Challenge 4 Kristin Abijaoude

kristin_abijaoude
challenge4
challenge_4
fed_rates
Author

Kristin Abijaoude

Published

October 12, 2022

Code 
library(tidyverse)
library(dplyr)
library(summarytools)

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

Read in data

Code 
fedfunds <- read_csv("_data/FedFundsRate.csv")
fedfunds
# A tibble: 904 × 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  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
 7  1955     1     1          NA      NA      NA    1.39    11.9     4.9      NA
 8  1955     2     1          NA      NA      NA    1.29    NA       4.7      NA
 9  1955     3     1          NA      NA      NA    1.35    NA       4.6      NA
10  1955     4     1          NA      NA      NA    1.43     6.7     4.7      NA
# … with 894 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 (Percent Change)`, ⁶​`Unemployment Rate`, ⁷​`Inflation Rate`

Briefly describe the data

Today, we are going to analyze the Federal Funds Rate dataset.

Before I get into the dataset itself, let’s first learn about what federal fund rates are. According to Investopedia and Business Insider, federal funds rates are rates that banks and credit unions charge each other before borrowing on an non-collateral basis (in other words, as an unsecured loan). The target rates are set by the Federal Open Market Committee, the policymaking body of the Federal Reserve System. This is essential to stabilize economic growth in the US.

In other words, when there is too much growth, the FOMC raise interest rates, which discourages spending, borrowing, and investing; and therefore, reduce inflation and bring economic growth under control.

On the other hand, the FOMC lowers interest rates to encourage spending, borrowing, and investing in order to expand economic power. However, when rates are too low, that opens the door to out-of-control inflation, which leads to reduce purchasing power and undermining economic growth.

In addition to federal funds rates, this dataset also measures inflation rates, unemployment rates, and changes in real GDP in percentages as well.

Code 
#First, let's dissect the dataset itself

print(dfSummary(fedfunds,
                        varnumbers = FALSE,
                        plain.ascii  = FALSE, 
                        style        = "grid", 
                        graph.magnif = 0.70, 
                        valid.col    = FALSE),
      method = 'render',
      table.classes = 'table-condensed')

Data Frame Summary

fedfunds

Dimensions: 904 x 10
Duplicates: 0
Variable Stats / Values Freqs (% of Valid) Graph Missing
Year [numeric]
Mean (sd) : 1986.7 (17.2)
min ≤ med ≤ max:
1954 ≤ 1987.5 ≤ 2017
IQR (CV) : 28 (0)
 64 distinct values 0 (0.0%)
Month [numeric]
Mean (sd) : 6.6 (3.5)
min ≤ med ≤ max:
1 ≤ 7 ≤ 12
IQR (CV) : 6 (0.5)
 12 distinct values 0 (0.0%)
Day [numeric]
Mean (sd) : 3.6 (6.8)
min ≤ med ≤ max:
1 ≤ 1 ≤ 31
IQR (CV) : 0 (1.9)
 29 distinct values 0 (0.0%)
Federal Funds Target Rate [numeric]
Mean (sd) : 5.7 (2.6)
min ≤ med ≤ max:
1 ≤ 5.5 ≤ 11.5
IQR (CV) : 4 (0.5)
 63 distinct values 442 (48.9%)
Federal Funds Upper Target [numeric]
Mean (sd) : 0.3 (0.1)
min ≤ med ≤ max:
0.2 ≤ 0.2 ≤ 1
IQR (CV) : 0 (0.5)
 4 distinct values 801 (88.6%)
Federal Funds Lower Target [numeric]
Mean (sd) : 0.1 (0.1)
min ≤ med ≤ max:
0 ≤ 0 ≤ 0.8
IQR (CV) : 0 (2.4)
 4 distinct values 801 (88.6%)
Effective Federal Funds Rate [numeric]
Mean (sd) : 4.9 (3.6)
min ≤ med ≤ max:
0.1 ≤ 4.7 ≤ 19.1
IQR (CV) : 4.2 (0.7)
 466 distinct values 152 (16.8%)
Real GDP (Percent Change) [numeric]
Mean (sd) : 3.1 (3.6)
min ≤ med ≤ max:
-10 ≤ 3.1 ≤ 16.5
IQR (CV) : 3.5 (1.1)
 113 distinct values 654 (72.3%)
Unemployment Rate [numeric]
Mean (sd) : 6 (1.6)
min ≤ med ≤ max:
3.4 ≤ 5.7 ≤ 10.8
IQR (CV) : 2.1 (0.3)
 71 distinct values 152 (16.8%)
Inflation Rate [numeric]
Mean (sd) : 3.7 (2.6)
min ≤ med ≤ max:
0.6 ≤ 2.8 ≤ 13.6
IQR (CV) : 2.7 (0.7)
 106 distinct values 194 (21.5%)

