Investigating the Impact of Research and Development costs on Performance of Loss Firms: Evidence from Tehran Stock Exchange

Transcription

1 Investigating the Impact of Research and Development costs on Performance of Loss Firms: Evidence from Tehran Stock Exchange Shokrollah Khajavi* Associate Professor of Accounting Department Faculty of Economics, Management and Social Sciences Shiraz University, Iran *Corresponding author: Abstract Mostafa Sadeghnia PhD student of Accounting, International Division, Shiraz University, Iran Research and development costs are of interest for many researchers. The old debate of expensing or capitalizing and deferent reaction of profit or loss firms' indictors to these costs is the main concern of such studies. Most of these investigations have been conducted in developed countries. In the same way, the purpose of this research is investigating the impact of R&D costs on performance of loss firms in a developing country. We have used profitability, stock market value, and sales growth as performance indicators of a company. In this way, we selected a sample of 113 listed firms in Tehran Stock Exchange in the time periods. In addition, we used Pooled/panel regression analysis to test the research hypotheses. According to the results, the R&D costs have a negative and significant relationship with the performance indexes. In other words, R&D costs in loss firms do not improve their performance. Keywords: Research and Development Costs, Financial Performance, Loss Firms, Tehran Stock Exchange. Page 765

2 1 Introduction R&D has been a challenging issue. One reason is that they are expensed based on GAAP accounting, however some researchers do not agree with this procedures. Especially, this issue is very important for loss firms. For example, Darrough and Ye (2007) believe that loss firms that are likely to stay in business for many years are able to survive and receive high market valuation because of their future prospects despite current losses. Since accounting earnings and book values do not fully capture the future prospects of these firms, appropriate adjustments have to be made to derive a correct valuation model. The market values of these loss firms are then no longer negatively related to their earnings. Other researchers like Franzen & Radhakrishnan (2009) expand the issue to the profit firms and compare R&D impact on profit and loss firms. They conclude, «The valuation multiplier on R&D expenditures is likely to be negative (positive) for profit (loss) firms. However, most of these researches have been done in developed countries. The issue may be virgin in developing country and needs more attention. In this way, in this research, we examine the role of R&D expense in a performance of loss-firms in Iran as a developing country. As we know, modern business firms make strategic choices about investment in R&D in the hope of enjoying competitive advantage in subsequent periods (Coad and Roa,2008). As loss-firms may choose R&D for survival, this scenario might be different for these kinds of companies than profitable ones. The main issue is that is really R&D can help looser become winner? In order to answer this question, we examine whether research and development costs affect performance indicators of company (profitability, stock market value, and sales growth). The reminder of this paper is organized in this way; first, research theories and history have been discussed. Then, research variables, population and statistical sample have been introduced. After that, research method, hypotheses and data analysis are described. Finally, research conclusion and recommendations are provided. 2 Literature review Modern business firms make strategic choices about investment in R&D in the hope of enjoying competitive advantage in subsequent periods. Their choice of R&D expenditure levels may depend upon many factors, and the choice of R&D investment levels is the outcome of lengthy negotiations within firms. Since the returns to R&D cannot be known ex ante (by definition), considerable leeway exists for behavioral factors and business intuition as opposed to any kind of serious cost-benefit analysis R&D investment is very much an art rather than a science (Coad and Roa,2008). Currently, R&D expenditures are fully expensed under generally accepted accounting principles. Additionally, firms investing in R&D activity are required to disclose the amount of the R&D expenditure for the period. Darrough and Ye (2007) provide evidence that R&D expenditures have a positive valuation multiplier for loss firms(franzen & Radhakrishnan,2009). Page 766

