What are the returns to education working in the Lithuanian labour market in 2004? Are there differences due to gender, or ethn

****************************** Economic Activity at 2 digit level *******************;

gen econ =int(k7/10);

gen agfish=1 if econ<=5;

replace agfish=0 if agfish==.;

gen manufac=1 if econ>=15 & econ<=37;

replace manufac=0 if manufac==.;

gen electric=1 if econ==40;

replace electric=1 if econ==41;

replace electric=0 if electric==.;

gen mineconst=1 if econ==45;

replace mineconst=1 if econ==10;

replace mineconst=1 if econ==11;

replace mineconst=1 if econ==12;

replace mineconst=1 if econ==13;

replace mineconst=1 if econ==14;

replace mineconst=0 if mineconst==.;

gen retail=1 if econ==50;

replace retail=1 if econ==51;

replace retail=1 if econ==52;

replace retail=0 if retail==.;

gen hotel=1 if econ==55;

replace hotel=0 if hotel==.;

gen finance=1 if econ>=65 & econ<=74;

replace finance=0 if finance==.;

gen pubadmin=1 if econ==75;

replace pubadmin=0 if pubadmin==.;

gen educa=1 if econ==80;

replace educa=0 if educa==.;

gen health=1 if econ==85;

replace health=0 if health==.;

gen service=1 if econ>=90 & econ~=.;

replace service=0 if service==.;

gen transport=1 if econ>=60 & econ<=64;

replace transport=0 if transport==.;

gen sector=1 if agfish==1;

replace sector=2 if manufac==1;

replace sector=3 if electric==1;

replace sector=4 if mineconst==1;

replace sector=5 if retail==1;

replace sector=6 if hotel==1;

replace sector=7 if finance==1;

replace sector=8 if pubadmin==1;

replace sector=9 if educa==1;

replace sector=10 if health==1;

replace sector=11 if service==1;

******************************* Occupation at 2 digit level *************************;

*1110 are senior legislators and government officials but we only have listed 110 which I think is a mistake. Should

be 1110 NOT 110;

replace k8=1110 if k8==110;

gen occ= int(k8/1000);

gen admin=1 if occ==1;

replace admin=0 if admin==.;

gen prof=1 if occ==2;

replace prof=0 if prof==.;

gen clerk=1 if occ==3;

replace clerk=0 if clerk==.;

gen sell=1 if occ==4;

replace sell=0 if sell==.;

gen agfishocc=1 if occ==5;

replace agfishocc=0 if agfishocc==.;

gen craft=1 if occ==6;

replace craft=0 if craft==.;

gen plant=1 if occ==7;

replace plant=0 if plant==.;

gen element=1 if occ==8;

replace element=0 if element==.;

***************************** Location of where the Individual lives *******************;

destring territory_code, replace;

gen alytus_=1 if territory_code==110 | territory_code==150 | territory_code==334 | territory_code==594 | territory_code==384 | territory_code==157 | territory_code==337 | territory_code==597 | territory_code==387;

replace alytus_=0 if alytus_==.;

gen kaunas_=1 if territory_code==190 | territory_code==120 | territory_code==464 | territory_code==494 | territory_code==524 | territory_code==534| territory_code==694 | territory_code==724 | territory_code==127 | territory_code==467 | territory_code==497 | territory_code==527 | territory_code==537 | territory_code==697 | territory_code==727;

replace kaunas_=0 if kaunas_==.;

gen klaipeda_=1 if territory_code==210 | territory_code==230 | territory_code==250 | territory_code==554 | territory_code==564 | territory_code==754 | territory_code==884 | territory_code==557 | territory_code==567 | territory_code==757 | territory_code==887;

replace klaipeda_=0 if klaipeda_==.;

gen marijampole_=1 if territory_code==180 | territory_code==484 | territory_code==584 | territory_code==844 | territory_code==394 | territory_code==187 | territory_code==487 | territory_code==587 | territory_code==847 | territory_code==397;

replace marijampole_=0 if marijampole_==.;

gen panevezys_=1 if territory_code==270 | territory_code==364 | territory_code==574 | territory_code==664 | territory_code==674 | territory_code==734 | territory_code==367 | territory_code==577 | territory_code==667 | territory_code==677 | territory_code==737;

replace panevezys_=0 if panevezys_==.;

gen siauliai_=1 if territory_code==290 | territory_code==324 | territory_code==474 | territory_code==544 | territory_code==654 | territory_code==714 | territory_code==914 | territory_code==327 | territory_code==477 | territory_code==547 | territory_code==657 | territory_code==717 | territory_code==917;

replace siauliai_=0 if siauliai_==.;

gen taurage_=1 if territory_code==944 | territory_code==634 | territory_code==874 | territory_code==774 | territory_code==947 | territory_code==637 | territory_code==877 | territory_code==777;

