A STUDY OF INTERACTION EFFECTS OF POLITICAL INFLUENCES AND EARNINGS MANAGEMENT ON ORGANISATIONAL PERFORMANCE

Muhammad Sadiq¹⁺ --- Zaleha Othman² --- Ooi Chee Keong³

^1,3Taylors University, Malaysia.
²Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia.

Keywords: Political influences, Earnings management, Organisational performance, Agency theory, Political economy theory.

JEL Classification: M41; D72; D73.

ARTICLE HISTORY: Received:1 March 2019Revised: 9 April 2019 Accepted:10 May 2019 Published: 20 May 2019.

Contribution/ Originality:This study contributes to the existing literature by examining the moderating effect of political influences and earnings management on organisational performance in Pakistan. This study also includes one new aspect of political connection i.e. political influences through significant government shareholding.

1. INTRODUCTION

It is often argued that politically influenced firms lead to better organisational performance. This is because such firms have easy access to long-term loans, government contracts, market power, and favourable tax treatments (Faccio, 2010; Pástor and Veronesi, 2013; Saeed et al., 2015). Empirical evidence proves that politically influenced firms get preferential treatment and accumulate political benefits from their connections (Khwaja and Mian, 2005; Sadiq and Othman, 2017). 

Many studies show that governments give privileges to politically influenced firms, which ultimately increases their ability to demonstrate better organisational performance (e.g., Wu et al. (2012)) and increases the value of firms (Fisman, 2001). Johnson and Mitton (2003) showed that politically connected firms in Malaysia suffered more when the Asian financial crisis in 1997 reduced the government’s ability to provide subsidies and privileges, and they gained more when the imposition of capital controls allowed a higher level of subsidies. Saeed et al. (2017) also illustrated that the performance of politically connected firms in Pakistan significantly increases within a political regime as compared to a military regime.

On the contrary, some studies provide evidence that political influences negatively affect the organisational performance. For example, Fan et al. (2007) reported that firms with politically connected chief executive officers (CEOs) in China performed poorer after going public in comparison to firms with non-political CEOs. In a recent study, Cheema et al. (2016) illustrated that politically influenced firms reported poor organisational performance in Pakistan because the poor performance of politically influenced firms results from their operational inefficiencies (Saeed et al., 2017).

Despite detailed empirical work suggesting that political influences can benefit firms through political gains or prove detrimental to firms due to their operational inefficiencies, limited focus is given to the underlying mechanisms through which political influences affect organisational performance. This study aims to investigate whether earnings management is such a mechanism, because after obtaining political gains, firms may in all likelihood be compelled to report higher taxable income, which would subsequently motivate firms to manage earnings in order to report less taxable income (Li et al., 2016).

However, paying tax based on the managed earnings is possible only if the firm has politically connected management (Li et al., 2008) because the presence of politically connected people in management helps the firm to reduce tax burdens (Li et al., 2008;2016). In addition, political links can reduce the magnitude of punishment, which a firm may face if the government discovers the illegitimate earnings management activities of a firm. Thus, not only can political connections help firms to report less taxable income and poor organisational performance, but they can also lower the punishment linked with deceptive income-decreasing earnings management activities. This study finds empirical evidence that the interaction effect of political influences and earnings management is negatively and significantly related to organisational performance, which helps us to understand the underlying mechanism through which political influences affect organisational performance.

In this study, the determinants of organisational performance are examined to further understand the causal effect of politically connected companies. This study gives an insightful explanation of the relationship between political connection and firm performance in a single country - Pakistan. Most importantly, the results of the current study enable stakeholders to assess the effects of politically influenced companies on organisational performance, thus providing useful information for stakeholders to protect their interests. The results are also useful for regulators to use in monitoring any earnings management activities. Similar to past studies, the findings of the current study suggest that political influence gives rise to agency problems and thus affects the interpretation of earnings.
Specifically, this study makes the following contributions:

First, congruent with the study of Cheema et al. (2016) this study contributes to agency theory and political economic theory by including another aspect of political influences: the presence of civil/military bureaucrats in a firm. This is because Pakistan has been directly ruled by civil/military bureaucrats for a couple of decades, which has made these bureaucrats and politicians equally influential.

