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ECMT 6002/6702: Econometric Applications

创建日期：2024-06-15 18:10:30

所属分类：经济Economics

标签： ECMT 6002

Econometric Applications

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ECMT 6002/6702: Econometric Applications

Part I : Computing exercises
Information on the dataset
We will use the “ECONMATH" dataset (provided in Wooldridge’s textbook) with 856 samples with
17 variables:
• age : individual i’s age
• work : i’s hours of work (per week)
• study : i’s hours of study (per week)
• econhs : take 1 if individual i studied economics in high school
• colgpa : individual i’s college GPA measured at the beginning semester.
• hsgpa : individual i’s high school GPA
• acteng : individual i’s ACT English score
• actmth : individual i’s ACT math score
• act : individual i’s ACT composite
• mathscr : individual i’s math quiz score, 0-10
• male : take 1 if individual i is male
• calculus : take 1 if individual i took calculus course
• attexc : take 1 if individual i’s past attendance is “excellent”
• attgood : take 1 if individual i’s past attendance is “good”
• fathcoll : take 1 if individual i’s father has BA
• mothcoll : take 1 if individual i’s mother has BA
• score : individual i’s score in a certain course of interest, in percent
If you need more detailed explanation on the variables, you could see Wooldridge’s textbook “In-
troductory Econometrics: A Mordern Approach”.
1
Questions
Consider the multiple linear regression model:
yi
score
= β1 + β2 x2,i
study
+ β3 x3,i
econhs
+ β4 x4,i
colgpa
+ β5x5,i
male
+ β6 x6,i
calculus
+ β7 x7,i
attgood
+ β8 x8,i
attexc
+ ui. (1)
Answer to the following questions.
(i) Report the OLS estimates β̂7 and β̂8 with their estimated standard errors (with no correction
for heteroskedasticity/autocorrelation). Interpret the estimation results (Does this result
makes sense?).
(ii) Test if H0 : β7 = 0 (against H1 : β7 ̸= 0) and H0 : β8 = 0 (against H1 : β8 ̸= 0) based on the
estimation results given in (i). Interpret the test results.
(iii) Test if H0 : β7 = β8 = 0 (against H1 : H0 is not true) using the Wald, LR, and LM tests.
Report the test statistics and test results. (Use the 95% quantile of χ2(m) distribution for
correctly specified m.)
(iv) Implement the White’ test for heteroskedasticity. Report the test statistic and the test result.
Is heteroskedasticity detected? (Use the 95% quantile of χ2(m) distribution for correctly
specified m.)
(v) Report White’s robust standard errors of β̂7 and β̂8 and re-examine the hypotheses given in
(ii) using the computed standard errors.
Now include all the remaining variables as additional regressors.
(vi) Report the OLS estimates β̂7 (associated with attgood) and β̂8 (associated with attexc) with
their estimated standard errors (with no correction for heteroskedasticity/autocorrelation).
Compare the estimation results to those in (i) and interpret the difference.
(vii) Based on the results in (vi), discuss on potential problems that can occur in the linear
regression model (1) when you are interested in the effect of attgood and attexc.
2
Part II : Alcohol Abuse and Employment
Information on the dataset
The dataset for this exercise is obtained from the Journal of Applied Econometrics data archive.
This dataset was used to examine the effect of alcohol abuse on employment status as in the paper by
Terza, J.V. (2002, Journal of Applied Econometrics). Do your own analysis. For example, you can
1. do similar analysis as in the original paper.
2. focus on the effect(s) of some other variable(s).
3. implement various diagnostic checks.
4. test some hypotheses of interest.
Briefly state what you want to do and why. Report the results.
Notes:
1. Even if there is no limit in the range of topics that you can choose, please summarize all the
results within around one page. The computing code needs not to be attached.
2. This is an econometric exercise. Make sure your results do not include any opinion
and interpretation which are outside the field of economics/econometrics.
Information on the dataset
• abuse : take 1 if individual i abuses alcohol
• status : take 1 if individual i is out of workforce, take 2 if unemployed, take 3 if employed.
• unemrate : employment rate for the state where individual ’i’ resides.
• age : individual i’ age.
• educ : individual i’s years of schooling.
• married : if individual i is married.
• famsize : individual i’s family size.
• exhealth : take 1 if individual i is in excellent health.
• vghealth : take 1 if individual i is in very good health.
• goodhealth : take 1 if individual i is in good health.
• fairhealth : take 1 if individual i is in fair health
3
• northeast : take 1 if individual i lives in northeast US.
• midwest : take 1 if individual i lives in midwest US.
• south : take 1 if individual i lives in south US.
• centcity : take 1 if individual i lives in a central city of metropolitan area
• outercity : take 1 if individual i lives in a outer city of metropolitan area
• qrt1 (qrt2, qrt3) : takes 1 if individual i’s was interviewed in the first (second, third) quarter.
• beertax : state (where individual i resides) beer tax, $ per gallon.
• cigtax : state (where individual i resides) cigarette tax, $ per gallon.
• ethanol : state (where individual i resides) per-capita ethanol consumption.
• mothalc (fathalc) : take 1 if individual i’s mother (father) is an alcoholic.
• livealc : take 1 if individual i lives with an alcoholic.
• inwf : take 1 if individual i is in workforce (i.e., state > 1).

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1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A PHIL2617 PHYS3116 MIE250 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