Abstract
Purpose
This study aims to explain the effect of research and development (R&D) incentives on economic growth, focusing on the case of Türkiye. A one-sector endogenous growth model has been constructed. The model includes three actors: firm, consumer and government. The consumer derives utility from consumption, supplies human capital and engages in saving. The representative firm invests in R&D to maximize the current value of profit flows by choosing how much input it will use and how much R&D it will undertake. The public sector provides incentives for labor and capital used in R&D production. R&D has been defined as a function that endogenously increases total factor productivity (TFP).
Design/methodology/approach
In line with the stated purpose, this study presents a dynamic general equilibrium model. Then, this study calibrates the model parameters with Türkiye's data.
Findings
The results imply that incentives for R&D personnel instead of physical capital have a stronger impact on economic growth.
Practical implications
The findings of this study point to an important conclusion on how to distribute R&D incentives across the two main factors in R&D production, labor and capital. Incentives given to R&D personnel are more effective in Türkiye.
Originality/value
This study shows that the R&D incentives provided by the public sector can be important in emerging countries where many firms have just started their R&D activities. In this study, the authors worked on Türkiye as an emerging country. This study discusses policies on how the R&D incentives will be more effective on economic growth in Türkiye. This study considers that these policies may apply to all emerging countries, due to similar R&D activities in countries that cannot export technology and mostly import technology.
研究目的
本研究擬以土耳其的實例為焦點, 探討研究與開發 (研發) 的激勵如何影響經濟的增長;具體地說, 研究旨在探討透過不同生產要素所提供的研發激勵所產生的影響存在著什麼差異。
研究設計/方法/理念
為達研究目的, 研究人員構建了一部門內生增長模型。模型內有三個參與者: 公司、消費者和政府。消費者從消費中得到他們所需要的, 提供人力資本, 並參與儲蓄的活動。為了要把利潤的現值儘量提高, 代表公司透過調控投入的數量和研發的承擔, 投資在研發上。公共部門會為研發生產上使用的勞工和資本提供激勵。研究與開發被解釋為一個以內生方式增加全要素生產率的功能。構建的模型是因應土耳其的經濟狀況而調整出來的, 當中也進行了仿真模擬。
研究結果
研究結果暗示, 為研發人員提供的激勵, 而不是物質資本, 更能推動經濟增長。
實務方面的啟示
研究結果, 就如何於研發生產的兩個主要因素之間, 即勞工與資本之間, 分配研發激勵的問題上, 提供了重要的結論;就土耳其而言, 分配給研發人員的激勵是更為有效的。
研究的原創性/價值
我們展示了在新興國家裏, 公共部門提供的研發激勵是重要的, 而在這些國家裏, 剛開始進行研發活動的公司為數不少。在本研究裏, 我們把土耳其當作新興國家看待。我們討論了若要在土耳其使研發激勵更有效地幫助推動經濟增長, 什麼政策是最合適的呢? 因為那些不能把技術出口到其它地方, 而主要靠引進技術的國家均進行相似的研發活動, 所以我們認為討論得來的政策是可應用於所有新興國家的。
Keywords
Citation
Akad, İ. and Değer, Ç. (2023), "Does the distribution of R&D incentive among production factors matter? A dynamic general equilibrium model for Türkiye", European Journal of Management and Business Economics, Vol. 32 No. 5, pp. 586-601. https://doi.org/10.1108/EJMBE-08-2022-0255
Publisher
:Emerald Publishing Limited
Copyright © 2023, İpek Akad and Çağaçan Değer
License
Published in European Journal of Management and Business Economics. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
A productive innovation ecosystem is needed to engage in R&D activities, improve innovation performance and make them sustainable. The innovation ecosystem gets stronger with skilled labor and technology investments. Therefore, it is not a coincidence that innovation performance is higher in developed countries. The effects of R&D expenditures in developing countries do not always yield positive results. The reason for this is that the already limited innovation capacity of developing economies cannot reach the necessary support in terms of relevant institutions and resources (Kleiner‐Schäfer and Liefner, 2021; Wan et al., 2022). According to Aubert (2005), R&D and innovation initiatives in emerging economies get negatively affected by the low level of education and ineffective information infrastructures in those economies. Aubert (2005) claims that this prevents the formation of a powerful private sector, especially in emerging economies while weakening the innovation ecosystem.
Most R&D activities in emerging economies are carried out by the private sector in recent years. The share of Gross Domestic Expenditure on R&D (GERD) in the gross domestic product (GDP) data for selected emerging economies are shown in Figures 1 and 2. These figures support the claim that the private sector leads to R&D expenditures in developing countries.
