Abstract
Is climate change pushing governments to implement international treaties for the management of common resources? Yes, at least with respect to the Water Treaties (WTs) on common basins and rivers studied in this article. We found that climatic conditions, such as higher temperatures and lower precipitation, directly lead to a higher likelihood of signing WTs in the short, and even more so in the long run. By analyzing the impact of changes in climatic conditions observed between 1961–1975 and 1993–2007, we found that a one-degree Celsius increase in temperature has resulted in a 16.6% increase in the likelihood of signing WTs. These results are obtained for treaties related to environmental protection and economic development, and they also hold for “strong” treaties.
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Notes
The literature on water scarcity indicators (also called indicators of “water pressure”, “water stress”, “water capability”) is vast, however often limited to recent years (see for instance Gain et al. 2016, Rosa et al. 2020, Vallino et al. 2020) due to the lack of historical data. Indeed water scarcity, which can be defined simply as a situation where freshwater demand exceeds its availability, turns out to be very difficult to compute once we consider the multidimensional factors that affects both the demand, the access and the availability of freshwater. Candau et al. (2022) provides a sophisticated indicator of water scarcity at a very disaggregated geographical scale, but it is unfortunately only available for the year 2000 due to a lack of data.
More precisely called the Convention on the Protection and Use of Transboundary Watercourses and International Lakes.
The database on WTs states that “it is not clear if this treaty ever entered into force”.
See also Zawahri et al. (2014) that analyze treaties according to their content in order to study the factors influencing treaty design.
Cooperation can be boosted by the level of development or by the specialization of countries.
We only use indicators of water scarcity as a control because these indicators often have limitations in terms of the number of countries and the number of years. For example, the data in the FAO database, Aquastat, are four-year average measures of water stress and are available for only a handful of countries in the 1960 s (and even in the 1970 s).
In an online appendix (see Candau and Gbandi 2022), we relax this specification with fixed effects and add political and economic variables (such as the presidential election one year before the signing of a treaty, the common political regime between the partners, past conflicts between the countries, economic interdependence as measured by international trade, etc.).
See “Appendix 1” for the list of countries.
This database has been produced by the Oregon State University, additional information can be found at: http://www.transboundarywaters.orst.edu.”
The database is constantly updated and a new database is coming (summer 2023) with more than 100 treaties translated into English.
The number of bilateral combinations per treaty is given by the following combination (without double counting): \(C_{n}^{2}=\frac{(n!)/((n-k)!)}{2}\), with \(n\ge 2\) and \(k=2\); n designing the number of countries engage in a cooperation on water resources, and k is the number of countries in a dyad.
Not reported here, we have also estimated our baseline equation by considering a sample where all the possible dyads in each continent were considered (and not just dyads that share a basin). We find similar result with this sample, but further investigations may be interesting in order to better understand how managing freshwater resources may have effects beyond the river/lake basins. As such, a country not close geographically, but indirectly affected by resource depletion, may have an incentive to enter into an agreement.
Indeed, unlike the previous version of PRIO, this newest database accounts for dyads that share river basin without sharing a border.
A mean temperature is generated with these maximum and the minimum temperatures.
These regions are often specialized in agriculture and/or are the location of large cities. Therefore, in these regions flooding or drought often have serious consequences that are also largely mediatized at the national level. Weather fluctuations in these regions can thus have political implication at the national level. We also rely on climate variables built on the countries’ total surface as robustness checks.
Available on request at https://www.emdat.be/.
Though not reported here, we also verify that these variables still have a similar effect when taken separately (for instance, the coefficient of temperature in country i equals 0.0099 (significant at 5%) and that of precipitation in i equals \(-\,\)0.023, also significant at 5%).
In an online Appendix (see Candau and Gbandi 2022), we also analyze to what extent these weather variables have a non-linear effect on the signature of WTs.
See for instance Battaglini and Harstad (2020) who propose a model explaining under which conditions strong or weak treaties are negotiated. They assume that politicians focus on their probability to be elected (or re-elected) and then chose strategically the content of international treaties to win votes accordingly.
We have carried out several other estimations not reported here. For instance, by considering treaties with fewer than thirty signatories, we find that temperature and precipitation are significant, while this result does not hold for a number of members above this threshold.
More precisely we exclude: Albania; Austria; Belgium; Bosnia and Herzegovina; Bulgaria; Croatia; Denmark; Estonia; Finland; France; Germany; Greece; Hungary; Italy; Latvia; Lithuania; Luxembourg; Netherlands; Norway; Poland; Portugal; Republic of Moldova; Slovakia; Slovenia; Spain; Sweden; Switzerland; Ukraine.
It is worth noting that this approach serves to overcome the limitations of cross-sectional approaches. Indeed, in comparison with the literature where the averages of different variables are taken over a long period of time with the risk of bias due to omitted variables, here the estimates are immune to time-invariant omitted variables by long differentiating. Furthermore, in comparison with the FE model presented in (2), coefficients \(\alpha\), \(\beta\) and \(\mu\) are estimated from long-term changes in average conditions instead of year-on-year changes and can thus be used to take into account the adaptation of governments to signing WTs.
See for instance the New York Times article of Stevens (1998).