Second, this study shows that politically influenced firms report poor organisational performance with the objective of reporting less taxable income through earnings management activities, which explains the underlying mechanism through which political influences affect organisational performance. Therefore, this study examines the interactive effects of political influences and earnings management on organisational performance in Pakistan.

The remainder of this paper is structured as follows: A brief section offers a review of the related literature, followed by the development of the hypotheses. Then the theoretical framework is formulated to examine the interactive effects of political influences and earnings management on organisational performance, which is supported by a research methodology adopted for this study, followed by the results, a summary, and a conclusion.

2. LITERATURE REVIEW

2.1. Political Influences, Earnings Management, and Organizational Performance

Prior studies show that political influences are linked to better organisational performance. For example, using Chinese firms’ data, Wu et al. (2012) asserted that politically influenced firms obtain government subsidies and report better organisational performance as compared to non-politically influenced firms. Likewise, using data from German firms, Niessen and Ruenzi (2010) showed that politically influenced firms have slightly fewer growth opportunities but better accounting performance. Su and Fung (2013) explained that state-owned and non-state-owned firms use political influences to enhance performance. They argued that politically influenced firms accumulate political benefits in terms of higher long-term loans on lower interest rates.

Some researchers argued that the effects of political influences are more pronounced in firms with less outside monitoring, indicating that politically influenced firms accentuate organisational performance (Xu et al., 2015). Using a survey of private firms, Li et al. (2008) found that firms of private entrepreneurs linked to the Communist Party of China showed better organisational performance, and that they procured political benefits in terms of bank loans and help in the legal system. Li et al. (2008) further opined that political influences are more important to organisational performance in regions with weaker legal protection and weaker market institutions. 

On the contrary, several studies, including a few recent studies, have drawn linkages between political influences and poor organisational performance (Boubakri et al., 2008; Faccio, 2010; Wu et al., 2012; Cheema et al., 2016). These studies have vividly stated that politically influenced firms show poor organisational performance as opposed to non-politically influenced firms. Using data from multiple countries, Faccio (2010) for instance, documented that the market-to-book ratio of politically influenced firms was found to be lower by 0.48%, and the return on equity (ROE) of politically influenced firms was found to be lower by 5.38% in comparison to non-politically influenced firms. The ROE of politically influenced firms significantly declined with the level of corruption in each country. Using data from Chinese listed firms, Fan et al. (2007) observed a similar pattern among firms with politically connected CEOs. In addition, Wu et al. (2012) provided evidence signifying that politically influenced Chinese listed firms manipulated earnings in order to gain tax benefits.
In addition, Saeed et al. (2015) found that politically influenced firms get more subsidies as compared to non-politically influenced firms, and that the subsidies obtained by firms with political influences were negatively related to organisational performance. Similarly, some researchers have examined the moderating effects of political influences and government subsidies on organisational performance. For example, Zhang et al. (2014) indicated that the moderating effects of political influences and government subsidies have insignificant effects on organisational performance, because a firm’s executives’ government background and connections weakens subsidy effects. Other researchers argue that the effect of political influence is subject to firm ownership. For instance, Wu et al. (2013) found that private firms with politically influenced managers show better organisational performance, while state-owned firms with politically influenced managers show poor organisational performance, because the poor performance of state-owned firms is linked to operational inefficiencies, such as employing surplus workers.  

Pakistan is not excluded from political influences, where politically influenced firms have access to long-term loans, government contracts, and preferential treatment (Khwaja and Mian, 2005; Saeed et al., 2015). In fact, in Pakistan, politically influenced firms received 40% more loans as compared to non-politically influenced firms (Khwaja and Mian, 2005). Therefore, one could argue that political influences are likely to be associated with better organisational performance, since they have lucrative offers of accepting long-term loans, government contracts, and subsidies. However, based on the results of a recent study in Pakistan, political influences are associated with poor organisational performance (Cheema et al., 2016) because politically influenced firms are associated with operational inefficiency (Saeed et al., 2017).

Previous studies have found that politically influenced firms can have both negative and positive effects on organisational performance. The positive effect of political influences on organisational performance is predominant due to the benefits that firms accumulate through their political connections. However, the underlying mechanisms that negatively affect the performance of politically influenced firms are still not apparent and thus require more investigation.

While prior studies have shown that operational inefficiencies and surplus workers negatively affect the performance of politically influenced firms, they have given little focus to other underlying mechanisms through which political influences affect organisational performance. Therefore, this study aims to investigate whether earnings management is such a mechanism. After obtaining government subsidies and contracts as well as easy access to bank loans on lower interest rates, it is likely that firms may report higher taxable income, which may motivate politically influenced firms to manage earnings downwards in order to report less taxable income (Li et al., 2016). Therefore, the interaction effect of political influences and earnings management is negatively and significantly related to organisational performance.
H1. The interaction effects of political influences and accrual-based earnings management are negatively related to organisational performance in comparison to non-politically influenced firms.

3. RESEARCH METHODOLOGY

3.1. Data Collection and Sampling

This paper collected data from 128 listed firms on the Pakistan Stock Exchange (PSE), which consisted of 64 politically influenced and 64 non-politically influenced firms. The data used in this study were a balanced panel and gathered manually from annual reports from 2009 to 2013 published by listed firms on the PSE. Initially, the sample required data from 2008 and 2014, because one-year lagged and lead data were required to represent earnings management attributes, and the firms with missing data from these years were removed from the sample. After using the filter on non-financial listed firms, the final sample included 64 politically influenced firms, and therefore 64 similar non-politically influenced firms were chosen. Thus, this paper used the matching method of panel data. First, we extracted the data related to significant government shareholding and politically influenced firms through bureaucrat(s) that indicated patterns of shareholdings and board of directors (BOD) of all non-financials listed firms on the PSE. Second, in order to identify the indirectly (close relatives of politicians) politically influenced firms; this study relied upon online resources, which reported the list of politically influenced firms and their associated firms within the Pakistani market. Third, in order to measure the firm’s political connections, a dataset on politically influenced people at the national and provincial levels was required. The political data were taken from Election Commission of Pakistan (ECP), which conducted elections for the local government, provincial, and national assemblies. It maintained comprehensive information on provincial and national elections, including parties’ positions, candidate lists, and electoral outcomes.

Table 1 provides the sector distribution of the sample. A majority of 30 firms (23.44%) are from the manufacturing sector, followed by 20 (15.62%) from the fuel and energy sector, 18 (14.06%) from sugar, 12 (9.37%) from cement, and 10 (7.81%) from chemical and pharmaceutical, with the remaining firms comprising the services sector.

Table-1. Industry distribution of the sample.

Industry	Observations	Percent	Cum.	% of PI firms
Cement	60	9.37	9.375	50%
Chemicals and pharmaceutical	50	7.81	17.19	50%
Fuel and energy	100	15.62	32.81	50%
Manufacturing	150	23.44	56.25	50%
Services	50	7.81	64.06	50%
Sugar	90	14.06	78.12	50%
Textile	140	21.88	100	50%
Total	640	100

3.2. Instrumentation and Measurement

To test our hypothesis, we used panel corrected standard error (PCSE) to remove heteroscedasticity. Thus, the current study used the PCSE technique to test the following regression:

The model was adopted from Cheema et al. (2016) and Wu et al. (2012) while investigating the relationship between political influences and organisational performance. However, this study includes the moderating effects of earnings management. Several different aspects of political influences, such as the presence of politician(s) or their close relative(s) in a firm (PC), the presence of top military and civil bureaucracy in a firm (BUR), and a firm significantly owned by a government (GOVT), were compared with accrual-based earnings management (AEM) in order to test the impact on organisational performance.

3.3. Measurements of Variables

3.3.1. Measurement of Organizational Performance

PERF denotes organisational performance, which is the dependent variable in the regression model. Some researchers (Chen et al., 2011) have used market-based measures (i.e., Tobin’s Q, market-to-book ratio, and return on stocks), while other researchers (Cheema et al., 2016) have used accounting-based measurements (i.e., ROE, ROA) to measure organisational performance.

However, in the Pakistani context, Cheema et al. (2016) claimed that the use of market-based attributes to measure organisational performance is not suitable, because the PSE has often been criticised for price manipulation, inefficiency, and insider trading. An amnesty scheme introduced by the Government of Pakistan in 2012 resulted in an inflow of black money into the market, causing overvaluation of the market. Therefore, this study used only accounting-based attributes (i.e., ROA and ROE) to measure organisational performance, because a market-based measure was not suitable for this study.

Following Cheema et al. (2016); Su and Fung (2013) this study used two accounting-based measures of organisational performance: ROE and ROA. ROE was calculated as the percentage of net income to shareholders’ equity, whereas ROA was calculated as the percentage of net income to total assets of the firm.

3.3.2. Measurement of Accrual-Based Earnings Management

This study adopted an accruals quality model in order to capture the AEM activities of a firm. An accruals quality model was first introduced by Dechow and Dichev (2002) and later modified by McNichols (2002). McNichols (2002) argued that the accruals quality reduces when the magnitude of accruals estimation errors increases. Some researchers suggested that low-variance firms have better accruals quality (Francis et al., 2005). Dechow and Dichev (2002) proposed a model of accruals quality that matches the total current accruals to cash flows, and thus a poor match indicated poor quality and a good match signified a good quality of accruals. McNichols (2002) modified the accruals quality model by including additional explanatory variables to cash flows (i.e., revenue, and property, plant, and equipment [PP&E]), because she argued that additional explanatory variables are pertinent in forming expectations about current accruals. The modification is illustrated in the following equation:

Where all variables are scaled by lagged total assets. is total current accrual in year t of firm i; OCF is operating cash flows; GPPE is gross PP&E in year t of firm i; and is revenue in year t of firm i. The error term in the above equation shows the extent to which the total current accruals map into explanatory variables (i.e., lagged, current and lead operating cash flows, change in total revenues, and gross PP&E), and the standard deviation obtained from this regression is a proxy for accruals quality. Thus, the standard deviation is equals to the difference between operating cash flows, change in sales revenue, gross property, plant, and equipment, and total current accruals, which represents accruals quality. The higher the difference between operating cash flows and total current accruals the lower the quality of accruals and vice versa (Dechow and Dichev, 2002). The modification is illustrated in the following equation:

Where,
All variables are same as above.

3.3.3. Measurement of Political Influences

This study measured political influences as a dummy variable, which is equal to 1 if a firm is politically influenced and 0 if non-politically influenced. To suit the context in Pakistan, this study used three aspects of political influences.

First, congruent with previous studies (Faccio, 2006; Cheema et al., 2016) a firm was considered politically influenced with the presence of a politician or close relative of a politician in a firm. Second, a firm was considered politically influenced if it was significantly owned by the government (Nee et al., 2007) since the representatives of the government are then present on the BOD, who are likely to influence decision making to achieve government objectives and agendas. Third, consistent with prior studies (Cheema et al., 2016; Sadiq and Othman, 2017) a firm was considered as politically influenced with the presence of a former or current civil/military bureaucrat(s) in the firm.

This study adopted a bureaucratic aspect of political influences because Pakistan has been directly governed by bureaucrats and military dictators for many years (Cheema et al., 2016) which makes these civil and military bureaucrats equally influential to politicians. Thus, this study divided political influences into three independent binary variables: PC, GOVT, and BUR. PC referred to the connections of a firm with politicians (direct connections) or the presence of a close relative (indirect connections) of a politician in senior management or on the BOD. PC included both direct and indirect political connections. PC was equal to 1 for political connections and 0 otherwise. GOVT referred to firms that are significantly owned (at least 10%) by the government. GOVT was equal to 1 for government-owned firms and 0 otherwise. BUR referred to firms with civil/military bureaucrats in senior management or on the BOD. BUR was equal to 1 in the case of the presence of civil/military bureaucrats in senior management and 0 otherwise.

3.3.4. Measurement of Control Variables

In addition to the variables of political influences, this study included several control variables, which were used in previous studies (Li et al., 2016; Sadiq and Othman, 2017). We included financial leverage (LEV), firm size (SIZE), audit quality (BIG4), and growth opportunities (GROWTH) as controls for other effects. SIZE was the natural log of total assets, which was used as a control for size effects. LEV was the ratio of debt to total assets. GROWTH was the percentage change in the sales of the present year in comparison to the sales of the previous year. BIG4 was a dummy variable that was coded 1 if a firm was audited by one of the top big four audit firms and 0 otherwise.

4. RESULTS

Table 2 shows the descriptive statistics of all the variables used in the regressions. The table shows the standard deviation, mean values, minimum values, and maximum values of the dependent and explanatory variables. The descriptive statistics showed that there was no concern with outliers, because the data did not indicate any deviation from normality. For the dependent variables, ROA and ROE, the mean percentages were 7.85% and 15.16%, respectively. For the earnings management variables, the mean value of AEM was 0.0091, which is close to the mean value of Sadiq and Othman (2017). For the political influence variables, the data reflected a total of 128 firms (i.e., 640 observations). About 50% (i.e., 64 firms) of the firms were politically influenced; 28.90% of the firms were politically influenced with the presence of politician(s) on the BOD or in senior management; 11.71% of the firms were politically influenced through significant government ties; and 19.68% of the firms were politically influenced with the presence of civil/military bureaucrat(s). For the control variables, the means for LEV, SIZE, GROWTH, and BIG4 were 62.82%, 6.84, 16.71%, and 44.68%, respectively. The data showed that about 45% of the firms were audited by one of the top big four audit firms.

Table-2. Summary statistics of the variables used in analysis.

Variable	Observations	Mean	Std. Dev.	Min	Max
ROA	640	7.859141	13.98446	-49.38	61.43
ROE	640	15.16299	52.21917	-310.95	218.44
AEM	640	0.009101	0.257245	-1.92648	1.76998
PI	640	0.50000	0.500391	0	1
PC	640	0.289063	0.453682	0	1
GOVT	640	0.117188	0.321895	0	1
BUR	640	0.196875	0.397948	0	1
LEV	640	0.628243	0.315846	0.031464	3.011882
SIZE	640	6.847306	0.668267	4.729821	8.616926
Growth	640	0.167116	0.503893	-1.45916	7.980104
BIG4	640	0.446875	0.497559	0	1

Note: ROA is the percentage of net profits/loss divided by total assets; ROE is the percentage of net income/loss divided by equity; AEM represents the residuals of accruals earnings management activities, which is calculated using McNichols (2002) Modified Model; PI represents the aggregate measure of politically influenced firms, coded 1 if a firm is politically influenced through any aspects of political influences and 0 otherwise; PC is a dummy variable, coded 1 with the presence of a politician(s) on the board of directors or in senior management of a firm and 0 otherwise; GOVT is a dummy variable coded 1for government ownership in a listed firm and 0 otherwise; BUR is a dummy variable coded with the presence of a current/former civil/military bureaucrat(s) on the board of directors or in senior management of a firm and 0 otherwise; BIG4 is a measure of firms’ audit quality, which is coded 1 for top big four auditors and 0 otherwise; LEV is equal to the ratio of total debt/liabilities to total assets; SIZE is equal to log of total assets of the firm; GROWTH is measured as the difference of current-year sales and previous sales divided by previous-year sales.

Correlation analysis confirmed that BIG4 was positively and significantly correlated with ROA and ROE, with coefficients of 0.374 and 0.201, respectively. This correlation implies that firms audited by one of the top big four auditors showed better organisational performance. The correlation indicated that LEV was negatively correlated with ROA and ROE, with coefficients of -0.415 and -0.168, respectively, and was significant at 1%. This correlation suggested that firms with high leverage are poor performers. Consistent with previous studies (Saleh and Ahmed, 2005) SIZE was positively correlated with ROA and ROE. However, SIZE was significantly correlated with ROE, but not significantly correlated with ROA, with correlation coefficients of 0.090 and 0.039, respectively. Congruent with prior research, high-growth firms were positively correlated with organisational performance. We find that although GROWTH was positively correlated with ROE and ROA, it was more significantly correlated with ROA than with ROE, with coefficients of 0.125 and 0.033, respectively.

5. REGRESSION RESULTS

Table 4 shows the results of the relationships between organisational performance and the interaction effects of political influences alongside AEM. The results showed the positive and significant relationship between organisational performance (ROA and ROE) and AEM. However, the coefficients of AEM were not significant: 2.0742 (z = 1.16) and 6.7764 (z = 1.00). In addition, the results showed the negative and significant relationship between organisational performance (ROA and ROE) and PC, with coefficients of -4.8057 (z = -3.43) and -20.0941 (z = -6.37), respectively. This is consistent with the findings of previous studies (Cheema et al., 2016) which indicated that PC firms in Pakistan report poor organisational performance.

The coefficient of GOVT was positively and significantly related to ROA, with a coefficient of 4.9024 (z = 1.80). However, the coefficient of GOVT was negatively but not significantly related to ROE, with a coefficient of -0.6818 (z = -0.09). Therefore, it is suggested that using only one measure — i.e., ROA or ROE — to compute organisational performance may mislead the findings. BUR was not significantly related to ROA and ROE, suggesting that the presence of bureaucrats in senior management or on the BOD within the sampled firms does not explain the changes in organisational performance. This finding is in line with Cheema et al. (2016) with regression coefficients of ROA and ROE of 1.0134 (z = 0.69) and -0.3184 (z = -0.05), respectively. 

Consistent with our predicted hypothesis, the interaction effect of PC and AEM (i.e., PCAEM) was negatively and significantly related to ROA and ROE, with coefficients of -26.4381 (z = -2.59) and -40.1938 (z = -1.83), respectively. The significant negative relationship between PCAEM and organisational performance (ROA and ROE) suggested that PC firms are engaged in income-decreasing earnings management activities in order to report less taxable income and poor organisational performance. This result is consistent with previous studies (Li et al., 2016) which argued that paying tax based on the managed earnings is only possible for politically influenced firms, because the presence of politically connected people in management helps the firm to reduce tax burdens (Li et al., 2008;2016).

The interaction effect of GOVT and AEM (i.e., GOVAEM) was positively and significantly related to ROA and ROE, with coefficients of 29.5150 (z = 1.81) and 173.6871 (z = 2.94), respectively. The significant positive relationship between GOVAEM and organisational performance (ROA and ROE) suggested that GOVT firms were engaged in income-increasing earnings management activities in order to report better organisational performance. This is because government-owned firms are always being criticised by opposition parties as being poorly performing firms. Subsequently, this may motivate managers of government-owned firms to get engaged in income-increasing earnings management activities in order to report better organisational performance. 

In addition, the interaction effect of BUR and AEM (i.e., BURAEM) was negatively and significantly related to ROA and ROE, with coefficients of -26.5164 (z = -2.21) and -113.3405 (z = -2.43), respectively. The significant negative relationship between BURAEM and organisational performance (ROA and ROE) indicated that BUR firms were engaged in income-decreasing earnings management activities in order to report less taxable income. This finding is congruent with our predicted hypothesis and previous studies (Li et al., 2016) which argued that politically influenced firms manage earnings downwards in order to report less taxable income.

Table-3. Pearson correlations of the interaction effect of political influences and accruals earnings management on organisational performance (i.e., ROA and ROE).

Note: Other variables remain unchanged; PCAEM is the interaction variable of PC and AEM; GOVAEM is the interaction variable of GOVT and AEM; BURAEM is the interaction variable of BUR and AEM.

BIG4 was positively and significantly associated with ROA and ROE. The positive coefficients suggested that firms audited by one of the top big four auditors showed better organisational performance and curtailed earnings management activities as compared to firms audited by the non-BIG4 audit firms. GROWTH was also positively and significantly related to ROA and ROE, which is consistent with the expectation that high-growth firms tend to have better organisational performance in comparison with low-growth firms. LEV was negatively significant, suggesting that high-leverage firms show poor organisational performance. This result is consistent with previous studies (Cheema et al., 2016) because high-leverage firms are more inclined to use income-decreasing earnings management activities (Saleh and Ahmed, 2005) particularly firms that are politically influenced, since their political connections help them to default and write-off the loans (Khwaja and Mian, 2005). Consistent with the study of Cheema et al. (2016) SIZE was negatively and significantly related to ROA, but insignificantly positively associated with ROE.

Table-4. Linear regression results of the relationships between the interaction effects of accruals earnings management and multiple aspects of political influences (i.e., PCAEM, GOVAEM, and BURAEM) on organisational performance (i.e., ROA and ROE).

		ROA			ROE
	Coefficient	Z	P>z	Coefficient	z	P>z
AEM	2.0742	1.16	0.246	6.7764	1.00	0.317
PC	-4.8057	-3.43	0.001	-20.0941	-6.37	0.000
GOVT	4.9024	1.80	0.072	-0.6818	-0.09	0.931
BUR	1.0134	0.69	0.488	-0.3184	-0.05	0.962
PCAEM	-26.4382	-2.59	0.010	-40.1938	-1.83	0.068
GOVAEM	29.5150	1.81	0.071	173.6871	2.94	0.003
BURAEM	-26.5164	-2.21	0.027	-113.3405	-2.43	0.015
BIG4	7.8230	12.60	0.000	5.3064	2.03	0.042
LEV	-14.8523	-7.66	0.000	-17.2078	-2.59	0.010
SIZE	-2.4322	-3.47	0.001	3.5626	1.32	0.186
Growth	3.6199	3.08	0.002	4.8865	1.68	0.094
_cons	24.4389	5.39	0.000	0.7537	0.04	0.97
Industry effect		Yes			Yes
R-square		0.3614			0.3221
Observations		640			640

Note: ROA is the percentage of net profits/loss divided by total assets; ROE is the percentage of net income/loss divided by equity; AEM represents the residuals of accruals earnings management activities, which is calculated using McNichols (2002) Modified Model; PC is a dummy variable, coded 1 with the presence of a politician(s) or close relatives of a politicians in a firm and 0 otherwise; GOVT is a dummy variable coded 1for government ownership in a listed firm and 0 otherwise; BUR is a dummy variable coded 1 with the presence of a current/former civil/military bureaucrat(s) on the board of directors or in senior management of a firm and 0 otherwise; PCAEM is the interaction variable of PC and AEM; GOVAEM is the interaction variable of GOVT and AEM; BURAEM is the interaction variable of BUR and AEM; BIG4 is a measure of firms’ audit quality, which is coded 1 for top big four auditors and 0 otherwise; LEV is equal to the ratio of total debt/liabilities to total assets; SIZE is equal to log of total assets of the firm; GROWTH is measured as the difference of current-year sales and previous sales divided by previous-year sales.

6. SUMMARY AND CONCLUSION

This study provided evidence that the interaction effects of political influences (i.e., PCAEM and BURAEM) and earnings management are negatively and significantly associated with organisational performance. In addition, the interaction effect of political influences (i.e., GOVAEM) is positively and significantly related to organisational performance. We are of the opinion that earnings management is the underlying mechanism through which firms show poor/better organisational performance, unlike prior studies that test only the direct relationship between political influences and organisational performance and have failed to discuss that earnings management is the underlying mechanism through which politically influenced firms manage earnings downwards in order to report less taxable income and hide political gains. This result is consistent with the argument of Li et al. (2016) who asserted that paying taxes based on the managed earnings is possible only if the firm has politically connected management.

This study is the first to examine how the interaction effect of political influences and earnings management relates to organisational performance. This study contributes to the field of organisational performance and earnings management by integrating agency theory and political economy theory, and it contributes to the ongoing debate on the role of political influences in emerging markets. It also demonstrates the underlying mechanism (i.e., earnings management) through which politically influenced firms show poor organisational performance. We offer insights to policy makers and regulators who are interested in improving corporate governance in transitional economies such as Pakistan, where politics and businesses are closely linked to each other.

This study contributes to agency theory and political economy by using three aspects of political influences, enriching the measurement for political influences. Most importantly, this study produced imperative findings suggesting that the presence of politically influenced people on the BOD or in senior management creates agency costs, which may result in a lower quality of earnings. Hence, to reduce these costs, strong regulatory bodies and enlightened shareholders are needed.

Funding: This study received no specific financial support.

Competing Interests: The authors declare that they have no competing interests.

Contributors/Acknowledgement: All authors contributed equally to the conception and design of the study.

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