PART I. MAIN INGREDIENTS OF A GLOBAL SOLUTION METHOD FOR MACROECONOMIC MODELS
1. Model with elastic labor supply.
2. Time invariant decision functions.
3. An example of a global projection-style Euler equation method.
• Unidimensional and multidimensional grids and basis functions.
• Ill-conditioning and numerical stability.
• Numerical integration.
• Optimization methods.
• Evaluation of the accuracy of solutions.
PART II. HETEROGENEOUS AGENTS MODELS
1. Heterogeneous agents models with complete markets.
2. Generalized stochastic simulation algorithm for models with finite set of agents.
3. Heterogeneous agents models with a continuum of agents
• Aiyagari model;
• Krusell and Smith model.
4. Overlapping-generation models.
PART III. NUMERICAL METHODS FOR SOLVING STATE-DEPENDANT MACROECONOMIC MODELS WITH APPLICATIONS
1. Models with sovereign default. Envelope condition method.
2. Models with quasi-geometric discounting.
3. New Keynesian models with a zero lower bound on nominal interest rates. Epsilon distinguishable set and cluster grid algorithms.
4. Smolyak method. A multi-country model of international trade.
5. Algorithms with precomputation of integrals.
PART IV. NUMERICAL METHODS FOR SOLVING TIME-DEPENDANT MACROECONOMIC MODELS.
1. Extended path method.
2. Extended functions path method.
PART V. MACHINE LEARNING AND DEEP LEARNING IN ECONOMICS
1. Introduction to machine learning
• Supervised learning.
• Unsupervised learning.
2. Deep learning.
PART VI. HARDWARE AND SOFTWARE FOR COMPUTATIONALLY INTENSE MACROECONOMIC MODELS.
1. Parallel computations in economics.