In emerging economies, where most of the R&D activities are conducted by a weak private sector, an important part of the technology need is met by foreign direct investments (FDI). The impact of imported technology on the innovative performance of emerging countries has been discussed widely in the literature. Most of the studies indicate that technology import made through the FDI channel positively affects innovation performance (Coe and Helpman, 1995; Kokko, 1996; Coe et al., 1997; Liu and Wang, 2003; Sinaniand Meyer, 2004; Salomon and Shaver, 2005; Zhang, 2017). Regarding the effect of technology import on technology production in developing economies, Wang and Kafouros (2009) emphasize that FDIs do not reduce the need for R&D in these countries. Therefore, technology import acts as an input to produce new technologies in developing countries. In other words, the technology export of these countries is based on technology import.
In this study, a growth model for a closed economy, that is, a growth model without technology imports is constructed. The aim is to identify how the public sector should support R&D in an economy that grows with its R&D activities and is not dependent on FDI for growth. For this purpose, an R&D production function has been stated and a growth model in which this production function affects economic growth endogenously has been constructed. In the R&D production function, apart from the final production function, the efficiency of the R&D personnel and R&D capital in technology and innovation production has been determined. The determination of the effectiveness of R&D production factors is important to produce a policy for regulating the distribution of R&D incentives between R&D personnel and R&D capital.
2. Literature review
In the Romer model, which is regarded as the pioneer in the literature of R&D-based growth models, R&D is embedded in an industry that creates a patent and sells it to the intermediate goods sector. This patent, produced by the R&D sector, is used in the production of final goods with human and physical capital (Romer, 1990). In other words, there is a horizontal interaction between the sectors in the Romer model. Following Romer's model, Aghion and Howitt (1990) and Grossman and Helpman (1993) proposed R&D-based growth models. These three models have asserted that the increase in the labor force that will work in the R&D sector will positively affect growth in the long term. R&D has been addressed as a sector producing innovation and patents in the three models. There are similar and opposing perspectives in the literature. For instance, R&D has been modeled as a firm's expenditure to provide resources for innovation and productivity instead of a sector producing innovation and patent (Wakelin, 2001; Coad and Rao, 2010; Ngai and Samaniego, 2011; Coe and Helpman, 1995; Audretsch and Feldman, 1996).
The relationship between R&D expenditures and growth and the effects of R&D incentives at the firm and sector levels have been examined in the literature. We will first summarize the studies on the relationship between R&D expenditures and growth. We will then review the literature on the effects of R&D incentives on firms and the sector, specifically in the third section of the study. Many studies have revealed that R&D expenditures are effective on economic growth. Sample literature showing such studies is presented in Table 1.
Many studies conclude that R&D expenditures generate an increase in TFP and thus economic growth. Hence to ensure economic growth, the R&D activities of the firms are increased. Such activities increase the costs of the firms. To cover costs, public support policies have been developed where a part of the R&D expenditures of the firms are matched by the public. The number of studies modeling the effect of public support policies on economic growth with a theoretical approach is low. In these studies, R&D incentives are generally divided into two categories as direct and indirect incentives, and the effectiveness of these incentives on economic growth is investigated. In the study by Ghosh (2007), a dynamic general equilibrium model with a multi-sectoral endogenous growth model was built to measure the effect of alternative R&D policies, and the model was calibrated with the data ofCanada. The results obtained from the study showed that R&D incentives had a positive effect on the increase in productivity in the Canadian economy. Bye et al. (2009) calibrated a small open economy general equilibrium model calibrated with Norwegian data. It was found that R&D incentives for the formation of capital provided low R&D intensity, but they resulted in growth and an increase in welfare compared to direct R&D incentives. Segerstrom (1991) built a dynamic general equilibrium model with a different approach and divided the firms that carry out R&D activities as innovative firms and firms following these firms as forger firms. It was found in the model that incentives for innovation have a positive effect on growth.
Cheng and Tao (1999) have calibrated a small open economy general equilibrium model by Segerstrom (1991) with Slovenian data. In this study, where R&D has been modeled as an endogenous growth element, two different results emerged in the case of R&D function being linear and convex. In the model with a linear R&D function, the effects of R&D incentives were unclear while in the case of a convex function, the R&D incentives were found to promote production. Bor et al. (2010) have calibrated the dynamic general equilibrium model they constructed for Taiwan and found that public R&D incentives will provide resources for economic growth via technological development and human capital impacts. In this study, it has been investigated which of these incentives is more effective on economic growth in a situation where public R&D incentives are given to R&D personnel and R&D capital in a closed economy.
