Dynamic relationships among tourist arrivals, crime rate, and macroeconomic variables in Taiwan

Lee, Jia-Jan; Lee, Yuan-Ming; Huang, Sheng-Ju

doi:10.1080/10941665.2018.1500380

Cited by 14 publications

(8 citation statements)

References 23 publications

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“…In addition, increasing inflation complements tourist arrivals. These results are in line with the existing literature including Levantis and Gani (2000), Lorde and Jackman (2013), Moyo and Ziramba (2013), Giusti and Raya (2019), Lee et al (2018), Sharma and Pal (2020), Karimi et al (2019) and Martins et al (2017).…”

Section: Introductionsupporting

confidence: 93%

Does crime-tourism nexus hold for Pakistan?

Ahad¹,

Anwer²,

Ahmad³

2021

IJOEM

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PurposeThe primary objective of this study is to investigate the linkage of tourism and crime for Pakistan along with exchange rates, terrorism and domestic prices in the presence of structural breaks over the period 1984–2017.Design/methodology/approachThe order of integration is tested through ADF and PP unit root tests. The robustness of unit root test is testified via structural break unit root test. Furthermore, the authors use Bayer and Hanck (2013) combined cointegration test to confirm the existence of a long-term theoretical relationship among the variables. For the robustness of cointegration analysis, the authors also employ ARDL bound testing in the presence of structural break years. Moving forward, the authors apply VECM Granger causality to find out the direction of causality. Subsequently, variance decomposition approach and impulse response function are used to distinguish leader from the followers.FindingsThe unit root test shows that the order of integration is one, I(1). The cointegration analysis confirms the long-run relationship between underlying variables. The authors find inverse and significant impact of crime and exchange rate on tourism in the long run. On contrary, domestic prices play a positive and significant role to determine tourism in short and long run. Also, terrorism is found to be insignificant with negative impact. Further, the bidirectional causality between crime and tourism is observed in the long run. Similarly, unidirectional causality from terrorism to exchange and exchange rate to domestic price is observed in the short run.Originality/valueThe contemporary studies on crime-tourism nexus offer limited evidence, as they frequently suffer from omitted variable bias and ignore possible endogeneity issues. This study uses vector autoregressive models to overcome these biases. Similarly, the authors accommodate the role of structural break years through their analysis. Hence, the results offer more credible evidence. Moreover, the authors contribute to the existing tourism demand literature by adding crime as a potential determinate in case of Pakistan.

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Section: Introductionsupporting

confidence: 93%

Does crime-tourism nexus hold for Pakistan?

Ahad¹,

Anwer²,

Ahmad³

2021

IJOEM

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“…Upon synthesizing quarterly data over 2000:Q1–12014:Q3, Kim and Lee (2017) also identified exchange rate to be playing a significant role in attracting tourists from South Korea to Japan. Similarly, Lee, Lee, and Huang (2018) identified a significant effect of exchange rate variation on the tourism demand of Taiwan. Assaf et al (2018) also found corroborative evidence of significant effect of exchange rate fluctuations on tourist inflows on nine Southeast Asian nations.…”

Section: Literature Reviewmentioning

confidence: 97%

Exchange Rate Volatility and Tourism Demand in India: Unraveling the Asymmetric Relationship

Sharma

Pal

2019

Journal of Travel Research

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This study explores the asymmetric effect of exchange rate volatility on tourism demand in India from January 2006 to April 2018. Tourism demand is captured from a twin perspective—quantity and value. While quantity is represented by foreign tourist arrival in India, earnings from foreign tourists are used to represent value. The study is unique from a methodological point of view as it makes the first ever application of the nonlinear autoregressive distributed lag model of Shin, Yu, and Greenwood-Nimmo (2014), in the tourism demand literature to capture nonlinearity simultaneously in the short- as well as long-run. Results of our analysis show that tourism demand in India responds asymmetrically to both nominal and real exchange rate volatility. Also, the long-run effects of exchange rate uncertainty are shown to be more damaging than the short-run effects. Our findings are fairly robust to alternative specifications.

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“…Therefore, high rates of tourist victimization typically occur at high-crime destinations (Harper, 2001). Thirdly, some tourists are likely to behave abnormally, and because of the change in their routines, they may commit illegal behavior (Lee et al, 2018; Sharpley, 1994). Finally, the absence of capable guardians against a violation—the only element where the government may deter crime (Montolio & Planells-Struse, 2016)—has resulted in the high incidence of crime in tourist areas.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Most studies are based on cross-sectional analyses (Xu et al, 2019), time series (Ho et al, 2017; McPheters & Stronge, 1974), and panel data (Biagi & Detotto, 2014; Grinols et al, 2011; Montolio & Planells-Struse, 2016). Some of the econometric methods in the previous literature include the Granger causality tests (Lee et al, 2018), panel fixed effect model (Rosalina et al, 2015), logistic regression model (Ho et al, 2017), and system GMM (Biagi & Detotto, 2014; Montolio & Planells-Struse, 2016). However, the spatial effect of tourism on crime calls for further investigation.…”

Section: Literature Reviewmentioning

confidence: 99%

Revisiting the Relationship Between Tourism and Crime Based on a Dynamic Spatial Durbin Model

Zhang

Xiang

2021

Crime & Delinquency

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To determine the extent to which tourism development affects crime rate, this study uses a dynamic spatial Durbin model (DSDM) to examine the spatial effect of tourism on crime. Based on a panel data set of 21 cities in Sichuan Province, China, over the 2008 to 2018 period, and after controlling for the interactive effect, the results reveal that tourism exerts a significantly negative impact on crime. This implies that tourism development can reduce crime. Moreover, tourism has a negative spatial spillover effect; thus, increased tourist arrivals decrease crime in neighboring cities. Per capita GDP, wages, unemployment, population density, hotels, scenic spots, and travel agents generate various direct and spillover effects. Finally, we provide policy suggestions.

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Dynamic relationships among tourist arrivals, crime rate, and macroeconomic variables in Taiwan

Cited by 14 publications

References 23 publications

Does crime-tourism nexus hold for Pakistan?

Does crime-tourism nexus hold for Pakistan?

Exchange Rate Volatility and Tourism Demand in India: Unraveling the Asymmetric Relationship

Revisiting the Relationship Between Tourism and Crime Based on a Dynamic Spatial Durbin Model

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