replace taurage_=0 if taurage_==.;

gen telsiai_=1 if territory_code==614 | territory_code==684 | territory_code==744 | territory_code==784 | territory_code==617 | territory_code==687 | territory_code==747 | territory_code==787;

replace telsiai_=0 if telsiai_==.;

gen utena_=1 if territory_code==300 | territory_code==344 | territory_code==454 | territory_code==624 | territory_code==824 | territory_code==434 | territory_code==347 | territory_code==457 | territory_code==627 | territory_code==827 | territory_code==437;

replace utena_=0 if utena_==.;

gen vilnius_=1 if territory_code==010 | territory_code==134 | territory_code==424 | territory_code==854 | territory_code==894 | territory_code==864 | territory_code==794 | territory_code==814 | territory_code==414| territory_code==137| territory_code==427| territory_code==857| territory_code==897 | territory_code==867 | territory_code==797 | territory_code==817 | territory_code==417;

replace vilnius_=0 if vilnius_==.;

assert loc_~=0;

****************************** One variable for territory of where the Individual LIVES *************;

gen loc_=1 if vilnius_==1;

recode loc_ .=0;

recode loc_ 0=2 if alytus_==1;

recode loc_ 0=3 if kaunas_==1;

recode loc_ 0=4 if klaipeda_==1;

recode loc_ 0=5 if marijampole_==1;

recode loc_ 0=6 if panevezys_==1;

recode loc_ 0=7 if siauliai_==1;

recode loc_ 0=8 if taurage_==1;

recode loc_ 0=9 if telsiai_==1;

recode loc_ 0=10 if utena_==1;

assert loc_~=0;

,

Further Guide

You may organise your report as follows;

Session 1. Introduction

· Lithuanian labour market

· Mincer wage equation:

Session 2. Returns to education

Link theories (human capital and signalling theories) to empirical results.

Session 3. Wage discrimination

Link human capital model to empirical results.

Session 4. Tenure & work experience

Link human capital model to empirical results.

Session 5. Differences in wage between groups

Differences in education, sex, occupation, industry etc.

Session 6. Conclusion

Appendices (e.g. robustness checks)

References

Borjas, G. (2016) Labor economics. 7th ed. New York, N.Y: McGraw-Hill Education.

Outreg2

Please download this file from Princeton University.

https://www.princeton.edu/~otorres/Outreg2.pdf

Now, outreg2 is a user-written do-file for Stata (i.e. it was not written by the Stata Corporation but by a user of Stata). As such, you need to download this onto your version of Stata that you use.

Click on the Help tab in Stata:

Click on Search

Search for outreg2

Then, fifth result down:

Click on the link

Now click on install

Click here

You can now type help outreg2 at the command line for details on how to use this package. However, I give you details below.

STUDY AND ADAPT THIS DO-FILE!!

#delimit;

drop _all;

capture log close;

version 15.1;

*log results to a file called Lithuania.log;

log using "I:LSBUEconometricscoursework examplelecture4.log", replace;

*Loading the data set;

use "I:LSBUEconometricscoursework examplelecture4.dta",clear;

*******************************************************************;

*Generating variables;

gen wage=k18;

What is the difference between tenure and work experience? Which economic theories do these variables imply?

gen lnwage=log(wage);

gen tenure=2004-k26;

gen tensq=tenure*tenure;

gen exp=2004-k79;

gen expsq=exp*exp;

gen gender=1 if sex==2;

replace gender=0 if gender==.;

gen education=k77;

What is the command cd?

*******************************************************************;

What is ib1. representing? In Stata, search for Factor Variables for an explanation

*Doing analysis;

reg lnwage gender tenure tensq;

*Changing directory to my USB pen;

cd " "I:LSBUEconometricscoursework example";

outreg2 using results1.doc, replace;

reg lnwage gender tenure tensq ib1.education;

outreg2 using results1.doc, append;

*******************************************************************;

log close;

*Saving the data under a different name;

save " I:LSBUEconometricscoursework exampleseminar4.dta", replace;

Do you understand what is happening here?

Results Generated

You should get a set of results like this. If you don’t, put your hand up in class next week!

