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TABLE 7.10 continued Description Variables (1) (2) (3) (4) (5) GDP, PPP (constant 2005 international $) World Bank growth Real GDP chain per worker unit: I$ per worker in 2000 constant prices, PWT 6.2 growth rgdpwok pwt Real GDP per capita (constant prices: Laspeyres) unit: I$ in 2000 constant prices, PWT 6.2 growth rgdpl pwt Real GDP per capita (constant prices: chain series) unit: I$ in 2000 constant prices, PWT 6.2 growth rgdpch pwt Real GDP chain per equivalent adult unit: I$ per eq. adult in 2000 constant prices growth rgdpeqa pwt Kleibergen-Paap rk Wald F statistic 19.72 16.28 16.36 16.36 16.45 Stock-Yogo weak ID test critical values (10 percent maximal IV size) 16.38 16.38 16.38 16.38 16.38 Stock-Yogo weak ID test critical values (15 percent maximal IV size) 8.96 8.96 8.96 8.96 8.96 Stock-Yogo weak ID test critical values (20 percent maximal IV size) 6.66 6.66 6.66 6.66 6.66 Observations 96 97 98 98 98 R-squared 0.212 0.127 0.161 0.162 0.150 Robust standard errors in brackets. *** p
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.
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Public Disclosure Authorized Public
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Th e Urban Development Series discu
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© 2012 International Bank for Reco
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vi ■ CONTENTS Project Appraisal i
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viii ■ CONTENTS Appendix II: Addi
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x ■ CONTENTS 7.4 Tourism Is Coupl
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xii ■ CONTENTS 9.1 How to Organiz
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Exegi monumentum aere perennius reg
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ACKNOWLEDGMENTS ■ xvii Cultural O
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xx ■ OVERVIEW What Are the Object
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xxii ■ OVERVIEW and captures the
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xxiv ■ OVERVIEW periphery, especi
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xxvi ■ OVERVIEW tourism—by impr
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xxviii ■ OVERVIEW 3. Institutiona
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1 Livable Historic City Cores and E
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LIVABLE HISTORIC CITY CORES AND ENA
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2 Investing in the Sense of Place:
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INVESTING IN THE SENSE OF PLACE ■
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0 45° INVESTING IN THE SENSE OF PL
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FIGURE 2.4 continued INVESTING IN T
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A Dubious Alternative: Property Rec
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46 ■ THE ECONOMICS OF UNIQUENESS
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TABLE 4.1 Overview of Hedonic Price
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Boxes, fi gures, maps, notes, and t
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China. See also specifi c cities ac
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public sector role, 222-26, 223b, 2
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Kraay, A., 198 Kratz, C. G., 96 L l
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Pine Ridge Reservation (U.S.), 238
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Shaoxing, China, local residents re
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urban economics appraisal approach,
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ECO-AUDIT Environmental Benefits St
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ECONOMICS UNIQUENESS

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