-hw2
Author

Yakub Rabiutheen

Published

August 16, 2022

Code 
library(tidyverse)
library(summarytools)

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)

Loaded the Fed Funds Dataset

Code 
library(readr)
fedfunds <- read_csv("_data/FedFundsRate.csv")

Add any comments or documentation as needed. More challenging data may require additional code chunks and documentation.

Describe the data

Doing a Head of the Dataset to get a view of what the Data Looks like.

Code 
head(fedfunds)
# A tibble: 6 × 10
   Year Month   Day Federal Fu…¹ Feder…² Feder…³ Effec…⁴ Real …⁵ Unemp…⁶ Infla…⁷
  <dbl> <dbl> <dbl>        <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
1  1954     7     1           NA      NA      NA    0.8      4.6     5.8      NA
2  1954     8     1           NA      NA      NA    1.22    NA       6        NA
3  1954     9     1           NA      NA      NA    1.06    NA       6.1      NA
4  1954    10     1           NA      NA      NA    0.85     8       5.7      NA
5  1954    11     1           NA      NA      NA    0.83    NA       5.3      NA
6  1954    12     1           NA      NA      NA    1.28    NA       5        NA
# … with abbreviated variable names ¹​`Federal Funds Target Rate`,
#   ²​`Federal Funds Upper Target`, ³​`Federal Funds Lower Target`,
#   ⁴​`Effective Federal Funds Rate`, ⁵​`Real GDP (Percent Change)`,
#   ⁶​`Unemployment Rate`, ⁷​`Inflation Rate`

Getting the column names

Code 
colnames(fedfunds)
 [1] "Year"                         "Month"                       
 [3] "Day"                          "Federal Funds Target Rate"   
 [5] "Federal Funds Upper Target"   "Federal Funds Lower Target"  
 [7] "Effective Federal Funds Rate" "Real GDP (Percent Change)"   
 [9] "Unemployment Rate"            "Inflation Rate"

Renaming columns as I had difficulty invoking the column name in code.

Code 
names(fedfunds)[names(fedfunds) == "Real GDP (Percent Change)"] <- "Real GDP"
colnames(fedfunds)
 [1] "Year"                         "Month"                       
 [3] "Day"                          "Federal Funds Target Rate"   
 [5] "Federal Funds Upper Target"   "Federal Funds Lower Target"  
 [7] "Effective Federal Funds Rate" "Real GDP"                    
 [9] "Unemployment Rate"            "Inflation Rate"

Summary of the Datset and found a lot of NAs to clean up.

Code 
summary(fedfunds)
      Year          Month             Day         Federal Funds Target Rate
 Min.   :1954   Min.   : 1.000   Min.   : 1.000   Min.   : 1.000           
 1st Qu.:1973   1st Qu.: 4.000   1st Qu.: 1.000   1st Qu.: 3.750           
 Median :1988   Median : 7.000   Median : 1.000   Median : 5.500           
 Mean   :1987   Mean   : 6.598   Mean   : 3.598   Mean   : 5.658           
 3rd Qu.:2001   3rd Qu.:10.000   3rd Qu.: 1.000   3rd Qu.: 7.750           
 Max.   :2017   Max.   :12.000   Max.   :31.000   Max.   :11.500           
                                                  NA's   :442              
 Federal Funds Upper Target Federal Funds Lower Target
 Min.   :0.2500             Min.   :0.0000            
 1st Qu.:0.2500             1st Qu.:0.0000            
 Median :0.2500             Median :0.0000            
 Mean   :0.3083             Mean   :0.0583            
 3rd Qu.:0.2500             3rd Qu.:0.0000            
 Max.   :1.0000             Max.   :0.7500            
 NA's   :801                NA's   :801               
 Effective Federal Funds Rate    Real GDP       Unemployment Rate
 Min.   : 0.070               Min.   :-10.000   Min.   : 3.400   
 1st Qu.: 2.428               1st Qu.:  1.400   1st Qu.: 4.900   
 Median : 4.700               Median :  3.100   Median : 5.700   
 Mean   : 4.911               Mean   :  3.138   Mean   : 5.979   
 3rd Qu.: 6.580               3rd Qu.:  4.875   3rd Qu.: 7.000   
 Max.   :19.100               Max.   : 16.500   Max.   :10.800   
 NA's   :152                  NA's   :654       NA's   :152      
 Inflation Rate  
 Min.   : 0.600  
 1st Qu.: 2.000  
 Median : 2.800  
 Mean   : 3.733  
 3rd Qu.: 4.700  
 Max.   :13.600  
 NA's   :194

