An introduction to Stata programming:
Gespeichert in:
1. Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
College Station, Texas
Stata Press
2016
|
Ausgabe: | Second editon |
Schriftenreihe: | A Stata Press publication
|
Schlagworte: | |
Online-Zugang: | Klappentext Inhaltsverzeichnis |
Beschreibung: | Literaturverzeichnis: Seite 397-402 |
Beschreibung: | xxii, 412 Seiten Diagramme |
ISBN: | 9781597181501 1597181501 |
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adam_text | An Introduction to Stata Programming, Second Edition covers three types of programming: do-
file programming, ado-file programming, and Mata functions that work in conjunction with
do- and ado-files. Baum emphasizes how you can usefully automate your work with Stata
and how programming can help you use Stata more effectively. The introductory chapters
discuss the benefits of learning Stata programming, and they present elementary concepts of
the command-line interface and some commonly used tools for working with programs and
datasets.
Tliis second edition contains several new sections and examples, and it has been completely
updated for Stata 14. In particular, Baum has added discussions of major additions to Stata,
including the margins and marginsplot commands, the gmm command, factor-variable
operators, the putexcel command, and other new import and export features.
The format of the book is unique among Stata-oriented texts. Beginning with chapter 4,
each even-numbered chapter is a “cookbook” chapter containing several “recipes”, 47 in
total. Each recipe presents a specific problem: how can I perform a certain task with Stata
programming? The recipe then provides a complete solution to the problem and discusses
how the features presented in the previous chapter can be best put to use. The major focus
of the book is do-file programming; the last four chapters discuss ado-file programming and
Mata, Statas matrix programming language. This includes a complete, concise introduction
to Mata, with numerous examples of its usefulness. The Mata coverage discusses Mata-based
likelihood function evaluators and the use of associative arrays.
Contents
1
2
List of figures
List of tables
Preface
Acknowledgments
Notation and typography
Why should you become a Stata programmer?
Do-file programming..................................
Ado-file programming ................................
Mata programming for ado-files.......................
1.1 Plan of the book.............................................
1.2 Installing the necessary software ...........................
Some elementary concepts and tools
2.1 Introduction.................................................
2.1.1 What you should learn from this chapter..............
2.2 Navigational and organizational issues.......................
2.2.1 The current working directory and profile.do.........
2.2.2 Locating important directories: sysdir and adopath . . .
2.2.3 Organization of do-files, ado-files, and data files..
2.3 Editing Stata do- and ado-files .............................
2.4 Data types...................................................
2.4.1 Storing data efficiently: The compress command . . . .
2.4.2 Date and time handling ..............................
2.4.3 Time-series operators................................
2.4.4 Factor variables and operators.......................
xvii
xix
xxi
xxiii
xxv
1
2
2
2
3
4
5
5
5
5
6
6
7
8
9
11
11
13
14
Contents
viii
2.5 Handling errors: The capture command.............................. 16
2.6 Protecting the data in memory: The preserve and restore commands 17
2.7 Getting your data into Stata ..................................... 18
2.7.1 Inputting and importing data.............................. 18
Handling text files ...................................... 19
Free format versus fixed format......................... 20
The import delimited command.............................. 21
Accessing data stored in spreadsheets................... 23
Fixed-format data files................................... 24
2.7.2 Importing data from other package formats ................ 29
2.8 Guidelines for Stata do-file programming style.................... 30
2.8.1 Basic guidelines for do-file writers...................... 31
2.8.2 Enhancing speed and efficiency............................ 33
2.9 How to seek help for Stata programming............................ 33
3 Do-file programming: Functions, macros, scalars, and matrices 37
3.1 Introduction...................................................... 37
3.1.1 What you should learn from this chapter................... 37
3.2 Some general programming details.................................. 38
3.2.1 The varlist............................................... 39
3.2.2 The numlist............................................... 39
3.2.3 The if exp and in range qualifiers........................ 39
3.2.4 Missing-data handling..................................... 40
Recoding missing values: The mvdecode and mvencode
commands......................................... 41
3.2.5 String-to-numeric conversion and vice versa............... 42
Numeric-to-string conversion.............................. 43
Working with quoted strings............................... 44
