RSAC and MSc thesis template
The use of non-financial performance measurements in CEO compensation after the financial crisis
Name: Giovanni Kuhurima Student number: 11397098
Thesis supervisor: Pouyan Ghazizadeh Date: June 25, 2018
Word count: 4974, 0
MSc Accountancy & Control, specialization Control
Statement of Originality
This document is written by student Giovanni Kuhurima who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
This thesis studies the use of non-financial performance measures in CEO compensation after the financial crisis. For this research, data has been collected of stock-listed firms of the USA, for the years 2005-2006 and 2012-2013. These years are considered as pre-crisis (2005-2006) and post-crisis (2012-2013). The use of non-financial performance measurements is the dependent variable in this study. This information is found in the proxy statements that are published by the firms every year.
1 Introduction
Background
The financial crisis of 2008 had a huge impact on the market. The crisis, which started in 2008, has led to uncertainty in the markets. Organizations had to react on the situation in order to ‘survive’. A couple effects are decline in revenue, sales, which may be crucial for companies. Even though this happens, sometimes CEO’s still receive bonuses even when there is no profit made. They have to be incentivized even during a period of bad
performance. Determining bonuses for CEO’s during times of financial distress may become more difficult, as financial measures become less reliable and therefore noisier.
A CEO compensation plan consists of two types of performance measurement. The two types are financial and non-financial measurements. Financial measurements are measures that can be taken from the financial statements such as profit, costs etc. Non-financial measurements are more firm-specific and looks at measures such as efficiency and customer satisfaction. Both types have their advantages and disadvantages, and therefore the choice of using them may differ during times. Most CEO compensation plans are determined by both types. Study on the use of financial and non-financial measurements in CEO compensation plans has been done by Ittner et al. (1997). Even though financial measures are considered as the most important, they find that there is a rise in the use of non-financial measures due to a decrease in informativeness of financial performance measurements. When looking at the choice between financial and non-financial, Said et al. (2003) find that non-financial
measurements are used for aligning interest of shareholders with the managers, and therefore included in the CEO compensation. Besides, there is also evidence that the use of non-financial measurements in CEO compensation is positively associated with future non-financial performance, as non-financial measurements leads to a shift in a more long-term perspective for managers (Banker, Potter, & Srinivasan, 2000). This shows the importance of the use of both financial and non-financial measurements.
This study will look at how the financial crisis affected the use of non-financial performance measurements after the crisis. The following research question will be answered:
Does the financial crisis affect the use of non-financial performance measurements for the years after the crisis?
The post-crisis years are defined as the period after 2011. In this study we will look and compare the effect of the stabilizing years after the crisis. The end of the financial crisis leads to a decrease in noise in financial measures. Therefore it is expected that in the period after the crisis, a decrease in non-financial performance should occur based on prior literature. Data of 70 American listed firms, for the years 2005-2006 and 2012-2013 were collected and used from several databases. The use of non-financial performance measurements in the CEO compensation for the period before the crisis and after the crisis will be investigated. The study provides evidence that when there is a new CEO is hired during the crisis years, less non-financial performance measurements are used in the CEO compensation plan. It also provides evidence that when there is no change in CEO, the use of non-financial performance measurements increases after the crisis. These results together may provide evidence that there is a change in the use of non-financial performance measurements that is influenced by the crisis, but the hiring of a new CEO has also plays a major factor.
This study will add on existing literature such as Ittner (1997). The same topic is discussed, the use of non-financial performance measurements. It will provide empirical evidence of the use of non-financial performance measurements before and after the crisis. Previous literature has shown the effect of an increase in noise, but it is unknown how the decrease in noise influences the choice in the use of non-financial measurements.
2 Literature review
The literature review consists of four parts. The first part discusses the CEO compensation. The second part is about performance measurements. The third part discusses the financial crisis. At the end the hypothesis that will be answered by this study is stated.
2.1 CEO compensation
The CEO compensation consists of two parts: the fixed and the variable parts. It includes base salary, annual bonus, long-term incentives and several stock-related bonuses (Murphy K. , 1999)
The fixed part of the compensation is the base salary. This is the key component of the contract and consists of the fixed amount the CEO receives. Since this part is fixed, the financial performance of the firm does not directly influence this compensation. The variable part consists of the annual bonus plan, stock options and other forms of compensation The annual bonus plan is based on the firm’s performance of the year. Achieving the targets that are set prior year should lead to a bonus for the executive, while not achieving the target will lead to missing the bonus. Companies use a variety of financial and nonfinancial measurements for determining this bonus. A more complex incentive are stock options. Stock options are contracts which give the recipient the right to buy a share of stock at a pre-specified "exercise" (or "strike") price for a pre-specified term (Murphy K. , 1999). More recent study show that these incentives are complex since they cover multiple years. Its measurement is much more complex compared to the more short-term oriented incentive plans such as the annual bonus plan (Murphy G. , 2012).
