scholarly journals DESTABILIZING EFFECTS OF BANK OVERLEVERAGING ON REAL ACTIVITY—AN ANALYSIS BASED ON A THRESHOLD MCS-GVAR

2017 ◽  
Vol 22 (7) ◽  
pp. 1750-1768 ◽  
Author(s):  
Marco Gross ◽  
Jerome Henry ◽  
Willi Semmler
Keyword(s):  
Regime Switching ◽  
Large Scale ◽  
Banking System ◽  
Real Activity ◽  
Vector Autoregressive ◽  
Joint Dynamics ◽  
Global Vector ◽  
Optimal Leverage ◽  
The Relationship ◽  
Activity Dependent

We investigate the consequences of overleveraging and the potential for destabilizing effects arising from financial- and real-sector interactions. In a theoretical framework, we model overleveraging and demonstrate how a highly leveraged banking system can lead to unstable dynamics and downward spirals. Inspired by models developed by Brunnermeier, Sannikov and Stein, we empirically measure the deviation-from-optimal-leverage for a sample of large EU banks. This measure of overleveraging is used to condition the joint dynamics of credit flows and macroeconomic activity in a large-scale regime change model: a Threshold Mixed-Cross-Section Global Vector Autoregressive (T-MCS-GVAR). The regime-switching component of the model is meant to make the relationship between credit and real activity dependent on the extent to which the banking system is overleveraged. We find significant nonlinearities as a function of overleverage. The farther the observed leverage in the banking system from optimal leverage, the more detrimental is the effect of a deleveraging shock on credit supply and economic activity.

scholarly journals DEMANDA DE DINERO Y CAPTACIÓN BANCARIA EN MÉXICO

2020 ◽  
Vol 79 (314) ◽  
pp. 75
Author(s):  
Ramón Valencia Romero ◽  
Jorge Andrés González Moya ◽  
Humberto Ríos Bolívar
Keyword(s):  
Money Demand ◽  
Economic Activity ◽  
Opportunity Cost ◽  
Regime Switching ◽  
Banking System ◽  
Vector Autoregressive ◽  
Switching Model ◽  
Bank Deposits ◽  
Bank Funding ◽  
First Time

<p>Considerando las variables de actividad económica y de costo de oportunidad de mantener dinero que inciden en la demanda de dinero (M1), analizamos su efecto en la captación del sistema bancario mexicano (2006-2018). Por primera vez se introduce a M1 como determinante de la captación. El análisis emplea un modelo de vectores autorregresivos (VAR, <em>Vector Autoregression</em>) para evaluar la cointegración, así como modelos de corrección de errores. Concluimos que la captación bancaria no fue determinada por la variable actividad económica (el IGAE), sino por algunas variables de costo de oportunidad; sobresale el papel de M1 como determinante de la captación. Por último, obtuvimos un comportamiento estable de la captación. La estabilidad la analizamos con un modelo de cambio de régimen, e identificamos dos regímenes, alta y baja volatilidad; predomina este último.</p><p align="center"><strong> </strong></p><p align="center">MONEY DEMAND AND BANK DEPOSITS IN MEXICO</p><p align="center"><strong>ABSTRACT</strong></p><p>Considering that the variables economic activity and opportunity cost of holding money affect money demand (M1), their effect on deposits at the Mexican banking system is analyzed for the period 2006-2018. For the first time ever, M1 is introduced as a determinant of bank deposits. A Vector Autoregressive Model is used to assess cointegration. Error Correction Models were used. We concluded that bank deposits were not determined by the variable economic activity (IGAE), the rate of inflation nor the bank funding rate, but by some opportunity cost variables. The role of M1 stands out as a determinant of bank deposits. Finally, a stable behavior of bank deposits is obtained. Stability is analyzed using a Regime Switching-Model, two regimes are identified, high and low volatility, the latter predominates.</p>

A Comparative Analysis on International Portfolio Flows to Asian Stock Markets With a Nonlinear Perspective

