4.2 Future survivorship

For future survivorship, Table 4 shows that the R&D variable plays a significant role in a firm's 1-year outlook over the three crises years with negative coefficients of 88.16, 95.25, and 64 across 2008–2010. This reveals key points about the practice of R&D expenditure in the technology sector and why firms who practice higher levels tend to experience positive future returns and a higher likelihood of survivorship.

Furthermore, our findings suggest that firms with higher MktCap tend to survive and are more likely to outperform in the longer-term. With negative coefficients ranging from 2.17 and 0.48 in 2008, and 0.86 and 0.91 in 2010, the explanatory power for future failure is in line with the argument that undercapitalisation is a core reason to every technology business failure evaluated [20]. The R&D is significantly negative which highlights the importance of R&D expenditure in the technology sector as an investment rather than an asset. Support for this expenditure figure in providing a 'truer measure of a company's value because this spending often turns out to be money in an investor's pocket in the future' is also advocated in reference to [21]. This implies that expenditure in the technology industry leads to improved efficiency, increased sales, and ultimately increasing company value.

The level of discretionary accruals (MJDA) practiced by firms is also a good predictor of future failure in the medium- to long-term in 2008 and 2010. In predicting future failure in Table 4, the coefficients suggest that higher levels of discretionary accruals translate to greater likelihood of failure with positive coefficients of 0.18 in 2008; 0.36 and 0.27 respectively in 2010. Importantly, this conforms closely with our expectation that practising earnings management introduces

3m

68

3m

6m

1y 3y

5y EP

BM

PS

MktCap

Salesg EBITDA

Failed\_6m

Failed\_1y

Failed\_3y

Failed\_5y

The table shows the correlation matrix of our data set we used. It uses a Pearson correlation calculation.

\*Significance

\*\*Significance

\*\*\*Significance

Table 3. Correlation

 Table

 at 1% level.

 at 5% level.

 at 10% level.

 -0.04

 -0.03

 -0.12

\*\*\*



\*\*\*


0.07\*\*



0.04

 -0.01

 0.17\*\*\*

\*\*\*

 -0.05

 -0.08

\*\*




\*\*\*


0.01

 -0.09

 -0.12\*\*\*


 0.01

 0.24\*\*\*

0.49\*\*\* 0.34\*\*\*

0.71\*\*\*

1\*\*\*

1\*\*\*

\*\*\*

\*\*\*

 0

 -0.12

\*\*\*





 -0.04

 -0.04

 -0.02

 -0.04

 0.03

 0.51

\*\*\*

1\*\*\*

\*\*\*

\*\*\*

\*\*\*

 0.05

 -0.28

\*\*\*





 -0.02

 0.01

 -0.02

 -0.1

\*\*\*

0.06\*

1\*\*\*

\*\*

\*\*\*

\*\*\*

 -0.04

 -0.05

 -0.04

 -0.02

 0

 -0.01

 0

 -0.04

 -0.06\*

0.01

 1\*\*\*

Accounting and Finance - New Perspectives on Banking, Financial Statements and Reporting

