ECONOMICS UNIQUENESS

UNESCO WORLD HERITAGE LIST, TOURISM, AND ECONOMIC GROWTH ■ 209
Notes
Th e authors wish to thank Daron Acemoglu, Th omas Chaney, Decio Coviello, Pierangelo
De Pace, Fuad Hasanov, Camelia Minoiu, Xavier Sala-i-Martin, and James Stock
for stimulating discussions and helpful comments. We also thank Mileva Radisavljević
and Latoya McDonald for editorial assistance. All remaining errors are ours.
1. Th e coeffi cient of correlation associated with fi gure 7.1 is equal to 0.27.
2. We further discuss the relevance of exploiting the “between” rather than the “within”
variation.
3. We use diff erent normalizations, including population in 1980 and surface area. We
also use an additional instrument based on the kilometers of coastal area.
4. More and more tourism brochures use the label WHL to advertise for a destination.
We further disentangle the “advertising eff ect” from the “testimony eff ect” by using
the “fl ow” of sites added rather than the “stock” of sites in a given year when using
fi rst-diff erences.
5. Sites are dated according to their century of creation. Where specifi c dates are unavailable,
sites are dated according to the corresponding civilization’s period of peak
infl uence.
6. Note also that some sites are historic markets or harbors that still have an economic
relevance.
7. We use diff erent methodologies to defi ne voting coincidence amongst all UN General
Assembly votes, as shown in table 8.2. Th acker (1999) codes votes in agreement as 1,
votes in disagreement as 0, and abstentions or absences as 0.5. Barro and Lee (2005)
use the fraction of times a country votes in accordance with the country of interest
(either both voting yes, both voting no, both abstaining, or both absent). Kegley and
Hook (1991) compute a similar fraction but disregard abstentions and absences. See
Dreher and Sturm 2006 for data and a more detailed discussion of these diff erent
methodologies.
8. We also looked at countries that have been under UN embargo or the target of sanctions.
We fi nd that overall these countries have a number of sites greater than the
median.
9. A controversy has emerged surrounding the creation of such areas and the resulting
rural population displacement and associated land tenure insecurity.
10. Tourism arrivals are also available from World Tourism Organization. However, the
economic impact of tourism arrival can diff er radically depending on the source and
destination countries of tourism (that is, regional versus international tourism). Th e
focus of this chapter being to quantify the impact of international tourism specialization
on economic growth, we use tourism receipts to be able to measure the reliance
of a country on tourism in its exports of goods and services. For robustness, we also
defi ne Tourism as the average of tourism receipts as a share of GDP and obtain similar
results.
11. Taking the average of tourism receipts over the whole period instead of the fi rst ten
years yields similar results.
12. For example, Sala-i-Martin et al. (2004) determined a ranking of variables according
to their signifi cance in growth regressions using a Bayesian averaging methodology.
Th e independent variables we chose are based on the top fi ve variables of this list.