In order to successfully transform into a knowledge economy and eradicate poverty, many ASEAN countries have allocated a considerable amount of their yearly expenditures in research and development over the last decade. The objective of this paper is to examine the long-run relationship between research and development expenditure and gross national income of five major ASEAN countries – Thailand, Malaysia, Singapore, Indonesia and Philippines. The results of a cross-country panel data analysis performed in this study suggest that there is a long-run cointegration relationship between these two variables. Findings imply that higher research and development expenditure has a favorable impact on the long-run prosperity of these countries

Chong, Fen Nee

Liew, Venus Khim-Sen

Suhaimi, Rosita

In order to successfully transform into a knowledge economy and eradicate poverty, many ASEAN countries have allocated a considerable amount of their yearly expenditures in research and development over the last decade. The objective of this paper is to examine the long-run relationship between research and development expenditure and gross national income of five major ASEAN countries - Thailand, Malaysia, Singapore, Indonesia and Philippines. The results of a cross-country panel data analysis performed in this study suggest that there is a long-run cointegration relationship between these two variables. Findings imply that higher research and development expenditure has a favorable impact on the long-run prosperity of these countries

Fennee, Chong

Rosita, Suhaimi

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Does research and development expenditure cointegrate with the gross national income of ASEAN countries?

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Munich Personal RePEc ArchiveDoes Research and DevelopmentExpenditure Co-integrate with GrossNational Income of ASEAN Countries?Chong, Fen Nee and Liew, Venus Khim-Sen and Suhaimi,RositaFaculty of Business and Law, Auckland University of Technology,New Zealand, Faculty of Economics and Business, UniversityMalaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia,Faculty of Business Management,Universiti Teknologi MARA, 94300Kota Samarahan, Sarawak, Malaysia2016Online at https://mpra.ub.uni-muenchen.de/107981/MPRA Paper No. 107981, posted 27 May 2021 07:20 UTC Does Research and Development Expenditure Co-integrate with Gross National Income of ASEAN Countries?1 Fen Nee Chong Faculty of Business and Law,  Auckland University of Technology, New Zealand  E-mail: fennee.chong@aut.ac.nz  Venus Khim-Sen Liew Faculty of Economics and Business, University Malaysia Sarawak,  94300 Kota Samarahan, Sarawak, Malaysia E-mail: ksliew@unimas.my  Rosita Suhaimi Faculty of Business Management,Universiti Teknologi MARA,  94300 Kota Samarahan, Sarawak, Malaysia E-mail: rositasu@sarawak.uitm.edu.my   ABSTRACT In order to successfully transform into a knowledge economy and eradicate poverty, many ASEAN countries have allocated a considerable amount of their yearly expenditures in research and development over the last decade. The objective of this paper is to examine the long-run relationship between research and development expenditure and gross national income of five major ASEAN countries – Thailand, Malaysia, Singapore, Indonesia and Philippines. The results of a cross-country panel data analysis performed in this study suggest that there is a long-run cointegration relationship between these two variables. Findings imply that higher research and development expenditure has a favorable impact on the long-run prosperity of these countries.  Keywords: Research and development expenditure, Gross national income.  1.0 Introduction The economic theory which only take into account labour, capital, land and entrepreneurship as the inputs to produce goods and services for economic profit have been adjusted many times. Nowadays, most countries have switched from the old production functions to adopt the                                                           1 Suggested citation: Chong, F.N., Liew, V.K.S & Suhaimi, R. (2016). Does Research and Development Expenditure Cointegrate with The Gross National Income of ASEAN Countries? International Journal of Economic Research, 13(3), 1231-1237.  knowledge-economy model. The main ingredient under knowledge-economy is intellectual capital that focuses on technological progress. Specifically, technological progress is defined as innovations, inventions or research and development works which are supported by the allocation set aside as gross expenditure in research and development (Karczewska, 2015).   