2018 ◽  
pp. 108-128
Author(s):  
Ayben Koy
Keyword(s):  
Stock Markets ◽  
Regime Switching ◽  
Vector Autoregressive ◽  
Portfolio Flows ◽  
Positive Effects ◽  
Long Run ◽  
International Portfolio ◽  
Nonlinear Relation ◽  
Market Regimes ◽  
The Relationship

After the Asian financial crisis was solved by International Monetary Fund in late 1997, the recovery in Asian economies begun by 1999. Most of the countries affected by the crisis needed to change their exchange rate policies. This chapter brings insight on how the international portfolio flows to Asian stock markets are affected from the shocks on EUR/USD parity. The weekly observations between 01/01/2010 to 21/04/2017 belong to India, Indonesia, Philippine, South Korea, Thailand, Malaysia, and Vietnam. Use of Markov regime switching vector autoregressive models presents the relationship according to the different regimes of the markets in the study. The results indicate that (1) the international portfolio flows through Asian stock markets are governed by a long run, nonlinear relation; (2) the shocks on EUR/USD parity have positive effects on the countries' portfolio flows except Malaysia; and (3) the responses to the shocks vary according to the market regimes or according to the countries.

Leveraging the Equivalence of Hysteresis Models From Different Fields for Analysis and Numerical Simulation of Jointed Structures

2008 ◽  
Vol 3 (3) ◽  
Author(s):  
T. J. Royston
Keyword(s):  
Large Scale ◽  
Structural Model ◽  
Constitutive Models ◽  
Hysteretic Behavior ◽  
Joint Interface ◽  
Element Analysis ◽  
Wide Range ◽  
Joint Dynamics ◽  
Analytical Tools ◽  
The Relationship

An important problem that spans across many types of systems (e.g., mechanical and biological) is how to model the dynamics of joints or interfaces in built-up structures in such a way that the complex dynamic and energy-dissipative behavior that depends on microscale phenomena at the joint/interface is accurately captured, yet in a framework that is amenable to efficient computational analyses of the larger macroscale system of which the joint or interface is a (spatially) small part. Simulating joint behavior in finite element analysis by meshing the joint regions finely enough to capture relevant micromechanics is impractical for large-scale structural systems. A more practical approach is to devise constitutive models for the overall behavior of individual joints that accurately capture their nonlinear and energy-dissipative behavior and to locally incorporate the constitutive response into the otherwise often-linear structural model. Recent studies have successfully captured and simulated mechanical joint dynamics using computationally simple phenomenological models of combined elasticity and slip with associated friction and energy dissipation, known as Iwan models. In the present article, the author reviews the relationship, and in some cases equivalence, of one type of Iwan model to several other models of hysteretic behavior that have been used to simulate a wide range of physical phenomena. Specifically, it is shown that the “parallel-series” Iwan model has been referred to in other fields by different names, including “Maxwell resistive capacitor,” “Ishlinskii,” and “ordinary stop hysteron.” Given this, the author establishes the relationship of this Iwan model to several other hysteresis models, most significantly the classical Preisach model. Having established these relationships, it is then possible to extend analytical tools developed for a specific hysteresis model to all of the models with which it is related. Such analytical tools include experimental identification, inversion, and analysis of vibratory energy flow and dissipation. Numerical case studies of simple systems that include an Iwan-modeled joint illustrate these points.

scholarly journals Comparison of hidden and observed regime-switching autoregressive models for (u, v)-components of wind fields in the northeastern Atlantic

2016 ◽  
Vol 2 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Julie Bessac ◽  
Pierre Ailliot ◽  
Julien Cattiaux ◽  
Valerie Monbet
Keyword(s):  
Regime Switching ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Wind Data ◽  
Wind Fields ◽  
Weather Types ◽  
Vector Autoregressive ◽  
Regime Switching Models ◽  
Switching Models ◽  
Northeastern Atlantic

