1 research methods lecture 2 the dummies’ guide to stata wiji arulampalam 18/10/2006
TRANSCRIPT
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Research Methods
Lecture 2
The dummies’ guide to STATA
Wiji Arulampalam18/10/2006
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Econometrics Software
• You can use any software that does what you need
• See Timberlake for details of what does what well [www.timberlake.co.uk]
• PC Give is hard to beat for time series analysis– Microfit, EViews are good alternatives
• STATA does (just about) everything. • STATA (and everything else) is available as a
delivered application on the network.
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WHY STATA
• Need to know how to use STATA for (i) Econometrics A [next term](ii) Econometrics B [this term](iii) Panel Data Econometrics [next term]
• E-Views demo will be given by the Econometrics tutors!
• The above two should be sufficient
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STATA
• Hopefully you will have access by next week
• So full demo next week
• Stata command file wages.do and data file wages.dta on the module web page for you to practice
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STATA
• Use STATA: FOR– large survey datasets (merging them) – complex nonlinear models (e.g. LDV’s)
• But see also LimDep– nonparametric and evaluation methods– you want to
• continue studying economics • be a professional economist • learn something new
– you hate PC Give.
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Some useful websites
• Stata’s own resources for learning STATA– Stata website, Stata journal, Stata library, Statalist
archive– http://www.stata.com/links/resources1.html
• Michigan’s web-based guide to STATA (for SA)• UCLA resources to help you learn and use
STATA: – http://www. ats.ucla.edu/stat/stata – including movies and “web-books”
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Accessing STATA
Available from your ‘Delivered Applications’
Double click on icon!
Wstata.exe
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Buttons/Menu
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Enter commands here
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OR use the do editor to create a .do file
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Results window
Better to save the output – more later
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Click for Extensive Help OR
Type help in command line
help
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Type help in command line
help xxx
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14Exit, clear
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Click and point in v9
Exit, clear Menu/tabs
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Important features (1)
• NOTE– Always use lowercase in STATA– Otherwise you can get very confused
• More--more-- in your output window more output to come. [Press spacebar and the next page appears]– Command set more off turn this off
• Not enough memory [so reset!]– . set mem XXXm (allocate XXX mb of data)– . set matsize XXX (max matrix size XXX square)
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Important features (2)
• To Break– To stop anything hit the “break” (menu button with red
cross, or hit Ctrl and C simultaneously)
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Using data on disk (1)
• Opening a dataset
– datasets need to be rectangular
[variables in columns; observations in rows ]
– Stata datasets have a .dta extension
– Will read excel or text files
– Otherwise use Stat/Transfer to convert other format
files to stata files
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Using data on disk (2)
• There are several ways of getting data into STATA: eg: wages.dta
. use wages (or click: file/open on the menu bar)
. use lwage ed exp in 1/1000 if fem==1
. insheet using wages.csv (or .txt)
(imports an Excel csv file or a “text” file)
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Opens the file
List of variables
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Basic data reporting (1)
• .describe (or press F3 key)
– Lists the variable names and labels
• .describe using wages
– Lists the variable names etc WITHOUT loading the
data into memory (useful if the data is too big to fit)
• .codebook
– Tells you about the means, labels, missing values etc
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Basic data reporting (2)
• sort and count
– .sort personid
• sorts data by personid
– .count if personid==personid[_n-1]
• counts how many unique separate personids
• _n-1 is the previous observation
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First look at the data (1)
• .list lwage ed exp in 1/10 if fem>=0
– Lists the first 10 rows of var1 to var3 for which var4≥0
• .tab fem union (or tabulate)
[variables should be integers]
– gives a crosstab of fem vs union
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First look at the data (2)
• .summ fem union (or summarize or sum)– means, std devs etc for x1 and x2
• .corr ed exp in 1/100 if fem<1 (,cov)– correlation coeffs (or covariances) for selected data– .pwcorr ed exp lwage [does all pairwise corr coeffs]
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Tabulating (1)
• tab x1 x2 if x4==0, sum(x3)
– gives the means of x3 for each cell of the x1 vs x2 crosstabulation for observations where x4=0
• tab x1 x2, missing
– Includes the missing values
• tab x1 x2, nolabel
– Uses numeric codes instead of labels
– Eg “1” instead of “NorthWest” etc
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Tabulating (1)
• tab x1 x2, col– Gives % of column instead of count– Can get row percentages by using row instead– Or both by using row col
• table educ ethnic, c(mean wage) row col
– Customises the table so it includes the mean (or median or mx or count or sd ….) of wage by cells
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Labelling
• Always have your data comprehensively labelled.label data “This is pooled GHS 90-99”
.label variable reg “region”
.lab define reglab 0 “North” 1 “South” 2 “Middle”
.lab values region reglab
• Tedious to do for lots of variables– but then your output will be intelligibly labelled– other people will be able to understand it in future
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Data manipulation (1)
• Data can be renamed, recoded, and transformed:Command .generate or gen for short
. gen logrw=log((earn/hours)/rpi)
. gen agesq=age^2 (squares)
. gen region1=(region==1) (1 if true, 0 if not)
. gen ylagged=y[ _n-1 ]
(_n is the obs # in STATA)
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Data manipulation (2)
• Command recode:
. recode x1 .=0, 1/5=1 (. is missing value (mv))
. replace rate=rate/100
. replace age=25 if age==250
. egen meaninc=mean(income), by (region)
(see help egen for details)
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Data selection (1)
• You can also organise your data set with various commands:
. keep if _n<=1000 ( _n is the observation number)
. drop region
. drop if ethnic~=1
keeps only the first 1000 observations, drops region, and drops all the observations where the variable ethnic≠1 (~= is “not equal to”)
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Data selection (2)
• Then save the smaller file for subsequent analysis
. save newfile
. save, replace (take care – it overwrites existing file)
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Functions
• Lots of functions are possible. • See . help functions
– Obvious ones like• Log(), abs(), int(), round(), sqrt(), min(), max(), sum()
– And many very specialised ones.– Statistical functions
• distributions– String functions
• Converting strings to numbers and vice versa– Date functions
• Converting dates to numbers and vice versa– And lots more
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Command files
• Stata command files have a .do extension• It is ALWAYS good practice to use a .do file
– you will know exactly what you have done. – It makes it easy to develop ideas.– And correct mistakes.
• . do wages.do, nostop– (echoes to screen, and keeps going after error
encountered)
• Or . run wages.do (executes “silently”)
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Keeping track of output (1)
• Can scroll back your screen (upto a point)
• But better to open a log file at the beginning of your session, and close it at the end.
• Click on file, log, begin . Or type
. log using myoutput
. Commands……………………
. log close
[log command allows the replace and append options.]
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Keeping track of output (2)
• Default is .smcl file extension (that STATA can read)
• .log extension gives an ASCII file that anything can edit
• ALWAYS LOG your output
is a good way of developing a .do file – since it saves the commands as well as the output
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Next Lecture
Monday 23rd October F107 11:00-12:00
STATA demo