Purpose This study aims to estimate the determinants of international tourist flows between destinations by using the panel gravity model. Design/methodology/approach The multi-dimensional panel gravity model was used to analyse tourism originating from 30 different countries to the 14 most-visited countries in the world between 2008 and 2016. Income (i.e. per capita gross domestic product for both the origin and destination countries), distance between countries, various economic indicators and six dummy variables were added to the gravity model as control variables. Findings The results indicated that tourist arrivals depended mainly on economic factors, i.e. income and trade variables were significant determinants of tourist arrivals. The results also suggested that estimated international tourist flows are a negative function of distance, as is postulated in economic theory. Originality/value In recent years, gravity models have been used frequently to analyse international tourism demand and have demonstrated their ability to evaluate the effects of various determinants of international tourism for many countries. The literature includes studies that used a two-dimensional panel gravity model to analyse the determinants of tourism demand to a single country from many different countries. This study differs in terms of specificity; in that, it relied on a three-dimensional panel gravity model that allowed for modelling of multiple destination countries. As a result, more comprehensive and general results relative to the determinants of tourism demand were obtained. In addition, the application of a non-nested three-dimensional panel data model, which has limited use, contributes a new perspective to the econometric literature.
ÖZET: Ülkelerin ekonomik istikrarı hakkında önemli bilgiler veren reel döviz kurlarının durağanlığını incelemek için son yıllarda oldukça fazla çalışma yapılmaktadır. Reel döviz kurlarının durağanlığını analiz etmek için, serinin hem genel hem de bireysel olarak durağanlığının incelenmesine imkan tanıyan panel birim kök testleri sıklıkla kullanılmaktadır. Genel olarak, makro iktisadi zaman serilerinde bazı yıllarda yapısal kırılmalar olduğu görülmektedir. Bu kırılmalar dikkate alınmadan birim kök testleri yapılırsa; kırılma noktası dikkate alınarak durağan olan bir seride, durağanlığın reddi gibi yanıltıcı bir sonuçla karşılaşılabilinir. Bu çalışmada, 25 OECD ülkesinde Satın Alma Gücü Paritesi teorisinin geçerliliğini sınamak için uygulanan panel durağanlık testleri, yapısal kırılmanın olduğu ve olmadığı durumlarda ele alınmıştır. Sonuçlara göre, yapısal kırılma dikkate alınmadan yapılan birim kök testlerinde sadece 10 ülkede SGP teorisi geçerli iken, kırılmalar dikkate alındığında teorinin ülkelerin tamamında geçerli olduğu görülmüştür. ABSTRACT:In the last years, many studies have analyzed the stationarity of reel exchange rates which gives important knowledge about economic stability of countries. The panel unit root tests which include both pooled and individual unit root tests are used frequently to analyze the stationarity of real exchange rates. Generally, structural breaks issue have taken place in macroeconomic time series for some years. If unit root tests are used without taking account these structural breaks, stationarity hypothesis can be rejected mistakenly. In this study, panel unit root tests with and without structural breaks were used to analyze the validity of Purchasing Power Parity hypothesis in 25 OECD countries. According to the results, while in panel unit root tests with no break, PPP theory is valid for only 10 countries; it is valid for all countries in panel unit root tests with structural breaks.
Bu çalışmada Erzurum kent atmosferindeki hava kalitesinin değişimi; Erzurum'da hava kirliliğinin ilk kez görülmeye başlandığı 1978-1979 kış döneminden başlayarak 2018-2019 dönemine kadar kükürt dioksit (SO2) ve çapı 10 mikrondan küçük partikül madde (PM10) parametreleri kriter olarak alınmış; kent atmosferindeki nispi nem, ortalama sıcaklık, yağış, rüzgâr yönü ve hızı gibi meteorolojik parametreler de göz önünde bulundurularak istatistiksel olarak incelenmiştir. Bu amaçla görünürde ilişkisiz regresyon modellerinden (SUR) yararlanılmıştır. Erzurum kent atmosferinde hava kalitesinin değişimini etkileyecek en önemli faktör 2005 yılında kentsel ısınma amacıyla kullanılmaya başlanan doğal gaz olduğu için bu modellerden elde edilen sonuçların doğal gaz kullanımı ile ilişkisi belirlenmiştir. 2005 yılının ve varsa diğer yılların etkilerinin bir başka ifade ile yapısal kırılma tarihlerinin belirlenmesi amacıyla testler uygulanmıştır. Elde edilen sonuçlar doğal gazın kentte yaygınlaşmaya başlamasından sonraki yıl olan 2006 yılının PM10 modelinde yaklaşık %75 korelasyon ve 2009 yılının ise SO2 modelinde %72 korelasyon ile yüksek düzeyde anlamlı önemli bir yapısal kırılma olduğunu göstermiştir.In this study, the alteration of air quality in the Erzurum urban atmosphere starting from the winter period of [1978][1979], when air pollution began to appear in Erzurum for the first time, until the 2018-2019 period was statistically analyzed by choosing as the criteria parameters sulfur dioxide (SO2) and particulate matter of less than 10 microns in diameter (PM10) and taking into account meteorological parameters such as the relative humidity, average temperature, precipitation, wind direction and speed. Seemingly Unrelated Regression (SUR) models have been used for this purpose. Since the most important factor that will affect the change of air quality in the Erzurum urban atmosphere is natural gas, which was started to be used for urban heating in 2005, the relationship between the results obtained from these models and the use of natural gas was determined. In order to determine the effects of 2005 and other years, if any, tests were firstly applied for determining the structural break dates. The results obtained showed that there was a highly significant structural break with a correlation of aproximately 75% in the PM10 model of 2006, the year after the natural gas became widespread in the city, while it was 2009 for the SO2 model with with a correlation of 72%.
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