Macroeconomic Factors and Micro-Level Bank Risk
Claudia M. Buch
Bundesbank Discussion Paper 20/2010,
2010
Abstract
The interplay between banks and the macroeconomy is of key importance for financial and economic stability. We analyze this link using a factor-augmented vector autoregressive model (FAVAR) which extends a standard VAR for the U.S. macroeconomy. The model includes GDP growth, inflation, the Federal Funds rate, house price inflation, and a set of factors summarizing conditions in the banking sector. We use data of more than 1,500 commercial banks from the U.S. call reports to address the following questions. How are macroeconomic shocks transmitted to bank risk and other banking variables? What are the sources of bank heterogeneity, and what explains differences in individual banks’ responses to macroeconomic shocks? Our paper has two main findings: (i) Average bank risk declines, and average bank lending increases following expansionary shocks. (ii) The heterogeneity of banks is characterized by idiosyncratic shocks and the asymmetric transmission of common shocks. Risk of about 1/3 of all banks rises in response to a monetary loosening. The lending response of small, illiquid, and domestic banks is relatively large, and risk of banks with a low degree of capitalization and a high exposure to real estate loans decreases relatively strongly after expansionary monetary policy shocks. Also, lending of larger banks increases less while risk of riskier and domestic banks reacts more in response to house price shocks.
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Financial Factors in Macroeconometric Models
Sebastian Giesen
Volkswirtschaft, Ökonomie, Shaker Verlag GmbH, Aachen,
2013
Abstract
The important role of credit has long been identified as a key factor for economic development (see e.g. Wicksell (1898), Keynes (1931), Fisher (1933) and Minsky (1957, 1964)). Even before the financial crisis most researchers and policy makers agreed that financial frictions play an important role for business cycles and that financial turmoils can result in severe economic downturns (see e.g. Mishkin (1978), Bernanke (1981, 1983), Diamond (1984), Calomiris (1993) and Bernanke and Gertler (1995)). However, in practice researchers and policy makers mostly used simplified models for forecasting and simulation purposes. They often neglected the impact of financial frictions and emphasized other non financial market frictions when analyzing business cycle fluctuations (prominent exceptions include Kiyotaki and Moore (1997), Bernanke, Gertler, and Gilchrist (1999) and Christiano, Motto, and Rostagno (2010)). This has been due to the fact that most economic downturns did not seem to be closely related to financial market failures (see Eichenbaum (2011)). The outbreak of the subprime crises ― which caused panic in financial markets and led to the default of Lehman Brothers in September 2008 ― then led to a reconsideration of such macroeconomic frameworks (see Caballero (2010) and Trichet (2011)). To address the economic debate from a new perspective, it is therefore necessary to integrate the relevant frictions which help to explain what we have experienced during recent years.
In this thesis, I analyze different ways to incorporate relevant frictions and financial variables in macroeconometric models. I discuss the potential consequences for standard statistical inference and macroeconomic policy. I cover three different aspects in this work. Each aspect presents an idea in a self-contained unit. The following paragraphs present more detail on the main topics covered.
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The GVAR Handbook: Structure and Applications of a Macro Model of the Global Economy for Policy Analysis
Filippo di Mauro, M. Hashem Pesaran
Oxford University Press,
2013
Abstract
The recent crisis has shown yet again how the world economies are globally interlinked, via a complex net of transmission channels. When it comes, however, to build econometric frameworks aimed at analysing such linkages, modellers are faced with what is called the "curse of dimensionality": there far too many parameters to be estimated with respect to the available observations. The GVAR, a VAR based model of the global economy, offers a solution to this problem. The basic model is composed of a large number of country specific models, comprising domestic, foreign and purely global variables. The foreign variables, however, are treated as weakly exogenous. This assumption, which is typically held when empirically tested for virtually all economies - with the notable exception of the US which is treated differently - allows to estimate first the individual country models separately. Only in a second stage country-specific models are simultaneously solved, thus allowing global interactions.This volume presents - for a first time in a compact and rather easy to read format - principles and structure of the basic GVAR model and a number of its many applications and extensions developed in the last few years by a growing literature. Its main objective is to show how powerful the model can be as a tool for forecasting and scenario analysis. The clear modelling structure of the GVAR appeals to policy makers and practitioners as shown by its growing use among major institutions, as well as by econometricians, as shown by the main extensions and applications.
