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III. HYPOTHESIS DEVELOPMENT
Previous studies on basic regression model
Cheng (2015) uses the cross-sectional modified Jones model to estimate the DA.
The model is introduced by Defond (1994) who assumed that the magnitude of NDA in the same industry is the same. However, the assumption is not seemingly correct. First, each company has different products and holds different scale of asset. Therefore, the magnitude of the variances for revenue will vary in the cross-sectional modified Jones model. Secondly, although the industry classification allows us to investigate more details about peer groups companies, the number of observations will be different across the industry after the classification. Thirdly, the model is potentially lack of explanation power with only three independent variables even though it is verified theoretically Hujino (2009). And hence, application of other models should be considered for the research of EM. Since CEO is able to manage credit sales to control revenue, the modification version of Jones model is more suitable, according to Dechow (1995). The model deducts account receivable from revenue and focus on the credit sales in the event period results from EM.
Hypothesis 1: The modified Jones model is not effective detecting EM in China.
Application of the accrual model in the developing counties
Recently, Ball (2008) and Armstrong (2008) reported that strong monitoring and auditing can restrict EM in the UK and the U.S. However, weaker regulation as well as loose auditing would breeds the vigorous EMs in the market. In China Wang (2008) reported that SOE hires local auditors who provide lower-quality of auditor’s check. And Cheng (2015) argued that the Chinese financial regulation is still under developing.
Therefore, SOE may be able to manage earnings. However, the modified Jones model may not have economically plausible in detecting EM by Dechow (1995). In fact, the model is mostly applied for developed countries. It means that it cannot be applicable under strong monitoring and market regulation. Yoon (2006) introduced their model is
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more effective than the modified Jones model in Korea because their prior research found that income-increasing firms frequently employ non-cash revenues including asset-disposition gains, increases in accounts receivables and increases in inventories. Income-decreasing firms generally employ on-cash expenses including bad-debt expenses, asset-disposal losses and increases in accounts payables. Yoon (2006) model was used in Korean with these accounting items which include features of Korean companies. In addition, Islam (2011) and Alareeni (2014) applied Yoon (2006) model in Bangladesh and Palestine, respectively. From these results, Yoon (2006) models catch some characteristic of developing countries.
Hypothesis 2: Yoon (2006) model is not effective detecting EM in China.
The accrual model with Chinese characteristic
Because Yoon (2006) stated that their model especially focused on unique characteristic of Korean companies, therefore Alareeni (2014) found that Yoon (2006) model does not show better goodness of fit in Palestine. McNichols (2001) pointed that the accrual models are likely to suffer from serious omitted variables problem because the omitted variables represent noise which reduce power and create type II errors. From this perspective, it will be necessary for the accrual model to include specific features of Chinese companies. Baolong (2015) stated that when Chinese company appropriate account receivable, inventory, fixed asset and intangible asset, the price of accounting item depends on accounting method either Chinese Accounting Standard (CAS 2006) or the New Accounting Standard for Business Enterprises (ASBE) to. Particularly, the impairment test and cost method is different between CAS 2006 and ASBE. ASBE allows company to choose the First In First Out (FIFO), the Last In First Out (LIFO), the weighted average cost method or the specific identification method to assign the accrual cost of inventories. But CAS 2006 does not allow to use the LIFO. For the impairment test ASBE allows to reverse the price, but CAS 2006 does not allow to reverse the price.
These accounting methods affect the price of particular accounting items. And it will be possible for Companies to manage earnings by switching the method. Therefore,
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based model should include the change of account receivables, inventories and impairment in each years and consider those effect for extracting exact magnitude of EM.
Hypothesis 3: The new model is not effective detecting EM in China.
Factor of earnings management in Chinese pre-IPO companies
Cheng (2015) found that SOE accesses more bank loans in comparison with NSOE. Chen (2010) found that there is a negative relationship between CEO’s incentive of the SOE and bank loans. Their finding suggests that SOE have less incentive to manage their earnings due to outside support. However, their investigation is based on the modified Jones model, which might not be suitable in detecting EM in China if the model does not have enough effectiveness. Therefore, it is necessary to investigate which accounting items affects the magnitude of EM with the most suitable accrual-based model.
Hypothesis4: SOE has less incentives to manage earnings because of bank loans.
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This section elaborates on the potential misspecification problems with the current accrual-based models due to the lack of relevant variables, mismeasurement of collected raw data and the wrong classification of data.
Fist, two variables of the modified Jones model is not plausible for the study of Chinese IPO companies. (1) The lagged total asset is a stock variable, but total accrual is flow variable. (2) The PPE accounts for the non-current accrual, which expect to explain non-discretionary accrual. However, PPE itself is also the stock variable, therefore, it should be replaced by other feasible variable to explain non-discretionary accrual. Above factors suggests the lack of explanation power in the Modified Jones model.
Secondly, I suggest that the Modified Jones model can be applied in any kinds of data; however. Yoon (2006) model can be used for panel data only.
Yoon (2006) model uses the panel data analysis with between data when Yoon and Miller applied it for detecting earnings management in Korea because the model shows multicollinearity with the high correlation between (ΔREV-ΔREC)/REC and (ΔEXP-ΔPAY)/REV.
Where REV = net sales revenue, REC = trade receivables, EXP= sum of cost of goods sold and selling and general administrative expenses excluding non-cash expenses, PAY=
trade payables and Δ=change operator.
The panel data analysis is corrected over cross sectional data and times series data.
Baltagi (2008) and Hsiao (2003) pointed that the advantage of panel data analysis is (1) Panel data can eradicate multicollinearity, increase the degree of freedom and improve the unbiasedness. (2) it can control the individual diversity and let us know the common effect in data. In other hand, the negative aspects of panel data analysis is to affect the quality of statistics, for example, the feature of times series data will be minimize if the analysis uses between data. From this perspective Yoon (2006) model does not consider the time effect on their analysis.