How does Accounting Conservatism Impact Depreciation
Expenditures?
Name: Yuchen Ren
Student number: 11668814 Thesis supervisor: Qi Yang Date: June 25, 2018
Word count: 7,900
MSc Accountancy & Control, specialization: Accountancy Faculty of Economics and Business, University of Amsterdam
Statement of Originality
This document is written by student Yuchen Ren 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 paper analyzes the impact of unconditional conservatism on firms’ depreciation measurement, that is, whether management tends to overstate annual depreciation amount in companies with high degree of unconditional conservatism, and whether life cycle stage and new investment impact this relation. Three main hypotheses are developed respectively, and methodology to the recognition of unconditional conservatism and classification of life cycle stages are used based on previous model. Few prior researches study the direct relation between conservatism and depreciation measurement, so this paper has theoretical contribution on conservatism development and also, empirical contribution on the valuation reference of management and investment decision-making of external financial information users.
Contents
1! Introduction ... 5!
2! Literature Review ... 7!
2.1! Concept Development ... 7!
2.2! Unconditional and conditional conservatism ... 7!
2.3! Economic effects of unconditional conservatism ... 9!
3! Hypothesis Development ... 11!
3.1! Link between unconditional conservatism and depreciation expenses ... 11!
3.2! The impact of life cycle stage on unconditional conservatism ... 11
3.3! The impact of new investment on the association between unconditional conservatism and depreciation expenses ... 13!
4! Research Design ... 14!
4.1! Sample selection ... 14!
4.2! Empirical design ... 14
5! Analysis of Results ... 17!
5.1! Descriptive statistics ... 17!
5.2! Depreciation expenses and unditional conservatism ... 17
5.3! Impact of life cycle stage on unconditional conservatism ... 20
5.4! Impact of investment on the association between depreciation expenses and unconditional conservatism ... 22!
6 Conclusion ... 23
1! Introduction
Accounting conservatism is an important convention of financial reporting, which can be defined as accounting policies or tendencies that result in the downward bias of accounting net asset value relative to economic net asset value (Ruch and Tylor, 2015). It is derived from the fact that conservatism is ultimately reflected in the understatement of assets and overstatement of liabilities. The Financial Accounting Standards Board (FASB) believes that conservatism biases accounting information and compromises neutrality.
Prior researchers identified two types of conservatism: conditional conservatism and unconditional conservatism. Beaver and Ryan, 2005 first define conditional conservatism as under favorable circumstances book values are not written up, but under unfavorable circumstances book values are written down, in other words, it holds asymmetric reaction on positive and negative news. On the other hand, unconditional conservatism is that the accounting process determined at the inception of assets and liabilities yield expected unrecorded goodwill, which means a consistent under-valuation of net assets, without the impact from any news event.
During the years, researchers focus more on the study of conditional conservatism than unconditional conservatism. For instance, a great amount of literature emphasizes on the relationship between conditional conservatism and investment efficiency (Juan Manuel, Beatriz, Fernando,2016), management compensation (Zwiebel and Jeffrey, 1995), financing strategies (Haw et al., 2014), etc. Since conditional conservatism could communicate information on uncertain events so that it seems more appealing to researchers and stakeholders. However, less attention has been paid on the relationship between unconditional conservatism and accounting valuation.
Accelerated depreciation method, recognition of R&D costs, advertising expenses and impairment decisions can all due to unconditional conservatism. This paper, however, chooses annual depreciation expenses as one of the aspects, study if conservative firms tend to overstate depreciation expenses through accounting estimation and judgement. However, because accounting conservatism decreases managerial incentives to make negative net present value investments (Watts, 2003; Ball and Shivakumar, 2005), it could also be the case that conservatism makes firms invest less, so that the amount of assets increases is relatively low, leading to less depreciation expenses increase. Thus, the second research question is
regardless of investment amount changing. The last question relates to a robustness test, aiming at eliminating the impact of firms’ different life-cycle stage, because according to Givoly and Hayn (2000), unconditional reporting conservatism decreases over life cycle stages.
This paper aims to study whether conservatism directly impacts of firms’ accounting measures on depreciation expenses, and fill the gap between conservatism and depreciation recognition since few research has been done in this field, and furthermore, provide more empirical evidence for previous research about how conservatism impacts on earnings. By doing so, this study contributes to the literature in two ways. Theoretically, because conditional conservatism seems to dominate the research on the effects of conservatism, this paper could provide more evidence from the perspective of unconditional conservatism, and make the concept of accounting conservatism more complete. On practical level, by examining how conservatism affect financial reporting practice, specifically, how management use depreciation measurement to influence earnings, this paper relatively characterizes the reporting regime of firms. Because conservatism is a fundamental feature of accounting, these findings may affect conclusions from studies of valuation reference. Furthermore, it helps external financial information users like investors and analysts to adjust the earnings and net assets multiples computed for conservative firms, which may influence the yield to investment strategies and investors’ decisions. Last but not the least, Ruch and Tylor (2015) conclude that unconditional conservatism has the ability to facilitate earnings management through the accumulation of reserves on the balance sheet in order for management to meet an earnings target, while conditional conservatism is unlikely to do so. By confirming whether depreciation method used in a firm is related to earning management, the conclusion can be implied to alert and prevent such managerial behavior.
The remainder of the paper is organized as follows. Section 2 includes literature review and Section 3 shows how the hypotheses are developed; Section 4 explains the sample selection and methodologies used to examine each research questions; Section 4 proposes hypotheses supported by simulation analysis and provides the results and the last section concludes, and provides implications for future research.
2! Literature review
2.1! Concept development
Since 15th century, accounting conservatism has already come into practices in the commercial partnership. And it attracted particular attention from researchers after 1995. Accountants traditionally expressed conservatism by the rule "anticipate no profits but anticipate all losses (Bliss, 1924), which means that accountants have preference on certain accounting methods that leads to lower reported values for shareholders' equity. Prior research has also examined variation in accounting methods across firms to capture variation in conservatism (Watts and Zimmerman, 1990; Christie, 1990; Lev, 1989).
