Modelización de la trayectoria del efecto de programas y políticas: implicaciones para la evaluación
In program evaluation, results could change dramatically depending on the when, it is mainly in impact evaluation. Although it is pretty relevant, only hypothetical proposals have been found in the consulted literature about how interventions effects evolve over time. This paper analyzes the plausibility of those hypothetical proposals. In this sense, it is analyzed the number of consulting on the Internet through Google Trends. In order to develop the method, several assumptions have been made regarding interventions categories and about the relationship between the number of consulting and program impact too. From visual analysis is concluded that the effect on the number of consulting fits to a sigmoidal, leptokurtic, and positive biased function. Eventually, relevance for program evaluations and methodological implications are discussed.