The business environment
The relationship between innovation and productivity may also be dependent on the business environment in which firms operate. Business environments are predominantly a country-level characteristic, with some variation across industries and regions within an individual country. Thus, in firm-level analysis they are typically subsumed within “fixed effects” in regressions. In order to see how business environments and innovation may combine to affect growth, the next section makes use of cross-country data.
Examining the relationship between innovation and economic performance at the country level poses its own challenges, as many factors will affect a country’s growth and, at the same time, be related to the country’s ability to innovate. In an effort to overcome this problem, the analysis below focuses on the performance of individual industries. It seeks to explain differences between the average rates of export growth of industries with different levels of innovation intensity (as defined in Chapter 1) across various countries over the period 1990-2010.29
The growth rates of industries’ exports can be affected by a number of country-level characteristics (such as macroeconomic conditions or political stability), as well as a number of industry-level characteristics. For instance, industries which cater for consumer demand in emerging markets may grow faster.
In addition, certain industries may grow faster in countries with specific characteristics. In particular, better economic institutions may enable the exports of innovation-intensive industries to grow more rapidly.
Indeed, poor economic institutions – high incidence of corruption, weak rule of law, burdensome red tape, and so on – can substantially increase the cost of introducing new products and greatly increase the uncertainty of returns to investment in new products and technologies. As a result, risk-adjusted returns to innovation may look less attractive when economic institutions are weak. This will primarily affect industries where the introduction of new products and technologies is essential in order to maintain the competitiveness of exports, so firms tend to introduce new products more frequently – in other words, innovation-intensive industries.
The BEEPS results provide some support for this view. Firms that have introduced a new product in the last three years regard all aspects of their immediate business environment as a greater constraint on their operations than firms that do not innovate. Such differences between innovative and non-innovative firms’ perception of their business environment are particularly large when it comes to the skills of the workforce, corruption and customs and trade regulations (as discussed in more detail in Chapter 3).
In order to examine the relationship between the quality of economic institutions and the growth of innovative industries, we can look at growth rates for the exports of various industries in various countries.30 These can be explained by country fixed effects (roughly corresponding to the average growth rates of total exports in individual countries) and industry fixed effects (namely the average growth rates of global exports for individual industries), as well as the initial exports of a given industry in a given country, expressed as a percentage of that country’s total goods exports. In addition, regressions include interaction terms between the innovation intensity of a given industry and a country-level characteristic: either the quality of economic institutions or the level of financial development. A positive and significant coefficient for the interaction term between innovation intensity and the quality of economic institutions would imply that innovation-intensive exports grow relatively fast compared with other exports in countries that have superior economic institutions.
The quality of economic institutions is measured using the average of four of the World Bank’s Worldwide See Kaufmann et al. (2009) for a discussion.”]31[/tooltip] These indicators range from -2.5 to 2.5, with higher values corresponding to stronger underlying economic institutions. Financial development is captured by the ratio of private-sector credit to GDP (as reported in the World Bank’s Global Financial Development Database)32 and primarily reflects the level of development of banking services. In order to see whether these same factors influence the incidence of innovation in advanced economies and emerging/developing economies, the relevant coefficients were allowed to vary between the two groups of countries.33
The results are presented in Table 2.4. They suggest that the exports of innovation-intensive industries do grow faster relative to other exports in countries with stronger economic institutions and that this effect is statistically significant. These estimates also indicate that the impact the quality of institutions has on the relative performance of innovation-intensive exports is greater in emerging/developing economies than it is in advanced economies (where the quality of economic institutions tends to be higher).
In order to understand the magnitude of this effect, we can look at one industry which is in the top 25 per cent in terms of innovation intensity (for instance, pharmaceuticals) and another which is in the bottom 25 per cent (such as basic metals). A 1-standard-deviation improvement in the quality of economic institutions (say, from the level of Albania to that of Poland) will boost the average growth rate of the exports of the more innovation-intensive industry, pharmaceuticals, by an extra 0.35 percentage point a year relative to the growth rate of basic metals. In the case of emerging markets, the extra growth premium for the more innovation-intensive industry stands at 0.95 percentage point a year. This is a sizeable difference, given that the median rate of growth across all industries and countries in the sample is around 8 per cent.
The specifications reported in columns 3 and 4 suggest a similar relationship with financial development, with the exports of innovation-intensive industries also growing faster relative to other exports in countries with higher credit-to-GDP ratios. This reflects the fact that industries that are more innovation-intensive may be more reliant on the availability of credit in order to fund investment in the development of new products (as discussed in more detail in Chapter 4 of this report).
Table 2.4. Determinants of growth in innovation-intensive industries
[1] | [2] | [3] | [4] | |
---|---|---|---|---|
Dependent variable | Industry’s average annual export growth, 1990-2010 (per cent) | |||
Industry’s share in |
-0.176*** |
-0.175*** |
-0.175*** |
-0.175*** |
(0.020) |
(0.020) |
(0.021) |
(0.021) |
|
Innovation intensity * |
0.008*** |
|||
(0.0030) |
||||
Innovation intensity * |
0.013*** |
|||
(0.004) |
||||
Innovation intensity * |
0.022*** |
|||
(0.006) |
||||
Innovation intensity * |
0.007** |
|||
(0.004) |
||||
Innovation intensity * |
0.010** |
|||
(0.004) |
||||
Innovation intensity * |
0.013** |
|||
(0.006) |
||||
Industry fixed effects |
Yes |
Yes |
Yes |
Yes |
Country fixed effects |
Yes |
Yes |
Yes |
Yes |
Number of observations |
3,069 |
3,069 |
3,001 |
3,001 |
Number of countries |
144 |
144 |
140 |
140 |
R2 |
0.501 |
0.503 |
0.500 |
0.500 |
Source: Authors’ calculations using data from UN Comtrade and Feenstra et al. (2005) (exports data), US Bureau of Labor Statistics (deflators, employment), USPTO (US patent grants), and the World Bank’s Worldwide Governance Indicators (ratio of private-sector credit to GDP).
Note: The dependent variable is average annual growth in exports for a given industry in a given country between 1990 and 2010. Export values have been deflated using industry-specific deflators calculated for US industries. As the United States is used to estimate the innovation intensity of industries, it is excluded from all regressions. All regressions include country and industry fixed effects. Data on Worldwide Governance Indicators are averages for the period 1996-2010; data on the ratio of private-sector credit to GDP are averages for the period 1990-2010. Robust standard errors are indicated in parentheses. ***, ** and * denote statistical significance at the 1, 5 and 10 per cent levels respectively.