0.02

 0.01

 -0.03

 -0.02

 -0.05

 0.06\*


 -0.03

 -0.09\*\*\*

1\*\*\*

 0.05

 -0.14

\*\*\*




 -0.19

\*\*\*


0.48

\*\*\* 1\*\*\*

\*\*\*

\*\*

\*\*\*

 0.02

 -0.15

\*\*\*






\*\*\* 1\*\*\*

\*\*\*

\*\*

\*\*\*

\*\*\*

 -0.09

\*\*\*

0.29

0.28

0.18

0.11

0.42

\*\*\*

1\*\*\*

\*\*\*

\*\*\*

\*\*\*

\*\*\*

 -0.08

\*\*

0.19

0.23

0.15

0.13

\*\*\*

1\*\*\*

\*\*\*

\*\*\*

\*\*\*

0.03

 0.26

\*\*\*

0.3

0.62

\*\*\*

1\*\*\*

\*\*\*

 0.14

\*\*\*

0.42

0.49

\*\*\*

1\*\*\*

\*\*\*

0.21

0.67

\*\*\*

1\*\*\*

\*\*\*

 0.3

\*\*\*

1\*\*\*

 1

\*\*\*

 6m

 1y

 3y

 5y

 EP

 BM

 PS

 MktCap

 Salesg

EBITDA

 Failed\_6m

 Failed\_1y

 Failed\_3y

 Failed\_5y


The table shows the valuation and accounting variables' effect on the technology firms' returns from 2008 to 2010. The dependent variables are 3 months (3m), 6 months (6m), 1 year (1y), and 3 years (3y) returns of the technology firms. Then we use the earnings to price ratio (EP), book to market ratio (BM), price to sales ratio (PS), market capitalization (MktCap), EBITDA, sales growth (Salesg), modified Jones for discretionary accruals (MJDA), and research and development (R&D) as our independent variables. The values in parentheses are the t-values to the corresponding coefficients.

\* Significance at 10% level.

\*\*Significance at 5% level.

\*\*\*Significance at 1% level.

#### Table 4.

Multivariate analysis of periodic returns of NASDAQ technology firms—using modified Jones model for discretionary accruals (MJDA).

a double-edged sword. On one hand, firms practising greater degrees of earnings management tend to enjoy greater returns up to a certain point as seen in our analysis on future returns, however at the same time high levels of discretionary accruals damages their earnings quality and heightens risk of potential failure.

#### 4.3 Ethical behaviour of the firms

Furthermore, the earnings managements can be related with the opportunistic behaviour of the firm. We investigate this issue by analysing the effect of ethical behaviour of the firms using ETHICS variable on their future returns and future survivorship. Since the ETHICS is an annual value identical within a year while different across the years, we include this in our overall sample including all periods Model : Failed firmt ¼ a þ b1EP þ b2BM þ b3PS þ

71

b4MktCap þ

> 2008

> > 1y

> > > Const

EP BM

PS MktCap EBITDA

Salesg MJDA

R&D

3m 6m

1y 3y

χ<sup>2</sup>

Pseudo R2

N

The table shows the valuation and accounting variables' effect on the technology firms' returns from 2008 to 2010. The dependent variables are dummy variables indicating 1 if the technology firm fails in 1 year (1y), and 3 years (3y), and 5 year (5y) and 0 otherwise. Then we use the earnings to price ratio (EP), book to market ratio (BM), price to sales ratio (PS), market capitalization (MktCap), EBITDA, sales growth (Salesg), modified Jones for discretionary accruals (MJDA), and research and

development (R&D) as our independent variables. The values in parentheses are the t-values to the corresponding coefficients.

\*Significance at 10% level.

\*\*Significance at 5% level.

\*\*\*Significance at 1% level.

Table 5. Logistic analysis of failed NASDAQ firms using modified Jones model for

discretionary

 accruals (MJDA).

0.57 350

0.20 350

0.63

241

241

241

275

275

275

0.26

0.29

0.49

0.21

0.24

38.78\*\*\*

78.62\*\*\*

60.26\*\*\*

52.54\*\*\*

77.59\*\*\*

57.14\*\*\*

49.95\*\*\*

78.30\*\*\*

0 (�0.27)

0.05 (1.57)

�0.01 (�0.78)

0 (1.35)

0 (0.28)

�0.01

\*\*\* (�5.85)

0.02 (0.68) �0.04\*\* (�2.02)

�88.16

\*\*\* (�3.04)

0.08 (1.44) �4.3\* (�1.85)

0.18\* (1.85)

�0.01 (�0.58)

0.15 (0.78) 0.03 (1.14)

0.4 (0.18)

�1.43 (�1.23) �0.06 (�0.32) �95.25\*\*\* (�3.09)

0.51 (0.99) 0.14 (1.38) �3.4 (�0.84)

0.02\* (1.92)

0.01 (1.15) �0.03\*\*\* (�4.2)

0 (�0.35) �0.02\*\*\* (�5.61)

0 (0.33)

�0.01 (�0.95)

0.01 (0.65) �0.03\*\*\* (�4.52)

�2.49 (�0.78)

0.03\*\*\* (2.72)

0.03 (1.51)

0 (�0.45)

0 (0.29) 0 (0.45)

0 (0) �0.02\*\*\* (�5.26)

�0.04 (�0.45)

0.19 (0.97) �64\*\*\* (�3.92)

