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Journal Article
The Welfare Cost of Business Cycles with Heterogeneous Trading Technologies
The author investigates the welfare cost of business cycles in an economy where households have heterogeneous trading technologies. In an economy with aggregate risk, the different portfolio choices induced by heterogeneous trading technologies lead to a larger consumption inequality in equilibrium, while this source of inequality vanishes in an economy without business cycles. Put simply, the heterogeneity in trading technologies amplifies the effect of aggregate output fluctuation on consumption inequality. The welfare cost of business cycles is, therefore, larger in such an economy. In the ...
Working Paper
Beliefs, Aggregate Risk, and the U.S. Housing Boom
Endogenously optimistic beliefs about future house prices can account for the path and standard deviation of house prices in the U.S. housing boom of the 2000s. In a general equilibrium model with incomplete markets and aggregate risk, agents form beliefs about future house prices in response to shocks to fundamentals. In an income expansion with looser credit conditions, agents are more likely to underpredict house prices and revise up their beliefs. Matching the standard deviation and steady rise in house prices results in homeownership becoming less affordable later in the boom as well as ...
Working Paper
Beliefs, Aggregate Risk, and the U.S. Housing Boom
Endogenously optimistic beliefs about future house prices can account for the path and standard deviation of house prices in the U.S. housing boom of the 2000s. In a general equilibrium model with incomplete markets and aggregate risk, agents form beliefs about future house prices in response to shocks to fundamentals. In an income expansion with looser credit conditions, agents are more likely to underpredict house prices and revise up their beliefs. Matching the standard deviation and steady rise in house prices results in homeownership becoming less affordable later in the boom as well as ...
Working Paper
Macro Credit Policy and the Financial Accelerator
This paper studies macro credit policies within the celebrated financial accelerator model of Bernanke, Gertler and Gilchrist (1999). The focus is on borrower-based restrictions on lending such as loan-to-value (LTV) ratios. We find that the efficacy of cyclical taxes on LTV ratios depends upon the nature of the underlying loan contract. If the loan contract contains equity-like features such as indexation to aggregate conditions, then there is little role for cyclical taxation. But if the loan contract is not indexed to aggregate conditions, then there are substantial gains to procyclical ...
Working Paper
Optimal Contracts, Aggregate Risk, and the Financial Accelerator
This paper derives the optimal lending contract in the financial accelerator model of Bernanke, Gertler and Gilchrist (1999), hereafter BGG. The optimal contract includes indexation to the aggregate return on capital, household consumption, and the return to internal funds. This triple indexation results in a dampening of fluctuations in leverage and the risk premium. Hence, compared with the contract originally imposed by BGG, the privately optimal contract implies essentially no financial accelerator.
Working Paper
Targeting Long Rates in a Model with Segmented Markets
This paper develops a model of segmented financial markets in which the net worth of financial institutions limits the degree of arbitrage across the term structure. The model is embedded into the canonical Dynamic New Keynesian (DNK) framework. We estimate the model using data on the term premium. Our principal results include the following. First, the estimated segmentation coefficient implies a nontrivial effect of central bank asset purchases on yields and real activity. Second, there are welfare gains to having the central bank respond to the term premium, eg., including the term premium ...
Working Paper
Tractable latent state filtering for non-linear DSGE models using a second-order approximation
This paper develops a novel approach for estimating latent state variables of Dynamic Stochastic General Equilibrium (DSGE) models that are solved using a second-order accurate approximation. I apply the Kalman filter to a state-space representation of the second-order solution based on the ?pruning? scheme of Kim, Kim, Schaumburg and Sims (2008). By contrast to particle filters, no stochastic simulations are needed for the filter here--the present method is thus much faster. In Monte Carlo experiments, the filter here generates more accurate estimates of latent state variables than the ...
Working Paper
The market resources method for solving dynamic optimization problems
We introduce the market resources method (MRM) for solving dynamic optimization problems. MRM extends Carroll?s (2006) endogenous grid point method (EGM) for problems with more than one control variable using policy function iteration. The MRM algorithm is simple to implement and provides advantages in terms of speed and accuracy over Howard?s policy improvement algorithm. Codes are available.
Working Paper
Trends and cycles in small open economies: making the case for a general equilibrium approach
Economic research into the causes of business cycles in small open economies is almost always undertaken using a partial equilibrium model. This approach is characterized by two key assumptions. The first is that the world interest rate is unaffected by economic developments in the small open economy, an exogeneity assumption. The second assumption is that this exogenous interest rate combined with domestic productivity is sufficient to describe equilibrium choices. We demonstrate the failure of the second assumption by contrasting general and partial equilibrium approaches to the study of a ...
Working Paper
Finite-State Markov-Chain Approximations: A Hidden Markov Approach
This paper proposes a novel finite-state Markov chain approximation method for Markov processes with continuous support, providing both an optimal grid and transition probability matrix. The method can be used for multivariate processes, as well as non-stationary processes such as those with a life-cycle component. The method is based on minimizing the information loss between a Hidden Markov Model and the true data-generating process. We provide sufficient conditions under which this information loss can be made arbitrarily small if enough grid points are used. We compare our method to ...