Abstract. Several multi-site stochastic generators of zonal and meridional components of wind are proposed in this paper. A regime-switching framework is introduced to account for the alternation of intensity and variability that is observed in wind conditions due to the existence of different weather types. This modeling blocks time series into periods in which the series is described by a single model. The regime-switching is modeled by a discrete variable that can be introduced as a latent (or hidden) variable or as an observed variable. In the latter case a clustering algorithm is used before fitting the model to extract the regime. Conditional on the regimes, the observed wind conditions are assumed to evolve as a linear Gaussian vector autoregressive (VAR) model. Various questions are explored, such as the modeling of the regime in a multi-site context, the extraction of relevant clusterings from extra variables or from the local wind data, and the link between weather types extracted from wind data and large-scale weather regimes derived from a descriptor of the atmospheric circulation. We also discuss the relative advantages of hidden and observed regime-switching models. For artificial stochastic generation of wind sequences, we show that the proposed models reproduce the average space–time motions of wind conditions, and we highlight the advantage of regime-switching models in reproducing the alternation of intensity and variability in wind conditions.

scholarly journals Estimating the Impact of Credit Risk Determinants in two Southeast European Countries: A Non-Linear Structural VAR Approach.

2018 ◽  
Vol 10 (1) ◽  
pp. 55-74
Author(s):  
Michail Karoglou ◽  
Konstantinos Mouratidis ◽  
Sofoklis Vogiazas
Keyword(s):  
Credit Risk ◽  
Regime Switching ◽  
Banking System ◽  
Spillover Effects ◽  
Structural Var ◽  
Vector Autoregressive ◽  
Greek Crisis ◽  
Long Run ◽  
Risk Determinants ◽  
The Impact

We study the impact of credit risk determinants on the Romanian and Bulgarian banking systems using a structural Markov Regime-Switching vector autoregressive (MRS-SVAR) analysis. To capture changes in the domestic macroeconomic conditions as well as the spillover effects from the Greek crisis we account for endogenous breaks in the mean and/or volatility dynamics. Our empirical results suggest that an increase of interest rate also increases the Romanian and Bulgarian credit risk in the short-run while in the medium and long-run it reduces it. We also find evidence of spillover effects from the Greek crisis on both the Romanian and Bulgarian banking system, which interestingly, are imminent in the low volatility regime.

Relationship between total plasma homocysteine and the risk of aneurysms – a meta-analysis

VASA ◽  
2020 ◽  
pp. 1-6
Author(s):  
Hanji Zhang ◽  
Dexin Yin ◽  
Yue Zhao ◽  
Yezhou Li ◽  
Dejiang Yao ◽  
...  
Keyword(s):  
Large Scale ◽  
Meta Analysis ◽  
Single Species ◽  
Total Plasma ◽  
Control Groups ◽  
Randomized Controlled ◽  
Randomized Controlled Studies ◽  
The Difference ◽  
The Relationship ◽  
Healthy Participants

Summary: Our meta-analysis focused on the relationship between homocysteine (Hcy) level and the incidence of aneurysms and looked at the relationship between smoking, hypertension and aneurysms. A systematic literature search of Pubmed, Web of Science, and Embase databases (up to March 31, 2020) resulted in the identification of 19 studies, including 2,629 aneurysm patients and 6,497 healthy participants. Combined analysis of the included studies showed that number of smoking, hypertension and hyperhomocysteinemia (HHcy) in aneurysm patients was higher than that in the control groups, and the total plasma Hcy level in aneurysm patients was also higher. These findings suggest that smoking, hypertension and HHcy may be risk factors for the development and progression of aneurysms. Although the heterogeneity of meta-analysis was significant, it was found that the heterogeneity might come from the difference between race and disease species through subgroup analysis. Large-scale randomized controlled studies of single species and single disease species are needed in the future to supplement the accuracy of the results.

New ''Cold War''

2020 ◽  
pp. 27-34
Author(s):  
Vladimir Batiuk
Keyword(s):  
Cold War ◽  
Nuclear Weapons ◽  
Armed Conflict ◽  
Large Scale ◽  
Arms Race ◽  
Ideological Struggle ◽  
Nuclear Arms Race ◽  
The Cold War ◽  
The Relationship ◽  
Nuclear Arms

In this article, the ''Cold War'' is understood as a situation where the relationship between the leading States is determined by ideological confrontation and, at the same time, the presence of nuclear weapons precludes the development of this confrontation into a large-scale armed conflict. Such a situation has developed in the years 1945–1989, during the first Cold War. We see that something similar is repeated in our time-with all the new nuances in the ideological struggle and in the nuclear arms race.

