




































American Research Journal of Economics, Finance and Management 

Volume 10 Issue 4, October-December 2022 

ISSN: 2836-9416 

Impact Factor: 4.85 

Journal Homepage: https://americaserial.com/Journals/index.php/ARJEFM, 

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1 | P a g e  

ACCRUALS AND EARNINGS MANAGEMENT: IMPLICATIONS 
FOR STOCK LIQUIDITY 

 
 

1Dr. Samir A. Ben Ammar and 2Dr. Nadia R. Chaouch 
1Associate Professor at the Graduate Institute of Accounting and Business Administration, University 

of Mannouba, Tunisia 
2Professor in the Graduate Institute of Management and President of the Research Laboratory 

Gouvernance d'entreprise, Finance Appliquée et Audit. 
 

Abstract: The quality of financial information is a central theme in accounting and finance 
literature, with significant implications for market efficiency and liquidity. As emphasized by Levitt 
(2000), high-quality financial information serves as the cornerstone of a robust and efficient market, 
essential for maintaining liquidity and market efficiency. Quality accounting standards, according to 
Levitt, contribute to improved liquidity and reduced capital costs, making them vital for market 
health. 
This study delves into the role of accounting figures as critical financial indicators that enhance 
information efficiency and bolster market outlook and liquidity. Drawing on the insights of Chung 
(2009) and Bachtiar (2008), it explores how high-quality accounting standards, when effectively 
disclosed, can lead to higher returns, improved liquidity, and reduced capital costs. The investigation 
further examines the link between the quality of disclosed earnings and stock liquidity through the 
ask-bid spread, as proposed by Bachtiar. 
In the context of emerging markets like Tunisia, liquidity is of paramount importance and directly 
influences the pricing process. This research adds depth to the literature by examining the 
relationship between earnings management, information disclosure, and stock liquidity, as explored 
in studies by Allayannis et al. (2009), Iatridis et al. (2009), Matoussi, Karaa, and Maghraoui (2004), 
Bhattacharya, Desai, and Venkataraman (2013), and Fizazi et al. (2009). 
Keywords: Financial information quality, Market efficiency, Stock liquidity, Accounting standards, 
Emerging markets. 
  
I. Introduction  
Quality of financial information has been the topic of countless debates in the accounting and financial 
literature. Indeed, according to Levitt (2000), it is the driving force of a powerful and an efficient 
market. Without it, liquidity diminishes and market efficiency ceases to exist. The author adds that high 
quality accounting standards consist in improving liquidity and reducing capital cost. Accounting 
figures, as one of the financial indicators, reduce inefficiency of information and contributes to 
improving market outlook and liquidity. Stocks liquidity can thus be perceived as a measure of market 
efficiency and used as an effective tool of disseminating useful information (Chung 2009). Bachtiar 
(2008) argues that high returns disclosed through high quality accounting standards can eventually 
improve liquidity and reduce capital cost. Furthermore, Bachtiar checked the inherent hypothesis of a 

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Volume 10 Issue 4, October-December 2022 

ISSN: 2836-9416 

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2 | P a g e  

positive relationship between the quality of disclosed earnings of firms and the liquidity of their stocks 
through the ask-bid spread. By increasing the liquidity of stocks, transaction costs may decrease. 
Liquidity plays also an important role in the pricing process. It represents a key concept in emerging 
markets like Tunisia. Numerous studies have focused on the relationship between earnings 
management and disclosure (Allayannis et al., 2009;Iatridis et al., 2009), while others have examined 
the relationship between information disclosure and stocks liquidity(Matoussi, Karaa, and Maghraoui 
2004; Bhattacharya, Desai, and Venkataraman,2013; Fizazi et al. 2009 ).   
Nevertheless, studies of the relationship between earnings and liquidity management remain rare, 
especially in emerging markets (Beneish et al., 2012, Peterson et al., 2015, Sohn 2016). Thus, our study 
will aims inextending the debate on this issue by examining the impact of earnings management on 
market liquidity in the Tunisian context. In Tunisia, few researches have been focused on the 
relationship between the practice of earnings management and liquidity, while the issue of accounting 
manipulation was regularly addressed by researchers. In the United States, many researchers have 
explicitly addressed the practices of earnings management. Several recent studies, such as those of 
Mastumra (2003) and young (2005) have attempted to determine the impact of an earnings 
management policy on the financial market.   
Therefore, it seems appropriate to investigate this relationship in a sample of listed Tunisian 
companies. Indeed, studying emerging markets like the Tunis Stock Exchange (TSE), earnings 
management may be very revealing because it traces the specificity most pursued by stock market 
investors. Indeed, our study of the Tunisian stock market comes under this perspective. This emerging 
and recent market is known by a strong information asymmetry and very low information efficiency. 
These specificities may lead us to identify earnings management practices specific to the Tunisian 
market. Therefore, we can determine the degree of impact of these accounting practices on investor 
behavior via stocks liquidity. The aim of this paper is to determine whether earnings management has 
an impact on stocks liquidity for the case of Tunisian firms. This amounts to studying the relationship 
between liquidity (via the askbid spread) and accruals using the modified models of Jones (1995). 
Therefore, this paper is structured as follows: the first section reviews the relevant literature. The 
second section presents our research hypotheses and methodology, while the third section focus on the 
results obtained on the Tunisian stock market. In the last section, a discussion of the results and a 
conclusion will be proposed.   
II. Literature Review  
1. Earnings Management Theories 
The earnings management theories are based on two main hypotheses. The first hypothesis assumes 
that information asymmetry between informed and less informed shareholders is likely to be reduced 
by disseminating information (Glosten and Milgrom 1985). Such an accounting policy-based signaling 
leads to a reduction in the askbid spread and an increase in liquidity. The second hypothesis assumes 
that an information disclosure policy reduces information-searching costs. This results in lower 
transaction costs and a higher transaction volume. Kraft et al. (2014) show that reducing information 
asymmetry is a basic fundamental to the decision to publish manipulated earnings. Liquidity is 
considered as the facility to trade large volumes of stocks without causing a significant price shift during 
a narrow time span (Etemadi and Resayian 2010). This concept heavily depends on informational 

