While traditional macroeconometric forecasting models are vulnerable to the Lucas critique—that claims that the effects of an economic policy cannot be predicted using historical data from a period when that policy was not in place—microfounded models should not be, at least in theory. Further, since the microfoundations are based on the preferences of the decision-makers in the model, DSGE models feature a natural benchmark for evaluating the welfare effects of policy changes (for discussion of both points, see Woodford, 2003, pp.11–12 and Tovar, 2008, pp.15–16).
In economics, general equilibrium theory attempts to explain the behavior of supply, demand, and prices in a whole economy with several or many interacting markets, by seeking to prove that a set of prices exists that will result in an overall (or "general") equilibrium. General equilibrium theory contrasts to the theory of partial equilibrium, which only analyzes single markets.
General equilibrium theory both studies economies using the model of equilibrium pricing and seeks to determine in which circumstances the assumptions of general equilibrium will hold. The theory dates to the 1870s, particularly the work of French economist Léon Walras in his pioneering 1874 work Elements of Pure Economics.
Overview
It is often assumed that agents are price takers, and under that assumption two common notions of equilibrium exist: Walrasian (or competitive) equilibrium, and its generalization; a price equilibrium with transfers.
Broadly speaking, general equilibrium tries to give an understanding of the whole economy using a "bottom-up" approach, starting with individual markets and agents. Macroeconomics, as developed by the Keynesian economists, focused on a "top-down" approach, where the analysis starts with larger aggregates, the "big picture". Therefore, general equilibrium theory has traditionally been classified as part of macroeconomics.
New in Stata 17: Bayesian dynamic stochastic general equilibrium models
Find out how to fit Bayesian linear and nonlinear dynamic stochastic general equilibrium (DSGE) models in Stata 17.
https://www.stata.com
published: 20 Apr 2021
Roadmap (Introduction to Dynamic Stochastic General Equilibrium)
published: 08 May 2017
This video shows how to solve a simple DSGE model
In this video, it is shown, how a simple dynamic stochastic general equilibrium model can be solved.
published: 03 Dec 2018
IMF asks Larry Christiano, what are DSGE models?
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very popular in policy making circles.
Lawrence Christiano is the Alfred W. Chase Professor of Business Institutions at Northwestern University. He has also served as a consultant to the Federal Reserve Banks of Chicago, Cleveland and Minneapolis, and a Research Affiliate of the National Bureau of Economic Research (NBER). He is also a Fellow of the Econometric Society.
published: 27 Jan 2016
IMF asks Larry Christiano, why are dsge models so popular?
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very popular in policy making circles.
Lawrence Christiano is the Alfred W. Chase Professor of Business Institutions at Northwestern University. He has also served as a consultant to the Federal Reserve Banks of Chicago, Cleveland and Minneapolis, and a Research Affiliate of the National Bureau of Economic Research (NBER). He is also a Fellow of the Econometric Society.
published: 27 Jan 2016
Dynamic Stochastic General Equilibrium models using Julia
published: 24 May 2017
General Equilibrium I: Introduction to Dynamic General Equilibrium
published: 07 Mar 2022
A 5 Minute Intro into Dynamic Stochastic General Equilibrium Models
Macro Struggle | DSGE Model Explained:
In this video I introduce a DSGE (Dynamic Stochastic General Equilibrium) model and show an example of a First Order Condition that results from within a DSGE model.
Timestamps:
0:00 - Intro
0:25 - The Problem
1:27 - Turn it into a Value Function
1:47 - Example FOC: Consumption and Real Money Demand
published: 22 Jul 2022
Add oil to Dynamic Stochastic General Equilibrium (DSGE) Models
Add oil to Dynamic Stochastic General Equilibrium (DSGE) Models
In this video, I teach you how to add oil to DSGE models. To do this, we will expand the simple real business cycle (RBC) model that we set up in previous tutorials.
The model is straightforward: we add oil as an input in the production function of firms. Now, firms demand capital, labor, and oil to produce output. From the maximization problem, we derive the oil price.