3. The model
The model has three agents. These are sector-representative firms, consumers and the government. The functional relationships between these three actors in the economic model can be listed as follows:
The consumer maximizes their utility and obtains wages by supplying labor to the firm. A part of this wage is paid for the goods and services provided by the firm. Saving finances capital accumulation and capital income is obtained from the firms in this way. Additionally, income tax is paid to the government, which is the third agent of this model.
The firm maximizes profit. The supply labor by the consumer is equal to the demand of labor by the firm. The firm pays the wage arising from this equilibrium to the consumer. The same situation is valid for capital supply (savings) and the capital demand of the firm. The firm pays the interest rate arising from capital market equilibrium to the consumer as a price for renting. In addition to these payments, a certain percentage of the profit obtained is paid to the public sector as corporate tax. The revenue of the firm is the goods and services purchased by the consumer and the public sector. Another source of income for the firm is the incentives provided by the public sector.
The government funds the incentives and public expenditures with the income tax obtained from the consumer and the corporate tax levied on the profit of the producer.
All supplies and demands are equal for the producer and the consumer in the model. A balanced budget has been ensured with collected taxes, provided incentives and public expenditures.
Numerical solutions of the model have been performed in Dynare (Juillard et al., 1996) run under Octave (Eaton et al., 2012). This software combination offers a numerical solution to dynamic general equilibrium models by including the necessary equation systems after introducing the model's parameters, endogenous variables and exogenous variables to the system. The distinction between endogenous and exogenous variables is quite important in the analysis of the model, for the concepts of endogeneity and exogeneity can directly affect the outcome of the model simulation.
3.1 Firm
The firm aims to increase TFP by making R&D expenditures while maximizing the current value of all profits achieved during its existence. R&D is an endogenous process aiming to increase the productivity of the production in the firm and is defined as follows:
RDt is R&D production at time t; Qt represents the physical capital stock used in R&D; Nt represents the number of labor used in R&D production, and θ is the capital share in R&D production. In the model, the final good production function is in the form of a Cobb–Douglas production function.
Yt represents the final good production amount of the firm, and Kt and Lt represent the physical capital and labor force used in the production of final goods, respectively. α is a parameter indicating the share of capital used in the production of final goods.
It is assumed that the R&D expenditures, RDt, directly translate to TFP, represented via At, as follows:
As in equation 1, Qt represents the stock of physical capital, Nt represents the number of labor and θ represents the share of capital in R&D production. We have notationally replaced RDt and At. Making this substitution in the production function:
where we introduce ψ < 1 as a parameter that indicates that the R&D has diminishing impact on the production of final output. Given these specificaitons, the firm's nominal profit function at time t, is as follows:
3.2 Consumer
The intertemporal utility function of the consumer is based on a constant relative risk a version form as follows:
where ct represents the consumption demand,
The labor supplied by the consumer to the firm, LSt, is exogenous. The labor supply of the consumer is met by the firm's demand and the available labor is employed in two different ways. The firm uses a part of this labor supply in the R&D production (Nt) and the other part in the final good production (Lt). Therefore, the firm makes two different wage payments to the consumer identified through w1t and w2t. The consumer pays an income tax,
3.3 Government
The government finances expenditures, including the incentives it provides to firms, with the taxes it collects. Also, there is no public borrowing and the government budget is balanced. Tax revenues consist of production tax collected from firms and income taxes collected from consumers. The public provides R&D incentives
Income tax collected out of wage income is:
Out of the profits made, tax collection is done as:
3.4 Closure of the model
The model has a balanced government budget:
Regarding the asset market equilibrium, savings done by the consumer finance the physical capital used in the production of final goods and the capital used in R&D activities. That is;
Labor market equilibrium is such that the labor demand by the firm for final output production and R&D activities are met by the consumer's supply of labor. Labor demand is equal to the sum of demand for final output production and R&D activities, i.e. LDt = Lt + Nt. With no demographic dynamics and inelastic labour supply, this demand is equal to an exogenous labor supply, LSt. Hence;
4. Calibration and scenario analysis
The model has been calibrated with the data collected from Türkiye. Model parameters have been calculated by giving hypothetical values to some parameters depending on the data of Türkiye. Data from 2015 were used due to the year being a relatively recent year devoid of economic tribulations. Hence year 2015 is a good candidate for a representative point on a steady state. The basic data of Türkiye for 2015 are shown in Table 2.