3 One way to examine this valuation is reviewing effect of R&D on firm performance. Previous research use deferent performance indicators. Coad and Roa(2008) study the co-evolution of sales growth, employment growth, profits growth and the growth of research and development (R&D) expenditure. Chan et al (2014) Examines whether firms with greater research and development (R&D) expenditures earn higher stock returns when they have good corporate governance. Franzen & Radhakrishnan (2009) use a simple residual-income based valuation model similar to Ohlson (1995) to derive the relation between stock price and R&D expense, earnings (before R&D expense) and book value of equity for R&D firms with profits and losses. In this research, we use profitability, stock market value, and sales growth as performance indicators of company and evaluate their relationship with R&D. 3 Prior studies Berger et al (1996) in their research on USA markets concluded that book value is more important than profit in explaining stock price changes. Graham & King (2000) investigated the relationship between stock prices and accounting numbers in six Asian countries, Indonesia, South Korea, Malaysia, Philippines, Taiwan, and Thailand. They concluded that power of explaining stock prices by accounting numbers in Taiwan and Malaysia is relatively low, while it is relatively high in Philippine and South Korea. Moreover, they concluded that explanatory power of book value in South Korea and Philippine is high and in Taiwan it is low. Lakoishok and Sougiannis (2001) examined stock prices and research and development costs. The results indicated that in companies with high research and development costs, market value of company is higher than return on stock. Sharad &Zhang (2006) investigated the relationship between research and development costs with abnormal profit durability. The results indicated that research and development costs increase abnormal profit durability. Franzen & Radhakrishnan (2009) examined the relationship between research and development costs with profit-making companies. The results indicated that evaluation of multiplier coefficient on research and development costs is possibly negative (positive) for profit (loss) of company. 4 Research hypotheses This research develops one main and three sub hypotheses: Main hypothesis: there is a significant relationship between research and development costs and company performance indicators. Sub hypotheses include: 1. There is a significant relationship between research and development costs an operational profit. 2. There is a significant relationship between research and development costs and company market value. Page 767

4 3. There is a significant relationship between research and development costs and company sales growth. 5 Research methodology 5.1 Sample and data Research statistical population includes all companies listed in Tehran stock exchange in time span. Through screening method, only companies that have below qualifications have been selected: 1. They are listed in Tehran stock exchange up to the end of March, 2002, and their fiscal year ends in March. 2. They have not changed their fiscal year during research period. 3. They have provided financial information required for this research in period, completely. 4. They are not banks, insurance and investment companies, due to different nature of such companies` operations. For instance, most stocks of manufacturing companies are in possession of insurance and investment companies. Therefore, manufacturing investment insurance companies being together shall led to a correlation between observations. This issue would lead to linearity and serial correlation problem between model`s disturbing components, and subsequently, wrong deduction of data analysis results According to above-mentioned qualifications, 113 companies were selected as sample. In this research data and variables are collected through financial statements, explanatory notes, weekly and monthly reports of stock exchange using Rah Avard Novin application. 5.2 Research variables Independent variable The independent variable used is research and development costs in Firms which have been derived from company explanatory notes. RDD it = dummy variable of research and development costs at the end of fiscal year t for lossfirms of I; It is equals one if the R&D expenditures (item 46) are notavailable and zero otherwise. Dependent variables Dependent variables in sub hypotheses one to three are: profitability, market value of company, and sales growth respectively: OI it = operational profit at the end of fiscal year t for company I; MV it = market value at the end of fiscal year t for company I; SG it = sales growth at the end of fiscal year t for company I; Control variables Control variable used in this research as other factors affecting performance indicators include: A) Company size: normal logarithm of total assets as a representative for company size (McGuire et al, 2012). B) Non-current liabilities at the end of fiscal year t for company 1; Page 768