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3 | P a g e  

transparency. Indeed, information asymmetry between investors reduces transparency of market 
transactions and may lead to dysfunctions. Botosan and Plumlee (2002) argue that information 
inefficiency reduces market liquidity and increases capital cost. Earnings management also helps to 
moderate information asymmetry, since stocks become more liquid (Chung, 2009). At present, only 
few studies have explored the relationship between earnings management and stocks liquidity. 
Richardson (2000) found that managers tend to manipulate earnings when there is a strong 
information asymmetry.  
2. Earnings and Liquidity Management Research  
In the literature, there are several measures of market liquidity. Some of them are the transactions 
volume, the turnover ratio and the ask-bid spread. In this context, relevant empirical research can be 
classified into two main trends:  
- The first trend included studies on measuring liquidity through the ask-bid spread (Ascioglu et 
al., 2012, Kan, 2013, Bafghi et al. (2014)). These studies consider the ask-bid spread as the best 
estimator of stocks liquidity, and they focused on the adverse selection dimension of the ask-bid spread. 
They concluded that companies that use earnings management as their performance measurement 
disclose higher adverse selection costs. As a direct result of these costs, liquidity providers widen their 
spreads, reducing thus liquidity.  
In the Spanish context, Livnat et al. (2008) investigate on the relationship between disclosure and 
stocks liquidity over the 1994-2000period. The authors found a positive relationship between liquidity 
and financial disclosure. Lakhal (2008) examined the effect of quarterly earnings disclosure on market 
liquidity to show that they reduced information asymmetry between different market participants and 
improved stocks liquidity. In the German context, Grüning et al. (2010) found that information 
disclosure in annual reports improves liquidity by acting on investor forecasts who adjust their 
portfolios. In the Tunisian context, Triki and Omri (2008), examining a sample of 20 Tunisian firms 
over the 2000-2005period,found a negative relationship between earnings quality and the ask-bid 
spread 
The second trend included studies that examined liquidity through transaction volume. These studies 
found a positive correlation between the amount of IAS to US GAAP-recon ciliated earnings and 
transaction volume (Peterson et al., 2015, Yuan and Cheng , 2016). Chen and Sami (2006) studied the 
reaction of the US financial market in terms of transaction volume when changing accounting tools. 
The studied sample consists of 38 non-US companies (ten countries) listed on the American market 
between 1995 and 2001. After running several statistical tests, positive correlation was found between 
the amount of readjusted earnings and transaction volume. Thus, it was concluded that US investors 
take into account earnings informational content in their investment decisions.  
Most studies taking transaction volume as a liquidity measure expand in three main directions: its 
relationship to the ask-bid spread, price change and information. Subscribing to this perspective, 
several studies conducted on the US market examined the reaction of stock prices following a disclosure 
of manipulated earnings as information to investors. This methodology consisted of determining the 
abnormal volumes around the disclosure date of managed earnings. 
 
 

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4 | P a g e  

III. Methodology   
Focusing on the Tunisian context, the stocks liquidity will be investigated through the ask-bid spread 
and discretionary accruals according to the modified models of Jones. 
1. Tunisian Context  
In Tunisia, as soon as the New Market is created in 1996, new companies, small and with a high growth 
potential, can access equity markets in order to raise funds such as to ensure their growth (Matoussi 
2004). These companies seemed to be highly motivated to manage their earnings. Tunisian accounting 
regulations are mainly legal in origin. In addition to the regulatory framework, companies should 
comply with the code of commercial rules, which contains few accounting rules or principles. In theory, 
such an absence of legal constraints offers companies a large number of accounting tools. This situation 
makes the Tunisian context as an interesting ground to study earnings management practice. First, 
Tunisian accounting standards offer managers considerable flexibility to choose accounting practices. 
Moreover, the Tunisian context is known by a concentration of corporate ownership and a relatively 
illiquid financial market. In Tunisia, unlike other countries like North America, earnings disclosure 
attracted particularly investors ‘attention, motivating thus firms to engage in earnings management. 
Our assumption is that the Tunisian market is likely to represent a fertile ground in terms of an upward 
earnings management.  
2. Research Hypotheses  
Based on previously mentioned theoretical and empirical foundations, some hypotheses can be 
deduced such as:  
• H1: there is a negative relationship between discretionary accruals and market liquidity Chung 
et al (2009) examined a sample of US companies, assuming that earnings management reduces stock 
liquidity. They measured earnings management through discretionary accruals over the October 2001 
to December 2002period. The price range was also used as a liquidity indicator.  
Dumontier et al. (2002), studying the French market found that investors admit manipulations as soon 
as they have the means to detect them. Accordingly, Ascioglu et al. (2011) used a triple measure to 
determine the impact of earnings management on stock market liquidity. The first measure consists of 
accounting data while the other two relate to real earnings management, which included operating cash 
flow and discretionary costs. The results point to a direct relationship between illiquidity measure and 
earnings management through discretionary accruals. 
• H2: discretionary accruals explain liquidity better than non-discretionary accruals. A number of 
univariate regressions in which the dependent variable is liquidity should be run whereas the 
independent variable is one of earnings management components (discretionary, non-discretionary 
accruals) in each regression.   
• H3: structuring total accruals into discretionary and non-discretionary accruals better explains 
liquidity. By decomposing total accruals into discretionary and non-discretionary accruals, their 
explanatory power improves.  
• H4: investors react according to the direction of earnings management (upward or downward).  
3. Variables and Model  
A panel data estimation technique was used in order to test the proposed hypothesis on the relation 
between earnings management and market liquidity. Specifically, we exploited the models of Chung et 

