Session1(approx. 3 hours)
 Using Stata programming: somefundamental concepts
 • Should youbea Stataprogrammer?
 • Overview of the Stataenvironment
 • Do-andado-filesinStata
 • Producingreproducibleresearchresults
 • Workingwith the commandline
 • Datatypes
 • Time seriesoperators
 • Factorvariables 
 • Debugging andtracing
 • Protecting yourdata
 • Guidelinesforwritingdo-files
 Session2(approx. 3 hours)
 Programming Stata do-files
 • Workingwith missingvalues
 • Recodingdiscreteandcontinuousvariables
 • Generate and egenfunctions
 • Transformationofstringandnumericvariables
 • Local macros andscalars
 • Looping commands: forvalues andforeach
 • Globalmacros
 • Extended macro functions and listfunctions
 • Statamatrices
 
 • Prefix commands: by,statsby,rolling
 • Combining data sets with append andmerge
 • Transformingdatawithreshape
 Session3(approx. 1.5 hours)
 Programming concepts and toolsin action
 • Toolsfor do-fileauthors
 • Loopingoverobservations is rarelyappropriate
 • Thebyprefixcanoftenreplacealoop
 • Repeatedstatementsareusuallynotneeded
 • Somesimplecommandsareoftenoverlooked
 • Reusingresults:returnandereturncommands
 • Tabulating and computing groupstatistics
 • Summarizinggroupcharacteristicsoverobservations
 • Addingaggregatecharacteristicstomicroobservations
 • Computing durations andspells
 • Aggregatingtransactionsdata
 Session4(approx. 1.5 hours)
 Automation with do-fileprogramming
 • Statas post and postfilecommands
 • Production of summarystatistics
 • Production of estimatestables
 • Productionofsetsoftablesandgraphs
 
 Session5(approx. 3 hours)
 Ado-file programming
 • Structure of anado-file
 • The syntaxstatement
 • Includingasubsetofobservations
 • Using programoptions
 • Temporaryvariablesandtempnames
 • The returnstatement
 • A sampleprogram
 • A second example of ado-fileprogramming
 • A third example of ado-fileprogramming
 • Maximumlikelihoodestimation
 • Nonlinear least squaresestimation
 • Writingan egenfunction
 • Programs forgmm
 • ado-files for Monte Carlosimulation
 • Writingan e-classprogram
 
 Session6(approx. 4 hours)
 Introduction to Mata
 • Matafundamentals
 • Syntax of thelanguage
 • DesignofaMatafunction
 • Matasinterfacefunctions
 • A simple Matafunction
 • A multi-variablefunction
 • Example of Mataprogramming
 • Mata-basedlikelihoodfunctionevaluators
 • Creating arrays of temporary objects withpointers
 • Matastructures
 • A Mata-based estimationroutine
 Recommended reading:AnIntroduction to Modern Econometrics Using Stata, Stata Press, 2006; Chinesetranslation available from Renmin University Press.
 AnIntroduction to Stata Programming, Second Edition,Stata Press, 2016.