Agency theory
An organization that works with managers wants to align the executive’s interests with the organization’s interest, also known as agency theory. This happens when a person perform actions on behalf of another person. A problem that arises when the interest of both persons are not aligned, is called ‘agency theory’. This happens when the person does not perform actions that are in the best interest of the firm (Jensen & Meckling, 1976)
One of methods to improve the alignment of the interest of the CEO is the use of incentive plans, that rewards the CEO when the actions taken are in the interest of the firm. A CEO that is incentivized by this plan takes more ownership in this company (Beatty & Zajac, 1994).
A problem that may are is the agency problem, whereas the executive to not act in the best interest of the organization. To cover this problem , a part of the compensation is based on individual performance. The performance measures that are used for rewarding the individual performance are usually based on non-financial measures (Bushman 1996).
2.2 Performance measurements
Different performance measurements are available for organizations to use. The two are financial and non-financial performance measurements.
Financial
In the past, most firms only used financial performance measures for rewarding the CEO. Examples of financial performance measurements are profit, sales, stock price (Ibrahim & Lloyd, 2011). Bacidore et al (1997) argue that these measurements provide information about the performance of the firm, and therefore also the performance of the decisions of the CEO. There are two types of financial measures, market measures and accounting measures. They differ from each other as market measures are more forward-looking measures as they are based on the stock prices. Accounting measures are based on results from the financial statements, and are therefore more backward-looking measures. Another difference between the two measures is that accounting measures are less congruent with the value of the firm. Non-financial
Non-Financial performance measurements measure the non-financial aspects of the firm. Examples of non-financial performance measurements are workforce development, product quality, customer satisfaction, on time delivery, innovation measures, attainment of strategic objectives, market share, efficiency, productivity, leadership and employee satisfaction (Ibrahim & Lloyd, 2011; Ittner, Larcker, & Rajan, 1997). These nonfinancial measurements are not always in the annual report, as firms are not obliged to share this information.
There are several reasons why firms would choose for the use of non-financial measurements. Ittner et al (1997) studies the use of non-financial performance measurements, and finds several reasons. First of all, the firm’s strategy is an important factor in using non-financial measures. Long-term oriented strategies follows with more use of non-financial, while short-term oriented strategies comes with more focus on financial performance measurements. This
is in line with a study by Sliwka (2002) as he finds that non-financial performance are
important when they are related to the strategy. Another reason is that non-financial measures provides information that can’t be provided by financial measures. Ittner (1998) finds that non-financial measures about customer satisfaction are important for determining customer behavior, and is positively related to the firm’s performance. These measures provides information that leads to an increase in firm value. Last of all is the noise in financial
measures. Noise in financial measures, which reduces the informativeness of the metric, will lead to more focus on non-financial measures (Ittner 1997). Davila (2004) finds the same in the airline industry, as the noise in financial measures has led to a shift towards more use of non-financial measures.
Difference/arguments
Both measurements have their advantages and disadvantages. A major difference between both is collecting the data, as financial performance measurements are more easy to obtain and to measure, while nonfinancial performance measurements need more effort and work before they can be used. One of the common used performance measurements for evaluating CEO’s is the balance scorecard (Kaplan & Norton, 2005). It consists of both financial and nonfinancial performance measurements. The combination of both is important, as they argue that having only financial measurements will lead to a short-term oriented focus. Several studies highlight the advantages of using nonfinancial measurements against financial
measurements. Banker, Potter and Srinivasan (2000) find that nonfinancial measurements are more accurate in predicting long-term profits, and therefore should be included in the bonus of a manager. In this way the manager is motivated to take actions that are aligned with the long-term interest of shareholders. Said (2003) concludes that nonfinancial measurements can support the improvement of firm performance. Rewards based on individual performance measurements are also part of nonfinancial performance measurements in CEO bonuses. Bushman et al. (1996) finds that CEO’s are rewarded based on their individual performances. These individual performance measurements are a part of the non-financial part of the annual bonus plan. However, nonfinancial measurements do have a limitation, as it is subject to manipulation (Ittner, Larcker, & Rajan, 1997).
Noise
The study by Ittner (1997) shows that the use of financial and non-financial performance measurements is also based on the amount of noise in performance measures. Financial
measures are more volatile to external noise than non-financial measures. When there is more noise in financial performance measures, firms tend to use more non-financial measures for the CEO compensation.
