A dynamical model for real economy and finance

Grassetti, Francesca; Mammana, Cristiana; Michetti, Elisabetta

doi:10.1007/s11579-021-00311-3

Cited by 4 publications

(4 citation statements)

References 22 publications

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“…Grassetti et al studied discrete-time dynamic models with four variables and delays. It describes the interaction between the three-sector real economy and the financial market with four assets [ 4 ]. Prianyshnykova and Hudenko highlighted the financial and economic necessity and semantics of practical approaches for countries to overcome the negative impacts of the COVID-19 pandemic [ 5 ].…”

Section: Related Workmentioning

confidence: 99%

The Impact of Tax Reduction and Fee Reduction Based on Big Data Algorithm on the High-Quality Development of the Real Economy under the Action of Coupling Effect or Substitution Effect

Zhang

2022

Computational Intelligence and Neuroscience

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The basic idea of the mass of medical growth is to adhere to local market price thinking with a Chinese touch and follow the development policy of “quality first, efficiency first.” It insists on properly handling a series of important relationships betwixt socialism and market economy, the first to drive the rich later, the government and the market, equality and efficiency, short-term growth and long-term development, China and the international economy, ecology and growth of the region. Under the guidance of the qualitative thinking theory, it combines the strategic goals of China’s economic qualitative development and actively draws on the research results of other countries. It uses big data algorithms to focus on the impact of qualitative development on tax and income reduction in the real economy. It conducts research experiments on the impact of tax reduction and fee reduction based on big data algorithms on the top-notch growth of the real economy. Its experimental data show that: in 2018, the share of primary, tertiary, and primary sector in China’s dimensional economy top-notch growth coordination index was 7.2%, 40.7%, and 52.2%, respectively. Its contribution rate to economic growth was 4.2%, 36.1%, and 59.7%, respectively. From these data, it can be concluded that the top-notch growth of the real economy is getting better and better under the influence of tax reduction and fee reduction by big data algorithms.

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Section: Related Workmentioning

confidence: 99%

The Impact of Tax Reduction and Fee Reduction Based on Big Data Algorithm on the High-Quality Development of the Real Economy under the Action of Coupling Effect or Substitution Effect

Zhang

2022

Computational Intelligence and Neuroscience

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“…The literature on interactions between finance and real economy or capital accumulation takes place mainly in the context of DGSE models. (for a review of the literature, see Cochrane 2006; for further developments see Grassetti et al 2022, Grosshans and Zeisberger 2018, Böhm et al 2008 Orive, Bernanke e al. 1999, Campello et al 2010, Holmstrom and Tirole 1997, Jermann, and Quadrini 2012, Khan Thomas 2013, Monacelli et al 2011.…”

Section: Literature Reviewmentioning

confidence: 99%

Financial Markets and the Real Economy: A Statistical Field Perspective on Capital Allocation and Accumulation

Gosselin¹,

Lotz²,

Wambst³

2022

Preprint

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This paper provides a general method to directly translate a classical economic framework with a large number of agents into a field-formalism model. This type of formalism allows the analytical treatment of economic models with an arbitrary number of agents, while preserving the system's interactions and microeconomic features of the individual level.We apply this methodology to model the interactions between financial markets and the real economy, described in a classical framework of a large number of heterogeneous agents, investors and firms. Firms are spread among sectors but may shift between sectors to improve their returns. They compete by producing differentiated goods and reward their investors by paying dividends and through their stocks' valuation. Investors invest in firms and move along sectors based on firms' expected long-run returns.The field-formalism model derived from this framework allows for collective states to emerge. We show that the number of firms in each sector depends on the aggregate financial capital invested in the sector and its firms' expected long-term returns. Capital accumulation in each sector depends both on short-term returns and expected long-term returns relative to neighbouring sectors.For each sector, three patterns of accumulation emerge. In the first pattern, the dividend component of short-term returns is determinant for sectors with small number of firms and low capital. In the second pattern, both short and long-term returns in the sector drive intermediate-to-high capital. In the third pattern, higher expectations of long-term returns drive massive inputs of capital.Instability in capital accumulation may arise among and within sectors. We therefore widen our approach and study the dynamics of the collective configurations, in particular interactions between average capital and expected long-term returns, and show that overall stability crucially depends on the expectations' formation process.Expectations that are highly reactive to capital variations stabilize high capital configurations, and drive low-to-moderate capital sectors towards zero or a higher level of capital, depending on their initial capital. Inversely, low-to moderate capital configurations are stabilized by expectations moderately reactive to capital variations, and drive high capital sectors towards more moderate level of capital equilibria.Eventually, the combination of expectations both highly sensitive to exogenous conditions and highly reactive to variations in capital imply that large fluctuations of capital in the system, at the possible expense of the real economy.

