LI Econometrics Stata Assignment
Hello, dear friend, you can consult us at any time if you have any questions, add WeChat: daixieit
LI Econometrics
Stata Assignment
In this assignment, you will explore correlates of earnings. You will use data on real individuals collected by the Office for National Statistics and published in the Quarterly Labour Force Survey. In the course of working on this assignment, you will:
. be introduced to an important source of data for research on the UK (the UK Data Service); . become familiar with processing and analysing data using Stata;
. interpret regression output;
. develop critical thinking about economic phenomena and econometric analysis of them.
Practical details
Marking criteria: see Assignment Remit.
Word limit: no more than 1000 words. Reasonable use of tables and igures does not count toward the word limit.
Submission ile: one ile (in .pdf or .doc format).
Figures and tables: should be numbered and titled appropriately. Tables should be formatted and presented as in standard economics journals (copy-pasted output from Stata is not acceptable).
Appendix: an appendix should be included at the end of the assignment, containing a copy of the Stata code used to obtain the results. This should be the exact code used to go from loading the dataset to generating the results presented (no more, no less). For convenience, you can simply copy and paste the .do ile.
Preliminaries
You will have accessed the data and documentation you need to complete this assignment during Computer Workshop 5. Please refer to that workshop and the accompanying guide on how to access the dataset (“Computer Workshop 5 – UK Data Service Access Instructions”).
0. Loading data and deining the sample
a) Load the main dataset (lfsp jm19 eul pwt18.dta) in Stata.
b) We will focus on individuals reporting positive gross weekly earnings and not currently working towards a qualiication. To keep only these observations, do:
keep if GRSSWK > 0 & QULNOW == 2
c) Check: the resulting dataset should contain 8949 observations. If this is not the case, something has gone wrong somewhere.
1. Marriage and earnings
a) Plot the distribution of weekly earnings (GRSSWK) in a histogram. Briely comment.
b) Construct a new variable by taking the logarithm of earnings (log(GRSSWK)). Using the variable detailing respondents’marital status (MARDY6), create a dummy variable taking a value of one if the respondent is married, cohabiting or in a civil partnership (“married”, for short). Finally, construct variables for respondents’age and age squared (the relevant variable is AGE). Then, estimate the regression:
log(earnings)i = α + β Married i + 1 Age i+ 2 Agei(2) + Ei (1)
Report your indings in a table and interpret all coefficients. Does marriage appear to have a signiicant impact on earnings? Why might that be?
c) Why is it important to account for respondents’age in equation 1? [Hint: think theoretically about how age correlates both with earnings and the probability of being married.]
2. Men and women
a) Create a dummy variable taking a value of one for female respondents (the relevant variable is SEX). Estimate equation 1 separately for men and women and report your indings in additional columns of the table you created above. What do you conclude about the impact of marriage on the earnings of men and women?
b) Interpret your indings using economic theory and intuition.
3. Other factors
a) Pick an additional dimension on which information is available in the dataset (consult the user manual and codebook (lfs user guide vol3 variabledetails2019.pdf) for details) and
construct variable(s) which allow you to explore the relationship between this dimension and earnings. Without running additional regressions (yet), why does economic theory tell you to expect this dimension to matter for earnings? Can we expect these dimensions to interact with the “marriage efect” or “gender efect” we explored already?
b) Estimate additional regressions to test whether your theoretical predictions hold in the data. Present these in a second table and discuss.
4. Taking a step back
a) In deining our sample, we kept only individuals reporting positive gross weekly earnings. Why might that afect any conclusions we draw about the efect of marriage on respondents’labour market outcomes?
b) In this assignment, you have used labour force data from the UK. For a diferent country of your choice, speculate on the diference in results you would expect to ind, if any, if you were to re-do this assignment using data from that country.
2023-11-27