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008 250107s2025 flu gob 001 0 eng d
040 _aOCoLC-P
_beng
_erda
_epn
_cOCoLC-P
020 _a9781003100263
_q(electronic bk.)
020 _a1003100260
_q(electronic bk.)
020 _z9780367554460
020 _a9781040298220
_q(electronic bk. : PDF)
020 _a1040298222
_q(electronic bk. : PDF)
020 _z9780367569921
020 _a9781040298244
_q(electronic bk. : EPUB)
020 _a1040298249
_q(electronic bk. : EPUB)
024 7 _a10.1201/9781003100263
_2doi
035 _a(OCoLC)1483105609
035 _a(OCoLC-P)1483105609
050 4 _aHB172
072 7 _aBUS
_x021000
_2bisacsh
072 7 _aKC
_2bicssc
100 1 _aCroissant, Yves,
_d1969-
_eauthor.
_1https://id.oclc.org/worldcat/entity/E39PBJw4yVK4tMqfkbBwb8Pfbd
_992761
245 1 0 _aMicroeconometrics with R /
_cYves Croissant.
250 _aFirst edition.
264 1 _aBoca Raton, FL :
_bCRC Press,
_c2025.
300 _a1 online resource (xxii, 494 pages).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aChapman & Hall/CRC the R series
505 0 _aPreface Part 1. The ordinary least square estimator 1. Simple linear regression model 2. Statistical properties of the simple linear estimator 3. Multiple Regression Model 4. Interpretation of the Coefficients Part 2. Beyond the OLS estimator 5. Maximum likelihood estimator 6. Non-spherical disturbances 7. Endogeneity 8. Treatment Effect 9. Spatial econometrics Part 3. Special responses 10. Binomial models 11. Censored and truncated models 12. Count data 13. Duration models 14. Discrete choice models References Indexes
520 _a"This book is about doing microeconometrics, defined by Cameron and Trivedi (2005) as the analysis of individual-level data on the economic behavior of individuals or firms using regression methods applied to cross-section and panel data with R. Microeconometrics became increasingly popular in the last decades, thanks to the availability of many individual data sets and to the development of computer performance. R appeared in the late nineties as a clone of S. It became increasingly popular among statisticians, especially in fields where S was widely used. 20 years ago, using R for doing econometrics analysis required a lot of programming because a lot of core methods of econometrics were not available in R. Nowadays, most of the basic methods described in the book are available in contributed packages. Moreover, the set of packages called the tidyverse developed by Rstudio (now Posit) for all the basic tasks of an applied statistician (importing, tidying, transforming and visualizing data set) makes the use of R faster and easier. The book uses extensively specialized econometrics packages and the tidyverse and seeks to demonstrate that the adoption of R as the primary software for an econometrician is a relevant choice. The first part of the book is devoted to the ordinary least square estimator. Matrix algebra is progressively introduced in this part and a special attention is paid on the interpretation of the estimated coefficients. The second part goes beyond the basic OLS estimator by testing the hypothesis on which this estimator is based on and providing more complex estimators relevant when some of these hypotheses are violated. Finally, the third part of the book presents specific estimators devoted to special responses, eg count, binomial or duration data"--
_cProvided by publisher.
588 _aOCLC-licensed vendor bibliographic record.
650 7 _aBUSINESS & ECONOMICS / Econometrics
_2bisacsh
_992762
650 0 _aMicroeconomics.
_958393
650 0 _aR (Computer program language)
_965001
830 0 _aChapman & Hall/CRC the R series (CRC Press)
_965439
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781003100263
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 _cE-Books
999 _c67387
_d67387