程序代写案例-TERM 2021
时间:2021-05-07
SUMMER TERM 2021
DEPARTMENTALLY ARRANGED 24-HOUR ONLINE EXAMINATION COVER SHEET
ECON0019 QUANTITATIVE ECONOMICS AND ECONOMETRICS

ASSESSMENT COMPONENT: 40% 24-hour online examination
ASSESSMENT RELEASE: Friday 7th May 2021 at 09:00 (London time)
SUBMISSION DEADLINE: Saturday 8th May 2021 at 09:00 (London time)
The estimated time it should take to complete this examination is 3 hours
SUBMISSION INSTRUCTIONS
Please read and observe the following instructions to ensure anonymity in marking and compliance
with UCL’s assessment regulations.
1. Submission
All work must be uploaded via Moodle Assignment using the link provided in the module
Moodle page by the submission deadline and following the Module Leader’s instructions.
2. SoRAs and Extenuating Circumstances
a. Students with a SoRA, i.e. Reasonable Adjustments arrangements, should submit
their work within the 24-hour period as any additional time permitted by these
arrangements is covered by the long duration time of this examination.
b. If you have extenuating circumstances that affect your ability to submit your work
within the submission deadline, you should submit an Extenuating Circumstances
claim here. If you need assistance completing the claim, you should contact your
home department.
3. Submission Naming and Candidate Number
a. All work must be submitted anonymously using a file name that includes the
Candidate Number.
b. You can find your Candidate Number in your Portico account under ‘My Studies’ and
then the ‘Examinations’ container.
c. Include your Candidate Number at the top left-hand corner of the first page of your
work and in the file name.
4. Submission Format and Timing
a. Unless instructed otherwise by the Module Leader, the file containing your work
should be a PDF file. Your work can be handwritten or typed.
b. Allow sufficient time for submitting your work and once your submission has been
accepted by Moodle, take and save a screenshot. If you experience issues with
uploading your work go to Help & Support | Information Services Division - UCL –
University College London.
c. If the issue cannot be resolved by contacting ISD, contact the Module Administrator
and not the Module Leader.
5. Page Limit for this Examination:
a. The page limit for this examination is 5 pages. Please note that one page is one side
of a sheet of paper and the page size corresponds to A4 dimensions. The submission
can be handwritten or typed, but the font size should be no smaller than the
equivalent to an 11pt font size.
b. The page limit is meant to help you economise your explanations and write focused
and succinct answers. If you exceed the maximum number of pages, the mark will
be reduced by 10 percentage points, but the penalised mark will not be reduced
below the pass mark. Marks already at or below the pass mark will not be reduced.
6. No Significant Attempt: You will be awarded a mark of 0% in this examination when you: (1)
do not attempt the examination or, (2) attempt so little of the examination that it cannot be
assessed. Please refer to Section 3: Module Assessment | Academic Manual - UCL –
University College London on the consequences of not making a significant attempt.
7. Late Submissions
a. Markers mark the examination based on academic merit. If necessary, late
submission penalties will be applied administratively after marking.
b. The assessment submission link will allow work to be submitted up to 2 weeks late.
This arrangement is in place for students with Extenuating Circumstances.
c. Late Submission Penalties will be applied according to Section 3: Module Assessment
| Academic Manual - UCL – University College London.
8. Academic Misconduct
a. All students should be familiar with UCL’s assessment regulations on misconduct:
Section 9: Student Academic Misconduct Procedure | Academic Manual - UCL –
University College London
b. Examination offences include (but are not limited to) (self-)plagiarism, unauthorised
collaboration, falsification, contract cheating, and falsification of extenuating
circumstances. You should be familiar with: Academic Integrity | Students - UCL –
University College London.
9. Examination Paper Queries: If you suspect that there is an error or ambiguity in one or more
questions of your examination:
a. Do not communicate with the Module Leader or any student.
b. Make a reasonable assumption about what the question means and continue to
complete and submit your examination.
c. Use the Examination Paper Query Form available on the module Moodle page to
convey your query and, if relevant, any assumptions that you have made to enable
you to complete the question(s). Include the completed Examination Paper Query
Form as the first page of your submission.
SUMMER TERM 2021
DEPARTMENTALLY ARRANGED 24-HOUR ONLINE EXAMINATION
ECON0019: QUANTITATIVE ECONOMICS AND ECONOMETRICS
Answer BOTH questions.
