R/data.R

In farr: Data and Code for Financial Accounting Research

#' Dates for Apple Events
#'
#' A data set containing the dates of Apple media events
#' since 2005.
#'
#' @format A tibble with 47 rows and 3 variables:
#' \describe{
#'   \item{event}{Description of event}
#'   \item{event_date}{First date of event}
#'   \item{end_event_date}{Last date of event}
#'   ...
#' }
#' @source \url{https://en.wikipedia.org/wiki/List_of_Apple_Inc._media_events}
"apple_events"

#' Tags on StackOverflow
#'
#' A data set containing data on tagged questions on StackOverflow
#'
#' @format A tibble with 40,518 rows and 4 variables:
#' \describe{
#'   \item{year}{Year}
#'   \item{tag}{Tag}
#'   \item{number}{Number of questions with tag during year}
#'   \item{year_total}{Total number of questions with tag during year}
#'   ...
#' }
"by_tag_year"

#' AAER dates from SEC
#'
#' A data set containing dates and descriptions for AAERs
#'
#' @format A tibble with 40,518 rows and 4 variables:
#' \describe{
#'   \item{aaer_num}{AAER number}
#'   \item{aaer_date}{Date}
#'   \item{aaer_desc}{Description}
#'   \item{year}{Year of AAER}
#'   ...
#' }
"aaer_dates"

#' Data on accruals and auditor choice
#'
#' A data set containing data about accruals for 2,000 firms.
#'
#' @format A tibble with 16,237 rows and 14 variables:
#' \describe{
#'   \item{gvkey}{GVKEY (firm identifier)}
#'   \item{datadate}{Fiscal year-end}
#'   \item{fyear}{Fiscal year}
#'   \item{big_n}{Indicator for Big Four auditor}
#'   \item{ta}{Total accruals (scaled by assets)}
#'   \item{roa}{Return on assets}
#'   \item{cfo}{Cash flow from operating activities (scaled by assets)}
#'   \item{size}{Size}
#'   \item{lev}{Leverage}
#'   \item{mtb}{Market-to-book ratio}
#'   \item{inv_at}{1/Total assets}
#'   \item{d_sale}{Change in revenue}
#'   \item{d_ar}{Change in accounts receivable}
#'   \item{ppe}{Property, plant & equipment (scaled by assets)}
#'   ...
#' }
"comp"

#' Test scores
#'
#' A simulated data set of test scores.
#'
#' @format A tibble with 4000 rows and 5 variables:
#' \describe{
#'   \item{id}{Student identifier}
#'   \item{grade}{School grade at time of test}
#'   \item{post}{Indicator for being in grade 10 or 11}
#'   \item{treat}{Indicator for student attending camp after grade 9}
#'   \item{score}{Test score}
#' }
"test_scores"

#' Dates for Inevitable Disclosure Doctrine (IDD)
#'
#' Dates of precedent-setting legal cases adopting or reject the
#' Inevitable Disclosure Doctrine (IDD) by state.
#'
#' @format A tibble with 24 rows and 3 variables:
#' \describe{
#'   \item{state}{Two-letter state abbreviation}
#'   \item{idd_date}{Date of precedent-setting legal case}
#'   \item{idd_type}{Either "Adopt" or "Reject"}
#' }
#' @source \doi{10.1016/j.jfineco.2018.02.008}
"idd_dates"

#' Data on firm headquarters based on SEC EDGAR filings.
#'
#' Data on firm headquarters based on SEC EDGAR filings.
#' Dates related to SEC filing dates. Rather than provide dates for
#' all filings, data are aggregated into groups of filings by state and
#' CIK and dates are collapsed into windows over which
#' all filings for a given CIK were associated with a given state.
#' For example, CIK 0000037755 has filings with a CA headquarters from
#' 1994-06-02 until 1996-03-25, then filings with an OH headquarters from
#' 1996-05-30 until 1999-04-05, then filings with a CA headquarters from
#' 1999-06-11 onwards.
#' To ensure continuous coverage over the sample period, it is assumed that
#' any change in state occurs the day after the last observed filing for
#' the previous state.
#'
#' @format A tibble with 24 rows and 3 variables:
#' \describe{
#'   \item{cik}{SEC's Central Index Key (CIK)}
#'   \item{ba_state}{Two-letter abbreviation of state}
#'   \item{min_date}{Date of first filing with CIK-state combination in a contiguous series of filings}
#'   \item{max_date}{Date of last filing with CIK-state combination in a contiguous series of filings}
#' }
#' @source \url{https://sraf.nd.edu/data/augmented-10-x-header-data/}
"state_hq"