As one of the most rapidly developing economy entity in the world, ASEAN countries recognize the importance of moving up the value chain to produce higher value added technology intensive products in order to become high-income economies. To achieve this goal, it is imperative for ASEAN countries to allocate a proportion of their GDPs in research and development. In fact, numerous studies contend that improving the innovative capacity of a nation is crucial to ensure the long-run economic growth of a country and one of the avenues to improve innovative capacity is by providing sufficient funding to support academic researches and preparing the necessary platform to facilitate both business and private research and development (Pavitt, 1980 and Piras et al. 2012).   Even though both research and development expenditure and gross national income are on the upward trend in most ASEAN countries, however, it is not known whether the investments in research and development provides the outcome as anticipated to the nations’ wealth. Indeed, investing in research and development is not only risky but also could take a long gestation period. With that in mind, the objective of this paper is to assess the long-run relationship between research and development expenditure and the gross national income of five major ASEAN countries, namely, Indonesia, Singapore, Malaysia, Philippines and Thailand.  2.0 Literature Review The neoclassical theory of economic growth proposed by Solow (1957) asserts that sustainable technological progress is the crucial driving force for productivity and economic advancement. This was supported by Inekwe (2015) who posits that technological progress via research and development is important for the growth of businesses and consequently the improvement of a country. However, the high cost of developing new technology can be improvident for some countries and therefore, the acquisition of technology varies across different countries whereby some countries achieve technological progress via imitation whilst others by means of innovation or both. Among the ASEAN-5 countries included in this study, Indonesia, Malaysia, Philippines and Thailand’s are predominantly agricultural economies while Singapore’s economy was driven by the manufacturing sector. Nevertheless, in order to foster productivities and eradicate poverty these five ASEAN countries have taken measures to transform their economies into a knowledge-based economy. In their quest to achieve this aspiration, technological progresses via research and development initiatives involving the industries, academics and international collaborations activities have been instigated.    From the economic policy maker’s perspective, investment in research and development is a proactive strategy which allows poor countries to achieve higher livings standard and thus, catch up with their developed counterparts. Thirthe et.al (2003) found that research and development activities in Asia and Africa have brought about technological advancements in the agricultural sector and that has contributed to a reduction of twenty-seven millions of people living in poverty each year. A later study conducted by Freire-sern (2001) also found a significant relationship between aggregate research and development spending and economic growth whereby and 1% increase in research and development expenditure results in 0.08% increase in the real GDP. Tiits (2007) highlights the importance for small countries to implement proactive foreign investment strategies in the field of research and development whilst Walde and Woitek (2004) find research and development activity shows pro-cyclical rather than countercyclical behavior on the GDP growth of G7 countries.   Contradict to Walde and Woitek (2004), Saint-Paul (1993) postulates research and development expenditure does not correlate with the cyclical behavior of the economy and this finding was supported by Fatas (2000). Similar studies by Salter and Martin (2001) and Piras et al. (2012) propound that the social-economic benefits of research and development could be hard to measure as they vary across industries and field. Based on the literature review discussed above, the empirical findings on the payoff for research and development expenditure are inconclusive. It is therefore the aim of this paper to investigate whether research and development expenditure has any impact on ASEAN-5’s economic wellbeing.  3.0 Methodology To accomplish our objective in this study, panel unit root tests and panel cointegration tests are adopted in our analysis. i. Panel unit root tests The well-established Augmented Dickey-Fuller (ADF) regression with intercept and linear trend specification is as follow:   , for  and , (1)  where  is the value of the variable of interest for country at time .  N and T are the total number of cross-section and time series units respectively.  