human capital and the capacity of firms to absorb technology account for 23 percent and 20 percent, respectively, of the model’s goodness of fit.

More interestingly, however, is the fact that horizontal factors that in principle affect overall firm performance and the accumulation of any type of capital (not only knowledge capital) also matter as determinants of innovation performance: results from Figure 7 suggest that _Institutions, Infrastructure_ and _Market Sophistication_ pillars account, together, for a substantial part (34.7 percent) of the explained variance of the model.<sup>9</sup> This reinforces the idea presented by Cirera and Maloney (2017) that complementary factors of the business environment - that go beyond specific barriers to innovation - are key to improve the performance and returns to innovation. These factors are normally neglected in the advanced country literature because markets in high-income countries function normally well, but this is not necessarily the case in middle- and low-income countries.

Table 1 below displays how developing East Asian countries covered by the GII data set perform in terms of all enabling factors. The country’s performance in each pillar is measured relative to the pillar’s median value in the global sample (of the GII data) and the expected level of the country’s performance in that pillar given its income level (measured in GDP per capita). Countries whose observed values of pillars are below both the median and the predicted value are marked as one. The enabling factor where this set of countries mostly underperform is _Institutions_ ; of the seven developing East Asian countries included in the above-mentioned data set, six underperform in this domain; the exception is Malaysia.<sup>10</sup> After _Institutions_ , _Business Sophistication_ and _Human Capital_ stand as the worst performing pillars: four of the seven developing East Asian countries covered by the GII data set present a deficit in these two domains.

**Table 1. How developing East Asian countries perform in terms of overall innovation enabling factors, 2017**

|**Country**|**Institution**<br>**s**|**Human**<br>**capital**|**Infrastructure**|**Market**<br>**sophistication**|**Business**<br>**sophistication**|
|---|---|---|---|---|---|
|Cambodia|1|1|1|0|1|
|China|1|0|0|0|0|
|Indonesia|1|1|1|0|1|
|Malaysia|0|0|0|0|0|
|Philippines|1|1|0|1|0|
|Thailand|1|1|1|0|1|
|Vietnam|1|0|0|0|1|

Source: Own elaboration based on GII dataset and WDI dataset.

Note: a value of 1 indicates a variable where the country is below the median country AND below the level predicted by its GDP per capita. The median value (for each variable) is calculated within the 127 countries covered under the GII survey.

To shed light on more granular aspects that might be driving these results, Table 2 focuses on the components under the _Institutions_ pillar: _Political environment_ , _Regulatory environment_ and _Business environment_ . Results suggest that _Regulatory environment_ – encompassing regulatory quality, rule of law, and cost of redundancy dismissal - is the key obstacle for innovation across developing East Asian countries covered in the GII data set; all of them have a deficit in this

> 9 The remaining 7.5 percent of R2 comes from GDP per capita.

> **10** But in this case the country underperforms in relation to the predicted level but not in relation to the median value of all countries.

9