Credit supply shocks and the Great Depression in Germany

2020 ◽  
Author(s):  
Max Breitenlechner ◽  
Daniel Gründler ◽  
Gabriel P Mathy ◽  
Johann Scharler
Keyword(s):  
Great Depression ◽  
Aggregate Demand ◽  
Banking Crisis ◽  
Expansion Phase ◽  
Vector Autoregressive ◽  
Credit Supply ◽  
The Great Depression ◽  
Supply Shocks ◽  
Structural Vector Autoregressive Model ◽  
Structural Vector

Abstract At the peak of the Great Depression in mid-1931, Germany experienced a severe banking crisis. We study to what extent credit constraints contributed to the downturn by fitting a structural vector autoregressive model with data from January 1925 to September 1935. Adverse credit supply shocks contributed strongly to the downturn especially at the time of the 1931 banking crisis. Before that, credit supply shocks had also contributed to the expansion phase preceding the depression. We also find that aggregate demand and U.S. business cycle shocks were the primary drivers of the German Great Depression.

scholarly journals A Spatial Panel Structural Vector Autoregressive Model with Interactive Effects and Its Simulation

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 883
Author(s):  
Yaqing Liu ◽  
Hongbing Ouyang ◽  
Xiaolu Wei
Keyword(s):  
Autoregressive Model ◽  
Common Factors ◽  
Interactive Effects ◽  
Vector Autoregressive Model ◽  
Finite Sample ◽  
Vector Autoregressive ◽  
Spatial Panel ◽  
The Common ◽  
Structural Vector Autoregressive Model ◽  
Structural Vector

The existing spatial panel structural vector auto-regressive model can effectively capture the time and spatial dynamic dependence of endogenous variables. However, the hypothesis that the common factors have the same effect for all spatial units is unreasonable. Therefore, incorporating time effects, spatial effects, and time-individual effects, this paper develops a more general spatial panel structural vector autoregressive model with interactive effects (ISpSVAR) that can reflect the different effects of common factors on different spatial units. Additionally, based on whether or not the common factors can be observed, this paper proposes procedures to estimate ISpSVAR separately and studies the finite sample properties of estimators by Monte Carlo simulation. The simulation results show the effectiveness of the proposed ISpSVAR model and its estimation procedures.

Debt, Deleveraging, and the Liquidity Trap: A Fisher-Minsky-Koo Approach*

2012 ◽  
Vol 127 (3) ◽  
pp. 1469-1513 ◽  
Author(s):  
Gauti B. Eggertsson ◽  
Paul Krugman
Keyword(s):  
Fiscal Policy ◽  
Great Depression ◽  
Aggregate Demand ◽  
New Keynesian ◽  
Liquidity Trap ◽  
The Great Depression ◽  
Lost Decade ◽  
Debt Deflation

Abstract In this article we present a simple new Keynesian–style model of debt-driven slumps—that is, situations in which an overhang of debt on the part of some agents, who are forced into rapid deleveraging, is depressing aggregate demand. Making some agents debt-constrained is a surprisingly powerful assumption. Fisherian debt deflation, the possibility of a liquidity trap, the paradox of thrift and toil, a Keynesian-type multiplier, and a rationale for expansionary fiscal policy all emerge naturally from the model. We argue that this approach sheds considerable light both on current economic difficulties and on historical episodes, including Japan’s lost decade (now in its 18th year) and the Great Depression itself.

scholarly journals Atif Mian and Amir Sufi. House of Debt: How They (and You) Caused the Great Recession, and How We Can Prevent It from Happening Again. University of Chicago Press. USA. 2014. 192 pages.

2013 ◽  
Vol 52 (3) ◽  
pp. 247-260
Author(s):  
Asad Zaman Kemal
Keyword(s):  
Financial Crisis ◽  
Financial Markets ◽  
Great Depression ◽  
Global Financial Crisis ◽  
Aggregate Demand ◽  
Jel Classification ◽  
Recent Book ◽  
The Great Recession ◽  
The Great Depression ◽  
University Of Chicago Press

This is a review and a summary of some of the key arguments presented by Mian and Sufi in their recent book “House of Debt.” It highlights the contribution of Mian and Sufi by showing how they have solved the mystery of why there was a huge drop in aggregate demand during the Great Depression of 1929 and also following the recent Global Financial Crisis of 2007-08. The article shows how major economists like Keynes, Friedman, Lucas and others tried and failed to provide an adequate explanation of this mystery. The key to the mystery is the huge amount of levered debt present during both of these economic crises. The solution suggested by Mian and Sufi is to replace interest based debt by equity based contracts in financial markets. This solution resonates strongly with Islamic teachings on finance. These links are also highlighted in this article. JEL classification: B22, E12, E32 Keywords: Great Depression, Global Financial Crisis, Debt-Deflation, Levered Debt

scholarly journals Analysis of the development of the unemployment rate in Lithuania: application of the SVAR model

Ekonomika ◽  
2015 ◽  
Vol 94 (3) ◽  
pp. 86-95
Author(s):  
Tomas Reichenbachas
Keyword(s):  
Unemployment Rate ◽  
Supply And Demand ◽  
Long Term Effects ◽  
Structural Unemployment ◽  
Vector Autoregressive ◽  
Svar Model ◽  
Structural Vector Autoregressive Model ◽  
Economic Boom ◽  
Structural Vector

The paper analyses the dynamics of unemployment in Lithuania, using a structural vector autoregressive model (sVAR) with long-term restrictions proposed by Fabiani et al. (2001). In accordance with it, the unemployment rate is predetermined by economic shocks, some of them with long-term effects (structural) and some with short-term ones (cyclical). The greater part of changes in unemployment in the period of 2002 to 2014 were predetermined by cyclical shocks (of productivity and labour supply and demand). The cyclical unemployment, peaked in the years 2010 to 2011, amounted to ca. 6%. On the other hand, structural unemployment is slow to change, in the years of the economic boom (2006 to 2007) it amounted to ca. 8% (at the time, the cyclical unemployment was negative and the economy encountered overheating, while in 2014 structural unemployment was slightly higher and amounted to ca. 11%).

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