Information-Theoretic Estimation of Econometric Functions

This chapter introduces an information-theoretic approach to specify econometric functions as an alternative to avoid parametric assumptions. We investigate the performances of the information-theoretic method in estimating the regression (conditional mean) and response (derivative) functions. We have demonstrated that they are easy to implement and are advantageous over parametric models and nonparametric kernel techniques. For the implementation of our estimation method, a recursive integration procedure is introduced. An empirical illustration is also presented to study the Canadian earning function. The asymptotic properties of the regression and derivative functions are established. In addition, a test for normality is also proposed.

Identification and analysis of influence factors on the number of economic crimes

The article discusses the impact of various factors on the number of economic crimes. During the analysis, econometric functions and models were used, with the help of which the most significant correlating factors were identified.