The Robustness of Identified VAR Conclusions about Money

Faust, Jon

doi:10.17016/ifdp.1998.610

Cited by 197 publications

(254 citation statements)

References 12 publications

(15 reference statements)

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“…As regards the identification of macroeconomic shocks in step 4, we apply sign restrictions on short‐run impulse response functions (Faust , Canova and De Nicoló , Peersman , Uhlig ) and contemporaneous zero restrictions. The identification scheme is implemented in two steps.…”

Section: The Favar Methodologymentioning

confidence: 99%

Macroeconomic Factors and Microlevel Bank Behavior

Buch¹,

Eickmeier²,

Prieto³

2014

J of Money Credit Banking

101

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We analyze the link between banks and the macroeconomy using a model that extends a macroeconomic VAR for the U.S. with a set of factors summarizing conditions in about 1,500 commercial banks. We investigate how macroeconomic shocks are transmitted to individual banks and obtain the following main findings. Backward-looking risk of a representative bank declines, and bank lending increases following expansionary shocks. Forwardlooking risk increases following an expansionary monetary policy shock. There is, however, substantial heterogeneity in the transmission of macroeconomic shocks, which is due to bank size, capitalization, liquidity, risk, and the exposure to real estate and consumer loans.JEL codes: E44, G21

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Section: The Favar Methodologymentioning

confidence: 99%

Macroeconomic Factors and Microlevel Bank Behavior

Buch¹,

Eickmeier²,

Prieto³

2014

J of Money Credit Banking

101

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“…We aim at estimating an aggregate supply shock, an aggregate real demand shock and a monetary policy shock. This is achieved by applying an identification scheme proposed recently by Faust (1998) and Uhlig (2005) for monetary policy shocks and extended to other macroeconomic shocks by Canova and De Nicoló (2003), Peersman (2005) and Peersman and Straub (2006). This identification scheme consists of imposing short‐run sign restrictions on impulse responses.…”

Section: Methodsmentioning

confidence: 99%

Macroeconomic Fluctuations and Bank Lending: Evidence for Germany and the Euro Area

Eickmeier

Hofmann

Worms

2009

German Economic Review

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Abstract:This paper analyzes how bank lending to the private nonbank sector responds dynamically to aggregate supply, demand and monetary policy shocks in Germany and the euro area. The results suggest that the dynamic responses in the two areas are broadly similar, although there are some differences in the relative contribution of the three shocks to the development of output, prices, interest rates and bank loans over time. In order to assess the role of bank lending in the transmission of macroeconomic shocks, we perform counterfactual simulations and analyze the dynamic responses of German loan sub-aggregates in order to test the distributional implications of potential credit market frictions. The results suggest that there is no evidence that loans amplify the transmission of macroeconomic fluctuations or that a "financial accelerator" via bank lending exists.Keywords: Business cycle fluctuations, bank lending, SVAR model, sign restrictions JEL classification: E32, E44, G21 Non-technical summaryTwo related issues form the starting point of our analysis. The first one is the question why the development of bank credit in Germany has differed so much from that in the euro area in recent years. Contrary to the euro area, there was a slowdown in credit growth in Germany and there is an ongoing discussion about the factors that have led to this marked difference.The other issue is the more general question whether bank loans dampen or amplify the effects of macroeconomic shocks. This latter question is closely related to the empirical literature on the "financial accelerator" which faces the -still unresolved -problem of identifying credit demand and credit supply movements.In order to shed some light on these issues, we analyse how bank lending to the private nonbank sector responds dynamically to macroeconomic shocks in Germany and the euro area. We first estimate the joint dynamic behaviour of real GDP, the price level, the short-term nominal interest rate and the stock of outstanding bank loans using a vector-autoregressive (VAR) model. Based on this model, we identify an aggregate supply shock, a demand shock and a monetary policy shock by imposing short-run sign restrictions on impulse responses.This method has the advantage of being relatively agnostic. It therefore implies a much smaller probability of "creating" certain results by imposing strong a priori restrictions than e.g. long-run or zero restrictions, which are often used in the structural VAR literature. We then assess the patterns of the dynamic responses of economic activity, prices, interest rates and bank lending to the three identified macroeconomic shocks as well as the contribution of the three shocks to fluctuations in output, prices, interest rates and bank lending over time based on historical decompositions.The results suggest that the dynamic response of bank lending to macroeconomic fluctuations in Germany and in the euro area is broadly similar, although there are some differences in the relative contribution of the three shocks ...

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“…() (CFGZ henceforth) employ a VAR that contains endogenous variables similar to those in VAR‐CEE, but most importantly, it focuses on distinguishing financial uncertainty and financial condition shocks. Shocks are identified by the penalty function approach (PFA) initially proposed by Faust () and Uhlig (). Briefly stated, the PFA selects a structural VAR model by maximizing a criterion function subject to inequality constraints.…”

Section: How Important Are Financial Uncertainty Shocks In Explainingmentioning

confidence: 99%

Can Stock Volatility Be Benign? New Measurements and Macroeconomic Implications

Huang¹,

Luo²

2019

J of Money Credit Banking

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We find nonsynchronized movements of two new measures of financial market uncertainty-good and bad volatility-which are based on the maximum and minimum stock prices within a month. Good (bad) volatility is associated with better (worse) expectations about the future economic situation and clearly signals acceleration (deceleration) in economic activity. The VAR results indicate that (i) output, employment, and stock price plummet rapidly in response to a bad volatility shock, while their responses to a good volatility shock are modest, and (ii) bad volatility shocks explain the bulk of economic activity and stock price fluctuations in the medium run.JEL codes: C32, E32, E44

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The Robustness of Identified VAR Conclusions about Money

Cited by 197 publications

References 12 publications

Macroeconomic Factors and Microlevel Bank Behavior

Macroeconomic Factors and Microlevel Bank Behavior

Macroeconomic Fluctuations and Bank Lending: Evidence for Germany and the Euro Area

Can Stock Volatility Be Benign? New Measurements and Macroeconomic Implications

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