In this thesis, we demonstrate the efficiency of Laplace domain techniques for the design and analysis of economic systems. To make the techniques applicable to economic modeling, we establish the economic analogs to the various tools and nomenclature in the engineering literature. We show that the Laplace domain provides an alternative description of economic systems, offering insights into behavior not apparent in the time domain. This allows economic discounting and cycles to be efficiently analyzed using pole-zero maps, Bode plots, and similar techniques. In addition, we demonstrate that transforming the linear differential equations of economic engineering into algebraic equations in the Laplace domain simplifies the design of economic systems.

We use the Laplace domain techniques to design and analyze a macroeconomic model. By designing the model in the Laplace domain, we are able to integrate supply chain dynamics and the housing market using two-port network theory.
By analyzing the model using a pole-zero map, we show that the economy's discount rates and business cycles are represented by complex poles and the economy's transmission blocking rates by complex zeros. Additionally, we demonstrate that the Bullwhip effect, a supply chain phenomenon, can be intuitively visualized using a Bode plot. These applications illustrate how Laplace-domain techniques enable the efficient design and analysis of economic systems.

This research paper describes the design and implementation of a Model Predictive Controller, using economic engineering principles, on a model of the US economy. The purpose of the Model Predictive Controller is to mimic the US
government policy by maximizing the Net Domestic Product. The Model Predictive Controller is integrated with a bond graph model which is modeled based on macroeconomic principles and used to simulate the US economy. In all cases, the Model Predictive Controller was able to successfully stabilize the US economy, while maximizing the Net Domestic Product e.g. the economic output of the economy. The model described in this paper provides a promising new way of generating more accurate prospects of future market movements.