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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

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