This paper-based thesis is composed of four autonomous chapters and contributes to the field of nonlinear econometrics.The first chapter focuses on the contribution of nonlinear econometrics through the measurement of financial performance using a dichotomous variable as an independent variable. The next three chapters are based on nonlinear regression models where the dichotomous variable is the dependent variable in the equation. Given the links between financial risk and the macroeconomic context, this section is linked to the theme of optimal allocation through the study of crises and recessions. This class of model (probit / logit) is used in the second chapter to empirically study the role of financial development in the probability of the occurrence of banking crises. Then, the last two chapters focus on the methodological framework developed by Kauppi and Saikkonen (2008) and Candelon, Dumitrescu and Hurlin (2012; 2014) concerning the forecasting of business cycles using probit / logit models. Thus the third chapter examines the empirical relationship linking the evolution of the interest rate spread and the future probability of expansion / recession in an extended data panel while testing the homogeneity of this relationship. Finally, the fourth chapter proposes a theoretical contribution by deriving the response functions of probit / logit models from the approach of Kauppi and Saikkonen (2008). These response functions are then used in an empirical framework to estimate the impact of an exogenous shock on the expansion / recession cycle.