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5 | P a g e  

al. (2009) and Bafghi et al. (2014), based on the ask-bid spread as a measure of liquidity. The ask-bid 
spread is interesting in that it takes into account the notion information asymmetry. The market is all 
the more liquid because the difference between the best selling price and the best purchasing price is 
small (Ascioglu et al., 2012, kan 2013). It was proved to be the most appropriate measure for the 
Tunisian context and the most important determinant of liquidity of the Tunis stock exchange 
(Matoussi and Zemzem 2004). The proposed models are as follows (1-3):  
LIQit 0 1TACit 2SIZEit 3VOLit 4SPit 5Rit 6VRit it                   (1)  
LIQit 0 1DACit 2SIZEit 3VOLit 4SPit 5Rit 6VRit it                   (2)  
LIQit 0 1NDACit 2SIZEit 3VOLit 4SPit 5Rit 6VRit it                  (3)  
where : LIQit :spread of firm i at moment t.  
TAC :total accruals of firm i at moment t.  
DACit :discretionary accruals of firm i at moment t.  
NDACit :non-discretionary accruals of firm i at moment t.  
SIZEit :market value of firm i at moment t.  
VOLit :average trading volume of firm i at moment t.  
SPit :average stock price of firm i at moment t.  
Rit: stock return of firm i at moment t.  
VRit :stock return volatility of firm i at moment t.  
Opting for the decomposition method is almost motivated by the specificity of the Tunisian context, as 
a controlled market. Therefore, we have chosen the model of Chung, Sheu, and Wang (2009). Bafghi et 
al. (2014), considered to be among the most suitable models to estimate the ask-bid spread. Moreover, 
the authors believe that this model provides the best liquidity estimators. Our models relate total 
accruals, discretionary and non-discretionary accruals to firms' stocks liquidity after checking for the 
contribution of each. They also enable to estimate the effect of earnings management on liquidity. First, 
they distinguish between discretionary and non-discretionary accruals as well as the perception of their 
effect on firm liquidity. Second, they take into account the effect of other variables likely to affect stocks 
liquidity.  
Comparing the coefficients of determination (R²) of the models in (1) and (2) will allow us to check 
whether the variable "Discretionary Accruals (DAC)" explains liquidity and detects any additional 
information contained in the discretionary accruals likely to affect total accruals (TACs). To this end, 
the modified model of Jones’s for earnings management was selected for this study. In summary, total 
accruals are decomposed in equations (2) and (3) into nondiscretionary accruals (NDACs) and 
discretionary accruals (DACs). This will determine the additional explanatory power of the 
discretionary (non-discretionary) component of accruals in our liquidity measurement model.  
a. The endogenous variables 
Market liquidity 
The theory provides a number of liquidity measures: the ask-bid spread of illiquidity ratio, transaction 
volume, etc. In our study, we measured this variable by the average annual spread (Attig and al. 2006 
and Bafghi et al., 2014), as it had been shown that it was the most appropriate measure for the Tunisian 
context and most likely to determine liquidity of the Tunis stock exchange (Matoussi and al., 2004). 

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The spread was calculated for each sample value and for each day, as the difference between the best 
purchasing price and the best selling price divided by the average of the two prices.  
The spread of the Tunis stock exchange that corresponds to the indicated market costs was selected to 
measure liquidity (4).  
Askit Bid   it 
SPRDit= Ask it Bid it                               (4)  
2 
With:  
Askit = the price ask of stocki on day t. Bidit = the price bid of stocki on day t.  
Earnings Management Component  
As indicated above, the modified models of Jones (1995) were adopted for the earnings management 
measurement  
(5).  
TACit / Ait 1 (1/ Ait 1) 1( REit / Ait 1) 2(PPEit / Ait 1) e it                     (5)  
 with :  
TACit :total accruals of firm i in year t.    
Ait-1 :total assets at the end of year t-1.  
ΔREit :(CA) net total revenues between t and t-1 of firm i.  

REit Revit Rec it  
ΔRevit : total revenues variation between t and t-1 of firm i.                     
ΔRecit : receiveables variation between t and t-1 of firm i.  
PPEit :gross provisions of firm i at moment t.  
eit :residuals of discretionary accruals model of firm i in year t (DACit). βi: Coefficients estimated for 
firm i. α : Constant term  
b. The Control Variables  
According to the literature many determinants of the ask-bid spread, including transaction volume, 
price volatility, stock price and firm size (Amihud 2002, Brockman and Chung 2001) could be provided. 
A fortiori, Ascioglu et al. (2012) highlighted the positive relationship between transaction volume and 
liquidity level, while others found a negative relationship with size and price (Amihud 2002).  
Transaction Volume  
An increase in transaction volume involves a serious disequilibrium in the equity market. It implies 
additional costs that should be compensated by widening the spread. Atiase and Bamber(1994) 
considered transactions volume s a proxy of information asymmetry. Moreover, Stoll (1978) shown that 
transaction volume and risk affect the stock holding cost and that stock price was a proxy for the 
unobservable minimum cost. The authors argued that spreads negatively relate to transaction volume. 
Similarly, (Chen et al., 2007) found that liquidity is an increasing function of transaction volume.  
Stock Price  
The financial literature assumes that price significantly explains stock liquidity. Indeed, the studies of 
Attig et al., (2006), Brockman and Chung (2001), and Ajina et al., (2015) found that stock price 
positively correlates with liquidity.    
Stock returns  

