PhD Class Notes

I have often been asked by classmates about my class notes. I figured I would make it a public good and publish them here for the future generations of econ grad students.

I hope they help someone!

Copyright notice: I only publish here: either (1) personal notes for classes for which the lecture notes/material was made publicly available by the instructor (with a reference to it), or (2) notes that are based on my own summary of various sources (also referenced).

Graduate Classes at NYU

Macroeconomics

Macro 1 - Dynamic Programming

This lecture series was taught by Prof John Stachurski and Prof Tom Sargent in the Fall Semester 2018 at NYU. The material and lecture notes are posted and available on John Stachurski's website.

These notes are my own.

Lecture 1: Introduction [slides]
Lecture 2: Dynamic Programming and Fixed Points [notes] [slides]
Lecture 3: Contraction and Fixed Points [notes] [slides]
Lecture 4: Dynamical Systems [notes] [slides]
Lecture 5: Markov Chains [notes] [slides]
Lecture 6: Deterministic Linear Models and VARs [notes] [slides]
Lecture 7: Random Coefficient Models and Non-linear Models [notes] [slides]
Lecture 8 and 9: Job Search [notes] [slides 1] [slides 2]
Lecture 10: Quadratic Optimization and LQ problem [notes] [slides]
Lecture 11: the Kalman filter [notes] [slides]
Lecture 12: Optimal Savings and Optimal Growth [notes] [slides]
Lecture 13: the Euler Equation [notes] [slides]
Lecture 14: Extensions [slides]
Review of concepts [notes]

If you are interested in these topics, I highly encourage you to also take a look at the QuantEcon website.

Macro 2 - Recursive Macroeonomics

This lecture series was taught by Prof Lars Ljungqvist and Prof Tom Sargent in the Fall Semester 2018 at NYU. We mainly followed Chapters 8, 9, 11 and 12 from Recursive Macroeconomics Theory (2018, 4th edition) by Ljungqvist and Sargent.

These notes are my own.

Lecture 1: Complete Market Economies [notes]
Lecture 2: OLG Economies [notes]
Lecture 3: the Neoclassical Growth Model [notes]
Lecture 4: OLG in a Production Economy [notes]

Macro 3 - New-Keynesian Models and Monetary Economics

This lecture series was taught by Prof Marc Gertler in the Spring Semester 2019 at NYU. We mainly followed Monetary Policy, Inflation, and the Business Cycle (2015, 2nd edition) by Jordi Galí. The material and lecture notes are posted and available on Marc Gertler's website.

These notes are my own.

Lecture 1: Real Business Cycles
- Part 1: [notes] [slides]
- Part 2: [notes] [slides]
Lecture 2: New-Keynesian Models
- Part 1: [notes] [slides]
- Part 2: [notes] [slides]
- Part 3: [notes] [slides]
Lecture 3: Welfare and Optimal Monetary Policy [notes] [slides]
Lecture 4: Investment [notes] [slides]
Lecture 5: Financial Frictions
- Part 1: [slides]
- Part 2: [slides]

Macro 4 - Heterogeneous Agents Models

This lecture series was taught by Prof Corina Boar in the Spring Semester 2019 at NYU. We mainly followed Prof Gianluca Violante's course on Heterogeneity in Macroeconomics, which is publicly available on his website.

These notes are my own.

Lecture 1: Heterogeneity in the Neoclassical Growth Model [notes] [lecture notes]
Lecture 2: The Income Fluctuation Problem (1) [notes] [lecture notes]
Lecture 3: The Income Fluctuation Problem (2) [notes] [lecture notes]
Lecture 4: Numerical Techniques [lecture notes]
Lecture 5: Bewley Economics [notes] [lecture notes]
Lecture 6: Application of Bewley Economics [notes] [lecture notes]
Lecture 7: Transition and Aggregate Uncertainty in Bewley models [notes] [lecture notes]
Lecture 8: Extensions
- Optimal Ramsey Taxation with Incomplete Markets [lecture notes 1] [lecture notes 2]
- Micro and Macro Labor Supply Elasticity [lecture notes]
- Lifecycle Economies [lecture notes]
- Aggregate shocks in lifecycle economies and default [lecture notes]
- Industry Dynamics [lecture notes]

Microeconomics

Micro 1 - Decision Theory

This lecture series was taught by Prof Ariel Rubinstein and follows from his personal notes posted on his website. The course material is accessible for free after registration. You can see me here by the way!

The notes are my own.

Lecture 1: Preferences [notes]
Lecture 2: Utility [notes]
Lecture 3: Choice [notes]
Lecture 4: Consumer Preferences [notes]
Lecture 5: Consumer Demand [notes]
Lecture 6: Budget sets and the Dual problem [notes]
Lecture 7: Expected Utility [notes]
Lecture 8: Risk Aversion [notes]
Review of concepts [notes]

Micro 2 - General Equilibrium Theory

This lecture series was taught by Prof Alberto Bisin in the Fall Semester 2018 at NYU. The lecture notes are available on his personal website. [lecture notes]

These notes are my own.

