1 MONETARY POLICY INDICATORS ANALYSIS BASED ON REGRESSION FUNCTION ANAMARIA POPESCU * ABSTRACT. This article highlights the effective possibilities for the use of linear regression model to analyze the values of interest rates of standing facilities. In this context, I consider these indicators as dependent variables whose variation is significantly determined by the evolution of the monetary policy interest rate representing the interest rates used for the principal money market operations of the BNR. To emphasize the practical aspects related to the use of linear regression in analyzing the instruments of monetary policy, we have developed a practical study in which we defined the interest rate of the monetary policy in the period 2010-2014 as independent variable. The objectives of this analysis is to determine the function that best describes the relationship of the three indicators, observing the relationship that is established between them and estimating a valid and statistically significant econometric model. 1. INTRODUCTION The linear regression model involves the identification of variables for defining the model and the specification of the residual variable. The purpose of using the regression model is to obtain the parameters corresponding to the set of variables formulated by analyzing the dependence between variables, where data series are recorded at the level of population statistics for a period or a moment, and to highlight the dependence between variables in a given time horizon. In theoretical analysis, the dependence between variables is stochastic. In such a model, the consideration of the residual variable is required. The other factors that influence the outcome variable are grouped in the residual variable. The linear regression model is based on data series for the two characteristics. These are represented by vectors x (variable factor) and y (variable outcome). This requires to define the methods used to estimate the two parameters; to specify the methods used for testing the properties of the regression model estimators and to establish how to use the regression model in making predictions [1],[3]. * 2010 Mathematics Subject Classifications. 62P20, 91B84, 62J02, 62M10 Key words and phrases. Simple regression, correlation, monetary policy, credit facility, deposit facility, Data Analysis