ScienceGuy

The study investigates the impact of monetary policy on CO2 emissions while controlling for income, trade, foreign direct investment (FDI) and accounting for structural breaks using annual data from 1971 to 2014. By utilizing the extended environmental Kuznets curve (EKC) framework and dynamic ARDL simulations, the results reveal that the Kuznets curve is a long-run phenomenon for India, not a short run. Moreover, interest rates are identified to possess a significantly positive relation with emissions in the short as well as long run. This indicates the sub-optimality of the present monetary policy for sustainable growth. Hence, it suggests incorporating environmental impacts into the central bank’s framework. Additionally, trade is found to be inelastic and weakly beneficial for the environment, while FDI is elastic and significantly detrimental. The latter evidence supports Pollution Haven Hypothesis. Further, following Itkonen (Itkonen, Energy, 2012) arguments, the study demonstrat

The course by IMF provides an overview of empirical methods and analytical techniques for assessing the impact and effectiveness of development innovations at product and policy levels and the way to measure what's working. The course provides tools to evaluate the causal impact of various policies and programs. I.  Impact Evaluation as an instrument of Development Policy II. RCT Basics III. Statistical Concepts IV. Statistical Inference V. Regression Analysis VI. Imperfect Compliance and Attrition VII. Power Calculations VIII. Differences in Differences IX. Regression Discontinuity Designs Click here to read my notes

Machine learning is the science of getting computers to work without being explicitly programmed. The Machine learning course offered by Stanford University provides an introduction to this. It flows very smoothly and in the way that the hardest and toughest topics get absorbed with ease. Indeed, the instructor has delivered and designed an incredible course. For starting ML, no other resource could be better, I.  Introduction     - Introduction     - Model and Cost function     - Parameter learning     - Linear algebra review II. Linear regression with multiple variables      - Multiple linear regression     - Computing parameters analytically III. Logistic regression     - Classification and representation     - Logistic regression model     - Multiclass classification     - Solving the problem of overfitting IV. Neural networks     - Neural networks     - Applications V. Neural networks: Learning     - Cost function and backpropagation     - Backpropagation in practice     - Applica