This research note examines the change in data measurement for international tourist arrivals to the United States due to the requirement that all tourists must complete the INS I-94 entry form and its impact on tourist arrivals in the aftermath of the September 2001 terrorist attacks. Using fractional integration techniques, we find that the majority of tourist arrivals from various regions around the world are mean reverting, but the degree of persistence increased in the post-September 2001 period.
ApergisNMervarAPayneJE (2017) Forecasting disaggregated tourist arrivals in Croatia: Evidence from seasonal univariate time series models. Tourism Economics23: 78–98.
2.
AssafAGBarrosCPGil-AlanaLA (2011) Persistence in the short- and long-term tourist arrivals to Australia. Journal of Travel Research50: 213–229.
3.
BaiJPerronP (2003) Computation and analysis of multiple structural change models. Journal of Applied Econometrics18: 1–22.
4.
BloomfieldP (1973) An exponential model in the spectrum of a scalar time series. Biometrika60: 217–226.
5.
ChuFL (2008) A fractionally integrated autoregressive moving average approach in forecasting tourism demand. Tourism Management29: 79–88.
6.
CunadoJGil-AlanaLAPerez de GraciaF (2005) The nature of seasonality in Spanish tourism time series. Tourism Economics11: 483–499.
7.
CunadoJGil-AlanaLAPerez de GraciaF (2008a) Fractional integration and structural breaks: Evidence from international monthly arrivals in the USA. Tourism Economics14: 13–23.
8.
CunadoJGil-AlanaLAPerez de GraciaF (2008b) Persistence in international monthly arrivals in the canary islands. Tourism Economics14: 123–129.
9.
CunadoJGil-AlanaLAPerez de GraciaF (2011) Modelling international monthlytourist in Spain. Estudios de EconomiaAplcada29: 723–736.
10.
DickeyDAHaszaDPFullerWA (1984) Testing for unit roots in seasonal time series. Journal of the American Statistical Association79: 355–367.
11.
Gil-AlanaLA (2005) Modelling international monthly arrivals using seasonal univariate long-memory processes. Tourism Management26: 867–878.
12.
Gil-AlanaLA (2008) Fractional integration and structural breaks at unknown periods of time. Journal of Time Series Analysis29: 163–185.
13.
Gil-AlanaLA (2009) Americans traveling to Europe: A new perspective based on persistence. Tourism and Hospitality Research9: 3–8.
14.
Gil-AlanaLA (2010) International arrivals in the canary islands: persistence, long memory, seasonality and other implicit dynamics. Tourism Economics16: 287–302.
15.
Gil-AlanaLA (2011) Tourism in South Africa-time series persistence and the nature of the shocks: are they transitory or permanent?. African Journal of Business Management5: 4686–4698.
16.
Gil-AlanaLACunadoJPerez de GraciaF (2008) Tourism in the canary islands: Forecasting using several seasonal time series models. Journal of Forecasting27: 621–636.
17.
Gil-AlanaLACunadoJPerez de GraciaF (2014) Persistence, long memory, and seasonality in Kenyan tourism series. Annals of Tourism Research46: 89–101.
18.
Gil-AlanaLAMervarAPayneJE (2015) Measuring persistence in Croatian tourism: Evidence from the Adriatic region. Applied Economics47: 4901–4917.
19.
Gil-AlanaLAMervarAPayneJE (2016) Modelling the degree of persistence in Croatian tourism. Tourism Economics22: 655–664.
20.
Gil-AlanaLAPerez de GraciaFCunadoJ (2004) Seasonal fractional integration in the Spanish tourism quarterly time series. Journal of Travel Research42: 408–414.
21.
HyllebergSEngleRFGrangerCWJ (1990) Seasonal integration and cointegration. Journal of Econometrics44: 215–238.
22.
RobinsonPM (1994) Efficient tests of nonstationary hypotheses. Journal of American Statistical Association89: 1420–1437.
23.
SongHLiG (2008) Tourism demand modelling and forecasting: A review of recent research. Tourism Management29: 203–220.