Feltham and Ohlson (1995) analyse the relationship between accrual accounting and valuation of a firm's equity and goodwill. They first use firm’s market value and accounting date to record operating and financial activities. In a perfect market, there is no differences between the book value and market value of financial activity. But operating activity use accounting for accruals conventions on assets, leading to the discrepancy between a firm’s market and book values. They took into account three variables regarding operating activity: accounting conservatism, persistence of abnormal earnings and growth, then develop a linear model on multiple types of analysis, and finally conclude that accounting conservatism is the one who determine the growth.
Basu (1997) brings up another interpretation of accounting conservatism that it results in earnings reflecting ‘bad news’ more quickly than ‘good news’. Using firms’ stock returns to measure news, he finds that the contemporaneous sensitivity of earnings to negative returns is two to six times that of earnings to positive returns, and that negative earnings changes are less persistent than positive earnings changes. Heated debates arise, however, over Basu’s conclusion afterwards. Even though his measure is reckoned, by some scholars, as invalidated due to the possible causes of measurement error, the new definition and model are still widely upheld and used.
2.2! Unconditional and conditional conservatism
Previous researches started to classify different types of accounting conservatism since Basu (1997). Beaver and Ryan (2005) classify accounting conservatism into unconditional
conservatism and conditional conservatism and illustrate the differences and relation between them.
Unconditional conservatism, also called news independent or ex ante conservatism, means that aspects of the accounting process determined at the inception of assets and liabilities yield the expected unrecorded goodwill, in other words, it occurs when net assets are consistently under-recognised in terms of accounting. Examples of unconditional conservatism include the immediate expensing of the cost of internally generated intangible assets, recognition of development expenditures, and using accelerated depreciation method. Conditional conservatism, also called news dependent or ex post conservatism, on the other hand, means that book values are written down under sufficiently adverse circumstances but are not written up under favourable circumstances, or as Basu (1997) states in his paper, there are systematic differences between negative news and positive news periods in the timeliness and persistence of earnings. Examples of conditional conservatism include using lower-of-cost-or-market accounting convention for inventory, different treatment on loss and gain contingencies, and impairment accounting for long-term tangible and intangible assets (Ji 2013).
Both of unconditional conservatism and conditional conservatism lead to understating the book value of net assets, compared to their market value (Kabir and Laswad, 2014). Meanwhile, however, there are appreciable differences between them. It is important to distinguish different types of accounting conservatism and to identify their relationship with each other, because they help explain why conservatism has long been controversial in accounting field.
First of all, on income statement, unconditional conservatism is likely to have a relatively consistent impact from period to period, for example, always timely record advertising expenditures. Unlike unconditional conservatism, conditional conservatism depends on economic environment faced by firms (news), and thus it carries new information (Ball et al. 2013a), but it also means the effect of conditional conservatism on income statement is temporary, due to the fluctuation in the content and timing of economic news across periods (Chen, Folsom, Paek, & Sami, 2014). Gassen, Fülbier and Sellhorn (2006) also find that income smoothing and conditional conservatism, two attributes of earnings, are fundamentally different because increasing the importance of funding leads to increasing the
conditional conservatism and increasing the importance of the dividends leads to income smoothing. On balance sheet, although they both induce understating firms’ equity, the timing of recognition on balance sheet is different. For example, recognise research and development costs at early stage of a construction might eliminate the need to record more R&D expenses in the event of bad news about the fair value of the construction.
Furthermore, the application of unconditional conservatism and conditional conservatism affect each other. Beaver and Ryan (2005) imply that unconditional conservatism is a primary source of unrecorded goodwill, which creates ‘‘accounting slack’’ that might preempt the application of conditional conservatism. In other words, the unconditional understatement of assets limits the amount of write-downs recognized in the presence of bad news events, and therefore, reduces asymmetric timeliness in earnings, therefore, the presence of conditional conservatism might contradict the presence of unconditional conservatism. Qiang (2007) also provides empirical evidence that the two types of conservatism have a negative relation with each other in firms, and researchers therefore should trade-off between them.
Last but not the least, Ball and Shivakumar (2005) point out that conditional conservatism can improve contracting and investment efficiency through the timely recognition of losses, which would confront managers’ opportunistic behavior. On the contrary, unconditional conservatism could offset such effect and even mislead investors with distorted financial information.
There are also alternative explanations for the classification of conservatism. For example, Lawrence et al. (2013) distinguish between discretionary and non-discretionary conservatism, where non-discretionary conservatism means accounting principles are applied without bias, while discretionary conservatism results from purposeful intervention in the financial reporting process.
2.3! Economic effects of unconditional conservatism
According to the studies above, we can see that there is an optimal level of conservatism, which depends on the firm’s economic circumstances and manager’s intention. On the one hand, conservatism can enhance the prudence on accounting reports, on the other hand, there are also rising concerns that conservatism might instead jeopardize the quality of accounting information, since it has distinct effects on different users.
Ruch and Tylor (2015) identify the effects of conservatism on financial reporting into two forms, valuation and stewardship. Equity holders, more specifically, investors and analysts, use accounting reports to valuate firms. And unconditional conservatism may reduce value relevance of the accounting reports by omitting information that is useful in assessing the firm’s value (Collins, Maydew, and Weiss 1997; Lev and Zarowin, 1999). For instance, R&D expenses could provide future benefits to the firm in the form of future sales. However, the immediate recognition of R&D under conservatism ignores these future benefits by prohibiting accounting from capitalizing the expenses. However, as the only study over the direct relationship between unconditional conservatism and value relevance over time, Balachandran and Mohanram (2011) find no evidence that the decline in value relevance over time can be related to an increase in unconditional conservatism in those years.
On the perspective of stewardship, debt holders prefer to timely recognise losses while require high verifiability of gains because of asymmetric payoffs. In this case, unconditional conservatism impedes firms from record certain unverifiable incomes, which provides something akin to a ‘‘worst-case scenario’’ to lenders (Watts, 2003a). Ahmed et al. (2002) illustrate that if accounting conservatism, both conditional and unconditional, can restrict the overpaid dividends to shareholders, bondholders are willing to accept a lower interest rate, and they further conclude that conservatism is positively associated with conflict over dividend policy and negatively associated with debt cost of capital.
