European Journal of Economics, Finance and Administrative Sciences ISSN 1450-2275 Issue 30 (2011) © EuroJournals, Inc. 2011 http://www.eurojournals.com The Determinants of International Tourism Demand for Egypt: Panel Data Evidence Mohamed Abbas Mohamed Ali Ibrahim Assist. Professor in Economics, Faculty of Managerial Sciences and Humanities Almajmaah University, Saudi Arabia E-mail: email@example.com Abstract Tourism industry has been an important contributor to the Egyptian economy. Egypt is one of the most important tourist destinations in the Middle East and North Africa. The purpose of this study is to recognize the main determinants of the international tourism flows to Egypt. The annual panel data set includes the number of tourist arrivals from most important generating countries during the period 1990–2008, and a number of possible explanatory variables. Keywords: International tourism demand, Panel data, SUR estimators. 1. Introduction Tourism industry effects positively on the economy besides an increase in foreign exchange earnings, and employment opportunities. International tourism arrivals in Egypt increased from 2.6 million in 1990 to 12.8 million in 2008, which represents an average annual growth rate of about 21.5 %. The growth of tourist receipts has been even more spectacular, rising from $ 2.95 billion in 1995 to $ 12.1 billion in 2008 with an average annual growth rate of about 24% (http://data.worldbank.org/indicator/). The direct and indirect effect of travel and tourism in Egypt in 2010 was accounted for 13% of GDP and 2,543,000 jobs (10.9% of total employment). The travel and tourism sector generated $14 billion in export revenue, representing 22% of total exports in 2010, that made tourism, the Egypt's first largest contributor of foreign exchange earnings (WTTC, 2010). Tourism industry is very important to the economy and is identified as one of the major sources of economic growth. Therefore serious attention should be given in studying the factors that affect international tourist arrivals to this country. In this paper, a dynamic demand model for tourism in Egypt is used to identify and estimate the income, tourism price, and trade value elasticities of the tourism demand to Egypt from origin countries. Using a dynamic specification, we inspect the extent to which current tastes are influenced by past consumption behavior. The results obtained may be valuable for helping professionals and policy-makers in the decision making process. The rest of the paper is organized as follows: In Section 2, the tourism data sources are presented and, the main characteristics of demand from the different generating countries are explained. Section 3 focuses on methodology and econometric methods used for estimation while section 4 presents the empirical results and their economic interpretation. Conclusion and policy implication are presented in section 5. 51 European Journal of Economics, Finance and Administrative Sciences - Issue 30 (2011) 2. Tourism Demand Source markets for world international tourism as shown in table 1 are still largely concentrated in the industrialized countries of Europe, the Americas and Asia and the Pacific. However, with rising levels of disposable income, many emerging economies have shown fast growth over recent years, especially in particular markets in North-East and South-East Asia, Central and Eastern Europe, the Middle East, Southern Africa and South America. As shown in Table 1, Europe is the largest source market, in 2008 it was generating 55% of international arrivals worldwide, followed by Asia and the Pacific (20%) and the` Americas (16%). Table 1: Sources of World Tourist Arrivals 1990-2008 1990 2008 From Tourist arrivals* Tourist arrivals* Market share** (%) Market share** (%) (million) (million) Europe 254.2 58 507.2 55 Asia and the Pacific 58.8 13 181.2 20 Americas 99.3 23 151 16 Middle East 8.2 2 32 4 Africa 9.8 2 26.3 3 Origin not specified 7.8 2 21.3 2 World 438 100 919 100 Source: * World Tourism Organization (UNWTO)(2010),Tourism Highlights. ** Computed by the author. As shown in table 2 and figure 1, European international tourism has been increased more than double between 1990 and 2008, where the European tourist arrivals to Egypt reached to 75% in 2008. Asia and pacific represents the next market to Egypt, which represents 13% of the Egyptian tourism arrivals. Table 2: Sources of Tourist Arrivals for Egypt by region(1990-2008) 1990 2008 From Tourist arrivals* Relative Importance Tourist arrivals* Relative Importance (million) (%) (million) (%) Europe 0.881 33 9.621 75 Asia and the Pacific 0.124 5 1.675 13 Americas 0.161 6 0.4 3 Middle East 0.9435 36 0.611 4.7 Africa 0.267 10 0.486 4 Origin not specified 0.2545 10 0.042 0.3 World 2.631 100 12.835 100 Source: *Collected from: WTTC, data export; http://www.wttc.org/eng/Tourism_Research/Economic_Data_Search_Tool/index.php. Ministry of Tourism, Central Agency for Public Mobilization and Statistics and Central Bank of Egypt, Time Series (2008), http://www.cbe.org.eg/ ** Computed by the author. 