NANOCONOMICS

Econographication Virtual Lab, 2024

This conceptual paper introduces a new econometric approach that, for the first time, demonstrates how two dependent (endogenous) variables, denoted as (Y), influenced by an infinite number of independent (exogenous) variables (Xi), can be represented on two separate axes within the same coordinate system. This innovative mathematical and graphical method provides a unique way to analyse and evaluate two phenomena simultaneously within a single graphical space. The proposed model is called the "Dual-Endogenous Multi-Exogenous Integrated Model (DEMEI-Model)." To illustrate, we use this model to examine the interaction between inflation and unemployment from a multidimensional perspective. While demonstrated here in economic analysis, this statistical method can be applied broadly across both natural and social sciences. Finally, the DEMEI-Model is applied to microeconomics, focusing on demand and supply analysis as a case study.

Econographication Virtual Lab, 2024

This paper introduces a novel approach to evaluating the relationship between inflation and unemployment—two critical macroeconomic indicators—that departs from traditional models such as the Phillips curve. The proposed framework is called the Multidimensional Dynamic Interconnected Inflation-Unemployment Coordinate Space (MDIIU-Coordinate Space), designed to model the Macroeconomic Growth Massive Leaking Space Manifolds (MGML-Manifolds). The MGML-Manifolds unify inflation and unemployment into a single economic indicator, enabling the study and visualization of these two variables as an integrated whole. The MDIIU-Coordinate Space employs an innovative graphical approach with a unique coordinate system that incorporates two dependent (endogenous) variables—inflation and unemployment—interconnected with an infinite number of independent (exogenous) variables to construct the MGML-Manifolds. These exogenous variables, which include domestic and external economic, social, political, and technological factors, are dynamic and change in real-time within the same graphical space. The primary objective of this framework is to interconnect the two dependent variables with an extensive array of independent variables, exploring how these exogenous factors can directly or indirectly influence inflation and unemployment, either independently or simultaneously. We propose that while inflation and unemployment are distinct economic phenomena with their own underlying dynamics, both have similar negative effects on economic performance. The relationship between these variables can manifest as either an inverse or direct proportional relationship, depending on whether inflation or unemployment is contracting or expanding, individually or collectively. Additionally, the MGML-Manifolds integrate the MGML-Index and real GDP performance (Ɍ) to complement the analysis, offering insights into how inflation and unemployment jointly impact GDP performance in both the short and long run.

Econographication Virtual Lab (EVL), 2024

This paper introduces a novel coordinate Plane called “the Dual-Alpha Hyper-Dynamic Vertical Manifolds (DHV-Manifolds).” The DHV-Manifolds framework employs an innovative graphical representation, incorporating a unique coordinate plane that integrates two dependent (endogenous) variables, denoted as +α₁ and +α₂, which are interconnected with an infinite set of independent (exogenous) variables, represented as +β₁ᵢ and +β₂ᵢ, where i = {0, 1, ..., ∞}. These components are utilized to construct the DHV-Manifolds. The primary objective of this framework is to link the two dependent variables, +α₁ and +α₂, with a comprehensive set of independent variables to explore how these exogenous variables influence the dependent variables—either individually or in combination. The relationship between +α₁ and +α₂ may exhibit either direct or inverse proportionality.

This monograph presents a new research field entitled “Economic Simulating”. The mission of economic simulating is to offer academics, policy-makers, and researchers new analytical tools to study the origins, trend, and possible solutions of economic problems from a new perspective. The present monograph, in effect, is a simple and flexible document for the learning and teaching of economic simulating. The general objective of economic simulating is to analyze the impact of economic problems in a specific period of time. This monograph is divided into fifteen chapters. The first chapter reviews the literature framework on economic simulating as a whole. The rest of the chapters will present a serial of new simulators to evaluate the origins, trend, vulnerability, and possible solutions to economic problems. Finally, economic simulating offers a new and dynamic area of research without any methodological or theoretical restriction to study different economic problems anywhere and anytime respectively.