3.3 Functions for the generate command................................ 44
3.3.1 Using if exp with indicator variables .................... 47
3.3.2 The cond() function ...................................... 49
Contents ix
3.3.3 Recoding discrete and continuous variables.............. 49
3.4 Functions for the egen command.................................... 51
Official egen functions .................................. 52
egen functions from the user community.................. 53
3.5 Computation for by-groups ........................................ 54
3.5.1 Observation numbering: _n and _N........................ 55
3.6 Local macros...................................................... 57
3.7 Global macros..................................................... 60
3.8 Extended macro functions and macro list functions................. 60
3.8.1 System parameters, settings, and constants: creturn .... 62
3.9 Scalars........................................................... 62
3.10 Matrices.......................................................... 64
4 Cookbook: Do-file programming I 67
4.1 Tabulating a logical condition across a set of variables.......... 67
4.2 Computing summary statistics over groups ......................... 69
4.3 Computing the extreme values of a sequence........................ 70
4.4 Computing the length of spells.................................... 71
4.5 Summarizing group characteristics over observations............... 76
4.6 Using global macros to set up your environment.................... 78
4.7 List manipulation with extended macro functions................... 79
4.8 Using creturn values to document your work........................ 81
5 Do-file programming: Validation, results, and data management 83
5.1 Introduction...................................................... 83
5.1.1 What you should learn from this chapter................. 83
5.2 Data validation: The assert, count, and duplicates commands .... 83
5.3 Reusing computed results: The return and ereturn commands .... 90
5.3.1 The ereturn list command.................................. 94
5.4 Storing, saving, and using estimated results...................... 97
5.4.1 Generating publication-quality tables from stored estimates 102
5.5 Reorganizing datasets with the reshape command................... 104
x Contents
5.6 Combining datasets.............................................. 109
5.7 Combining datasets with the append command..................... Ill
5.8 Combining datasets with the merge command....................... 113
5.8.1 The one-to-one match-merge.............................. 115
5.8.2 The dangers of many-to-many merges...................... 116
5.9 Other data management commands.................................. 117
5.9.1 The fillin command...................................... 117
5.9.2 The cross command....................................... 117
5.9.3 The stack command ...................................... 118
5.9.4 The separate command.................................... 119
5.9.5 The joinby command...................................... 120
5.9.6 The xpose command....................................... 121
6 Cookbook: Do-file programming II 123
6.1 Efficiently defining group characteristics and subsets.......... 123
6.1.1 Using a complicated criterion to select a subset of observations 124
6.2 Applying reshape repeatedly..................................... 125
6.3 Handling time-series data effectively........................... 129
6.3.1 Working with a business-daily calendar................. 132
6.4 reshape to perform rowwise computation.......................... 133
6.5 Adding computed statistics to presentation-quality tables....... 136
6.6 Presenting marginal effects rather than coefficients............ 138
6.6.1 Graphing marginal effects with marginsplot ............ 140
6.7 Generating time-series data at a lower frequency................ 141
6.8 Using suest and gsem to compare estimates from nonoverlapping
samples........................................................ 146
6.9 Using reshape to produce forecasts from a VAR or VECM........... 149
6.10 Working with IRF files......................................... 152
7 Do-file programming: Prefixes, loops, and lists 157
7.1 Introduction.................................................... 157
7.1.1 W hat you should learn from this chapter............... 157
Contents x
7.2 Prefix commands.................................................. 157
7.2.1 The by prefix............................................ 158
7.2.2 The statsby prefix....................................... 160
7.2.3 The xi prefix and factor-variable notation .............. 161
7.2.4 The rolling prefix....................................... 162
7.2.5 The simulate and permute prefixes........................ 164
7.2.6 The bootstrap and jackknife prefixes..................... 167
7.2.7 Other prefix commands.................................... 169
7.3 The forvalues and foreach commands............................... 169
8 Cookbook: Do-file programming III 177
8.1 Handling parallel lists ......................................... 177
8.2 Calculating moving-window summary statistics..................... 178
8.2.1 Producing summary statistics with rolling and merge .... 180
