Edward Leamer (1983) has argued persuasively that because any econometric analysis involves numerous debatable decisions, findings cannot be convincing unless they are shown to be robust. In the previous section, we already discussed robustness of our estimates to changes in several of the modeling decisions. Here we provide further robustness of parameter estimates to alternative variable definitions and to the inclusion of additional control variables in the estimated fully specified model29.
The first major controversy centers on the use of an appropriate export price index to deflate China’s nominal dollar exports to the real values. In the previous section, we consistently use the Hong Kong export price index as the deflator to define the dependent variable, China’s real exports. Now we use two other alternative deflators, the U.S. CPI and the U.S. import price index of manufactured imports from non-industrial countries.
Columns 1 and 2 of Table 8 show the key parameter estimates for the case of China’s processing exports. The coefficient of the RMB real exchange rate is −0.75, while that of the intra-regional RER flexibility is in the range of −1.08 to −1.33. Columns 3 and 4 show the corresponding results for China’s ordinary exports. The results show that the coefficient of RER is about −0.90, while that of ci RER is very low in magnitudes and wt statistically insignificant when the deflator is the U.S. CPI. Otherwise, all these estimates are statistically significant at any reasonable level. The estimates are within one standard error of the corresponding estimates for the benchmark results that are reported in Tables
29 All the estimates that are reported in this section are one-step system GMM estimators that are obtained under the assumption that RERci and RERw are predetermined (weakly exogenous) in the model. Though the pooled OLS, fixed-effect and differenced GMM estimators are relatively biased for the reasons
explained in the methodologies, the key parameter estimates under these alternative estimators are nonetheless comparable with those of the consistent system GMM estimates.
4 and 5 respectively. In other words, the estimates of the impact of real exchange rate misalignment and of the costs of not having a common currency on China’s exports, particularly the processing exports, do remain robust, regardless of how we deflate nominal dollar value of the exports. The long-run behavior of the model is also unchanged form the benchmark case.
Next, we augment the benchmark models by including a supply shift variable to control for structural break in the estimated relationships and to examine if the estimates of the key parameters are robust to the inclusion of the variable. Since it is difficult to find a good proxy for the supply shift effect, we follow the recent trade literature and use alternative proxies such as real GDP of China, cumulative foreign direct investment (FDI) into China and China’s gross fixed capital formation. It should be noted that all proxies are too endogenous. The study thus uses the lag dated (t−2) of the proxy as an argument in the model. The study does not use China’s capital stock as a proxy, because the variable is both endogenous and measured with much error. Instead, the gross fixed capital formation will be a better proxy, since it is correlated with the capital stock but uncorrelated with the measurement error.
Columns 5 through 10 of Table 8 report estimates of the key parameters of the
augmented model. The results show that the inclusion of proxy for the supply side effect significantly affect the short-run dynamics of the intra-regional RER flexibility between China and the rest of East Asia. But the direction of the effect is invariably downward to be further negative. This is true for both the processing exports and the ordinary exports,
though their magnitudes are different as expected. The findings clearly imply that the benchmark estimates that are reported respectively in Tables 4 and 5 (column 4 in each case) provide a conservative lower-bound limit for the estimates of the key parameters.
The long-run behavior of the model is also unchanged that the long-run effect of intra-regional RER flexibility would be prohibitively high for exports that are produced along the production networks.
In the view of a small sample involving 34 cross-sections and 14 periods, we consistently estimated the autoregressive and distributed lag model of the second order. As we
indicated earlier, the selection of the order of autoregressive and distributed lags is based on the minimization of Akaike’s and Schwarz Bayesian Information Criteria. An
arbitrary first order ADL specification with (or without) the proxy for the supply shift effect causes no change in the short-run dynamics, but only causes the long-run effect of RERw to be −2.87. The key parameter estimates are statistically significant at 1%.
Furthermore, we found that in most cases the more distant lags of the dependent variable, real exchange rates, and real GDP did not cause any significant changes in the estimates of the key parameters, nor in their asymptotic efficiency. Following Grossman and Levinsohn (1989), we also tested separately for the joint significance of different lag lengths based on nested-hypothesis testing. The results also provide general support for the ADL(2,2) model used in the present study.