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    Title: 貸款限制與景氣循環:異質個人模型
    Collateral Constraints and Business Cycles : A Heterogeneous Agent Model
    Authors: 賴政澤
    Lai, Zheng-Ze
    Contributors: 陳明郎
    李文傑

    Chen, Been-Lon
    Lee, Wen-Chieh

    賴政澤
    Lai, Zheng-Ze
    Keywords: 房價
    住宅需求衝擊
    CES效用函數
    抵押品限制式
    金融中介
    限制式非經常性束縛
    違約衝擊
    貸款成數衝擊
    不確定性衝擊
    land prices
    housing demand shocks
    CES preference function
    collateral constraints
    financial intermediaries
    occasionally binding constraints
    default shocks
    loan-to-value shocks
    uncertainty shocks
    Date: 2024
    Issue Date: 2024-07-01 12:18:04 (UTC+8)
    Abstract: 本篇論文包含三篇關於金融摩擦以及金融中介的文章。第一篇文章延伸Liu等人(2013)的研究。透過考慮企業家的擔保品渠道 (collateral channel),Liu等人(2013)文中的正向住房需求衝擊提高了土地價格和商業投資,但消費卻於衝擊開始時減少,這一理論結果與實證研究相異。Liu等人(2013)的模型假設同期、不同商品(非耐久財與耐久財)與跨期、同一商品組合的替代彈性均為一,本文則放寬這一假設,並於模型中以貝氏方法估計此兩參數。結構模型中,基於美國總體經濟數據的貝氏估計表明,同期不同商品間的替代彈性大於一,而跨期同一組商品組合的替代彈性小於一。本文的衝擊反應函數顯示,在放寬了替代彈性的假設後,正向住房需求衝擊同時提高了土地價格、商業投資和消費,從而解決Liu等人(2013)一文中,理論結果與實證結果相異的問題。若以邊際數據密度(marginal data density)作為模型適配度的度量,我們的模型能更好地解釋美國的經濟數據。
    第二篇文章聚焦於以下主題:在具有異質性家計單位和擔保品限制式的實質景氣循環模型中,既有模型因金融危機而考慮了兩種外生衝擊:違約衝擊和貸款成數(loan-to-value ratio)衝擊。Iacoviello(2015)一文中,考慮金融中介但假設借款人永遠借至貸款上限;發現廠商違約率上升後產出增加,而家計單位的貸款成數上升後產出減少。這兩理論結果皆與實證證據不一致。Jensen等人(2018)一文中,允許借款人不必借至貸款上限但未考慮銀行體系的金融中介效果;發現當家計單位的貸款成數上升後,總和消費減少。這一理論結果亦與實證證據不一致。本文透過於模型中同時考慮金融中介並允許借款人並不總是借至貸款上限,解決了Iacoviello(2015)以及Jensen等人(2018)兩篇文章中,理論結果與實證證據不一致的問題。突顯了在實質景氣循環模型中,同時考慮金融中介及限制式非經常成立(occasionally binding constraints)的重要性。
    第三篇文章著重金融中介如何在景氣循環模型中傳遞信用供給的不確定性衝擊。實證分析顯示在歷經信用供給不確定性衝擊後,美國的產出、消費、投資和房價將同時下降。然而既有假設直接金融的理論模型難以得出此一實證結果。在本文中,我們放寬直接金融的假設,將銀行部門納入了一考慮異質性家計單位的實質景氣循環模型中,且借款人的借款上限由其擔保品的價值決定。研究結果表明,模型中的異質性家計單位和金融中介都是使理論模型與實證結果相匹配所不可或缺的要素。本文亦探討了銀行的角色,發現存款利率和貸款利率之間的利差是重要的傳遞機制。
    This dissertation contains three articles about financial frictions and financial intermediaries. The first paper extends Liu et al. (2013)’s work. Through the collateral channel for entrepreneurs, a positive housing demand shock in Liu et al. (2013) increases land prices and business investment, but consumption decreases on impact thus comovement problem arises. First chapter extends Liu et al. (2013) by considering a generalized utility function with flexible intratemporal and intertemporal elasticity of substitutions. Based on aggregate U.S. data, Bayesian estimation of structural model suggests that the intratemporal substitution is larger than unity and the intertemporal substitution is smaller than unity. Our impulse responses show that a positive housing demand shock increases land prices, business investment, and consumption, which resolves the comovement problem in Liu et al, (2013). Using the marginal data density as the measure of fit for models, we find that our model can better explain the same U.S. aggregate data.
    The second paper focus on the following topic: in a real business cycle model with heterogeneous agents and collateral constraints, previous models study impulse responses to two financial shocks: default-redistribution and loan-to-value shocks. With banks and always binding collateral constraints as in Iacoviello (2015), output increases after entrepreneur defaults and decreases after positive household loan-to-value (LTV) shocks, inconsistent with evidence. Without banks but with occasionally binding collateral constraints as in Jensen et al. (2018), consumption decreases under positive LTV shocks, also inconsistent. In contrast, in the model with banks and occasionally binding collateral constraints, consumption, investment, and output decrease together under entrepreneur defaults while increasing together after positive household loan-to-value shocks. This matches the empirical results. The model with banks and occasionally binding collateral constraints resolves the inconsistencies of previous models by allowing constrained optimization with shocks to shift regimes between binding and non-binding collateral constraints. This highlights the importance of including occasionally binding collateral constraints in models with the financial sector to accurately represent financial business cycles.
    The third paper investigates how financial intermediaries propagate credit supply uncertainty shocks within a business cycle model. When discussing credit supply uncertainty shocks, current research assumes direct finance and focuses on the effect of these shocks on entrepreneurs. How uncertainty shocks affect borrowing-constrained households and how these shocks propagate through the economy when financial intermediation is considered remains unexplored. In this paper, we incorporate banking sectors into a dynamic stochastic general equilibrium (DSGE) model with patient savers and impatient borrowers where the latter’s’ borrowing constraints are restricted by the value of their collateral assets. Our result shows that both heterogeneous agents and financial intermediaries are critical for matching empirical evidence. Uncertainty targeting entrepreneurs still induces countercyclical dynamics via precautionary motives. However, when volatility hits constrained households’ collateral constraints, their pullback triggers spillovers to banks, patient households and entrepreneurs, generating comovements on output, consumption and investment. We also explore the role of banks and find that the spread between saving rates and lending rates is an important mechanism to deliver comovements.
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    Description: 博士
    國立政治大學
    經濟學系
    105258501
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0105258501
    Data Type: thesis
    Appears in Collections:[經濟學系] 學位論文

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