The course provides an overview of the relationships between the environment, ecosystems, society and the economics under various governance and resource management institutions. The course will follow a well balance learning pathway combining both economic theories and policy analysis to examine the decision- making processes involved while considering environmental considerations in policy making and taking economic decisions. Various kinds of environmental issues will be discussed from both producer and consumer perspectives under different kinds of market and non-market-based institutions. Topics will include, role of technology, limits to growth, steady state economics, limitations of market- based mechanisms, economics of conservation, consumption of goods and services (food, energy and other important commodities) and preservation (threatened species and natural sources) including considerations for intergenerational transfer of natural wealth to meet some desired states of the economy in future. The course will use an interactive and experiential learning platform for learning various topics with the help of discussion sessions, small projects on policy analysis and writing exercises on current real world environmental issues and policy initiatives.
- Docente: Rajendra Chaini
This course is a continuation of Quantitative Methods I course (ECON 2123) that was offered during Semester 1. The course introduces students with theories and applications of inferential statistics that include simple regression analysis, multiple regression analysis, residual analysis, time-series analysis and decision making under uncertainty. The course will start with a preliminary review of parametric and non-parametric estimations and the concept of hypothesis testing including Analysis of Variance and then will introduce basic concepts and applications of simple and multiple regression analyses along with correlation and residual analysis. Finally, the course will provide an overview of non-parametric tests of hypothesis, forecasting with time series analysis and decision-making under uncertainty. The modality of offering this course includes in-class practice and experiential learning through projects and thus students can expect a good combination of lessons on theoretical concepts along with their applications through individual and group projects.
- Docente: Rajendra Chaini