Dropping all NAs

Code 
year_metrics <- fedfunds %>%
  drop_na(Year,`Real GDP`,`Inflation Rate`,`Unemployment Rate`,`Effective Federal Funds Rate`)
year_metrics
# A tibble: 236 × 10
    Year Month   Day Federal F…¹ Feder…² Feder…³ Effec…⁴ Real …⁵ Unemp…⁶ Infla…⁷
   <dbl> <dbl> <dbl>       <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
 1  1958     1     1          NA      NA      NA    2.72   -10       5.8     3.2
 2  1958     4     1          NA      NA      NA    1.26     2.6     7.4     2.4
 3  1958     7     1          NA      NA      NA    0.68     9.6     7.5     2.4
 4  1958    10     1          NA      NA      NA    1.8      9.7     6.7     1.7
 5  1959     1     1          NA      NA      NA    2.48     7.7     6       1.7
 6  1959     4     1          NA      NA      NA    2.96    10.1     5.2     1.7
 7  1959     7     1          NA      NA      NA    3.47    -0.8     5.1     2  
 8  1959    10     1          NA      NA      NA    3.98     1.6     5.7     2.7
 9  1960     1     1          NA      NA      NA    3.99     9.2     5.2     2  
10  1960     4     1          NA      NA      NA    3.92    -1.5     5.2     2  
# … with 226 more rows, and abbreviated variable names
#   ¹​`Federal Funds Target Rate`, ²​`Federal Funds Upper Target`,
#   ³​`Federal Funds Lower Target`, ⁴​`Effective Federal Funds Rate`,
#   ⁵​`Real GDP`, ⁶​`Unemployment Rate`, ⁷​`Inflation Rate`
# ℹ Use `print(n = ...)` to see more rows
Code 
summary(year_metrics)
      Year          Month            Day    Federal Funds Target Rate
 Min.   :1958   Min.   : 1.00   Min.   :1   Min.   : 1.000           
 1st Qu.:1972   1st Qu.: 3.25   1st Qu.:1   1st Qu.: 3.750           
 Median :1987   Median : 5.50   Median :1   Median : 5.250           
 Mean   :1987   Mean   : 5.50   Mean   :1   Mean   : 5.407           
 3rd Qu.:2002   3rd Qu.: 7.75   3rd Qu.:1   3rd Qu.: 7.000           
 Max.   :2016   Max.   :10.00   Max.   :1   Max.   :11.000           
                                            NA's   :131              
 Federal Funds Upper Target Federal Funds Lower Target
 Min.   :0.2500             Min.   :0.00000           
 1st Qu.:0.2500             1st Qu.:0.00000           
 Median :0.2500             Median :0.00000           
 Mean   :0.2812             Mean   :0.03125           
 3rd Qu.:0.2500             3rd Qu.:0.00000           
 Max.   :0.5000             Max.   :0.25000           
 NA's   :204                NA's   :204               
 Effective Federal Funds Rate    Real GDP       Unemployment Rate
 Min.   : 0.070               Min.   :-10.000   Min.   : 3.400   
 1st Qu.: 2.655               1st Qu.:  1.400   1st Qu.: 5.000   
 Median : 4.845               Median :  3.100   Median : 5.700   
 Mean   : 5.084               Mean   :  3.116   Mean   : 6.074   
 3rd Qu.: 6.875               3rd Qu.:  4.800   3rd Qu.: 7.100   
 Max.   :19.080               Max.   : 16.500   Max.   :10.400   
                                                                 
 Inflation Rate  
 Min.   : 0.600  
 1st Qu.: 2.000  
 Median : 2.800  
 Mean   : 3.740  
 3rd Qu.: 4.725  
 Max.   :13.000

I tried to use a line graph but it looks messy.

Code 
library(ggplot2)
ggplot(data=year_metrics, aes(x=`Year`, y=`Real GDP`))+
  geom_line()

This Bar Graph came out much cleaner looking.

Code 
perctgdp<-ggplot(year_metrics, aes(x =`Year`, y =`Real GDP`,fill=`Real GDP`)) + geom_bar(stat = "identity")
perctgdp

I added limits and breaks to see the most recent year 2017.

Code 
perctgdp<-perctgdp+scale_x_continuous(limits=c(1954,2017),breaks=seq(1954,2017,5))

Relabeled the Y axis to make to clear this not that actual GDP rate but the Percentage change of the GDP

Code 
print(perctgdp + labs(
  title = "GDP Percentage Change by Year",
  y = "GDP Percentage Change", x = "Year"
))

Code 
ggplot(year_metrics) +
  aes(x = `Unemployment Rate`, y = `Inflation Rate`) +
  geom_point(colour = "#0c4c8a") +
  theme_minimal()

I did a Correlation test of Unemployment rate and the Inflation rate. It got only a moderate Correlation.

Code 
cor(year_metrics$`Unemployment Rate`,year_metrics$`Inflation Rate`)
[1] 0.2095474

Trying to Graph both the Unemployment Rate and Inflation Rate by Year

Code 
df <- year_metrics %>%
  select(Year, `Unemployment Rate`, `Inflation Rate`) %>%
  gather(key = "variable", value = "value", -Year)

Graph that shows inflation rate vs Unemployment Rate by Year

As shown here, there can be periods of High Inflation and low unemployment which is why there isn’t a strong correlation.

Code 
ggplot(df, aes(x =`Year`, y = value)) + 
  geom_line(aes(color = variable, linetype = variable)) + 
  scale_color_manual(values = c("darkred", "steelblue"))+labs(
  title = "Inflation and UnEmployment Rates by Year",
  y = "Variable Rates", x = "Year")