This electronic monograph is divided into fifteen chapters. The objective of this electronic monograph is to show the impact of pandemics on the economic performance of any country anytime and anywhere. This first chapter explains each chapter of this electronic monograph. The second chapter analyses the impact of Globalization as in the main reason of the fast spread of COVID-2019 worldwide. We divided into three large sections how Globalization is the main reason of the faster COVID-19 spread worldwide followed by: (a.) the institutional, legal, and political approach of Globalization; (b.) the massive transportations systems and the development of information communication technologies (ICT’s); (c.) the free trade liberalization and labor mobility. Hence, the main objective of this research is to show that Globalization is the major responsible of the fast and unstoppable spread of COVID-2019 globally. Finally, the same research suggests a deep reform of Globalization to avoid again any massive contagious epidemic diseases to reduce its impact economically and socially. The third chapter tries to expose how poverty can be a crucial issue in the faster expansion of COVID-19 in developing countries like Guatemala. This research chapter's primary objective is to prove that the rapid development of COVID-19 infected cases is directly involved in the massive poverty levels in developing countries. However, this chapter also looks at the dramatic reduction of the middle class and the expansion of poverty. This research focuses on how developing, and least developed countries are extremely vulnerable to COVID-19. According to the World Health Organization (WHO), how developing countries such as Guatemala got exponential COVID-19 contagious cases growth rates of 300% daily. According to our preliminary results in the case of Guatemala, we can observe that poverty originated from enormous inflation, massive unemployment, deep-rooted discrimination -by race and economic-, income inequality -the largest in Latin America-, a large informal economy –urban and rural-, and a vast corruption -myopic governments with personal agendas-. Finally, this chapter tries to present policies (Ruiz Estrada, 2011) and (Ruiz Estrada and Park, 2018) to the Guatemalan government, the private sector, and civil society from a holistic approach to Guatemala conditions and characteristics. In the fourth chapter, we evaluate visually how the COVID-19 quarantines can generate massive unemployment, the constant expansion of inflation, the reduction of the purchasing power parity, and the poverty expansion from a multidimensional perspective. This visualization is only possible under the creation of a new multidimensional graphical modeling is called “The Multidimensional Poverty Kaleidoscope Graph.” The multidimensional poverty kaleidoscope graph is not intended to use a forecasting model in any case. However, its application is not limited to the study of a select group of countries. It is not constrained by issues about the region or countries interested in applying the multidimensional poverty kaleidoscope graph. There are four primary phases in the implementation of the multidimensional poverty kaleidoscope graph. The first phase is the design of the input-output-table. The second phase is divided into two sections of analysis: the first section of study assumes that the COVID-19 quarantine time framework growth rate (Y = Independent variable) impact directly on our four variables in the report such as the inflation growth rate (X1), the unemployment growth rate (X2), purchasing power parity growth rate (X3) and the government budget deficit (X4). In the second section of the analysis, the last past four variables in analysis became our dependent variables and directly affected the poverty growth rate (Z). The third phase is the construction of the multidimensional poverty kaleidoscope graph. Finally, the multidimensional poverty kaleidoscope graph was applied to three countries: The U.S., Malaysia, and Guatemala. The chapter fifth exposes a new view of COVID-19 in general. We are interested in going more rooted in the transformation from COVID-19 to COVID-20. This research aims to prove that COVID-19 can transform anytime and anywhere quantitatively and qualitatively, respectively. This research believes that COVID-19 is transforming and generating a new mutation that can change in a new virus. This new virus will be entitled “COVID-20.” The COVID-20 is going to be more potent and complex than