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100-days-of-ml-code

100-Days-Of-ML-Code中文版

100-days-of-ml-code-1

100 Days of ML Coding

1806

18.06 course at MIT

a2reg

a2reg : Estimating panel data models with high dimensional fixed effects

abcdsge

code for Approximate Bayesian Computing estimation of a small DSGE model

abce

Agent-Based Complete Economy, the Python library that makes AB modelling easier..

abcgmm

code for ABC of GMM estimation

adv_econometrics

Assignments and exercises from Advanced Econometrics 1&2

advanced-did

Advanced Differnce-in-Differences Mixtape Track

advanced-econometric-models

advanced-machine-learning

Machine Learning Courses by Higher School of Economics

advanced-r-programming

Course on Advanced R Programming (Johns Hopkins University)

advanced-r-solutions

Set of solutions for the Advanced R programming book

advecon

Stata codes for Advanced Econometrics Class

afe2020

Advanced Financial Econometrics - Trinity Term 2020

andrew_machine_learning_r

This repository, which is work in progress, contains R versions of Andrew Ng's Machine Learning programing exercies.

ann-for-macroeconomic-data-analysis

The analysis and prediction of macroeconomic time-series is a factor of great interest to national policymakers. However, economic analysis and forecasting are not simple tasks due to the lack of a precise model for the economy and the influence of external factors, such as weather changes or political decisions. Our research is focused on Spanish speaking countries. In this thesis, we study different types of neural networks and their applicability for various analysis tasks, including GDP prediction as well as assessing major trends in the development of the countries. The studied models include multilayered neural networks, recursive neural networks, and Kohonen maps. Historical macroeconomic data across 17 Spanish speaking countries, together with France and Germany, over the time period of 1980-2015 is analyzed. This work then compares the performances of various algorithms for training neural networks, and demonstrates the revealed changes in the state of the countries’ economies. Further, we provide possible reasons that explain the found trends in the data.

applied-econometrics

DSGE/CGE/VAR/DID/RD/IV/Panel Data

applied-methods-phd

Repo for Yale Applied Empirical Methods PHD Course

applied-metrics

Code to support work for ARE213: Applied Econometrics at UC Berkeley

applied-time-series-analysis-with-r

Time Series Analysis : Text Time Series Analysis And Applications by R. Shumway & D. Stoffer

applied_computational_economics_and_finance

ECON457 2018 Applied Computational Economics and Finance

applied_metrics

A PhD course in Applied Econometrics and Panel Data

appliedeconometircsformacroeconomics

Some Scripts for the course Applied Econometrics for Macroeconometrics

appliedeconometrics

Stata、计量经济学、DSGE

arch

ARCH models in Python

are212

are213

PhD Applied Econometrics class taught at UC Berkeley

arec422_backup

The copy of course notes for AREC422 (Econometric Analysis in Agricultural and Environmental Economics, University of Maryland). This course offers a hands-on introduction to econometrics. We will explore the linear regression model from the ground up by analyzing real-world datasets and learning how to distinguish causation from correlation. Students will gain practical experience using econometrics to address important questions in agricultural economics and environmental economics.

artificial-intelligence-fomc-monetary-policy-analysis-for-eur-usd-version-1