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Numerous models studying the relationship between returns and liquidity have been developed in the 
literature. Most of them indicate that the expected returns negatively correlate with liquidity (Amihud 
2002). Indeed, this negative sign was explained by investors requiring a liquidity premium to 
compensate the high transaction costs. Thus, under equilibrium uninformed investors require 
compensation for holding stocks with high private information.  
Returns Volatility  
Asymmetry of market information is measured by returns volatility. Accordingly, any change in price 
produced by a change in investor forecasts results in an increase in returns variance (or volatility). In 
this regard, Ascioglu et al. (2007) shown that volatility had an impact on inventory cost and stock risk 
management, and therefore widened the spread. Empirical studies in the US market such as those of 
Stoll (1978), Roulstone (2003) and Wang et al. (2009) revealed a positive relationship between 
volatility and ask-bid spread.   
Firm Size  
Firm size is considered to approximate the degree of information asymmetry and therefore adverse 
selection costs. Under the same perspective, Bhattacharya et al. (2013) shown that small firms 
presented a larger information asymmetry than large firms. On the other hand, stocks of small-
capitalized firms were less liquid than stocks of largecapitalized firms (Brown and Hillegeist 2007). 
Indeed, stock liquidity depended on firm size for two reasons. First, a large firm attracts the interest of 
analysts and investors. Second, its size allows it to disseminate a large amount of information that leads 
to reducing information asymmetry and improving liquidity.   
c. Sample and study period  
With the aim of avoiding missing data problems that may result in biased estimations, stocks with a 
low number of trading days in our sample were disregarded, allowing us to retain the 23 most liquid 
stocks for our study. Then, only 299 observations were considered to represent 23 firms over the 2010-
2012period.   
As for the Tunisian data, firm liquidity data was collected from the Tunis stock exchange, and the 
accounting figures were extracted from the official bulletins published by the Financial Market Council 
(CMF).   
IV. Results and discussion   
The descriptive statistics of the studied variables will be detailed, with respect to various relevant tests. 
The models parameters will be estimated and the contribution of discretionary (non-discretionary) 
accruals to stock spreads will be determined.  
1. Descriptive statistics  
A descriptive analysis of the studied variables was carried out initially (Table 1). It resulted in the 
following observations: 
• Accounting results disclosed by Tunisian firms seems to be lower than cash flow, which explains 
the negative sign of total accruals. This negative sign is mainly generated by non-discretionary accruals.   
• Earnings management through discretionary accruals carries additional information that does 
not necessarily exist in non-discretionary accruals, which confirms our hypotheses formulated above.  
Table 1. Descriptive Statistics 

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  VARIABLES   Average   Standard 
deviation   

Min   Max   

Dependent 
variable   

LIQ   0.676   1.242   -2.207   7.821   

Independent 
variables   

TAC1   
TAC2   
NDAC1   
NDAC2   

0.0576  
0.0576  
0.0576   
0.0552   

0.130   
0.130   
0.0341   
0.0225   

-0.256   
-0.256   
-0.149   
0.0156   

0.892  
0.892  
0.122   
0.100   

 DAC1   6.11e-09   0.125   -0.325   0.811   
 DAC2   0.00240   0.127   -0.271   0.796   

Control 
Variables   

SIZE   
R   
SP   

16.37  18.53   
31.00   

1.707  34.38   
39.70   

12.13   
-40.46   
1.370   

19.83  
380.7   
203.4   

 VOL   2.700   0.169   2.212   2.886   
  
  
2. Tests specific to panel data  
To investigate the components of earnings management that explain stock liquidity of Tunisian firms, 
econometric regressions on panel data covering the 2000-2012period was carried out in order to 
deduce the appropriate estimation methods. To this end, we proceed in two steps: 
- First, the absence of any multi co linearity problem between the independent variables was checked, 
using the Pearson correlation test between the continuous variables and the Variance Inflation Factor 
(VIF) test. The VIF values were much lower than the generally required 5% or even 10% significance 
level. Therefore, correction can be avoided (Tables 1 and 2, Appendix I-1).  
Table 2 illustrates the Pearson correlation matrix, reporting the relationships between the variables of 
the models (M1, M2 and M3)  
The VIF (Variance Inflation Factor) and Pearson correlation tests indicate that the correlation between 
the variables is acceptable since the variance inflation factors (VIF) have values below 10. All Pearson 
correlation coefficients do not exceed 0.8(Tables 2). 

 
variables. In addition, the correlation coefficients are small (maximum of 0.3453 for prices and 
LIQ).This indicates a direct relationship between the dependent variables and the control variables.   

Table 2: Results o f  the   Pearson Correlation Test (Modified Models Of Jones)   
  

  LIQ   TAC1   DAC1   NDAC1   SIZE   VOL   SP   R   VR   
LIQ   1.0000                   
TAC1   0.0117   1.0000                 
DAC1   0.0231   0.9650   1.0000               
NDAC1   - 0.0405   0.2608   - 0.0015   1.0000             
SIZE   - 0.0682   0.3658   0.1649   0.7878   1.0000           
VOL   0.2556   0.0391   0.0400   0.0017   0.0024   1.0000         
SP   0.3453   0.0505   0.0649   - 0.0465   - 0.0551   0.2247   1.0000       
R   0.0247   - 0.0426   - 0.0543   0.0375   - 0.0525   - 0.0379   0.0801   1.0000     
VR   - 0.1295   - 0.0135   - 0.0052   - 0.0321   - 0.0459   0.0200   - 0.1123   - 0.0389   1.0000   

  
As shown in Table 2 above, no significant correlation was found between the dependent and independen t  

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The results conclude to a positive relationship between stock spreads and discretionary accruals (2). 
This result validates the considered hypothesizes. A second measure of multi co linearity was thus used 
basing on VIF values. VIF values were ranged within 1.02 and 2.69 when using the modified models of 
Jones. These values are perfectly below the accepted critical value of 10, which leads us to conclude that 
there is no multi co linearity problem. 
- Second, before estimating our models it is necessary to run different preliminary tests in order to 
ensure an efficient use of data. Indeed, panel data requires adapted estimation methods. The results of 
these tests are presented in Table 4.  
Table 4: Results of the Hausman Test and the Validity of Specific, Heteroscedasticity, 
Autocorrelation Effects 

