Modeling with Impact

EcoMod School of Modeling and Data Science - Washington DC 2019

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Date: 
March 25, 2019 - March 29, 2019

The EcoMod School will offer intensive five-day courses in the international capital of the USA.  Since the courses are run simultaneously, participants can only choose one course for this period.

Carr Workplace at The Willard Building
1455 Pennsylvania Avenue Northwest Suite 400
Washington, DC 20004
United States

The training is fully practical and provides 'hands-on' experience through intensive use of exercises on the computer. The fee for each course is US$3,767.00. This includes course materials, lectures, computer labs, morning and afternoon coffee breaks, receptions.

A discount of US$500.00 is offered on the regular fee, and US$400.00 on the university fee for registrations and payments completed by February 8, 2019. University students and staff get a discount of 25% off the regular fee (US$2,825.00). Please send a copy of your student or staff card by email to office@ecomod.net.

EcoMod offers a limited number of partial scholarships to candidates from developing countries and transition economies. Please pre-register for the course and then submit the application, click here. The deadline to apply for a scholarship is two months before the beginning of the course (January 25, 2019).

The following courses will be offered:

Dynamic Stochastic General Equilibrium (DSGE) Modeling Step-By-Step
March 25, 2019 - March 29, 2019

Intensive course at the introductory level.

This course is tailored for professionals involved in economic forecasting and policy analysis in the central banks, ministries, research organizations, and international institutions.

The course will introduce all the basic tools for constructing and implementing dynamic stochastic general equilibrium (DSGE) models for policy analysis and forecasting.

Practical General Equilibrium Modeling with GAMS
March 25, 2019 - March 29, 2019

Intensive course at the introductory level. For those who have little or no experience in modeling and in GAMS.