	(1)	(2)
VARIABLES	lnwage	lnwage
gender	-0.221***	-0.280***
	(0.0174)	(0.0161)
tenure	0.0255***	0.0181***
	(0.00294)	(0.00269)
tensq	-0.000529***	-0.000388***
	(8.88e-05)	(8.09e-05)
2.education		-0.564***
		(0.204)
3.education		-0.843***
		(0.227)
4.education		-0.832***
		(0.205)
5.education		-0.976***
		(0.204)
6.education		-1.055***
		(0.205)
7.education		-1.046***
		(0.204)
8.education		-1.139***
		(0.205)
9.education		-1.143***
		(0.208)
10.education		-1.114***
		(0.223)
11.education		-1.148***
		(0.242)
12.education		-1.263***
		(0.205)
13.education		-1.445***
		(0.231)
14.education		-1.133**
		(0.498)
Constant	6.418***	7.428***
	(0.0175)	(0.203)
Observations	3,442	3,442
R-squared	0.065	0.240

Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

From this table you should now be able to make the table look real professional. Marks will definitely be lost for those students who simply copy and paste and do not leave professional looking results in their report.

What does this mean?

,

Session 2018/2019, Semester 2	Coursework
Module:	Introduction to Econometrics
Module Code:	BBS_5_ECO
Instructions to Students · You are to write: · a professional REPORT in a Word document of approximately 2000 words. Marks will be awarded for presentation as well as content. · in a separate text file, you are to save your do-file(s) that you used to (a) generate the data used in your analysis, and that you used to (b) analyse the data. The do file(s) should also show how you created any figures that are used in the REPORT. · You are to upload through Moodle: · a Microsoft WORD file that contains your REPORT no later than 5 p.m. Friday 3rd MAY, 2019. Do not submit a PDF file, submit only a Word document. · for the same deadline, the do file you used should be uploaded · for the same deadline, the log file you generated from the do file should be uploaded · Do not copy and paste diagrams from publications. Generate all figures in Stata and copy into your report. Remember to save the coding you used to generate the report as a do file. No analysis or graphs should be done in Excel. All work analysing the data will be conducted in the econometric package Stata, version 15.1, available in all London Road computer suites, the Library, and the Learning Resource Centre.

The REPORT will have as its title:

“An Examination of the Lithuanian Labour Market during the first quarter of 2004”

You will use the data set supplied in Excel format that can be found on the Moodle site. No other data is to be used apart from this data set. This is an authentic household labour force survey data set purchased for research purposes.

You will aim, as a minimum, to answer four main questions. Using a Mincer wage equation:

1. What are the returns to education working in the Lithuanian labour market in 2004? Are there differences due to gender, or ethnicity? Explain and discuss.

2. Is there any evidence of wage discrimination within the labour market of Lithuania in 2004 based on age, gender, and ethnicity?

3. Examine and discuss the differences between tenure and work experience in helping to determine the wage in the labour market.

4. Examine and discuss the differences between working part-time and full-time in the labour market. This examination could look at the differences in wage between the groups; differences due to gender, ethnicity, or location, to name a few.

Many other questions can be addressed which could add content to the report especially when writing the general introduction to the labour market in Lithuania. Students should read the questionnaire for inspiration but as a minimum, the above four questions should be addressed in detail .

Advice to Students

· Be sure to use Equation Editor for writing out the functional form and specification of your estimating equations. The preceding is not optional. You must use Equation Editor.

· Whether you use standard errors, t values, or p values be clear to state what you have used but use one of the preceding.

· Report and explain the F statistic in any estimating equation.

· Explicitly comment in the report whether heteroscedasticity is an issue at any time and if so what you did about it. Report your tests for heteroscedasticity and make sure that these tests can be seen in the do file.

· Explicitly comment in the report whether multicollinearity was an issue at any time and if so what you did about it. Report your tests for heteroscedasticity and make sure that these tests can be seen in the do file.

· You should test to see whether the data you use in any estimating equation is actually normally distributed or not. Make sure you report the test and that the code can be seen in the do file.

· Make sure to comment on the goodness of fit of your estimating equations.

· Be clear in your report what hypothesis is being tested and whether you are using a one-tailed or two-tailed test for your hypothesis testing.

· Conduct tests of misspecification on any estimating equations. Make sure you report the test and that the code can be seen in the do file.

· Always interpret your estimated equations.

· Draw conclusions from your interpretations at the appropriate point in your report.

· Make recommendations at the appropriate point in your report.

· Always label your graphs, figures and diagrams. Insert tables of figures, equations, and tables at the start after your table of contents.

· The report should be a maximum of 2,000 words long excluding references and appendices. Near the start of your report there must be a table of contents. To generate a Table of Contents in Word use the Table of Contents feature:

If you have never used this before then go to: https://www.youtube.com/watch?v=ErIY5hrFMzc

Students who do not have a Table of Contents will have marks deducted.

Additional advice will be given in the seminar classes which you need to attend.

· Check your spelling before submission using the spellchecker in Microsoft Word . This is meant to be a professional report you are writing. Write in paragraphs.

· The REPORT should be referenced at the end using the Harvard Referencing style. Details of how to reference can be found at: https://my.lsbu.ac.uk/my/wcm/connect/9c19919b-d27d-430e-b821- 0e71bcecae22/harvard-referencing-helpsheet.pdf?MOD=AJPERES (Or simply Google Harvard Referencing LSBU to get the appropriate LSBU pdf file.)

