Entrepreneurial Risk Choice and Credit Market Equilibria

Schumacher, Heiner; Gerling, Kerstin; Kowalik, Michal

doi:10.1515/bejeap-2014-0160

Cited by 3 publications

(1 citation statement)

References 24 publications

(6 reference statements)

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“…On the other hand, the uncertainty of starting a business may also put it at risk or even fail to start a business and choose to go out to work again. With the number and scale of rural laborer's back home to start undertaking expanding continuously, it is more important to improve the quality of rural laborer's back home to start undertaking [4]. Enhancing the entrepreneurial risk awareness of rural laborer's back home, establishing a risk early warning system, monitoring and preventing entrepreneurial risks, and taking timely countermeasures are helpful to enhance the enterprise's ability to resist risks, prolong the operating cycle of enterprises, and promote economic development.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Influence of Back Home to Start Undertaking and Rural Revitalization Based on Artificial Intelligence

Chang

Liao

2022

Mobile Information Systems

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The strategy of rural revitalization is to take measures to deal with the big problem of rural decline, mainly from the aspects of developing rural economy, getting rid of poverty, and adjusting rural structure, and changing the traditional thinking of rural development when implementing policies. With the number and scale of rural laborer’s back home to start undertaking expanding continuously, it is more important to improve the quality of rural laborer’s back home to start undertaking. On the basis of analyzing the motivation and problems of rural laborer’s back home to start undertaking, this paper puts forward a risk identification model based on artificial intelligence (AI) algorithm and explores the development path of rural laborer’s back home to start undertaking under the background of rural revitalization. Through simulation experiments, the effectiveness and superiority of this algorithm are analyzed. The results show that the accuracy rate of venture risk assessment in this paper is 93.95%, and the error is 10.24% lower than that of the back propagation neural network (BPNN). It can be seen that this method has a significant effect in the analysis of the risk and influencing factors of rural laborer’s back home to start undertaking. The overall requirements of rural revitalization strategy for industrial prosperity will inevitably encourage and attract more rural laborer’s to back home to start undertaking, and “starting a business to help the poor” will become a new path for rural poverty alleviation and development in the future.

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Section: Introductionmentioning

confidence: 99%

Analysis of the Influence of Back Home to Start Undertaking and Rural Revitalization Based on Artificial Intelligence

Chang

Liao

2022

Mobile Information Systems

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Task Discretion, Labor-market Frictions, and Entrepreneurship

Canidio¹,

Legros²

2021

The Journal of Law, Economics, and Organization

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An agent can perform a job in several ways, which we call tasks. Choosing agents’ tasks is the prerogative of management within firms, and of agents themselves if they are entrepreneurs. While agents’ comparative advantage at different tasks is unknown, it can be learned by observing their performance. However, tasks that generate more information could lead to lower short-term profits. Hence, firms will allocate workers to more informative tasks only if agents cannot easily move to other firms. When, instead, workers can easily move to other firms, agents may prefer to become entrepreneurs and acquire task discretion, even if their short-term payoff is lower than employees. Our model generates novel predictions with respect to, for example, how the wage dynamics of agents who switch between entrepreneurship and employment are affected by labor and contracting frictions. (JEL D83, J24, J62, J63, L26, M13).

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Good Co(o)p or Bad Co(o)p? Redistribution Concerns and Competition in Credit Markets with Imperfect Information

D'Amato

Pietro

Pietroluongo

et al. 2021

The B.E. Journal of Economic Analysis &Amp; Policy

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Non-profit organizations (NPOs), such as financial cooperatives, have a longstanding tradition in advanced market economies. We develop a model of ‘mixed credit markets’ where pure for-profit institutions (e.g. commercial banks) can coexist with financial NPOs which feature a concern for inter-member surplus redistribution (e.g. credit cooperatives) and enjoy privileged borrower-specific information vis-à-vis their for-profit peers, while facing higher funding costs. We formally investigate market competition between the two alternative financial organizations both offering contracts whose terms entail cross subsidization. We argue that heterogeneity in organizational models can explain stable coexistence under competitive conditions, and also help us interpret the variety of market outcomes — in terms of e.g. overall coverage and market shares — as documented in modern financial systems. Importantly, the viability of redistribution-oriented NPOs is shown not to rest on under-investment issues or concerns about market power, for they can successfully operate in markets where credit rationing never arises.

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Entrepreneurial Risk Choice and Credit Market Equilibria

Cited by 3 publications

References 24 publications

Analysis of the Influence of Back Home to Start Undertaking and Rural Revitalization Based on Artificial Intelligence

Analysis of the Influence of Back Home to Start Undertaking and Rural Revitalization Based on Artificial Intelligence

Task Discretion, Labor-market Frictions, and Entrepreneurship

Good Co(o)p or Bad Co(o)p? Redistribution Concerns and Competition in Credit Markets with Imperfect Information

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