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“…The literature on interactions between finance and real economy or capital accumulation mainly occurs in the context of DGSE models. A review of the literature is provided by Cochrane (2006), while further developments can be found in Grassetti et al (2022), Grosshans and Zeisberger (2018), Böhm et al (2008), Caggese and Orive (2012), Bernanke et al (1999), Campello et al (2010), Holmstrom and Tirole (1997), Jermann and Quadrini (2012), Khan and Thomas (2013), and Monacelli et al (2011). Theoretical models in this literature typically include several types of agents at the aggregated level, such as producers for possibly several sectors, consumers, and financial intermediaries.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The literature on interactions between finance and real economy or capital accumulation takes place mainly in the context of DGSE models. (for a review of the literature, see Cochrane 2006; for further developments see Grassetti et al 2022, Grosshans and Zeisberger 2018, Böhm et al 2008, Caggese and Orive, Bernanke e al. 1999, Campello et al 2010, Holmstrom and Tirole 1997, Jermann, and Quadrini 2012, Khan Thomas 2013, Monacelli et al 2011.…”

Section: Literature Reviewmentioning

confidence: 99%

A statistical field approach to capital accumulation

Gosselin

Lotz²,

Wambst

2021

J Econ Interact Coord

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This paper presents a model of capital accumulation for a large number of heterogenous producerconsumers in an exchange space in which interactions depend on agents' positions. Each agent is described by his production, consumption, stock of capital, as well as the position he occupies in this abstract space.Each agent produces one differentiated good whose price is fixed by market clearing conditions. Production functions are Cobb-Douglas, and capital stocks follow the standard capital accumulation dynamic equation. Agents consume all goods but have a preference for goods produced by their closest neighbors.Agents in the exchange space are subject both to attractive and repulsive forces. Exchanges drive agents closer, but beyond a certain level of proximity, agents will tend to crowd out more distant agents.The present model uses a formalism based on statistical field theory developed earlier by the authors. This approach allows the analytical treatment of economic models with an arbitrary number of agents, while preserving the system's interactions and complexity at the individual level.Our results show that the dynamics of capital accumulation and agents' position in the exchange space are correlated. Interactions in the exchange space induce several phases of the system.A first phase appears when attractive forces are limited. In this phase, an initial central position in the exchange space favors capital accumulation in average and leads to a higher level of capital, while agents far from the center will experience a slower accumulation process. A high level of initial capital drives agents towards a central position, i.e. improve the terms of their exchanges: they experience a higher demand and higher prices for their product. As usual, high capital productivity favors capital accumulation, while higher rates of capital depreciation reduce capital stock.In a second phase, attractive forces are predominant. The previous results remain, but an additional threshold effect appears. Even though no restriction was imposed initially on the system, two types of agents emerge, depending on their initial stock of capital. One type of agents will remain above the capital threshold and occupy and benefit from a central position. The other type will remain below the threshold, will not be able to break it and will remain at the periphery of the exchange space. In this phase, capital distribution is less homogenous than in the first phase.

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A dynamical model for real economy and finance

Cited by 4 publications

References 22 publications

The Impact of Tax Reduction and Fee Reduction Based on Big Data Algorithm on the High-Quality Development of the Real Economy under the Action of Coupling Effect or Substitution Effect

The Impact of Tax Reduction and Fee Reduction Based on Big Data Algorithm on the High-Quality Development of the Real Economy under the Action of Coupling Effect or Substitution Effect

Financial Markets and the Real Economy: A Statistical Field Perspective on Capital Allocation and Accumulation

A statistical field approach to capital accumulation

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