Discussion - Week 11
2023-11-20
rm(list = ls())
library(tidyverse)
library(bea.R)
# Setup API key
beaKey <- "A31F4917-2490-488D-AFFD-86A2D5BCFF74"beaSets(beaKey = beaKey)## $Dataset
## DatasetName DatasetDescription
## 1 NIPA Standard NIPA tables
## 2 NIUnderlyingDetail Standard NI underlying detail tables
## 3 MNE Multinational Enterprises
## 4 FixedAssets Standard Fixed Assets tables
## 5 ITA International Transactions Accounts
## 6 IIP International Investment Position
## 7 InputOutput Input-Output Data
## 8 IntlServTrade International Services Trade
## 9 IntlServSTA International Services Supplied Through Affiliates
## 10 GDPbyIndustry GDP by Industry
## 11 Regional Regional data sets
## 12 UnderlyingGDPbyIndustry Underlying GDP by Industry
## 13 APIDatasetMetaData Metadata about other API datasets
##
## attr(,"params")
## ParameterName ParameterValue
## 1 USERID A31F4917-2490-488D-AFFD-86A2D5BCFF74
## 2 METHOD GETDATASETLIST
## 3 RESULTFORMAT JSONbeaSearch("nonfarm proprietors", beaKey = beaKey)## SeriesCode RowNumber
## 1: A1646C 750
## 2: B046RC 10
## 3: Q1808C 100
## 4: Q1809C 110
## 5: H1810C 120
## ---
## 212: B1203C 60
## 213: B1205C 70
## 214: B1206C 80
## 215: B1207C 90
## 216: Y370RC 100
## LineDescription
## 1: Nonfarm proprietors' income with IVA and CCAdj
## 2: Nonfarm proprietors' income
## 3: Communication
## 4: Electric, gas, and sanitary services
## 5: Wholesale trade
## ---
## 212: Adjustment to depreciate expenditures for mining exploration, shafts, and wells
## 213: Bad debt expense
## 214: Income received by fiduciaries
## 215: Income of tax-exempt cooperatives
## 216: Adjustment to depreciate expenditures for intellectual property products
## LineNumber ParentLineNumber Tier Path TableID DatasetName
## 1: 72 0 72 T11300 NIPA
## 2: 1 0 0 1 T61200A NIPA
## 3: 10 8 2 1.8.10 T61200A NIPA
## 4: 11 8 2 1.8.11 T61200A NIPA
## 5: 12 1 1 1.12 T61200A NIPA
## ---
## 212: 5 0 0 5 T71400 NIUnderlyingDetail
## 213: 6 0 0 6 T71400 NIUnderlyingDetail
## 214: 7 0 0 7 T71400 NIUnderlyingDetail
## 215: 8 0 0 8 T71400 NIUnderlyingDetail
## 216: 9 0 0 9 T71400 NIUnderlyingDetail
## TableName
## 1: Table 1.13. National Income by Sector, Legal Form of Organization, and Type of Income
## 2: Table 6.12A. Nonfarm Proprietors' Income by Industry
## 3: Table 6.12A. Nonfarm Proprietors' Income by Industry
## 4: Table 6.12A. Nonfarm Proprietors' Income by Industry
## 5: Table 6.12A. Nonfarm Proprietors' Income by Industry
## ---
## 212: Table 7.14. Relation of Nonfarm Proprietors' Income in the National Income and Product Accounts to Corresponding Measures as Published by the Internal Revenue Service
## 213: Table 7.14. Relation of Nonfarm Proprietors' Income in the National Income and Product Accounts to Corresponding Measures as Published by the Internal Revenue Service
## 214: Table 7.14. Relation of Nonfarm Proprietors' Income in the National Income and Product Accounts to Corresponding Measures as Published by the Internal Revenue Service
## 215: Table 7.14. Relation of Nonfarm Proprietors' Income in the National Income and Product Accounts to Corresponding Measures as Published by the Internal Revenue Service
## 216: Table 7.14. Relation of Nonfarm Proprietors' Income in the National Income and Product Accounts to Corresponding Measures as Published by the Internal Revenue Service
## ReleaseDate NextReleaseDate MetaDataUpdated Account
## 1: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:29.923 National
## 2: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:29.923 National
## 3: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:29.923 National
## 4: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:29.923 National
## 5: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:29.923 National
## ---
## 212: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:32.840 National
## 213: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:32.840 National
## 214: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:32.840 National
## 215: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:32.840 National
## 216: Jul 31 2018 8:30AM Jan 1 1900 12:00AM 2019-03-06T10:13:32.840 National
## apiCall
## 1: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIPA', 'TableName' = 'T11300', ...))
## 2: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIPA', 'TableName' = 'T61200A', ...))
## 3: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIPA', 'TableName' = 'T61200A', ...))
## 4: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIPA', 'TableName' = 'T61200A', ...))
## 5: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIPA', 'TableName' = 'T61200A', ...))
## ---
## 212: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIUnderlyingDetail', 'TableName' = 'T71400', ...))
## 213: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIUnderlyingDetail', 'TableName' = 'T71400', ...))
## 214: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIUnderlyingDetail', 'TableName' = 'T71400', ...))
## 215: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIUnderlyingDetail', 'TableName' = 'T71400', ...))
## 216: beaGet(list('UserID' = '[your_key]', 'Method' = 'GetData', 'DatasetName' = 'NIUnderlyingDetail', 'TableName' = 'T71400', ...))data <- beaGet(list('UserID' = beaKey,
'Method' = 'GetData',
'DatasetName' = 'NIPA',
'TableName' = 'T10705',
'Frequency' = 'A',
'Year' = 'X'))library(dplyr)
datanew <- data %>% head(1)
datanew <- pivot_longer(datanew,cols = 8:101,names_to = 'year',values_to = 'GDP')
datanew$year <- gsub("DataValue_","",datanew$year)
datanew$year <- as.numeric(datanew$year)plot(datanew$year,datanew$GDP)
library(ggplot2)
ggplot(data=datanew, aes(x=year, y=GDP, group=1)) +
geom_line()+
geom_point(color = 'blue') +
ggtitle('Plot on the GDP over Time') +
xlab('Year') +
ylab('GDP')
We can find there exists a decrease of GDP during the finacial crisis in 2008-2009 and Covid-19 in 2019-2020. The financial crisis caused the economic situation to decline, unemployment to increase, and therefore GDP to decrease. The COVID-19 affected many industries, especially manufacturing and services, resulting in lower GDP.