denotes the error term, while ,  and are unknown parameters to be estimated. The estimator of interest is . The null hypothesis of a unit root is specified as:   =0, for all .         (2)  Panel unit root test of Im et al. (2003) considers the following alternative hypothesis:   <0, for some .         (3)   The ADF-type t-statistics of Im et al. (2003) is given as:   ,          (4)  where  is the individual ADF t-statistics for the unit root test.  In another approach, Maddala and Wu (1999) propose to combine the p-values of the individual ADF t-statistics to obtain:   ,        (5)  where  is a chi-squared test statistic with 2N degree of freedom and  is the p-value of the ADF t-statistics for cross-section unit .   In the spirit of Maddala and Wu (1999), Choi (2001) suggests the following statistic:   ,        (6)  where Z is  a statistic with standard normal distribution, and  is the inverse of the standard collective distribution function. Choi (2001) is more practical than Im et al. (1999) for its less restrictive assumptions. Moroever, Choi (2001) improves over Maddala and Wu (1999) in terms of finite sample size and power (Ling et al., 2010)2.   ii. Panel Cointegration Tests Engle and Granger’s (1987) residuals-based static cointegration regression is given as:   ,      (7)  where y is the dependent variable and  xs are a set of independent variables. If  is stationary, it implies that there is cointegration between the y and x’s variables.  The unit root property of  can be determined based on ADF regression:                                                           2 See also Hlouskova and Wagner (2006), which indicates that  statistic is increasingly oversized in short panels with 10-15 years periods of data.     , for  and ,  (8)  where  is estimated from Equation (7).  The ADF-type test statistics considered by Pedroni (1997, 1999) are known as the Panel ADF and Group ADF statistics. Referring to Equation (8), Panel or the within-group ADF statistic is obtained by pooling the autoregressive coefficients, across different cross-section units. Meanwhile the Group or the between-group ADF statistic is based on group average approach for each cross-section unit.  The null hypothesis for all Pedroni’s tests is no cointegration. The alternative hypothesis for the within-group estimation is = 0, for all , while for the between-group estimation, the alternative hypothesis is <0, for all . Before computing the test statistics, one needs to follow the five steps in the Pedroni’s procedure (Pedroni, 1999)3.   In a separate endeavor, Kao (1999) derives a different ADF-type statistic. See Kao (1999) for procedure to compute the statistic4. Guitierrez (2003) shows via a Monte Carlo study that Kao’s tests have higher power than Pedroni’s tests when a small number of time series observations (T) are included in the panel. Compare to the former, the latter allows for a more flexible alternative hypothesis and suffers less from small sample size distortion (Pedroni, 2001 and Kim et al., 2005). Furthermore, the latter can address problem of omitted variables and simultaneity bias in a non-stationary static panel setting (Cavalcanti et al., 2011). To provide a more robust analysis, all the methods discussed above are utilized in this study.   4.0  Empirical Results This study includes a sample of five ASEAN countries namely, Indonesia, Malaysia, Philippines, Singapore and Thailand. Annual data from 2000 to 2010 on gross national income (GNI) and research and development expenditure (RDE) are obtained from IMD and World Bank database. All data are logarithmic transformed before applied. The results of Im et al. (2003), Maddala and Wu (1999) and Choi (2001) panel unit root tests are summarized in Table 1. The results as shown in Table 1 suggest that LGNI and LRDE are not stationary at 5% significance level. It can be said so because the marginal significance value of all test statistics are bigger than 0.05, and hence the null hypothesis of stationary series could not be rejected. Nonetheless, ÄLGNI and ÄLRDE are stationary since the null hypothesis of all the tests can be rejected at 5% significance level. With that, it can be concluded that LGNI and LRDE variables are integrated of order 1 as they become stationary after first-differencing.                                                             3 Together with the two ADF-type tests, Pedroni also proposed five other statistics. 4 Kao (1999) also introduces four other Dickey-Fuller statistics, which assume no serial correlations in the residuals.    