Generated by summarytools 1.0.1 (R version 4.2.1)
2022-12-20

Tidy Data (as needed)

Create the date variable with ‘unite()’ command

Code 
#unite year, month, and day column to create a single column for date
fedfunds <- unite(fedfunds, `Year`, `Month`, `Day`, col = "Date YYYY/MM/DD", sep = "/")
fedfunds
# A tibble: 904 × 8
   `Date YYYY/MM/DD` Federal F…¹ Feder…² Feder…³ Effec…⁴ Real …⁵ Unemp…⁶ Infla…⁷
   <chr>                   <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
 7 1955/1/1                   NA      NA      NA    1.39    11.9     4.9      NA
 8 1955/2/1                   NA      NA      NA    1.29    NA       4.7      NA
 9 1955/3/1                   NA      NA      NA    1.35    NA       4.6      NA
10 1955/4/1                   NA      NA      NA    1.43     6.7     4.7      NA
# … with 894 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 (Percent Change)`, ⁶​`Unemployment Rate`, ⁷​`Inflation Rate`

Fill in NAs with ‘is.na()’ command

Here, I fill in the NAs with various values that I believe would make sense to the reader as well as myself. For example, I replace the NAs with the mean (average) in the following variables: federal funds target rate, unemployment rate, and inflation rate. Meanwhile, I replace the NAs with the highest or lowest value in upper and lower federal funds rate columns, as well as real GDP change. I specified the value replacing the NAs in the chunk below.

Code 
#find the mean of federal funds target rate
mean.fedtarget <- mean(fedfunds$`Federal Funds Target Rate`, na.rm = TRUE)

#the mean
mean.fedtarget
[1] 5.658415
Code 
#[1] 5.658415 %

#replace NAs with the mean
fedfunds$`Federal Funds Target Rate`[is.na(fedfunds$`Federal Funds Target Rate`)]<-mean.fedtarget

#replace NAs in upper federal funds target rate with 1
fedfunds$`Federal Funds Upper Target`[is.na(fedfunds$`Federal Funds Upper Target`)] <-1 

#replace NAs in lower federal funds target rate with 0
fedfunds$`Federal Funds Lower Target`[is.na(fedfunds$`Federal Funds Lower Target`)] <-0

#replace NAs in real GDP change with 0
fedfunds$`Real GDP (Percent Change)`[is.na(fedfunds$`Real GDP (Percent Change)`)] <-0

#find the mean of unemployment rate
mean.unemploy <- mean(fedfunds$`Unemployment Rate`, na.rm = TRUE)

#the mean
mean.unemploy
[1] 5.979122
Code 
#[1] 5.979122 %

#replace NAs in unemployment rate with the mean
fedfunds$`Unemployment Rate`[is.na(fedfunds$`Real GDP (Percent Change)`)] <- mean.unemploy

#find the mean of inflation rate
mean.inflation <- mean(fedfunds$`Inflation Rate`, na.rm = TRUE)

#the mean
mean.inflation
[1] 3.73338
Code 
#3.73338 %

#replae NAs in inflation with mean
fedfunds$`Inflation Rate`[is.na(fedfunds$`Inflation Rate`)] <- mean.inflation

