Dynamic General Stochastic Equilibrium (DGSE) models are well grounded theoretically, in harmony with the empirical evidence to predict and provide accurate interpretation of past and present economic events.
The term Dynamic implies the model is time-dependent. It involves expectations regarding future outcomes tightly knit with the present decision of the economic agents. Economic agents’ objective is to optimize the return from their intertemporal choices given the constraints. Economic agents include households, firms, monetary and fiscal authorities.
It is General as it considers the whole economy with the interaction of many individual parts. The model provides a unique platform for macro equilibrium based on the microeconomics foundation.
Stochastic nature is inbuilt in the system. Unexpected events occur in the economy, and this model is congruent with the probability of being affected by the random shock.
Equilibrium is based on Walrasian Equilibrium where all economic agents are optimizing their return and all markets are clear of excess or shortages.
Algorithm of DGSE Model
The algorithm for solving dynamic stochastic general equilibrium (DSGE) models generally consists of the following steps:
Step 1. Derive the first-order conditions of the model.
Step 2. Find the steady-state.
Step 3. Linearize the system around the steady-state.
Step 4. Solve the linearized system of equations (i.e. decision rules for jump variables and laws of motion for state variables).
Mathematical formulas/topics involved with DGSE Model
For solving a DGSE model, we use the following equations/topics from mathematics.
- Constrained optimization
- Taylor Series
- Euler equation
- Maximum likelihood method
- Simultaneous Equation
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