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Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Policy Research Working Paper 6918 Institutions and Firms Return to Innovation Evidence
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Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Policy Research Working Paper 6918 Institutions and Firms Return to Innovation Evidence from the World Bank Enterprise Survey The World Bank Development Research Group Macroeconomics and Growth Team June 2014 Ha Nguyen Patricio A. Jaramillo WPS6918 Policy Research Working Paper 6918 Abstract This paper poses a question: do firms in developing countries not innovate because they are unwilling to? The question moves away from the conventional focus on the obstacles (such as the lack of access to finance) that hinder firms innovation ability. The World Bank s Enterprise Survey is used first to estimate the return to firms innovation across many developing countries, in terms of sales and sales per worker. Then the return to innovation is compared across countries with different levels of institutional quality. In countries with lower institutional quality (specifically, rule of law, regulatory quality, property and patent right protection), the return to firms innovation is lower. This suggests that poor institutional environment lowers firms return to innovation and hence discourages them from investing in researching and adopting new products. This paper is a product of the Macroeconomics and Growth Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at The author may be contacted at The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Institutions and Firms Return to Innovation: Evidence from the World Bank Enterprise Survey Ha Nguyen World Bank Patricio A. Jaramillo George Washington University Key words: Innovation, Institutions, Rule of Law, Property Right Protection JEL Classification: O31, O57. The paper is a part of the World Bank Latin America Economic Policy Sector (LCSPE) s project on Latin America s convergence. We thank the support from LCSPE. We thank Luis Serven, Ufuk Akcigit, Jorge Araujo, Francesco Caselli, Maya Eden, Matteo Iacoviello, Bill Maloney, Ekaterina Vostroknutova, Pluvia Zuniga for very helpful comments and feedback. We thank Maria Ivanova Reyes for her able research assistance. 1. Introduction Firms innovation and technology adoption is widely considered as the key driver to economic growth. Google and Apple are two prime examples in the developed world, where their innovation and new products not only contribute to the economy, but also fundamentally change the way we work, entertain and communicate. Many developing countries, via different means such as foreign direct investment, also try to encourage firms to adopt new technologies and management practices. Yet many firms do not innovate or adopt new technology. In seeking explanations for that, the conventional focuses have been on the obstacles to firms. For example, firms might not have the ability to innovate: they might not have the know-how or access to new technologies 1. Even if they do, they might not have access to finance for the research or the adoption. Girma et al (2008) show that private and collectively owned firms without foreign capital participation and those with poor access to domestic bank loans innovate less than other firms do. In this paper, we do not follow the conventional path to examine the obstacles to firms innovation, but rather, turn our focus to firms incentives to innovate. This angle, although more neglected, deserves more attention in our view. We argue that in many developing countries, firms might not have the incentives to innovate because the reward to innovation is small. For instance, in an environment where property rights are not well protected, a firm s new product can be easily copied 2. This will significantly reduce the return to innovation. Lin et al (2010) use the 2003 World Bank Enterprise Survey of over 2,400 firms in 18 Chinese cities to show that firms perception about property rights protection is positively and significantly related to corporate R&D activity. Another example is that in a monopolized sector, the incumbent might not need to innovate: their products, good or bad, are the only ones available in the market. To make our point, we will proceed in two steps. In the first step, we estimate the return to firms innovation across many developing countries. We measure the quantitative return in terms of sales, and sales per worker. We find that the return is low, which implies that the incentive to innovate is small. In the second step, we compare the return to innovation across countries with different institutional quality. We find that in countries with lower institutional quality (in particular, rule of law, regulatory quality and property right protection), the return to firms innovation is lower. 1 Burstein and Monge-Naranjo (2009) shows that developing countries output can grow significantly when they eliminate all barriers to foreign know-how. 2 In this line, see Branstetter et al (2006). 2 Estimating the return to firms product innovation is not entirely new. Previous studies have tried to measure the sale and employment return to firms innovation, but mostly are limited in a single country. Earlier studies focus on the manufacturing sector in developed countries, such as Van Reene (1997) for the UK, Greenan and Guellec (2001) for France, Hall et al. (2008) for Italy, Guadalupe et al (2012) for Spain. Recent studies start to quantify the return in developing countries, Benavente and Lauterbach (2008) for Chile, Aboal et al. (2011) for Uruguay, and Crespi and Tacsir (2012) for four Latin American countries. The main contribution of this paper is the second step, where we show the return to firms product innovation positively correlates with countries institutional quality. In other words, in countries with lower levels of institutional quality, the return to firms product innovation is lower. This is an interesting result because this suggests that poor levels of institutions depress the return to innovation, and therefore discourage firms to innovate. Related to our findings, Goni and Maloney (2014) find that at the country level, the rates of return from R&D expenditures follow an inverted