Write R code to generate the expected output shown below each question.

The Big Mac index

“The big mac index was invented by The Economist in 1986 as a lighthearted guide to whether currencies are at their “correct” level. It is based on the theory of purchasing-power parity (PPP), the notion that in the long run exchange rates should move towards the rate that would equalise the prices of an identical basket of goods and services (in this case, a burger) in any two countries.” (Source: https://www.economist.com/news/2020/07/15/the-big-mac-index)

1. Read the file ‘bigmac.csv’ available at: https://raw.githubusercontent.com/dratnadiwakara/fin4820/master/bigmac.csv as a data.table. Print the first few rows of the data.table.

##     year iso_a3 currency_code           name local_price  dollar_ex
##  1: 2000    ARG           ARS      Argentina        2.50   1.000000
##  2: 2000    AUS           AUD      Australia        2.59   1.680000
##  3: 2000    BRA           BRL         Brazil        2.95   1.790000
##  4: 2000    CAN           CAD         Canada        2.85   1.470000
##  5: 2000    CHE           CHF    Switzerland        5.90   1.700000
##  6: 2000    CHL           CLP          Chile     1260.00 514.000000
##  7: 2000    CHN           CNY          China        9.90   8.280000
##  8: 2000    CZE           CZK Czech Republic       54.37  39.100000
##  9: 2000    DNK           DKK        Denmark       24.75   8.040000
## 10: 2000    EUZ           EUR      Euro area        2.56   1.075269
##     dollar_price gdp_dollar
##  1:     2.500000         NA
##  2:     1.541667         NA
##  3:     1.648045         NA
##  4:     1.938776         NA
##  5:     3.470588         NA
##  6:     2.451362         NA
##  7:     1.195652         NA
##  8:     1.390537         NA
##  9:     3.078358         NA
## 10:     2.380800         NA

Data Dictionary:
year: Year of observation
iso_a3: Three-character ISO 3166-1 country code
name: County name
local_price: Price of a Big Mac in the local currency
dollar_ex: Local currency units per dollar (Exchange rate)
dollar_price: Price of a Big Mac in dollars
gdp_dollar: GDP per person, in dollars

2. Calculate the mean, min, and max dollar_price of a big mac for each year

##    year mean_price min_price max_price
## 1: 2000   2.069903 1.1894737  3.580247
## 2: 2001   1.891209 1.1729622  3.641618
## 3: 2002   2.020765 0.7987220  4.088785
## 4: 2003   2.147612 1.1956522  4.598540
## 5: 2004   2.259276 0.6399659  5.183163
## 6: 2005   2.508365 1.2686675  6.062867

3. Create a new data.table ‘bigmac_USA’ by selecting all USA (iso_a3==“USA”) observations. Select only ‘year’ and ‘local_price’ variables.

##    year local_price
## 1: 2000        2.51
## 2: 2001        2.54
## 3: 2002        2.49
## 4: 2003        2.71
## 5: 2004        2.90
## 6: 2005        3.06

4. Rename local_price to US_price

##    year US_price
## 1: 2000     2.51
## 2: 2001     2.54
## 3: 2002     2.49
## 4: 2003     2.71
## 5: 2004     2.90
## 6: 2005     3.06

5. Merge ‘bigmac’ and ‘bigmac_USA’ using ‘year’

##    year iso_a3 currency_code        name local_price dollar_ex dollar_price
## 1: 2000    ARG           ARS   Argentina        2.50      1.00     2.500000
## 2: 2000    AUS           AUD   Australia        2.59      1.68     1.541667
## 3: 2000    BRA           BRL      Brazil        2.95      1.79     1.648045
## 4: 2000    CAN           CAD      Canada        2.85      1.47     1.938776
## 5: 2000    CHE           CHF Switzerland        5.90      1.70     3.470588
## 6: 2000    CHL           CLP       Chile     1260.00    514.00     2.451362
##    gdp_dollar US_price
## 1:         NA     2.51
## 2:         NA     2.51
## 3:         NA     2.51
## 4:         NA     2.51
## 5:         NA     2.51
## 6:         NA     2.51

6. Calculate ‘bigmac_ex’ by dividing local_price by US_price. Calculate ‘diff’ as (bigmac_ex-dollar_ex)/dollar_ex

##    year iso_a3 currency_code        name local_price dollar_ex dollar_price
## 1: 2000    ARG           ARS   Argentina        2.50      1.00     2.500000
## 2: 2000    AUS           AUD   Australia        2.59      1.68     1.541667
## 3: 2000    BRA           BRL      Brazil        2.95      1.79     1.648045
## 4: 2000    CAN           CAD      Canada        2.85      1.47     1.938776
## 5: 2000    CHE           CHF Switzerland        5.90      1.70     3.470588
## 6: 2000    CHL           CLP       Chile     1260.00    514.00     2.451362
##    gdp_dollar US_price   bigmac_ex         diff
## 1:         NA     2.51   0.9960159 -0.003984064
## 2:         NA     2.51   1.0318725 -0.385790173
## 3:         NA     2.51   1.1752988 -0.343408489
## 4:         NA     2.51   1.1354582 -0.227579478
## 5:         NA     2.51   2.3505976  0.382704476
## 6:         NA     2.51 501.9920319 -0.023361806

7. Create a variable named ‘undervalued’ which takes the value 1 if diff is less than 0 and zero otherwise.

##    year iso_a3 currency_code        name local_price dollar_ex dollar_price
## 1: 2000    ARG           ARS   Argentina        2.50      1.00     2.500000
## 2: 2000    AUS           AUD   Australia        2.59      1.68     1.541667
## 3: 2000    BRA           BRL      Brazil        2.95      1.79     1.648045
## 4: 2000    CAN           CAD      Canada        2.85      1.47     1.938776
## 5: 2000    CHE           CHF Switzerland        5.90      1.70     3.470588
## 6: 2000    CHL           CLP       Chile     1260.00    514.00     2.451362
##    gdp_dollar US_price   bigmac_ex         diff undervalued
## 1:         NA     2.51   0.9960159 -0.003984064           1
## 2:         NA     2.51   1.0318725 -0.385790173           1
## 3:         NA     2.51   1.1752988 -0.343408489           1
## 4:         NA     2.51   1.1354582 -0.227579478           1
## 5:         NA     2.51   2.3505976  0.382704476           0
## 6:         NA     2.51 501.9920319 -0.023361806           1

8. How many currencies are undervalued relative to USD in 2020.

##    undervalued  N
## 1:           1 53
## 2:           0  3

10. Own analysis

  1. Come up with a question you can answer using this data set
  2. Write the code to answer that question