Penman and Zhang (2002) find evidences to support the idea that unconditional conservatism practices could facilitate real earnings management. Because reverses can be accumulated over accounting periods and once managers are required to meet certain earning target, they can be released into earnings. In this way, managers have the opportunity to exploit accounting conservatism to fulfill their own interests (Jackson and Liu, 2010).
The researches above show that unconditional conservatism has a pervasive impact among multiple financial information users, thus, indicate the significance to study the implementation of unconditional conservatism within firms.
3! Hypothesis development
3.1! Link between unconditional conservatism and depreciation expenses
Accounting depreciation is the systematic reduction of the recorded cost of a fixed asset (Kieso et al., 2007). There are some major factors for firms to consider when booking depreciation expenditures. Firstly, which depreciation method should be implied? Secondly, if it’s straight line method, the useful life and residual value should be assessed; if accumulated depreciation method is chosen, then the firm has to decide the depreciation rate. It is known for researchers that conservative firms are likely to choose accumulated depreciation method which can recognize more depreciation early in the life of a fixed asset, and defer some income tax expense recognition into a later period, so as to overvalue the costs and understate the asset amount. However, the rest of the factors haven’t been systematically studied by scholars.
Under IFRS framework, a firm may need its past experiences, professional judgement, industry practices, etc. to estimate the useful life of an asset, and the amount can be revised during the life of the asset. Same with the estimation of residual value. The residual value of an asset is determined by considering the estimated amount that an asset's owner would earn by disposing of the asset, less any disposal cost, and it should be reviewed at least once a year. Additionally, there are also multiple methods to evaluate depreciation rate. For instance, Nadiri and Prucha (2001) assess the depreciation rate of both physical and R&D capital for the US manufacturing sector. And the result is generally much different from those reported by Epsten and Denny (1980), Bischoff and Kokkelenberg (1987) or Kollintzas and Choi (1985). Altogether, firms have certain autonomy to imply conservative accounting not only on depreciation methods, but also on the depreciation amount which is subjected to managerial judgement and estimation procedures. Thus, we can predict that conservative firms tend to recognise more depreciation expenses in view of the subjectivity of accounting standards application.
3.2! The impact of life cycle theory on unconditional conservatism
There are multiple factors that have effects on the degree of unconditional conservatism, within which life cycle stage factor is considered to be highly important. Under life cycle
stages exhibit different financial characteristics and require different management skills, priorities and strategies, and hence, hold different degree of conservatism. Particularly, firms are less conservative since they expect to maximize revenue growth early in its life cycle stages, and create competitive advantages, which implies that the cross-sectional variations in unconditional conservatism is systematically impacted by its life cycle stage, because same accounting standards could have differential impact on firms in different life cycle stages. However, there is no significant evidence on the association between conditional conservatism and life cycle stages. (James, Keejae and Sang-Hyun, 2018).
As a result, this paper first examines the direct association between unconditional conservatism and depreciation expenditures, that is, regardless the life cycle stages, firms that are relatively more conservative than the other companies are likely to overstate depreciation expenditures over years. And my first hypothesis will be:
H1: Regardless the life cycle theory, firms with higher degree of unconditional conservatism tend to hold higher annual depreciation expenditure on their financial statements.
Subsequently, I use the proxy introduced by Dickinson (2011) to calculate life cycle stages, and analyze its impact on unconditional conservatism level.
Following Dickinson (2011), the life cycle theory prescribes that firms tend to maximize revenue growth early in their life cycle stages. The prediction is based on the premises that the reward for acquiring market share to create demand advantages or for building capacity to create cost advantages is the largest in a firm’s early life cycle stages but it diminishes over time. Accordingly, Dickinson believes that firms’ life cycle stages can be classified by cash flow pattern, which is, instead of revenue growth, capital expenditures, dividend payout ratio and firm ages, more consistent with life cycle theory. I divide the sample firms into five different stages of their life cycle: Introduction, Growth, Mature, Shake- out and Decline Stage, based on the cash flow from operating activities, investment activities and financial activities. Thus, hypothesis 2 will be:
H2: A firm in different life cycle stages hold different degree of unconditional conservatism, and have respectively affect depreciation expenditure amount.
3.3! The impact of investment on the association between unconditional conservatism and depreciation expenses
Watts (2003) and Ball and Shivakumar (2005) state that accounting conservatism is potentially mitigate agency problems associated with management’s investment decision-making, and thus firms with higher degree of conservative accounting have less incentives to take in negative net present value projects (NPV<0). Later Todd Kravet (2014) develops the research and finds that accounting conservatism is negatively associated with acquisition riskiness. More specifically, Juan Manuel, Beatriz and Fernando (2016) bring up further conclusion: More conservative firms invest more in setting prone to underinvestment; meanwhile, it is also associated with reduced overinvestment, even for opaque ones, for example, firms may invest less on research and development. Therefore, I expect that accounting conservatism is likely to affect firms’ investment amount and the impact could be both positive and negative.
However, this fact could undermine hypothesis 1 above, because if firms invest less, more specifically on fixed assets, the assets amount in conservative firms may be relatively affected, which brings an alternative explanation for the lower depreciation expenditure in conservative firms as in hypothesis 1: It could be the case that in conservative firms, management tend to invest less on fixed assets, and thus fewer capitalized assets are recorded. Because fixed assets amount directly determines the depreciation expenditures during the year, so the depreciation on these assets are consequently less. Hence, conservatism may not be the direct reason for larger amount of depreciation expenses. To clarify whether investment amount on fixed assets will affect the association between unconditional conservatism level and depreciation expenditures, therefore underpin hypothesis 1, I further use annual increase in non-current assets as another factor, and examine its impact on hypothesis 1, so the last hypothesis will be:
H3: Investment amount on non-current assets in a financial period will affect the association between depreciation expenditures and unconditional conservatism.