Lecture 1: Abstract Exchange Economies [notes]
Lecture 2: Two-period Economies [notes]
Lecture 3: Asymmetric Information [notes]
Lecture 4: Infinite Horizon Economies [notes]

Micro 3 - Game Theory

This lecture series was taught by Prof Ennio Stacchetti in the Spring Semester 2019 at NYU. We mainly followed Game Theory (1991) by Fudenberg and Tirole. A Course in Game Theory (1994, 1st edition) by Osborne and Rubinstein, which is freely available on Ariel Rubinstein's website.

These notes are my own.

Lecture 1: Normal and Extensive Form Games [notes]
Lecture 2: Rationalizability [notes]
Lecture 3: Nash equilibrium [notes]
Lecture 4: Perfect Equilibrium [notes]
Lecture 5: Perfect Bayesian Equilibirum and Sequential Equilibrium [notes]
Lecture 6: Bargaining [notes]
Lecture 7: Cooperative Games [notes]

Micro 4 - Imperfect Information and Mechanism Design

This lecture series was taught by Prof Alessandro Lizzeri in the Spring Semester 2019 at NYU. We mainly followed Microeconomic Theory (1995) by Mas-Colell, Whinston and Green and Auction Theory (2010, 2nd edition) by Vijay Krishna.

These notes are my own.

Lecture 1: Principal-Agent Problems [notes]
Lecture 2: Adverse Selection, Selecting and Screening [notes]
Lecture 3: Mechanism Design [notes]

Econometrics

Metrics 1 - Probability and Measure Theory

This lecture series was taught by Prof Quang Vuong in the Fall Semester 2018 at NYU. We mainly followed Introduction to the Mathematical and Statistical Foundations of Econometrics (2004) by Bierens.

Unfortunately, I don't have great [notes] for this course but you can take a look at my notes from my Advanced Probability graduate course at HKU.

Lecture 1: Probability Theory
Lecture 2: Random Variables and Random Vectors
Lecture 3: Borel Measurability, Integration and Expectation
Lecture 4: Distribution and Transformation
Lecture 5: Multivariate Normal Distribution
Lecture 6: Modes of Convergence

Metrics 2 - Linear Inference and Instrumental Variables

This lecture series was taught by Prof Konrad Menzel in the Fall Semester 2018 at NYU. We mainly followed Econometrics (2018) by Hansen, which is freely available from his own website.

The notes are my own.

Lecture 1: Linear Regression [notes]
Lecture 2: Restricted Least Squares and Hypothesis Testing [notes]
Lecture 3: LASSO and Shrinkage [notes]
Lecture 4: Bootstrap [notes]
Lecture 5: IV and Causal Inference [notes]
Lecture 6: Panel Data [notes]
Lecture 7: Quantile Regression [notes]

Metrics 3 - Time Series Econometrics

This lecture series was taught by Prof Timothy Cogley in the Spring Semester 2019 at NYU. We mainly followed Time Series Analysis (1994) by Hamilton.

These notes are my own.

Lecture 1: Time Domain Analysis [notes]
Lecture 2: Frequency Domain Analysis [notes]
Lecture 3: Maximum-Likelihood Estimation [notes]
Lecture 4: ML Applications [notes]
Lecture 5: ML Estimation and DSGE [notes]
Lecture 6: Identified VARs [notes]
Lecture 7: Conditional Heteroskedasticity [notes]
Lecture 8: Unit Root and Integration [notes]

Metrics 4 - Structural Estimation

This lecture series was taught by Prof Tim Christensen in the Spring Semester 2019 at NYU. We mainly followed Econometrics (2000) by Fumio Hayashi, Microeconometrics: Theory and Applications (2005) by Cameron and Trivedi, and Econometrics (2012, 5th edition) by Woolridge.

These notes are my own.

Lecture 1: Introduction to Structural Estimation [notes]
Lecture 2: Extremum Estimation [notes]
Lecture 3: M Estimators [notes]
Lecture 4: Generalized Method of Moments (GMM) [notes]
Lecture 5: Simulated Method of Moments (SMM) [notes]
Lecture 6: Minimum Distance Estimation (MD)
Lecture 7: Hypothesis Testing [notes]
Lecture 8: Quasi Bayesian Estimation [notes]
Lecture 9: Bootstrap [notes]
Review of concepts [notes]

Maths

Mathematics for Economists

This lecture series was taught by Prof Luke Geldermans in the Fall Semester 2018 at NYU. We mainly used the text book Real Analysis with Economic Applications (2007) by Eke Ok.

These notes are my own.

Lecture 1: Relations [notes]
Lecture 2: Sequences and Functions [notes]
Lecture 3: Countable and Uncountable Sets [notes]
Lecture 4: Minkowski’s Inequality [wiki] =)
Lecture 5: Connectedness and Compactness [notes]
Lecture 6: Sequential Compactness and Completeness [notes]
Lecture 7: Contraction Maps and Fixed Points [notes]
Lecture 8: Continuity on Metric Spaces [notes]
Lecture 9: Homeomorphisms [notes]
Lecture 10: Correspondences [notes]
Lecture 11: The Maximum Theorem [notes]
Lectures 12-13: Dynamic Programming [notes]
Lectures 14-16: Linear Spaces [notes]
Lectures 17-18: Convex Sets [notes]
Lectures 18-20: Separation and Extensions [notes]
Lectures 21-23: Optimization [notes]

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