 

F  1.26 1.938  
  
The linearization of the panel data was performed and included the dependent variable ask-bid spread 
(LIQ). Thus, the STATA software version 13.0 for Windows was used.  At the beginning, the presence 
of specific effects was conducted and based on various homogeneity tests. The collected results led us 
reject the null hypothesis of homogeneity of all the parameters. The calculated Fisher statistics clearly 
exceed the tabulated threshold with zero probabilities (Prob> F = 0).Therefore, panel data estimation 
method is that with specific effects. Thus, fixed and random effects models were estimated in order to 
test whether the specific effects result from the heterogeneity of the constants or that of the coefficients. 
Accordingly, the Hausman test was applied. The probability of the Chi-square statistics shows zero 
values for the modified models of Jones (1), (2) and (3)leading us to select the fixed effects model.   
Finally, the Breush-Pagan and Wooldridge tests were conducted to control for heteroscedasticity and 
errors autocorrelation. The probabilities of each LR2test point to an errors heteroscedasticity problem 
and an absence of autocorrelation.  A re-estimation of the model after correction using the White 
method with the Robust command (Petersen, 2009), was finally done.  
3. Results of the Regressions  
The coefficients of determination (R²) of the first three models were compared when running multiple 
regressions, with the aim of identifying the variables determining stock liquidity. These variables are 
total accruals, discretionary accruals and non-discretionary accruals. It aims at assessing the 

P-value   0   
 Wooldridge test   

  ( 1 )   ( 2 )    ( 3 )    
Hausman   test    

Chi - deux   40.30   41.51   61.09   
P - value   0   0   0   

Breuch - Pagan   test   
LR2   53.34   53.44   52.40   

0   0   
  0.978   

P - value   0.301   0.334   0.179   

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explanatory power of the three models (1), (2) and (3) in the Tunisian context. Multiple regressions 
were run by disaggregating total accruals into discretionary and non-discretionary components (DAC 
and NDAC) in order to test the suggested hypotheses H1 and H2. The results are presented in Table 5.  
Table 5: Results of the Regressions: Liquidity and Acruals  

  Modified models of Jones    
Earnings management 
Measures   

Total Accruals   Discretionary 
Accruals   

Non-
Discretionary 
Accruals   

  (1)   (2)   (3)   
VARIABLE   LIQ   LIQ   LIQ   
Earnings management   1.287   1.243   01.411   
  (2.32)**   (2.32)**   (0.12)   
Size   -1.273   -1.293   -1.315   
  (41.06)***   (47.11)***   (18.59)***   
SP   0.002   0.002   0.002   
  (1.09)   (1.08)   (1.19)   
Vol   0.052   0.052   0.053   
  (1.95)*   (1.96)*   (1.76)*   
Return   -0.006   -0.006   -0.006   
  (1.56)   (1.54)   (0.19)   
VR   0.005   0.005   0.006   
  (0.14)   (0.15)   (0.19)   
Constant   -6.646   -6.918   -7.280   
  (10.04)***   (11.01)***   (6.59)***   
Observations   299   299   299   
Number of firmes   23   23   23   
R²   (0.82)   (0.76)   (0.70)   
Stat -F   4.93   4.86   6.54   
F Prob   0   0   0   

  
Notes: ***, ** and * denote significance levels of 1%, 5% and 10% respectively. Values in parentheses 
are "t-Student". 
The investigated model has considerable explanatory powers. Indeed, the respective coefficients of 
determination R2 are 82% for (1), 76% for (2) and 076% for (3). The Fisher test on the overall model 
significance shows that at the 1% level there is at least one independent variable whose impact on the 
dependent variable is significant. The respective Fisher's statistics for both models are F (6, 270) = 4.93 
for (1), 4.86 for (2) and 6.54 for (3). The coefficients of determination of these regressions reveal the 
relevance of the different components of accruals in explaining the ask-bid spread. If the coefficients 
are all significant, then each accruals component carries information about the ask-bid spread.  
The regressions in Tables N ° 5 estimate the effect of earnings management on stock liquidity. The 
results indicate a positive and a significant relationship between accruals (TAC, CAD) and the ask-bid 

