The Determinants of International tourism

Document Sample
The Determinants of International tourism Powered By Docstoc
					European Journal of Economics, Finance and Administrative Sciences
ISSN 1450-2275 Issue 30 (2011)
© EuroJournals, Inc. 2011

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

     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% (
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

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;
        Ministry of Tourism, Central Agency for Public Mobilization and Statistics and Central Bank of Egypt, Time
        Series (2008),
        ** 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 (%)
                                                           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-

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).
         * 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: 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
( 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. 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
55             European Journal of Economics, Finance and Administrative Sciences - Issue 30 (2011) 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 ( 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. Tourism in Egypt is very
sensitive to prices, according to the selected model, the estimated values for the relative cost of living
of tourists in Egypt (-1.96), the real effective exchange rate has a significant effect with inelastic value
(-0.25), The results confirm the expected negative sign and show that it is significant for explaining the
changes in the number of tourist arrivals. The trade openness has significant and positive impact (0.10)
on the tourism demand in Egypt. Finally, there are competitor destinations that are making major
efforts to improve the quality/price relationship of their products. This is the case of countries like
Tunisia which has high significant estimated value (5.2) which may be interpreted as high elastic.

1]     Abdul Rahim, K. (2009), "Dynamic Model for International Tourism Demand for Malaysia:
       Panel Data Evidence", International Research Journal of Finance and Economics, Issue 33,
       EuroJournals Publishing, Inc.,
2]     Aslan, A et. al (2009), "International Tourism Demand for Turkey: A Dynamic Panel Data
       Approach", Research Journal of Internatıonal Studies, Issue 9 (January, 2009) 65.
3]     Carey, K., (1991),"Estimation of Caribbean Tourism Demand: Issues in Measurement and
       Methodology", Atlantic Economic Journal, 19(3): 32-40.
4]     Central Agency for Public Mobilization and Statistics, Annal Statistics, Cairo, Egypt.
5]     Central Bank of Egypt (2008), Time Series,
6]     Dritsakis, N. (2004),"Cointegration Analysis of German and British Tourism Demand for
       Greece", Tourism Management, 25: 111-119.
7]     Fujii, E. T., & Mak, J. (1981), "Forecasting Tourism Demand: Some Methodological Issues",
       Annals of Regional Science, 15(2): 72–82.
8]     Garín Muñoz, T. (2007), "German Demand for Tourism in Spain", Tourism Management, 28,
9]     Garin-Munoz, T., and Matrin, F. L. (2007), "Tourism in The Balearic Islands: A dynamic
       model for international demand using panel data", Tourism management, 28: 1224-1235.
10]    Gonzalez, P., and Moral, P. (1995),"An Analysis of The International Tourism demand of
       Spain", International Journal of Forecasting, 22(2): 233–251.
11]    Holtz-Eakin, D. (1988), "Testing for individual effects in autoregressive models", Journal of
       Econometrics, 39: 297–308.
12]    Kulendran, N., & Witt, S. (2001), "Cointegration Versus Least Squares Regression", Annals of
       Tourism Research, 28, 291–311.
13]    Lim, C. (1999), "A Meta-analytical of International Tourism Demand", Journal of Travel
       Research, 37(3): 273-284.
14]    Martin, C.A., and Witt, S.F. (1987), "Tourism Demand Forecasting Models: Choice of
       Appropriate Variable to Represent Tourists’ Cost of Living", Tourism Management, 8(3):
15]    Ministry of Tourism, Tourism Highlights, Cairo, Egypt.
16]    Morley, C.L. (1993), "Forecasting Tourism Demand Using Extrapolative Time Series
       Methods", Journal of Tourism Studies,. 4(1): 19-25.
58           European Journal of Economics, Finance and Administrative Sciences - Issue 30 (2011)

17]   Morley, C. L. (1998), "A Dynamic International Demand Model", Annals of Tourism
      Research,. 23(1): 70-84.
18]   Naude, A.W., and Saayaman, A, (2005), "Determinants of Tourist Arrivals in Africa: a Panel
      Data Regression Analysis", Tourism Economics, 11(3): 365-391.
19]   Ouerfell, C. (2008), "Co-integration Analysis of Quarterly European Tourism Demand in
      Tunisia", Tourism Management, 29(1):127-137.
20]   Page, S., Yeoman, I., Munro, C., Connell, J., & Walker, L. (2006), "A case study of best
      practice-visit Scotland’s prepared response to an influenza pandemic", Tourism Management,
      27(3): 61–393.
21]   Richter, L. K. (2003), "International tourism and its global public health consequences",
      Journal of Travel Research, 41(4): 340–347.
22]   Song, H., and Witt, F. S. (2000), Tourism Demand Modeling and Forecasting: Modern
      Econometric Approaches, (1st ed.), Pergamon: Oxford.
23]   Song, H., Witt, S. F., and Li, G. (2003)", Modelling and Forecasting The Demand for Thai
      Tourism", Tourism Economics, 9(4): 363–388.
24]   Song, H., Kevin, F., and Chon, K. (2003), "Modelling and Forecasting The Demand for Hong
      Kong Tourism", Hospitality Management, 22: 435-451.
25]   Tan, Y. F., McCahon, C., and Miller, J. (2002), "Modelling Tourist Flows to Indonesia and
      Malaysia", Journal of Travel and Tourism Marketing, 12(1-2): 63–84.
26]   Turner, L. W., and Witt, S. F. (2001), "Factors Influencing Demand for International Tourism:
      Tourism Demand Analysis Using Structural Equation Modeling", Tourism Economics, 7(1):
27]   Turner, L. W., Reisinger, Y., and Witt, S. F. (1998), "Tourism Demand Analysis Using
      Structural Equation Modeling", Tourism Economics, 4(4): 301-323.
28]   Wang, S. Yu. (2008), "The Impact of Crisis Events and Macroeconomic Activity on Taiwan’s
      International Inbound Tourism Demand", Tourism Management, pp. 1-8.
29]   World Bank Indicator,
30]   World Tourism Organization (UNWTO)(2010), Tourism Highlights, Cairo, Egypt.
31]   World        Travel       and      Tourism       Council      (WTTC),       Data      Export;
32]   World Travel and Tourism Council (WTTC) (2010), Travel & Tourism Economic Impact:
      Egypt, World Travel and Tourism Council, London.

Shared By:
Description: tourism and travel to egypt