The nonlinear progressive water pricing policy in Tunisia: equity and efficiency

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Economic theory and recent empirical evidence show that nonlinear progressive water pricing policies are the most useful tool to reduce water demand in water stressed countries. The originality of our paper is to implement Pedroni (1999) panel cointegration tests, using databases on a breakdown of two consumption blocks (a lower and an upper block) from the Tunisian water regulator over 27 years. The results reveal that increasing block tariffs have been successful in managing scarce water in Tunisia. The authors observe that, in the long-run, proportion of subscribers in the upper water consumption block decreases when price increases, while in the lower block, which is composed essentially of low-income households characterized by inelastic water demand, proportion of subscribers is less elastic to price changes and still unchanged. This paper calls for the implementation of nonlinear progressive pricing to reduce demand by large consumers in order to promote efficiency in use and to promote the access of poor consumers to the resource in order to promote equity.

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    • Fig. 1. Proportion of consumers in the upper block (time on x-axis, “80” stands for 1980 and “00” for 2000; % of consumers in the block on the y-axis)
    • Fig. 2. Proportion of consumers in the lower block (time on x-axis, “80” stands for 1980 and “00” for 2000; % of consumers in the block on the y-axis)
    • Fig. 1A. Lower consumption block, yearly average values
    • Fig. 2A. Upper consumption block (block 3 and 4), yearly average values
    • Fig. 3A. Upper consumption block(block 5), yearly average values
    • Table 1. Tariff of water distribution in Tunisia in 2007, in Tunisian dinars per m3
    • Table 2. Fixed charges for water distribution in Tunisia in 2007, in Tunisian dinars per quarter
    • Table 3. First generation panel unit roots tests
    • Table 4. Pesaran (2007) panel unit root test
    • Table 5. Pedroni (1999) cointegration tests
    • Table 6. FMOLS estimation results