  Models of social learning feature either binary signals or abstract signal
structures often deprived of micro-foundations. Both models are limited when
analyzing interim results or performing empirical analysis. We present a method
of generating signal structures which are richer than the binary model, yet are
tractable enough to perform simulations and empirical analysis. We demonstrate
the method's usability by revisiting two classical papers: (1) we discuss the
economic significance of unbounded signals Smith and Sorensen (2000); (2) we
use experimental data from Anderson and Holt (1997) to perform econometric
analysis. Additionally, we provide a necessary and sufficient condition for the
occurrence of action cascades.
