Journal of Quantitative Economics
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Total Pages | : 392 |
Release | : 2004 |
Genre | : Econometrics |
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Author | : |
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Total Pages | : 392 |
Release | : 2004 |
Genre | : Econometrics |
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Total Pages | : 0 |
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Release | : 2010 |
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Total Pages | : 268 |
Release | : 1996 |
Genre | : Econometrics |
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Author | : Vikram Dayal |
Publisher | : Springer Nature |
Total Pages | : 323 |
Release | : 2020-02-03 |
Genre | : Mathematics |
ISBN | : 9811520356 |
This book provides a contemporary treatment of quantitative economics, with a focus on data science. The book introduces the reader to R and RStudio, and uses expert Hadley Wickham’s tidyverse package for different parts of the data analysis workflow. After a gentle introduction to R code, the reader’s R skills are gradually honed, with the help of “your turn” exercises. At the heart of data science is data, and the book equips the reader to import and wrangle data, (including network data). Very early on, the reader will begin using the popular ggplot2 package for visualizing data, even making basic maps. The use of R in understanding functions, simulating difference equations, and carrying out matrix operations is also covered. The book uses Monte Carlo simulation to understand probability and statistical inference, and the bootstrap is introduced. Causal inference is illuminated using simulation, data graphs, and R code for applications with real economic examples, covering experiments, matching, regression discontinuity, difference-in-difference, and instrumental variables. The interplay of growth related data and models is presented, before the book introduces the reader to time series data analysis with graphs, simulation, and examples. Lastly, two computationally intensive methods—generalized additive models and random forests (an important and versatile machine learning method)—are introduced intuitively with applications. The book will be of great interest to economists—students, teachers, and researchers alike—who want to learn R. It will help economics students gain an intuitive appreciation of applied economics and enjoy engaging with the material actively, while also equipping them with key data science skills.
Author | : Vikram Dayal |
Publisher | : Springer |
Total Pages | : 117 |
Release | : 2015-03-17 |
Genre | : Business & Economics |
ISBN | : 8132223403 |
This book gives an introduction to R to build up graphing, simulating and computing skills to enable one to see theoretical and statistical models in economics in a unified way. The great advantage of R is that it is free, extremely flexible and extensible. The book addresses the specific needs of economists, and helps them move up the R learning curve. It covers some mathematical topics such as, graphing the Cobb-Douglas function, using R to study the Solow growth model, in addition to statistical topics, from drawing statistical graphs to doing linear and logistic regression. It uses data that can be downloaded from the internet, and which is also available in different R packages. With some treatment of basic econometrics, the book discusses quantitative economics broadly and simply, looking at models in the light of data. Students of economics or economists keen to learn how to use R would find this book very useful.
Author | : V. Pandit |
Publisher | : Academic Foundation |
Total Pages | : 426 |
Release | : 2008 |
Genre | : Business & Economics |
ISBN | : 9788171886821 |
Presidential addresses delivered at the annual conferences of TIES.
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Total Pages | : 208 |
Release | : 2000 |
Genre | : Developing countries |
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Author | : Econometric Society |
Publisher | : Amsterdam : North-Holland Publishing Company |
Total Pages | : 492 |
Release | : 1971 |
Genre | : Econometrics |
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Author | : J.E. Trinidad-Segovia |
Publisher | : MDPI |
Total Pages | : 418 |
Release | : 2021-02-12 |
Genre | : Business & Economics |
ISBN | : 3036501967 |
This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice.