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Earnings Management Around Zero: A motivation to local politician signalling competence
Augusta Ferreira , João Carvalho & Fátima Pinho
To cite this article: Augusta Ferreira , João Carvalho & Fátima Pinho (2013) Earnings Management Around Zero: A motivation to local politician signalling competence, Public Management Review, 15:5, 657-686, DOI: 10.1080/14719037.2012.707679
To link to this article: https://doi.org/10.1080/14719037.2012.707679
Published online: 03 Aug 2012.
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EARNINGS
MANAGEMENT AROUND ZERO
A motivation to local politician signalling competence
Augusta Ferreira, Joa˜o Carvalho and Fa´tima Pinho
Augusta Ferreira
Instituto Superior de Contabilidade e Administrac¸a˜o University of Aveiro
Aveiro, Portugal
E-mail: augusta.ferreira@ua.pt
Joa˜o Carvalho
Escola de Economia e Gesta˜o University of Minho, Braga, Portugal E-mail: jcarvalho@eeg.uminho.pt
Fa´tima Pinho
Instituto Superior de Contabilidade e Administrac¸a˜o University of Aveiro
Aveiro, Portugal
E-mail: fatima.pinho@ua.pt
Abstract
Literature earnings management aims to determine what causes/motivates managers to disclose earnings close to zero and to use this as an instrument to influence users’
decisions. However, limited research has been carried out on this subject in the public sector. Therefore, the main purpose of this paper is to evaluate whether local politicians (in Portuguese municipalities), aiming to demonstrate their high level of competence and skills, engage in earnings management in such a way as to ensure that earnings are positive but close to zero. We examined whether political competition is a determining factor of earnings management close to zero and if managers use discretionary accruals in order to do this. Results indicate that, in order to report positive net earnings close to zero, discretionary accruals are used. This study identified the overriding tendency to avoid the reporting of losses in those municipalities where political competition is greatest.
Key words
Public accounting, agency theory, public choice theory, earnings management, muni- cipalities, political competition
Ó2013 Taylor & Francis
INTRODUCTION
The study of earnings management may contribute to identifying the behavioural patterns of managers and the accounting policies they use in opportunistic election situations. This contribution is important because it allows us to predict future manager behaviour. According to Healy and Wahlen (1999: 368), ‘Earning management occurs when managers use judgment in financial reporting and in structuring transactions to alter financial reports to either mislead some stakeholders about the underlying economic performance of the company or to influence contractual outcomes that depend on reported accounting numbers’.
Based on agency theory, numerous contributions have been made from studies developed in companies (private sector). However, in the public sector, the contributions based on the same theory are limited. For this reason, we have chosen to study earnings management in the public sector (municipalities).
Apart from budget accounting (cash basis) in the public sector and in (unclear what is meant by concrete?) municipalities, there has been a progressive and simultaneous demand for the application of an accounting model based upon accrual accounting. The purpose of this paper is to respond to the lack of information in this area, to be able to evaluate responsibility, performance and efficiency regarding the allocation of public resources and the degree of satisfaction of citizens/voters’ needs. If politicians engage in earnings management, inefficiencies in public resources management arise which could jeopardize future sustainability.
No earnings management studies of Portuguese municipalities have been carried out, but elected politicians are responsible for municipal management and are highly autonomous. According to the constitutional principle of municipal autonomy, politicians have at their disposal a wide range of functional responsibilities. These include the direct supply of goods and services to the community. Moreover, with a view to strengthening the level of municipal autonomy, a municipal’s budget is independent to that the government’s budget, although it respects the principles of the Budget Framework Law (Law No. 91/2001, 20 August). They are also responsible for the efficient and effective application of available resources in accordance with the population’s needs. The mayor manages a considerable number of resources, which stem from revenues (ruled by the Local Finance Law – Law 42/98, 6 August), such as the levy of taxes, the setting of prices and local taxes charged for goods and services provided by municipal organizations, and, finally, from loan contracts. Therefore, if a manager adopts opportunistic behaviour when preparing financial information, the efficiency of accounting as a mechanism for contracting and monitoring is reduced.
It is important to study the reasons why earnings management occurs in Portuguese
municipalities. This knowledge could help prevent future politicians from behaving
inappropriately. It is also important to study if managers use discretionary accruals for
the purpose of earnings management, as it could contribute to helping regulatory bodies
to reduce discretionarity in accounting standards.
Therefore, this paper on municipal earnings management aims to determine whether politicians are motivated to employ earnings management in such a way that earnings are positive but close to zero. In particular, we examined whether political competition is a determining factor of earnings management close to zero and if managers use discretionary accruals in earnings management.
The second section focuses on the theoretical framework and develops the hypotheses. The third section describes the data and the methodologies used. The fourth section summarizes the results of the empirical analysis. The final section draws some conclusions and makes some suggestions for further research.
THEORETICAL FRAMEWORK AND HYPOTHESES
In the public sector, public choice theory introduced the idea that the democratic process can be viewed as a competitive market whose operative agents (including politicians, citizens, public officials and interest groups) have selfish motivations. It assumes that politicians are motivated to maximize votes for re-election (Buchanan and Tullock, 1962).
A consequence of the positive approach taken by public choice theory is that, in order to maximize votes, a politician is motivated to manipulate economic policies to their own advantage (in an agency relationship, each actor takes actions designed to benefit themselves). Through increased public spending, politicians can earn votes, while increases in taxation tend to take place at the cost of such votes. Thus, there is a tendency, in democratic regimes, to produce budgets with deficits and for politicians to engage in political economic cycles, characterized by increased public spending in the pre-election period followed by inflationary pressures and restrictive policies in the post-election period. Studies conducted on public choice theory have confirmed the existence of political budget cycles in local government to promote re-election.
Examples of these studies are:
. Drazen and Eslava (2005), who studied Colombian municipalities;
. Akhmedov and Zhuravskaya (2004), who analysed regional elections in Russia;
. Coelho (2004) and Veiga and Veiga (2004), who studied Portuguese municipalities;
. Preussler and Portugal (2003) and Nakaguma and Brender (2006), who evaluated a number of federal states in Brazil;
. Escudero and Prior (2003), who addressed local governments in Spain; and . Baber and Sen (1986), who looked at local US governments.
According to agency theory, one can expect that accounting information is used by
both the politician (manager), as a way of signalling their own performance, and the
principal (local participants in the political process, citizens/voters, creditors and
donors) for monitoring political action and establishing contractual terms (Maher and Keller, 1979; Zimmerman, 1977). Therefore, in the presence of conflicts of interest between politician and principal, it can be determined that the politician has enough motivation to engage in earnings management.
In terms of agency theory, Stalebrink (2002) conducted a study on earnings management that examined financial information prepared on an accrual basis for local authorities in Sweden, on the premise that the primary objective of the politician is re- election. This study allowed him to conclude that re-election oriented earnings management takes place. Amongst several of the aspects studied, and considering the level of the entity’s ability to balance costs with revenue, Stalebrink (2002) believes that politicians have an incentive to report earnings close to zero. In this way, they underline their ability to harmonize the level of costs with income (sustainability) and, as mentioned by Leone and Horn (2005), earnings facilitate the evaluation of political performance with regard to sustainability and resource use. The results of Stalebrink’s analysis (2002), mainly based upon regression models with panel data, allowed him to conclude that politicians employ various accounting practices to reach a level of earnings close to zero.
It is interesting to note that the motivation associated with achieving positive, but close to zero earnings, has already been studied in the context of non-profit entities (e.g. hospitals) and for-profit entities within the private sector. This issue was first studied in the 1990s by Hayn (1995) and Burgstahler and Dichev (1997). Such studies rely on the analysis of the frequency distribution of cross-sectional earnings (earnings variation) to identify earnings management.
Ballantine et al. (2007) and Leone and Horn (2005) researched non-profit hospitals.
The analysis, in both studies, led to the conclusion that, in order to avoid costs related to reporting negative earnings, or excessive positive earnings, hospital managers manage earnings in such a way as to achieve positive earnings close to zero. These studies also concluded that earnings management is achieved using discretionary accruals.
Elshafie (2007) has also studied the motivation for keeping this specific level of earnings and compared the performance of for-profit hospitals with non-profit hospitals.
He concluded that, in both cases, managers use discretionary accruals to manage earnings, but that the management model was more aggressive in for-profit hospitals.
Based on the methodology employed by Burgstahler and Dichev (1997), and apart from the above-mentioned studies by Ballantine et al. (2007) and Leone and Horn (2005), the studies conducted by Ferreira et al. (2008, 2009a, 2009b) are consistent with the existence of earnings management. In Portugal, municipalities are now active in more areas. Central government has transferred many of the responsibilities related to meeting citizens/voters’ needs to municipalities. At present, municipalities provide a wide range of services to citizens/voters across a number of domains including education, health, housing, security and public order. This ongoing transfer of responsibility aims to satisfy citizens/voters’ needs and expands local politicians’
competence and the mechanisms to administrate public resources.
In the context of a new wave of public management, one that has introduced a different paradigm for the performance evaluation of public managers, the level of earnings achieved by municipalities is an efficiency and efficacy indicator. Therefore, it is a resource management and competence (accountability) indicator for local politicians aiming to meet citizens/voters’ needs. Level of earnings is a quantitative indicator. Nevertheless, since this study addresses the evaluation of public managers through the ability to meet citizens/voters’ needs, other figures should be considered in the evaluation process, namely qualitative indicators. The budget balance is also an important indicator, since it shows the budget deficit and its supera´vit.
If one considers that the resources municipalities have to allocate stem mostly from taxes
1levied on citizens/voters and that municipality costs aim to meet different citizen/voters’ needs, as a function of public choice and agency theories, then the level of earnings reported by municipalities is relevant.
The main goal of municipalities is not profit, but sustainability for the future. In fact, we could interpret negative earnings as demonstrating the incompetence of local politicians, through the overuse of resources required in order to reach a given level of needs satisfaction. From a sustainability perspective, earnings close to zero indicate the capacity of local politicians to keep the level of costs in line with income.
One way municipalities finance their activities is through debt. Reporting negative earnings contributes negatively to risk analysis and leads to high financing costs. In this sense, and taking into consideration Leone and Horn’s study (2005), maintaining positive earnings close to zero is one of the objectives of local politicians. This is because they may use the cost savings from debt to develop a municipality’s activities or, alternatively, to their own benefit.
On the other hand, citizens/voters may interpret high positive earnings as tax overloads required to satisfy their needs. In accordance with Leone and Horn (2005), high positive earnings can also be interpreted as a deferral, to future periods, of activities aimed at satisfying needs, or even as the incompetence of local politicians managing the available resources or taxes.
These factors have consequences for local politicians because if they report negative or high positive earnings, this may lead to a damaging evaluation of their performance.
In order to avoid the costs arising from reporting negative or high positive earnings, mayors need to find ways of reporting positive earnings close to zero.
In this context, we can use the assumption of the public choice theory and agency
theory to study earnings management. The conclusions of the empirical studies based on
the public choice theory have identified political competition as a motivation for
earnings management. The empirical studies based on the agency theory demonstrate
that politicians intended to disclose positive earnings close to zero. The studies based on
the agency theory also allow us to identify discretionary accruals as an instrument to
carry out earnings management.
HYPOTHESES
Based on a theoretical framework and in the context of the Portuguese municipalities, we have developed the following hypothesis:
H
1– In order to demonstrate their high level of competence, local politicians try to manage earnings in such a way as to report positive earnings close to zero.
Earnings management through accounting occurs through the selection of policies and accounting practices in such a way that they influence accruals (the difference between cash flow and operating earnings that comes from accounting principles and policies). This paper focuses on accounting earnings management, which explains the following hypothesis:
H
2– Earnings management is achieved through accounting practices.
Public choice theory states that local politicians aim to maximize votes in order to ensure re-election. In this context, and where there is strong political competition (SPC), there will be greater scrutiny and monitoring, particularly by citizens, interest groups and political parties. Thus, when the competition is strong, mayors are more likely to look for ways of emphasizing their competence and performance than when it is weak.
As net earnings demonstrate a local politician’s competence, the greater the scrutiny and monitoring, the higher the local politician’s motivation to manage earnings. This leads to the following hypothesis:
H
3– Local politicians who face SPC tend to be more prone to upward earnings management and tend to report higher levels of income than local politicians facing weaker political competition.
The following section details the data gathered and explains the methodology used to test these hypotheses.
DATA DESCRIPTION AND METHODOLOGIES Data description
The data examined in this study comes from the financial statements of a number of
Portuguese municipalities between 2002 and 2008. The data was provided by the
Centre for Research on Public Policy and Administration
2at the School of Economics
and Management of the University of Minho, and collected from municipal balance
sheets and profit and loss statements.
It was not possible to include all municipalities: firstly, because municipalities report their financial statements at different times in compliance with the accounting model of the Official Local Administration Accounting Plan; and, secondly, due to the quality of the information provided (in each year, observations referring to municipalities which recognize fixed assets, but which do not recognize amortization costs, were not included). The calculation of some variables requires information from two consecutive years. Therefore, the study does not include those municipalities that do not offer information for two consecutive years.
Data relating to the 2001 and 2005 elections came from the website http://
www.marktest.com/.
Methodology
Test of H 1 hypothesis
To test H
1, the methodology designed by Burgstahler and Dichev (1997) was used.
Following the research by Hayn (1995), these authors developed a methodology based on the analysis of the frequency distribution of cross-sectional earnings, on the assumption that, in the absence of earnings management, this distribution is smooth. To avoid heteroscedasticity problems, the authors divide net earnings by the market value of the capital at the beginning of the period.
As this study addresses local municipalities, we cannot use market value of capital.
Thus, like Leone and Horn (2005), the study uses total assets in the previous financial year as a conversion factor.
If the analysis of the frequency distribution of cross-sectional earnings shows a high number of municipalities reporting earnings in the interval immediately to the right of zero, this may be seen as an indicator of a municipalities’ tendency to report slightly positive earnings. In the same manner, a small number of municipalities reporting earnings in the interval immediately to the left of zero would indicate an avoidance of the reporting of negative earnings (Burgstahler and Dichev, 1997). In this case, we corroborate the H
1hypothesis.
In order to confirm the graphical analysis, Burgstahler and Dichev (1997) developed the statistic Z (significance measure) on the premise that, in the absence of earnings management, the frequency distribution of cross-sectional earnings is relatively smooth.
The statistic is derived by the difference between the expected number of observations in the interval and the actual number of observations in the interval, divided by the standard deviation of the difference:
Z ¼ ðna i ne i Þ=ðs ðna i ne i ÞÞ
where na
i– actual number of observations in a certain interval i; ne
i– expected
number of observations in a certain interval i, defined as the average of the
actual number of observations in two immediately adjacent intervals assuming that, in the absence of earnings management, the frequency distribution of cross- sectional earnings is relatively smooth: ne
i¼ (na
t71þ na
tþ1)/2; s (na
i7 ne
i) – standard deviation of the difference between the actual number of observations in a certain interval i and the number of expected observations in that same interval i:
s ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Np i ð1 p i Þ þ ðN ðp ði 1 Þ þ p ðiþ 1 Þ Þð1 p ði 1 Þ p ðiþ 1 Þ ÞÞ=4 q
where N is the total number of observations in the sample; and p
iis the probability that one observation is placed in the interval i.
Regarding the premises put forward here, and in the absence of earnings management, Z would be zero. If Z has a positive (negative) value, significantly different from zero, in a certain interval, then the actual number of observations in that interval is higher (lower) than the expected number, thus confirming the earnings management hypothesis.
Test of H 2 hypothesis
If discontinuity around zero occurs and if it stems from earnings management via discretionary accruals, then we expect a smooth frequency distribution of cross- sectional earnings before management (earnings excluding the effect of discretionary accruals). If this occurs, we should understand it as confirmation of earnings management using an opportunistic choice of accounting options.
Cash flows reflect financial flows that occurred in a particular financial year. Earnings are determined on an accrual basis and reflect economic flows in a given financial year, no matter when the corresponding financial flow occurred or is going to occur.
Therefore, and for any given financial year, earnings differ from cash flows because they incorporate accruals. The main purpose of these accruals is to evaluate economic performance, by applying accounting principles and policies in a way that allows correlation of economic effort with activity level (earnings) during the financial year. In this way,
E it ¼ OCF it þ TotalAccrual it
where E
itis the net earnings of municipality i in period t; OCF
itis the operating cash
flow of municipality i in period t; and TotalAccrual
itis the total accruals of municipality i
in period t.
We calculate total accruals based on this formula:
TotalAccrual it ¼ E it OCF it
and the equation is:
TotalAccrual it ¼ DCA it DCash it DCL it Amort it
where TotalAccrual
itis the total accruals of municipality i in period t; DCA
itis the variation of current assets of municipality i between periods t and t 7 1; DCash
itis the cash variation of municipality i between periods t and t 7 1; DCL
itis the variation of current liability of municipality i between periods t and t 7 1; and Amort
itis the amortization of the accounting year of municipality i in period t.
This definition considers that accruals are a measure of a manager’s discretion in choosing accounting options. The accruals are considered as a preferred instrument for measuring earnings management because its use has a low cost and is difficult to detect (Young, 1999). Besides which, the measure is also an aggregate one, consisting of the net effect of various accounting practices (DeAngelo, 1986; Young, 1999).
Since accruals reflect the choice of accounting practices in the context of earnings management, total accruals are composed of discretionary accruals (reflecting changes in earnings that stem from a manager’s discretionary choice of accounting options) and non-discretionary accruals (reflecting changes in earnings that result from regular activity). However, neither of these can be observed directly, so methodologies aim to estimate discretionary accruals.
The first studies conducted by Healy (1985) and DeAngelo (1986) based their calculations of discretionary accruals on total accruals. Conversely, expectation models, such as the one proposed by Jones (1991), favour factor analysis to control the effect of changes in economic activity on the non-discretionary accruals. To estimate discretionary accruals, this study used the most commonly used model, as proposed by Jones (1991). According to Young (1999), this model is a good measurement mechanism for non-discretionary accruals.
Jones (1991) developed an expectation model that controls for the effect of changes in economic activity on non-discretionary accruals. He introduced variables for variations stemming from changes in activity levels (variation in sales) and depreciation of fixed assets:
TotalAccrual it
TotalAssets it1
¼ a 1 1 TotalAssets it1
þ b 1 DSS t TotalAssets it1
þ b 2 GTA t
TotalAssets it1
þ e it
Every variable was scaled to control for heteroscedasticity. The conversion factor is
the total amount of assets for the period t 7 1.
where TotalAccrual
itis the total accruals of municipality i in period t; TotalAssets
it71is the total assets of municipality i at the end of period t 7 1; DSS
itis the sales and services variations of municipality i between the periods t and t 7 1
3; GTA
itis the gross tangible assets of municipality i in period t; and e
itis the random error.
Parameters a
1, b
1iand b
2i, estimated by means of the previous regression, are used as estimators of a
1, b
1iand b
2i, respectively, for the estimation of discretionary accruals:
DisAccrual it ¼ TotalAccrual it
TotalAssets it1
a 1 1 TotalAssets it1
þ b 1i DSS it TotalAssets it1
þ b 2i GTA it
TotalAssets it1
where DisAccrual
itis the estimate of discretionary accruals of municipality i for period t, divided by total assets in period t 7 1.
One can apply Jones’ model (1991) to time series or cross-sectionally. As the data- collection time of our study was limited and it focuses on municipalities only, we applied Jones’ model cross-sectionally.
According to the premises, as stated above, and as far as an H
1test is concerned, the present study analyses the frequency distribution of cross-sectional net earnings before discretionary accruals. This was calculated as summarized below (every variable was scaled, using total asset amount for the period t 7 1 as a conversion factor in order to avoid heteroscedasticity problems):
EBeforeDisAccrual it ¼ E it DisAccrual it
where EBeforeDisAccrual
itis the net earnings before discretionary accruals of municipality i in period t divided by total assets in period t 7 1; E
itis the net earnings of municipality i in period t divided by total assets in period t 7 1; and DisAccrual
itis the estimate of discretionary accruals of municipality i in period t divided by total assets in period t 7 1.
In order to validate this analysis, the study also tested H
2, using the approach suggested by Leone and Horn (2005). This consists of the following regression (every variable was scaled, using the total assets of the previous year as the conversion factor, to avoid heteroscedasticity problems):
DisAccrual it ¼ a þ g 1 EBeforeDisAccrual it þ g 2 E it 1 þ g 3 DisAccrual it 1 þ e it
where DisAccrual
itis the estimate of discretionary accruals of municipality i in period t
divided by total assets in period t 7 1; EBeforeDisAccrual
itis the net earnings before
discretionary accruals of municipality i in period t divided by total assets in period
t 7 1; E
it71is the net earnings of municipality i in period t 7 1 divided by total
assets in period t 7 1; DisAccrual
it71is the estimate of discretionary accruals of
municipality i in period t 7 1 divided by total assets in period t 7 2; and e
itis the residuals.
These authors rely on the premise that discretionary accruals are used as a way of keeping positive net earnings close to zero (not very high). Thus, they expect an inverse relation between DisAccrual
itand EBeforeDisAccrual
itand, consequently, a negative value for the coefficient g
1. Leone and Horn (2005) include the independent E
it71variable because, according to Kothari et al. (2005), there is a positive relation between past performance and discretionary accruals for the present period. Thus, they expect g
2to be positive. Finally, they also consider the DisAccrual
it71variable in the regression to control for the probability of autocorrelation in discretionary accruals.
Test of H 3 hypothesis
To test the H
3hypothesis, we consecutively applied a number of procedures in order to confirm the results achieved by each procedure. As with the H1 hypothesis, the study employed the Burgstahler and Dichev (1997) methodology.
For the period covered by this study, 2002–8, we predicted that the performance of local politicians would be influenced by political competition, arising from municipal elections in 2001 and 2005. Given these circumstances, we divided the sample into two sub-periods. One sub-period covers the years 2003 and 2004, because these were the years prior to the election year. We predicted that, for this period, the occurrence of earnings management would be influenced by political competition. The calculation was based on the 2001 elections. A second sub-period covers the years 2006 and 2007, which are post-election years. For these years, it was predicted that the occurrence of earnings management would be influenced by political competition. This calculation was based on the 2005 elections. We exclude the year 2005 because it was an election year.
For each sub-period, we adopted a similar procedure to the one used by Moreira (2006, 2008). This consists of the division of the sample, according to the level of political competition, which then allows for the comparison of the frequency distributions of cross-sectional net earnings amongst the different samples. In each period, we divided the sample into two subsamples: one subsample includes municipalities in which there is weak political competition (WPC) and the other includes municipalities in which there is SPC.
In defining the political competition variable, we attempted to include all political parties. Thus, we used the measure developed by Laakso and Taagepera (1979). This measure is widely referenced in the literature, as it is considered to be a good proxy for political competition. Hence,
PComp ¼ 1 P s 2 i
where PComp is the political competition; and s
iis the votes achieved by party i at a
certain electoral time.
As stated by Taagepera (2002), this ratio indicates, on average, the number of political parties, which are active in the political arena. However, when a political party has/wins a majority, members from a different political party also have to be present.
Therefore, municipalities with WPC are those with PComp less than two and municipalities with SPC are those with PComp more than two.
Following Moreira (2006, 2008), for each subsample and sub-period, we also calculate the frequency grade of earnings management, defined as:
Fgm ¼ ne i na i
na i
where Fgm is the frequency grade of earnings management; na
iis the actual number of observations in a certain interval i; and ne
iis the expected number of observations in a certain interval i defined as the average of the actual number of observations in two immediately adjacent intervals assuming that, in the absence of earnings management, the frequency distribution of cross-sectional earnings is relatively smooth:
ne
i¼ (na
i71þ na
iþ1)/2.
The purpose of calculating this variable is to test statistically whether there are differences in earnings management between subsamples, for the various sub-periods.
Similar to Moreira (2008), the Z2 statistic proposed by Sandy (1990) was used to test the statistical difference in success of two independent samples. This was designed to test whether there are differences in earnings management across the subsamples for the period under analysis. The Z2 statistic is the probability density function of the difference between proportions of success in two independent samples. It gives an approximately normal distribution with zero mean and a standard deviation of one.
Under the null hypothesis of no previous statistical difference in the proportions, the Z2 may be summarized as:
Z2 ¼ ^ p SPC ^ p WPC s
where ^ p SPC – proportion of municipalities with SPC that manipulate net earnings; ^ p WPC – proportion of municipalities with WPC that manipulate net earnings; and s – the standard deviation is estimated as:
s ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi pð1 pÞ
n WPC
þ pð1 pÞ n SPC
s
where
n – expected number of municipalities with SPC and WPC; and p – weighted proportion of both samples:
p ¼ n SPC ^ p SPC n WPC ^ p WPC
n SPC þ n WPC
We tested the statistical significance of Z2 through the p-value, assuming a bidirectional test.
Finally, to complete the graphical analysis, and in keeping with Moreira (2006, 2008), Kim et al. (2003) and Beatty et al. (2002), a probit model was designed to test the probability of the influence of political competition leading to slightly positive and slightly negative earnings. A panel data method was also used to test the impact of political competition on the reporting of slightly positive and slightly negative earnings and to assess whether, given the known advantages of this methodology, it would provide better estimates.
The probit model is as follows:
Inter it ¼ a þ y 1 DPComp þ y 2 DE it 1 þ y 3 EDisAccrual it
þ y 4 LnTotalAssets it þ e it
where Inter
itis the dummy variable, the value of which is one if the municipality reports net earnings in the interval [0;0.03] and zero if it reports net earnings in the interval [ 7 0.03;0[; DPComp is the dummy variable, the value of which is one if the municipality has political competition equal or higher to 2 and zero if it has political competition lower than 2 (when a party has an absolute majority); DE
it71is the dummy variable, the value of which is one if municipality i reports positive net earnings in period t 7 1 and zero if it reports negative net earnings; EDisAccrual
itis the estimate of discretionary accruals for municipality i in period t divided by total assets in period t 7 1; LnTotalAssets
itis the natural logarithm of total assets of municipality i in period t divided by total assets in period t 7 1; and e
itis the random error.
As our objective was to test whether political competition influences the probability of reporting slightly positive earnings, we expected the coefficient y
1to be positive. We introduced the DE
it71variable into the analysis because we expected that the sign of net earnings for the former period would cause the sign of net earnings for the present period to be the same. Thus, the sign of y
2is also expected be positive. The study used the EDisAccrual
itvariable in the model, because, in the presence of earnings management, this variable should stimulate a positive relationship with the dependent variable. Therefore, the sign of y
3should also be positive. The LnTotalAssets
itvariable is a proxy for evaluating whether the municipality dimension has some influence upon earnings levels for the present period. There is no specific expectation with regard to the sign of y
4.
The panel data method considers both the cross-sectional dimension and temporal dimension. This allows one to analyse a given observation unit cross-sectionally over a particular time period. It has features that allow some limitations of cross-sectional regression and time series regression to be overcome (Baltagi, 2008).
Thus, we tested the above-mentioned model with panel data. In this case, the impact of political competition upon the disclosure of slightly positive earnings was evaluated.
We expect the same signs for the coefficients, as with the probit model.
In the panel data methodology, the study relies upon three estimation techniques for
unbalanced panels: pooled ordinary least squares (pooled OLS), the fixed effects model
(FEM) and the random effects model (REM). According to Baltagi (2008), this study applies the F-test to determine whether the pooled OLS or FEM model is more efficient and applies the Hausman test to determine whether the FEM or REM model is more efficient.
The F-test tests the hypothesis that all coefficients (excluding the constant) are equal to zero, i.e. testing the hypotheses of specific effects in municipalities. Where the null hypothesis is accepted, and the F-test is not significant, the pooled OLS is the best estimation model, meaning that there are no significant effects between municipalities. Where this is the case, we interpret the results of the pooled OLS model. Where the null hypothesis is rejected, a Hausman test is carried out to check whether the FEM or REM is more appropriate.
The Hausman test tests the null hypothesis that the REM is a more appropriate model than the FEM. The null hypothesis is that the coefficients in both models are similar.
Therefore, if they differ from each other, it means the FEM is simultaneously consistent and efficient. Consequently, if the null hypothesis is not rejected, and the test is not statistically significant, the REM results may be interpreted. If the null hypothesis is rejected, and the test is statistically significant, the FEM results are interpreted (Vieira, 2007).
EMPIRICAL ANALYSIS Hypotheses testing
Results of the H 1 hypothesis test
Table 1 summarizes the descriptive statistics for net earnings for each year studied.
Average net earnings are always positive, which is consistent with the hypothesis that the goal of municipalities is to report positive net earnings.
Figure 1 is a histogram of the frequency distribution of cross-sectional net earnings for intervals of 0.03.
4This indicates that there is a clear discontinuity around the first interval, to the right of zero. Table 2 shows that, for this interval, Z is 9.651, which is statistically significant at the 1 per cent level and confirms the observed discontinuity.
Table 1: Descriptive statistics for net earnings in period t converted by total assets at the end of period t 7 1
No. of observations Average Standard deviation Q1 Q2 Q3
Year E
itE
itE
itE
itE
itE
it2003 118 0.100 0.181 0.013 0.055 0.129
2004 241 0.058 0.143 0.006 0.037 0.093
2005 266 0.035 0.079 70.006 0.022 0.059
2006 272 0.038 0.160 0.000 0.022 0.054
2007 276 0.024 0.057 70.006 0.016 0.049
2008 280 0.006 0.039 70.014 0.005 0.025
Total/average 1,453 0.044 0.110 70.001 0.026 0.068
Indeed, it indicates that the frequency distribution of the net earnings in the first interval to the right of zero is higher than expected.
We may interpret these results as indicators that, for the municipalities included in the sample, local politicians try to do earnings management in such a way as to avoid
Figure 1: Histogram of frequency distribution of cross-sectional net earnings for intervals of 0.03. The first interval to the right of zero includes all net earnings that are inside the interval [0;0.03]. The second interval includes all net earnings that are inside the interval [0.03;0.06[ and so forth
Table 2: Statistical significance of discontinuities close to zero in the frequency distribution of cross- sectional converted net earnings
2003–8 E
itNo. of observations
Z-statistic
Interval Real Expected (p-value)
]70.03;0] 276 278 70.085
(70.932)
]0;0.03] 458 265 9.651***
(0.000)
Notes: (a) ***significance level at 1 per cent. (b) The statistical significance evaluated on the assumption thatZ
follows a standard normal distribution. (c)
Z-Statistic is given by:Z¼ ðnaineiÞ=ðs ðnaineiÞÞ
where
naiis the actual number of observations in a certain interval
i;neiis the expected number of observations in a certain interval
i, defined as the average of the actual number of observations in two immediately adjacent intervals:nei¼
(na
t71þnatþ1)/2; and
s(nai7nei) is the standard deviation of the difference between the actual number of observations i n a c e r t a i n i n t e r v a l
ia n d t h e n u m b e r o f e x p e c t e d o b s e r v a t i o n s i n t h a t s a m e i n t e r v a l
i:
s¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiNpi ð1piÞ þ ðN ðpði1Þþpðiþ1ÞÞð1pði1Þpðiþ1ÞÞÞ=4
p
, where
Nis the total number of observations in
the sample; and
piis the probability that one observation is placed in the interval
i.reporting negative earnings. This may be understood as an attempt to report positive earnings close to zero.
By doing this, local politicians aim to report earnings that will not be interpreted by the public or interest groups as excessive. They present the idea that their public resource management is conducted based on economic and efficiency principles; in general, such resources are at the disposal of the public need. Thus, the results confirm/led us to accept H
1.
Results of the H 2 hypothesis test
As the information required to calculate some of the variables is spread across various consecutive periods, the sample is smaller than initially planned. For the sake of comparability, the test was only applied to municipalities for which it was possible to calculate discretionary accruals for a given time period.
The descriptive statistics for the variables used in the test are summarized in Table 3.
All variables show a positive average.
The frequency distribution of cross-sectional earnings before discretionary accruals has been depicted in a graph and the frequency distribution of cross-sectional net earnings for intervals of 0.03. The histogram analysis in Figure 2 shows that both frequency distributions and discontinuities can be pinpointed to the right of zero.
In the first interval immediately to the left of zero, only the frequency distribution of cross-sectional earnings before discretionary accruals reveals discontinuities.
The statistical significance of discontinuities around zero is shown in Table 4. For the first interval to the right of zero, Z is 8.942, which is statistically significant at the 1 per cent level. For the frequency distribution of cross-sectional net earnings, 4.026 is also statistically significant at the 1 per cent level, for the frequency distribution of cross- sectional net earnings before discretionary accruals.
These results are consistent with the idea that local governments avoid disclosing negative net earnings and try to disclose positive net earnings close to zero. They also suggest that the municipalities under analysis use the discretional power allowed in election practices and accounting policies to report low positive net earnings.
The regression results summarized in Table 5 confirm Leone and Horn’s expectations (2005), both for g
1and g
2, which means that g
1is negative, and g
2is
Table 3: Descriptive statistics for the variables used in the test of H
2with discretionary accruals calculated using Jones’ model (1991)
Independent variables No. of observations Average Standard deviation Q1 Q2 Q3
E
it1,154 0.029 0.095 70.006 0.017 0.049
DisAccrual
it1,154 0.000 0.054 70.018 0.006 0.026
EBeforeDisAccrual
it1,154 0.027 0.099 70.017 0.012 0.054
Figure 2: Histograms of frequency distribution of cross-sectional net earnings and frequency distribution of cross-sectional net earnings before discretionary accruals to intervals of amplitude 0.03
Table 4: Statistical significance of discontinuities close to zero in the frequency distribution of cross- sectional converted net earnings and the frequency distribution of cross-sectional converted net earnings before discretionary accruals
2003–8 2003–8
E
itEBeforeDisAccrual
itNo. of observations
Z-statistic No. of observations
Z-statistic
Interval Real Expected (p-value) Real Expected (p-value)
]70.03;0] 233 234 70.031 267 207 3.641***
(70.975) (0.000)
]0;0.03] 383 222 8.942*** 283 216 4.026***
(0.000) (0.000)
Notes: (a) ***significance level at 1 per cent. (b) The statistical significance evaluated on the assumption thatZ
follows a standard normal distribution. (c)
Z-statistic is given by:Z¼ ðnaineiÞ=ðs ðnaineiÞÞ
where
naiis the actual number of observations in a certain interval
i;neiis the expected number of observations in a certain interval
i, defined as the average of the actual number of observations in two immediately adjacentintervals:
nei¼(na
t71þnatþ1)/2; and
s(nai7nei) is the standard deviation of the difference between the actual number of observations in a certain interval
iand the number of expected observations in that same interval
i:s¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Npi ð1piÞ þ ðN ðpði1Þþpðiþ1ÞÞð1pði1Þpðiþ1ÞÞÞ=4
p
, where
Nis the total number of observations in
the sample and
piis the probability that one observation is placed in the interval
i.positive. It is also worth mentioning that the t-value is significant for all coefficients. On the other hand, the adjusted R
2shows very high values. The results confirm H
2. This allows us to conclude that local politicians use discretionary accruals as a way of maintaining positive net earnings close to zero.
Results of the H 3 hypothesis test
The histogram in Figure 3 shows the frequency distribution of cross-sectional net earnings for intervals 0.03, for the subsample of municipalities with SPC and WPC, in the pre-election period (2003–4).
5There is a discontinuity around the first interval to the right of zero.
Table 6 shows that, for SPC municipalities, Z is 2.509, statistically significant at the 5 per cent level, and 70.860, which is not statistically significant, for the first interval to the right and left of zero, respectively. As for WPC municipalities, Z is 2.103, statistically significant at the 5 per cent level, and 0.250, which is not statistically significant, for the first interval to the right and left of zero, respectively.
Table 5: Results using Leone and Horn’s regression (2005)
2005 2006 2007 2008
Coefficient Coefficient Coefficient Coefficient Independent variables Expected sign (t-value) (t-value) (t-value) (t-value)
Const 70.008** 0.004* 0.009*** 70.001
(72.255) (1.655) (3.316) (70.575)
EBeforeDisAccrual
it7 70.819*** 70.504*** 70.414*** 70.762***
(714.615) (712.178) (710.101) (720.267)
E
it71þ 0.527*** 0.256*** 0.038** 0.260***
(10.605) (6.573) (2.423) (6.670)
DisAccrual
it710.016 70.016 0.041 0.107**
(0.332) (70.376) (0.727) (2.545)
F statistic 77.907*** 50.519*** 35.251*** 146.178***
Adjusted R
20.650 0.389 0.286 0.629
No. of observations 125 234 258 258
Notes: (a) *Significance level at 10 per cent; **significance level at 5 per cent; ***significance level at 1 per cent. (b) The
model is:
DisAccrualit¼aþg1EBeforeDisAccrualitþg2Eit1þg3DisAccrualit1þeit
where
DisAccrualitis the estimate of discretionary accruals of municipality
iin period
tdivided by total assets in period
t71;
EBeforeDisAccrualitis the net earnings before discretionary accruals of municipality
iin period
tdivided by total assets in period
t71;
Eit71is the net earnings of municipality
iin period
t71 divided by total assets in period
t71;
DisAccrualit71
is the estimate of discretionary accruals of municipality
iin period
t71 divided by total assets in period
t72; and
eitis the residuals.
Figure 4 is a histogram of the frequency distribution of cross-sectional net earnings for intervals of 0.03 for subsamples of SPC and WPC municipalities in post-election periods (2006–7).
6There appears to be discontinuity around the first interval to the right of zero.
Figure 3: Frequency distribution histogram of cross-sectional net earnings for intervals of 0.03 for the subsamples of SPC and WPC municipalities in pre-election period (2003–04)
Table 6: Statistical significance of discontinuities around zero in the frequency distribution of cross-sectional net earnings for SPC and WPC municipalities in pre-election period (2003–4)
Pre-election period (2003–4)
SPC WPC
No. of observations
Z-statistic No. of observations
Z-statistic
Interval Real Expected (p-value) Real Expected (p-value)
]70.03;0] 16 20 70.860 30 29 0.250
(70.370) (0.803)
]0;0.03] 37 22 2.509** 47 33 2.103**
(0.012) (0.036)
Notes: (a) ***significance level at 1 per cent. (b) The statistical significance evaluated on the assumption thatZ
follows a standard normal distribution. (c)
Z-statistic is given by:Z¼ ðnaineiÞ=ðs ðnaineiÞÞ
where
naiis the actual number of observations in a certain interval
i;neiis the expected number of observations in a certain interval
i,defined as the average of the actual number of observations in two immediately adjacent intervals:
nei¼(nat71þnatþ1)/2; and
s(nai7nei) is the standard deviation of the difference between the actual number of observations in a certain interval
iand the number of expected observations in that same interval
i:s¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiNpi ð1piÞ þ ðN ðpði1Þþpðiþ1ÞÞð1pði1Þpðiþ1ÞÞÞ=4
p
,
where
Nis the total number of observations in the sample and
piis the probability that one observation is placed in the interval
i.In this case, Table 7 shows that Z for SPC municipalities is 5.213, statistically significant at the 1 per cent level, and 72.744, also statistically significant at the 1 per cent level, for the first interval to the right and left of zero, respectively. For WPC municipalities, Z is 4.541, statistically significant at the 1 per cent level, and 1.261, which is not statistically significant, for the first interval to the right and left of zero, respectively.
In both cases, Z values appear to indicate that discontinuity is higher in SPC municipalities. However, since Z depends on the number of observations and varies across intervals and distributions, statistical comparison should not be used to evaluate the frequency grade of earnings management (Fgm), as previously defined.
Table 8 shows that Fgm for municipalities which have net earnings in the first interval to the right of zero is always higher than Fgm for municipalities which have net earnings in the first interval to the left of zero. This is consistent with the idea that local governments avoid reporting negative earnings and try to report positive earnings close to zero, interpreted as a positive performance. It is also consistent with the graphical analysis that points out higher discontinuity in the interval to the right of zero and for Z.
Comparing Fgm for SPC municipalities with Fgm for WPC municipalities, we see that, in both periods, Fgm is higher in SPC municipalities, either for the first interval to the right of zero or for the first interval to the left of zero. These results seem to indicate that, as a trend, the higher the political competition, the higher the predisposition to manage earnings. We should also point out that Fgm is higher in the post-election period than in the pre-election period. This may be because, in this period, there was a higher consolidation and reporting of financial statements and awareness that net earnings were a performance measure for local politicians.
The Z2 test for the difference in success between two independent samples for the pre-election period is not statistically significant for the first interval to the left of zero
Figure 4: Frequency distribution histograms of cross-sectional net earnings for intervals of 0.03 for
subsamples of SPC and WPC municipalities for post-election period (2006–07)
and is statistically significant at 5 per cent for the first interval to the right of zero. For the post-election period, the test is statistically significant at 5 per cent for the first interval to the left of zero and significant at 1 per cent level for the first interval to the right of zero.
These results confirm the graphical analysis, indicating once again that the mayors who face greater political competition have a greater need to demonstrate their high level of competence and thus tend to report positive earnings close to zero.
As referred to above, in order to complete the analysis, a probit model was used to test the probability of political competition having an influence on reporting slightly positive and slightly negative earnings. In order to check which variables have more influence on net earnings behaviour, two models were chosen for each period: Model A, using the DPComp
2001variable, and Model B, using the DPComp
2001, DE
it71and LnTotalAssets
itvariables. For the post-election period, a Model C that uses the DPComp
2005, E
it71, LnTotalAssets
itand DisAccrual
itvariables was also tested.
The regression results for the probit model with cross-sectional data are detailed in Table 9. Given the value of R
2McFadden, the regressions corresponding to each of the models can be considered significant, with the exception of Model A, where R
2McFadden is very low, indicating that there are other explanatory variables besides the
Table 7: Statistical significance of discontinuities close to zero in the frequency distribution of cross- sectional net earnings for SPC and WPC municipalities in post-election period (2006–7)
Post-election period (2006–7)
SPC WPC
No. of observations
Z-statistic No. of observations
Z-statistic
Interval Real Expected (p-value) Real Expected (p-value)
[70.03;0[ 31 49 72.744*** 74 63 1.261
(70.006) (0.207)
[0;0.03] 85 43 5.213*** 105 62 4.541***
(0.000) (0.000)
Notes: (a) ***significance level at 1 per cent. (b) The statistical significance evaluated on the assumption thatZ
follows a standard normal distribution. (c)
Z-statistic is given by:Z¼ ðnaineiÞ=ðs ðnaineiÞÞ
where
naiis the actual number of observations in a certain interval
i;neiis the expected number of observations in a certain interval
i, defined as the average of the actual number of observations in two immediately adjacent intervals:nei¼(na
t71þnatþ1)/2; and
s(nai7nei) is the standard deviation of the difference between the actual number of observations in a certain interval
iand the number of expected observations in that same interval
i:s¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiNpi ð1piÞ þ ðN ðpði1Þþpðiþ1ÞÞð1pði1Þpðiþ1ÞÞÞ=4
p
,
where
Nis the total number of observations in the sample and
piis the probability that one observation is placed in the
interval
i.DPComp variable. This interpretation seems consistent with the fact that R
2McFadden for Model B increases in both the pre-election and post-election periods and increases further in Model C in the post-election period.
The Likelihood Ratio (LR) statistic is significant at the 1 per cent level for Models B and C in both periods. In Model A, the LR statistic is significant only at 5 per cent for the pre-election and post-election periods, which is in line with the low value of R
2McFadden. When comparing Model B with Model C, we found that, in Model C, the values of R
2McFadden and LR increase, the DisAccrual
itvariable is significant at the 1 per cent level, DPComp
2005variable is not significant in Model C and LnTotalAssets
itvariable remains not statistically significant.
Therefore, we looked at the pre-election period for Model B and the post-election period for Model C. In the pre-election period in Model B, the coefficients of the DPComp
2001and DE
it71variables are statistically significant at the 10 per cent and 1 per cent level, respectively. The coefficient of the LnTotalAssets
itvariable is not significant.
Table 8: Frequency grade of manipulation
Pre-election period (2003–4) Post-election period (2006–7)
]70.03;0] ]0;0.03] ]70.03;0[ ]0;0.03]
SPC WPC SPC WPC SPC WPC SPC WPC
Fgm 0.20 0.05 0.68 0.45 0.36 0.17 1 0.69
Difference in Fgm 0.15 0.24 0.19 0.31
Standard deviation 0.01 0.09 0.07 0.08
Z2 1.288 2.063** 2.706** 3.797***
(p-value) (0.198) (0.039) (0.007) (0.000)
Notes: (a) **significance level at 5 per cent; ***significance level at 1 per cent. (b) The statistical significance evaluated on the
assumption that
Zfollows a standard normal distribution. (c)
Fgmis given by:
Fgm¼ neinai
nai
where
Fgmis the frequency grade of manipulation;
naiis the actual number of observations in a certain interval
i; andneiis the expected number of observations in a certain interval
idefined as the average of the actual number of observations in two immediately adjacent intervals:
nei¼(na
i71þnaiþ1)/2.
(d)
Z2 is given by:Z2¼^pSPC^pWPC
s
where
^pSPCis the proportion of municipalities with SPC that manipulate net earnings;
^pWPCis the proportion of municipalities with WPC that manipulate net earnings; the standard deviation is estimated as:
s¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi pð1pÞ=nWPCþpð1pÞ=nSPC
p
, where
nis the expected number of municipalities with SPC and WPC; and p
is the weighted proportion of both samples:
p¼ ðnSPC^pSPCnWPC^pWPCÞ=ðnSPCþnWPCÞ.The coefficients of the DPComp
2001and DE
it71variables are positive, indicating that both political competition and net earnings for the previous period increase the likelihood of local governments disclosing positive earnings close to zero for the current period.
For the post-election period, in Model C, the DPComp
2005and LnTotalAssets
itvariables are not significant. The coefficients of the DE
it71and DisAccrual
itvariables are significant at the 1 per cent level and are positive. The interpretation of the DE
it71variable is
Table 9: Results of the probit model with cross-sectional data
2003–4 2006–7
Model A Model B Model A Model B Model C
Independent Expected Coefficient Coefficient Coefficient Coefficient Coefficient variable sign (Z-statistic) (Z-statistic) (Z-statistic) (Z-statistic) (Z-statistic)
Const 0.097 70.543* 0.212** 70.555 70.225
(0.480) (70.187) (2.203) (70.294) (70.117)
DPComp
2001þ 0.619** 0.543*
(2.062) (1.669)
DPComp
2005þ 0.392** 0.307* 0.266
(2.458) (1.663) (1.416)
DE
t71þ 1.311*** 1.734*** 1.770***
(3.912) (9.684) (9.680)
DisAccrual
itþ 6.625***
(3.004)
LnTotalAssets
it70.011 70.013 70.030
(70.072) (70.123) (74.958)
R
2McFadden 0.043 0.198 0.016 0.299 0.323
LR statistic 4.331** 19.786*** 6.118** 110.449*** 119.608***
Notes: (a) *Significance level at 10 per cent; **significance level at 5 per cent; ***significance level at 1 per cent. (b) The
dependent variable,
INTER, has seventy-seven observations for the pre-election period, of which twenty-seven are zero and fiftyare one. The SPC municipalities represent approximately 65 per cent of the total number of observations. For the post-election period, we have 283 observations of which 102 are zero and 181 are one. The SPC municipalities represent approximately 64 per cent of the total number of observations. (c) The model used is:
Interit¼aþy1DPCompþy2DEit1þy3DisAccrualitþy4LnTotalAssetsitþeit
