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Abstract

In this paper, we demonstrate that using finite sample correction bootstrapping techniques is advisable in samples that cover less than two complete business cycles, even when high-frequency data seemingly provide a sufficient number of observations to overcome the small sample bias. This is particularly relevant in the current research environment. Because the recent financial crisis is considered as a structural break, research on current problems is often conducted using post-crisis data. That is, the available samples cover only a few years of data, often spanning only one business cycle or even less. We provide ample simulation-based evidence that samples of daily or monthly dynamic data covering periods of this magnitude are prone to a fairly substantial bias. Moreover, we are able to show that standard bootstrap-based bias correction techniques still work in those cases.

Abstract

This paper examines the impact of cultural distance in general and the Confucius Institute Network in particular on cross-border flows of tourists, goods and investment in and out of China. We estimate a panel gravity model of inbound and outbound flows between 2004 and 2012. We find that the  presence of Confucius Institute(s) in the source country increases inbound tourism and equity flows and outbound export and FDI flows for China, while other measures of cultural distance have less of an impact.