Research Design Proceeding E Book 4A Turky

2374 No. Security code Company Name Industry 1 2284 ITOHAM FOODS INC. Foods 2 3569 SEIREN CO., LTD. Textiles 3 3730 MACROMILL, INC. Communications 4 4812 Information Service Inti-Dentsu Communications 5 4902 KONICA MINOLTA HOLDINGS, INC. Chemicals 6 6305 Hitachi Consruction Machinery Co., Ltd. Machinery 7 5445 TOKYO TEKKO CO., LTD. Machinery 8 6504 FUJI ELECTRIC HOLDINGS CO., LTD. Electric Electoronics Equipment 9 6506 YASKAWA Electric Corporation Electric Electoronics Equipment 10 6581 Hitachi Koki Co., Ltd. Electric Electoronics Equipment 11 6588 TOSHIBA TEC CORPORATION Machinery 12 6592 MABUCHI MOTOR CO., LTD. Electric Electoronics Equipment 13 6622 DAIHEN CORPORATION Electric Electoronics Equipment 14 6737 EIZO NANAO CORPORATION Electric Electoronics Equipment 15 6753 Sharp Corporation Electric Electoronics Equipment 16 6701 NEC Corporation Electric Electoronics Equipment 17 6702 FUJITSU LIMITED Electric Electoronics Equipment 18 6724 SEIKO EPSON CORPORATION Electric Electoronics Equipment 19 6770 ALPS ELECTRIC CO., LTD. Electric Electoronics Equipment 20 6861 KEYENCE CORPORATION Electric Electoronics Equipment 21 5201 Asahi Glass Company, Limited Electric Electoronics Equipment 22 6954 FANUC LTD Electric Electoronics Equipment 23 7201 NISSAN MOTOR CO., LTD. Transportation Equipment 24 7261 Mazda Motor Corporation Transportation Equipment 25 7731 NIKON CORPORATION Electric Electoronics Equipment 26 7701 Shimadzu Corporation Electric Electoronics Equipment 27 8015 TOYOTA TSUSHO CORPORATION Wholesaler 28 8012 NAGASECO., LTD. Wholesaler 29 8035 Tokyo Electron Limited Wholesaler 30 8088 IWATANI CORPORATION Wholesaler 31 8051 YAMAZEN CORPORATION Wholesaler 32 8585 Orient Corporation Finance Insurance 33 8601 Daiwa Secruities Group Inc. Finance Insurance 34 9433 KDDI CORPORATION Communications 35 9984 SOFTBANK CORP. Communications 36 6841 Yokogawa Electric Corporation Communications Source: eol database http:www.eol.co.jpeservice01.html TABLE 5. Japanese GAAP Companies in Japan N=36 3.2. Measurements The SEC rule companies tend to be more efficient in the capital cost, because of the company size. If arbitrary application of IFRS is admitted 2375 in the United States and Japan, some of them would choose the U.S.GAAP or IFRS. The Japanese GAAP companies would keep using Japanese GAAP approved the equivalence or change IFRS. We put the year ending March 2007 FY2007 with the boundary changing something for Japanese and U.S.GAAP. FY2007 is the year when CESR has announced the technical advice for the equivalence of the third country. It is assumed that there are some effects given to the market favorability of Japan and U.S.GAAP. First, we use Earnings persistence to measure earnings quality Francis et al., 2005. Earnings persistence captures the permanence of earnings from one period to the next and it is estimated by regressing current period earnings on prior period earnings. Higher earnings persistence is considered a characteristic of higher earnings quality. Our review of the prior research suggests that persistence is expected to be increasing in growth Collins and Kothari, 1989 and Francis et al., 2002. The persistence model is as follows: EARN it = α0 + α1EARN it-1 + αβεB it + αγ EARN it -1MB it + α4STANDARD t + α5 EARN it-1 STANDARD t + it …………………….........1 Where: EARN is income before extraordinary items scaled by average total assets ave.TA MB is the market to book ratio STANDARD is an indicator variable equal to one if a company prepares the financial statements based on the SEC rule or IFRS response to the single set has already been effective and zero otherwise . Second, we use accrual measurement to measure accrual quality. We follow Dechow and Dichev 2002 and Francis et al. 2005 to estimate a proxy for accrual quality that is commonly used in the literature. The total current accrual model is as follow: TCA = α + α 1 CFOi t+1 + α 2 CFO it + α 3 CFO it-1 + α 4 SALES it + α 5 PPE

i,t

+ it ……………………………………………………………………..β 2376 Where: TCA is total accrual and can measure with the equation as follow: CURRENT ASSET it - CURRENT LIABILITIES it - CASH it + SHORT TERM DEBT it CFO is operating cash flow SALES is the year to year change in sales PPE is gross level of property, plant and equipment All variables are scaled by average assets in year t. Equation 2 is then estimated annually on a cross sectional basi s for each of Fama and French‘s 1997. The firm specifc resuduals from the estimation are used to form the accrual quality metric. Specifically, the firm specific accrual quality metric equals the standard deviation of the residuals for each firm. Following Dichow and Dichev 2002 and Francis et.al. 2005, we expect that accrual quality is negatively associated with smaller firms, greater cash flow variability, longer operating cycles and reporting of losses. Finally, an indicator variable taht capture the effect of accounting standard is included. Our accrual qualitu model is as follows: SD_AQ

