The article examines the Hong Kong export performance. A standard export demand formulation is used as the benchmark. Then, we investigate the effects of real exchange rate volatility, “third” country competition, domestic wages, and costs of imports from China on export volume. The study models the Hong Kong domestic exports and re-exports separately, compares the performance of exports to the rest of the world, US and Japan, and uses destination-and-export-type specific unit value indexes to construct real exchange rates. It is found that Hong Kong export performance varies across export types and across destinations. In general, Hong Kong exports display mean-reverting dynamics, are positively influenced by foreign income, and are adversely affected by high value of its currency. The lagged export variable, foreign income, and real exchange rate provide most of the explanatory power. The other variables contribute only marginally in explaining the variability of Hong Kong exports.

The linkages between the People’s Republic of China and the other Chinese economies of Hong Kong and Taiwan are assessed, and compared against those with Japan and the US. We first characterize the time series behavior of three criteria of integration, namely real interest parity, uncovered interest parity, and relative purchasing power parity. There is evidence that these parity conditions tend to hold over longer periods between the People’s Republic of China and all other economies, although they do not hold instantaneously. Overall, the magnitude of deviations from the parity conditions is shrinking over time. Amongst all, however, Hong Kong exhibits indications of a more advanced level of integration with the mainland. We also find that evidence is surprisingly positive for integration with the US. We then turn to examining the determinants of the degree of integration. Regression results suggest that the degrees of financial and integration depend upon the extent of capital controls, foreign direct investment linkages as well as exchange rate volatility.

We introduce a time series model that captures both long memory and conditional heteroskedasticity and assess their ability to describe the US inflation data. Specifically, the model allows for long memory in the conditional mean formulation and uses a normal mixture GARCH process to characterize conditional heteroskedasticity. We find that the proposed model yields a good description of the salient features, including skewness and heteroskedasticity, of the US inflation data. Further, the performance of the proposed model compares quite favorably with, for example, ARMA and ARFIMA models with GARCH errors characterized by normal, symmetric and skewed Student-t distributions.

The status of real and financial integration of China, Hong Kong, and Taiwan is investigated using monthly data on one-month interbank rates, exchange rates, and prices. Specifically, the degree of integration is assessed based on the empirical validity of real interest parity, uncovered interest parity, and relative purchasing power parity. There is evidence these parity conditions tend to hold over longer periods, although they do not hold instantaneously. Overall, the magnitude of deviations from the parity conditions is shrinking over time. In particular, China and Hong Kong appear to have experienced significant increases in integration during the sample period. It is also found that exchange rate variability plays a major role in determining the variability of deviations from these parity conditions.

We introduce a time series model that captures both long memory and conditional heteroskedasticity and assess their ability to describe the US inflation data. Specifically, the model allows for long memory in the conditional mean formulation and uses a normal mixture GARCH process to characterize conditional heteroskedasticity. We find that the proposed model yields a good description of the salient features, including skewness and heteroskedasticity, of the US inflation data. Further, the performance of the proposed model compares quite favorably with, for example, ARMA and ARFIMA models with GARCH errors characterized by normal, symmetric and skewed Student-t distributions.