Three Essays on Real-Financial Linkage in Dynamic Stochastic General Equilibrium Models

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Creator: 

Reza, Abeer

Date: 

2013

Abstract: 

In this thesis, I contribute to the growing literature on the linkage between real and financial sectors in a New-Keynesian dynamic stochastic general equilibrium (DSGE) framework. The first chapter of this thesis shows that financial frictions can mitigate an important puzzle related to investment-specific technology shocks. Evidence from estimated DSGE models and SVAR analysis suggests that investment shocks are an important source of business cycle fluctuation in the post-war U.S. economy. In most theoretical models, however, consumption falls on impact, contradicting its observed co-movement with output. This chapter shows that introducing financial frictions alongside endogenous capacity utilization in a New-Keynesian model can produce a positive consumption response to an investment shock. The second chapter documents a new challenge for a class of models with binding borrowing constraints related to government spending shocks. We highlight that DSGE models with housing and collateralized borrowing predict a fall in both house prices and consumption following positive government spending shocks. In contrast, we show house prices and consumption in the U.S. rise after identified positive government spending shocks, using a structural vector auto-regression methodology and accounting for anticipated effects. The final chapter of this thesis develops a search-theoretic banking model in a New Keynesian DSGE framework that can simultaneously explain cyclical movements in interest spreads and flows in gross loan creation and destruction, that were recently emphasized in the literature. Search frictions in the banking sector generates a counter-cyclical interest spread that amplifies business-cycles. In addition, the model generates responses in gross loan destruction and net loan flows to a credit supply shock that can qualitatively match empirical responses estimated in a vector auto-regression framework.

Subject: 

SOCIAL SCIENCES Economics - Theory

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Doctor of Philosophy: 
Ph.D.

Thesis Degree Level: 

Doctoral

Thesis Degree Discipline: 

Economics

Parent Collection: 

Theses and Dissertations

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