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Recognising the significant role of artificial intelligence in the labour market is essential for China to develop sustainably. The research utilises the mixed frequency vector auto-regression (MF-VAR) technique, which would innovatively incorporate data at different frequencies into one model to identify the intricate correlation between the monthly artificial intelligence index (AII) and the quarterly unemployment rate (UR) in China. Through comparison, the MF-VAR method has a more substantial explanatory power than the low-frequency VAR (LF-VAR) model, the impulse responses of the former reveal that AII exerts favourable and adverse influences on UR. Among them, the positive effect occurs on the AII in the first and second months. In contrast, the negative one appears on the AII in the third month, highlighting that artificial intelligence has both stimulating and inhibiting effects on the labour market in China. By analysing UR’s predictive error variance decomposition, the total impact of China’s artificial intelligence technology on employment is a substitution; this outcome is accordant with the theoretical dis¬cussion. In the new round of scientific and technological revolution and industrial transformation, meaningful recommendations for China would be put forward to avert the wave of unemployment brought by the development of artificial intelligence technology. First published online 09 September 2024

This investigation examines the time-varying causality between the exchange rate and the number of the inbound tourism of China using the rolling window estimation. The full-sample causality test suggests no causality between the exchange rate and the number of inbound tourists. However, the parameter stability test revels that this causality is unstable, which suggests that fullsample causality tests cannot be relied upon. Then, we use a time-varying rolling window approach to revisit the dynamic causality, and the results show that the exchange rate has an increasing impact on the number of inbound tourism since 2009, which is consist with the continuous market process of the Renminbi exchange rate. Our result proves that inbound tourists will be more concern about the exchange rate with the expansion of the currency’s trading band. The rolling window test reveals that inbound tourism factors should be taken into consideration by China’s government with the development of the tourism industry and the marketization of the exchange rate.

This paper employs wavelet analysis to examine the relationship between the U.S. output and asset prices. We use the theory of the monetary transmission mechanism to explain the relationship between them. Wavelet analysis takes the simultaneous examination of co-movement and causality into account in both the time and frequency domains. We do find the positive correlation between each two series in the time domain. More specifically, the output and asset prices including oil, stock and house prices exhibit positive co-movement in the most of the sample period. However, the relationship between output and gold prices is a positive correlation for only a few years. From the frequency domain, output and stock, house prices correlate with each other across different frequencies. In addition, output and oil prices correlate at middle (medium run) and higher (short run) frequencies and output and gold prices correlate at higher (short run) frequencies. These findings offer important implications analysing how to apply assets prices to forecast output and analysing periodic variation of economic growth and economical sustainability for policymakers and practitioners.