For simplicity, we use an exogenous oil supply, but I explain in more detail the difference between endogenous and exogenous oil supply.
Finally, in the model, we define oil supply and oil demand shocks. We can see how, when the productivity of firms increases, they demand more inputs to produce goods. As the demand for oil increases, the price of oil rises...
published: 13 Aug 2024
Macroeconomics - A Dynamic General Equilibrium Approach
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very pop...
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very popular in policy making circles.
Lawrence Christiano is the Alfred W. Chase Professor of Business Institutions at Northwestern University. He has also served as a consultant to the Federal Reserve Banks of Chicago, Cleveland and Minneapolis, and a Research Affiliate of the National Bureau of Economic Research (NBER). He is also a Fellow of the Econometric Society.
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very popular in policy making circles.
Lawrence Christiano is the Alfred W. Chase Professor of Business Institutions at Northwestern University. He has also served as a consultant to the Federal Reserve Banks of Chicago, Cleveland and Minneapolis, and a Research Affiliate of the National Bureau of Economic Research (NBER). He is also a Fellow of the Econometric Society.
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very pop...
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very popular in policy making circles.
Lawrence Christiano is the Alfred W. Chase Professor of Business Institutions at Northwestern University. He has also served as a consultant to the Federal Reserve Banks of Chicago, Cleveland and Minneapolis, and a Research Affiliate of the National Bureau of Economic Research (NBER). He is also a Fellow of the Econometric Society.
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very popular in policy making circles.
Lawrence Christiano is the Alfred W. Chase Professor of Business Institutions at Northwestern University. He has also served as a consultant to the Federal Reserve Banks of Chicago, Cleveland and Minneapolis, and a Research Affiliate of the National Bureau of Economic Research (NBER). He is also a Fellow of the Econometric Society.
Macro Struggle | DSGE Model Explained:
In this video I introduce a DSGE (Dynamic Stochastic General Equilibrium) model and show an example of a First Order Cond...
Macro Struggle | DSGE Model Explained:
In this video I introduce a DSGE (Dynamic Stochastic General Equilibrium) model and show an example of a First Order Condition that results from within a DSGE model.
Timestamps:
0:00 - Intro
0:25 - The Problem
1:27 - Turn it into a Value Function
1:47 - Example FOC: Consumption and Real Money Demand
Macro Struggle | DSGE Model Explained:
In this video I introduce a DSGE (Dynamic Stochastic General Equilibrium) model and show an example of a First Order Condition that results from within a DSGE model.
Timestamps:
0:00 - Intro
0:25 - The Problem
1:27 - Turn it into a Value Function
1:47 - Example FOC: Consumption and Real Money Demand
Add oil to Dynamic Stochastic General Equilibrium (DSGE) Models
In this video, I teach you how to add oil to DSGE models. To do this, we will expand the simple...
Add oil to Dynamic Stochastic General Equilibrium (DSGE) Models
In this video, I teach you how to add oil to DSGE models. To do this, we will expand the simple real business cycle (RBC) model that we set up in previous tutorials.
The model is straightforward: we add oil as an input in the production function of firms. Now, firms demand capital, labor, and oil to produce output. From the maximization problem, we derive the oil price.
For simplicity, we use an exogenous oil supply, but I explain in more detail the difference between endogenous and exogenous oil supply.
Finally, in the model, we define oil supply and oil demand shocks. We can see how, when the productivity of firms increases, they demand more inputs to produce goods. As the demand for oil increases, the price of oil rises.
When there is a supply shock, the oil supply exceeds oil demand, resulting in a decrease in oil prices. Since the oil supply is exogenous, we cannot determine with certainty what causes it to expand. It follows a random process (AR 1). While simple, this assumption can also be considered realistic. In reality, we cannot accurately predict when an event will result in a change in oil supply. Historically, oil shocks have been associated with war, political instability, COVID-19, the discovery of new oil reserves, the loss of oil transportation at sea, and many other unexpected events that can have a significant impact on oil prices.
