targeting restores uniqueness. We also derive equilibrium existence conditions under rational expectations for arbitrary non-linear models.

International Comparison of the Efficiency of Agricultural Science, Technology, and Innovation: A Case Study of G20 Countries

An efficiency-oriented innovation analysis will enhance the understanding of the operational quality related to the transformation process of limited innovation investments for improving innovation outputs. The purpose of this study was to measure the static-dynamic efficiency of agricultural science, technology, and innovation (ASTI) and identify the efficiency determinants across the Group of Twenty (G20) countries. First, the static comprehensive efficiency of ASTI was measured employing the Data Envelopment Analysis (DEA)-BCC model, and some of the binding constraints to higher efficiency were investigated. Then, we applied the DEA-Malmquist index model to calculate the efficiency change of ASTI in certain periods and decomposed the sources of efficiency change. Finally, the G20 countries were classified into four-level clusters based on the rankings of efficiency measurement and capability evaluation of ASTI to locate the type of ASTI level and identify the type change in both the efficiency and capability. The empirical results indicate the following. (1) The efficiency range of the G20 developing countries was relatively larger than the G20 developed countries. The G20 developed countries showed a fluctuating downward trend, while the G20 developing countries showed an upward trend from the perspective of efficient proportion. The R&D expenditure redundancy and the agricultural journal papers deficiency were the main binding constraints to the higher efficiency of ASTI. (2) The total factor productivity change (TFPC) of ASTI showed an alternating trend of “decline–growth–continuous decline–growth recovery”, where the G20 developed countries experienced “growth–decline–growth” and the G20 developing countries underwent a fluctuating upward trend. The TFPC of ASTI in most G20 countries was primarily due to technological change. (3) The G20 developed countries usually had advantages in capacity, while the G20 developing countries performed better in efficiency.