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ECON 6074: Causal Inference
创建日期：2024-04-23 17:18:18
所属分类：经济Economics
标签： ECON 6074
Causal Inference

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Final Exam – Data Project

ECON 6074: Causal Inference

Instructions
• Please submit your work in one zip file containing three files: a) write up of your answers
(including tables), b) log file, and c) do-file that works with your matched data set.
• You will conduct empirical analysis using a dataset from the study by Duflo, Dupas, and
Kremer (2011) “Peer Effects, Teacher Incentives, and the Impact of Tracking: Evidence
from a Randomized Evaluation in Kenya” American Economic Review, 101(5): 1739-1774.
• Each student is assigned with a unique dataset. Look up your matched Final Exam Dataset
ID number and download your unique data set “Final_M2_2022_ID[#].dta”. If your
answers do not match with your assigned dataset you will receive 0 points.

1. [25 points] The Impact of Tracking on Students’ Achievements
a. (5 points) What is the authors’ identification strategy to estimate the impact of
tracking on students’ achievements? Explain how this method can identify the
treatment effect using the potential outcomes framework. What are the key
assumptions associated with this identification strategy?
b. (5 points) Conduct a balance check to examine whether students in tracking and
non-tracking schools are similar to each other.
c. (10 points) Report the OLS estimate of the effect of tracking on standardized
endline test score [stdR_totalscore] with and without individual controls (control
variables: student’s gender [girl], age [agetest], being assigned to contract teacher
[etpteacher], percentile in initial distribution [percentile]).
d. (5 points) Provide a test of whether the effect of tracking on standardized endline
test score differs across students at different percentiles of initial distribution (e.g.
students in the bottom half versus students in the top half).

2. [35 points] The Effect of Assignment to Upper Tracking Section on Achievement
a. (5 points) Propose an identification strategy to estimate the impact of being in
upper tracking (top half) section on achievement? Use the potential outcomes
framework to illustrate the identification strategy and key assumptions.
b. (5 points) Create a graph which plots standardized endline test score
[stdR_totalscore] on the assignment variable [percentile] and visually inspect
whether there is discontinuity at the cutoff.
c. (5 points) Create graphs to examine whether covariates [girl; agetest; etpteacher]
are balanced around the cutoff point. Do students at the bottom of the upper section
look similar to students at the top of the lower section?
d. (10 points) Use parametric approach to estimate the effect of being assigned to the
upper section [tophalf] on test score. That is, regress test score on indicator for upper
section controlling for the assignment variable, individual controls [girl; agetest;
etpteacher], and school fixed effect [schoolid]. Use different polynomials of the
assignment variable: 1. Linear, 2. Quadratic, 3. Cubic. And report the estimated
coefficients on assignment to upper section. How do the estimates vary across
different polynomials?
e. (10 points) Use local linear regression (nonparametric approach) to estimate the
effect of being assigned to upper section. Report results from using at least three
different bandwidths. How does the estimate from the nonparametric approach
compare to the estimate from the parametric approach in part d?
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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 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