rm asset impairment provisions cannot be reversed once they are accrued. Some studies have found that after the promulgation of the standard, listed companies are more cautious about the provision for long-term asset impairment, and the amount has decreased [29] ; some studies have found that listed companies accumulate short-term after the implementation of the new standard. The earnings management incentive for asset impairment provision is stronger than the long-term asset impairment provision [30] . Based on the above analysis, we believe that in the case of distinguishing the impairment of the convertible assets and the impairment of the non-returnable assets, the company will reduce the level of significance of the provision for impairment of the assets that can be reversed after the short selling control is higher than the non-returnable assets. Based on this, we propose the second hypothesis of this paper:

H2: After relaxing short selling control, the significance of the company will reduce the provision for impairment of assets that can be reversed is higher than the provision for impairment of non-returnable assets.

3. Research Design

3.1. Model Setting and Research Variables

Since the quasi-natural experiment of relaxed short selling is gradually carried out at different points in time, this paper draws on the model research design of Bertrand and Mullainathan [36] and Chen et al. [37] to test the relaxation of short selling control to the company. A company that is not short-sellable is used as a control group in a given year.

The test model for Hypothesis 1 is designed as follows:

WD i , t = β 0 + β 1 Short i , t + β 2 Roa i , t + β 3 Growth i , t + β 4 Ind Δ Roa i , t + β 5 IndGrowth i , t + β 6 Mshare i , t + β 7 Lev i , t + β 8 Size i , t + β 9 KS i , t + β 10 PH i , t + β 11 BG i , t + β 12 NK i , t + β 13 WL i , t + β 14 PG i , t + β 15 Log ( MV ) i , t + β 16 Turnover i , t + β 17 Volatility i , t + β 18 Age i , t + α t + α i + ε i , t

Asset Devaluation (WD): In order to test our hypothesis, we use the existing literature [29] [34] to measure the proportion of assets depreciation, that is, (the increase in current asset impairment provision―the current asset impairment reserve is reversed or resold)/the beginning of the total assets. CWD and LWD represent the ratio of the reversible asset impairment provision and the non-returnable asset impairment provision to the total assets at the beginning of the period, respectively. Since the company’s provision for asset impairment provision in the current period is usually small, the values of WD, CWD and LWD are expressed as a percentage.

Whether it can be sold short (Short): Drawing on the existing literature [19] [38] , short is a dummy variable. If a company can sell short in a certain year of the sample interval, the variable takes 1; otherwise it takes 0.If a company enters the short-selling list in 2011, the value of 2011-2016 is 1, and the value of 2007-2010 is 0; for companies that have not entered the short-selling list, the variable has a value of 0.

The rest of the control variables are defined in the variable definition as shown in Table 1.

3.2. Sample Selection and Data Sources

The data in this paper is derived from the CSMAR database and the Wind database. The research sample is owned by the A-share listed companies of the Shanghai and Shenzhen Stock Exchanges. Considering the data limitations required by the model and the time to relax short-selling control, the sample period of this paper is determined as 2008-2016, and the data is screened according to the following criteria: 1) Excluding the special nature of the financial industry, the financial industry companies are excluded. 2) Excluding samples with missing relevant variables; 3) Excluding samples for special treatment (ST). After the above screening process, 17,122 samples were finally obtained, of which 3291 were short-selling companies. In order to alleviate the influence of outliers, in this regression analysis, all continuous variables were subjected to extreme processing (Winsorize) at the 1% and 99% levels.

China’s securities market can sell short-selling stocks mainly for the following six adjustments: the first time is March 31, 2010, the stocks of the Shanghai Stock Exchange are all constituents of the SSE 50 Index, and the Shenzhen Stock Exchange is all 40 of the Shenzhen Index. The constituent stocks have a total of 90 stocks; the second time is December 5, 2011, the stocks under the Shanghai Stock Exchange are expanded to all constituents of the SSE 180 Index, and the stocks under the Shenzhen Stock Exchange are expanded to 98 constituents in the Shenzhen 100 Index; The third time is January 31, 2013, the number of stocks that can be sold in Shanghai and Shenzhen stocks increased to 500; the fourth time is September 16, 2013, the number of short-selling stocks in Shanghai and Shenzhen stocks increased from 500 up to 700; the fifth time is September 22, 2014, the number of short-selling stocks in Shanghai and Shenzhen stocks increased to 900; the sixth is the number of stocks that can be sold in Shanghai and Shenzhen add another 50 on December 12, 2016, a total of 950. Table 2 shows the distribution of short-selling stocks in the sample study interval.

Table 1. Variable definition.

Table 2. Short saleable stock distribution.

Data sources: The data in this table is derived from the CSMAR database and the Wind database.

3.3. Descriptive Statistics of Variables

Table 3 lists the descriptive statistics for the variables. It can be seen that the provision ratio (WD) of listed companies’ assets impairment provision is 0.2% on average, the median is 0, and the standard error is 0.773, indicating that the provision ratio of asset impairment provision exists big difference between different listed companies. On average, about 19.2% of the sample size is short-sellable. Descriptive statistics for the remaining variables are shown in Table 3.

4. Analysis of Empirical Results

4.1. Regression Results

Table 4 provides the test results for Hypothesis 1.

The results in Table 4 show that the Short coefficient is −0.06 after controlling other variables and is significant at the 1% level. In other words, after controlling for other factors affecting the proportion of asset impairment provision, the implementation of the loose short-selling control policy has significantly reduced the company’s asset impairment provision ratio, which is consistent with the expectation of Hypothesis 1.

