旅游外汇收入

其驱动要素主要包括入境旅游者人数、旅游外汇收入、入境旅游者花费、停留天数等，这些要素之间彼此影响、相互联系。（2）城市目的地响应系统的核心是供给侧研究。

The elements include inbound tourist arrivals , international tourism receipts , inbound tourists expenditures and stay of length . All these elements affect each other and interrelated . ( 2 ) The core of urban destination response system is the supply side study .

在省际层面上运用面板数据模型（PANELDATA），就我国旅游外汇收入对经济的影响进行实证分析。

Using the model of Panel Data , this paper analyses the economic impact of tourism foreign exchange earning in the regions between provincial borders of China .

并以西安市为案例，运用计量经济模型，定量分析了旅游外汇收入对GDP的影响。

Using the model of econometrics , the paper analyzes the spillover effect of international tourism receipt on GDP .

基于30年入境旅游外汇收入的最佳建模与预测

Optimal Modeling and Forecasting on 30 Year Tourism Foreign Exchange Earnings

2000年到2009年十年间，辽宁省旅游外汇收入增长了三倍多。

Since 2000 , foreign exchange earnings in tourism of Liaoning have tripled .

我国国际旅游外汇收入的时间序列预测模型

Model of time series predication for international tourist foreign exchange earnings in China

旅游外汇收入与我国经济发展的关系分析

On the Relationship Between Tourism Receipt of Foreign Exchange and Chinese Economic Growth

1993年1至9月全国旅游外汇收入情况

Jan. -Sep.1993 Nationwide Tourist Revenue in Foreign Currency

云南省的旅游外汇收入增长基本表现为分异，人均国内旅游收入出现了一定的趋同趋势；全省的国际旅游与国内旅游经济增长都存在向低收入、高收入组的趋同。

Yunnan tourism foreign exchange earnings growth performs divergence , and the per capita gross domestic tourism income has the convergence trend .

依据时间序列的平稳性检验可以判定：旅游外汇收入和经济增长两时间序列之间应不是协整的。

Based on the stationarity test of time alignment , it can be determined that there is no cointegration between foreign exchange earnings from tourism and economic growth .

第三部分，构建基于时间序列数据和面板数据的对数线性模型，对影响中国旅游外汇收入影响因素进行实证分析。

In the third part , based on time sequence method , the panel data model , we construct the empirical model analyzing the factors influencing the inbound tourism .

经过二十多年的发展，到2001年，我国旅游外汇收入和接待海外旅游者人数在全球旅游业的排行榜上均已位居第五。

Through twenty years development , we have made the Tourism income and the number of receiving oversea tourists the fifth place by 2010 . While we made such big progress , there comes many problems .

2005年陕西省的旅游外汇收入为4.46亿美元，全省旅游业总收入298.1亿元人民币，均跌出前10位。

In 2005 , the number of Shaanxi 's foreign exchange is 4.46 billion dollar and it is the eleventh in our country ; the number of Shaanxi 's entire province tourism gross income 29.81 billion Yuan .

为了验证人工神经网络模型的可行性，笔者用同样的训练样本分别建立了旅游外汇收入二次曲线模型、指数曲线模型和入境游客三次曲线模型、指数曲线模型。

In order to verify the feasibility of ANN , adopting same training sample the author establishes quadratic curve model and index model of tourism foreign exchange income and cubic curve model and index model of total inbound tourist quantity .

本文共分为四个部分，在第一部分，介绍了研究旅游外汇收入影响因素的背景、意义，以及国内外旅游需求影响因素研究的现状。

This paper can be divided into four parts . In the first part , this paper introduces the background and significance of the research of the factors affecting the tourist foreign exchange income and present situation of the research .

国际旅游（外汇）收入339.49亿美元，比上年增长15.9%。

The income of international travel is33.95 billion , 15.9 % more than that in2005 .

服务贸易稳步发展，入境旅游人数和外汇收入大幅度增加。

Service trade has developed steadily , and the number of inbound tourist arrivals and our foreign exchange earnings from tourism increased considerably .

旅游业向来是外汇收入的重要来源。

Tourism used to be a major source of foreign exchange .

人们怀疑旅游业在增加外汇收入方面所起的作用。

Tourism 's role in increasing foreign currency revenue has been doubted .

要持续提高入境旅游消费，促进外汇收入增长，可以从研究入境旅游消费结构的特点和变化趋势入手。

To improve the inbound tourism consumption and promote the growth of foreign exchange incomes from inbound tourism can optimize consumption structure characteristics and trends start .

从1978-2009年广东省入境旅游人数和旅游外汇收入都居于全国第一。近些年广东省入境旅游的增长速度比较缓慢，出现停滞增长的现象。

From 1978 to 2009 , the international tourist arrivals in Guangdong and the tourism foreign exchange revenues are both the NO.1 . Unfortunately , inbound tourism growth rate becomes slowly and stagnant growth evenly in recent years .

首先阐述马氏链用于预测的基本原理，并对马氏链预测方法加以改进，且应用于辽宁省入境旅游人数及国际旅游外汇收入的预测。第六章，结论与展望。

First , Markov chain describes the basic principle used to predict , and Markov Chain Model to be improved , and applied for tourist arrivals in Liaoning Province and the international tourism foreign exchange earnings forecasts . Chapter ⅵ, Conclusions and Outlook .

入境旅游人数以及旅游（外汇）收入是衡量一个国家旅游实力和开放程度的重要指标。

The number of intry-boundary tourists and tourist incomes of foreign exchange are important indexes .

东部旅游带与西部旅游带旅游外汇收入增长速度的相对差异变化呈下降趋势。

Travel east and west with the Tourism foreign exchange earnings growth rate changes in the relative differences decreased .

2001年，新疆接待国际旅游人数27.3万人次，旅游外汇收入9856万美元；

In 2001 , the region hosted 273,000 international tourists , and earned US $ 98.56 million in foreign exchange .

最后利用修正后的模型对湖北省今后五年的入境旅游需求进行定量预测，着重关注客流量和入境旅游外汇收入。

Finally , the model makes quantitative forecast of inbound tourism demand in Hubei Province in the next five years , focusing on traffic and inbound tourism foreign exchange earnings .

2002年，湖北省国内旅游收入384亿元，比上年增长14%。国际旅游外汇收入2.84亿美元，比上年增长41.4%。

In 2002 , the domestic tourism revenue in Hubei is 38400 million Yuan , while the in-bound tourism revenue is 284 million dollars , increasing 14 % and 41.4 % respectively .

国内入境旅游主要从影响因素、时间特征、空间特征、旅游人数和外汇收入预测等方面展开研究，海南在此方面研究相对薄弱。

Domestic inbound tourism research focus on influence factors and features of time and space characteristics , tourist arrivals and foreign exchange revenue forecast such aspects , hainan research relatively weak .

入境旅游是旅游业发展的重要组成部分，入境旅游人数以及旅游外汇收入是衡量一个国家和地区旅游经济实力的重要指标。

Inbound tourism contributes a lot to the development of tourist industry . The number of inbound tourist and foreign exchange income are important indexes of the strength of national and regional tourist economy .

对基本引力模型进行适当修改，结合主要影响因素构建武汉入境旅游需求引力模型，并用时间序列方法预测了未来几年武汉入境旅游外汇收入和旅游者停留天数变化情况。

Appropriate modification basic gravity model , combining the main influence factors to the entry tourism demand construct wuhan gravity model , using time series prediction years with wuhan tourism foreign currency income and tourists changes stay days .