The distinction between the content (development or environmental issues) and the nature (weak or strong) of treaties may, however, be related. For instance, Battaglini and Harstad (2020) argue that weak treaties are more numerous when they concern environmental issues than when they are related to security issues.
To select these contents, we use the “Issue Area” column of the International Freshwater Treaty Database that identifies, in the text of the treaty, the main issue area of the document. Since more than one issue area can be listed, we focus on treaties that are exclusively on “Water quantity and Water quality issues”, “Economic development” and “Environmental services or protection”.
See the Stata command “nlcom”.
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Appendices
Appendix 1: List of Countries
The current study is based on a sample of countries that includes: Afghanistan; Albania; Algeria; Angola; Argentina; Armenia; Austria; Azerbaijan; Bangladesh; Belgium; Belize; Benin; Bhutan; Bosnia and Herzegovina; Botswana; Brazil; Bulgaria; Burkina Faso; Burundi; Cambodia; Cameroon; Canada; Central African Republic; Chad; Chile; China; Colombia; Congo; Costa Rica; Croatia; Denmark; Djibouti; Dominican Republic; Ecuador; Egypt; El Salvador; Equatorial Guinea; Eritrea; Estonia; Ethiopia; Finland; France; Gabon; Gambia; Georgia; Germany; Ghana; Greece; Guatemala; Guinea; Guinea-Bissau; Guyana; Haiti; Honduras; Hungary; India; Indonesia; Iran (Islamic Republic of); Iraq; Israel; Italy; Jordan; Kazakhstan; Kenya; Kyrgyzstan; People’s Democratic Republic; Latvia; Lebanon; Lesotho; Liberia; Libya; Lithuania; Luxembourg; Malawi; Malaysia; Mali; Mauritania; Mexico; Mongolia; Morocco; Mozambique; Myanmar; Namibia; Nepal; Netherlands; Nicaragua; Niger; Nigeria; Norway; Pakistan; Panama; Paraguay; Peru; Poland; Portugal; Republic of Korea; Republic of Moldova; Rwanda; Senegal; Sierra Leone; Slovakia; Slovenia; Somalia; South Africa; Spain; Sudan; Suriname; Sweden; Switzerland; Syrian Arab Republic; Tajikistan; Thailand; Togo; Tunisia; Turkey; Turkmenistan; Uganda; Ukraine; United Republic of Tanzania; United States of America; Uruguay; Uzbekistan; Zambia; Zimbabwe.
Appendix 2: Descriptive Statistics
See Table 7.
Appendix 3: Two Lags
In this appendix we analyze temperature and precipitations shocks over two years. The join effects over these periods are obtained by summing up the coefficients on the lags over the periods. The join coefficients and their standard errors and significance levels are computed using on the “Delta method”.Footnote 28 We find that temperature shocks during the two years preceding the WTs increase the likelihood to enter a WT while the join precipitations’ shocks during this time periods reduce this probability (Table 8).
Appendix 4: Downstream/Upstream Countries
Another interesting discussion concerns the role of countries’ geographic location relative to the basin’s common resource. Where does the change in temperature/precipitation have the most impact on the likelihood of signing a treaty, in the downstream country or in the upstream country? One could argue that since upstream countries have the ability to control river flows (e.g. through dams), the incentive to sign an agreement in the event of a water shortage could be zero for these countries. Such a proposal, however, is based on the assumption that water storage by upstream countries is sufficiently large to compensate for the water shortage due to a warmer climate (and on the inability of the downstream country to respond in other ways). If this capacity is not met, it is likely that the signing of the treaty will depend on the temperature/rainfall in that upstream country. If we now consider downstream countries, especially weak countries (with economic and/or military power disadvantage), then the change in temperature/precipitation may not impact treaties, since these countries may not have the bargaining power to negotiate them. On the contrary, if the power asymmetry is reversed (strong country downstream vs. weak country upstream), then it may be the temperature fluctuation at that location that will be decisive. In short, from this narrative approach, it is difficult to know what to expect. We therefore propose a simple empirical test of whether location along the river matters. We estimate our baseline equation by adding for each pair only the temperature and precipitation of the downstream (column 1) and upstream (column 2) countries. The upstream/downstream dummy variable is also constructed from the shared watershed database (PRIO project). We only consider country pairs where the upstream/downstream relationship is clear, i.e. we do not consider river border cases or mixed upstream/downstream cases.
The results are ambiguous. On the one hand, precipitation has a greater effect in downstream countries, but on the other hand, temperature has a significant effect only in upstream countries. These results can therefore be interpreted in different ways, by focusing on temperature one could argue that upstream countries are the key players, while the results concerning precipitation are less conclusive. These ambiguous results explain our choice not to go into detail about upstream versus downstream countries in our baseline estimate. After all “it takes two to tango” and it is not sure that a systematic relationship can be established for dowstream/upstream countries. More data on the timing of climate shocks and their policy implications in each country, as well as the exogenous determinants of downstream and upstream country dependence and power asymmetry, can help advance this issue (Table 9).
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Candau, F., Gbandi, T. When Climate Change Determines International Agreements: Evidence from Water Treaties. Environ Resource Econ 85, 587–614 (2023). https://doi.org/10.1007/s10640-023-00776-4
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DOI: https://doi.org/10.1007/s10640-023-00776-4