COVID-19, according to our observations. We are considering that COVID-20 started massively from January 2020 until the end of December 2020, according to this research. This transformation is not only in symptoms and characteristics but also in its way of transmission, controls, treatments, and eradication. The sixth chapter tries to compare the characteristics of the animal viral strain (e.g., avian influenza and rabies) and the new viral strain called the COVID-19. The main idea is to evaluate a serial of parameters such as the composition, behavior, structure, environments, reproduction, mutation periods, and the reaction together of different viral strains under the use of an extensive database according to twenty-six variables with his twenty-six large databases respectively. This research aims to plot the twenty-six databases in the viral strain coordinate space (VS-Coordinate Space) to generate different viral strain surfaces (VS-Surfaces). Therefore, we will build three different VS-Surfaces with similar sizes and colors to identify different viral strains' characteristics and behavior simultaneously. Hence, we can compare the COVID-19 viral strain surface with each animal viral strain surface, such as avian influenza and rabies. If the COVID-19 viral strain surface cannot show similitudes with the other VS-surfaces from the animal viral strain surfaces (avian influenza and rabies), we can confirm that the new COVID-19 viral strain surface has a possible human intervention, manipulation, and reproduction. Finally, we can generate a list of possible origins of the latest COVID-19 viral strain surface according to missing characteristics and behavior from the animal viral strains surfaces as soon as possible. It is to control this worldwide pandemic urgently. The chapter seventh intends to evaluate how long any country it takes for its economic recovery from the Post-COVID-19 period under the application of a new indicator called "COVID-19 Waves Oscillations." The main objective is to evaluate the world economy economic recovery time framework from COVID-19, respectively. The calculation of COVID-19 Waves Oscillation requests a holistic mathematical approach under the creation of a simple formula. This formula uses the interval of COVID-19 cases daily to elaborate a series of waves from Nano-Waves until Mega-Waves. At the same time, we will demonstrate how the COVID-19 waves oscillation can significantly impact COVID-19 openness behavior (full business and financial activities reactivation –commonly). Finally, we can elaborate on a large number of simulations to evaluate how long it can take different countries to full economic recovery from COVID-19. According to chapter eighth evaluates the big socio-economic dilemma of COVID-19, such as whether we stay at home in quarantine or work as usual. We try to assess quarantines' pros and cons or work in pandemic times from a multidimensional perspective. This research chapter's primary objective is to prove the final impact in both scenarios and the ultimate effect on any country's socio-economic performance. However, this chapter also looks at the negative implications of quarantine (s) on different social groups from low-income people (informal labor sector) to high-income people (formal labor sector). This research focuses on how quarantine or without quarantine is not the most significant public health policy to solve COVID-19 in the medium and long run. Simultaneously, we did many simulations to evaluate the negative impact of COVID-19 on socio-economic performance in households and firms. Additionally, we propose a new socio-economic simulator to assess the decision to implement full quarantine or without quarantine and its negative impact in the short run. The new simulator is entitled "The Virtual Socio-Economic Evaluation of Decisions and Scenarios Disk Synchronization for Pandemics Simulator (VSEDSDSP-Simulator)." According to the VSEDSDSP-Simulator results from different simulations, we can observe that extremes such as a full quarantine or without quarantine can generate an immediately deadly effect in the socio-economic performance in the short and long run without prejudice or preference among different social groups. Hence, this chapter supports an alternative statement is that COVID-19 is not only a simple physical disease; also, COVID-19 is a psychological disease (depression, anxiety, and nostology) that also can directly affect producers' and consumers' productivity and behavior (decisions) considerably.

