By Vikram Dayal
This ebook provides an creation to R to accumulate graphing, simulating and computing abilities to allow one to determine theoretical and statistical versions in economics in a unified means. the nice benefit of R is that it really is free, extremely versatile and extensible. The booklet addresses the categorical wishes of economists, and is helping them circulation up the R studying curve. It covers a few mathematical issues reminiscent of, graphing the Cobb-Douglas functionality, utilizing R to check the Solow development version, as well as statistical issues, from drawing statistical graphs to doing linear and logistic regression. It makes use of information that may be downloaded from the web, and that is additionally to be had in numerous R applications. With a few remedy of simple econometrics, the booklet discusses quantitative economics largely and easily, taking a look at types within the mild of knowledge. scholars of economics or economists willing to profit how you can use R could locate this booklet very helpful.
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Additional info for An Introduction to R for Quantitative Economics: Graphing, Simulating and Computing
1 Introduction We use matrices to store data and matrix manipulations underlie econometric estimation. They help us generalize formulae to many variables. 95 n (xi − x)2 The formula for the variance of x is var x = [1/(n − 1)] i=1 We can first calculate a vector of the deviation of each value of x from the mean of x, square the deviations, add them up, and then divide by n − 1. We can get the value of n by using the command length: > length(x)  5 © The Author(s) 2015 V. x, using not star but % * %, the symbol for matrix multiplication in R.
Elasticity is often denoted by . = ( y/y)/( x/x) or in terms of the derivative, = (x/y) dy/d x. 3 Loading the Mosaic Package We will work with the mosaic package Pruim et al. (2014) which we had installed (see Chap. 4); so we load it. 4 Linear Function The linear function (here, y = f (x) = a + bx) is straightforward. However, we will see that the elasticity of the linear function, which is itself a function, is not. We use the following steps. 1. 2. 3. 4. 5. 6. Make the linear function (use makeFun).
It can help us understand statistics and econometrics. 2 Probability Distributions We can easily generate synthetic data from probability distributions. 1 Normal Distribution We load the mosaic package which we will use for plotting graphs. > library(mosaic) We start with the normal distribution. We need to indicate the sample size (n), the mean (mu), and the standard deviation (sd). > n <- 1000 > mu <- 800 > sd <- 35 © The Author(s) 2015 V. 1007/978-81-322-2340-5_8 51 52 8 Statistical Simulation 25 Percent of Total Fig.
An Introduction to R for Quantitative Economics: Graphing, Simulating and Computing by Vikram Dayal