I present a microeconometric model to analyse residential water demand using panel data. Pricing has an increasing-block structure. Database contains individual consumptions from water meters and lacks further information. Permanent income is treated as an unobservable individual effect determining optimal consumption. I also consider a time-varying shock to connect latent and observed demands. The economic setup gives rise to a random effects model with a nonlinear individual effect. I use likelihood-based indirect inference for estimation. I compute price-elasticities and predict the effects of a tariff change. The methodology can be applied to analyse demands of other goods with increasing tariffs.