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Introduction to R for Quantitative Economics: Graphing, Simulating and Computing 2015 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 109 pages, kõrgus x laius: 235x155 mm, kaal: 2291 g, 9 Illustrations, color; 70 Illustrations, black and white; XV, 109 p. 79 illus., 9 illus. in color., 1 Paperback / softback
  • Sari: SpringerBriefs in Economics
  • Ilmumisaeg: 30-Mar-2015
  • Kirjastus: Springer, India, Private Ltd
  • ISBN-10: 813222339X
  • ISBN-13: 9788132223399
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  • Pehme köide
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Introduction to R for Quantitative Economics: Graphing, Simulating and Computing 2015 ed.Suurem pilt
  • Formaat: Paperback / softback, 109 pages, kõrgus x laius: 235x155 mm, kaal: 2291 g, 9 Illustrations, color; 70 Illustrations, black and white; XV, 109 p. 79 illus., 9 illus. in color., 1 Paperback / softback
  • Sari: SpringerBriefs in Economics
  • Ilmumisaeg: 30-Mar-2015
  • Kirjastus: Springer, India, Private Ltd
  • ISBN-10: 813222339X
  • ISBN-13: 9788132223399
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9788132223399.html
Märksõnad:
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.
1 Introduction
1(6)
1.1 Three Key Skills
1(2)
1.2 How to Use the Book
3(1)
1.3 Help
4(1)
1.4 R Code and Output
4(1)
1.5 An Overview of Typical R Code
4(2)
1.6 Exploring Further
6(1)
References
6(1)
2 R and RStudio
7(8)
2.1 R and RStudio
7(1)
2.2 Working Directory: Projects
8(1)
2.3 Script
8(1)
2.4 Different Objects in R
9(3)
2.4.1 Vectors
9(1)
2.4.2 Matrices
10(1)
2.4.3 Data Frames
11(1)
2.4.4 Lists
12(1)
2.5 Example: Net Present Value
12(1)
2.6 Exploring Further
13(2)
References
14(1)
3 Getting Data into R
15(4)
3.1 Introduction
15(1)
3.2 Chhatre and Agrawal (2009) Data
15(2)
3.3 Graddy (2006) Data
17(1)
3.4 Crude Oil Price Data
17(1)
3.5 Exploring Further
18(1)
References
18(1)
4 Supply and Demand
19(8)
4.1 Introduction
19(1)
4.2 Supply and Demand in General
19(1)
4.3 The Mosaic Package
19(1)
4.4 Demand
20(1)
4.5 Supply and Demand
21(1)
4.6 Equilibrium
22(1)
4.7 Fish Data
23(1)
4.8 Crude Oil Price Data
24(1)
4.9 Exploring Further
25(2)
References
25(2)
5 Functions
27(12)
5.1 Introduction
27(1)
5.2 Change, Derivative and Elasticity
27(1)
5.3 Loading the Mosaic Package
28(1)
5.4 Linear Function
28(3)
5.5 Log-Log Function
31(2)
5.6 Functions with Data
33(5)
5.7 Exploring Further
38(1)
References
38(1)
6 The Cobb-Douglas Function
39(6)
6.1 Introduction
39(1)
6.2 Cobb-Douglas Production Function
39(4)
6.3 Exploring Further
43(2)
References
43(2)
7 Matrices
45(6)
7.1 Introduction
45(1)
7.2 Simple Statistics with Matrices
45(2)
7.3 Simple Matrix Operations with R
47(2)
7.4 Regression
49(1)
7.5 Exploring Further
50(1)
References
50(1)
8 Statistical Simulation
51(8)
8.1 Introduction
51(1)
8.2 Probability Distributions
51(3)
8.2.1 Normal Distribution
51(1)
8.2.2 Uniform Distribution
52(1)
8.2.3 Binomial Distribution
53(1)
8.3 Central Limit Theorem
54(1)
8.4 The t-Test
55(1)
8.5 Logit Regression
56(2)
8.6 Exploring Further
58(1)
References
58(1)
9 Anscombe's Quartet: Graphs Can Reveal
59(6)
9.1 Introduction
59(1)
9.2 The Data: 4 Sets of xs and ys
59(1)
9.3 Same Regressions of ys on xs
60(1)
9.4 Very Different Scatter Plots
61(2)
9.5 Exploring Further
63(2)
Reference
63(2)
10 Carbon and Forests: Graphs and Regression
65(10)
10.1 Introduction
65(1)
10.2 Graphs
65(3)
10.3 Multiple Regression
68(4)
10.4 Exploring Further
72(3)
References
72(3)
11 Evaluating Training
75(10)
11.1 Introduction
75(1)
11.2 Lalonde Dataset
76(1)
11.3 Matching Treatment and Control
77(3)
11.4 Comparing Treatment and Control
80(2)
11.5 Exploring Further
82(3)
References
83(2)
12 The Solow Growth Model
85(8)
12.1 Introduction
85(1)
12.2 The Solow Model
85(3)
12.3 Growth Time Series
88(2)
12.4 Distribution Over Time
90(2)
12.5 Exploring Further
92(1)
References
92(1)
13 Simulating Random Walks and Fishing Cycles
93(8)
13.1 Introduction
93(1)
13.2 Difference Equations
93(2)
13.3 Stochastic Elements
95(1)
13.4 Random Walk
96(1)
13.5 Fishing
97(3)
13.6 Exploring Further
100(1)
References
100(1)
14 Basic Time Series
101
14.1 Introduction
101(1)
14.2 Air Passengers
101(2)
14.3 The Phillips Curve
103(1)
14.4 Forecasting Inflation
104(3)
14.5 Volatility in the Stock Market
107(2)
14.6 Exploring Further
109
References
109
Vikram Dayal is an Associate Professor at the Institute of Economic Growth, Delhi. He is the author of the book titled The Environment in Economics and Development: Pluralist Extensions of Core Economic Models, published in the SpringerBriefs in Economics series in 2014. In 2009 he co-edited the Oxford Handbook of Environmental Economics in India with Professor Kanchan Chopra. He has been incorporating the use of software in teaching quantitative economicshis  open access notes on Simulating to understand mathematics for economics with Excel and R are downloadable at http(colon)(double back slash)textbookrevolution(dot)org. His research on a range of environmental and developmental issues from outdoor and indoor air pollution in Goa, India to tigers and Prosopis juliflora in Ranthambhore National Park has been published in a variety of journals. He visited the Workshop in Political Theory and Policy Analysis in Bloomington, Indiana as a SANDEE (South Asian Network for Development and Environmental Economics) Partha Dasgupta Fellow in 2011. He studied economics in India and the USA and did his doctoral degree from the University of Delhi.