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The purpose of this paper is to develop a modelling approach that enables the analysis of long-term food security policies. Specifically, the authors explore the effect of China’s agricultural domestic support on its agricultural and food market by also considering the impact of incomplete price transmission.

The authors extend the standard Global Trade Analysis Project (GTAP) modelling framework. First, the authors incorporate incomplete price transmission into the GTAP model by generating tariff-equivalent price transmission elasticities. Second, the authors improve the current representation of China’s agricultural domestic support in the GTAP model and the underlying database by considering the production requirements and the trade-distorting effect of different policy instruments. Running a set of simulations, the authors examine first how the incorporation of incomplete price transmission affects the model’s results and second how increased agricultural domestic support affects China’s agricultural and food market accounting for incomplete price transmission.

Considering incomplete price transmission mitigates the domestic price increases as responses to high international agricultural prices, which also lead to an increase in China’s trade deficit and prohibits net food sellers from receiving high prices. In the long term, an increase in China’s agricultural domestic support to its World Trade Organisation de minimis commitment level would increase domestic agricultural production and reduce its demand pressure on the international market.

This paper contributes to the literature by examining the impact of increased agricultural domestic support on the domestic market while innovatively accounting for incomplete food price transmission. The authors combine econometric estimated price transmission elasticities and an extended GTAP framework to underscore the importance of enhancing the model’s ability in accounting for incomplete price transmission when analysing the impact of agricultural policies.

This paper aims to present and discuss some quantitative results obtained in assessing the economic impact of variations in tourism flows, induced by climate change, for some Mediterranean countries.

Estimates by a regional climate model are used to build a tourism climate index, which indicates the suitability of climate, in certain locations, for general outdoor activities. As climate change is expected to affect a number of variables like temperature, wind and precipitation, it will have consequences on the degree of attractiveness of touristic destinations. The authors estimate the macroeconomic consequences of changing tourism flows by means of a computable general equilibrium model.

The authors found that more incoming tourists will increase income and welfare, but this phenomenon will also induce a change in the productive structure, with a decline in agriculture and manufacturing, partially compensated by an expansion of service industries. The authors found that, in most countries, the decline in agriculture entails a lower demand for water, counteracting the additional demand for water coming from tourists and bringing about a lower water consumption overall.

A great deal of uncertainty affects, in particular: estimates of future climate conditions, especially for variables different from temperature, the relationship between climate and tourist demand, and its interaction with socio-economic variables. This also depends on the reliability of the TCI index as an indicator of climate suitability for tourism, on its application to spatially and temporally aggregated data, on the degree of responsiveness of tourism demand to variations in the TCI. Furthermore, as the authors followed here a single region approach, the authors were not able to consider in the estimates the impact of climate change on the global tourism industry. Nonetheless, the authors believe that a quantitative analysis like the one presented here is not without scope. First, it provides an order of magnitude for the impact of climate change on tourism and the national economy. Second, it allows to assess systemic and second-order effects, which are especially relevant in this context and, moreover, appear to be sufficiently robust to alternative model specifications. In other words, the value added of this study does not lie in the specific figures obtained by numerical computations, but on the broader picture emerging from the overall exercise.

To the authors' knowledge, this is the first study in which, by assessing higher tourism attractiveness into a general equilibrium framework, the effect described above is detected and highlighted.