#' GVKEYs used in Li, Lin and Zhang (2018)
#'
#' @format A tibble with 5,830 rows and 1 variable:
#' \describe{
#'   \item{gvkey}{GVKEY}
#' }
#' @source \url{https://research.chicagobooth.edu/-/media/research/arc/docs/journal/online-supplements/llz-datasheet-and-code.zip}
"llz_2018"

#' Customer names that represent non-disclosures.
#'
#' Data to be combined with data in compsegd.seg_customer to create an
#' indicator for non-disclosure of customer names.
#'
#' @format A tibble with 432 rows and 2 variables:
#' \describe{
#'   \item{cnms}{Matches field in compsegd.seg_customer (WRDS)}
#'   \item{disclosure}{Indicator that name is not disclosed}
#' }
"undisclosed_names"

#' Data on firms suffering natural disasters.
#'
#' Data on firms suffering natural disasters based on the sample
#' in Michels (2017).
#'
#' @format A tibble with 423 rows and 12 variables:
#' \describe{
#'   \item{cusip}{CUSIP supplied by Michels (2017)}
#'   \item{eventdate}{Date of relevant natural disaster supplied by Michels (2017)}
#'   \item{cik}{Matched CIK (SEC firm identifier)}
#'   \item{permno}{Matched PERMNO (CRSP security identifier)}
#'   \item{gvkey}{Matched GVKEY (Compustat firm identifier)}
#'   \item{date_filed}{Date of next filing of type 10-Q, 10-K, 10QSB, 10-K405 after event}
#'   \item{form_types}{List of relevant form types filed on date_filed}
#'   \item{next_period_end}{Next fiscal period-end after event date}
#'   \item{next_fqtr}{Fiscal quarter of next period-end after event date}
#'   \item{prev_period_end}{Last fiscal period-end before event date}
#'   \item{prev_fqtr}{Fiscal quarter of last period-end before event date}
#'   \item{recognize}{Indicator for event being recognized (next_period_end before date_filed)}
#' }
"michels_2017"

#' Data on public float.
#'
#' Data on public float of listed companies from Iliev (2010).
#'
#' @format A tibble with 7,213 and 9 variables:
#' \describe{
#'   \item{gvkey}{Compustat firm identifier (GVKEY)}
#'   \item{fyear}{Fiscal year}
#'   \item{fdate}{Date of end of fiscal year}
#'   \item{pfdate}{Date for public float value}
#'   \item{pfyear}{Year for public float value}
#'   \item{publicfloat}{Public float in $ million}
#'   \item{mr}{Indicator for filing of a management report}
#'   \item{af}{Indicator for accelerator filer}
#'   \item{cik}{SEC firm identifier (CIK)}
#' }
"iliev_2010"

#' Firm-years in RDD analysis of Bloomfield (2021).
#'
#' Firm-years in RDD analysis of Bloomfield (2021).
#'
#' @format A tibble with 1,855 rows and 2 variables:
#' \describe{
#'   \item{fyear}{Fiscal year}
#'   \item{permco}{CRSP firm identifier (PERMCO)}
#' }
"bloomfield_2021"

#' Treatment indicators for SHO pilot firms
#'
#' A data set containing the tickers, GVKEYs, and
#' treatment indicator for SHO pilot program.
#'
#' @format A tibble with 3,030 rows × 4 variables.
#' \describe{
#'   \item{ticker}{Ticker}
#'   \item{gvkey}{GVKEY (firm identifier)}
#'   \item{permno}{PERMNO (CRSP security identifier)}
#'   \item{pilot}{SHO pilot program treatment indicator}
#' }
"fhk_pilot"

#' Firm-years for replication of Fang, Huang and Karpoff (2016)
#'
#' A data set containing the GVKEYs and
#' datadates for firm-years used in Fang, Huang and Karpoff (2016).
#'
#' @format A tibble with 60,272 rows × 2 variables.
#' \describe{
#'   \item{gvkey}{GVKEY (firm identifier)}
#'   \item{datadate}{Fiscal year-end}
#' }
"fhk_firm_years"

#' Tickers of pilot firms for Reg SHO.
#'
#' A data set containing the tickers and
#' company names for pilot firms from Reg SHO pilot.
#' Data are scraped from the SEC's own website.
#'
#' @format A tibble with 986 rows × 2 variables.
#' \describe{
#'   \item{ticker}{Ticker}
#'   \item{co_name}{Company name}
#' }
#' @source \url{https://www.sec.gov/rules/other/34-50104.htm}
"sho_tickers"

