Applied Microeconometrics - Introduction to stata 2 ... · Applied Microeconometrics Introduction...

Applied MicroeconometricsIntroduction to stata 2: Beyond variables

Loops, macros, scalars (& graphs if we have time)

Alessandro Martinello

alfa 4035B

[email protected]

AM’s reminders

Mail policyNO content questions by emailAsk during/between classes or just walk over to α 4035B

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Last time

What is stata

Opening dataset (use [using] [if])

VariablesCreating and replacing (gen, gen, replace)Data selection (booleans, [if])Descriptive statistics (tabulate, table, summarize [, detail])Variable types and labels

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Other data in stata

MacrosGlobals, localsLoops

ResultsAccessing and storing them

Scalars (and matrices)

If time, graphs

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Macros as strings

Store and repeat text

Globals: e.g. global variables age female ln wageLasts all session, across files (clear all)Access as $variables

Locals: e.g. local variables age female ln wageLasts only while command (do-file) is executedAccess as ‘variables’ (grave accent - apostrophe)Invoked in loops

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Working with macros

Loops

foreach name in/of, forval name = numlistCommands between braces repeated‘name’ accessed as localSee also while (and if)

In regressionsOLS: reg depvar indepvar(s) [if] [, options ]

depvar indepvars can be macros/varlistInteraction syntax: i.discrete, c.continuous, #, ##Shortcuts for varlist: *, ?

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Acccessing results

Saved resultsIn e()/r(), see command help fileEstimation results: b[varname], se[varname]Save them as macros, scalars or matrix

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Graphs - examples: connectedFiscal revenue over GDP of selected countries over time

2030

4050

% o

f GD

P

1960 1970 1980 1990 2000 2010Year

Sweden Italy USGreece Germany Denmark

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Graphs - examples: scatterParticipation in financial markets over intelligence, DK

.1.2

.3.4

60 80 100 120 140BPP score (IQ scale)

<7th grade 8th grade or more Tertiary educ.

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Graphs - examples: kdensityCorrelation between intelligence and schooling, DK

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3

60 80 100 120 140 160BPP score (IQ scale)

<7th grade 8th grade or more Tertiary educ.

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Graphs - examples: spmapDistance to closest public school, DK (1950)

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Stata - graphing machine

help graphhelp twoway: combined with data management tools can doalmost anything

graph export mydir/mygraph.myformat, replace

Stata defaults are ugly - but can be easily changed

GUI interface / script (do-files)Repeatability (loops)

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Plotting demographic evolutions

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

-10 -5 0 5 10Population in millions

Males Females

Population by Age, Japan 1950

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00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+

00-0405-0910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485+


Males Females


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Applied Microeconometrics - Introduction to stata 2 ... · Applied Microeconometrics Introduction...

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