8.2.2 Calculating moving-window correlations................... 181
8.3 Computing monthly statistics from daily data..................... 182
8.4 Requiring at least n observations per panel unit................. 184
8.5 Counting the number of distinct values per individual ........... 185
8.6 Importing multiple spreadsheet pages............................. 186
9 Do-file programming: Other topics 189
9.1 Introduction..................................................... 189
9.1.1 What you should learn from this chapter.................. 189
9.2 Storing results in Stata matrices ............................... 189
9.3 The post and post file commands.................................. 193
9.4 Output: The export delimited, outfile, and file commands......... 196
9.5 Automating estimation output .................................... 199
9.6 Automating graphics.............................................. 503
9.7 Characteristics ................................................. 207
10 Cookbook: Do-file programming TV 211
10.1 Computing firm-level correlations with multiple indices...........211
10.2 Computing marginal effects for graphical presentation.............214
Contents
xii
10.3 Automating the production of DT^X tables......................... 216
10.4 Extracting data from graph files’ sersets........................ 220
10.5 Constructing continuous price and returns series ................ 225
11 Ado-file programming 231
11.1 Introduction..................................................... 231
11.1.1 What you should learn from this chapter................. 232
11.2 The structure of a Stata program................................. 232
11.3 The program statement ........................................... 233
11.4 The syntax and return statements ................................ 234
11.5 Implementing program options..................................... 237
11.6 Including a subset of observations............................... 238
11.7 Generalizing the command to handle multiple variables............ 240
11.8 Making commands byable........................................... 242
Program properties....................................... 243
11.9 Documenting your program......................................... 244
11.10 egen function programs ......................................... 246
11.11 Writing an e-class program ..................................... 248
11.11.1 Defining subprograms..................................... 250
11.12 Certifying your program......................................... 250
11.13 Programs for ml, nl, and nlsur.................................. 252
Maximum likelihood estimation of distributions’ parameters 255
11.13.1 Writing an ml-based command ............................ 260
11.13.2 Programs for the nl and nlsur commands.................263
11.14 Programs for gmm................................................ 265
11.15 Programs for the simulate, bootstrap, and jackknife prefixes.... 270
11.16 Guidelines for Stata ado-file programming style..................272
11.16.1 Presentation............................................. 273
11.16.2 Helpful Stata features ................................. 274
11.16.3 Respect for datasets ................................... 274
11.16.4 Speed and efficiency ................................... 275
Contents
xiii
11.16.5 Reminders................................................. 275
11.16.6 Style in the large........................................ 276
11.16.7 Use the best tools........................................ 276
12 Cookbook: Ado-file programming 277
12.1 Retrieving results from rolling.................................... 277
12.2 Generalization of egen function pct9010() to support all pairs of
quantiles.......................................................... 280
12.3 Constructing a certification script................................ 282
12.4 Using the ml command to estimate means and variances.............287
12.4.1 Applying equality constraints in ml estimation..............289
12.5 Applying inequality constraints in ml estimation .................. 291
12.6 Generating a dataset containing the longest spell.................. 294
12.7 Using suest on a fixed-effects model............................... 297
13 Mata functions for do-file and ado-file programming 301
13.1 Mata: First principles............................................. 301
13.1.1 What you should learn from this chapter.................... 302
13.2 Mata fundamentals.................................................. 302
13.2.1 Operators.................................................. 303
13.2.2 Relational and logical operators........................... 304
13.2.3 Subscripts................................................. 305
13.2.4 Populating matrix elements................................. 305
13.2.5 Mata loop commands......................................... 307
13.2.6 Conditional statements..................................... 308
13.3 Mata’s st_ interface functions..................................... 309
13.3.1 Data access................................................ 309
13.3.2 Access to locals, globals, scalars, and matrices............311
13.3.3 Access to Stata variables’ attributes ..................... 312