�2.4 (�0.91)

�0.01 (0)

The Roles of Accounting Valuations and Earnings Management in the Survivorship of Technology…

0.01 (0.02)

�1.06 (�0.65)

�0.05 (�0.1) 0.36\*\*\* (2.78)

�0.82 (�1.63)

0.27\* (1.67)

�1.66 (�1.32)

0.4 (0.78) �2.17\* (�1.81)

�0.21 (�1.18) �0.48\* (�1.89)

0.19 (1.09)

�1.17 (�0.84)

�0.28 (�0.65)

�0.77 (�0.84) �0.05 (�0.52)

�0.27 (�1.35)

�0.53 (�1.38) �0.01 (�0.26)

�0.01 (�0.4)

�0.09 (�0.29)

�0.04 (�0.31)

�0.01 (�0.36)

�0.43 (�1.3)

�0.02 (�0.03)

0.18 (0.31)

0.47 (0.85)

0.03 (0.27)

�0.34 (�1.29)

�0.06 (�0.53) �0.86\*\* (�2.29)

�1.14 (�0.74)

�0.36 (�0.37)

�0.45 (�0.58)

DOI: http://dx.doi.org/10.5772/intechopen.85395

0.01 (0.12) �0.91\*\*\* (�3.07)

�16.07 (�1.01)

5.54\* (1.66)

5y 0.77 (1.1) �5.86\*\* (�2.37)

3.29 (0.96)

�7.98 (�0.56)

1.24 (0.91) �13.27\* (�1.73)

�0.34 (�0.3)

�4.81 (�1.07)

�4.52 (�0.47)

1.12 (0.46)

1.35 (0.94) �12.41\*\* (�2.08)

1.77 (1.57)

0.41 (0.1)

1y

3y

5y

1y

3y

5y

b5EBITDA þ b6Salesg þ b MJDA 7

þ b8R&D þ b91y… þ b11 5<sup>y</sup> Years

2009

2010


The Roles of Accounting Valuations and Earnings Management in the Survivorship of Technology… DOI: http://dx.doi.org/10.5772/intechopen.85395

> Table 5.

\*\*Significance at 5% level.

\*\*\*Significance at 1% level.

Logistic analysis of failed NASDAQ firms using modified Jones model for discretionary accruals (MJDA).

a double-edged sword. On one hand, firms practising greater degrees of earnings management tend to enjoy greater returns up to a certain point as seen in our analysis on future returns, however at the same time high levels of discretionary accruals damages their earnings quality and heightens risk of potential failure.

Multivariate analysis of periodic returns of NASDAQ technology firms—using modified Jones model for

MODEL : ratþ<sup>p</sup> ¼ a þ b1EP þ b2BM þ b3PS þ b4MktCap þ b5EBITDA þ b6Salesg þ b7MJDA þ b8R&D

Accounting and Finance - New Perspectives on Banking, Financial Statements and Reporting

22.78 (0.51)

220.46\* (1.95)

23.41\*\* (2.18)

19.93\*\* (2.35)

�5.51 (�0.38)

�2.6 (�1.35)

�0.1 (�0.01)

> 4.25\*\* (2.34)

335.09\*\* (2.37)

F-test 2.55\*\*\* 4.81\*\*\* 6.27\*\*\* 3.46\*\*\* 2.47\*\* 3.80\*\*\* 1.36 1.16 1.96\*

N 350 350 350 350 241 241 275 275 275 The table shows the valuation and accounting variables' effect on the technology firms' returns from 2008 to 2010. The dependent variables are 3 months (3m), 6 months (6m), 1 year (1y), and 3 years (3y) returns of the technology firms. Then we use the earnings to price ratio (EP), book to market ratio (BM), price to sales ratio (PS), market capitalization (MktCap), EBITDA, sales growth (Salesg), modified Jones for discretionary accruals (MJDA), and research and development (R&D) as our independent variables. The values in parentheses are the t-values to the

Years 2008 2009 2010

3m 6m 1y 3y 3m 1y 3m 1y 5y

9.43 (1.56)

�28.34 (�1.26)

6.37\* (1.89)

0.42 (0.69)

�2.84\* (�1.69)

�0.07 (�0.46)