Given model calibration, three scenarios are investigated through the numerical solution of the model's steady state. The first scenario considers increasing the R&D capital incentives,
4.1 Scenario 1: Increasing R&D capital incentives while R&D personnel incentives are fixed
Increasing public incentives for the physical capital used in R&D (Qt) reduces the costs incurred by the company while reaching the technologies needed. This can create two different behaviors in the firm, as pointed out by Lach (2002). In his study, Lach (2002) calculated a ratio called the R&D incentives effect for the R&D expenditures that a company can make without R&D incentives and the R&D expenditures made by receiving R&D incentives. According to this ratio, it has been concluded that while R&D incentives increase R&D expenditures in small firms, it creates a negative but statistically insignificant effect on large firms. Hence, there are two possibilities. The R&D incentives will either increase the firm's R&D expenditures or create a crowding-out effect that reduces R&D expenditures ( Lach, 2002). Accordingly, in case of an increase in R&D capital incentives, the first variable to be examined in the model is the interest rate that determines the rental price of the capital. The incentive initially impacts the cost of capital to the firm and thus would change the use of capital in R&D.
Figure 3 shows the steady-state values of r2 for each unit increase of
4.2 Scenario 2: increasing R&D personnel incentives while R&D capital incentives are fixed
In this scenario, R&D personnel incentives are increased while capital incentives are held constant. Such an action would change the relative prices of labor used in R&D and labor used in final output production. For,
This is consistent with the findings of Wallsten (2000). Firms that want to benefit from the support provided by the government increase the price of this production factor by increasing their demand for R&D personnel (Wallsten, 2000). Hence an increased use of labor is likely.
What is the effect of wage increases on capital prices? Factors of production are substitutes, at least to a certain degree. Thus, in addition to a reallocation of labor between alternative uses, capital and labor would be substituted in R&D as well. Figure 5 shows the steady-state values of the R&D capital interest rate in each unit increased by
As can be seen in Figure 5, increasing R&D personnel incentives decreased capital prices. This is a cross effect and it might imply factor substitution. While the wage level increased in the factor market, capital prices have been decreasing.
Incentives for the R&D production factors have different effects on total output. Figure 6 shows the effects of incentives for R&D production factors on total output. Figure 6 shows that the increase in the R&D personnel incentives
The government offers R&D incentives and collects taxes to finance these incentives. One of these taxes is the income tax. Increasing expenditures such as R&D incentives should lead to an increase in income tax rates. Figure 5 shows the effect of increases in incentives, i.e.
According to Figure 7, the increase in capital incentive rates
4.3 Scenario 3: increasing both R&D capital and R&D personnel incentives
Determining the effects of simultaneously increasing incentive rates on capital accumulation and productivity increase are important for the incentive policies to be implemented.
Figure 8 shows in three dimensions the share of R&D capital Q in total output Y in case of increasing capital and labor R&D incentive ratios together. The figure shows the R&D personnel incentive rates on the right vertical axis and the physical capital incentive rates involved in R&D production on the horizontal axis. In Figure 8, the increasing trend of R&D capital is parallel to both incentive rate increases. In other words, with the increase of both incentive rates together, the share of R&D capital in Y has increased.
Figure 9 shows the steady-state values of r2 when
Increases in R&D capital impact R&D production. In Figure 10, the left vertical line shows the incentive rates for the R&D personnel, and the horizontal line shows the incentive rates for the R&D physical capital.
Figure 10 shows the R&D steady-state values when R&D capital and R&D labor incentives are increased together. Looking back at Figure 8, the increase in the numerical value of R&D is similar to the increase observed for R&D capital per output. The increase in the R&D capital would increase the numerical value of R&D, which had similar effects on the total output. These effects are shown in Figure 11, which shows the total output Y in three dimensions in the case of increased incentives for both R&D production factors.
In Figure 11, the vertical line involves the R&D personnel incentive rates and the horizontal line involves the R&D physical capital incentive rates. Increasing incentives for both R&D production factors generate an increase in total output Y.
Remember that Figure 6 shows the final output obtained as a result of the increases made by keeping either capital or labor incentive rates constant in the previous two scenarios. When
In Figure 12, the left vertical line shows the R&D personnel incentive rates and the horizontal line shows the R&D capital incentive rates. Compared to Figure 7, the income tax rate
5. Discussions
In the dynamic general equilibrium model we have set up, it is assumed that firms are engaged in R&D activities. Besides, R&D activities have been handled as a production function and a policy has been designed to increase the efficiency of production factors used in this production function. In the next step, the model has been calibrated with data from Türkiye. Our findings are given in Section 4.