i,t

=  o +  1 LNASSETS

i,t

+  2 SD_CFO

i,t

+  3 SD_SALES

i,t

+  4 LOSS

i,t

+  5 STANDARD t + 

i,t

.................................. ...................................3 Where SD_AQ is the standard deviation of the residual from the annual estimation of equation 2 for each industry. LNASSETS is the natural log of total assets, SD_CFO is the standard deviation of cash flow operations. SD_SALES is the standard deviation of sales. LOSS is an indicator variable equal to one if earnings before extraordinary items is negative and zaro ottherwise. STANDARD is an indocator variable equal to one if the year identified standard is effective and zero otherwise. 2377

4. Sample Data and Hypotheses

4.1. Sample Data The data is collected in the eol database 425 in Japan from the annual reports of companies listed on the first and second sections of the Tokyo Securities Exchange TSE. As of March 2008, there is consolidated accounting data is for 1,474 companies on TSE section 1. First, this paper chooses the data of EARN, MB, and TA on the 36 Japanese companies using the SEC rule SEC rule companies. Secondary, we suppose that the other group is compared with the group of SEC rule companies in the equivalent sector and scale. The group is composed with Japanese 36 companies which prepare their financial statements on the Japanese GAAP. They are called Japanese GAAP companies as TABLE 5 shown. The data set of two groups with different standards of accounting is handled by the dummy variable named STANDARD as one data set. For Indonesia sample we use Non-Financial Public companies that has listed in LQ 45 from 2002 to 2008. We prefer to use LQ 45 firms because they have good market performance and their stock is liquid. We first eliminate observations that lack lagged data and non-December year-ends. We eliminate non-December year-ends to simplify identification of when specific standards. We eliminate extreme value observations in the persistence and valuation samples consistent with prior research. Extreme observations are defined as share prices, book value per share, or earnings per share exceeding 1,000 per share in the 425 The eol is a service by eol Inc. that archive contains all the ―Yuhos‖ for every publicly traded company more than 4,000 firms and roughly 1,000 privately- held companies in Japan. Yuho is required for all listed and unlisted companies all listed companies and all unlisted companies with a sufficient level of capitalization to file a semi-annual report commonly by the Japanese Government .Refer http:www.eol.co.jpeservice01.html 2378 valuation sample. The availability of IDX data and variables to construct our accruals measures are the most restrictive constraints in forming our samples resulting in the forecast and accrual quality samples being the smallest. We also eliminate the firms which not consistently in LQ 45 during observation period 2002-2008. So, for Indonesian sample there were γ6 firms, and the detailed of the firms‘ name as below. TABLE 6. Indonesian Samples No. Security Code Companies name Industry 1. AALI Astra Agro Lestari Agriculture 2. ANTM Aneka Tambang Mining 3. ASII Astra International Automotive 4. BLTA Berlian Laju Tanker Transportation 5. BNBR Bakrie Brothers Investment 6. BTEL Bakrie Telecom Telecomunication 7. BUMI Bumi Resources Mining 8. CPIN Charoen Phokpand Basic Industry 9. CPRO Central Proteinaprima Basic Industry 10. ELTY Bakrieland Development Property 11. ENRG Energi Mega Persada Mining 12. INCO International Nickel Indonesia Mining 13. INDF Indofood Sukses Makmur Consumer Goods 14. INKP Indah Kiat Pulp Paper Basic Industry 15. ISAT Indosat Telecommunication 16. KIJA Kawasan Industri Jababeka Property 17. MEDC Medco Energi International Mining 18. PGAS Perusahaan Gas Negara Mining 19. PTBA Tambang Batubara Bukit Asam Mining 20. SMCB Holcim Basic Industry 21. TBLA Tunas Baru Lampung Agriculture 22. TINS TIMAH Mining 23. TLKM Telekomunikasi Indonesia Telecommunication 24. TRUB Truba Alam Manunggal Engineering Infrastructure 25. UNSP Bakrie Sumatra Plantations Agriculture 26. UNTR United Tractors Services 27. ITMG Indo Tambangraya Megah Mining 28. LPKR Lippo Karawaci Property 29. LSIP PP London Sumatera Agriculture 30. AKRA AKR Corporindo Trade 31. BISI Bisi International Agriculture 32. DEWA Darma Henwa Infrastructure 33. MIRA Mitra Rajasa Transportation 34. MNCN Media Nusantara Citra Media 35 SMGR Semen Gresik Basic Industry 36. SGRO Sampoerna Agro Agriculture