Publications by Bryan Calderon
ECNM HW3 Wine
Table of contents Preparation Clear Data Loading Packages Bringing in Data Introduction Variables 1. Cleaning the Data Understanding Missing Variables Dropping variables Cleaning the data 2. Data Exploration Summary table with changes Graphs Distribution of Key Variables Which variables drive cases sold? Trend deep dive Correlation Analys...
16477 sym Python (9353 sym/24 pcs) 16 img 4 tbl
Discussion Heteroskedasticity
Table of contents Part 1 Part 2 Running Model - Math scores Applying the White Test Applying the Auxiliary Regression Applying the Chi Squared Test Discussion Heteroskedasticity Author Bryan Calderon Part 1 ’1) What is “heteroskedasticity”, and the econometric issue it causes (affects point estimates or standard errors)? (2-3 sentences ...
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Meeting Final project
ECNM Research project Author Bryan Calderon Setup Data Graphs and charts # A tibble: 3 × 2 price_bucket count <chr> <int> 1 <$1MM 3021 2 $1-2MM 109 3 >$2MM 29 Summary Table of Numeric Variables for nj_dt2 Mean Median Minimum Maximum Kurtosis Skew SD NA Count Year 2,012 2,012 2,011 2,013 -0.70 -0.50 0.6...
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HW 2 - Insurance
Table of contents Preparation Clear Data Loading Packages Bringing in Data Introduction Variables 1. Cleaning Data Removing “Z_” prefix from the data set Distribution by variable “Z_” count after removal are now 0 Renaming Variables Understanding Missing Variables Cleaning the data Result of the data clean up 2. Data Exploration Su...
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ECNM Discussion 8
Table of contents Part 1 Adjusting the data set Running the Model Results from the Model Part 2) Part A Creating the two models Setup Optimal Lambda Ridge and Lasso regressions Results from the Models Part B Adjusting the scale of the models Setup Optimal Lambda Ridge and Lasso regressions Results from the Models ECNM Discussion 8 Author ...
4171 sym Python (5751 sym/43 pcs)
ECNM Discussion 7
Table of contents Loading Packages Bringing in Data Part 1 Overview Checking for balance Part 2 OLS Interpreting the results Part 3: Fixed Effects Models Dummy Variables Demeaned Regression Method Within Estimator Method Comparing the three methods Results Below is the two way FE (state and time) ECNM Discussion_7 Author Bryan Calderon L...
5926 sym Python (15377 sym/19 pcs) 2 tbl
ECNM Discussion 6
Discussion 6 Clear Data used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) Ncells 580775 31.1 1324645 70.8 NA 669422 35.8 Vcells 1068540 8.2 8388608 64.0 16384 1851968 14.2 Bringing in data Rows: 48 Columns: 6 ── Column specification ────────────────────────�...
4767 sym Python (4000 sym/18 pcs)
ECNM Discussion 5
Table of contents Part 1) What is bias of an estimator? Part 2) Omitted Variable Bias (OVB) Part 3) Applying Omitted Variable Bias on a data set Section 3.1 - Bringing in the data and creating new variables Section 3.2 - Omitting a variable (tax) Section 3.3 - Understanding the conditions Section 3.4 - Bias direction Section 3.5 - Using stargazer...
4876 sym Python (4633 sym/27 pcs) 2 img
ECNM_Discussion_4
Table of contents Clear Data Part 1) Gauss Markov Assumptions - Explantions Part 2) Cross sectional datasets Part 3) 4 Linear Regression Plots ECNM_Discussion_4 Clear Data rm(list = ls()) # Clear all files from your environment gc() # Clear unused memory used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) Ncel...
7419 sym Python (7079 sym/45 pcs) 14 img
ECNM Discussion 3
Table of contents 0.1 Clear Data 1 Part A 2 Part B ECNM Discussion 3 Author Bryan Calderon 0.1 Clear Data rm(list = ls()) # Clear all files from your environment gc() # Clear unused memory used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) Ncells 581808 31.1 1327592 71 NA 669431 35.8 Vcells...
4498 sym Python (5934 sym/44 pcs) 5 img