A.: Esto que mencionas sobre garantizar derechos…¿qué implica- implica-ciones tiene el enfoque de derechos ante quizás otro tipo de

The panel structure of our country dataset allows us to estimate the flow determinants of the sites being added yearly to the World Heritage List. The data range from 1978 to 2007, and the number of sites nominated in a given year serves as a dependent variable. We conduct pooled cross-section and random-effects estimations. Another approach used by Bertacchini and Saccone (2012) is to use fixed-effects models to account for cultural and natural endowments. Since fixed-effects models capture all time-invariant influences, including factors unrelated to cultural and natural endowment, such a procedure can only indirectly account for the cultural and natural endowment of a country. It seems preferable to measure cultural and natural potential more directly. Among the factors that remain constant over time are the size of the area and also the number of years of high civilization. The estimates in Table 4.7 indicate that the previous results from the cross-section analysis hold.

estimates concerning the impact of years in the Convention: The number of years a country has been part of the Convention is negatively correlated with the number of new sites a country obtains in a given year. The cross-section estimation suggests that the more years a country had been a member of the Convention, the more sites it had disposed in 2007. The panel estimation results now reveal a decreasing marginal rate of new sites. There may be two reasons for this. First, a country with more years in the Convention has already acquired more sites, so it has fewer potential new sites. Second, with more years in the Convention, there is increasing competition among the countries because in the meantime more countries have joined the Convention. This causes the probability of obtaining a new site in a given year to decrease.

To estimate the influence of the economic and political determinants, we perform neg- ative binomial regressions with random effects (Table 4.7, columns 1–3). This method seems warranted because the likelihood-ratio test indicates that the panel structure is preferred over a pooled estimation. The estimations of the economic and political deter- minants are well in line with the cross-section results. GDP per capita shows a positive and insignificant impact on the number of UNESCO sites inscribed per year. To control for the impact of the media, we use the number of households with a TV. This variable has fewer missing values than that for Internet users (especially for the earlier years). The impact of the media on the number of sites nominated in a given year is positive and statistically significant, as expected. The coefficients of UN Security Council membership are somewhat ambiguous: Although the coefficient of being a permanent member is larger than that of being a rotating member, only the coefficient of being a rotating member is significant. The coefficient of tourist expenditures is again negative and significant.

To address the issue of the reverse causality of the tourism variable, we introduce a one-year lag of relative tourist expenditures (Table 4.7, column 2). It seems unlikely that a site’s nomination in a given year has an impact on the tourist expenditures in the year before. This effect would only occur if a site is expected to be nominated. However, we did not find any evidence in the literature, travel guides, or newspapers that this might be the case. The coefficients of the lagged tourist expenditures confirm the negative and statistically significant correlation with the number of sites a country obtains in a given year. Thus, reverse causality does not seem to be an issue for the tourism variable. In a last step, we introduce federalism (Table 4.7, columns 3 and 6). As in the previous

Chapter 4. The UNESCO World Heritage List 127

Table 4.7: Panel Estimations of the Economic and Political Determinants of Yearly Nom- inated Sites in the World Heritage List 1977-2007 per Country

(1) (2) (3)

GDP -3.25e-05 -2.44e-05 -1.44e-06

(-0.260) (-0.154) (-0.0110)

GDP per capita 0.0200 0.0209 -0.00111

(1.552) (1.504) (-0.0618)

Tourists expend/exports -0.0208** -0.0199

(-2.274) (-1.443)

Lag Tourists expend/exports -0.0180*

(-1.861) TV per HH 0.00962** 0.00810** 0.00992* (2.481) (1.968) (1.705) Gvt spending/GDP -0.00870 -0.00344 -0.00523 (-0.420) (-0.156) (-0.169) # Years UNSC_perm 0.605 0.458 0.752 (1.279) (0.892) (1.422) # Years UNSC_rotating 0.332* 0.326 0.258 (1.769) (1.630) (1.090) Federalism 0.746 (1.446) # Years in Convention -0.0290** -0.0352*** -0.0430*** (-2.464) (-2.697) (-2.737) Size of country 0.0929** 0.112** -0.0387 (2.060) (2.226) (-0.479)

# Years of high civilization 0.000257*** 0.000278*** 0.000400***

(3.300) (3.238) (3.067)

Constant 0.275 0.673 0.418

(0.404) (0.822) (0.415)

Observations 1,344 1,233 672

Number of id 150 147 69

Notes: The dependent variable is a country’s total number of sites nominated in a given year. The coefficients are estimated with negative binomial panel estimations with random effects. The z-values are in parentheses. All regressions refer only to the countries of the World Heritage Convention in 2007. ⋆⋆⋆_, ⋆⋆_,⋆_{denotes significance at the 1%, 5%, and 10% level respectively. Data source: United Nations, World}

section, this variable is associated with a considerable loss in the number of observations. However, in the pooled cross-section estimation, the coefficient again shows positive and significant effects.

The panel regressions (in contrast to the cross-section estimations of the stock de- terminants) are subject to a second issue, which decreases the likelihood of achieving statistically significant coefficients. There is a time lag in the application process. Local politicians need time before a site is accepted on the country’s Tentative List and until it is officially nominated. After that, the Committee needs time to decide on the ap- plications. The duration varies greatly, ranging from 12 months to 8 years, as was the case of Dorset and East Devon Coast (UK) (Leask and Fyall, 2001). No information is available on the length of the nomination process for every particular site; therefore, it is not possible to apply specific lagged independent variables (e.g., for Dorset, a lag of eight years). The estimates shown, therefore, are necessarily an approximation to the time-dependent effect. As a consequence, the estimated coefficients underestimate the various impacts on the number of sites inscribed per year. In general, when controlling for historical, political, and economic determinants, the main results of the cross-section estimations are supported: GDP per capita has a positive effect, tourist expenditures a negative effect, media distribution (in this case the percentage of households with a TV) a positive effect, and being a rotating member of the UN Security Council all have a pos- itive effect on the number of UNESCO sites inscribed per year. All of these coefficients are statistically significant, which indicates that these political and economic factors do influence the composition of the List.