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spread. However, the relationship between non-discretionary accruals and the ask-bid is insignificant 
(3). In line with previous research, the results of the proposed study validate the hypothesis that market 
liquidity is a decreasing function of earnings management. These results are consistent with studies on 
the US market. This result corroborates those of Ascioglu et al. (2012); Bafghi et al. (2014); Peterson et 
al. (2015) and Sohn (2016). Similarly, Aharony, Lee, and Wong, (2000) indicated that Chinese firms do 
not have the same motivations for managing earnings like US firms. Worth noting is that the manager 
is not a shareholder in the Chinese sample.   
These firms have no interest in managing earnings. In such a context, it is the state which encourages 
firms to manage earnings in order to increase profits earned in terms of foreign currencies through 
selling stocks to foreign investors. Moreover, Hepworth (1953) argued that investors show more 
confidence to firms that generate stable and regular profits. Similarly, Faez et al. (2014), using the 
modified models of Jones on a sample of 72 firms examined over the 2005-2013period found that 
earnings management enhances information asymmetry and reduces liquidity. Indeed, studying an 
American sample, Ascioglu et al. (2012) found the same result using two measures of liquidity: ask-bid 
spread and transaction volume.  
The impact of the control variables on the ask-bid spread is assessed by the modified models of Jones 
(2). The t-Student test of the individual significance of the variables shows that firm size and volume 
significantly affect the ask-bid spread respective at the 1% and 5 % significance levels. This validates the 
hypothesis that firm size and transaction volume are complementary tools to the ask-bid spread. 
Consistent with our predictions, size of Tunisian firms negatively affects the ask-bid spread. This is 
consistent with several studies where size has a negative effect on the ask-bid spread. Many authors 
found similar results, like Durnev and Kim (2003). These studies in different contexts found a negative 
relationship between size and the ask-bid spread.   
The obtained results also show that stock price, returns and volatility do not significantly affect the ask-
bid spread. Moreover, we found that total accruals better explain the ask-bid spread than non-
discretionary accruals. Furthermore the collected results reveal that earnings management increases 
agency costs and information asymmetry. Therefore, liquidity providers bear higher costs and therefore 
a higher ask-bid spread and a less liquid market. These results allowed us to conclude that liquidity 
providers are aware that earnings management of the Tunisian firms of our sample is not very high. 
Moreover, this result is in line with the thesis that investors prefer firms with more stable earnings. 
Such a finding encourages us to test in a second phase the type of relationship between the direction of 
earnings management and market liquidity.  
Researchers like Easton, Harris and Ohlson (1992) argued that investors buy profits. Institutional 
investors are not attracted by firms with highly volatile earnings and are considered to be risky. Thus, 
institutional investors tend to favor firms that increase their profits. The finding on the study of the 
relationship between non-discretionary earnings and the ask-bid spread is that Tunisian investors do 
not give non-discretionary accruals its fair value. The explanatory power increases from 82% (R²) for 
model (1) to 70% for model (3) (Table N ° 5).  However, the relationship between discretionary accruals 
and the ask-bid spread could be studied. 
The results presented above show that the amounts manipulated by Tunisian firms positively correlate 
with the ask-bid spread. Nevertheless, the importance given by Tunisian investors to these accruals 

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remains lower than that given to non-discretionary accruals insofar as the coefficient of discretionary 
accruals is 1,243 in model (2)and significant at the 5% level, while the coefficient of non-discretionary 
accruals, which is 1.411(3), is not significant. It should be mentioned that our interpretations rely on 
the ability of the models of Jones (1995) to detect such accounting practices. Thus, we validate the 
suggested second and third hypotheses indicating that the discretionary accruals of Tunisian firms have 
an additional information content compared to the non-discretionary accruals and better explain stock 
liquidity. It should be noted that most of the studies, which used the ask-bid spread as a measure of 
liquidity, found a significant relationship with earnings management. However, using transaction 
volume as a measure of liquidity, some studies, such as those of Nowghabi et al. (2015) foundnon-
significant results.  
V. Conclusion  
This paper is focused on empirically evaluation of the impact of discretionary accruals on liquidity 
through the ask-bid spread and the effect of discretionary accruals direction. To this end, a research 
modified model of Jones was selected to evaluate the linear relationship and the effect of earnings 
management direction on the relationship between the spread and accruals by integrating a 
dichotomous variable. An explanation of the value of questioning the classical framework treating the 
relationship between liquidity and earnings management was done, such as to validate the negative 
relationship between these two variables in an emerging country like Tunisia. Moreover, a study of 
various approaches was proposed, and motivated by a wide range of theoretical arguments. In addition 
to high risk and returns, liquidity is another factor that motivates investors to purchase a given stock 
or reduce their ownership of another. This is particularly important for investors insofar as it motivates 
them to compensate for their lack of liquidity. Referring to experts' opinions, managing earnings is one 
of the factors that best determines liquidity.   
In the same vein, it is likely that upward earnings management will result in higher liquidity costs and 
lower stock liquidity. As a result, aggressive earnings management reflects low accounting information 
quality. As a first hypothesis, the relationship between earnings management (the various components 
of accruals) and the ask-bid spread was examined. We found that each of these earnings management 
components significantly informs about firm liquidity. In line with previous research, the obtained 
results reveal the positive relationship between the ask-bid spread and earnings management of 
Tunisian firms. An increase in discretionary accruals is perceived as an earnings management reflecting 
an unethical behavior or an unsatisfactory source of information. Moreover, our results corroborate 
those of Ascioglu et al. (2012) kan (2013) and Bafghi et al. (2014), who used the ask-bid spread as a 
measure of liquidity. The authors found that earnings management increases agency costs and 
information asymmetry. According to this finding, liquidity providers bear higher costs and thus a 
wider spread and a less liquid market. These results allowed us to conclude that liquidity providers are 
aware of earnings management and they prefer firms which generate more stable profits. In particular, 
such a practice is not observed in the Tunisian firms of our sample.  
To support this observation, the relationship between earnings management direction and liquidity 
through the ask-bid spread and the different control variables (size, returns and transaction volume) 
was examined. The results pointed to a significant relationship between earnings management and the 
ask-bid spread. Explicitly, investors react according to earnings management direction. As for the 

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control variables, the correlation analysis confirmed our conclusions as we found a negative and a 
significant correlation between the ask-bid spread and firm size in the two measurement models. This 
negative effect can be attributed to the substantial control practiced over large firms.  
Appendix. Earnings Management and Liquidity  
 AppendixI-1.Vif Tests 

 
References   

Aharony, Joseph, Chi-Wen Jevons Lee, and Tak Jun Wong. 2000. “Financial Packaging of IPO Firms 
in China.” Journal of Accounting Research 38 (1): 103–26.  

Ajina, Aymen, Faten Lakhal, and Danielle Sougné. 2015. “Institutional Investors, Information 
Asymmetry and Stock Market Liquidity in France.” International Journal of Managerial Finance 
11 (1): 44–59.  

Allayannis, George, and Paul J. Simko. 2009. “Earnings Smoothing, Analyst Following, and Firm 
Value.” Analyst Following, and Firm Value (August 25, 2009).  

Amihud, Yakov. 2002a. “Illiquidity and Stock Returns: Cross-Section and Time-Series Effects.” Journal 
of Financial Markets 5 (1): 31–56.  