Table 1. Results of Panel Unit Root Tests  Panel unit root tests Variable Im et.al (2003) Maddala and Wu (1999) Choi (2001) LGNI -0.523 [0.301] 10.540 [0.395] -1.627 [0.052]  -2.029 [0.021] 23.189 [0.010] -2.813 [0.003] LRDE -0.198 [0.422] 13.388 [0.203] -0.762 [0.223]  -2.349 [0.009] 26.941 [0.003] -2.726 [0.007] Notes: LGNI and LRDE represent the logarithms of GNI and R&D expenditure. The first differenced variable is given by a symbol  in front of the variable name. The values in brackets are the p-values of the test statistics.  Since all the variables are integrated of order 1 there is a possibility that they are cointegrated. As such, the cointegration tests of Pedroni (1997, 1999 and 2001) and Kao (1999) are employed and the results are presented in Table 2. Similar to the unit root tests, the results of cointegration tests are sensitive to the lag used in the estimation. Cavalcanti et al. (2011), consider lag 0,1,2,3 separately in their study. This study fixes the maximum lag as 3 and let AIC decides on the optimal lag length. The results depicted in Table 2 show that there are some evidences of cointegration between R&D expenditure and GNI.   Table 2: Panel Cointegration Tests Results  Pedroni (1999,2001) Kao (1999) Variable Panel ADF Group ADF ADF LGNI 0.045  [0.519] -4.413   [0.000] -1.514 [0.065] LRDE -4.672 [0.000] -12.117 [0.000] -0.749 [0.227] Notes: LGNI and LRDE represent the logarithms of GNI and R&D. The values in brackets are the p-values of the test statistics. 5.0 Conclusion This study examines the relationship between gross national income and research and development expenditure of Indonesia, Malaysia, Philippines, Singapore and Thailand. Panel unit root test and panel cointegration test are used to examine the data. Empirical evidence suggests that there is a long-run cointegration relationship between these two variables in the panel countries examined. Consistent with Inekwe (2015), result implies that research and development investment is crucial to the longrun prosperity of developing countries and in this study, the ASEAN-5.   References Cavalcanti, T. V., Kamiar, K. and Raissi, M. (2011). Growth, development and natural resources: New evidence using a heterogeneous panel analysis, The Quarterly Review of Economics and Finance, 51, 305–318. Choi, I. (2001.) Unit root tests for panel data, Journal of International Money and Finance, 20(2), 249–272. Fatas, A. (2000). Do business cycles cast long shadows? Short-run persistence and economic growth. Journal of Economic Growth, 5, 147-162. Engle, Robert F.; Granger, Clive W. J. (1987). Co-integration and error correction: Representation, estimation and testing. Econometrica, 55 (2), 251–276. Gutierrez, L. (2003). On the power of panel cointegration tets: A Monte Carlo comparison. Economics Letters, 80(1), 105-111. Im, K. S., Pesaran, H.M. and Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53-74. Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of  Econometrics, 90, 1-44. Kim, H., Oh, K.Y., & Jeong, C.W. (2005). Panel cointegration results on international capital mobility in Asian countries. Journal of International Money and Finance, 24(1), 71–82. Ling, T.H, Liew, V.K.S & Syed K.W. (2010) Does Fisher Hypothesis hold for the East Asian economies? An application of panel unit root tests, Comparative Economic Studies, 52, 273–285. Maddala, G.S. and Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test, Oxford Bulletin of Economics and Statistics, 61, 631-652. Pavitt, K. (1980).Technical innovation and British economic performance. Macmillan  (London). Saint-Paul, G. (1993). Productivity growth and the structure of the business cycle. European Economic Review, 37, 861-883. Pedroni, P. (1997). On the role of cross-sectional dependency in panel unit root and panel cointegration exchange rate studies. Working Paper, Indiana University Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics & Statistics, 61, 653-670. Pedroni, P. (2001). Purchasing power parity tests in cointegrated panels, Review of Economics and Statistics, 83, 727-731. Piras, G. and Postiglione, P. and Aroca, P. (2012). Specialization, R&D, and productivity growth: Evidence from EU. The Annals of Regional Science 49(1), 35-51. Salter, A. J. and Martin, B. R. (2001). The economic benefits of publicly funded basic research: A critical review, Research Policy, 30, 504-524. Tiits, M. (2007). Technology-intensive FDI and economic development in small country: The case of Estonia. TRAMES. 11(61/56), 3, 324-342.  Walde, K. and Woitek, U. (2004). R&D expenditure in G7 countries and the implications for endogenous fluctuations and growth. Economics Letters, 82, 91-97. 

Does Research and Development Expenditure Co-integrate with Gross National Income of ASEAN Countries?

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Does Research and Development Expenditure Co-integrate with Gross National Income of ASEAN Countries?

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