5 Data analysis method and testing the hypotheses This research reviews the relationship between research and development costs and performance indicators by using following: The following model is used to test the first sub hypothesis: OI it = α 0 + α 1 RD it + α 2 RDD it + α 3 Size it + α 10 LTDG it + ε it If a 2 regression coefficient is significant, the impact of research and development costs in Firms in explaining company profitability is approved. To test the second sub hypothesis, the following model is used: MV it = α 0 + α 1 RD it + α 2 RDD it + α 3 Size it + α 10 LTDG it + ε it If a 2 regression coefficient is significant, the impact of research and development costs in Firms in explaining company market value is approved. SG it = α 0 + α 1 RD it + α 2 RDD it + α 3 Size it + α 10 LTDG it + ε it If a 2 regression coefficient is significant, the impact of research and development costs in Firms in explaining company sales growth is approved. 5 Results Research descriptive statistics are presented in table 1. By comparing coefficient of changes (through dividing standard deviation to average) in dependent variables in research time period, it is concluded that sales growth variable comparing to market value and operational profit, has higher coefficient of changes and dispersion and subsequently, lower stability. It indicates that company sales growth should be under influence of other factors, which some of them are used in this research as control variables. Among control variables, company size has the lowest coefficient of changes and subsequently, highest stability. On the other side, growth of non-current has the highest coefficient of changes and dispersion, and subsequently lowest stability. It indicates that mentioned companies have significant differences in terms of non-current liabilities growth. Other results of descriptive statistics indicate that mentioned companies on average possess 15% operational profit, and 10% research and development costs. Results also indicate that only 9% of year-companies have had research and development costs. Moreover, these companies have had 31% growth in non-current liabilities on average. Page 769

6 Variables Standards Operation al profit Market value Sales growth Research Research and and developmen developmen t t in Firms Compan y size Growth of noncurrent liabilities Number Average Mean Maximum Minimum Standard deviation Coefficient of changes Final results of research variables have been presented in table 2. According to unit root tests by Levin et al test, since P-Value is less than 5%, total variables have been in stable level in research period. Stability means that average and variance of variables during time, and also covariance of changes in different years have been fixed. Table 2: testing stability of variables in research period Stability test Value of Levin, Lin & Chu Possibility of Levin, Variables test Lin & Chu test Operational profit Market value Sales growth Research and development Research and development in Firms Company size Growth of non-current Results of testing correlation among variables in research period is presented in table 3.It indicate that operational profit, market value and sales growth negatively correlated with research and development costs in Firms. In addition, it indicates that in Firms, research and development costs have not led to increase in sales and subsequently operational profit. Page 770

7 Variables Variables Operational profit Market value Sales growth Research and development Research and development in Firms loss- Company size Growth of noncurrent Market value Table 3: correlation among research variables Research Research and Sales and development growth developm in lossent Firms Operation al profit Compan y size Growth of non-current Before testing research hypotheses, a proper pattern for regression model was selected using F Limier and Hausman tests. Model type is shown in testing the hypotheses. Results regarding F Limier have been presented in table 4. Possibility value of F Limier test in table 4, is less than significance level of 5%, so using pooled data model to test above hypothesis is rejected. Table 4: choosing pooled data against plan data Model OI it = α 0 + α 1 RD it + α 2 RDD it + α 3 Size it + α 10 LTDG it + ε it Test type Value of test Freedom degree Possibility of test F Limier (112, 1013) Since pooled data model is not selected against plan data, Hausman test is used to choose fixed effects pattern against random effects. Results of Hausman test are presented I table 5. Possibility value of Hausman test in table 5 is less than significance level of 5%, so there is no enough reason to reject fixed effects pattern, and it shall be used to test the first hypothesis. Table 5: choosing fixed effects pattern against random effects Model OI it = α 0 + α 1 RD it + α 2 RDD it + α 3 Size it + α 10 LTDG it + ε it Test type Test value Freedom degree Test possibility Hausman Panel regression model of fixed effects of impact of research and development costs on operational profit in research period, shown in table 6, indicates that panel effect of research and development costs on profitability in Firms is negative (-0.14) and considering to t test (), it is significant. It indicates that in Firms, research and development costs have negative impact on profitability. Other results indicate that there is a negative and significant relationship between Page 771

