The term structure of the interest rate is a crucial tool to underline the decision-making process of several agents: investors, regulators, and risk managers. The data that form the basis of empirical/theoretical studies are particular observations of a function [representing the term structure of the interest rate for each instant of time]. Most of the studies in the literature do not take into account that the data are discretizations of functions. And, therefore, they do not incorporate information that reflects important aspects of the data, such as the smoothness characteristics of the curves. In this work, we propose the use of a set of techniques known by functional data analysis to describe the sources of variability of the interest curves. We also estimate functional linear regression models, where the covariates are some macroeconomic variables.