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

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efore our sample period. They should not directly affect the current f<strong>in</strong>anc<strong>in</strong>g and <strong>in</strong>vestment<br />

decisions <strong>of</strong> the firms <strong>in</strong> our sample.<br />

In Column 3 and 6 <strong>of</strong> Table 2, we report the estimated results from the <strong>in</strong>strumental variable<br />

regressions. Other covariates <strong>in</strong> the first-stage regression are omitted for presentational convenience.<br />

In the first stage, the two <strong>in</strong>struments are significant and positive determ<strong>in</strong>ants <strong>of</strong> IP rights<br />

enforcement. Larcker and Rusticus (2010) demonstrate that when the <strong>in</strong>strument is only weakly<br />

correlated with the endogenous variable, IV methods can produce highly biased estimates even<br />

when the variable is only slightly endogenous. This is the so-called weak-<strong>in</strong>strument problem. In<br />

their survey <strong>of</strong> the weak-<strong>in</strong>strument literature, Stock et al. (2002) develop benchmarks for the F-<br />

statistic; when the number <strong>of</strong> <strong>in</strong>struments is 1, 2, 3, 5, and 10, the suggested critical F-values are<br />

8.96, 11.59, 12.83, 15.09, and 20.88, respectively. If the first-stage partial F-statistic falls below<br />

these critical values, the <strong>in</strong>struments are considered to be weak and the validity <strong>of</strong> <strong>in</strong>ference is<br />

potentially compromised. The reported partial F-test statistics <strong>in</strong> the first stage confirm that<br />

“Christian Colleges” and “British Settlement” are <strong>in</strong>deed strong <strong>in</strong>struments, with an F-statistic <strong>of</strong><br />

513.49 (<strong>in</strong> Column 3) and 2,636.71 (<strong>in</strong> Column 6).<br />

In the second-stage, we f<strong>in</strong>d that the coefficients <strong>of</strong> IPP1 and IPP2 are larger than that <strong>in</strong> the<br />

probit model. Although we cannot directly test whether a s<strong>in</strong>gle <strong>in</strong>strumental variable is uncorrelated<br />

with the error term <strong>in</strong> the regression <strong>of</strong> access to external debt, we can conduct the overidentification<br />

test <strong>of</strong> whether a set <strong>of</strong> <strong>in</strong>strumental variables (IVs) satisfy the exclusion restriction, when the<br />

number <strong>of</strong> <strong>in</strong>struments is greater than the number <strong>of</strong> endogenous regressors (Wooldridge, 2002). The<br />

reported J-statistics from the overidentification test cannot reject the null hypothesis that the two<br />

<strong>in</strong>struments are not correlated with the error term <strong>in</strong> Equation (1), thus the two <strong>in</strong>struments satisfy<br />

24

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