Download An Introduction to R for Quantitative Economics: Graphing, by Vikram Dayal PDF

By Vikram Dayal

This booklet provides an creation to R to accumulate graphing, simulating and computing abilities to permit one to work out theoretical and statistical versions in economics in a unified method. the good good thing about R is that it really is free, extremely versatile and extensible. The ebook addresses the explicit wishes of economists, and is helping them stream up the R studying curve. It covers a few mathematical issues corresponding to, graphing the Cobb-Douglas functionality, utilizing R to check the Solow progress version, as well as statistical subject matters, from drawing statistical graphs to doing linear and logistic regression. It makes use of info that may be downloaded from the web, and that's additionally to be had in several R programs. With a few remedy of uncomplicated econometrics, the booklet discusses quantitative economics commonly and easily, versions within the mild of information. scholars of economics or economists prepared to benefit tips to use R may locate this booklet very helpful.

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Extra resources for An Introduction to R for Quantitative Economics: Graphing, Simulating and Computing

Example text

Compute the derivative (a function) (use D) The D function in the mosaic package computes the derivative. dx function (x, a = 2, b = 2) b The output indicates that the derivative of y1 is b, and b here is 2. We repeat for y2. 5. Since the derivatives are themselves functions, the code is similar to that used in Step 2. Step 4. Plot the derivative (Fig. 2). 5). 5, b = 0, lty = 2, col = "black")) In Fig. 2 we see the derivatives are flat lines. Step 5. Compute the elasticity (a function) using makeFun and substituting for x, y and dy/dx in the formula = (x/y)dy/d x from steps 1 and 3.

On downloading the workbook file, we select the sheet with oil crude prices since 1861. Then we remove all rows above the header row, and change the current price column header to current and the other to const_ 2013. We then bring it into R Studio. We go to the environment window and click on Import Dataset; then from text file, choose Oil prices; then select header. Alternatively, you can type in the following command, changing the file path as required. 26 We will look at this data in Chap. 4.

3) ˜ L, K = 20, A = 5, ylim = range(-5, + 101), xlim = range(-1, 21)) We see that as we increase L the amount of increase in Y diminishes (Fig. 1). We can now see how the curve relating aggregate production to L changes as we change the amount of K. We plot two curves for Y versus L; one with K = 20 and the other with K = 40. 3) ˜ L, K = 40, A = 5, ylim = range(-5, + 151), xlim = range(-1, 21), lty = 2, add = TRUE) An increase in K shifts the Y versus L curve up—increasing K helps L become more productive (Fig.

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