4! Research Design
4.1! Sample Selection
This paper uses archival research as the empirical approach. I obtain accounting data from the COMPUSTAT Global Fundamentals Annual files and stock price and return data from the CRSP Stock Market Indexes database for the years 2000-2017, deleting firms that are inactive on the COMPUSTAT database, financial serves companies including banks, broker or dealers, etc., since depreciation accounting rules tend to affect operating assets much more than financial assets. I further eliminate firm years with missing data for any of the variables used in estimation, and firm years with negative total assets or book value of equity. The final sample comprises 9,188 firm-year observations for 540 firms worldwide.
4.2! Empirical design
Givoly and Hayn (2000) develop four measures of accounting conservatism: (1) the level and rate of accumulation of negative non-operating accruals over time; (2) measures based on Basu's (1997) asymmetric earnings-return association during good and bad news periods; (3) measures based on the time-series properties such as skewness and variability of earnings and cash flows; and (4) the market- to-book ratio. Because the aim of this paper is to examine the relation between unconditional conservatism and depreciation, our measurement for conservatism should be based on accounting or marketing data in a certain financial year, while method (3) uses time-series data, and thus is not appropriate in this study. Similarly, as method (2) is for measuring conditional conservatism instead of unconditional conservatism, it should also be off the table. Finally, the method itself cannot be relied on depreciation expenses, which eliminates method (1). Therefore, market-to-book ratio becomes the most suitable method, in accordance with the statement of Givoly and Hayn (1995) that conservatism is ultimately reflected in the understatement of assets and overstatement of liabilities, leading to market value of equity exceeding book value of equity in the long run. Market-to-book ratio captures how market values firms’ net assets of relative to the recorded book values, and indicates this relative under- or overstatement. It is calculated as follows:
!"#$% = !'($%/#'(_+,- (1)
where !'($% is the market value of equity in year t for firm +, and #'($% is book value of equity. A ratio higher than 1 means conservative accounting, and an increase in the ratio over
period suggests an increase in the level of reporting conservatism. Therefore, the regression model for hypothesis 1 is:
.//012-345647+1,+8/-(954/:4:$% = ;<+ ;>!"#$%+ ;?@8/,682:$%+ A/30:,6B$% + C$% (2)
Controls in the equation (2) represents a vector of control variables. Specifically, I control for firm size (SIZE) measured as the log of total assets, considering the magnitude of depreciation over each firms closely related to its assets amount; capital intensity (CAPInt) measured as the log of property, plant, and equipment divided by the number of employees, capital expenditures (CAPEX), that is firms’ capital expenditures plus research and development expense, and revenue growth (Growth), since firms holds different degree as they grow (Anthony and Ramesh, 1992; Tian et al., 2009); leverage (LEV) is the scaled decile rank of firms’ debt to total assets ratio, calculated as short-term debt plus long-term debt at the end of fiscal year t-1, divided by total assets; ROA as firms’ earning generated relative to the value of its assets, in order to exclude the effect on which firms utilize conservatism to manage earnings, except for depreciation expenditure, for example, impairment analysis, R&D expenditures, etc. Additionally, I take a close look at specific industries since the level of conservatism varies across industries (INDUSTRY), for example, conservatism is particularly evident in pharmaceutical industry.
To conduct the hypothesis 2, I use the method introduced by Dickinson (2011), and divide the total sample into five life cycle stages based on the cash flow pattern classification, as shows in the Table 1, where CFO = cash flows from operating activities, CFI = cash flows from investing activities, CFF = cash flows from financing activities. Since the three types of cash flows can have either positive or negative cash flows, there could be eight possible cash flow patterns. Following Dickinson (2011), I combine these eight possible combinations into five stages as shows below, and run the regression model (2) again within each five group, to exclude the interference of life stage factor and enhance my conclusion.
Table 1 Dickinson (2011)’s life cycle stage pattern
1 2 3 4 5 6 7 8
Introduction Growth Mature Shakeout Shakeout Shakeout Decline Decline
CFO - + + - + + - -
CFI - - - - + + + +
For hypothesis 3, I use the annual growth of non-current assets (NAC%) as another independent variable to examine the new investment on non-current assets each year, and conduct regression (2) again to analyze if annual depreciation expenses and unconditional conservatism is significant related under this scenario.
Other control variables also include leverage (LEV), revenue growth (Growth). As Smith and Watt (1992) indicates, leverage controls for the investment opportunities, as well as revenue growth, which is calculated as the percentage change of revenues from the previous year.
5! Analysis of results
5.1! Descriptive statistics
Table 2 presents the descriptive statistics of our sample. Panel A includes the frequency distribution of sample firms through the years from 2000 to 2017, 510 firms each year in average and 9,188 firm-year observations in total. Panel B presents the descriptive statistics of the variables used in the analysis, where the average annual depreciation expense level is $426.5 million. The mean of MB ratio is 3.95 (>1), indicating that generally speaking, the market value of sample firms is greater than their book value. Panel C illustrates the correlation of the main variables, and those significant at the 0.4 or above level are in bold. According to the Panel C, depreciation expenses are significantly related with firm size and leverage level, which can be the very important control variables during the statistical tests.
5.2! Depreciation expenses and unconditional conservatism
Table 3 reports the output of regression (1) for each fiscal year from 2000 to 2017. As mentioned above, I use MB ratio to evaluate the degree of accounting conservatism. The estimate of the coefficient on MB ratio is overall negative over the year (mean coefficient of MB ratio = - 0.23). This evidence is consistent with the notion that when excluding the factors like firm size, leverage, etc., a firm is less conservative, that is, the lower its MB ratio is, the less depreciation expenditure it tends to recognize. However, this relation is not significant (t value <1.96).
Considering accounting methods are considerably diverse among different industries, I expect differences in the conservatism degree and depreciation amount. I further divide the sample into 12 distinct industries based on the primary SIC code, including Chemicals, Computers, Durable Manufacturers, Extractive Industries, Food, Insurance and real estate, Mining and Construction, Pharmaceuticals, Retail, Services, Textiles and Printing, Transportation. Table 4 shows the industry composition of the sample.
