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Essays on U.S. Housing Price and Macroeconomy /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Essays on U.S. Housing Price and Macroeconomy // Yanchen Hu.
作者:	Hu, Yanchen,
面頁冊數:	1 electronic resource (237 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-06, Section: A.
Contained By:	Dissertations Abstracts International86-06A.
標題:	American studies. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31836905
ISBN:	9798346852674

Essays on U.S. Housing Price and Macroeconomy /
Hu, Yanchen,

Essays on U.S. Housing Price and Macroeconomy /Yanchen Hu. - 1 electronic resource (237 pages)

Source: Dissertations Abstracts International, Volume: 86-06, Section: A.

This dissertation studies the relationship between the U.S. aggregate housing price index and the macroeconomy. The contributions are two-fold. On the one hand, I quantify the effect of the aggregate housing price on the U.S. economy through two mechanisms -- the wealth channel and the collateral channel. To make the model-implied housing price dynamics more empirically appealing, I introduce two new elements into the model. First, I model the expectations of future housing price as a convex combination of conventional rational expectations and irrational extrapolations. Second, I introduce a new structural shock that perturbs the households' expectations on future housing price. On the other hand, this dissertation also makes contributions on computational algorithm. First, I formalize an algorithm that incorporates exotic information set (EIS) into a nonlinear DSGE model. Second, I develop a variant of the conventional Sequential Monte-Carlo sampling by replacing the likelihood tempering with model tempering to reduce the computational cost due to occasionally binding constraints.In the first chapter, I estimate a three-shock New-Keynesian macro-housing model augmented with endogenous growth and housing price extrapolation. Estimation shows that both channels are indispensable in matching the model impulse response functions (IRFs) with the empirical IRFs implied by vector autoregression (VAR). The estimated model matches well the empirical standard deviations of several key macro variables. Housing price extrapolation explains nearly 90% of housing price variance. Spillover of extrapolation into the macro business cycle exclusively occurs in the medium run. Quantitatively, the spillover effect is non-trivial and is similar in magnitude as the effect of endogenous growth. An exception is aggregate investment, where the spillover is minimal. The reason for the exception -- sectoral shift of investment from physical capital to adoption capital, is pivotal in the propagation of extrapolation and large housing boom into the medium-term business cycles. Spillover of housing price into the macroeconomy is shock dependent, through wealth effect with TFP shock and through collateral effect with housing price and monetary policy shocks. The model casts doubt upon the merit of the leaning-against-the-wind policy in response to bubble in asset prices. Historical simulation contradicts the John Taylor's hypothesis that 2002-2004 loose money leads to housing bubble and severe downturn when the bubble bursts.In the second chapter, I estimate a macro-housing model with housing price extrapolation using a model-based tempering schedule for sequential Monte Carlo (SMC) sampling. The estimates point to a model economy with low real friction, high volatility, extraordinary extrapolation, and a Fed with low inertia in policy rates. In contrast to the first chapter, the housing price (HP) shocks significantly affect the business-cycle fluctuations, with an even greater significance after the beginning of this century. Moreover, the HP shocks are the primary driving forces of the Great Recession and the subsequent slow recovery. The collateral channel leads to rapid household deleveraging and drives the recession in the early stage. The housing wealth channel works in in the late stage of the recession and subsequent recovery, through persistent housing capital loss and drop in aggregate demand. I use counterfactual pre-recession shocks to shed light on the prominent explanations of the Great Recession in the literature. In discordance with the argument in Taylor (2012), I find that following Taylor's rule from 2002-2004 would have alleviated the recession by 25%. Contradicting Fernald (2015), I find that maintaining an average TFP growth for a few years before the recession could not have alleviated the recession but would have raised the overall trend of GDP by 4-5%.In the third chapter, I develop a multi-step SCEQ algorithm for solving non-linear dynamic stochastic state-space models with exotic information set (EIS) based on the Simulated Certainty-Equivalent (SCEQ) algorithm in Cai and Judd (2023). Based on the order of shock revelations, each period is divided into multiple subperiods. To accommodate this timing, my algorithm extends SCEQ in two dimensions. First, the simulation step is carried out before entering the next subperiod by fixing the level of variables whose decisions have been made in the current subperiod. Second, in addition to the conventional certainty equivalence assumption, a subperiod version of certainty equivalence is applied such that the shock values of future subperiods take on their mean values in the current period. This multi-step SCEQ algorithm can be implemented using commercialized nonlinear programming (NLP) algorithms. The algorithm is capable of solving large-scale DSGE models, as demonstrated in this dissertation.

