Time-varying impact of economic policy uncertainty and geopolitical risk on tourist arrivals: Evidence from a developing country

2022 ◽  
Vol 41 ◽  
pp. 100928
Author(s):  
Hongwei Zhang ◽  
Zhuoyu Jiang ◽  
Wang Gao ◽  
Cai Yang
2020 ◽  
Vol 12 (16) ◽  
pp. 6523 ◽  
Author(s):  
Yanhong Feng ◽  
Dilong Xu ◽  
Pierre Failler ◽  
Tinghui Li

Due to multiple properties, the international crude oil price is influenced by various and complex interrelated factors from different determinants in different periods. However, the previous studies on crude oil price fluctuation with economic policy uncertainty (EPU) haven’t taken a wider range of volatility sources into their analysis frameworks. In this paper, the time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model is introduced in order to avoid important information loss, as well as capture the time-varying impact on crude oil price fluctuation by EPU. Furthermore, the differences on crude oil fluctuations from net-oil exporting and net-oil importing country’s EPU are also elaborated. Here are three findings as follows. First, the impacts of global EPU on the crude oil price volatility show time-varying characteristics both in time duration and time-points. Second, the instantaneous impacts of global EPU on the price volatility of crude oil are directly relevant to major events, and the impacts are different in event types as well. Third, the time-varying characteristics depicting the impacts of EPU in countries who are net-oil exporter and net-oil importer on price volatility of crude oil show heterogeneity in fluctuation range, fluctuation intensity, and stage.


2021 ◽  
Vol 9 ◽  
Author(s):  
Yuegang Song ◽  
Yanling Yang ◽  
Jianzhong Yu ◽  
Zhichao Zhao

The outbreak of the COVID-19 pandemic has caused an upsurge economic policy uncertainty (EPU). Study on the time-varying effect of EPU is of substantial implication for the central bank in implementation of monetary policy. To empirically investigate the time-varying effect of EPU, the paper considers the shock of the monetary policy implemented by China's central bank on different economic variables including interest rate, output gap, and inflationary gap using the latent threshold time-varying parameter vector autoregressive model (LT-TVP-VAR Model). Data period is chosen to be January 2015 through April 2021. Our findings show that (i) EPU has a significant threshold effect on the shock of quantitative monetary policy instrument and the shock of price-based monetary policy, and that the two types of policy are positively correlated; (ii) the price-based monetary policy instrument has a significant counter-cyclical effect on both output gap and inflationary gap; (iii) relative to the quantitative monetary policy instrument, the price-based monetary policy instrument has a more significant counter-cyclical effect on output gap; and (iv) a higher level of EPU is associated with a more significant monetary policy effect on output gap and inflationary gap.


Author(s):  
Guangtong Gu ◽  
Wenjie Zhu ◽  
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...  

The modern finance industry is composed of not only numerous financial intermediaries but also internet-based mechanisms which are operated by mobile phone users and online consumers daily. In the coming 10 years, estimates suggest that over half of banks’ functions will likely be replaced by high-tech artificial intelligence. Given the great ongoing shifts in contemporary financial systems, the transmission effects of internet-based finance practices have introduced an important yet unaddressed empirical question on the coupling relationship between the internet finance industry and economic policy uncertainty (EPU). This paper adopts the time-varying parameter vector autoregressive model with stochastic volatility (TVP-SV-VAR) model and novel data from Alibaba Corp. to investigate this relationship. We find: First, the impact of internet-based financial approaches on EPU is greater than the reversal effect, indicating that China’s gross domestic product (GDP) is largely influenced by the online finance industry. Second, the lag impacts are time varying and become stable after 2016, corresponding to the current Chinese government’s long-term strategic plan that emphasizes maintaining the economy’s overall stability. Lastly, additional evidence shows that the online financial approaches are positively correlated with consumers’ behaviors, implying that the online finance industry is gaining its momentum when people are using e-currency rather than real cash. After all, it takes time to observe the real effect of these macro policies. With internet and information technology developing, artificial intelligence is being used in the areas of big data, credit lending, and risk control. This largely reduces the data analyzing cost for internet finance companies and makes risk control more convenient.


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