#' Russell 3000 stocks at time of SEC Reg SHO sample formation.
#'
#' A data set containing the tickers and
#' company names for Russell 3000 at time SEC created the pilot sample.
#' Data are created from sample supplied by FHK.
#'
#' @format A tibble with 3000 rows × 2 variables.
#' \describe{
#'   \item{russell_ticker}{Ticker}
#'   \item{russell_name}{Company name}
#' }
"sho_r3000"

#' Russell 3000 sample used by SEC
#'
#' A data set containing the tickers, PERMNOs, and
#' treatment assignments for Russell 3000 sample used by SEC.
#'
#' @format A tibble with 2,954 rows × 3 variables.
#' \describe{
#'   \item{ticker}{Ticker}
#'   \item{permno}{PERMNO (CRSP security identifier)}
#'   \item{pilot}{Indicator for stock being part of Reg SHO pilot program}
#' }
#' @source \url{http://iangow.me/far_book/natural-revisited.html#the-sho-pilot-sample}
"sho_r3000_sample"

#' Russell 3000 sample used by SEC with GVKEYs
#'
#' A data set containing the tickers, PERMNOs, GVKEYs, and
#' treatment assignments for Russell 3000 sample used by SEC.
#'
#' @format A tibble with 2,951 rows × 3 variables.
#' \describe{
#'   \item{ticker}{Ticker}
#'   \item{permno}{PERMNO (CRSP security identifier)}
#'   \item{gvkey}{GVKEY (Compustat firm identifier)}
#'   \item{pilot}{Indicator for stock being part of Reg SHO pilot program}
#' }
#' @source \url{http://iangow.me/far_book/natural-revisited.html#the-sho-pilot-sample}
"sho_r3000_gvkeys"

#' Event windows from Zhang (2007)
#'
#' A data set containing the event windows used in Zhang (2007).
#' Data obtained from Panel of Table of Zhang (2007).
#'
#' @format A tibble with 17 rows × 3 variables.
#' \describe{
#'   \item{event}{Identifier for the event}
#'   \item{beg_date}{First date of event window}
#'   \item{end_date}{Last date of event window}
#' }
#' @source \doi{10.1016/j.jacceco.2007.02.002}
"zhang_2007_windows"

#' Event dates from Zhang (2007)
#'
#' A data set containing the event dates used in Zhang (2007).
#' Data obtained from Panel of Table of Zhang (2007).
#' If an event spans multiple dates, then a row is
#' included for each date.
#'
#' @format A tibble with 30 rows × 3 variables.
#' \describe{
#'   \item{event}{Identifier for the event}
#'   \item{date}{Date of event}
#'   \item{event_desc}{Description of the event}
#' }
#' @source \doi{10.1016/j.jacceco.2007.02.002}
"zhang_2007_events"


#' AAERs from Bao et al. (2020)
#'
#' A data set containing AAER firms-years used in Bao et al. (2020).
#'
#' @format A tibble with 415 rows and 4 variables:
#' \describe{
#'   \item{p_aaer}{AAER identifier}
#'   \item{gkvey}{GVKEY (firm identifier)}
#'   \item{min_year}{First affected year}
#'   \item{max_year}{Last affected year}
#'}
"aaer_firm_year"

#' Australian banks
#'
#' A data set containing identifying information for 10 Australian banks.
#'
#' @format A tibble with 10 rows and 3 variables:
#' \describe{
#'   \item{gvkey}{GVKEY (firm identifier)}
#'   \item{ticker}{Stock exchange ticker}
#'   \item{co_name}{Bank name}
#'}
"aus_banks"

#' Australian bank fundamental data
#'
#' A data set containing fundamental financial information for Australian banks.
#'
#' @format A tibble with 283 rows and 7 variables:
#' \describe{
#'   \item{gvkey}{GVKEY (firm identifier)}
#'   \item{datadate}{Fiscal year-end}
#'   \item{at}{Total assets}
#'   \item{ib}{Income before extraordinary items}
#'   \item{xi}{Extraordinary items}
#'   \item{do}{Income from discontinued operations}
#'}
"aus_bank_funds"

#' Australian bank stock market data
#'
#' A data set containing fundamental financial information for Australian banks.
#'
#' @format A tibble with 3,047 rows and 4 variables:
#' \describe{
#'   \item{gvkey}{GVKEY (firm identifier)}
#'   \item{datadate}{Last trading date of month}
#'   \item{ret}{Stock return for month}
#'   \item{mkt_cap}{Market capitalization on datadate}
#'}
"aus_bank_rets"