A SAM-based Multiplier Model to Track Growth-Poverty-Inequality Nexus in Bangladesh

This paper offers a social accounting matrix (SAM) based analysis leading to a better understanding of the way various agents in the real economy interact, the way socio-economic groups make their living, the channels through which demand driven interventions may affect the poor, and the potential growth-poverty-inequality nexus. This is done in two steps. First, the paper reveals the economic structure of Bangladesh with a SAM framework where the macro (national accounts and input-output table) and micro (national surveys) data are juxtaposed under a unified data matrix to portray the meso level interactions of various economic agents, that is production sectors, factors of production, household groups, and other institutions. Subsequently, the SAM is used to develop a multiplier simulation model, which enables tracking and quantifying the nature and extent of the linkages among the demand driven shocks (stimuli), economic growth, income generation, and concomitant poverty and distribution implications from the perspective of different socio-economic groups in Bangladesh.Social Accounting Matrix (SAM); Multiplier Model; Growth-Poverty-Inequality;

Modelling Gender Impacts of Policy Reforms in Bangladesh: A Study in a Sequential Dynamic CGE Framework

The research explores the gender aspects of policy reforms in Bangladesh in a sequential dynamic computational general equilibrium (CGE) framework. This research uses the most updated SAM of Bangladesh and is the first attempt to build a gendered sequential dynamic CGE model for the Bangladesh economy. A ‘home production’ version of gendered CGE model for the Bangladesh economy is developed. This research tries to understand how gender interests are affected by greater exposure to trade and other policy reforms. The shortrun and long-run impacts of policy reforms in the labour market and in the household in a gendered framework are also explored. The research performs two simulations to examine the impact of: (1) domestic trade liberalisation in Bangladesh, and (2) the phasing-out of Multi-fibre Agreement (MFA) on textile and garments. This research builds a gendered social accounting matrix (SAM) for the year 2000 and uses it in a sequential dynamic computable general equilibrium framework. The representative household approach is followed. It is found that domestic trade liberalisation leads to a significant expansion of the ready-made garment sectors in the economy as a result of which the share of market labour supply of unskilled female labour increases. But, this results in a fall in the shares of domestic labour supply and leisure of unskilled female members of the households. The fall in the share of leisure time may have significant negative implications for the time spent on education by this labour category. It is also observed that the long run impacts are different from the short run impacts with respect to the magnitude of the effects. In the case of second simulation, it can be noted that the phasing out of the MFA works in completely the opposite direction. The share of market labour supply of unskilled female members of the households decrease, and the shares of domestic work and leisure increase for most of the households both in the short and long run

Animal Models: Challenges and Opportunities to Determine Optimal Experimental Models of Pancreatitis and Pancreatic Cancer.

At the 2018 PancreasFest meeting, experts participating in basic research met to discuss the plethora of available animal models for studying exocrine pancreatic disease. In particular, the discussion focused on the challenges currently facing the field and potential solutions. That meeting culminated in this review, which describes the advantages and limitations of both common and infrequently used models of exocrine pancreatic disease, namely, pancreatitis and exocrine pancreatic cancer. The objective is to provide a comprehensive description of the available models but also to provide investigators with guidance in the application of these models to investigate both environmental and genetic contributions to exocrine pancreatic disease. The content covers both nongenic and genetically engineered models across multiple species (large and small). Recommendations for choosing the appropriate model as well as how to conduct and present results are provided