Table 5 reports means of key variables by industry. Firms in Pharmaceuticals, Transportation and Extractive Industries have larger non-current assets, as well as higher depreciation expenditures. Agriculture and Electric, gas and sanitary services firms hold relatively more intensive capital. And more importantly, the Chemical industry has the highest MB ratio
Table 2 Descriptive statistics
Panel A: Frequency of firms by year
Fiscal Year Frequency Fiscal Year Frequency
2000 540 2010 526 2001 525 2011 525 2002 519 2012 519 2003 514 2013 515 2004 507 2014 506 2005 544 2015 498 2006 532 2016 494 2007 519 2017 345 2008 534 Total 9,188
Panel B: Descriptive statistics
Variable Observation Mean Standard
deviation Min Max
Depreciation 9,188 426.507 1530.316 0.008 25847.000 MB ratio 9,188 3.950 72.618 -1351.686 5603.074 SIZE 9,188 3.102 0.981 -0.073 5.647 CAPInt 9,187 2.118 0.617 -0.416 5.216 CAPEX 9,184 -1.244 0.469 -4.109 1.114 LEV 9,188 0.208 0.451 0.000 39.593 Growth 9,156 0.088 1.478 -1.000 136.679 ROA 9,188 1.141 0.824 0.000 20.778 NCA 9,188 6719.668 22222.390 -42845.150 366680.000
Panel C: Pearson and Spearman correlation coefficients
Dep. MB SIZE CAPInt CAPEX LEV Growth ROA NCA
Dep. 0.3022 0.9688 0.3508 0.1229 0.4048 0.0049 -0.2204 0.9596 MB 0.0006 0.3168 0.0421 0.145 0.0645 0.1761 -0.046 0.3024 SIZE 0.4514 0.014 0.2822 0.0201 0.3705 0.0178 -0.2321 0.9741 CAPInt 0.2768 -0.002 0.2559 0.3223 0.2524 -0.01 -0.5071 0.3338 CAPEX 0.1046 0.0092 0.0445 0.3078 -0.027 0.0608 -0.1345 0.0383 LEV 0.0455 0.0364 0.2652 0.2309 0.0174 -0.024 -0.2143 0.4088 Growth -0.0059 0.0002 -0.0153 0.0212 0.0115 -0.0191 0.019 0.0104 ROA -0.1154 0.0009 -0.1799 -0.421 -0.1201 -0.1667 -0.0168 -0.2784 NCA 0.9457 0.0016 0.4971 0.2574 0.0645 0.05 -0.0047 -0.1356
Table 3 Association of depreciation expenses and accounting conservatism Fiscal
Year obs
MB
ratio SIZE CAPInt CAPEX LEV Growth ROA
Adj R- squared 2000 532 1.07 392.19 148.88 111.42 -432.27 47.02 -22.45 0.217 (-0.39) (11.17) (2.14) (1.19) (-2.20) (0.73) (-0.61) 2001 523 0.46 422.09 205.17 178.33 -454.48 179.98 4.09 0.223 (0.17) (10.98) (2.66) (1.70) (-2.06) (1.25) (0.12) 2002 517 0.76 412.99 320.63 86.27 -529.95 -25.53 35.59 0.227 (0.22) (10.76) (4.13) (0.96) (-2.50) (-0.21) (0.72) 2003 512 0.05 454.61 343.85 79.01 -785.18 -93.03 38.75 0.247 (0.35) (11.29) (4.29) (0.85) (-3.19) (-0.52) (0.68) 2004 505 -8.09 480.02 349.12 71.70 -853.86 -177.55 36.61 0.265 (-0.88) (11.37) (4.28) (0.68) (-3.16) (-0.91) (0.64) 2005 542 -1.70 488.35 317.27 90.84 -788.80 -40.17 28.69 0.264 (-0.68) (11.89) (4.02) (0.88) (-3.02) (-0.28) (0.50) 2006 530 10.41 563.16 364.52 65.45 -1043.12 -135.17 25.45 0.258 (-1.06) (11.69) (3.99) (0.55) (-3.5) (-0.61) (0.38) 2007 518 -8.27 667.34 412.32 75.45 -1175.58 672.69 48.51 0.224 (-0.71) (10.52) (3.63) (0.52) (-2.8) (2.57) (0.55) 2008 531 -4.17 686.58 413.48 102.05 -943.54 -391.20 52.06 0.226 (-0.58) (10.99) (3.86) (0.69) (-2.62) (-1.52) (0.94) 2009 525 -2.52 718.81 434.21 163.36 -1093.99 -0.50 104.03 0.232 (-0.23) (11.06) (3.74) (1.11) (-2.83) (-0.05) (1.15) 2010 523 10.72 793.06 484.32 181.69 -1398.20 -33.45 114.45 0.248 (-0.92) (11.46) (4.07) (1.22) (-3.23) (-0.55) (1.19) 2011 522 -4.00 840.72 502.26 207.03 -1632.81 -76.77 111.64 0.265 (-0.55) (12.00) (4.04) (1.20) (-3.88) (-0.39) (1.2) 2012 517 1.25 868.89 574.31 261.29 -1770.60 -292.05 98.17 0.288 (-0.66) (12.33) (4.69) (1.6) (-4.28) (-1.35) (1.03) 2013 512 -16.54 906.92 495.25 406.70 -1618.91 -190.49 59.56 0.287 (-1.2) (11.93) (3.11) (1.49) (-3.89) (-1.17) (0.58) 2014 506 -0.18 894.25 590.52 285.51 -1124.13 -103.61 91.67 0.283 (-0.15) (11.43) (4.61) (1.50) (-2.8) (-0.28) (0.99) 2015 498 0.27 944.89 671.19 357.69 -696.39 -155.64 96.59 0.266 (0.23) (10.82) (4.35) (1.63) (-2.54) (-0.33) (0.77) 2016 494 -0.28 1004.46 773.93 196.24 -1112.40 249.49 190.27 0.248 (-0.51) (10.43) (4.72) (0.89) (-2.74) (0.55) (1.28) 2017 345 -3.30 1440.32 854.15 95.45 -1895.61 -117.90 360.71 0.297 (-0.9) (9.94) (3.98) (0.26) (-2.87) (-0.24) (1.66) Mean 508 -0.23 702.70 423.84 137.39 -1068.55 -84.90 55.81 0.253 (-0.47) (11.23) (3.91) (1.05) (-3.01) (-0.18) (0.77)
Table 4. Identify of industry sub-samples
Industry Primary SIC codes
Firm-years % of obs
Agriculture 1-999 18 0.2
Chemicals 2800-2824, 2840-2899 487 5.3
Computers 7370-7379, 3570-3579, 3670-3679 569 6.19
Durable Manufacturers 3000-3999, except 3570-3579,
3670-3679 2921 31.79
Electric, gas and sanitary
services 6000-6499 160 1.74
Extractive Industries 2900-2999, 1300-1399 123 1.34
Food 2000-2111 436 4.75
Insurance and real estate 6500-6999 213 2.32
Mining and Construction 1000-1999, except 1300-1399 788 8.58
Other 9000 and above 58 0.63
Pharmaceuticals 2830-2836 293 3.19
Retail 5000-5999 1016 11.06
Services 7000-7370, 7379-8999 876 9.53
Textiles and Printing 2200-2790 696 7.58
Transportation 4000-4899 534 5.81
(8.33) followed by the Durable Manufacturers (5.14), Food industry (4.96) and Pharmaceuticals (4.03), which is consistent with previous prediction. I further conduct the regression (1) at industry level and Table 6 summarize the coefficients and t value of each independent variables.
