Basic Econometrics - Chapter 1

Chapter1

Neville Andrade

3 August 2016

Chapter 1 - Page 27

#### U.S. Egg production

egg_prod <- read.table(file = "https://raw.githubusercontent.com/cablegui/Econometrics/master/OriginalData/Table%201.1.txt", 
    skip = 7, header = TRUE)

colnames(egg_prod)

## [1] "STATE" "Y1"    "Y2"    "X1"    "X2"

head(egg_prod)

##   STATE     Y1     Y2    X1    X2
## 1    AL 2206.0 2186.0  92.7  91.4
## 2    AK    0.7    0.7 151.0 149.0
## 3    AZ   73.0   74.0  61.0  56.0
## 4    AR 3620.0 3737.0  86.3  91.8
## 5    CA 7472.0 7444.0  63.4  58.4
## 6    CO  788.0  873.0  77.8  73.0

Desription of data set

======================

Data set shows U.S. egg production and egg prices for 50 U.S. states for 1990 and 1991. This is an example of cross-sectional data. Cross-sectional data is data collected on one or more variables at the same point in time. This data set has two cross-sectional data, for 1990 and 1991. The variables are the amount of eggs (in millions) and the price per dozen (in cents).

STATE – The short code for the state within the U.S. union
Y1 – Eggs produced in 1990 (millions)
Y2 – Eggs produced in 1991 (millions)
X1 – Price per dozen (cents) in 1990
X2 – Price per dozen (cents) in 1991

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 3.2.3

ggplot(egg_prod, aes(x=Y1, y=X1)) + geom_point() + 
  ylab("Price per dozen (cents) in 1990") +
  xlab("Eggs produced in 1990 (millions)")

ggplot(egg_prod, aes(x=Y2, y=X2)) + geom_point() +
ylab("Price per dozen (cents) in 1991") +
  xlab("Eggs produced in 1991 (millions)")

Fig 1. U.S. egg production plots