> 1.2 (0.4)

�0.25 (�0.52)

56.41\*\*\* (3.15)

0.03 0.08 0.11 0.05 0.05 0.09 0.01 0.00 0.03

2.61 (0.13)

�117.87 (�1.52)

> 22.56\* (1.93)

5.15\*\* (2.46)

�5.57 (�0.96)

�0.41 (�0.8)

0.92 (0.09)

0.9 (0.55)

286.02\*\*\* (4.61)

14.33\*\* (2.24)

�44.66 (�1.43)

�0.61 (�0.13)

�0.54 (�1.12)

�0.8 (�0.47)

�0.04 (�0.75)

6.23\* (1.66)

�1.08 (�1.27)

4.55 (0.29)

�1.6 (�0.13)

14.96 (0.24)

�5.36 (�0.57)

> 0.63 (0.67)

�2.96 (�0.89)

�0.08 (�0.79)

�16.35\*\* (�2.21)

> 30.75 (0.98)

2 (1.19) �2.84

�76.04\* (�1.82)

> 23.24 (0.11)

�2.03 (�0.07)

�5.09 (�1.63)

33.94\*\*\* (3.08)

0.22 (0.64)

�16.96 (�0.69)

(�0.51)

127.85 (1.24)

Furthermore, the earnings managements can be related with the opportunistic behaviour of the firm. We investigate this issue by analysing the effect of ethical behaviour of the firms using ETHICS variable on their future returns and future survivorship. Since the ETHICS is an annual value identical within a year while different across the years, we include this in our overall sample including all periods

4.3 Ethical behaviour of the firms

Const �4.45

EP �9.82

BM �0.59

PS 0.44

MktCap 4.72\*\*

EBITDA �0.27

Salesg 2.2

MJDA 0.32

R&D �5.25

corresponding coefficients.

Significance at 10% level. \*\*Significance at 5% level. \*\*\*Significance at 1% level.

discretionary accruals (MJDA).

\*

70

Table 4.

Adjusted R2

(�0.76)

(�0.67)

(�0.42)

(0.4)

(2.5)

(�1.1)

(1.08)

(1.34)

(�0.29)

4.57 (0.31)

47.8 (1.29)

12.85\*\*\* (3.66)

0.54 (0.19)

3.53 (0.74)

�0.63 (�1.01)

�3.84 (�0.75)

1.23\*\* (2.07)

155.73\*\*\* (3.36)

2.99 (0.11)

252.49\*\*\* (3.85)

19.83\*\*\* (3.18)

1.77 (0.36)

�1.31 (�0.16)

�0.72 (�0.64)

�6.07 (�0.67)

> 0.93 (0.88)

265\*\*\* (3.22)

firms are more likely to reduce their future returns while leaving their future

The Roles of Accounting Valuations and Earnings Management in the Survivorship of Technology…

To provide a robustness check on the results obtained, we have compare the output generated when running our returns and survivorship analyses using the Modified Jones Discretionary Accruals (MJDA) method. As shown in Table 7, there

From Table 7, we can deduce that our results in evaluating predictors of future performance are robust in being replicated across the MJDA and JDA procedures. Each regression model provides the same significance and similar explanatory power through their R-squared. All variables across the two methods possess the same signage of coefficients and remain within the statistical significance zone. In testing the robustness of our results in finding predictors of the survivorship of tech-firms, we find similar result using the JDA as presented in Table 8. All models remain significant just as in the MJDA results and the variables hold the same meaning within the outputs. These confirm that our results are consistent with the initial findings. We further perform our robustness check on the results from