------------------------------------------------------------------------------
👉You can learn step by step how to estimate the model in stata here:
https://www.youtube.com/watch?v=-n2MC26-WEA
👉If you would like to contact me for research or job proposals, feel free to do so at [email protected]
I can provide assistance to international agencies, banks and/or firms.
----------------------------------------------------------------------------
👉Buy the Complete STATA Do file + math solution + math notation from the video at:
https://jdeconomicstore.com/b/rbc-model-with-oil
👉Download the Dataset for Free at:
https://jdeconomicstore.com/b/rbc-model-with-oil
👉You can get access to the MAtlab-Dynare course which includes the slides and math for the oil model in this video at:
https://jdeconomicstore.com/b/dsge-dynare-course
👉Subsctibe my memberships and support more content creation:
https://www.youtube.com/channel/UC5P21WGFO4WRUlAiGLcwymg/join
👉Learn simple RBC DSGE model in Stata:
https://www.youtube.com/watch?v=sOG3YW0iCQg&list=PLsZ8kVwX52ZHewGr0jLceiyCazP0GWhoB&pp=gAQB
👉Learn DSGE Models in Matlab:
https://www.youtube.com/watch?v=SAfLK8Ji2ZM&pp=ygUKZHNnZW1hdGxhYg%3D%3D
Add oil to Dynamic Stochastic General Equilibrium (DSGE) Models
In this video, I teach you how to add oil to DSGE models. To do this, we will expand the simple real business cycle (RBC) model that we set up in previous tutorials.
The model is straightforward: we add oil as an input in the production function of firms. Now, firms demand capital, labor, and oil to produce output. From the maximization problem, we derive the oil price.
For simplicity, we use an exogenous oil supply, but I explain in more detail the difference between endogenous and exogenous oil supply.
Finally, in the model, we define oil supply and oil demand shocks. We can see how, when the productivity of firms increases, they demand more inputs to produce goods. As the demand for oil increases, the price of oil rises.
When there is a supply shock, the oil supply exceeds oil demand, resulting in a decrease in oil prices. Since the oil supply is exogenous, we cannot determine with certainty what causes it to expand. It follows a random process (AR 1). While simple, this assumption can also be considered realistic. In reality, we cannot accurately predict when an event will result in a change in oil supply. Historically, oil shocks have been associated with war, political instability, COVID-19, the discovery of new oil reserves, the loss of oil transportation at sea, and many other unexpected events that can have a significant impact on oil prices.
------------------------------------------------------------------------------
👉You can learn step by step how to estimate the model in stata here:
https://www.youtube.com/watch?v=-n2MC26-WEA
👉If you would like to contact me for research or job proposals, feel free to do so at [email protected]
I can provide assistance to international agencies, banks and/or firms.
----------------------------------------------------------------------------
👉Buy the Complete STATA Do file + math solution + math notation from the video at:
https://jdeconomicstore.com/b/rbc-model-with-oil
👉Download the Dataset for Free at:
https://jdeconomicstore.com/b/rbc-model-with-oil
👉You can get access to the MAtlab-Dynare course which includes the slides and math for the oil model in this video at:
https://jdeconomicstore.com/b/dsge-dynare-course
👉Subsctibe my memberships and support more content creation:
https://www.youtube.com/channel/UC5P21WGFO4WRUlAiGLcwymg/join
👉Learn simple RBC DSGE model in Stata:
https://www.youtube.com/watch?v=sOG3YW0iCQg&list=PLsZ8kVwX52ZHewGr0jLceiyCazP0GWhoB&pp=gAQB
👉Learn DSGE Models in Matlab:
https://www.youtube.com/watch?v=SAfLK8Ji2ZM&pp=ygUKZHNnZW1hdGxhYg%3D%3D
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very popular in policy making circles.