Investigating Diseases and Chemicals in COVID-19 Literature with Text Mining (Preprint)

2020 ◽  
Author(s):  
Amir Karami ◽  
Brandon Bookstaver ◽  
Melissa Nolan
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Topic Modeling ◽  
Large Scale ◽  
Clinical Manifestations ◽  
International Health ◽  
Research Papers ◽  
Strategic Plans ◽  
Funding Agencies ◽  
The Relationship

BACKGROUND The COVID-19 pandemic has impacted nearly all aspects of life and has posed significant threats to international health and the economy. Given the rapidly unfolding nature of the current pandemic, there is an urgent need to streamline literature synthesis of the growing scientific research to elucidate targeted solutions. While traditional systematic literature review studies provide valuable insights, these studies have restrictions, including analyzing a limited number of papers, having various biases, being time-consuming and labor-intensive, focusing on a few topics, incapable of trend analysis, and lack of data-driven tools. OBJECTIVE This study fills the mentioned restrictions in the literature and practice by analyzing two biomedical concepts, clinical manifestations of disease and therapeutic chemical compounds, with text mining methods in a corpus containing COVID-19 research papers and find associations between the two biomedical concepts. METHODS This research has collected papers representing COVID-19 pre-prints and peer-reviewed research published in 2020. We used frequency analysis to find highly frequent manifestations and therapeutic chemicals, representing the importance of the two biomedical concepts. This study also applied topic modeling to find the relationship between the two biomedical concepts. RESULTS We analyzed 9,298 research papers published through May 5, 2020 and found 3,645 disease-related and 2,434 chemical-related articles. The most frequent clinical manifestations of disease terminology included COVID-19, SARS, cancer, pneumonia, fever, and cough. The most frequent chemical-related terminology included Lopinavir, Ritonavir, Oxygen, Chloroquine, Remdesivir, and water. Topic modeling provided 25 categories showing relationships between our two overarching categories. These categories represent statistically significant associations between multiple aspects of each category, some connections of which were novel and not previously identified by the scientific community. CONCLUSIONS Appreciation of this context is vital due to the lack of a systematic large-scale literature review survey and the importance of fast literature review during the current COVID-19 pandemic for developing treatments. This study is beneficial to researchers for obtaining a macro-level picture of literature, to educators for knowing the scope of literature, to journals for exploring most discussed disease symptoms and pharmaceutical targets, and to policymakers and funding agencies for creating scientific strategic plans regarding COVID-19.

scholarly journals Strategic resources and smallholder performance at the bottom of the pyramid

2019 ◽  
Vol 22 (3) ◽  
pp. 365-380 ◽  
Author(s):  
Matthias Olthaar ◽  
Wilfred Dolfsma ◽  
Clemens Lutz ◽  
Florian Noseleit
Keyword(s):  
Large Scale ◽  
Business Environment ◽  
Agricultural Economics ◽  
Local Market ◽  
Bottom Of The Pyramid ◽  
Fine Grained ◽  
Strategic Resources ◽  
Relative Contribution ◽  
The Relationship ◽  
Resource Based Theory

In a competitive business environment at the Bottom of the Pyramid smallholders supplying global value chains may be thought to be at the whims of downstream large-scale players and local market forces, leaving no room for strategic entrepreneurial behavior. In such a context we test the relationship between the use of strategic resources and firm performance. We adopt the Resource Based Theory and show that seemingly homogenous smallholders deploy resources differently and, consequently, some do outperform others. We argue that the ‘resource-based theory’ results in a more fine-grained understanding of smallholder performance than approaches generally applied in agricultural economics. We develop a mixed-method approach that allows one to pinpoint relevant, industry-specific resources, and allows for empirical identification of the relative contribution of each resource to competitive advantage. The results show that proper use of quality labor, storage facilities, time of selling, and availability of animals are key capabilities.

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