13.4 Calling Mata with a single command line ..................... 312
13.5 Components of a Mata function...................................... 316
13.5.1 Arguments.................................................. 316
XIV
Contents
13.5.2 Variables.................................................. 317
13.5.3 Stored results............................................. 317
13.6 Calling Mata functions............................................. 318
13.7 Example: st_ interface function usage.............................. 320
13.8 Example: Matrix operations......................................... 322
13.8.1 Extending the command...................................... 327
13.9 Mata-based likelihood function evaluators.......................... 329
13.10 Creating arrays of temporary objects with pointers.................331
13.11 Structures........................................................ 334
13.12 Additional Mata features ......................................... 337
13.12.1 Macros in Mata functions ................................. 337
13.12.2 Associative arrays in Mata functions...................... 338
13.12.3 Compiling Mata functions.................................. 340
13.12.4 Building and maintaining an object library................ 341
13.12.5 A useful collection of Mata routines...................... 342
14 Cookbook: Mata function programming 343
14.1 Reversing the rows or columns of a Stata matrix ................... 343
14.2 Shuffling the elements of a string variable........................ 346
14.3 Firm-level correlations with multiple indices with Mata............ 348
14.4 Passing a function to a Mata function.............................. 353
14.5 Using subviews in Mata............................................. 356
14.6 Storing and retrieving country-level data with Mata structures . . . 358
14.7 Locating nearest neighbors with Mata............................... 363
14.8 Using a permutation vector to reorder results...................... 368
14.9 Producing UTgX tables from svy results............................. 370
14.10 Computing marginal effects for quantile regression................ 375
14.11 Computing the seemingly unrelated regression estimator............ 379
14.12 A GMM-CUE estimator using Mata s optimizeQ functions.............. 384
Contents
XV
References
Author index
Subject index
397
403
405
|
any_adam_object | 1 |
author | Baum, Christopher F. 1951- |
author_GND | (DE-588)128792612 |
author_facet | Baum, Christopher F. 1951- |
author_role | aut |
author_sort | Baum, Christopher F. 1951- |
author_variant | c f b cf cfb |
building | Verbundindex |
bvnumber | BV043276913 |
classification_rvk | ST 601 MR 2100 CM 2500 |
classification_tum | DAT 307f |
ctrlnum | (OCoLC)937388659 (DE-599)BSZ45287212X |
dewey-full | 519.5028553 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.5028553 |
dewey-search | 519.5028553 |
dewey-sort | 3519.5028553 |
dewey-tens | 510 - Mathematics |
discipline | Informatik Soziologie Psychologie Mathematik |
edition | Second editon |
format | Book |
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language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028698407 |
oclc_num | 937388659 |
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physical | xxii, 412 Seiten Diagramme |
publishDate | 2016 |
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spelling | Baum, Christopher F. 1951- Verfasser (DE-588)128792612 aut An introduction to Stata programming Christopher F. Baum, Department of Economics and School of Social Work, Boston College Second editon College Station, Texas Stata Press 2016 xxii, 412 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier A Stata Press publication Literaturverzeichnis: Seite 397-402 Stata (DE-588)4617285-3 gnd rswk-swf Stata (DE-588)4617285-3 s DE-604 Überarbeitung von 2009 978-1-59718-045-0 (DE-604)BV035366915 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028698407&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Klappentext Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028698407&sequence=000002&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 2 |
spellingShingle | Baum, Christopher F. 1951- An introduction to Stata programming Stata (DE-588)4617285-3 gnd |
subject_GND | (DE-588)4617285-3 |
title | An introduction to Stata programming |
title_auth | An introduction to Stata programming |
title_exact_search | An introduction to Stata programming |
title_full | An introduction to Stata programming Christopher F. Baum, Department of Economics and School of Social Work, Boston College |
title_fullStr | An introduction to Stata programming Christopher F. Baum, Department of Economics and School of Social Work, Boston College |
title_full_unstemmed | An introduction to Stata programming Christopher F. Baum, Department of Economics and School of Social Work, Boston College |
title_short | An introduction to Stata programming |
title_sort | an introduction to stata programming |
topic | Stata (DE-588)4617285-3 gnd |
topic_facet | Stata |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028698407&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028698407&sequence=000002&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT baumchristopherf anintroductiontostataprogramming |