The Business Cycle Model Beyond General Equilibrium

This paper presents the business cycle model without using assumptions of general equilibrium. We use agent-based models, risk assessments and economic space as ground for modelling business cycles. All economic agents are at risk but not for all agents risk assessments are performed. We propose that for each agent risk assessment can be performed and suggest treat risk ratings x of agents as their coordinate x on economic space. Agents fill economic domain bounded by most secure and most risky agents. Economic processes, exogenous or endogenous shocks induce evolution of agent’s risk coordinates. We show how risk motions of agents on the bounded economic domain induce the business cycle. We derive the system of economic equations that describe macroeconomic evolution and the business cycle on economic space. As example, we study simple model that describe relations between macro Assets A(t,x) and Revenue-on-Assets B(t,x). To show how economic equations describe the business cycle we obtain from them the system of ordinary differential equations that describes business cycle time fluctuations of macroeconomic Assets A(t) and Revenue-on-Assets B(t)

The Business Cycle Model Beyond General Equilibrium

This paper presents the business cycle model without using assumptions of general equilibrium. We use agent-based models, risk assessments and economic space as ground for modelling business cycles. All economic agents are at risk but not for all agents risk assessments are performed. We propose that for each agent risk assessment can be performed and suggest treat risk ratings x of agents as their coordinate x on economic space. Agents fill economic domain bounded by most secure and most risky agents. Economic processes, exogenous or endogenous shocks induce evolution of agent’s risk coordinates. We show how risk motions of agents on the bounded economic domain induce the business cycle. We derive the system of economic equations that describe macroeconomic evolution and the business cycle on economic space. As example, we study simple model that describe relations between macro Assets A(t,x) and Revenue-on-Assets B(t,x). To show how economic equations describe the business cycle we obtain from them the system of ordinary differential equations that describes business cycle time fluctuations of macroeconomic Assets A(t) and Revenue-on-Assets B(t)

Economic and Financial Transactions Govern Business Cycles

Problem/Relevance - This paper presents new description of the business cycles that for decades remain as relevant and important economic problem. Research Objective/Questions - We propose that econometrics can provide sufficient data for assessments of risk ratings for almost all economic agents. We use risk ratings as coordinates of agents and show that the business cycles are consequences of collective change of risk coordinates of agents and their financial variables. Methodology - We aggregate similar financial variables of agents and define macro variables as functions on economic space. Economic and financial transactions between agents are the only tools that change their extensive variables. We aggregate similar transactions between agents with risk coordinates x and y and define macro transactions as functions of x and y. We derive economic equations that describe evolution of macro transactions and hence describe evolution of macro variables. Major Findings - As example we study simple model that describes interactions between Credits transactions from Creditors at x to Borrowers at y and Loan-Repayment transactions that describe refunds from Borrowers at y to Creditors at x. We show that collective motions of Creditors and Borrowers from safer to risky area and back on economic space induce frequencies of macroeconomic Credit cycles. Implications – Our model can improve forecasting of the business cycles and help increase economic sustainability and financial policy-making. That requires development of risk ratings methodologies and corporate accounting procedures that should correspond each other to enable risk assessments of economic agent

Economic and Financial Transactions Govern Business Cycles

Problem/Relevance - This paper presents new description of the business cycles that for decades remain as relevant and important economic problem. Research Objective/Questions - We propose that econometrics can provide sufficient data for assessments of risk ratings for almost all economic agents. We use risk ratings as coordinates of agents and show that the business cycles are consequences of collective change of risk coordinates of agents and their financial variables. Methodology - We aggregate similar financial variables of agents and define macro variables as functions on economic space. Economic and financial transactions between agents are the only tools that change their extensive variables. We aggregate similar transactions between agents with risk coordinates x and y and define macro transactions as functions of x and y. We derive economic equations that describe evolution of macro transactions and hence describe evolution of macro variables. Major Findings - As example we study simple model that describes interactions between Credits transactions from Creditors at x to Borrowers at y and Loan-Repayment transactions that describe refunds from Borrowers at y to Creditors at x. We show that collective motions of Creditors and Borrowers from safer to risky area and back on economic space induce frequencies of macroeconomic Credit cycles. Implications – Our model can improve forecasting of the business cycles and help increase economic sustainability and financial policy-making. That requires development of risk ratings methodologies and corporate accounting procedures that should correspond each other to enable risk assessments of economic agent

