Publications by Zixuan Yin
Weekly Discussion
Weekly Discussion Author Zixuan Yin 1. Issue Summary 1.1 What is heteroskedasticity? and the econometric issue it causes. Heteroscedasticity refers to the situation where the error terms are not uniformly distributed around the predicted values of the dependent variable. Although the sum of the error terms is zero, the standard deviation of th...
1710 sym Python (7640 sym/38 pcs) 2 img
Weekly Discussion: Instrumental Variable
Weekly Discussion Author Zixuan Yin Paper: The Productivity of Mental Health Care: An Instrumental Variable Approach Mingshan Lu, Department of Economics, The University of Calgary, Canada 1. What is the research question that the authors are interested in estimating? The question that interests the author is how to estimate the effectiveness ...
3617 sym
Weekly Discussion
Weekly Discussion Author Zixuan Yin Part 1 Running Code When you click the Render button a document will be generated that includes both content and the output of embedded code. You can embed code like this: # Clear the workspace rm(list = ls()) # Clear environment - remove all files from your workspace invisible(gc()) # Clear unused me...
1915 sym Python (29722 sym/29 pcs)
Weekly Discussion
Weekly Discussion Author Zixuan Yin Part 1 graphics.off() # clear all graphs # Prepare needed libraries packages <- c("glmnet", # used for regression "caret", # used for modeling "xgboost", # used for building XGBoost model "ISLR", "dplyr", # used for data manipulation a...
1695 sym Python (29543 sym/28 pcs)
Document
Discussion Author Zixuan Yin 1. Setup # Clear the workspace rm(list = ls()) gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 592897 31.7 1350778 72.2 686425 36.7 Vcells 1079950 8.3 8388608 64.0 1875867 14.4 cat("\f") graphics.off() packages <- c("AER", # load dataset "plm", # ...
3461 sym Python (15871 sym/49 pcs)
Weekly Discussion
Clear and Import Data rm(list = ls()) gc() ## used (Mb) gc trigger (Mb) max used (Mb) ## Ncells 542080 29.0 1205592 64.4 686414 36.7 ## Vcells 988866 7.6 8388608 64.0 1875897 14.4 cat("\f") graphics.off() Part B 1. Set Up # Load Libraries library(stargazer) # summary statistics ## ## Please cite as: ## Hlavac, Marek...
5628 sym R (3781 sym/22 pcs)
Weekly Discussion
Clear and Import Data rm(list = ls()) gc() ## used (Mb) gc trigger (Mb) max used (Mb) ## Ncells 542073 29.0 1205572 64.4 686414 36.7 ## Vcells 988658 7.6 8388608 64.0 1875897 14.4 cat("\f") graphics.off() Part B 1. Set Up # Load Libraries library(stargazer) # summary statistics ## ## Please cite as: ## Hlavac, Marek...
4664 sym R (3781 sym/22 pcs)
Document
Clear and Import Data rm(list = ls()) gc() ## used (Mb) gc trigger (Mb) max used (Mb) ## Ncells 542074 29.0 1205575 64.4 686414 36.7 ## Vcells 988668 7.6 8388608 64.0 1875897 14.4 cat("\f") graphics.off() Part B 1. Set Up # Load Libraries library(stargazer) # summary statistics ## ## Please cite as: ## Hlavac, Marek...
4654 sym R (3781 sym/22 pcs)
Week 5 Discussion
Part 1 The bias of an estimator is the difference between the estimator’s expected value and real value. There are several reasons for bias of an estimator omitted variables, sample selection bias, model specification errors, and reverse causality. These biases can cause the model to estimate the coefficient of the estimator, overestimating o...
2759 sym R (6468 sym/21 pcs)
Week4
Part 1 The Gauss-Markov Assumptions are a set of conditions to make sure the regression model is valid and the predicted value of regression is unbiased. The set of conditions includes six assumptions, Linearity, Full column rank, The zero conditiolnal mean assumption, Homoscedasticity, Nonautocorrelation, Exogeneity, and the central limit theo...
6422 sym R (3172 sym/21 pcs) 8 img 1 tbl