Big Data Econometrics
Materials for TA session (update: March 15, 2021)
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Big Data Econometrics
Machine Learning - Regularized regression
```python import numpy as np import matplotlib.pyplot as plt from sklearn import linear_model
Machine Learning - Principal-Component-Analysis
In Depth: Principal Component Analysis
Machine Learning - Manifold-Learning
In-Depth: Manifold Learning
Machine Learning - Double LASSO
def fn_variance(data, ddof=0): n = len(data) mean = sum(data) / n return sum((x - mean) ** 2 for x in data) / (n - ddof) # Note this is equivalen...
Experimental Design - Randomized Experiments
def fn_variance(data, ddof=0): n = len(data) mean = sum(data) / n return sum((x - mean) ** 2 for x in data) / (n - ddof) # Note this is equivalen...
Experimental Design - AB Testing
import numpy as np from scipy.stats import ttest_ind from tqdm import tqdm def t_test(x,y,alternative='both-sided'): _, double_p = ttest_ind(x,y,equal_va...
Causal Inference - Instrumental Variables & Regression Discontinuity
```python def fn_tauhat_means(Yt,Yc): nt = len(Yt) nc = len(Yc) tauhat = np.mean(Yt)-np.mean(Yc) se_tauhat = (np.var(Yt,ddof=1)/nt+np.var(Yc,...
Causal Inference - Differences-in-Differences
```python import pandas as pd import numpy as np import random import statsmodels.api as sm from sklearn.model_selection import cross_val_score from sklearn....
Causal Inference - Lalonde dataset
Based on: https://rugg2.github.io/, https://github.com/iqDF/Lalonde-Causal-Matching
Basic & Econometrics - Spatial data - visualization
def point_inside_polygon(lat,lng,poly): p1 = Point(lng,lat) if p1.within(poly): return True else: return False def get_neigh...
Basic & Econometrics - OLS via Stochastic Gradient Descent
```python import numpy as np import pandas as pd from matplotlib import pyplot as plt from random import seed, random, gauss import statsmodels.api as sm
Basic & Econometrics - Misspecified model - pitfalls
```python import pandas as pd import numpy as np import statsmodels.api as sm
Basic & Econometrics - ARCH and GARCH modeling
# create a simple white noise with increasing variance from random import gauss from random import seed from matplotlib import pyplot # seed pseudorandom num...
Basic & Econometrics - Examples of feature engineering and cross-validation
Online Shoppers Intention Prediction
Basic & Econometrics - Computational efficiency
```python import numpy as np import pandas as pd
Basic & Econometrics - Cross-Validation Example
import pandas as pd import numpy as np import pandas as pd import numpy as np import random import statsmodels.api as sm from sklearn.model_selection import ...
Basic & Econometrics - API examples
```python importing necessary libraries import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns from sklearn import metr...
Randomized Experiments
Econ 570 Big Data Econometrics - 2nd TA session
Causal Inference
Econ 570 Big Data Econometrics - 2nd TA session
Basic Packages - Python and Jupyter Notebook
Econ 570 Big Data Econometrics - 2nd TA session
Causal Inference
A resource list for causality in statistics, data science
Table of Contents Editor’s Selection. Books Papers general Causal Discovery Simpson’s Paradox Machine Learning Fairness Physics Thesis Reviews Softwar...
Measuring the Effect of a Training Program on Fulfillment Center Associate Performance
Below is an application of the comprehensive causal inference framework to the question: “How would you measure the effect of a training program for Fulfillm...
A Comprehensive Causal Inference Framework for Business Questions
Below is a structured process you can follow to tackle a business question using causal inference methods. This framework builds on standard econometric and ...
Econometrics
Central Limit Theorem (CLT)
The Central Limit Theorem is a fundamental concept in probability theory and statistics. It states that, given certain conditions, the distribution of sample...