8 growth of non-current and profitability. Moreover, adjusted coefficients indicate that totally about 60% of changes in profitability are under influence of research and development, company size and growth of non-current. Results regarding F Limier test indicate that this model in general is significant and considering Durbin Watson test it lacks auto-correlation problem. Table 6: impact of research and development cost on profitability tests Regression Variables coefficients T test value T test possibility Fixed amount Research and development Research and development in Firms loss- Company size Growth of non-current Determination coefficient Adjusted F test possibility Durbin Watson test determination coefficient Results regarding F Limier have been presented in table 7. Possibility value of F Limier test in table 7, is less than significance level of 5%, so using pooled data model to test above hypothesis is rejected. Table 7: choosing pooled data against plan data Model MV it = α 0 + α 1 RD it + α 2 RDD it + α 3 Size it + α 10 LTDG it + ε it Test type Test value Freedom degree Test possibility F Limier (112, 1013) Since pooled data model is not selected against plan data, Hausman test is used to choose fixed effects pattern against random effects. Results of Hausman test are presented I table 8. Possibility value of Hausman test in table 8 is less than significance level of 5%, so there is no enough reason to reject fixed effects pattern, and it shall be used to test the first hypothesis. Table 8: choosing fixed effects pattern against random effects pattern Model MV it = α 0 + α 1 RD it + α 2 RDD it + α 3 Size it + α 10 LTDG it + ε it Test type Rest value Freedom degree Test possibility Hausman Panel regression model of fixed effects of impact of research and development costs on market value in research period, shown in table 9, indicates that panel effect of research and development costs on market value in Firms is negative (-0.373) and considering t test (), it is significant. It indicates that in Firms, research and development costs have negative impact on market value. Page 772

9 Other results indicate that there is a positive and significant relationship between company size and market value. Moreover, adjusted coefficients indicate that totally about 54% of changes in market value are under influence of research and development, company size and growth of noncurrent. Results regarding F Limier test indicate that this model in general is significant and considering Durbin Watson test it lacks auto-correlation problem. Table 9: impact of research and development cost on company market value tests Regression Variables coefficients T test value T test possibility Fixed amount Research and development Research and development in loss-firms Company size Growth of non-current Determination coefficient Adjusted F test Durbin Watson test determination coefficient possibility Results regarding F Limier have been presented in table 7. Possibility value of F Limier test in table 7, is less than significance level of 5%, so using pooled data model to test above hypothesis is rejected. Table 10: choosing pooled data model against plan data model Model SG it = α 0 + α 1 RD it + α 2 RDD it + α 3 Size it + α 10 LTDG it + ε it Test type Test value Freedom degree Test possibility F Limier (112, 1013) Panel regression model of fixed effects of impact of research and development costs on sales growth in research period, shown in table 11, indicates that panel effect of research and development costs on sales growth in firms companies is negative (-0.314) and considering t test (), it is significant. It indicates that in firms companies, research and development costs have negative impact on sales growth. Other results indicate that there is a positive and significant relationship between company size and growth of non-current liabilities with sales growth. Moreover, adjusted coefficients indicate that totally about 546 of changes in market value are under influence of research and development, company size and growth of non-current. Results regarding F Limier test indicate that this model in general is significant and considering Durbin Watson test it lacks auto-correlation problem. Page 773

10 Table 11: impact of research development on sales growth tests Regression T test value T test possibility Variables coefficients Fixed amount Research and development Research and development in firms companies Company size Growth of non-current Determination coefficient Adjusted determination F test possibility Durbin Watson test coefficient Conclusion As mentioned, companies invest in R&D in the hope of enjoying competitive advantage in subsequent periods. As loss firm want to survive, this issue may be more crucial for them than profitable ones. One obstacle is that R&D is an expanse in accounting standards. Therefore, we should measure its effect on performance indicators in deferent ways. In this way, research examines the role of R&D expense in a performance of firms companies. Results indicate that there is a negative and significant relationship between R&D costs and performance indicators of companies. In other words, research and development costs in firms companies cannot lead to improvement in company performance. On researcher s opinion, there are still different topics in this field that can be important for future studies. So, it is recommended to pay more attention to the following subjects, in order to make maximum use of research results; and to help better reviewing of research and development costs impact on other accounting indicators in future: Reviewing and testing other effective factors such as other revenues, failure to pay taxes, etc. in firms companies. Using other relevancy criteria, such as return on stock, in reviewing the impact of earnings sharing and research and development costs on company performance indicators: conducting a similar study in industry level. Page 774

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