Quantitative Economic Policies and Interactive Planning
Title | Quantitative Economic Policies and Interactive Planning PDF eBook |
Author | Andrew J. Hughes Hallett |
Publisher | CUP Archive |
Total Pages | 396 |
Release | 1983-01-20 |
Genre | Business & Economics |
ISBN | 9780521237185 |
Quantitative Economic Policy and Planning
Title | Quantitative Economic Policy and Planning PDF eBook |
Author | Nicolas Spulber |
Publisher | |
Total Pages | 413 |
Release | 1978 |
Genre | |
ISBN |
Quantitative Economic Policy
Title | Quantitative Economic Policy PDF eBook |
Author | Reinhard Neck |
Publisher | Springer Science & Business Media |
Total Pages | 386 |
Release | 2008-03-04 |
Genre | Political Science |
ISBN | 3540746846 |
Econometric techniques and models are still being extensively used in the business of forecasting and policy advice. This book presents recent advances in the theory and applications of quantitative economic policy, with particular emphasis on fiscal and monetary policies in a European and global context. The volume honors Andrew Hughes Hallett, a pioneer and major scientist in quantitative economic policy analysis, whose contributors are among his friends and former students.
The Theory of Quantitative Economic Policy with Applications to Economic Growth, Stabilization and Planning
Title | The Theory of Quantitative Economic Policy with Applications to Economic Growth, Stabilization and Planning PDF eBook |
Author | Karl August Fox |
Publisher | Amsterdam : North-Holland Publishing Company ; New York : American Elsevier |
Total Pages | 676 |
Release | 1973 |
Genre | Business & Economics |
ISBN |
The Theory of Quantitative Economic Policy
Title | The Theory of Quantitative Economic Policy PDF eBook |
Author | Karl August Fox |
Publisher | |
Total Pages | 0 |
Release | 1966 |
Genre | Economic policy |
ISBN |
Theory, Measurement, and Policy
Title | Theory, Measurement, and Policy PDF eBook |
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.
Quantitative Economics with R
Title | Quantitative Economics with R PDF eBook |
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.