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Author: Francis Amasa Walker
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 496
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Book Description
Author: Francis Amasa Walker
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 496
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Book Description
Author: Aman Ullah
Publisher: CRC Press
ISBN: 1482269902
Category : Business & Economics
Languages : en
Pages : 646
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Book Description
This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.
Author: John McMillan
Publisher: W. W. Norton & Company
ISBN: 0393323714
Category : Business & Economics
Languages : en
Pages : 289
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Book Description
McMillan takes readers on a lively tour, from the wild swings of the stock market to the online auctions of eBay to the unexpected twists of the world's post-communist economies.
Author: Davis R. Dewey
Publisher:
ISBN:
Category :
Languages : en
Pages : 454
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Book Description
Author: Jan Ubøe
Publisher: Springer
ISBN: 3319709364
Category : Business & Economics
Languages : en
Pages : 474
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Book Description
This textbook discusses central statistical concepts and their use in business and economics. To endure the hardship of abstract statistical thinking, business and economics students need to see interesting applications at an early stage. Accordingly, the book predominantly focuses on exercises, several of which draw on simple applications of non-linear theory. The main body presents central ideas in a simple, straightforward manner; the exposition is concise, without sacrificing rigor. The book bridges the gap between theory and applications, with most exercises formulated in an economic context. Its simplicity of style makes the book suitable for students at any level, and every chapter starts out with simple problems. Several exercises, however, are more challenging, as they are devoted to the discussion of non-trivial economic problems where statistics plays a central part.
Author: Dale J. Poirier
Publisher: MIT Press
ISBN: 9780262161497
Category : Business & Economics
Languages : en
Pages : 744
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Book Description
The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses-giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from the truth, argues Dale Poirier, who has developed a course for teaching comparatively both the classical and the Bayesian approaches to econometrics. Poirier's text provides a thoroughly modern, self-contained, comprehensive, and accessible treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model. Written primarily for advanced undergraduate and graduate students who are pursuing research careers in economics, Intermediate Statistics and Econometrics offers a broad perspective, bringing together a great deal of diverse material. Its comparative approach, emphasis on regression and prediction, and numerous exercises and references provide a solid foundation for subsequent courses in econometrics and will prove a valuable resource to many nonspecialists who want to update their quantitative skills. The introduction closes with an example of a real-world data set-the Challengerspace shuttle disaster-that motivates much of the text's theoretical discussion. The ten chapters that follow cover basic concepts, special distributions, distributions of functions of random variables, sampling theory, estimation, hypothesis testing, prediction, and the linear regression model. Appendixes contain a review of matrix algebra, computation, and statistical tables.
Author: Diane Coyle
Publisher: Princeton University Press
ISBN: 0691231036
Category : Business & Economics
Languages : en
Pages : 272
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Book Description
How economics needs to change to keep pace with the twenty-first century and the digital economy Digital technology, big data, big tech, machine learning, and AI are revolutionizing both the tools of economics and the phenomena it seeks to measure, understand, and shape. In Cogs and Monsters, Diane Coyle explores the enormous problems—but also opportunities—facing economics today and examines what it must do to help policymakers solve the world’s crises, from pandemic recovery and inequality to slow growth and the climate emergency. Mainstream economics, Coyle says, still assumes people are “cogs”—self-interested, calculating, independent agents interacting in defined contexts. But the digital economy is much more characterized by “monsters”—untethered, snowballing, and socially influenced unknowns. What is worse, by treating people as cogs, economics is creating its own monsters, leaving itself without the tools to understand the new problems it faces. In response, Coyle asks whether economic individualism is still valid in the digital economy, whether we need to measure growth and progress in new ways, and whether economics can ever be objective, since it influences what it analyzes. Just as important, the discipline needs to correct its striking lack of diversity and inclusion if it is to be able to offer new solutions to new problems. Filled with original insights, Cogs and Monsters offers a road map for how economics can adapt to the rewiring of society, including by digital technologies, and realize its potential to play a hugely positive role in the twenty-first century.
Author: Francis Amasa Walker
Publisher:
ISBN: 9783337598693
Category :
Languages : en
Pages : 488
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Book Description
Author: Francis Amasa Walker
Publisher: Hardpress Publishing
ISBN: 9781290621366
Category :
Languages : en
Pages : 476
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Book Description
Unlike some other reproductions of classic texts (1) We have not used OCR(Optical Character Recognition), as this leads to bad quality books with introduced typos. (2) In books where there are images such as portraits, maps, sketches etc We have endeavoured to keep the quality of these images, so they represent accurately the original artefact. Although occasionally there may be certain imperfections with these old texts, we feel they deserve to be made available for future generations to enjoy.
Author: Katharine G. Abraham
Publisher: University of Chicago Press
ISBN: 022680125X
Category : Business & Economics
Languages : en
Pages : 502
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Book Description
Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.
