Assessing financial stability policies in macro-economic models – Research Plenary Session @ FINEXUS Conference

Time and Venue: Wed, 17 Jan 2018, 10:15 – 11:15. Aula KOL-G-201, Univ. of Zurich
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Summary. Traditional economic approaches to macro-economic policy modeling have long been a reference for policy makers because they cast policy assessment in the quantitative context of economic incentives analysis and they propose optimal policy advises. At the same time, traditional approaches are poorly equipped to design and test financial-stability policies, as they overlook the role of externalities associated to asymmetric information, agents’ heterogeneity and direct interactions among them. In addition, they are not able to explain the endogenous emergence of systemic risk and financial crises as a result of agents’ interaction. These features are instead essential in order to study the dynamics of credit and financial markets, which are characterized by non-trivial feedback mechanisms. This is because the above aspects are at the core of the emergence of unintended amplifications effects within and across sectors, bankruptcy cascades (and other feedback loops), and income inequality. Capturing all these aspects requires a complementary modeling approach grounded on the science of complexity. The session examines recent insights on macro-economic policies for financial stability arising from a new strand of research based in particular on stock-flow consistent agent-based macro-economic models.


Panel click here for speaker biographies:

  Mauro Napoletano (Professor, SciencesPo)
Daniele Giachini (PostDoc, Sant’Anna School of Advanced Studies)
Mattia Guerini (PostDoc, OFCE)
Lilit Popoyan (PostDoc, Sant’Anna School of Advanced Studies)
Chiara Perillo (PhD Student, UZH)

Background information and policy context.

A deeper understanding of the impact of financial stability policies, and of their consequence for the overall dynamics of an economy, requires one to analyze those policies in models that account for factors that play a major role in financial crises, like agents’ heterogeneity, externalities diffusing over financial networks, and positive feedback mechanisms amplifying small local shocks. Furthermore, the foregoing factors need to be analyzed in dynamical models, wherein systemic risk and financial crises can emerge endogenously out of agents’ interaction. They also need a real sector that allows one to analyze the consequence of financial stability for real economic dynamics (and vice-versa). All the above ingredients are at the core of the research carried out by Sciences Po, the Sant’Anna School of Advanced Studies and the University of Zurich within the DOLFINS project. The session aims to provide an overview of the foregoing research, by highlighting how it sheds lights on mechanisms of transmissions and on policy implications that cannot be captured by more traditional models.

Innovation, Finance, and Economic Growth: An Agent-Based Approach. This paper extends the endogenous-growth agent-based model in Fagiolo and Dosi (2003) to study the finance-growth nexus. We explore industries where firms produce a homogeneous good using existing technologies, perform R&D activities to introduce new techniques, and imitate the most productive practices. Unlike the original model, we assume that both exploration and imitation require resources provided by banks, which pool agent savings and finance new projects via loans. We find that banking activity has a positive impact on growth. However, excessive financialization can hamper growth. Indeed, we find a significant and robust inverted-U shaped relation between financial depth and growth. Overall, our results stress the fundamental (and still poorly understood) role played by innovation in the finance-growth nexus.

Balance sheet policies in the K+S agent-based model. In this this paper we employ and modify the Schumpeter meeting Keynes agent-based model (K+S) to study three different types of policies: (i) balance sheet policies, by means of the introduction of a mark-to-market accounting standard in the banking sector; (ii) traditional interest-rate monetary policies, combined with a “lender of last resort” behavior from the central bank; (iii) automatic fiscal policies, to be compared with balance budget fiscal policy rules. We investigate how each of these single policies — as well as their combinations — might affect the stability of the financial system and the long-run growth and unemployment performances. The results suggest that a standalone monetary policy rule, even when satisfying the Taylor principle, is not able to stabilize the economy; counter-cyclical fiscal policies shall also be used to avoid falls in aggregate demand and to maintain the economy into a “good statistical equilibrium”. Finally, the mark-to-market balance sheet accounting standards are a source of instability because they spur credit in the short-run but increase the business cycle fluctuations as well as the likelihood of incurring into a debt-crisis.

Winter is possibly not coming: Mitigating financial instability in an agent-based model with interbank market. In this paper we develop an agent-based model to analyze the policy mix between macro-prudential regulations and monetary policy rules when interest rate corridor regimes are fixed. We aim at spelling out the optimal policy combination to achieve the resilience of the financial sector and promote macroeconomic stability. The model endogenously generates interbank market freeze dynamics. Our simulation results show that interest rate corridor width has a potential to be considered a macro-prudential tool due to its capacity to restrain the volatility of interbank interest rate. Moreover, considering the combined and single effects of regulatory tools we find that LCR is not an adequate instrument to curb with liquidity issues due to its pro-cyclical nature. Among others, the model confirms the expected proposition of Tinbergen’s principle showing that “leaning-against-the-wind” is a complementary policy to macro-prudential ones. Finally, considering combined and standalone Basel III instruments we find that Basel III provides a less vulnerable financial system.

Real implications of quantitative easing in the euro area: a financial network analysis. The long-lasting socio-economic impact of the 2008 financial crisis has questioned the adequacy of traditional tools in explaining periods of financial distress as well as the adequacy of the existing policy response. In particular, the effect of complex interconnections among financial institutions on financial stability has been widely recognized. A recent debate focused on the effects of unconventional policies aimed at achieving both price and financial stability. In particular, Quantitative Easing (QE, i.e., the asset purchasing program conducted by a central bank upon creation of new money) has been recently implemented by the European Central Bank (ECB). In this context two questions deserve more attention in the literature. First, to what extent, by injecting liquidity, the QE may alter the bank-firm lending level and stimulate the real economy. Second, to what extent, the QE may also alter the pattern of intra-financial exposures among financial actors (including banks, investment funds, insurance and pension funds) and what are the implications in terms of financial stability. Here, we address these two questions by developing a methodology to map the macro-network of financial exposures among institutional sectors across instruments (i.e., equity, bonds and loans) and we illustrate our approach on recently available data. On the one hand, we estimate a panel vector autoregression (VAR) aimed to assess the cross-country impact of QE on the lending of each country’s banking sector to other countries’ non-financial sectors, as well as the effect on macroeconomic variables such as output, prices, unemployment and inequality. On the other hand, we test the effect of the implementation of ECB’s QE on the time evolution of the financial linkages in the macro-network of the Euro Area. We then use financial contagion models to test the possible effects of these changes on financial stability.