#sanity check!
fedfunds
# A tibble: 904 × 8
   `Date YYYY/MM/DD` Federal F…¹ Feder…² Feder…³ Effec…⁴ Real …⁵ Unemp…⁶ Infla…⁷
   <chr>                   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
 1 1954/7/1                 5.66       1       0    0.8      4.6     5.8    3.73
 2 1954/8/1                 5.66       1       0    1.22     0       6      3.73
 3 1954/9/1                 5.66       1       0    1.06     0       6.1    3.73
 4 1954/10/1                5.66       1       0    0.85     8       5.7    3.73
 5 1954/11/1                5.66       1       0    0.83     0       5.3    3.73
 6 1954/12/1                5.66       1       0    1.28     0       5      3.73
 7 1955/1/1                 5.66       1       0    1.39    11.9     4.9    3.73
 8 1955/2/1                 5.66       1       0    1.29     0       4.7    3.73
 9 1955/3/1                 5.66       1       0    1.35     0       4.6    3.73
10 1955/4/1                 5.66       1       0    1.43     6.7     4.7    3.73
# … with 894 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 (Percent Change)`, ⁶​`Unemployment Rate`, ⁷​`Inflation Rate`
Code 
fedfundrates <-fedfunds %>% pivot_longer(cols=c(`Effective Federal Funds Rate`, `Real GDP (Percent Change)`,`Inflation Rate`, `Unemployment Rate`),
                    names_to='Factor',
                    values_to='Rate in percentage')%>%
  select(-c(`Federal Funds Target Rate`, `Federal Funds Upper Target`, `Federal Funds Lower Target`))

fedfundrates
# A tibble: 3,616 × 3
   `Date YYYY/MM/DD` Factor                       `Rate in percentage`
   <chr>             <chr>                                       <dbl>
 1 1954/7/1          Effective Federal Funds Rate                 0.8 
 2 1954/7/1          Real GDP (Percent Change)                    4.6 
 3 1954/7/1          Inflation Rate                               3.73
 4 1954/7/1          Unemployment Rate                            5.8 
 5 1954/8/1          Effective Federal Funds Rate                 1.22
 6 1954/8/1          Real GDP (Percent Change)                    0   
 7 1954/8/1          Inflation Rate                               3.73
 8 1954/8/1          Unemployment Rate                            6   
 9 1954/9/1          Effective Federal Funds Rate                 1.06
10 1954/9/1          Real GDP (Percent Change)                    0   
# … with 3,606 more rows

When I pivot the columns, I end up with 3616 rows!

Code 
nrow(fedfundrates)
[1] 3616

Visualizing Data

Code 
# create data
dates <- fedfunds$`Date YYYY/MM/DD`
dates <- ymd(dates)
Error in ymd(dates): could not find function "ymd"
Code 
gdp <- fedfunds$`Real GDP (Percent Change)`
unemploy <- fedfunds$`Unemployment Rate`
inflation <- fedfunds$`Inflation Rate`
fedfunds$`Federal Funds Lower Target`
  [1] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
 [16] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
 [31] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
 [46] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
 [61] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
 [76] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
 [91] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[106] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[121] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[136] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[151] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[166] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[181] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[196] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[211] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[226] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[241] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[256] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[271] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[286] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[301] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[316] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[331] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[346] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[361] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[376] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[391] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[406] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[421] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[436] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[451] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[466] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[481] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[496] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[511] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[526] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[541] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[556] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[571] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[586] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[601] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[616] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[631] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[646] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[661] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[676] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[691] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[706] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[721] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[736] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[751] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[766] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[781] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[796] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[811] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[826] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[841] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[856] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[871] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
[886] 0.00 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.50
[901] 0.50 0.50 0.50 0.75
Code 
# effective federal fund rate vs unemployment rate chart
ggplot(data = fedfunds, aes(x= `dates`)) + 
  geom_line(aes(y = `Effective Federal Funds Rate`), color = "darkred") +
  geom_line(aes(y = unemploy), color="darkgreen") +
  geom_line(aes(y = `Federal Funds Upper Target`), color="darkblue") +
  geom_line(aes(y= `Federal Funds Target Rate`), color ="purple")+
  geom_line(aes(y = `Federal Funds Lower Target`), color = "black")+
  geom_line(aes(y = inflation), color = "lightseagreen")+
  ylab("Percentages")+
  ggtitle("Effective Federal Funds Rate vfrom 1954 to 2017")

Sources:

https://www.investopedia.com/terms/f/federalfundsrate.asp

https://www.businessinsider.com/personal-finance/what-is-the-federal-funds-rate