The rationale behind the Cryptodata Multi-Level Analytical Intelligence System (Cryptodata MCAI-System) lies in the effectiveness of multi-level mega-data analysis frameworks, combined with the utilization of multidimensional graphs as a powerful tool for artificial intelligence learning. This approach enables a comprehensive understanding and resolution of economic, financial, and business challenges. The primary goal in developing the Cryptodata MCAI-System is to provide a new artificial intelligence learning tool capable of efficiently evaluating dynamic and complex economic, financial, and business issues, thereby facilitating a wide range of potential solutions. As such, the Cryptodata MCAI-System seeks to present academics, researchers, and policymakers with an alternative artificial intelligence approach. It introduces a suite of different types of multidimensional artificial intelligence learning tools, including the mega-dynamic disks coordinate space (vertical and horizontal position) learning machine tool, and the mega-disks networks mapping (MDN-Mapping) learning machine tool.

This electronic monograph (E-Monograph) has seven chapter with different models for policy modelling. The first chapter presents the introduction that we explain each chapter. Second chapter is interested to evaluate how artificial intelligence (AI) can change the way to do it policy modeling. The fast development of AI, big data, data sciences, neural networks, and graphical models is opening an infinity of opportunities for policymakers and academics to a new era under the uses of these alternative technologies. However, these alternative technologies can replace the traditional way how we analyze and solve socioeconomic problems. In our case, this research presents a new technology under the construction of an electronic application (theoretical framework) that is using AI, big data, data sciences, neural networks, and Econographicology simultaneously. The new electronic application is called “The Autonomous Policy Decision Maker Simulator (APDM-Simulator). Finally, we introduce the APDM-Simulator theoretical framework and a few examples of how to use the APDM-Simulator to solve any socio-economic issue(s). The APDM-Simulator is used as a main database based on the uses of all volumes (45) and issues (285) from the Journal of Policy Modelling (JPM) published by Elsevier in the last past forty-five years (1978-2023). Third chapter mention about the rationale of the Multi-Level Cryptodata Analytical Intelligence System (MCAI-System) revolves around the efficacy of multi-level mega-data analysis frameworks together with the uses of multidimensional graphs as the most effective analytical artificial intelligence learning machine tool to understand and solve any economic, financial, or business problems from a holistic approach. The main motivation behind the creation of the MCAI-System is to offer a new artificial intelligence learning machine tool to evaluate dynamic and complex economic, finance, or business problems to facilitate a large list of possible solutions efficiently. Thereby, the mission of the MCAI-System is to offer academics, researchers, and policy maker’s an alternative artificial intelligence approach. Hence, the MCAI-System is offering a set of different types of multidimensional artificial intelligence learning machines tools are presented: the mega-dynamic disks coordinate space (vertical position and horizontal position) learning machine tool and the mega-disks networks mapping (MDN-Mapping) learning machine tool. Fourth Chapter proposes the application of the special theory of relativity by Professor Albert Einstein in monetary policy. The money energy (Em) is able to show clearly than with low amounts of inflation growth rates and with a high-speed rate for one year. We can generate a large amount of money energy in short periods of time. At the same time, with sustainable and constant expansion of the GDP in real prices growth rate (∆GDPr) together with a large consumption growth rate (∆C) with moderate and controlled amounts of money supply growth rates (∆MS). We can generate a large amounts of money energy (Em) materialized in its value domestically (in the Purchasing Power Parity PPP) and internationally (the exchange rate) in a period of one year. The money energy (Em) requests the uses of two variables: The mass of inflation (Mi) and the money speed The Theory of the stick’s interconnectivity suggested the uses of an alternative Simulator. It is called “The Economic Cubic Warp Effect Simulator (ECWE-Simulator)”. The main objective of the ECWE-Simulator is to evaluate how strong or weak can be an economy in case of a financial crisis, war, natural disasters, and pandemic an economy under the uses of a large number of exogenous variables and endogenous variables that interacting together in the same graphical space framework. Hence, our final target is to observe HOW any crisis be natural or social can economy tolerate under certain circumstances and environments through the visualization of a cube that keep in constant movement and warp stage all the time. Finally, the evaluation of a natural or social crisis depend on the position and size that the cube is going to occupied in the ECWE-Simulator. Sixth chapter is interested to introduce a new graphical pictorial approach to visualize the final total output (GDP) size of any country by parts or full graphically. This new economic graphical pictorial approach is called “The Economic Growth Accumulation Process Helix (EGAP-Helix)”. The EGAP-Helix tries to show the physical size of the economic growth behavior of any country from a new geometrical graphical visualization perspective. Therefore, the main objective to build the EGAP-Helix is to have a general idea about the economic growth volumes and size performance using the economic growth spheres (EG-Spheres) and EGAP-Helix. Additionally, We suggest the uses of 3-Dimensional geometrical approach. In the same research we strongly recommended to use 3D printing to materialize the final printing of the EG-Sphers and the EGAP-Helix for methodological and teaching reasons. In our case, we take in consideration the uses of the GDP growth rates of U.S. in real prices to build each EG-Sphere and its EGAP-Helix from 2005 to 2022. Seventh chapter purposes of this paper is to suggest the uses of an alternative Simulator. It is called “The Economic Cubic Warp Effect Simulator (ECWE-Simulator)”. The main objective of the ECWE-Simulator is to evaluate how strong or weak can be an economy in case of a financial crisis, war, natural disasters, and pandemic an economy under the uses of a large number of exogenous variables and endogenous variables that interacting together in the same graphical space framework. Hence, our final target is to observe HOW any crisis be natural or social can economy tolerate under certain circumstances and environments through the visualization of a cube that keep in constant movement and warp stage all the time. Finally, the evaluation of a natural or social crisis depend on the position and size that the cube is going to occupied in the ECWE-Simulator. This research is interested to introduce a new graphical pictorial approach to visualize the final total output (GDP) size of any country by parts or full graphically. This new economic graphical pictorial approach is called “The Economic Growth Accumulation Process Helix (EGAP-Helix)”. The EGAP-Helix tries to show the physical size of the economic growth behavior of any country from a new geometrical graphical visualization perspective. Therefore, the main objective to build the EGAP-Helix is to have a general idea about the economic growth volumes and size performance using the economic growth spheres (EG-Spheres) and EGAP-Helix. Additionally, We suggest the uses of 3-Dimensional geometrical approach. In the same research we strongly recommended to use 3D printing to materialize the final printing of the EG-Sphers and the EGAP-Helix for methodological and teaching reasons. In our case, we take in consideration the uses of the GDP growth rates of U.S. in real prices to build each EG-Sphere and its EGAP-Helix from 2005 to 2022. Finally, chapter seventh tries to present a new mathematical prove to verify that a perfect interconnectivity of a serial of sticks can handle to floating or moving on any liquid or ice surface faster for longer times. However, this research opens a new opportunity to find new applications in spaces research in non-gravitational resistance environments that permit new idea to build special sticks for space bases to keep a perfect allocation and resistance in any altitude and pression levels without any restriction or constrains in its uses.