2.3 Financial crisis
Important factor in this study is the economic crisis, which started around 2008 with the bankruptcy of Lehman Brothers (Cordemans & Ide, 2012). This has led to panic in the market, where organization’s became more careful in their spending.
Financial measures gives information about how an organization has performed. Financial shocks, which is considered as noise, have affected the financial measures and therefore these financial measures are volatile to the financial crisis (Stock, 2012). Non-financial measures, however, are more firm-specific and can be considered as less vulnerable to noise. One of the first literature that looks at the weight on measures, finds that when noise
increases in a certain measure, the weight on that measure decreases. (Banker)
Bebchuk and fried (2010) find that there is a change of the use of performance measurements. During the crisis the focus is more on non-financial performance measurements. This led to a decrease in the use of financial performance measurements.
Previous research found evidence of this theory, as they find changes in the use of financial performance measures in CEO bonuses. Ittner et al (Ittner, Larcker, & Rajan, 1997) find that when financial measures become less reliable because of noise in the metrics, firms will focus more on non-financial measures. The decreasing informativeness was a reason of the change in focus. In line with this theory, Davila (2004) finds that the use of non-financial measurements is related with the volatility of financial performance measurements. A shift in the use of financial and non-financial measures is also find The economic crisis causes noise in performance measurements, so we can assume that the recovery years will lead to less noise in the performance measurements, as the opposite of the first effect. As Ittner (1997) finds that the emphasis on nonfinancial measurements will be more when financial
measurements become noisy, the assumption can be made that the opposite will happen when these measurements become less noisy, as that will be happening during the recovery years. 2.4 Hypothesis
The papers in the literature review contain some assumptions. Important for the hypothesis development is the impact noise in financial measurements has on the choice between
financial and nonfinancial measurements. The financial crisis leads to noise in measures and organizations are trying to find reliable information that is useful for evaluation and
rewarding of CEO’s. As it is obvious that at the start of the economic crisis a shift will be made towards nonfinancial measurements, this thesis will look at the post-crisis years. Based on the literature, the following hypothesis is stated:
H1: The financial crisis has a negative effect on the use of non-financial measures after the crisis.
It is expected that the results of this study should show that the use of non-financial measures is negatively related to the financial crisis. Ittner (1997) finds the shift in the use of financial performance measurements due to noise in the metrics. Since the financial crisis is over, less noise in the metrics are expected, and therefore a decrease in the use of non-financial
3 Methodology
This study looks at stock-listed firms in the USA. The data for this study are extracted from several databases. The data is collected for the period of 2005-2006, which are considered as the years before the crisis, and the years 2012-2013 that are considered as post-crisis years. In this chapter, the collection of data, the model used for this research and the variables are discussed.
Data collection
Three different databases were needed to collect the data for the research. Combining the information of all three will be used to answer the hypothesis.
The information about CEO’s were found in the Execucomp database. It is a sub database that collects information such as CEO salary, CEO bonuses. The variable with the CEO characteristics uses the data from this database.
The Compustat database was to collect financial information. This database consists of financial statements that are needed for determining the variables that uses financial information.
Lastly, the Lexis/Nexis database provides the proxy statements. These so-called DEF 14A documents includes information of CEO compensation on performance measurements and are used for determining the use of non-financial measures in CEO compensation. The data from the proxy statements were hand-collected.
First data was collected from the Execucomp database and Compustat database, since these did not require any hand-collecting. After gathering the data for the years 2005-2006 and 2012-2013 from the two databases, the collected data was combined into one dataset. This dataset consisted of a total number of 4844 observations. Hand-collect the data from the proxy statements of all observations did not seem realistic, and therefore a number of steps were taken to reduce this amount.
The first step to decrease the amount of observations was to keep only the 10 largest firms based on firm size of the year 2013. The size of the firm was determined by the variable firmsize, which is determined by the logarithm of total assets.
The second step was leaving out observations of two industries. The industry ‘Agriculture, forestry, & fishing’ was excluded because of missing data. The industry ‘Financial services’
was excluded because of an increase in regulation of CEO compensation in the financial industries industry, which may bias the results.
The total observations for this sample after these two steps are 280 observations. This sample is used for answering the research question.
Model
The influence of non-financial measurements after the crisis is tested by looking at the use of non-financial in the CEO compensation. Therefore the dependent variable for this test is the use of non-financial performance measures in CEO compensation (NF). This variable will have a value of 1 if the proxy statement consists of a non-financial objective/criteria, while it has a value of 0 if does not consist a non-financial objective/criteria.
