Note: The reported coefficients are beta coefficients, t‐values in parentheses. The explanatory variables are measured at time t, while the dependent variables are 3‐year changes between t and t+3. The explanatory variables show the share of HGFs in different industries at the same county, by using the 2‐digit input‐out matrix from OECD STAN. Firm controls are log employment, labor productivity and log capital per labor ratio. Standard errors are clustered at the county‐industry (2‐digit NACE)‐year level. The definition of HGF is the 3‐year Birch employment definition.

# 3.2 Which firms benefit?

Examining the heterogeneity of the spillover effects can provide us with some additional insights into the mechanisms behind our previous results and some related policy considerations. We explore this avenue in three ways. First, we study the difference between these relationships for manufacturing and services firms (Table 5). We find evidence of a positive relationship between productivity growth and intra‐industry HGF presence for both groups of firms. Vertical linkages, however, are more important in manufacturing, where all three spillover variables are positively associated with subsequent productivity, employment and sales growth. In services, it is still mainly intra‐industry linkages that matter, with a higher share of HGFs being associated with stronger subsequent productivity growth and higher profitability. These distinctions, however, may capture the different breadths of industries in manufacturing and services, rather than substantive differences between the two groups.

## **Table 5 Main results for Manufacturing and Services**

||**Labor prod**|**Productivity (**<br>**uctivity**|**3‐year change)**<br>**TFP**||
|---|---|---|---|---|
||**Manufacturing**|**Services**|**Manufacturing**|**Services**|
|HGF Downstream share|0.036***|‐0.006|0.059***|‐0.011|
||(4.941)|(‐0.897)|(7.003)|(‐1.209)|
|HGF Upstream share|0.058***|0.002|0.042***|‐0.001|
||(7.779)|(0.388)|(5.245)|(‐0.208)|
|HGF intra‐industry share|0.012*|0.012***|0.002|0.030***|
||(1.842)|(3.205)|(0.250)|(6.220)|
|Region‐Year FE|yes|yes|yes|yes|
|Sector‐Year FE|yes|yes|yes|yes|
|Firm controls|yes|yes|yes|yes|
|Observations|34,300|106,294|34,300|106,294|
|R‐squared|0.188|0.224|0.141|0.182|

Note: The reported coefficients are beta coefficients, t‐values in parentheses. The explanatory variables are measured at time t, while the dependent variables are 3‐year changes between t and t+3. The explanatory variables show the share of HGFs in different industries at the same county, by using the 2‐digit input‐out matrix from OECD STAN. Firm controls are log employment, labor productivity and log capital per labor ratio. Standard errors are clustered at the county‐industry (2‐digit NACE)‐year level. The definition of HGF is the 3‐year Birch employment definition.

Second, we investigate whether the strength of the association depends on the absorptive capacity of the non‐HGFs. We measure the absorptive capacity by the productivity of the firm. More productive firms are more likely to attract the business of rapidly growing buyers or may benefit more from knowledge spillovers because of their better absorptive capacity.

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