The interaction between monetary and macroprudential policy: Should central banks "lean against the wind" to foster macrofinancial stability?

The extensive harm caused by the financial crisis raises the question of whether policymakers could have done more to prevent the build-up of financial imbalances. This paper aims to contribute to the field of regulatory impact assessment by taking up the revived debate on whether central banks should "lean against the wind" or not. Currently, there is no consensus on whether monetary policy is, in general, able to support the resilience of the financial system or if this task should better be left to the macroprudential approach of financial regulation. We aim to shed light on this issue by analyzing distinct policy regimes within an agent-based computational macro-model with endogenous money. We find that policies make use of their comparative advantage leading to superior outcomes concerning their respective intended objectives. In particular, we show that "leaning against the wind" should only serve as first line of defense in the absence of a prudential regulatory regime and that price stability does not necessarily mean financial stability. Moreover, macroprudential regulation as unburdened policy instrument is able to dampen the build-up of financial imbalances by restricting credit to the unsustainable high-leveraged part of the real economy. In contrast, leaning against the wind seems to have no positive impact on financial stability which strengthens proponents of Tinbergen's principle arguing that both policies are designed for their specific purpose and that they should be used accordingly

Shadow banking, financial regulation and animal spirits: An ACE approach

Over the past decades, the framework for financing has experienced a fundamental shift from traditional bank lending towards a broader market-based financing of financial assets. As a consequence, regulated banks increasingly focus on coping with regulatory requirements meaning that the resulting funding gap for the real economy is left to the unregulated part of the financial system, i.e. to shadow banks highly relying on securitization and repos. Unfortunately, economic history has shown that unregulated financial intermediation exposes the economy to destabilizing externalities in terms of excessive systemic risk. The arising question is now whether and how it is possible to internalize these externalities via financial regulation. We aim to shed light on this issue by using an agent-based computational macro-model as experimental lab. The model is augmented with a shadow banking sector representing an alternative investment opportunity for the real sector which shows animal spirit-like, i.e. highly pro-cyclical and myopic, behavior in its investment decision. We find that an unilateral inclusion of shadow banks into the regulatory framework, i.e. without access to central bank liquidity, has negative effects on monetary policy goals, significantly increases the volatility in growth rates and that its disrupting character materializes in increasing default rates and a higher volatility in the credit-to-GDP gap. However, experiments with a full inclusion, i.e. with access to a lender of last resort, lead to superior outcomes relative to the benchmark without shadow banking activity. Moreover, our results highlight the central role of the access to contagion-free, alternative sources of liquidity within the shadow banking sector

Transfer Learning for Speech Recognition on a Budget

End-to-end training of automated speech recognition (ASR) systems requires massive data and compute resources. We explore transfer learning based on model adaptation as an approach for training ASR models under constrained GPU memory, throughput and training data. We conduct several systematic experiments adapting a Wav2Letter convolutional neural network originally trained for English ASR to the German language. We show that this technique allows faster training on consumer-grade resources while requiring less training data in order to achieve the same accuracy, thereby lowering the cost of training ASR models in other languages. Model introspection revealed that small adaptations to the network's weights were sufficient for good performance, especially for inner layers.Comment: Accepted for 2nd ACL Workshop on Representation Learning for NL

Banking, Shadow Banking, and Financial Regulation: An Agent-based Approach

The field of “macro-finance”, i.e. the intersection of financial economics and macroeconomics, received much attention [Morley (2015)] through the integration of banking, corporate finance and financial markets into macroeconomic models using various methodologies. Although standard (equilibrium) macro-models are still used, they are typically just augmented with ad-hoc assumptions when it comes to financial sector activity. To push policy-orientated macroeconomic modeling beyond this approach, agent-based computational economic (ACE) models has been identified as a new class of models that is able to overcome these deficiencies by enabling the modeling of dynamics resulting from the endogenous formation of systemic risk, bubbles and contagion effects. Therefore, these models help to gain insights into newly identified sources of financial instability and serve as suitable experimental labs to test the performance of monetary, fiscal and financial stability policies that aim to mitigate the negative effects of such phenomena in order to provide proper guidance for decision makers in central banks and financial supervisory authorities. The ultimate goal of the field is to contribute to the development of a regulatory framework that ensures the stability of the financial system without suppressing its growth-supporting capacity. This dissertation consists of papers that cover i) financial stability issues that has been identified as main sources of systemic risk being held responsible for the occurrence of the recent global financial crisis, ii) potential extensions of the deficient regulatory framework to mitigate accompanied externalities as well as iii) possible conflicts with monetary policy and iv) the regulatory inclusion of shadow banking activities

High nitrate to phosphorus regime attenuates negative effects of rising pCO2 on total population carbon accumulation

The ongoing rise in atmospheric pCO2 and consequent increase in ocean acidification have direct effects on marine calcifying phytoplankton, which potentially alters carbon export. To date it remains unclear, firstly, how nutrient regime, in particular by coccolithophores preferred phosphate limitation, interacts with pCO2 on particulate carbon accumulation; secondly, how direct physiological responses on the cellular level translate into total population response. In this study, cultures of Emiliania huxleyi were full-factorially exposed to two different N:P regimes and three different pCO2 levels. Cellular biovolume and PIC and POC content significantly declined in response to pCO2 in both nutrient regimes. Cellular PON content significantly increased in the Redfield treatment and decreased in the high N:P regime. Cell abundance significantly declined in the Redfield and remained constant in the high N:P regime. We hypothesise that in the high N:P regime severe phosphorous limitation could be compensated either by reduced inorganic phosphorous demand and/or by enzymatic uptake of organic phosphorous. In the Redfield regime we suggest that enzymatic phosphorous uptake to supplement enhanced phosphorous demand with pCO2 was not possible and thus cell abundance declined. These hypothesised different physiological responses of E. huxleyi among the nutrient regimes significantly altered population carrying capacities along the pCO2 gradient. This ultimately led to the attenuated total population response in POC and PIC content and biovolume to increased pCO2 in the high N:P regime. Our results point to the fact that the physiological (i.e. cellular) PIC and POC response to ocean acidification cannot be linearly extrapolated to total population response and thus carbon export. It is therefore necessary to consider both effects of nutrient limitation on cell physiology and their consequences for population size when predicting the influence of coccolithophores on atmospheric pCO2 feedback and their function in carbon export mechanisms

Geometry of moduli spaces of spin and prym curves of small genus

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