The following model is used to look at the influence of non-financial measurements after the crisis:
NF = α + β1 POSTCRISIS + β2 NEWCEO + β3 CRISISCEO + β4 LOSS_PREVYEAR + β5 FIRMSIZE + β6 LEVERAGE + β7 INDROA + β8 – β14 SICCAT
Test variables
The test variable is POSTCRISIS. This dummy variable has a value of 1 for the years 2012-2013 and 0 for the years 2005-2006. It is expected that half of all the observations are in the post-crisis years.
The next variables look at CEO characteristics. The variable NEWCEO is determined by hiring a new CEO. It has a value of 1 if a new CEO is hired year .When there is no change in CEO, it has a value of 0. Another CEO characteristic variable is CRISISCEO. This variable is determined by hiring a CEO during the crisis. If the new CEO is hired in the year 2008, 2009 or 2010, it has a value of 1. When this is not the case, when there is no new CEO or the CEO is hired after 2011, the variable has a value of 0.
The following variable is based on the financial performance of the firm. Previous years’ performance may have an impact on the use of non-financial measures, as it may be a reason to include more of non-financial measures. If the firm made a loss in the previous year, the
variable has a value of 1. If they made a profit in the previous year, the variable has a value of 0. This data is collected from the Compustat database.
The following control variables are included.
The variable INDROA is calculated by subtracting the firm’s ROA (Return on Assets) from the industry average ROA, where ROA is measured by dividing the net income with the total assets.FIRMSIZE is determined by the log of assets of the firm (Aldamen, 2011).
LEVERAGE measures the leverage of a firm. It is calculated by dividing the firm’s debt by its equity. The variables INDROA, FIRMSIZE, and LEVERAGE use data that are collected from the Compustat database.
The sample is also divided into different industries. The different industries each may have a different outcome, as some are more regulated than the other It is based on the SIC code, as it tells in what industry it operates.
Descriptive statistics
In table x the descriptive statistics of this sample are shown. Its minimum, maximum, mean and standard deviation is included.
Of all variables, 5 of them are dummy variables that has a minimum of 0 and a maximum of 1.
The mean of the variable NF is around 0.52. This means that in almost 52% of the observed CEO compensation plans, non-financial measures are used to determine the bonus a CEO earns. The other 48% bonus plans do not contain any non-financial measures. The variable POSTCRISIS has a mean of 0.5. This is because for all 280 observations, exactly half of all are in the post-crisis period.
Around 44% of the observed sample consist a change in CEO. One tenth of these changes, a new CEO is hired during the crisis (CRISISCEO). The variable LOSS_PREVYEAR has a mean of around 0.05. This means that in 95% it is the case that a profit has been made in the previous year. Recovering of the financial crisis may be an explanation of this low mean.
The leverage is calculated by the log of assets, and has an average of around 1.33. By looking at this variable, it means that there is 1.33 times more debt than equity, as leverage is the debt to equity ratio.
The variable INDROA has a negative mean of -0.02. Since it is negative, the investments that are made does not cover the costs. In fact, any investments will not result in any profit, so there is a case of losing money.
This is meeting my expectations, as previous studies have shown that the financial crisis has an impact on the use of non-financial measures in CEO compensation. The crisis may cause difficult times for firms.
Results
It is clear that non-financial measures are more used after the financial crisis. There is an increase from 46% before the crisis to 53% after the crisis.
Correlation
In table 1 the correlation between the variables is shown.
All the relations with the dependent variable is relatively small. The relation between firmsize and non-financial measures in CEO bonus is the largest of all relations, while
LOSS_PREVYEAR is the smallest. However, not all variables are significant related with the dependent variable.
The variables that are significant related with the use of non-financial measures are crisisceo, firmsize and INDROA. This means that these variables have an influence on the PERFMEAS variable.
Interesting is that CRISISCEO is negatively related with the use of non-financial
performance measures, which indicates that there is less use of non-financial performance measures.
Table 1 - Correlation matrix Correlation model NF POSTCRISI S NEWCE O CRISISCE O LOSS_PREVYEA R FIRMSIZ E LEVERAG E INDRO A NF 1 POSTCRISIS 0,064 1 NEWCEO 0,026 0,446*** 1 CRISISCEO -0,107* 0,333*** 0,3739*** 1 LOSS_PREVYEA R 0,007 0,143*** 0,0753 0,026 1 FIRMSIZE 0,262** * 0,284*** 0,2429*** 0,141** -0,012 1 LEVERAGE -0,022 -0,034 0,0162 0,02 -0,262*** -0,064 1 INDROA 0,169** * 0,209*** 0,0476 0,075 0,398*** 0,164*** -0,111* 1 Observations 280 * significant at α = 0,1 ** significant at α = 0,05 *** significant at α = 0,01
Regression
To test the hypotheses, a multivariate regression will be performed on the sample. The regression will run on a sample with all observations, and a smaller sample that contains only firms that did not hire a new CEO.