Model  ( 1 )   
  

Variable   VIF   1 /VIF   

Size   1.17   0.857231   

TAC   
SP   
VOL   
VR   
R   

1.16   
1.09   
1.06   
1.02   
1.01   

0.859804   
0.920805   
0.943766   
0.981432   
0.986284   

Mean VIF   1.08   -   

Model ( 2 )   
  

Variable   VIF   1 /VIF   
Size   2.69   0.371893   
TAC   
SP   
VOL   
VR   
R   

2.68   
1.08   
1.06   
1.03   
1.02   

0.373029   
0.925347   
0.944182   
0.970599   
0.981440   

Mean VIF   1.59   -   
Model ( 3 )   

  
Variable   VIF   1 /VIF   
Size   1.09   0.920669   
TAC   
SP   
VOL   
VR   
R   

1.06   
1.04   
1.04   
1.02   
1.02   

0.943840   
0.963947   
0.964137   
0.981468   
0.984587   

Mean VIF   1.04   -   

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Ascioglu, Asli, Carole Comerton-Forde, and Thomas H. McInish. 2011. “Stealth Trading: The Case of 
the Tokyo Stock Exchange.” Pacific-Basin Finance Journal 19 (2): 194–207.  

Ascioglu, Asli, Shantaram P. Hegde, Gopal V. Krishnan, and John B. McDermott. 2012. “Earnings 
Management and Market Liquidity.” Review of Quantitative Finance and Accounting 38 (2): 
257–74.  

Atiase, Rowland K., and Linda Smith Bamber. 1994. “Trading Volume Reactions to Annual Accounting 
Earnings Announcements: The Incremental Role of Predisclosure Information Asymmetry.” 
Journal of Accounting and Economics 17 (3): 309–29.  

Attig, Najah, Wai-Ming Fong, Yoser Gadhoum, and Larry HP Lang. 2006a. “Effects of Large 
Shareholding on Information Asymmetry and Stock Liquidity.” Journal of Banking & Finance 
30 (10): 2875–92.  

Beneish, Messod D., Eric Press, and Mark E. Vargus. 2012. “Insider Trading and Earnings Management 
in Distressed Firms*.” Contemporary Accounting Research 29 (1): 191–220.  

Bhattacharya, Nilabhra, Hemang Desai, and Kumar Venkataraman. 2013. “Does Earnings Quality 
Affect Information Asymmetry? Evidence from Trading Costs.” Contemporary Accounting 
Research 30 (2): 482–516.  

Biais, Bruno, Larry Glosten, and Chester Spatt. 2005. “Market Microstructure: A Survey of 
Microfoundations, Empirical Results, and Policy Implications.” Journal of Financial Markets 8 
(2): 217–64.  

Botosan, Christine A., and Marlene A. Plumlee. 2002. “A Re examination of Disclosure Level and the 
Expected Cost of Equity Capital.” Journal of Accounting Research 40 (1): 21–40.  

Brockman, Paul, and Dennis Y. Chung. 2001a. “Managerial Timing and Corporate Liquidity:: Evidence 
from Actual Share Repurchases.” Journal of Financial Economics 61 (3): 417–48.  

Brown, Stephen, and Stephen A. Hillegeist. 2007. “How Disclosure Quality Affects the Level of 
Information Asymmetry.” Review of Accounting Studies 12 (2–3): 443–77.  

Chan, Justin SP, Dong Hong, and Marti G. Subrahmanyam. 2008. “A Tale of Two Prices: Liquidity and 
Asset Prices in Multiple Markets.” Journal of Banking & Finance 32 (6): 947–60.  

Chen, Wei-Peng, Huimin Chung, Chengfew Lee, and Wei-Li Liao. 2007. “Corporate Governance and 
Equity Liquidity: Analysis of S&P Transparency and Disclosure Rankings.” Corporate 
Governance: An International Review 15 (4): 644–60.  

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American Research Journal of Economics, Finance and Management 

Volume 10 Issue 4, October-December 2022 

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Impact Factor: 4.85 

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Official Journal of America Serial Publication 
 

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15 | P a g e  

Chung, Huimin, Her-Jiun Sheu, and Juo-Lien Wang. 2009. “Do Firms’ Earnings Management 
Practices Affect Their Equity Liquidity?” Finance Research Letters 6 (3): 152–58.  

Cohen, Daniel A., Aiyesha Dey, and Thomas Z. Lys. 2008. “Real and Accrual-Based Earnings 
Management in the Pre-and Post-Sarbanes-Oxley Periods.” The Accounting Review 83 (3): 757–
87.  

Cohen, Daniel A., and Thomas Z. Lys. 2006. “Weighing the Evidence on the Relation between External 
Corporate Financing Activities, Accruals and Stock Returns.” Journal of Accounting and 
Economics 42 (1): 87–105.  

Datar, Vinay T., Narayan Y. Naik, and Robert Radcliffe. 1998. “Liquidity and Stock Returns: An 
Alternative Test.” Journal of Financial Markets 1 (2): 203–19.  

Demsetz, Harold. 1968. “Why Regulate Utilities?” The Journal of Law & Economics 11 (1): 55–65.  

Etemadi, H., and A. Resayian. 2010. “The Relationship between Some Corporate Governance 
Mechanisms and Stock Liquidity”.” Development and Capital Journal, 31–59.  

Faez, Ali, Mohammad Mirzaei, Mehran Orooei, and Asghar Ariyanpoor. 2014a. “Examining 
Relationship between Earnings Management and Stock Liquidity Using Modified Jones Model: 
Evidence from Listed Companies in Tehran Stock Exchange.” Advances in Environmental 
Biology, 1903–9. 