Economic Transactions Govern Business Cycles

This paper presents the business cycle model without using assumptions of general equilibrium. All economic agents are at risk but not for all agents risk assessments are performed. We propose that risk assessment can be completed for all agents and suggest use agents risk ratings as their coordinates x. We show that macroeconomics as ABM is described on bounded economic domain of economic space. Transactions between agents describe evolution of their economic and financial variables. Aggregations of economic or financial variables of agents in a unit volume near point x determine macro variables as functions of x. Aggregations of transactions between agents in unit volumes near points x and y determine macro transactions as functions of x and y. Macro transactions describe change of macro variables near points x and y. We explain how evolution of macro transactions can be described by economic equations on economic space. We show that business cycle fluctuations are consequence of these equations. We treat the nature of the business cycle fluctuations of particular macro variable as oscillations of “mean risk” of this economic variable on bounded economic domain. As example we describe interactions between transactions CL(t,x,y) that provide Loans from Creditors at point x to Borrowers at point y and transactions LR(t,x,y) that describe repayments from Borrowers at point y to Creditors at point x. Starting with economic equations we derive the system of ordinary differential equations that describe the business cycle fluctuations of macro Credits C(t) and macro Loan-Repayments LR(t) of the entire economics

Estimación de un modelo "macrosocial" para la economía peruana diseñado para simular los efectos de escenarios de crecimiento y de política económica sobre la pobreza y la distribución

El presente documento detalla la elaboración, estimación y utilización de un modelo denominado “macrosocial” para la economía peruana, que permite simular efectos a nivel microeconómico – específicamente sobre indicadores de pobreza y desigualdad – de distintos escenarios de crecimiento económico y de política económica. La primera parte del informe comprende una revisión de los modelos de este tipo, explicando sus características generales: el uso de modelos de equilibrio general computable desagregados y de procedimientos que relacionan variables de la economía –especialmente del mercado laboral– con indicadores microeconómicos de bienestar de los hogares. La segunda parte explica la construcción de una Matriz de Contabilidad Social, necesaria para implementar el modelo, a partir de la información oficial publicada disponible. Se pone especial atención a las desagregaciones de ramas de actividad, de tipos de hogares (distinguiendo rurales y urbanos) y de trabajadores (diferenciándolos según calificación y asalariamiento). La tercera parte detalla la estructura de un modelo de equilibrio general computable utilizado para modelar tanto las variables a nivel macroeconómico, las variables desagregadas de oferta, demanda y producción por sectores, la demanda e ingresos de factores, los gastos e ingresos de las instituciones (incluyendo hogares, empresas y gobierno) y el funcionamiento del mercado de trabajo. Se explican también el proceso de calibración de los parámetros del modelo y el análisis recursivo o multiperiodo. Asimismo, se detalla el procedimiento de “microsimulaciones” desarrollado para trasladar los resultados del modelo mencionado en indicadores de pobreza y desigualdad mediante simulaciones basadas en los cambios en el mercado laboral usando datos de encuestas del hogares (ENAHO). En la parte final se realizan ejercicios de simulación para escenarios macroeconómicos y de política económica proyectados en el Marco Macroeconómico Multianual (MMM). Se obtiene los valores esperados de variables desagregadas de gastos de los hogares, de empleo y remuneraciones. Posteriormente, a partir de dichos resultados se estima los posibles impactos sobre la tasa de pobreza y la desigualdad por ámbito geográfico

Introduction to dynamic general equilibrium

This introduces the symposium on dynamic general equilibrium.Macroeconomics Dynamic general equilibrium