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  • Econometrics II (Time Series Analysis)

Introduction

  • Syllabus
  • Computer Setup

Lectures

  • Introduction
    • 1. Time series vs cross-section
    • 2. Time Series concepts and models
  • Multivariate normal distribution
    • 1. Multivariate normal distribution
  • Review of maximum likelihood estimation
    • 1. Maximum likelihood estimation
    • 2. Maximum likelihood estimation of Gaussian models
  • ARMA models
    • 1. Introduction to AR and MA models
    • 2. Algebra of AR and MA models
    • 3. ARMA models
    • 3. Forecasting with ARMA models
  • Non-stationarity
    • 1. Non-stationarity and unit root processes
  • Conditional Heteroskedasticity
    • 1. ARCH processes
  • Multivariate models
    • 1. VARs
    • 2. State space models
    • 3. Applications of state space models
  • Other topics
    • 1. Regime-switching
    • 2. Granger Causality
    • 3. Bayesian approach

Assignments

  • Homework 0
    • README HW0
  • Homework 1
    • README HW1
    • HW1-empty
  • Homework 2
    • README HW2
    • HW 2 Part 1
    • HW 2 Part 2
    • HW 2 Part 3
  • Homework 3
    • Readme HW3
    • HW 3 Part 2-2
  • Homework 4
    • README HW4
    • Part 1
    • Part 2
  • Homework 5
    • README HW5
    • HW 5 part 1
  • Homework 6
  • Homework 7
  • Homework 8
    • HW8 Part 2
  • Homework 9
  • Homework 10

Projects

  • Midterm project
  • Final project

Tutorials

  • 1. Python
    • Intro
    • Functions
    • Modules
    • Paths
  • 2. Numpy
    • Numpy exampes I
    • Numpy exercises I
    • Multivariate Normal in Numpy
  • 3. Pandas
    • Intro
    • Pandas for time series data
  • 4. Matplotlib
  • Other tools
    • Command line
    • Git and GitHub
    • Conda

Data

  • 1. APIs
    • Download data from ECB’s SDW
    • Download data from EUROSTAT
    • Download data from FRED
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Contents
  • Documentation and tutorials
  • Useful links for Stata Users

Pandas

Contents

  • Documentation and tutorials
  • Useful links for Stata Users

Pandas¶

Pandas implements data frames and various tools for data analysis.

Documentation and tutorials¶

  • official Pandas documentation

  • Python Data Science Handbook, ch3

  • Software Carpentry lessons pandas

    • Reading Tabular Data into DataFrames

    • Pandas DataFrames

Useful links for Stata Users¶

  • Comparison of Pandas with Stata

  • Stata to Python Equivalents

  • Coming from Stata

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Pandas

By Nikolay Iskrev
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