U: they rise with distance to the frontier and then fall thereafter, potentially turning negative for the poorest countries. The comparison of firms return to innovation across countries in this study is made possible thanks to the World Bank s Enterprise Surveys (ES) -- a firm-level survey of a stratified representative sample of firms. It covers a large set of countries. This survey has been conducted since 2002 and typically answered by business owners and top managers. The survey covers a broad range of business environment topics, including access to finance, corruption, infrastructure, crime, competition, and performance measures 3. Firms are chosen by a stratified random sampling technique, where the strata are firm size, business sector, and geographic region within a country. Firm size levels are 5-19 (small), (medium), and 100+ employees (large-sized firms). In our paper, we focus on product innovation. A firm is understood to innovate if it introduced a new product or service or upgraded an existing product or service. In our data, only firms in the Latin America (LAC) and Eastern Europe and Central Asia (ECA) regions are surveyed about their product innovation. We estimate the percentage change in sales per worker within a firm if it has introduced or upgraded the products or services in the 3 years prior to the survey. The idea is that if a firm innovates, its sales and sales per worker should increase. Ideally one should look at firms profit as the best measure of the return. Unfortunately that is not possible in our study because data on 3 Methodological details can be found at the link below 3 reported profit are much more infrequent than data on sales, and because we are concerned about firms profit underreporting problem. Overall, we found that after a firm innovates, its sales per worker increase by 18%, although the significance is only at the 10% level. Obviously, without the appropriate instrument to capture the exogenous component of product innovation, the results suffer from biases. We will go back to discuss the sources of biases and how we try to mitigate them in more detail in Section 3. We will argue that if the biases are not systematically correlated with countries institutions, the cross country comparison of the institutions impacts -our ultimate interest- is valid. We found that the return to innovation is higher in countries with better institutions. Overall, if a country is ranked 1 percentile higher in the world s rule of law and regulatory quality rankings, the sale return to innovation is about % higher and the sale per worker return is about % higher. This implies that in countries with better rule of law and regulatory quality, the incentive to innovate for firms is higher. We also zoom into two important components to the return to innovation: property right protection and patent right protection. We found that in countries with good property and patent right protection, the return to innovation is also higher, with about the same magnitude. We will go back to these points in greater details. 2. Data and Variables The data are the World Bank Enterprise Survey- a rich firm-level survey database that provides information about firms characteristics such as ownership, size, sector, region in which it is located, annual sales, capacity utilization, employment, competition etc. In order to analyze the change within a firm, we specifically select firms that appear in at least 2 surveys (i.e. we have panel data). In our sample, 6,191 firms appear in two surveys and 256 firms appear in three. There are 44 countries with 6,447 unique firms. The detailed list of countries and firms is in Table A1 in the Appendix. Note that the innovation module in the survey only exists in LAC and ECA. At the end, only LAC and ECA countries remain. The data span from 2002 to The innovation module in Latin America is quite different to that in Eastern Europe and Central Asia. In Latin America (LAC) we use the following question to get data for innovation: During the last three years, did this establishment introduce onto the market any new or significantly improved products? (Yes/No/ Don t know) We define that a firm innovates when it answers Yes to this question. 4 In Eastern Europe and Central Asia (ECA), we use the following two questions in the survey to get data for innovation: Q1: In the last three years, has this establishment introduced new products or services (Yes/No/ Don t answer) Q2: In the last three years, has this establishment upgraded an existing product line or service (Yes/No/Don t answer). We define that a firm innovates when it answer Yes to either of the questions. By doing so, we can harmonize the innovation variables between LAC and ECA and hence can increase the sample size. The downside of this is that in ECA, we will mix the return of an upgraded product and that of a completely new product 4. Of 3,798 observations that answer, 1,855 answer Yes to one of the innovation questions. Figure 1 summarizes the profile of innovating firms by size and by regions. Large firms are more likely to innovate than small firms. Europe and Central Asia firms are more likely to innovate than Latin American firms. Figure 1. Firms Innovation in Emerging Markets Economies (number of observations) Source: Authors calculation based on The World Bank s Enterprise Survey. 4 See Akcigit and Kerr (2010) for a discussion about the innovation implications of completely new products and improve products. 