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Internationale Konjunkturprognose und konjunkturelle Stressszenarien für die Jahre 2012 bis 2014
Oliver Holtemöller, Axel Lindner, Sebastian Giesen
IWH Online,
No. 1,
2013
Abstract
Gegenstand der vorliegenden Studie sind die konjunkturellen Aussichten in den Ländern Deutschland, Brasilien, Italien, Polen, USA und Japan für den Rest des Jahres 2012 und für die Jahre 2013 und 2014. Die Weltwirtschaft befindet sich im Herbst 2013 in einer Schwächephase. Risiken für die internationale Konjunktur erwachsen vor allem aus der Schulden- und Vertrauenskrise im Euroraum, aber auch aus der Haushaltslage in den USA und aus der Abschwächung der Wachstumsdynamik in wichtigen Schwellenländern, vor allem in China. Die wahrscheinlichste wirtschaftliche Entwicklung in dem betrachteten Länderkreis (Basisszenario) wird anhand grundlegender volkswirtschaftlicher Kennzahlen, etwa der Zuwachsrate des Bruttoinlandsprodukts, beschrieben. Es wird auch die Entwicklung für den Fall skizziert, dass die Weltwirtschaft eine ungünstige oder sogar sehr ungünstige Wendung nimmt. Weil die Prognosen der Studie aus einem makroökonometrischen Modell für die internationale Konjunktur gewonnen werden, kann präzise definiert werden, was unter günstig und ungünstig zu verstehen ist: Im ersten Risikoszenario fällt nur mit einer Wahrscheinlichkeit von 10% gemäß der aus dem Modell resultierenden Wahrscheinlichkeitsverteilung die gesamtwirtschaftliche Nachfrage in der betrachteten Ländergruppe im Jahr 2013 noch geringer aus; das zweite Risikoszenario beschreibt eine Situation, in der sich mit einer Wahrscheinlichkeit von nur 1% eine noch geringere Nachfrage realisieren dürfte.
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Testing for Structural Breaks at Unknown Time: A Steeplechase
Makram El-Shagi, Sebastian Giesen
Computational Economics,
No. 1,
2013
Abstract
This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown et al. (J R Stat Soc B 37:149–163, 1975) and Zeileis (Stat Pap 45(1):123–131, 2004), Nyblom (J Am Stat Assoc 84(405):223–230, 1989) and Hansen (J Policy Model 14(4):517–533, 1992), and Andrews et al. (J Econ 70(1):9–38, 1996). Power and size properties are derived using Monte Carlo simulations. We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power. While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper.
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Mittelfristige Projektion der wirtschaftlichen Entwicklung
Oliver Holtemöller, Katja Drechsel, Brigitte Loose
Wirtschaft im Wandel,
No. 8,
2012
Abstract
Die konjunkturelle Schwächephase im Winterhalbjahr 2012/2013 wirkt sich auch auf das mittelfristige Wirtschaftswachstum in Deutschland aus. Unter Berücksichtigung der Herbstprognose 2012 von IWH und Kiel Economics ist nunmehr mit einer durchschnittlichen Wachstumsrate des Bruttoinlandsproduktes von 1¼% pro Jahr zwischen 2011 und 2017 zu rechnen. Dabei wird unterstellt, dass die Auslastung der deutschen Wirtschaft nach der vorübergehenden konjunkturellen Schwächephase überdurchschnittlich sein wird, weil die einheitliche europäische Geldpolitik in Deutschland noch längere Zeit expansiv wirken dürfte.
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What Drives Banking Sector Fragility in the Eurozone? Evidence from Stock Market Data
Stefan Eichler, Karol Sobanski
Journal of Common Market Studies,
No. 4,
2012
Abstract
This article explores the determinants of banking sector fragility in the eurozone. For this purpose, a stock-market-based banking sector fragility indicator is calculated for eight member countries from 1999 to 2009 using the Merton model (1974). Using a panel framework, it is found that the macroeconomic environment, the structure of the banking sector and the intensity of banking regulation all have an effect on banking sector fragility in the eurozone.
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The Performance of Short-term Forecasts of the German Economy before and during the 2008/2009 Recession
Katja Drechsel, Rolf Scheufele
International Journal of Forecasting,
No. 2,
2012
Abstract
The paper analyzes the forecasting performance of leading indicators for industrial production in Germany. We focus on single and pooled leading indicator models both before and during the financial crisis. Pairwise and joint significant tests are used to evaluate single indicator models as well as forecast combination methods. In addition, we investigate the stability of forecasting models during the most recent financial crisis.
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An Evolutionary Algorithm for the Estimation of Threshold Vector Error Correction Models
Makram El-Shagi
International Economics and Economic Policy,
No. 4,
2011
Abstract
We develop an evolutionary algorithm to estimate Threshold Vector Error Correction models (TVECM) with more than two cointegrated variables. Since disregarding a threshold in cointegration models renders standard approaches to the estimation of the cointegration vectors inefficient, TVECM necessitate a simultaneous estimation of the cointegration vector(s) and the threshold. As far as two cointegrated variables are considered, this is commonly achieved by a grid search. However, grid search quickly becomes computationally unfeasible if more than two variables are cointegrated. Therefore, the likelihood function has to be maximized using heuristic approaches. Depending on the precise problem structure the evolutionary approach developed in the present paper for this purpose saves 90 to 99 per cent of the computation time of a grid search.
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