flows in Ethiopia, reflecting the importance of last year’s performance on this year’s. This is
in line with the theoretical prediction that tourists are risk averse, preferring to spend holidays
in places that they are already familiar with or they had heard something positive about the
places they plan to visit (Sinclair and Stabler, 1997).
The result shows that a 100% increase
in tourist flows last year leads to a 90% increment this year, which is a very big amount. This
shows the substance of image in the tourism industry: once Ethiopia has entertained
200,000 tourists (which increased from 100,000 of the previous year), our model predicts
that it will entertain 380,000 tourists this year, other things constant. Conversely, if the
number of tourist arrivals drops by 100%, say from 200,000 to 100,000, this year, the
number of tourists next year should drop to 10,000 provided other factors remain constant.
Per capita income of the sending countries, which proxies the ability to pay for tourism of
tourists, is another positive and statistically significant determinant of tourist flows in
Ethiopia. However, the magnitude is very small: a 100% increase (decrease) in per capita
income of the sending countries leads to only 1.3% increase (decrease) in tourist arrivals.
Though it looks contrary to common sense at first sight, it is in line with the reality in SubSaharan Africa where demand for tourism is income inelastic. For example, tourist arrivals in
Sub-Saharan Africa in 2009, when the world economy was hit by global depression, grew by
5 % while negative growth rates were registered in all other regions of the world (UNWTO,
2010). From the two CPI ratios used, the ratio of CPIs of Ethiopia and Kenya is found to be a
statistically significant determinant of tourist flows in Ethiopia. A 100% increase in the
Ethiopia’s CPI to Kenya’s CPI leads to a 44% decrease in the number of tourist arrivals in
Ethiopia. This is in line with the expectation that as Ethiopia becomes an expensive tourist
destination relative to Kenya, many tourists who decided to visit East Africa would prefer
Kenya to Ethiopia. The statistical insignificance of the price differential between Ethiopia and
the sending countries may be explained in a number of ways. First, the ratios are not
exchange rate adjusted ratios. And tourists usually consider in that sense. But, that couldn’t
be done, since it introduces correlation with per capita GDP. Second, an increase in the
price level of the countries, while Ethiopia’s price is constant, will have two different effects.
On the one hand, it increases tourism’s competitiveness with other consumption goods
(substitution effect). On the other hand, it reduces the amount of income the individual has to
spend for consumption. Since tourism is a luxurious commodity, the expenditure on tourism
may be the first that has to be avoided. As a result, an insignificant result may be
theoretically expected (even when the exchange rate adjusted prices are taken). On
average, a country with higher number of population tends to send more tourists, other
things constant. And the result of this study corroborates this argument. A 100% increase in
the total population of the sending countries leads to a 3% increase in the number of tourist
arrivals in Ethiopia.
Not forgetting the caveats, one could get the following impression on the effects of
infrastructural development, distance and being an African from specification 2 and 3.
Urbanization is a statistically significant determinant of tourist flows in Ethiopia . One can see
from specification 2 that infrastructural development determines tourist flows in Ethiopia: a
100% increment in urbanization rate (for example, from the current 16% to 32%) results in a
220% increment in tourist flows to Ethiopia. Though year dummies are important to capture
international trends, tastes and preferences, their exclusion does not seem to induce the
result, as the positive and significant effect is also found in the random effects model. This
demonstrates that infrastructure development is a major determinant of tourist arrivals in
Ethiopia. Distance from Addis to capital cities of the sending countries is found to have
statistically significant effect on tourist flows in Ethiopia, though the magnitude is very small:
a 1000kms increment in distance results in a 0.12% reduction in tourist arrivals (in other
words, a country which is 2000kms far from Addis sends 0.12% less tourists than a country
which is 1000kms far). Finally, African dummy is positive and significant indicating that other
things constant, more Africans visit Ethiopia, most probably due to the presence of African
Union and the United Nations Economic Commission for Africa in Addis Ababa.
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