Test 1
The first test is performed on all the variables. The outcome is presented in table 2, with an R squared of 0.122.
Table 2 - Logistic regression 1 Logistic Regression 1
Variable Coefficient P-value
POSTCRISIS 0,174 0,6 NEWCEO 0,108 0,74 CRISISCEO -1,164** 0,02 LOSS_PREVYEAR -0,656 0,32 FIRMSIZE 0,32 0,12 LEVERAGE -0,004 0,8 INDROA 6,796** 0,02 SIC1000 1,559*** 0,01 SIC2000 0,7406117 0,29 SIC3000 0,6188899 0,38 SIC4000 1,225541* 0,1 SIC5000 0,354 0,55 SIC7000 0,0634 0,92 (CONSTANT) -3,797911 0,04 Adj./Pseudo R2 0,1219 Observations 280 * significant at α = 0,1 ** significant at α = 0,05 *** significant at α = 0,01
The expectation for the results was that the post-crisis years will lead to a decrease in the use of non-financial measurements. As the use of non-financial measurements is influenced by the noise in financial measurements, the decrease in noise after the crisis should lead to a decrease in the use of non-financial performance measurements.
The results show that there is a decrease in the use of non-financial performance
measurements when a CEO is hired during the crisis years.(B3 = -1.164, significant at = 0.05).
Since the relation of POSTCRISIS is not significant, the hypothesis can’t be accepted nor rejected.
The control variable firm size (B 0.3199, significant at = 0.10) is also significantly related. This means that the larger the company, the more non-financial measures is used. This could be explained by the fact that bigger companies uses more complicated bonus plans, and therefore have added more non-financial performance measures in the compensation plan. The results also show the relation of the different industries with the use of non-financial measures. The industry dummy variables that are significantly related are sic1000 (B 1,5593, significant at 0.01) and sic4000 (B 1.2255, significant at 0.1). These are the firms that are operating in the industries ‘mining and construction’ and ‘transportation and utilities’.
Test 2
The second test will be performed on the sample that only consists of firms that did not hire a new CEO during 2005 and 2012. The results can be found in table 3.
Table 3 - Logistic regression 2 Logistic Regression 2
Variable Coefficient P-value
POSTCRISIS 0,943** 0,05 LOSS_PREVYEAR 0,353 0,76 FIRMSIZE 0,602** 0,03 LEVERAGE -0,012 0,62 INDROA 4,558 0,27 SIC1000 1,612** 0,05 SIC2000 1,492 0,17 SIC3000 1,054 0,31 SIC4000 2,496** 0,02 SIC5000 0,787 0,35 SIC7000 0,510 0,54 (CONSTANT) -7,494** 0,02 Adj./Pseudo R2 0,2311 Observations 156 * significant at α = 0,1 ** significant at α = 0,05 *** significant at α = 0,01
The outcome of this test is differs from the previous test..
It is expected that, whenever there is no change in CEO, the use of non-financial measures will decrease as the noise in financial measurements decreases.
Postcrisis is significant related with the use of non-financial measures (B 0.9435, with a significance level of 0.05). This means that for firms that do not hire a new CEO, there is an increase in use of non-financial measures in the years after the crisis. This result is not as
expected in the hypothesis. During the years after the crisis, there is more use of
non-financial measures than before the crisis. Because POSTCRISIS is significant related in this test, the hypothesis can be rejected. Instead, there is evidence that the opposite effect
(increase in use of non-financial measures) occurs. An explanation to this could be that firms still consider the financial measures as noisy even though the crisis is over.
Firmsize remains significant related, while INDROA is not significant related in this test. The same industries are positively related compared to the sample that includes the change in CEO.
Conclusion
The purpose of this study is to look at the influence of the financial crisis on the use of non-financial performance measures. Data and information of American firms are used for this study from the years 2005-2006 and 2012-2013. The CEO compensation plan of the firm was used for finding evidence for the change in the use of non-financial performance
measurements for determining the CEO bonus.
The tests performed in this paper came with the following results. First of all, there is evidence that when there is a new CEO hired during the crisis years, which are 2008, 2009, and 2010, less non-financial measurements are used in the CEO compensation plan.
Secondly, for firms that did not hire a new CEO, during the post-crisis years there is an increase in the use of non-financial measurements for CEO compensation.
The results given in this paper do not provide evidence that after the crisis less non-financial performance measurements will be used. In fact, in firms without changing CEO, it even increases.
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