52 European Journal of Economics, Finance and Administrative Sciences - Issue 30 (2011) Figure 1: Tourist Arrivals share for Egypt by region (1990-2008). Source: Drawn by the author from table 2. Table 3 shows the market share of world international tourism by region in 1990 and 2008. Although the Egypt's market share from the world have been increased from 0.6% in 1990 to 1.4% in 2008. This market share is very small from that can Egypt has. Whenever, Egypt's market share represents only 1.97% from European international tourists. Table 3: The Market Share of Tourist Arrivals for Egypt by region(1990-2008) Market share by region (%) From 1990 2008 Europe 0.35 1.97 Asia and the Pacific 0.21 0.92 Americas 0.16 0.26 Middle East 11.51 1.90 Africa 2.72 1.85 Origin not specified 3.26 0.20 World 0.60 1.40 Source: Computed by the author from table 1 and table 2. This section explains the most relevant characteristics of international tourism demand in Egypt. The volume, composition and recent evolution of tourist flows are investigated by using the number of arrivals of tourists for the period 1990–2008. The aim of this paper is to investigate the international tourism demand of represented by eight countries which we can find data for them in Egypt, and represented 41% of all international tourism arrivals of Egypt with a total of almost 5.38 million international tourists in 2008. The total number of international tourists rose by yearly average of 21.5% between 1990 and 2008. Figure 2 shows The Relative Importance of International Tourist Arrivals by Country of origin for Egypt (1990-2008). Figure 2: The Relative Importance of International Tourist Arrivals by Country of origin for Egypt (1989- 2008). Source: Drawn by the author from table 3. 53 European Journal of Economics, Finance and Administrative Sciences - Issue 30 (2011) Table 4 shows the number of tourist arrivals and the relative importance of each of the origin markets according to 1990 and 2008 data. The traditional tourism markets for Egypt have been Europe region, USA and some Arab Countries like Saudi Arabia and Libya. In terms of composition, it can be observed that international tourism is highly concentrated in a few countries of origin such as Russia, France, Italy, Spain, Germany, United States of America, Saudi Arabia and Libya. Table 4: Tourist arrivals and Market share by country of origin for Egypt (1990-2008) 1990 2008 Country Tourism arrivals Tourism arrivals Market share* (%) Market share* (%) (million) (million) Saudi Arabia 0.1785 6.8 0.402287 3 United states 0.1195 4.5 0.319112 3 France 0.1285 4.9 0.586861 5 Germany 0.1795 6.8 1.202509 10 Britain 0.1800 6.8 1.201859 10 Italy 0.0915 3.5 1.073159 8 Spain 0.0135 0.5 0.156236 1 Switzerland 0.0090 0.3 0.175090 1 Study Group 0.9000 34.2 5.117113 41 other 1.7310 65.8 7.718237 59 Egypt (Total) 2.6310 100 12.83535 100 Source: Ministry of Tourism and Central Agency for Public Mobilization and Statistics, Central Bank of Egypt, Time Series (2008). http://www.cbe.org.eg/ * Computed by the author. Table 5 shows Yearly average growth rates for main markets between 1990 and 2008. What have been observed from the table, that tourist arrivals from European countries achieved high growth rates, ranged between 19.8% for France and 102% for Switzerland. Table 5: Yearly average growth rates of tourist arrivals by country of origin (1990-2008). Country Yearly Average Growth Rate (%) Saudi Arabia 7 United states 9.3 France 19.8 Germany 31.7 Britain 31.5 Italy 59.6 Spain 58.7 Switzerland 102.5 Study Group 27.7 other 18.3 Egypt (Total) 21.5 Source: Computed by the author from table 4. 2.1. Selection of the Variables 2.1.1. Dependent Variable The international tourism demand is often measured either in terms of the number of tourist arrivals, tourist expenditure, and number of tourist nights in the destination country (Ouerfelli, 2008). Data limitations constrain the representation of the dependent variable. In the case of this study, the available data have not permitted the construction of a tourism receipts or number of tourist night’s variables for each of the origin countries. An alternative way of measuring the volume of tourism is to use the number of tourists arriving to Egypt from the eight origin countries that have available data to represent international Tourism demand for Egypt. 54 European Journal of Economics, Finance and Administrative Sciences - Issue 30 (2011) Published articles in the tourism literature have denoted that number of tourist arrivals can be an appropriate indicator of demand for tourism (Ouerfell, 2008; Teresa, 2007; Naude and Saayman, 2005; Dritsakis, 2004; Li, 2004; Song et al., 2003; Song and Witt, 2003; Ten et al. 2002; Kulendran and Witt, 2001; Lim and McAleer, 2001, 1999; Morley, 1998; Gonzalez and Moral, 1995, Witt and Witt, 1995). Data on international arrivals from the eight origin countries for the period 1990-2006 were obtained from the Tourism Statistics published by Central Bank of Egypt. Data for the period 2007-2008 were obtained from the Tourism Statistics published by Ministry of Tourism in Egypt. 