分类： 管理学 >> 人力资源开发与管理 提交时间： 2021-01-30
摘要： This paper investigates the relationship between the service sector and GDP in Denmark by adopting unit root test, Johansen cointegration test and Granger causality test with yearly data. The characteristics of service sector against agriculture sector, industry sector are also discussed. Under the monthly scale, the behaviours of the number of rented hotel room, power production and IPI are studied. The deindustralization caused by the development of tourism and the financial crisis of 2008 is discussed. The existence of periodic sponge effect between tourism and the manufacturing is found. By presenting several convinced explanations, this phenomenon will help to understand the dynamic mechanism of the economic developments. In the context of flexicurity labour market with flexible employment policies in Denmark, the unemployment issue against the tourism, power production and IPI is explored. Lastly, an approach to calculate periodic sponge effect index with some examples of Denmark’s data is proposed.
分类： 统计学 >> 应用统计数学 提交时间： 2021-01-30
摘要： From a modelling perspective, our first contribution is to propose generalised linear regression GARMA (GLRGARMA) model and generalised linear regression SARMA (GLRSARMA) model with a innovative function of explanatory variables in order to extend GLGARMA to incorporate relevant information for model fitting and forecast in tourism area. Besides, the generalised Poisson (GP) distribution is adopted to accommodate over- equal- and under-dispersion for certain tourism data. Moreover, the performance of GLRGARMA model and GLRSARMA model with their nested sub-models are compared and evaluated using several well-known selection criteria. Our second contribution is to investigate the behaviour of tourism data. The pattern of long memory is examined. The analysis of Hurst exponent, ACF plot and periodogram plot shows that Gegenbauer long memory features are presented in tourism data. Furthermore, the distinct characteristics between Gegenbauer long memory and seasonality are demonstrated to reveal the that the GLRGARMA model is more suitable for modelling tourism data. Our third contribution is to derive a Bayesian approach via the efficient and user-friendly Rstan package in estimating our proposed models. For ML approach, the likelihood function is untractable because of involving very high dimensional integrals. Several monitors of convergence of posterior samples are discussed, such as the number of effective sample and bR estimate. The criteria for modelling performance are also derived.
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