6m 1y 3y 5y

Const �4.75 (�0.33) 9.48 (1.02) 6.25 (1.37) 7.22\* (1.94) EP �26.86\*\* (�2.33) �12.62\*\* (�2.17) �7.12\*\*\* (�2.81) �5.29\*\*\* (�3.14) BM �0.54 (�0.57) �1.22\* (�1.91) �0.27 (�1.4) 0.06 (0.54) PS 0.01 (0.06) �0.21 (�1.41) �0.16\*\* (�2.15) �0.02 (�0.42) MktCap 0.06 (0.11) �0.44 (�1.25) �0.49\*\*\* (�3.08) �0.61\*\*\* (�4.73) EBITDA 0.01 (0.72) 0 (0.08) 0 (�0.41) �0.01 (�0.64) Salesg �2.32\*\*\* (�3.42) �0.97 (�1.33) �0.12 (�0.61) 0.08 (0.58) MJDA 0.13\* (1.77) 0.09\* (1.71) 0.03 (1.08) 0.02 (1.1) R&D �53.67\*\*\* (�3.8) �73.42\*\*\* (�6.29) �5.84\*\*\* (�3.49) �1.23 (�1.03) ETHICS 0.69 (0.26) �1.3 (�0.76) �0.99 (�1.17) �1.18\* (�1.71) χ<sup>2</sup> 44.69\*\*\* 138.67\*\*\* 44.01\*\*\* 48.06\*\*\* Pseudo R2 0.38 0.48 0.06 0.05 N 866 866 866 866

The table shows the valuation and accounting variables' effect on the technology firms' returns from 2008 to 2010. The dependent variables are dummy variables indicating 1 if the technology firm fails in 6 months (6m), 1 year (1y), and 3 years (3y), and 5 year (5y) and 0 otherwise. Then we use the earnings to price ratio (EP), book to market ratio (BM), price to sales ratio (PS), market capitalization (MktCap), EBITDA, sales growth (Salesg), Modified Jones for discretionary accruals (MJDA), research and development (R&D), and firm's ethical behaviour score (ETHICS) as

Full logistic analysis of failed NASDAQ firms using modified Jones model for discretionary accruals (MJDA).

our independent variables. The values in parentheses are the <sup>t</sup>-values to the corresponding coefficients. \*

Tables 7 and 8 where we used our overall data including ETHICS.

Model : Failed firmt ¼ a þ b1EP þ b2BM þ b3PS þ b4MktCap þ b5EBITDA

þb6Salesg þ b7MJDA þ b8R&D þ b9ETHICS þ b106m… þ b135y

survivorships not significantly affected.

DOI: http://dx.doi.org/10.5772/intechopen.85395

is no difference between the two results.

4.4 Robustness check

Significance at 10% level. \*\*Significance at 5% level. \*\*\*Significance at 1% level.

Table 7.

73


The table shows the valuation and accounting variables' effect on the technology firms' returns from 2008 to 2010. The dependent variables are 3 months (3m), 6 months (6m), 1 year (1y), 3 years (3y), and 5 years (5y) returns of the technology firms. Then we use the earnings to price ratio (EP), book to market ratio (BM), price to sales ratio (PS), market capitalization (MktCap), EBITDA, sales growth (Salesg), modified Jones for discretionary accruals (MJDA), research and development (R&D), and firm's ethical behaviour score (ETHICS) as our independent variables. The values in parentheses are the <sup>t</sup>-values to the corresponding coefficients. \*

Significance at 10% level.

\*\*Significance at 5% level.

\*\*\*Significance at 1% level.

#### Table 6.

Full multivariate analysis of periodic returns of NASDAQ technology firms—using modified Jones model for discretionary accruals (MJDA).

(2008, 2009, and 2010) and run linear and logistic regressions as in our Sections 4.2 and 4.3. The results for the future returns and future survivorships are shown in Tables 5 and 6, respectively.

In Table 5, we do find highly similar relationship of EP, BM, MJDA and R&D with the future returns as in our Table 3. However, using the overall sample in Table 5 shows more significant effects of these variables on the future returns. Then we find that the ETHICS has positive effect on the future returns in technology firms. In other words, the ethical behaviour of the technology firms tend to increase the future returns. Thus, the opportunistic behaviour of the technology firms is likely to decrease their future returns.

The similar relationship of EP, BM, PS, MktCap, Salesg, MJDA, and R&D on future survivorships are also found between Tables 4 and 6 while the latter one using overall data tend to show more significant relationships. However, in this case, we do not find highly significant effect of ETHICS on the future survivorships of the technology firms. Therefore, the opportunistic behaviour of the technology

The Roles of Accounting Valuations and Earnings Management in the Survivorship of Technology… DOI: http://dx.doi.org/10.5772/intechopen.85395

firms are more likely to reduce their future returns while leaving their future survivorships not significantly affected.
