Data for: Does cash-based operating profitability explain the accruals anomaly in China?

Published: 30 April 2020| Version 1 | DOI: 10.17632/cjr2sf2dx7.1
Contributors:
Qingjie Du,
K.C. John Wei,
Yang WANG

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Data structure explanation for Does cash-based operating profitability explain the accruals anomaly in China? February 25, 2020 We provide the final data used in our test and the SAS code to generate all the tables in our paper. The data for the U.S. study is titled “data_pbfj_us”, the data for the Chinese study is titled “data_pbfj_cn”. The SAS code used to generate the results is titled “pbfj_acc_code”. Data structure for the U.S. sample Variable names: 1) permno: stock identifier 2) date: date of observation 3) ret: monthly stock return 4) mep: market cap in previous month 5) lnmep: logarithm of mep 6) micro: microcap stock indicator 7) str: short-term reversal, defined as return in previous month. 8) mom: momentum effect (MOM) 9) at: total assets 10) lnbtm: logarithm of firm’s book-to-market equity 11) op_raw: operating profitability (OP) 12) accat: accruals (ACC) 13) opcat: cash-based operating profitability (Cash-OP) Data structure for the Chinese sample Variable names: 1) permno: stock identifier, same as “stkcd” in CSMAR database 2) date: date of observation 3) ret: monthly stock return 4) mep: market cap in previous month 5) lnmep: logarithm of mep 6) shell: shell stock indicator 7) str: short-term reversal, defined as return in previous month. 8) mom: momentum effect (MOM) 9) at: total assets, same as “A001000000” in CSMAR database 10) lnbtm: logarithm of firm’s book-to-market equity 11) op_raw: operating profitability (OP) 12) accat: accruals (ACC) 13) opcat: cash-based operating profitability (Cash-OP)

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