1. In “Does Trade Cause Growth?” (American Economic Review, 1999), Je↵rey Frankel and David
Romer study the e↵ect of trade on income. Their simple specification is
log Yi = ↵+ Ti + Wi + "i,
where Yi is per capita income of country i, Ti is international trade, Wi is within-country trade,
and "i reflects other determinants of income. Since "i is likely to be correlated with the trade
variables, Frankel and Romer decide to use instrumental variables to estimate the coecients
and . As instruments, they use a measure of country’s geographic position (its proximity to
other countries) Pi and the country size Si.
(a) Explain in detail (step by step) how one can construct the instrumental variable estimates
ˆ and ˆ when one has data on Yi, Ti, Wi, Pi, and Si for a random sample of countries.
(b) Provide formal conditions for these estimates to be consistent. Which of them can be tested?
(c) Explain the economic intuition why the conditions from Question 1(b) may be satisfied in
this context. Also give at least one economic justification why at least one of them may be
violated.
(d) Suppose that, unfortunately, data on within-country trade Wi are not available. In order
to be able to estimate , the researchers add another assumption (on top of those you
proposed in item (b)): that Wi follows the model
Wi = ⌘ + Si + ⌫i,
and Pi is uncorrelated with ⌫i. Explain in detail (step by step) how one can estimate
from the data on Yi, Ti, Pi, and Si only and why that estimator will be consistent.
ECON0019 1 TURN OVER
(e) Suppose now it is known that = 0. Further, the true e↵ects of international trade on
income are heterogeneous across countries, denoted i, such that the true model for per
capita income is
log Yi = ↵+ iTi + "i.
Suppose the researchers estimate the regression of log Yi on Ti (and a constant), using Pi
as the single instrument. Under what condition would they asymptotically recover the
average causal e↵ect E[i]? Provide an economic justification for why this condition may
be violated in this context. Explain how to interpret the estimand of this IV procedure in
that case and the direction in which it may di↵er from the average causal e↵ect.
2. The transmission of human capital across generations has drawn attention for many decades
in Economics. Mikael Linhdahl, Marten Palme, Sofia Sadgren-Massih and Anna Sjogren (“A
Test of the Becker-Tomes Model of Human Capital Transmission Using Microdata on Four
Generations”, Journal of Human Capital, 2014) use Swedish data to examine this question
across several generations employing years of schooling as a measure for human capital.
(a) A simple version for the model entertained in their article, focussing on particular family,
is:
St = 0 + 1St1 + Et
where St is years of schooling for generation t and Et is “ability” for that generation. As-
sume that |1| < 1 so that stationarity and weak dependence hold. How would you test
whether Et is serially correlated in this particular context?
(b) Their model also postulates that ability is transmitted across generations according to:
Et = ↵0 + ↵1Et1 + Vt.
Assume that Vt is iid across generations, with mean zero and variance given by 2 > 0. If
↵1 6= 0 is contemporaneous exogeneity satisfied? Justify your answer. If one has data on
T generations, suggest a consistent estimator for ↵1 ⇥ 1 and a test for the null hypothesis
that ↵1 ⇥ 1 = 0. Explain your answer.
(c) Assume now that one has data on a cross-section with only two generations (“parent”
and “child”). Suppose that the data on years of schooling for the child only provides the
number of years when those are less than 12 years and, otherwise, one can only know that
an individual had 12 or more years of schooling. The data on years of schooling for the
parent is nonetheless complete, i.e., one observes the number of schooling years without the
restriction above. Let HEC be equal to 1 if the child has 12 or more years of education, and
ECON0019 2 CONTINUED
zero otherwise. Denote by SP the years of schooling for the parent. Consider the following
model:
HEC = 1(0 + 1 lnS
P + U 0).
Assume that U ⇠ N (0, 1) and notice that the regressor is the logarithm of SP . Write down
the log-likelihood function for the model above and a random sample of N families. How
would you estimate
E[@P(HEC = 1|SP )/@SP ]?
(d) Under the data scenario above (i.e., years of schooling for the child is censored at 12 years),
let SC be the child’s years of schooling. A friend is interested in the following regression:
SC = 0 + 1S
P + E
using this cross-sectional data. She suggests using only the uncensored observations (i.e.,
those for which SC < 12) and estimate the regression above with OLS. Will the estimator
consistently estimate 0 and 1? Explain your answer.
(e) Still on the regression from question 2(d), another friend instead suggests using a selection
model to estimate 0 and 1. Explain how you would construct such an estimator in this
particular setting.
ECON0019 3 END OF PAPER
























































































































































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