This tutorial will go through all the code you need for assignment 1.

Simple arithmetic

You can perform arithmetic to saved objects:

a <- 2
b <- 3
c <- 4
a + b * c

## [1] 14

Load data

For an example dataset, I will load the Cobb-Douglas data directly from the internet:

mydat <- read.csv("https://rtgodwin.com/data/cobbdouglas.csv")

Note that you can load any .csv dataset this way, by typing the location of the file in the quotations above.

Calculate a sample mean

The sample mean for my dependent variable ,log(output), is:

mean(log(mydat$output))

## [1] 9.770502

Note that the mydat$ part is telling R where to find the variable output.

Estimate and save a model

I will estimate the Cobb-Douglas production function, and save it as an “object”. I can choose any name for the object (I choose “mymod”):

mymod <- lm(log(output) ~ log(labour) + log(capital), data = mydat)

Use the estimated model

To see the results of the estimation you can use summary(mymod) to see lots of information, but if you just want to see the estimated β, run mymod:

mymod

## 
## Call:
## lm(formula = log(output) ~ log(labour) + log(capital), data = mydat)
## 
## Coefficients:
##  (Intercept)   log(labour)  log(capital)  
##       0.1768        0.2652        0.9121

To get, and save, the LS residuals from the estimated model, use:

myresids <- residuals(mymod)

To get the estimated coefficients from the model use:

coefficients(mymod)

##  (Intercept)  log(labour) log(capital) 
##    0.1768209    0.2651853    0.9121483

and to get only the estimate for labour (for example), extract the 2nd element:

coefficients(mymod)[2]

## log(labour) 
##   0.2651853

Estimation without an intercept

Usually, it’s a good idea to include an intercept in the model, but sometimes we don’t want it. R includes an intercept by default. To get rid of the intercept, put -1 at the end of the equation:

lm(output ~ labour + capital -1, data = mydat)

## 
## Call:
## lm(formula = output ~ labour + capital - 1, data = mydat)
## 
## Coefficients:
##  labour  capital  
##  42.914    1.621

(I omitted the log for simplicity).