We find that in the industry of Agriculture, Electric, gas and sanitary services, Extractive Industries and Pharmaceuticals, the coefficients of MB ratio are significantly negative (t value -2.1, -3.32, -3.22 and -1.67 respectively), which indicates that conservatism degree is significantly associated with firms’ annual depreciation expenditures. Additionally, the Adjusted R-squared increases from 25.3% to 52.9%.
5.3! Impact of life cycle stages on unconditional conservatism
Based on Dickinson (2011)’s model, I classify the sample into 5 life cycle stages by cash flow pattern, that is whether the cash flow from investing activities, operating activities and financing activities is positive or negative. Nonetheless, the amounts of firm-year observations are relatively too small in Agriculture and Electric, gas and sanitary services and Other industries, to provide a reasonable outcome. Hereby I exclude firms in these 3 fields and in Table 7 listed the mean of MB ratio sorted by different life cycle stages.
I observe a trend that the MB ratio stays relatively low in Introduction and Growth stages while hits the peak on Mature stage and declines afterwards. This pattern is more prominent in Chemicals, Durable Manufacturers and Pharmaceuticals industries, which indicates that the conservatism degree is affected greater by life cycle stages in these fields.
Table 8 summarize the coefficient and t value of MB ratio. I observe that after sorted by industry and life cycle stage, the association between depreciation expenses and MB ratio is more pronounced in certain sub-samples. For instance, when firms in Computers industry reach Mature stage, their coefficients is significantly related to MB ratio (t value =4.18), same in Pharmaceuticals (t value = -2.33) and Textiles and Printing (t value= 3.09) industries. As for Durable Manufacturers, this significant relation is more pervasive as in all three stages: Growth, Mature and Shake-out, during which the t value is 4.05, 3.19 and 2.42 respectively. However, considering the mean of coefficient, in none of the life cycle stages it is significant.
Table 5. Mean of key variables by industry
Industry Dep. MBratio SIZE CAPInt CAPEX LEV Growth ROA NCA Agriculture 8.79 2.00 2.38 3.04 -1.27 0.32 0.10 0.37 -415.96 Chemicals 323.25 8.33 3.35 2.37 -1.21 0.27 0.05 1.12 6978.42 Computers 439.93 2.13 2.77 1.99 -1.07 0.13 0.06 1.02 4111.10 Durable Manufacturers 152.91 4.96 2.90 1.97 -1.22 0.17 0.06 1.07 2989.95 Electric, gas and sanitary services 117.52 2.34 2.80 3.18 -1.18 0.25 0.14 0.32 4301.12 Extractive Industries 3635.36 2.30 3.74 2.93 -1.11 0.12 0.11 1.32 50637.57 Food 317.56 5.14 3.57 2.22 -1.39 0.26 0.06 1.15 8806.27 Insurance and real estate 79.71 2.99 2.76 2.43 -1.58 0.19 0.13 0.60 3010.89 Mining and Construction 668.79 2.15 3.30 2.85 -1.00 0.24 0.17 0.79 7485.37 Pharmaceuticals 1023.61 4.03 3.21 2.26 -0.85 0.35 0.62 0.65 17649.93 Retail 278.78 3.57 3.21 1.78 -1.39 0.22 0.06 2.12 4245.52 Services 226.47 2.95 2.96 1.58 -1.41 0.17 0.06 1.17 3502.28 Textiles and Printing 157.46 3.75 2.99 2.01 -1.42 0.23 0.03 1.33 2235.71 Transportation 1886.31 2.18 3.88 2.62 -1.16 0.31 0.07 0.75 28935.62 Other 299.29 1.98 3.14 2.04 -1.22 0.12 0.03 1.14 7240.94
5.4! Impact of investment on the association between depreciation and unconditional conservatism
As discussed above, I predict that firms’ investment decision on fixed assets can be affected by their unconditional conservatism level and therefore, impact annual depreciation expenses. Thus, I add an independent variable, that is, annual growth rate of non-current assets to regression (2), and test whether it make any difference on the relation between depreciation expenditures and unconditional conservatism. The results are displayed in the Table 9.
I observe that the estimate of coefficient is significantly related in Agriculture, Electric, Gas and Sanitary Services and transportation industries, which is more pronounced than in previous tests. Moreover, the mean of coefficient is negative (-5.22), which is consistent with the result of hypothesis 1 testing. However, this time the t value (3.19) indicates that the relation is significant.
Additionally, there is a significant positive coefficients of firm size (t value >1.96, p value <0.05), which can be explained by the notion that larger firms tend to invest more over years on fixed assets and expend their scales. Overall, the outcome is consistent with hypothesis 3 that the investment decisions on fixed assets over fiscal years impact the relation between annual depreciation expenditures and unconditional conservatism. And when examine this relation, it’s indispensable to include investment factor.