Marking Criteria

Research (uncovering of information) 5 Marks

Systematic identification and use of a range of academic textbooks, many of which will be econometric textbooks, although not exclusively. Marks are awarded for the range of econometric and academic textbooks utilized and suitably referenced. Additional marks will be awarded to students who quote and utilize from econometric journals, although it is expected that at this study level this may be the exception rather than the rule. No marks are awarded for information gleaned from the Internet. Use of EconLit is encouraged and the only online information that will be allowed in this coursework has to be found through EconLit. If you reference an article, it should be a book available from the University library or available through EconLit.

Analysis 30 Marks

Analysis here refers to the examination, interpretation, and discussion of the results of your empirical econometric investigation as it relates to the assessment brief, where sources of material are both of a theoretical and empirical nature.

By results is meant not just regression results but tables of frequencies, and graphs produced using the data supplied for the coursework.

Subject Knowledge 30 Marks

Understanding and application of subject knowledge and underlying principles. Note that a student may state relevant knowledge in answering the coursework question, but may not apply such knowledge sufficiently in the analysis: having knowledge does not guarantee analysis. In addition, the application of subject knowledge will require technical competency which is explained below.

Technical Competency 15 Marks

This criteria is defined as the demonstration of the skills to enable the evaluation and execution of ideas appropriate to the assessment; E.g. well-thought out specifications are required for this econometric exercise; appropriate mathematical equations; appropriate theoretical diagrams which help answer the coursework question; logical analysis and discussion using appropriate theoretical concepts for discursive or quantitative style assessments; use of mathematical techniques where appropriate in more quantitative assessments. All tables, and diagrams, must be constructed by yourself and not copied and pasted.

Under this criteria, the Stata do file and Stata log file submitted will also be evaluated. The do file must contain a "date stamp" in its list of commands.

The preceding is not an exhaustive list.

Communication and Presentation 20 Marks

Clarity of purpose in the exposition of the assessment; skills in the selected mode of media in which the assessment is conducted (e.g. Equation Editor and drawing facility in Word both professionally utilized); awareness and adoption of appropriate conventions (e.g. use of Harvard referencing; punctuation, grammar, and English prose that reads well); awareness of the nature of the audience (is the assessment for the lecturer; a 'public' report; an academic audience); work approaching expected employer standards or publication standards in academic journals.

Under no circumstances should any figure be copied and pasted into the final coursework document that has not been created in the econometric package Stata. This includes tables of results generated within Stata. Appropriate do files should be used for producing results in a Word document. Marks will be deducted if this is not adhered to.

( 2 )

,

#delimit; drop _all; capture log close; version 15.1; *log results to a file called Lithuania.log; log using "I:LSBUEconometricscoursework exampleLithuania.log", replace; *Loading the data set; use "I:LSBUEconometricscoursework exampleLithuania.dta",clear; *Generating variables; gen wage=k18; gen lnwage=log(wage); gen tenure=2001-k26; gen tensq=tenure*tenure; gen exp=2001-k79; gen expsq=exp*exp; gen gender=1 if sex==2; replace gender=0 if gender==.; gen education=k77; *Doing analysis; reg lnwage gender tenure tensq; *Changing directory to my USB pen; cd "I:LSBUEconometricscoursework example"; outreg2 using results1.doc, replace; reg lnwage gender tenure tensq ib1.education; outreg2 using results1.doc, append; *******************************************************************; log close; *Saving the data under a different name; save "I:LSBUEconometricscoursework exampleLithuania1.dta", replace;

,

Approved by order No.213 adopted on

8 December 2003 by the Director General

of Statistics Lithuania

STATISTICS LITHUANIA

Employment Statistics division

Gedimino av. 29, 2746 Vilnius

LABOUR FORCE SAMPLE SURVEY GU – 01

Territory code

Reference week

Name of municipality, local administrative, village

No. quarter

2004

–

year month day month day

Give back: by 15 day on the morrow of month

Household No.

Persons interviewed: 15 years old and over

Respondent code

Sex

male

1

female

2

Confidentiality is guaranteed

Date of birth (day, month, year)

Personal code

EMPLOYMENT (Persons interviewed: 15 years old and over)

	1	Did you have a job for pay or profit during the reference week, or did you contribute family business or farm or were not working, but had a job or business?
	1	Yes				2
	2	No
	3	Was a conscript on compulsory military or community service				49
	2	Did you work during the reference week?
	1	Yes				6
	2	Was not working because on lay-off				3
	3	No				5
	3	Are you going to receive ≥ 50% of wage from your employer?
	1	Yes				6
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