Data - FRB
Author
Info
The Financial Accounts of the United States includes data on transactions and levels of financial assets and liabilities, by sector and financial instrument; full balance sheets, including net worth, for households and nonprofit organizations, nonfinancial corporate businesses, and nonfinancial noncorporate businesses; Integrated Macroeconomic Accounts; and additional supplemental detail.
- Flow of Funds. pdf
Code
Z1_csv_var %>% group_by(table, table_desc) %>% summarise(Nobs = n()) %>% filter((table %in% (list.files(pattern = "\\.qmd$") %>% gsub(".qmd$", "", .)))) %>% mutate(html = paste0('<a target=_blank href=https://fgeerolf.com/data/frb/', table, '.html > html </a>')) %>% mutate(frb = paste0('<a target=_blank href=https://www.federalreserve.gov/releases/z1/20210610/html/', table, '.htm > frb </a>')) %>% {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}
Code
Z1_csv_var %>% group_by(table, table_desc) %>% summarise(Nobs = n()) %>% filter(!(table %in% (list.files(pattern = "\\.qmd$") %>% gsub(".qmd$", "", .)))) %>% mutate(frb = paste0('<a target=_blank href=https://www.federalreserve.gov/releases/z1/20210610/html/', table, '.htm > frb </a>')) %>% {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}
Code
Z1_struct_concepts %>% print_table_conditional()
id | default |
---|---|
SERIES_PREFIX | Series prefix |
UNIT | Units |
OBS_STATUS | Observation status |
SERIES_INSTRUMENT | Instrument type |
TIME_PERIOD | Time |
FREQ | Frequency |
CURRENCY | Currency |
SERIES_SECTOR | Sector |
UNIT_MULT | Unit multiplier |
DESCRIPTION | Series description |
SERIES_NAME | Series Name |
OBS_VALUE | Observation value |
SERIES_TYPE | Series type |
Code
Z1 %>% left_join(OBS_STATUS, by = "OBS_STATUS") %>% group_by(OBS_STATUS, Obs_status) %>% summarise(Nobs = n()) %>% print_table_conditional()
OBS_STATUS | Obs_status | Nobs |
---|---|---|
A | Normal | 3530542 |
ND | No data | 152994 |
Code
Z1 %>% left_join(SERIES_INSTRUMENT, by = "SERIES_INSTRUMENT") %>% group_by(SERIES_INSTRUMENT, Series_instrument) %>% summarise(Nobs = n()) %>% print_table_conditional()
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Z1 %>% left_join(SERIES_SECTOR, by = "SERIES_SECTOR") %>% group_by(SERIES_SECTOR, Series_sector) %>% summarise(Nobs = n()) %>% print_table_conditional()
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Z1 %>% left_join(SERIES_PREFIX, by = "SERIES_PREFIX") %>% group_by(SERIES_PREFIX, Series_prefix) %>% summarise(Nobs = n()) %>% print_table_conditional()
SERIES_PREFIX | Series_prefix | Nobs |
---|---|---|
FA | Transactions, SA | 958349 |
FC | Change in levels, NSA | 5138 |
FG | Growth rates, SA | 3670 |
FL | Levels, NSA | 807626 |
FR | Revaluation | 763625 |
FU | Transactions, NSA | 971206 |
FV | Other changes in volume | 21717 |
LA | Levels, SA | 3720 |
LM | Market value levels, NSA | 147506 |
PC | Percent change in index | 979 |
Code
Z1 %>% left_join(FREQ, by = "FREQ") %>% group_by(FREQ, Freq) %>% summarise(Nobs = n()) %>% print_table_conditional()
FREQ | Freq | Nobs |
---|---|---|
162 | Quarterly | 2924124 |
203 | Annual | 759412 |
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Z1 %>% left_join(UNIT_MULT, by = "UNIT_MULT") %>% group_by(UNIT_MULT, Unit_mult) %>% summarise(Nobs = n()) %>% print_table_conditional()
UNIT_MULT | Unit_mult | Nobs |
---|---|---|
1 | One | 16041 |
1000000 | Millions | 3667495 |
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Z1 %>% left_join(UNIT, by = "UNIT") %>% group_by(UNIT, Unit) %>% summarise(Nobs = n()) %>% print_table_conditional()
UNIT | Unit | Nobs |
---|---|---|
Currency | Currency | 3667495 |
Percent | Percent | 16041 |
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Z1 %>% left_join(CURRENCY, by = "CURRENCY") %>% group_by(CURRENCY, Currency) %>% summarise(Nobs = n()) %>% print_table_conditional()
CURRENCY | Currency | Nobs |
---|---|---|
NA | Not Applicable | 16041 |
USD | United States / United States Dollar | 3667495 |
Tobin’s Q for Nonfinancial Corporations
Code
ig_d("frb", "B103", "tobin-q-SDMX")
Equipment, Real estate
Code
ig_d("frb", "B103", "corporate-bonds-equities")
Current cost VS market value housing
Code
ig_d("frb", "B101", "structures-real-estate")
Corporate Equities, Pensions, Real Estate
Code
ig_d("frb", "B101", "line-3-23-27")