In the control variables, from the internal factors of corporate governance, the company size and management shareholdings are significantly positively correlated with the asset impairment provision ratio, that is, companies with large scale or management shares will make more provision for asset impairment. The company’s total return on assets is significantly negatively correlated with the proportion of assets impairment provision, that is, the proportion of assets impairment provision of companies with high total return on assets is low. At the same time, there is a significant relationship between the variables KS, PH, BG, NK, WL used to control earnings management factors and the proportion of asset impairment provision. From the control variables related to Short, the natural logarithm of the company’s market capitalization is significantly positively correlated with the asset impairment provision. The company’s listing age is significantly negatively correlated with the asset impairment provision.

Table 5 provides the test results for Hypothesis 2. In the test hypothesis 2, referring to the existing literature (Wei Chunyan and Chen Lei, 2015), the asset impairment is divided into the convertible part (CWD) and the non-returnable part (LWD) according to the details of the impairment items disclosed in the notes to the financial statements. Specifically, the reversible part includes accounts receivable, inventory, consumable biological assets, deferred income tax assets, financial lease unguaranteed residual value, amortized cost financial assets, entrusted loans, debt assets and debt instruments available for sale, etc.; the non-returnable portion is mainly for impairment of fixed assets and intangible assets. Column (1) in the table below reports the test results when the dependent variable is the reversible asset impairment, and column (2) reports the test result when the dependent variable is the non-returnable asset impairment.

Table 3. Descriptive statistics.

Data sources: The data in this table is derived from the CSMAR database and the Wind database.

Table 4. Proportion of relaxed short selling and asset impairment.

Data sources: The data in this table is derived from the CSMAR database and the Wind database.

Table 5. Relaxation of short selling control and asset impairment ratio―distinguishing the impairment of convertible assets and the impairment of non-returnable assets.

Data sources: The data in this table is derived from the CSMAR database and the Wind database.

The results in Table 5 show that when the dependent variable is the reversible asset impairment, the short coefficient is −0.043 and is significant at the 5% level, and when the dependent variable is not convertible, the coefficient of short is −0.009, which is only significant at the level of 10%. And the coefficient of the variable short has statistically significant difference in the grouping regression. The regression result is consistent with the expectation of Hypothesis 2, that is, after relaxing the short selling control, the company will reduce the provision for impairment of assets that can be transferred back is more significant than the provision for impairment of non-returnable assets.

4.2. Robustness Test

4.2.1. Using Alternative Methods to Measure Asset Impairment

In order to verify the robustness of the research conclusions, this paper further measures the asset impairment based on the asset impairment loss confirmed in the income statement. The specific calculation method is the current asset impairment loss divided by the total assets at the beginning of the year.

The results in Table 6 show that after controlling other variables that affect asset impairment, Short’s coefficient is −0.089, and is significant at the 1% level, that is, the implementation of the relaxed short-selling control policy significantly reduces the company’s asset impairment losses.. This conclusion further supports the research hypothesis of this paper.

4.2.2. Using Alternative Methods to Measure Relaxed Short Selling

At the same time, this paper uses the margin ratio to further measure the relaxation of short selling, and the margin ratio (S_Ratio) is calculated by the margin sales amount/circulation market value.

The results in Table 7 show that when the dependent variable is asset impairment (WD), the coefficient of S_Ratio is −1.523 and is significant at the 1% level; when the dependent variable is returnable to asset impairment (CWD), S_Ratio The coefficient is −0.943, which is also significant at the 1% level; when the dependent variable is non-returnable to asset impairment (LWD), the coefficient of S_Ratio is −0.247, which is only significant at the 5% level. In the second and third columns, the coefficient of the variable short has statistically significant difference in the grouping regression. This further validates the content of Hypothesis 1 and Hypothesis 2.

Table 6. Relaxation of short selling controls and asset impairment losses.

Data sources: The data in this table is derived from the CSMAR database and the Wind database.

Table 7. Ratio of securities lending ratio to asset impairment.

Data sources: The data in this table is derived from the CSMAR database and the Wind database.

The above empirical test results can fully support the hypothesis of the article. After relaxing the short selling control, the company reduced the proportion of the provision for impairment of assets, and the significance of the company will reduce the provision for impairment of assets that can be reversed is higher than the provision for impairment of non-returnable assets. In the robustness test, the conclusion is still true after replacing the main variables.

5. Conclusions

Existing literature studies have shown that the post-mortem price discovery function of short selling mechanism can be used as a pre-existing constraint mechanism to limit the opportunistic behavior of management and significantly reduce the company’s earnings management level, while there are many kinds of earnings management motives such as avoiding losses, “big bathing” and smoothing profits in the provision of asset impairment. Therefore, this paper focuses on the effect of relaxing short selling control on the accrual behavior of listed companies’ asset impairment provisions, and further investigates whether this effect will be different in the case of distinguishing the reversible asset impairment and the non-returnable asset impairment.

This paper takes the listed companies in Shanghai and Shenzhen in 2008-2016 as the research samples, and examines the aforementioned problems by means of the exogenous event of loose short selling control. The research in this paper finds that after relaxing the short selling control, the company reduces the proportion of the provision for impairment of assets, and the company’s reduced provision for the provision for impairment of assets can be higher than the non-returnable asset impairment provision. This also provides a basis for the relaxation of short-selling regulations to help companies reduce their earnings management, and provides an explanation for the continued expansion of short-selling targets.

The research in this paper still has some shortcomings: Since short selling transactions started late in China, the current stocks that can be sold short account for a small proportion of the overall sample. During the sample period, the sample size of stocks that can be sold short is only 19.2% of the total sample.

Cite this paper
Li, Z. (2018) Lifting of Short Selling Constraints and Accounting Policy Options—Empirical Data from Asset Impairment Provision. Modern Economy, 9, 1776-1791. doi: 10.4236/me.2018.911112.
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