The Finance-Growth Nexus in a Model with Locally Interacting Agents. Fagiolo, G. paper-progress, 2016. abstract bibtex In recent years many empirical papers investigated the link between the size of financial system and economic growth. Arcand et al. (2015) summarize and extend previous contributions, showing how an inverse U-shaped relation seems to emerge between finance and growth: when the ratio between credit to the private sector and output is below 80 – 100% then finance positively affects GDP growth, however, when the ratio goes beyond the threshold, the effect becomes negative. On the theoretical side the positive effects of a well developed financial systems are linked to their role in mitigating transaction and information costs (Levine, 2005), while the negative effects are linked to misallocation of resources (Tobin, 1964) and instability (Rajan, 2005, and de la Torre et al., 2011). However a theoretical analysis that is able to endogenously generate the inverse-U shaped relation providing a unified explanation of finance-growth nexus is still missing. The aim of this paper is to fill this gap. To do that we build upon the model of Dosi and Fagiolo (2003): we study an Agent-Based model where N agents produce, consume and save an homogeneous good. The technology space is modelled in terms of an endless lattice where agents are located and move in search of new technologies. As well as exploring the technological space, agents can also imitate the most productive technologies, generating in this way endogenous growth. Since both exploration and imitation require resources that agents may not have, in the model there are banks which pool agents' savings and finance new projects by loans. Our preliminary analysis shows that when banks are financing few projects and are well-capitalized, the endogenous money creation mechanism they provide is able to foster growth. However, when the number of projects financed increases, the probability that someone goes bankrupt increases too. When clients go bankrupt because their innovative projects fail, banks lose equity and have to restrain their lending activity, slowing down growth. Moreover, when many projects fail, banks can go bankrupt too, destroying the resources agents have saved. This curbs growth even more and what we get is the inverse U-shaped relation highlighted by the empirical analysis of Arcand et al. (2015). We will study our model under different parametrizations, concerning in particular the number of banks, the rule used to scream loan applications (asymmetric information vis a vis conservative) and capital requirements. In this way we will able to derive policy implications.
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title = {The Finance-Growth Nexus in a Model with Locally Interacting Agents},
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year = {2016},
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abstract = {In recent years many empirical papers investigated the link between the size of financial system and economic growth. Arcand et al. (2015) summarize and extend previous contributions, showing how an inverse U-shaped relation seems to emerge between finance and growth: when the ratio between credit to the private sector and output is below 80 – 100% then finance positively affects GDP growth, however, when the ratio goes beyond the threshold, the effect becomes negative. On the theoretical side the positive effects of a well developed financial systems are linked to their role in mitigating transaction and information costs (Levine, 2005), while the negative effects are linked to misallocation of resources (Tobin, 1964) and instability (Rajan, 2005, and de la Torre et al., 2011). However a theoretical analysis that is able to endogenously generate the inverse-U shaped relation providing a unified explanation of finance-growth nexus is still missing. The aim of this paper is to fill this gap. To do that we build upon the model of Dosi and Fagiolo (2003): we study an Agent-Based model where N agents produce, consume and save an homogeneous good. The technology space is modelled in terms of an endless lattice where agents are located and move in search of new technologies. As well as exploring the technological space, agents can also imitate the most productive technologies, generating in this way endogenous growth. Since both exploration and imitation require resources that agents may not have, in the model there are banks which pool agents' savings and finance new projects by loans. Our preliminary analysis shows that when banks are financing few projects and are well-capitalized, the endogenous money creation mechanism they provide is able to foster growth. However, when the number of projects financed increases, the probability that someone goes bankrupt increases too. When clients go bankrupt because their innovative projects fail, banks lose equity and have to restrain their lending activity, slowing down growth. Moreover, when many projects fail, banks can go bankrupt too, destroying the resources agents have saved. This curbs growth even more and what we get is the inverse U-shaped relation highlighted by the empirical analysis of Arcand et al. (2015). We will study our model under different parametrizations, concerning in particular the number of banks, the rule used to scream loan applications (asymmetric information vis a vis conservative) and capital requirements. In this way we will able to derive policy implications.},
bibtype = {article},
author = {Fagiolo, Giorgio},
journal = {paper-progress}
}
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To do that we build upon the model of Dosi and Fagiolo (2003): we study an Agent-Based model where N agents produce, consume and save an homogeneous good. The technology space is modelled in terms of an endless lattice where agents are located and move in search of new technologies. As well as exploring the technological space, agents can also imitate the most productive technologies, generating in this way endogenous growth. Since both exploration and imitation require resources that agents may not have, in the model there are banks which pool agents' savings and finance new projects by loans. Our preliminary analysis shows that when banks are financing few projects and are well-capitalized, the endogenous money creation mechanism they provide is able to foster growth. However, when the number of projects financed increases, the probability that someone goes bankrupt increases too. When clients go bankrupt because their innovative projects fail, banks lose equity and have to restrain their lending activity, slowing down growth. Moreover, when many projects fail, banks can go bankrupt too, destroying the resources agents have saved. This curbs growth even more and what we get is the inverse U-shaped relation highlighted by the empirical analysis of Arcand et al. (2015). We will study our model under different parametrizations, concerning in particular the number of banks, the rule used to scream loan applications (asymmetric information vis a vis conservative) and capital requirements. 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