Discussion Paper
No. 2013-32 | June 10, 2013
Einar Jon Erlingsson, Silvano Cincotti, Hlynur Stefansson, Jon Thor Sturluson, Andrea Teglio and Marco Raberto
Housing Market Bubbles and Business Cycles in an Agent-Based Credit Economy

Abstract

In this paper the authors present an agent-based model of a credit network economy. The artificial economy includes different economic agents that interact using simple behavioral rules through various markets, i.e., the consumption goods market, the labor market, the credit market and the housing market. A set of computational experiments, based on numerical simulations of the model, have been carried out in order to explore the effects of different households’ creditworthiness conditions required by the banking system to grant a mortgage. The authors find that easier access to credit inflates housing prices, triggering a short run output expansion, mainly due to the wealth effect. Also, with a more permissive policy towards household mortgages, and thus higher levels of credit, the artificial economy becomes more unstable and prone to recessions usually caused by falling housing prices. Often the authors find that an initial crisis can leave firms in a fragile state. If the situation is not cured, a subsequent crisis can lead to mass bankruptcies of firms with catastrophic effects on the credit sector and on the real economy. With stricter conditions on household mortgages the economy is more stable and does not fall into serious recessions, although a too severe regulation can slow down economic growth.

JEL Classification:

E20, E25, G21, R31, R38

Links

Cite As

[Please cite the corresponding journal article] Einar Jon Erlingsson, Silvano Cincotti, Hlynur Stefansson, Jon Thor Sturluson, Andrea Teglio, and Marco Raberto (2013). Housing Market Bubbles and Business Cycles in an Agent-Based Credit Economy. Economics Discussion Papers, No 2013-32, Kiel Institute for the World Economy. http://www.economics-ejournal.org/economics/discussionpapers/2013-32


Comments and Questions



Anonymous - Invited Reader comment 1
July 01, 2013 - 22:15 | Author's Homepage
See attached file.

Anonymous - assessment 2
July 04, 2013 - 16:15
I really enjoy the paper and I think that it is a major advance in ACE for studying how housing bubbles can considerably affect macroeconomic dynamics. To further improve the paper I would suggest: 1) to run simulations for a longer number of years to better assess the frequency of the formation on housing bubbles 2) to assess the possible interactions between different level of access to credit (beta parameter) and different policies, namely fiscal policies and capital requirements

Anonymous - Invited reader comments 3
July 16, 2013 - 08:57
I found the paper interesting and well written. I have three questions below, followed by a list a typos. - Firms have Leontieff production function, and a fixed amount of capital. Would the authors agree that their model is suitable for short term only? Or can they give more justifications for these assumptions? - P8-9. The way construction firms choose how much to produce seems a bit controversial. With the rule described, it can be that a very very small change of price cause a possibly huge change in quantity. In real life there are many difficulties in adjusting quantities produced, so why would we expect producers to overreact to price changes? - I have difficulties understanding the behavior of firms on the credit market. In real life firms need liquidity mainly because of the delay between the payment to suppliers and the payment from consumers. A firm that would need liquidity to pay the interest rate must die sooner or later. Also, a firm would not need liquidity to pay dividends, since dividends are paid out of profits when such a profit is positive. It is unclear to me if the simplifying assumption that “loans are infinitely lived and never paid back” is problematic or not. It would be useful if the authors justify this particular modeling choice explicitly. Some few typos:p.4: “whether” instead of wetherFootnote 5 p. 7: “1%” should be “one percentage point”?p.8: “look at the evolution” instead of “look to the evolution”p.9 : “As a consequence, that when…”. I think “that” should be deleted“a set of employees” instead of “a set of employee”P11: “construction firms” instead of “constructions firms”P 26: “These facts” instead of “This facts”P 28: “a useful” instead of “an useful”

Pasquale Cirillo - Invited reader report 4
July 17, 2013 - 09:30
My overall judgment is very positive. The paper is well written and clear. Regarding the language, I have only found minor typos, e.g. page 4 line -2 ("wether"), which can be easily corrected.The scientific content is interesting and thought-provoking, especially for what concerns the implications of the analysis in terms of economy policy.The model and the simulation procedure are clearly described, and this is a plus from the point of view of replicability. Given the richness of the model, it would be particularly worth to thoroughly investigate its capability of reproducing many important stylized fact of industrial dynamics and credit markets. I hope the authors will invest time on this in their future works.From a methodological point of view, also considering the reviews of the other referees, I simply have some questions related to the choice of the uniform distribution as the random generator for production (page 9) and prices (pages 10-11). 1) Why a uniform distribution? Is this choice somehow micro-founded/economically justified?2) If no, have the authors also tried other distributions? If yes, what are the consequences for the robustness of the results?3) Coming back to the uniform distributions, what are the reasons behind the choice of the supports? I am looking forward to the answers of the authors to these questions.

Tianhao Zhi - Invited reader report 5
July 29, 2013 - 09:22
see attached file

Anonymous - Invited reader report 6
July 29, 2013 - 10:19
see attached file

Anonymous - Invited reader comment 7
August 01, 2013 - 08:46
The model proposed is impressive. However, results do not look very surprising, and consequently also the general indications for policy sound a bit obvious. Moreover, since the paper is introduced in strong opposition to DSGE models, one would like to read more about what such mainstream models could not explain, which the proposed model is able to do. This is suggested in order to counter the risk that agent-based modelling turns more realistic only in the assumptions, and not in the outcomes.

Anonymous - Invited reader comments 8
August 07, 2013 - 10:28
see attached file

Anonymous - Referee report 1
August 12, 2013 - 10:30
see attached file

Einar Jon Erlingsson et al. - Reply to referee report 1
February 17, 2014 - 12:36
see attached file revised version of the paper see below

Anonymous - Referee report 2
August 16, 2013 - 10:16
see attached file

Einar Jon Erlingsson et al. - Reply to referee report 2
February 17, 2014 - 12:42
see attached file revised version of the paper see below

Anonymous - Invited Reader Comment 9
August 22, 2013 - 10:12
see attached file

Einar Jon Erlingsson et al. - Revised version
February 17, 2014 - 12:44
see attached file