The constructed model has been simulated for three different scenarios and the findings of each of these three scenarios showed that the increase in R&D capital and R&D personnel incentives had a positive effect on economic growth. In which scenario these positive contributions of R&D incentives are more effective is important for both social welfare and efficient use of resources. Therefore, the effects of these three scenarios on both TFP and social welfare should be carefully analyzed. Such an analysis could reveal how the incentives should be distributed between R&D capital and R&D personnel to ensure growth.
The three conducted scenarios have the following implications:
Scenario 1: In this scenario, the incentive rate on capital used in R&D
Scenario 2: In this scenario, the incentive rate on labor used in R&D
Scenario 3: In the last scenario, the incentive rate on capital used in R&D
6. Conclusion
The main result from the analysis of the constructed model is that in Scenario 2, the increase in R&D personnel incentives increased productivity. As a result, it has been concluded that economic growth is more prominent in Scenario 2 than in Scenarios 1 and 3. This result is an expected result, especially for Türkiye as an emerging economy. As Aubert (2005) stated, the shortage of skilled labor in emerging economies hinders the development of R&D activities. Model results support Aubert (2005). The increase in skilled labor, in other words, the increase in human capital accumulation, could accelerate economic growth.
Skilled labor is also important for the development of basic research outputs, which is the most important type of R&D in innovation production. Therefore, Türkiye needs to produce appropriate policies to achieve growth and development goals. These policies should have the potential to affect all segments of society. For example, bringing education to international standards, allocating research infrastructure to universities that are the engines of basic research, and providing necessary support are the most important policies to be followed. In addition to these policies, after providing the necessary basic research infrastructure, it is very important to establish applied research grounds where basic research can be applied. Once these steps are followed successfully, thanks to the high-value-added products produced by Türkiye will get the chance to improve its market share in international markets. In this case, creating an improvement in Türkiye's economic indicators will provide an opportunity to close the gap between developed countries and Türkiye.
Unfortunately, the results could not be compared to other studies in the literature. As far as the authors can determine, the impacts of incentives on R&D and growth are mostly studied in an empirical context supported by econometric analysis. Such studies do not consider incentives provided via factors of production. Therefore, a comparable analysis could not be identified. It could be a fruitful endeavor to conduct modelling studies similar to this one for different countries. The results from countries at different development levels may provide unique policy implications.
Figures
R&D expenditure-growth relationship: sample literature
| Author/Authors | Sample | Method | Results |
|---|---|---|---|
| Mansfield (1972) | USA | Descriptive analysis | Positive effect on economic growth |
| Freire-Seren (2001) | 21 OECD Countries | Panel Regression | Positive effect on economic growth |
| Zachariadis (2004) | 13 OECD Countries | Panel System Estimation | Positive effect on TFP |
| Cameron et al. (2005) | 14 Manufacture Industry from the UK | Equilibrium Correction Model (ECM) and Autodistributed Lag (ADL) | Positive effect on TFP |
| Křístková (2012) | Czechia | Computable General Equilibrium | Positive effect on economic growth |
| Inekwe (2015) | 66 Countries with different income levels | Generalized Method of Moments (GMM) | It has no impact in low-income countries but is positive in middle-high-income countries |
Source(s): Authors' compilation
Calibration data (Türkiye, 2015)
| Symbol | Database | Definition | Amount |
|---|---|---|---|
| C | TURKSTAT (National Accounts) | Household Consumption Data | 1.412 (billion TL) |
| G | TURKSTAT (National Accounts) | Public Expenditure | 325 (billion TL) |
| K | International Monetary Fund (IMF) | Capital Stock | 3.707 (billion TL) |
| r1 | Central Bank of the Republic of Türkiye | Interest rate (average, annual) | 0.094 (rate) |
| Q | TURKSTAT (R&D Accounts) | R&D CapitalStock (Calculated by authors using R&D investment) | 193 (billion TL) |
| L | TURKSTAT (EmploymentDataset) | Employment | 26,621 (thousand, count) |
| w1 | TURKSTAT | The average wage (annual) | 36,159 TL |
| N | TURKSTAT (R&D Accounts) | R&D personnel (full time equivalent) | 122,288 (count) |
| TURKSTAT (R&D Accounts) | R&D Incentives (total) | 8,036 million TL | |
| General Directorate of Budget and Financial Control | Corporation tax (total) | 33,388 million TL |
Source(s): Authors' compilation
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Acknowledgements
This paper is based on a part of İpek Akad's dissertation. Akad received financial support from the International Research Fellowship Program for PhD Students (2214-A) of the Scientific and Technological Research Council of Turkey (TUBITAK). The authors would like to acknowledge TUBITAK for allowing this research work.
Disclosure statement: No potential conflict of interest was reported by the authors.