{"product_id":"using-python-for-introductory-econometrics-paperback-1","title":"Using Python for Introductory Econometrics - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eDaniel Brunner\u003c\/b\u003e (Author), \u003cb\u003eFlorian Heiss\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e \u003cli\u003e\n\u003cb\u003eIntroduces\u003c\/b\u003e the popular, powerful and free programming language and software package \u003cb\u003e\u003ci\u003ePython\u003c\/i\u003e\u003c\/b\u003e\n\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003eFocus\u003c\/b\u003e: implementation of standard tools and methods used in \u003cb\u003eeconometrics\u003c\/b\u003e\n\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003eCompatible\u003c\/b\u003e with \u003cb\u003e\"Introductory Econometrics\"\u003c\/b\u003e by Jeffrey M. Wooldridge in terms of topics, organization, terminology and notation\u003c\/li\u003e \u003cli\u003eCompanion \u003cb\u003ewebsite\u003c\/b\u003e with full text, all code for download and other goodies\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cb\u003eTopics: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e \u003cli\u003eA gentle introduction to \u003ci\u003ePython\u003c\/i\u003e\n\u003c\/li\u003e \u003cli\u003eSimple and multiple regression in matrix form and using black box routines\u003c\/li\u003e \u003cli\u003eInference in small samples and asymptotics\u003c\/li\u003e \u003cli\u003eMonte Carlo simulations\u003c\/li\u003e \u003cli\u003eHeteroscedasticity\u003c\/li\u003e \u003cli\u003eTime series regression\u003c\/li\u003e \u003cli\u003ePooled cross-sections and panel data\u003c\/li\u003e \u003cli\u003eInstrumental variables and two-stage least squares\u003c\/li\u003e \u003cli\u003eSimultaneous equation models\u003c\/li\u003e \u003cli\u003eLimited dependent variables: binary, count data, censoring, truncation, and sample selection\u003c\/li\u003e \u003cli\u003eFormatted reports using Jupyter Notebooks\u003c\/li\u003e\n\u003c\/ul\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 430\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.87 x 10 x 8 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e May 25, 2020\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47204996448505,"sku":"9798648436763","price":36.32,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/N3ZReU1mSFV3ZDFucGJUUmtkckxoQT09_9b985c4a-5888-49bd-afd5-1ff56147ff11.webp?v=1768022697","url":"https:\/\/bookscloud.io\/products\/using-python-for-introductory-econometrics-paperback-1","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}