This paper aims to answer to what extent fertility has a causal effect on households economic wellbeing-an issue that has received considerable interest in development studies and policy analysis. However, only recently has the literature begun to give importance to adequate modelling for estimation of causal effects. We discuss several strategies for causal inference, stressing that their validity must be judged on the assumptions we can plausibly formulate in a given application, which in turn depends on the richness of available data. This discussion has a general importance, representing a set of guidelines that can be helpful to choose the appropriate strategy of analysis. We contrast methods relying on the Unconfoundedness Assumption, which include regressions and propensity score matching, with Instrumental Variable methods. We discuss why they give different estimates of the causal effect using data from the Vietnam Living Standard Measurement Survey.