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Does Enforcement of Intellectual Property Rights Matter in China ...

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system. The variation <strong>of</strong> this <strong>in</strong>dex is substantial: it ranges from 0.85 to 11.07 with a standard<br />

deviation <strong>of</strong> 1.81. The second <strong>in</strong>dex is the prov<strong>in</strong>cial government’s control <strong>of</strong> corrupt practices<br />

(denoted as “Corruption Control” thereafter) <strong>in</strong> the previous year. It has two components: the extent<br />

the local government <strong>in</strong>tervenes <strong>in</strong> bus<strong>in</strong>esses, measured as the time spent by bus<strong>in</strong>esses <strong>in</strong> deal<strong>in</strong>g<br />

with bureaucracy, and the non-tax expenses levied on enterprises, <strong>in</strong>clud<strong>in</strong>g <strong>in</strong>formal charges, any<br />

forms <strong>of</strong> apportionment, and illegal f<strong>in</strong>es from the local government, as a percentage <strong>of</strong> sales.<br />

“Corruption Control” varies from 1.765 to 12.350, with a standard deviation <strong>of</strong> 2.07. A higher value<br />

<strong>of</strong> “Corruption Control” corresponds to a lower level <strong>of</strong> corruption.<br />

In addition, the presence <strong>of</strong> large urban centers or well-function<strong>in</strong>g local universities might<br />

affect the availability <strong>of</strong> external f<strong>in</strong>anc<strong>in</strong>g and R&D <strong>in</strong>vestments for high tech firms. To capture<br />

these effects, we use two control variables: first, the dummy “Metropolis” is one if there is at least a<br />

city <strong>in</strong> the prov<strong>in</strong>ce with over two million <strong>in</strong>habitants; second, the variable “University” is the<br />

number <strong>of</strong> universities <strong>in</strong> the prov<strong>in</strong>ce.<br />

We l<strong>in</strong>k the above prov<strong>in</strong>cial characteristics with the correspond<strong>in</strong>g firm-level data, via the<br />

prov<strong>in</strong>cial locations <strong>of</strong> the firms. There are 27 prov<strong>in</strong>ces and four special districts (Beij<strong>in</strong>g, Tianj<strong>in</strong>,<br />

Shanghai and Chongq<strong>in</strong>g) <strong>in</strong> Ch<strong>in</strong>a. However, three relatively under-developed western prov<strong>in</strong>ces<br />

(N<strong>in</strong>gxia, Q<strong>in</strong>ghai and Tibet) do not have National Innovative and High Technology Industrial<br />

Development zones, so these prov<strong>in</strong>ces do not have high tech companies <strong>in</strong> our sample. Thus, the<br />

total number <strong>of</strong> prov<strong>in</strong>ces/districts <strong>in</strong> our analysis is 28. Panel B <strong>of</strong> Table 1 reports the correlation<br />

coefficients between IP rights enforcement and prov<strong>in</strong>cial-level variables.<br />

4. Empirical Analysis and Results<br />

We report our empirical analyses and results <strong>in</strong> three subsections. We exam<strong>in</strong>e the impact <strong>of</strong> IP<br />

20

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