Lawrence Christiano is the Alfred W. Chase Professor of Business Institutions at Northwestern University. He has also served as a consultant to the Federal Reserve Banks of Chicago, Cleveland and Minneapolis, and a Research Affiliate of the National Bureau of Economic Research (NBER). He is also a Fellow of the Econometric Society.
The IMF interviews Larry Christiano, an influential researcher in the design and use of Dynamic Stochastic General Equilibrium Models. These models are very popular in policy making circles.
Lawrence Christiano is the Alfred W. Chase Professor of Business Institutions at Northwestern University. He has also served as a consultant to the Federal Reserve Banks of Chicago, Cleveland and Minneapolis, and a Research Affiliate of the National Bureau of Economic Research (NBER). He is also a Fellow of the Econometric Society.
Macro Struggle | DSGE Model Explained:
In this video I introduce a DSGE (Dynamic Stochastic General Equilibrium) model and show an example of a First Order Condition that results from within a DSGE model.
Timestamps:
0:00 - Intro
0:25 - The Problem
1:27 - Turn it into a Value Function
1:47 - Example FOC: Consumption and Real Money Demand
Add oil to Dynamic Stochastic General Equilibrium (DSGE) Models
In this video, I teach you how to add oil to DSGE models. To do this, we will expand the simple real business cycle (RBC) model that we set up in previous tutorials.
The model is straightforward: we add oil as an input in the production function of firms. Now, firms demand capital, labor, and oil to produce output. From the maximization problem, we derive the oil price.
For simplicity, we use an exogenous oil supply, but I explain in more detail the difference between endogenous and exogenous oil supply.
Finally, in the model, we define oil supply and oil demand shocks. We can see how, when the productivity of firms increases, they demand more inputs to produce goods. As the demand for oil increases, the price of oil rises.
When there is a supply shock, the oil supply exceeds oil demand, resulting in a decrease in oil prices. Since the oil supply is exogenous, we cannot determine with certainty what causes it to expand. It follows a random process (AR 1). While simple, this assumption can also be considered realistic. In reality, we cannot accurately predict when an event will result in a change in oil supply. Historically, oil shocks have been associated with war, political instability, COVID-19, the discovery of new oil reserves, the loss of oil transportation at sea, and many other unexpected events that can have a significant impact on oil prices.
------------------------------------------------------------------------------
👉You can learn step by step how to estimate the model in stata here:
https://www.youtube.com/watch?v=-n2MC26-WEA
👉If you would like to contact me for research or job proposals, feel free to do so at [email protected]
I can provide assistance to international agencies, banks and/or firms.
----------------------------------------------------------------------------
👉Buy the Complete STATA Do file + math solution + math notation from the video at:
https://jdeconomicstore.com/b/rbc-model-with-oil
👉Download the Dataset for Free at:
https://jdeconomicstore.com/b/rbc-model-with-oil
👉You can get access to the MAtlab-Dynare course which includes the slides and math for the oil model in this video at:
https://jdeconomicstore.com/b/dsge-dynare-course
👉Subsctibe my memberships and support more content creation:
https://www.youtube.com/channel/UC5P21WGFO4WRUlAiGLcwymg/join
👉Learn simple RBC DSGE model in Stata:
https://www.youtube.com/watch?v=sOG3YW0iCQg&list=PLsZ8kVwX52ZHewGr0jLceiyCazP0GWhoB&pp=gAQB
👉Learn DSGE Models in Matlab:
https://www.youtube.com/watch?v=SAfLK8Ji2ZM&pp=ygUKZHNnZW1hdGxhYg%3D%3D
While traditional macroeconometric forecasting models are vulnerable to the Lucas critique—that claims that the effects of an economic policy cannot be predicted using historical data from a period when that policy was not in place—microfounded models should not be, at least in theory. Further, since the microfoundations are based on the preferences of the decision-makers in the model, DSGE models feature a natural benchmark for evaluating the welfare effects of policy changes (for discussion of both points, see Woodford, 2003, pp.11–12 and Tovar, 2008, pp.15–16).