The FMLS-based CUSUM statistic for testing the null of smooth time-varying cointegration in the presence of a structural break

Neto, David

doi:10.1016/j.econlet.2014.09.009

Cited by 4 publications

(9 citation statements)

References 10 publications

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“…Neto (2012) employs the residual-based non-cointegration test based on work by Engle and Granger (1987), Engle and Yoo (1987) and MacKinnon (2010). However, Neto (2014) concludes that there is a possibility for under-rejection of the null hypothesis of non-cointegration in the presence of structural breaks. Thus, a FMLS-based CUSUM TVC test developed by Xiao and Phillips (2002) is used.…”

Section: Empirical Approach: Tvc Modelmentioning

confidence: 95%

“…Given that many studies focus on single cointegration relationships, Neto (2012) simplifies the procedure of Bierens and Martins (2010), by focusing on one single cointegration relationship. Based on this approach, Neto (2014) develops an alternative, the cumulative sum (CUSUM) TVC test in case of presenting structural breaks using fully modified least squared (FMLS). This test coincides with the ordinary least squares-based CUSUM test developed in Xiao and Phillips (2002), which is designed for the fixed coefficient cointegration test.…”

Section: Empirical Approach: Tvc Modelmentioning

confidence: 99%

“…In this article, we employ the procedure in line with Bierens and Martins (2010) and Neto (2012, 2014), since the FMLS-based CUSUM TVC test is more robust when there is a possibility of structural breaks. In more detail, the independent variables in the long-run relationship are decomposed into a small numbers of smooth components based on the Chebyshev time polynomials.…”

Section: Empirical Approach: Tvc Modelmentioning

confidence: 99%

“…Several tests may be carried out based on the FMLS estimates of equation (3). First, as noted by Neto (2014), the smooth components will appear non-stationary if the original In GDPCP t and ln RPPP t are I (1)-processes. Second, cointegration tests based on equation (3) can be carried out.…”

Section: Empirical Approach: Tvc Modelmentioning

confidence: 99%

“…The aim of this article is to test the stability of the long-run income elasticity of tourism demand, measured as overnight stays, using the recently developed time-varying cointegration (TVC) model (Bierens and Martins, 2010; Neto, 2012). This model makes it possible to account for possible structural changes (Neto, 2014) and thus complements standard methods of time-varying models such as the recursive coefficient, subsample regressions or Kalman filter approaches. One advantage of the method is that it works without additional unit-root or cointegration tests for the different subsamples.…”

Section: Introductionmentioning

confidence: 99%

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Income elasticity of overnight stays over seven decades

Falk

Lin

2018

Tourism Economics

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This article provides new evidence on the stability of the long-run income elasticity of tourism and travel demand by use of the recently developed smooth time-varying cointegration regression model. The estimations control for relative purchasing power parity of the source country and make use of a specific country dataset where domestic and foreign overnight stays are available over a longer period of time (Switzerland, 1934–2015). Results show that the income elasticity of foreign overnight stays peaks at approximately two in the early 1960s, drops to around one in the early 1980s and from then on remains stable until the end of the sample. Domestic income elasticity reaches its highest levels in the 1930s, then steadily falls towards one in the mid-1960s, and therefrom remains stable until 2015. Different phases in the tourism area life cycle might be a major explanatory factor for variation in income elasticities over time.

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