English

ISBN: 9798346852674Subjects--Topical Terms:

2122720
American studies.
Subjects--Index Terms:

Housing price

Essays on U.S. Housing Price and Macroeconomy /
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520 $a This dissertation studies the relationship between the U.S. aggregate housing price index and the macroeconomy. The contributions are two-fold. On the one hand, I quantify the effect of the aggregate housing price on the U.S. economy through two mechanisms -- the wealth channel and the collateral channel. To make the model-implied housing price dynamics more empirically appealing, I introduce two new elements into the model. First, I model the expectations of future housing price as a convex combination of conventional rational expectations and irrational extrapolations. Second, I introduce a new structural shock that perturbs the households' expectations on future housing price. On the other hand, this dissertation also makes contributions on computational algorithm. First, I formalize an algorithm that incorporates exotic information set (EIS) into a nonlinear DSGE model. Second, I develop a variant of the conventional Sequential Monte-Carlo sampling by replacing the likelihood tempering with model tempering to reduce the computational cost due to occasionally binding constraints.In the first chapter, I estimate a three-shock New-Keynesian macro-housing model augmented with endogenous growth and housing price extrapolation. Estimation shows that both channels are indispensable in matching the model impulse response functions (IRFs) with the empirical IRFs implied by vector autoregression (VAR). The estimated model matches well the empirical standard deviations of several key macro variables. Housing price extrapolation explains nearly 90% of housing price variance. Spillover of extrapolation into the macro business cycle exclusively occurs in the medium run. Quantitatively, the spillover effect is non-trivial and is similar in magnitude as the effect of endogenous growth. An exception is aggregate investment, where the spillover is minimal. The reason for the exception -- sectoral shift of investment from physical capital to adoption capital, is pivotal in the propagation of extrapolation and large housing boom into the medium-term business cycles. Spillover of housing price into the macroeconomy is shock dependent, through wealth effect with TFP shock and through collateral effect with housing price and monetary policy shocks. The model casts doubt upon the merit of the leaning-against-the-wind policy in response to bubble in asset prices. Historical simulation contradicts the John Taylor's hypothesis that 2002-2004 loose money leads to housing bubble and severe downturn when the bubble bursts.In the second chapter, I estimate a macro-housing model with housing price extrapolation using a model-based tempering schedule for sequential Monte Carlo (SMC) sampling. The estimates point to a model economy with low real friction, high volatility, extraordinary extrapolation, and a Fed with low inertia in policy rates. In contrast to the first chapter, the housing price (HP) shocks significantly affect the business-cycle fluctuations, with an even greater significance after the beginning of this century. Moreover, the HP shocks are the primary driving forces of the Great Recession and the subsequent slow recovery. The collateral channel leads to rapid household deleveraging and drives the recession in the early stage. The housing wealth channel works in in the late stage of the recession and subsequent recovery, through persistent housing capital loss and drop in aggregate demand. I use counterfactual pre-recession shocks to shed light on the prominent explanations of the Great Recession in the literature. In discordance with the argument in Taylor (2012), I find that following Taylor's rule from 2002-2004 would have alleviated the recession by 25%. Contradicting Fernald (2015), I find that maintaining an average TFP growth for a few years before the recession could not have alleviated the recession but would have raised the overall trend of GDP by 4-5%.In the third chapter, I develop a multi-step SCEQ algorithm for solving non-linear dynamic stochastic state-space models with exotic information set (EIS) based on the Simulated Certainty-Equivalent (SCEQ) algorithm in Cai and Judd (2023). Based on the order of shock revelations, each period is divided into multiple subperiods. To accommodate this timing, my algorithm extends SCEQ in two dimensions. First, the simulation step is carried out before entering the next subperiod by fixing the level of variables whose decisions have been made in the current subperiod. Second, in addition to the conventional certainty equivalence assumption, a subperiod version of certainty equivalence is applied such that the shock values of future subperiods take on their mean values in the current period. This multi-step SCEQ algorithm can be implemented using commercialized nonlinear programming (NLP) algorithms. The algorithm is capable of solving large-scale DSGE models, as demonstrated in this dissertation.
546 $a English
590 $a School code: 0168
650 4 $a American studies. $3 2122720
653 $a Housing price
653 $a Medium-term business cycle
653 $a Housing price extrapolation
653 $a Great recession
653 $a Exotic information set
653 $a Simulated Certainty-Equivalent
690 $a 0511
690 $a 0501
690 $a 0323
690 $a 0770
710 2 $a The Ohio State University. $b Economics. $e degree granting institution. $3 3759220
720 1 $a Lam, Pok-Sang $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-06A.
790 $a 0168
791 $a Ph.D.
792 $a 2024
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