The rationale of the Multi-Level Cryptodata Analytical Intelligence System (MCAI-System) revolves around the efficacy of multi-level mega-data analysis frameworks together with the uses of multidimensional graphs as the most effective analytical artificial intelligence learning machine tool to understand and solve any economic, financial, or business problems from a holistic approach. The main motivation behind the creation of the MCAI-System is to offer a new artificial intelligence learning machine tool to evaluate dynamic and complex economic, finance, or business problems to facilitate a large list of possible solutions efficiently. Thereby, the mission of the MCAI-System is to offer academics, researchers, and policy maker's an alternative artificial intelligence approach. Hence, the MCAI-System is offering a set of different types of multidimensional artificial intelligence learning machines tools are presented: the mega-dynamic disks coordinate space (vertical position and horizontal position) learning machine tool and the mega-disks networks mapping (MDN-Mapping) learning machine tool.

This research introduces a modern national security model for drones. This new model is called the Drones National Defense Platform (DNDP). We present a comprehensive strategic plan for the future use of drones in national defense and warfare. The DNDP focuses on the effectiveness of multi-level mega-data analysis frameworks to address military and national security challenges from a holistic perspective. The main motivation behind the creation of the DNDP is to provide a modern defense system that leverages air, maritime, and terrestrial drones to evaluate dynamic and complex potential conflicts, whether war, warlike situations, domestic conflicts, or border issues, under a wide range of possible strategies, efficiently defending or attacking any foreign target. Thus, the mission of the DNDP is to offer the army, navy, air force, intelligence, and governments an alternative defense approach. The DNDP is supported by two key pillars: the National Drones Defense Mega-Dynamic Disks Mapping (NDDMD-Mapping) and the National Security Mega-Disks Networks Mapping (NSMDN-Mapping).

The Multi-Level National Security Intelligence System (MNSI-System) is founded on the effectiveness of multi-level mega-data analysis frameworks, coupled with the utilization of multidimensional graphs as a potent analytical tool within artificial intelligence. This approach offers a holistic perspective in comprehending and addressing complex military and national security challenges. The primary impetus behind the development of the MNSI-System is to provide a novel artificial intelligence tool capable of efficiently assessing dynamic and intricate scenarios, including potential wars, conflicts, and border issues. This tool aims to evaluate diverse strategies in a comprehensive manner. Consequently, the MNSI-System endeavors to furnish armed forces, intelligence agencies, and governments with an alternative artificial intelligence approach.