6! Conclusion
From the perspective of unconditional conservatism, this paper analyzes its relations with depreciation expenditure amount. Conservatism degree is influenced by multiple factors and it is imperative to consider those have great impact. Based on the empirical analysis, there is no evidence that the amount of depreciation expenditures is significantly associated with firms’ unconditional conservatism level. However, when we distribute our samples into different industries, the relation is substantial among certain industries, for instance Electric, gas and sanitary services, Pharmaceuticals, etc. Coherent with life cycle stages, a firm holds different degree of unconditional conservatism during each stage. In general, it follows the pattern that firms tend to be less conservative during the beginning and growth phase, then the degree upsurge when firms reach mature phase and decline afterwards. Sorting samples by 5 life stages, I find that the relation between depreciation and conservatism also becomes prominent when firms are at the mature stages. Investment level on fixed assets is another critical aspect when examine the relation. Similarly, when control the new investment on fixed assets, I conclude that more conservative firms record larger amount of annual depreciation amount. In conclusion, in firms with higher degree of unconditional conservatism, management are likely to use accounting rules to overstate depreciation expenses so that the overall assets amounts are relatively less. Finally, life cycle stage and investment decision-making are the two main factors that impact this relation.
There are, however, still limits of the study. First, because the implementation of accounting rule on depreciation depends on professional judgement and estimations to a great extent, it is difficult to distinct how unconditional conservatism affect specific factors, for example, residual value and useful year. Second, conservatism is a comprehensive concept and it can be implied in various ways and perspectives. So, the control variables I use in this paper may not cover all the important factors that have impact on the relation between conservatism and depreciation. However, the limits provide a direction for further research.
Table 6. Conservatism and Industry: coefficient and t value of annual OLS regressions. Industry
MBratio SIZE CAPInt CAPEX LEV Growth ROA NCA squared Adj
R-Agriculture -1.13 22.50 1.37 1.79 1.87 -0.51 4.77 -46.68 0.94 (-2.1) (8.29) (0.29) (2.38) (0.63) (-0.63) (1.96) (-4.09) Chemicals -0.04 509.97 145.69 -86.03 -97.47 220.81 -121.02 -1683.35 0.45 (-0.31) (16.93) (2.21) (-1.22) (-0.65) (1.52) (-2.02) (-6.43) Computers 2.36 766.92 738.93 73.81 -1380.58 -94.34 581.74 -3490.07 0.43 (0.21) (15.18) (5.41) (0.74) (-5.03) (-0.55) (5.85) (-9.07) Durable Manufacturers 0.03 240.28 203.48 27.00 -138.62 1.59 33.22 -922.97 0.24 (0.41) (25.86) (6.54) (1.32) (-2.47) (0.05) (1.78) (-12.41)
Electric, gas and
sanitary services -102.32 491.75 -77.10 -180.45 -597.84 101.66 431.86 -985.66 0.51 (-3.32) (7.85) (-1.22) (-3.39) (-1.82) (2.29) (3.17) (-4.82) Extractive Industries -1024.86 3730.71 -359.38 538.15 -11988.49 -952.94 -1784.40 -2396.91 0.66 (-3.22) (8.62) (-0.48) (0.5) (-2.35) (-0.67) (-2.26) (-0.76) Food -0.25 521.35 -576.55 121.95 -211.87 -53.28 40.89 -76.87 0.53 (-0.2) (20.23) (-7.51) (2.51) (-2.5) (-0.97) (1.06) (-0.4)
Insurance and real
estate 0.57 121.86 -0.34 2.92 128.39 4.00 -25.35 -261.54 0.64 (0.3) (17.09) (-0.04) (0.36) (3.72) (0.52) (-1.5) (-5.7) Mining and Construction -0.57 885.80 670.20 -62.16 -288.40 -56.97 395.72 -4461.51 0.45 (-0.1) (19.9) (8.98) (-0.66) (-1.86) (-1.37) (4.53) (-14.24) Pharmaceuticals -10.23 759.45 126.63 -430.70 -1597.29 -7.37 -695.56 -1305.31 0.47 (-1.67) (11.52) (0.4) (-1.63) (-3.91) (-0.77) (-3.36) (-1.73) Retail 0.08 328.61 127.83 89.14 143.57 -10.02 -2.48 -904.88 0.48 (0.33) (26.18) (3.33) (4.19) (2.15) (-0.19) (-0.34) (-10.6) Services 1.94 370.47 157.66 256.93 59.88 32.23 140.89 -940.74 0.29 (1.19) (15.94) 3.75 (6.08) (0.49) (0.42) (3.94) (-6.16)
Table 6. Extended Industry
MBratio SIZE CAPInt CAPEX LEV Growth ROA NCA squared Adj
R-Textiles and Printing 0.45 345.91 126.33 -88.35 -175.26 -37.13 114.07 -1369.29 0.52 (1.06) (21.13) 4.54 (-4.39) (-3.32) (-0.73) (6.46) (-14.46) Transportation -68.24 3370.04 1504.32 91.52 633.08 1342.18 2011.87 -16656.40 0.41 (-1.21) (17.49) 3.29 (0.26) (0.76) (1.73) (5.22) (-8.95) Other 122.42 156.07 -13.29 150.89 732.22 -37.29 -190.14 -93.20 0.93 (6.51) (6.8) -0.13 (2.93) (3.88) (-0.62) (-4.52) (-0.41)
Table 7. Descriptive statistics by life cycle stages
Mean of MB ratio Introduction Growth Mature Shake-out Decline
Chemicals 3.055 2.286 11.507 -1.026 3.377 Computers 1.558 2.084 2.636 1.278 2.030 Durable Manufacturers 2.123 2.660 3.309 2.347 57.182 Extractive Industries 0.319 1.735 2.888 2.542 1.164 Food 1.064 2.563 5.886 5.023 1.010
Insurance and real
estate 2.730 2.704 3.757 3.037 -0.091 Mining and Construction 1.746 1.880 1.784 2.312 2.033 Pharmaceuticals 3.884 4.544 4.542 6.457 -2.766 Retail 1.573 2.278 4.399 2.005 0.625 Services 3.319 3.170 3.412 2.549 1.545
Textiles and Printing 0.988 2.103 4.698 1.816 0.921
Transportation 0.662 1.607 2.487 1.035 2.318
Mean 1.918 2.468 4.275 2.448 5.779
Table 8. Conservatism and life stage: coefficient and t value of annual OLS regressions.