2.1.2. Independent Variables The most generally tested independent variables are income, population, relative prices, exchange rates, and transportation costs. In this study, we are going to consider a dynamic specification of international tourism and thus the selected independent variables will be the following: 188.8.131.52. Income The income measure selected in this study is the Real Gross Domestic Product of origin country in per capita terms and was collected from the World Bank Indicator published by World Bank (http://data.worldbank.org/indicator/). We expect that as origin’s income increases, the number of tourist arrivals in Egypt by its residents will increase. Therefore, we expect a positive sign for the estimated coefficient of this variable. 184.108.40.206. Price The selection of a price variable to be included in the study is particularly difficult. For a product similar international tourism, price is combined of several components. The price of goods and services bought in the destination would usually account for a significant part of the total price. The price variable specified in this way combines the effects of prices and exchange rate between destination and origin countries. However, other costs such as transportation to the destination, travel insurance, opportunity cost of travel time may also be significant and can affect totals. In this study tourism prices were described as costs of living in Egypt by the tourists from the origin countries. In explaining this price variable, consumer price indices were used as a proxy for the cost of tourism in destination (Egypt) relative to the cost of living in the origin country adjusted by the exchange rate (Abdul Rahim, K. 2009, Morley, 1993; Carey, 1991; Martin and Witt, 1987). Demand theory hypothesizes that the demand for international tourism is an inverse function of relative prices, i.e., lower the cost of living in the destination relative to the origin country, the greater the tourism demand and vice versa. We therefore expect a negative sign for this variable. Tourism prices, which include the cost of goods and services purchased by tourists in the destination country, are measured by relative prices or real exchange rates (Witt & Martin, 1987; Dritsakis & Gialitaki, 2001). The relative price variable TCPI is given by the indicative ratio of the consumer price indices (CPI) of the destination country to the origin countries. TCPIi,t= (CPIEgypt,t / CPIi,t) Where, CPIEgypt,t is the consumer price index of Egypt in year t, CPIi,t is the consumer price index of origin country i in year t. The relative real effective exchange rate between the destination country and origin countries which measures the effective prices of goods and services in a destination country in relative to origin countries. The relative real exchange rate is given by: RREERi,t = (REER Egypt / REERi,t) (1) where, REEREgypt is the real effective exchange rate in Egypt, REERi,t is the real effective exchange rate in origin country i in year t. We therefore expect a negative sign for TCPI and RREER. Data on real effective exchange rates (REER) and consumer price indices (CPI) for Egypt and origin countries were collected from the World Bank Indicator published by World Bank (http://data.worldbank.org/indicator/). 55 European Journal of Economics, Finance and Administrative Sciences - Issue 30 (2011) 220.127.116.11. Trade Openness International tourism is quite often the generator of international trade flows. Certain the increasing quantity of business travel, particularly in a destination where the economy is greatly driven by international business such as in Egypt, international arrivals could be determined by the level of business activities among the destination and its economic partners. In this study, trade opennes is included in this analysis because arrivals on business purposes consistently made up about 3.6 billion dollar in Egypt in year 2008 ((WTTC, 2010).). For this reason, volume of trade is hypothesized to affect the demand for travel to Egypt and it was therefore contained in the model to help explain demand. The initiative of including this variable in tourism demand analysis in inline with that of Turner et al. (1998), Turner and Witt (2001), Song and Witt (2003) where tourist flows are disaggregated into different purposes of visit, including business visit. Trade openness was measured as the total value of import and export of goods and services between Egypt and the origin country divided by GDP of Egypt: TOi,t = (EXi,t + IMi,t) / GDPt (2) where EXi,t is the export volume between Egypt and origin country i at time t, IMi,t is the import volume between Egypt and origin country i at time t, and GDPt is the Gross Domestic Products in Egypt at time t. Export and import values between Egypt and eight origin country were collected from the World Bank Indicator published by World Bank (http://data.worldbank.org/indicator/). 18.104.22.168. Special Factors A many number of special factors or events may influence the demand for international tourism such as the advertising and marketing expenditure in the origin country, tourist education, security at the destination, and other variables that depend on knowledge of consumer types and motivation. The data on these variables are either unavailable or difficult to measure. Finally, it is important to note that there are two more variables implicitly incorporated in the model. One of them is population, which is incorporated by using it in the denominator of the variables used for measuring income and volume of tourism. The other variable is the exchange rate that has been used for producing the cost of living of origin countries in Egypt. 