5 We use the following two proxies for firms performance: real sales, and real sales per worker. They are admittedly not ideal measures. The ideal measure should be firms profit. We do not use firms profit here because the data on profit are much spottier, 5 and because firms profit might be underreported in many developing countries. Sales can go up or down with a new product. A new product may cannibalize the business and the profits made from producing the old products when the new products replace and drive out the old products from the market. On the other hand, the new product on the market may compliment the old product. In any case, a successful introduction of a new or upgraded product should increase sales. Between the two measures of sales, in our view, sales per worker is a more precise measure of return to innovation than total sales. A sharper increase in sales per worker implies higher return. Note that a firm can answer Yes to these questions even if the firm just slightly modifies its product, or adopts the new product from overseas. It could also simply copy the product from another domestic firm. As long as the product is new or improved to that firm, the firm can answer Yes to the questions. In that sense, the understanding of Innovation is broader than one usually would think, but the implication to the return to innovation is unchanged: in an environment where a firm can freely copy a product and claim it as a new innovating product, the return to its innovation is not likely high. The return is not high for those that originally come up with the products and nor for those that copy it. Choosing control variables is not straight-forward, we need to find factors that potentially affect firm sales. Besides the change of manager, we found two variables in the questionnaire: whether a firm becomes an exporter between the two waves of the survey, and whether the number of a firm s competitors increases or decreases. We expect that becoming an exporter will boost firms sales and employment, and an increase of competitors will reduce sales and employment. We also include firm 5 In the dataset, a third of firms do not report labor costs, and 60% firms do not report costs on intermediate input and raw material. The vast majority of firms do not report costs on fuel, electricity and water, and rented buildings and equipment. For 438 firms in Brazil, Guatemala and Ecuador that report costs on labor, intermediate inputs and fuel and electricity, the calculated change in real profit is highly correlated with the change in real sales (the correlation=0.96). This suggests that sales measures are acceptable substitutes for profit. 6 size, industry, and country*time fixed effects. The detailed rational and data sources of these variables are discussed in the next section. We use Rule of Law and Regulatory quality to proxy for institutional quality. Rule of law reflects perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Regulatory quality reflects perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. The data are from the Worldwide Governance Indicators (WGI). It is a research data set summarizing the views on the quality of governance provided by a large number of enterprises, citizen and expert survey respondents in industrial and developing countries (Kaufmann, Kraay and Mastruzzi, 2010). We use the property right index by the Heritage Foundation 6 to proxy for property right protection. Property right protection assesses the extent to which private economic activity is facilitated by an effective legal system and rule-based governance structure in which property and contract rights are reliably respected and enforced. For the patent right protection, we use the patent right index from Park (2008). 3. Model 3.1 Model setup The baseline weighted regression is the following: y ijt = α + δd innov ijt + βx ijt + μ jt f j f t + μ s (f s ) + ε it where y ijt = ln y ijt ln (y ijt 1 ) is the dependent variable, and y ijt are sales and sales per worker innov of firm i in country j at time t respectively. D ijt equals 1 if firm i in country j innovates between time t and time t-1. The interactive dummy f j f t captures the macroeconomic conditions for country j at time t. The dummy f s captures the sector fixed effects. X jit are different firm-level control variables. The extended regression (to interact with various institution variables) is the following: y ijt = α + δd innov ijt + μ D innov ijt Ins j + βx ijt + μ jt f j f t + μ s (f s ) + ε it where Ins j is the institutional variable for country j. Note that institutional variables here are timeinvariant. Since the surveys are typically very close together, the institutional quality rarely changes. 6 7 D innov ijt Ins j is the interaction between a country s institutional variables and a firm s innovation. We ultimately are interested in μ. Note that since the data are collected by the stratified random sampling method, all the regressions are weighted accordingly to restore representativeness. In addition, we cluster the standard errors at the country level to capture potential correlations between the error terms, and allow for heteroscedasticity (i.e. having robust standard errors). Dependent variables: - Log of real sales (i.e. sales divided by country s price level) - Log of real sales per full-time employee Explanatory variables: - Innovation: whether a firm introduced products or services or upgraded its product or services in the last 3 years. This is problematic for our regressions if the two rounds of survey are less than 3 years apart. For this reason, we only keep countries that have surveys more than 3 years apart. - Changing manager: if a firm changed its manager between the two waves of the survey. This is to capture potential other restructuring activities besides innovation. There is no direct way to know if a firm changes its manager. We indirectly guess by using the manager s years of experience (as the firms are asked about the manager s experience). We identify if a firm changed it managers by comparing the change in the experience years of the managers and the years between the two surveys. If the change in the experience years is different to the change in years, we conclude that the firm changes its manager. For example, at the first round of the survey in 2005, a firm s manager has 10 years of experience; at the second round of survey in 2009, the firm s manager has 20 years of experience. Since Δyear EXPERIENCE is greater than Δyear SURVEY, we conclude that the firm must have changed its manager between the two rounds of the survey. We acknowledge that there is a possibility that the manager might not remember exactly his or her years of experience. As a robustness check we allow for that possibility by loosening the restriction: only when year EXPERIENCE is greater than year SURVEY +1 or smaller than year SURVEY -1 we can conclude the firm changes its manager. The variable is quite robust: if we follow the original criteria, we find that 3,495 out of 6,447 (54.2%) firms change their managers; if we follow the l
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