Industries Introduction Growth Mature Shake-out Decline
Chemicals -0.41 3.16 0.01 1.66 4.78 (-0.11) (0.44) (0.05) (0.22) (1.5) Computers 2.21 -0.78 85.35 0.11 2.08 (0.33) (-0.06) (4.18) (0.05) (0.52) Durable Manufacturers -1.48 15.20 1.92 11.13 0.00 (-0.27) (4.05) (3.19) (2.42) (0.03) Extractive Industries -25.43 -1.20 -17.64 -93.96 - (-0.58) (-0.06) (-0.73) (-0.58) - Food 422.97 7.06 1.31 4.96 111.57 (0.99) (1.07) (0.65) (1.45) -
Insurance and real
estate -1.12 -4.74 -2.33 -6.68 7.64 (-0.94) (-0.48) (-0.6) (-0.71) (0.93) Mining and Construction 1.53 -9.53 -46.54 -12.21 -1.71 (0.44) (-0.48) (-1.86) (-0.22) (-0.65) Pharmaceuticals -0.01 -10.67 -127.33 -18.74 -0.01 (-0.24) (-0.37) (-2.33) (-0.75) (-1.67) Retail -25.51 11.89 0.30 -5.95 -12.58 (-2.03) (1.74) (0.81) (-1.07) (-0.97) Services 5.60 14.41 0.74 0.12 0.88 (1.99) (1.2) (0.67) (0.23) (0.26)
Textiles and Printing -84.17 1.42 1.91 5.70 -58.08
(-1.58) (0.11) (3.09) (0.3) (-1.29)
Transportation -266.59 229.84 52.72 64.28 77.11
(-1.07) (1.15) (0.66) (0.37) (0.89)
Table 9. Conservatism and new investment: coefficient and t value of annual OLS regressions.
MBratio SIZE CAPInt CAPEX LEV Growth ROA NCA% _cons squared Adj
R-Agriculture -1.80 22.72 -2.69 2.15 2.56 -0.44 4.65 0.02 -33.19 0.95 (-3.05) (9.44) (-0.58) (3.11) (0.97) (-0.6) (2.16) (1.93) (-2.7) Chemicals -0.04 524.59 158.26 -93.26 -60.14 254.24 -139.82 -10.93 -1764.11 0.47 (-0.34) (17.36) (2.42) (-1.33) (-0.4) (1.76) (-2.33) (-3.22) (-6.76) Computers 11.30 733.84 585.00 302.90 -1147.80 -100.84 505.86 -1.01 -2818.60 0.42 (1.93) (19.64) (6.11) (3.88) (-4.97) (-0.69) (6.75) (-1.92) (-10.41) Durable Manufacturers 0.03 240.97 209.12 28.03 -137.58 0.60 32.71 -0.02 -934.59 0.24 (0.4) (25.77) (6.64) (1.36) (-2.43) (0.02) (1.74) (-0.9) (-12.44) Electric, Gas and Sanitary Services -128.06 512.60 -59.11 -186.32 -534.65 120.63 548.07 -3.22 -1111.02 0.54 (-4.1) (8.28) (-0.92) (-3.59) (-1.65) (2.77) (3.96) (-1.95) (-5.2) Extractive Industries 1.74 1836.89 1006.98 -381.84 -1067.57 -733.30 685.97 -16.72 -8611.02 0.44 (0.14) (17.23) (5.81) (-1.4) (-2.72) (-2.49) (3.07) (-2.32) (-11.76) Food -0.26 519.07 -570.49 123.66 -211.70 -56.38 38.94 -9.50 -79.13 0.52 (-0.22) (19.98) (-7.38) (2.55) (-2.51) (-1.02) (1.01) (-0.92) (-0.41) Insurance and Real Estate 0.81 125.31 2.55 3.47 137.68 3.61 -20.30 -0.10 -283.69 0.63 (0.41) (16.58) (0.3) (0.41) (3.81) (0.46) (-1.18) (-0.74) (-5.86) Mining and Construction -13.14 241.68 150.77 58.62 29.47 -10.83 33.62 -0.33 -868.86 0.56 (-1.35) (15.18) (5.02) (2.13) (0.44) (-1.41) (1.34) (-1.37) (-7.6) Other 121.56 156.46 -55.57 153.42 699.17 -25.40 -193.32 0.15 6.03 0.93 (6.41) (6.78) (-0.46) (2.96) (3.57) (-0.4) (-4.54) (0.67) (0.02) Pharmaceuticals -11.01 766.22 154.40 -421.04 -1564.81 31.22 -679.43 -0.57 -1403.78 0.47 (-1.64) (11.23) (0.46) (-1.57) (-3.74) (0.24) (-3.13) (-0.36) (-1.72)
Table 9. Extended
MBratio SIZE CAPInt CAPEX LEV Growth ROA NCA% _cons squared Adj
R-Retail 0.08 327.96 125.02 89.65 149.02 -19.57 -2.30 -0.81 -898.64 0.48 (-1.64) (11.23) (0.46) (-1.57) (-3.74) (0.24) (-3.13) (-0.36) (-1.72) Services 0.19 131.90 51.77 99.84 343.33 -0.59 47.37 -0.21 -315.98 0.40 (0.33) (25.96) (3.25) (4.21) (2.23) (-0.36) (-0.31) (-0.78) (-10.51) Textiles and Printing 0.44 349.56 133.26 -91.28 -187.22 -31.85 117.07 -0.29 -1399.92 0.52 (1.03) (21.16) (4.74) (-4.5) (-3.5) (-0.62) (6.51) (-0.26) (-14.53) Transportation -65.40 3413.03 1524.44 74.64 655.40 1383.29 1991.56 -30.22 -16886.50 0.42 (47.52) (3795.76) (2432.48) (784.30) (2317.41) (2918.31) (2765.04) (18.34) (-13171.81)
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