3. Model Specification and Econometric Method The model constructed in this study is based on the classical economic theory which assumes that income and price factors are probably to play a important role in determining the demand for international tourism. Several empirical studies have found that the conduct of tourists may also be affected by non-economic factors, such as political instability, terrorism and natural disasters (Hisao et al. 2008; Page et al, 2006; Richter, 2003; Wang, 2008). We estimate a model to explain the demand for Egypt international tourism by using data on number of tourists arriving from eight countries from major origin countries. These eight origins are: France, Italy, Spain, United Kingdom, Germany, Switzerland, United States of America and Saudi Arabia. The data set pointed out the annual arrivals during the period between 1990 and 2008 (t=1990, …, 2008). There are several advantages in using this type of data. First, the use of annual data avoids the problems due to seasonality. Second, by using the different origin countries as observational units, an increase in the range of variation of the variables is considered. Finally, the utilization of a pooled time-series/cross-sectional data set enables us to have more degrees of freedom than, and reduce the problem of multicollinearity, hence improving the accuracy of parameter estimates (Garin-Munoz and Martin Montero, 2007; Hsiao, 2003). Accordingly, the estimated demand function for tourism in Egypt involves the following variables; TAi,t = ƒ(POPi,t, RGDPPi,t, TCPIi,t TPi,t, TOi,t, CPITUNISt) (3) where TAi,t is the number of tourists arriving to Egypt from country i during year t, RGDPPi,t is the real gross domestic product per capita in each of the origin country; 56 European Journal of Economics, Finance and Administrative Sciences - Issue 30 (2011) TPi,t is the relative cost of living of tourists in Egypt; TOi,t is the trade volume between Egypt and each of the origin country; and CPITUNISt is the consumer price index in Tunisia to represent the cost of living of a competitive destination country. There are several functional forms that can be used to determine the demand for international tourism. In this study, the model to be estimated would be: log TAi,t = β0 + β1 log POPi,t + β2 log RGDPPi,t + β3 log TCPIi,t + β4 log RREERi,t + β5 log TOi,t + β6 Log CPITUNISt + ξ i,t. (4) 4. Empirical Results and Policy Implications For the estimation of equation (4) we have used E-views econometric software to obtain the Fixed Effects panel estimates of the model by SUR Method. Table 6 shows the results from the estimation. The results of Table 6 show that the model performs satisfactorily. Table 6: Estimation results for the fixed effects model (1990-2008) Dependent Variable: LOG(TA_?) Method: Seemingly Unrelated Regression Date: 02/15/11 Time: 18:18 Sample: 1990 2008 Included observations: 19 Number of cross-sections used: 8 Total panel (unbalanced) observations: 150 Convergence achieved after 110 iteration(s) Variable Coefficient Std. Error t-Statistic Prob. LOG(POP_?) -3.024169 0.311596 -9.705429 0.0000 LOG(RGDPP_?(-1)) 0.508386 0.097546 5.211768 0.0000 LOG(TCPI_?) -1.960031 0.173937 -11.26862 0.0000 LOG(RREER_?) -0.252406 0.065329 -3.863614 0.0002 LOG(TO_?) 0.102635 0.030187 3.399983 0.0009 LOG(CPITUNIS) 5.208612 0.207329 25.12241 0.0000 Fixed Effects (Cross) FR—C -7.783853 IT—C -7.294401 SA—C -11.18668 GE—C -6.098360 SPA—C -9.944474 SW—C -15.71085 EN—C -7.119405 US—C -3.492784 R2 0.874139 Mean dependent var 5.326226 Adjusted R2 0.862108 S.D. dependent var 0.930119 S.E. of regression 0.345389 Sum squared resid 16.22392 Durbin Watson 1.244382 In Table 6, we see the results with the fixed effects estimator. The explanatory power is very high (Adjusted R2=0.862). The explanatory variables are significant at 1% level with expected sign (Log(RGDPP), Log(TCPI), Log(TP), Log(TO), Log(CPITUNIS)), with the exception of Log (POP) which had a negative sign. 57 European Journal of Economics, Finance and Administrative Sciences - Issue 30 (2011) 5. Conclusion and Policy Implication On the basis of an international tourism demand model, we have estimated a fixed effects panel data model for Egypt and are affected by several factors. The purpose of this study is to measure the impact of the main determinants of international tourism flows to Egypt. Therefore, we have a complete panel data set with 150 observations. The empirical results have shown that, most of the variables in the model are statistically significant and consistent with the demand theory. However, the lonely variable is the population that was found to be inconsistent with the demand theory which had a negative sign. One of the main conclusions of the study is the significant value of the lagged real gross domestic product per capita (0.51), which may be interpreted as inelastic. 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