Learning by "Researching" ^TM

Training content is systematic and structured as follows:

1) Introduction to DSGE Models and Dynare
2) New Keynesian Models, Euler equation and New Philipps Curve
3) Small Open Economy Models
4) Extensions to New Keynesian Models and Habit formation
5) Kalman Filter and Estimation Methods

6) Bayesian Methods and Markov Chain Monto Carlo6-
7) Examples of Practical Application of DSGE Models and group research paper.

Training content is systematic and structured as follows:

1) CGE Model introduction

2) Production and Demand theories

3) GTAP model and database introduction

4) Modeling Nested Production functions in GEMPACK 

5) Elasticities: CES, Armington calibration 

6) Modeling Nested Demand functions and regional household

7) Practical CGE applications, aggregation, and simulations. 

8) SAM/I-O table construction - Bonus Module

Training content is systematic and structured as follows:

1. Working with GTAP slack variables
   
2. Target output change by violating zero profit condition
   
3. Introducing new conditions to GTAP through code modifications (in GEMPACK)
   
4. Introduce an exogenous tariff that targets a policy variable (e.g., real wages)
   
5. Linking GTAP with econometrics (R ) with a focus on reading outputs of a GTAP model (GEMPACK) using package HARr(R)
   
6. Setting up a dynamic GTAP
   
7. Calibrate and run a dynamic GTAP model
   
8. Linking GTAP with a GAMS model (Global Timber Model)
   
9. Linking GTAP with a PE model (poverty analysis)

Training content is systematic and structured as follows:

1) Modeling a simple economy

2)Arrow-Debreu, Cobb-Douglas and other CGE-related functions

3) Modeling the government

4) Modeling the rest of the world

5) Introduction to Dynamic CGE models 

6) Modeling a simple dynamic model

7) Practical CGE applications using GAMS, aggregation, and simulations.