Fizazi, Karim, Philippe Beuzeboc, Jean Lumbroso, Vincent Haddad, Christophe Massard, Marine 
Gross-Goupil, Mario Di Palma, Bernard Escudier, Christine Theodore, and Yohann Loriot. 2009. 
“Phase II Trial of Consolidation Docetaxel and Samarium-153 in Patients with Bone Metastases 
from Castration-Resistant Prostate Cancer.” Journal of Clinical Oncology 27 (15): 2429–35.  

Francis, Jennifer, Ryan Lafond, Per Olsson, and Katherine Schipper. 2007. “Information Uncertainty 
and Post earnings announcement drift.” Journal of Business Finance & Accounting 34 (3 4): 
403–33.  

Glosten, Lawrence R., and Paul R. Milgrom. 1985. “Bid, Ask and Transaction Prices in a Specialist 
Market with Heterogeneously Informed Traders.” Journal of Financial Economics 14 (1): 71–
100.  

Grüning, Nana-Maria, Hans Lehrach, and Markus Ralser. 2010. “Regulatory Crosstalk of the Metabolic 
Network.” Trends in Biochemical Sciences 35 (4): 220–27.  

Hakim, Faten, Fatma Triki, and Abdelwahed Omri. 2008. “Earnings Quality and Equity Liquidity: 
Evidence from Tunisia.” International Journal of Managerial and Financial Accounting 1 (2): 
147–65.  

mailto:contact@americaserial.com
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American Research Journal of Economics, Finance and Management 

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16 | P a g e  

Healy, Paul M., and Krishna G. Palepu. 2001. “Information Asymmetry, Corporate Disclosure, and the 
Capital Markets: A Review of the Empirical Disclosure Literature.” Journal of Accounting and 
Economics 31 (1): 405–40.  

Hepworth, Samuel R. 1953. “Smoothing Periodic Income.” The Accounting Review 28 (1): 32–39.  

Hirshleifer, David, Siew Hong Teoh, and Jeff Jiewei Yu. 2011. “Short Arbitrage, Return Asymmetry, 
and the Accrual Anomaly.” Review of Financial Studies 24 (7): 2429–61.  

Iatridis, George, and George Kadorinis. 2009. “Earnings Management and Firm Financial Motives: A 
Financial Investigation of UK Listed Firms.” International Review of Financial Analysis 18 (4): 
164–73.  

Jones, Charles I. 1995. “R & D-Based Models of Economic Growth.” Journal of Political Economy, 759–
84.  

Kothari, Sagar P., Andrew J. Leone, and Charles E. Wasley. 2005. “Performance Matched Discretionary 
Accrual Measures.” Journal of Accounting and Economics 39 (1): 163–97.  

Kraft, Anastasia, Bong Soo Lee, and Kerstin Lopatta. 2014. “Management Earnings Forecasts, Insider 
Trading, and Information Asymmetry.” Journal of Corporate Finance 26: 96–123.  

LaFond, Ryan, Mark H. Lang, and Hollis Ashbaugh Skaife. 2007. “Earnings Smoothing, Governance 
and Liquidity: International Evidence.” Governance and Liquidity: International Evidence 
(March 2007).  

Livnat, Joshua, and Germán López-Espinosa. 2008a. “Quarterly Accruals or Cash Flows in Portfolio 
Construction?” Financial Analysts Journal 64 (3): 67–79.  

Matoussi, Hamadi, Adel Karaa, and Randa Maghraoui. 2004. “Information Asymmetry, Disclosure 
Level and Securities Liquidity in the BVMT.” Finance India 18: 547–58.  

Matoussi, Hamadi, and Ahmed Zemzem. 2004. “Investissements Immatériels et Création de Valeur 
Etude Empirique Sur Le Marché Français.” In Normes et Mondialisation, CD-Rom.  

Nowghabi, Mohammad Hossein Vadiei, Ali Shirazd, Shaban Mohammadi, and Alireza Khorshidi. 2015. 
“The Effect of Earnings Management on Liquidity Criteria and Lack of Liquidity Stock.”  

Peterson, Kyle, Roy Schmardebeck, and T. Jeffrey Wilks. 2015. “The Earnings Quality and Information 
Processing Effects of Accounting Consistency.” The Accounting Review 90 (6): 2483–2514.  

Richardson, Scott A. 2000. “Accruals and Short Selling: An Opportunity Foregone?”  

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17 | P a g e  

Roulstone, Darren T. 2003. “Analyst Following and Market Liquidity*.” Contemporary Accounting 
Research 20 (3): 552–78.  

Shiri, Mahmoud Mousavi, and Masomeh Roshandel. 2015. “The Relationship between Stock Liquidity 
Risk and Financial Information Quality Criteria in Tehran Stock Exchange.” Iranian Journal of 
Management Studies 8 (4): 503.  

So, Eric C., and Sean Wang. 2014. “News-Driven Return Reversals: Liquidity Provision ahead of 
Earnings Announcements.” Journal of Financial Economics 114 (1): 20–35.  

Sohn, Byungcherl Charlie. 2016. “The Effect of Accounting Comparability on the Accrual-Based and 
Real Earnings Management.” Journal of Accounting and Public Policy 35 (5): 513–39.  

Stoll, Hans R. 1978. “The Supply of Dealer Services in Securities Markets.” The Journal of Finance 33 
(4): 1133–51.  

Wang, Ashley W., and Gaiyan Zhang. 2009. “Institutional Ownership and Credit Spreads: An 
Information Asymmetry Perspective.” Journal of Empirical Finance 16 (4): 597–612.  

Xu, Xiaogang, Dongfang Lin, Guoquan Yan, Xinyu Ye, Shi Wu, Yan Guo, Demei Zhu, Fupin Hu, 
Yingyuan Zhang, and Fu Wang. 2010. “vanM, a New Glycopeptide Resistance Gene Cluster 
Found in Enterococcus Faecium.” Antimicrobial Agents and Chemotherapy 54 (11): 4643–47.  

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