15 research outputs found
ν΅νμ μ± , λΆλμ° μμ₯ λ° κ΅μ μλ³Έ νλ¦μ λν λ Όλ¬Έ
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Όλ¬Έ(λ°μ¬) -- μμΈλνκ΅λνμ : μ¬νκ³Όνλν κ²½μ νλΆ, 2023. 2. μ΄μ¬μ.This dissertation consists of two articles on monetary poicies and housing markets and one article on international capital flows. Chapter 1 analyzes how the effectiveness of monetary policy shocks are affected by leveraged housing boom period, when housing prices have surged with excessive levels of leverage. Threshold SVAR models are estimated on three small open economies - Norway, Korea, and Canada - by using minimum of the standardized real house price gap and household credit gap as a threshold variable. For all countries, the effects of monetary policy shocks on real house prices and output turn out to be more significant and stronger during the boom regime when the both real house price gap and household credit gap are above the threshold value.
Chapter 2 expands the scope of discussion into rental housing markets. In terms of monetary policy transmission mechanisms, the role of homeownership decision channels, where households could decide between mortgaged housing and rental housing, is examined focusing on sticky responses of housing rents to monetary policy shocks. A New Keynesian model incorporated with homeownership channels shows that substitution of mortgaged housing with rental housing after interest rate hikes results in smaller short-term effects of monetary policies but more persistent long-term effects. Rent rigidity, on the other hand, amplfies the short-term effect of monetary policy by suppressing this substitution, but its quantitative effect is limited and temporary.
Chapter 3 examines the effectiveness of post-AFC reforms of AFC economies, which had tightened capital controls since the Asian Financial Crisis (AFC) to decrease the volatilities from international capital flow shocks. By classifying ASEAN+3 economies into AFC economies and Non-AFC economies, Bayesian panel VAR models are estimated on three sub-groups: (i) AFC economies in the AFC episodes, (ii) AFC economies in the GFC episodes, and (iii) Non-AFC economies in the GFC episodes. For AFC economies, the negative effects of net capital outflow shocks on real GDP growth rate during the AFC period become weaker during the GFC period. Furthermore, during the GFC episodes, AFC economies are more resilient to net capital outflow shocks than Non-AFC economies. These findings support the effectiveness of post-AFC reforms to strengthen resilience to capital flow shocks in AFC economies.λ³Έ νμλ
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Όλ¬Έκ³Ό κ΅μ μλ³Έ νλ¦μ λν νλμ μλ
Όλ¬ΈμΌλ‘ μ΄λ£¨μ΄μ Έ μλ€. μ 1μ₯μμλ λΆλμ° κ°κ²©κ³Ό κ°κ³ λΆμ±κ° λͺ¨λ μμΉνλ λ λ²λ¦¬μ§ λΆλμ° νΈν© κ΅λ©΄ (boom regime)κ³Ό κ·Έλ μ§ μμ κ΅λ©΄ (normal regime)μμ ν΅νμ μ±
μ ν¨κ³Όκ° μ΄λ€ μ°¨μ΄λ₯Ό κ°λμ§λ₯Ό λΉκ΅λΆμ νμλ€. μ΄λ₯Ό μν΄ μ€μ§ λΆλμ° κ°κ²© κ°κ³Ό κ°κ³ λΆμ± κ°μ μ΅μκ°μ λ¬Έν± λ³μ (Threshold variable)λ‘ μ¬μ©νμ¬ λ
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μ ν¨κ³Όκ° λ ν¬κ³ μ μν κ²μΌλ‘ λνλ¬λ€.
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Όμλ₯Ό νμ₯νμλ€. μ¦ κ°κ³κ° κΈλ¦¬ λ³λ μ΄ν λμΆμ ν΅ν μ£Όν 보μ μ μ£Όν μλ μ€ νλλ₯Ό μ ννλ κ²μ΄ κ°λ₯ν μ£Όν μμ κ²°μ μ±λ (homeownership decision channel)μ΄ ν΅νμ μ±
μ λ¬ κ²½λ‘μ λ―ΈμΉλ μν₯μ κΈλ¦¬ 좩격μ κ²½μ§μ μΌλ‘ λ°μνλ μ£Όν μλλ£ (sticky housing rent)λ₯Ό μ€μ¬μΌλ‘ λΆμνμλ€. μ£Όν μμ κ²°μ μ±λμ ν¬ν¨νλλ‘ νμ₯ν λ΄μΌμΈμ§μΈ λͺ¨ν (New Keynesian model)μ ν΅ν λΆμ κ²°κ³Ό κ°κ³λ€μ΄ κΈλ¦¬ μΈμ 좩격 μ΄ν λμΆμ ν΅ν΄ ꡬμ
ν μ£Όνμ μλ μ£ΌνμΌλ‘ λ체νλ μ£Όν μμ κ²°μ μ±λμ ν΅νμ μ±
μ λ¨κΈ° ν¨κ³Όλ₯Ό μ½νμν€μ§λ§ μ₯κΈ° ν¨κ³Όλ κ°ννλ κ²μΌλ‘ λνλ¬λ€. λ°λ©΄ λΉνλ ₯μ μ£Όν μλλ£λ μλ μ£ΌνμΌλ‘μ λ체λ₯Ό λ¨κΈ°μ μΌλ‘ μ΅μ νμ¬ ν΅νμ μ±
μ λ¨κΈ° ν¨κ³Όλ₯Ό κ°ννμμ§λ§, κ·Έ μν₯μ μΌμμ μ΄κ³ μ νμ μ΄μλ€.
μ 3μ₯μμλ μμμ κΈμ΅ μκΈ° κ²½ν κ΅κ°λ€μ μΈνμκΈ° μ΄ν κΈμ΅κ°ν(post-AFC reform)μ΄ κ΅μ μλ³Έ νλ¦ μΆ©κ²©μ λ°λ₯Έ λ³λμ±μ μνμν€λλ° ν¨κ³Όμ μ΄μλμ§λ₯Ό μ€μ¦ λΆμνμλ€. ASEAN+3 κ΅κ°λ€μ μμμ κΈμ΅ μκΈ°λ₯Ό κ²½νν κ΅κ°λ€ (AFC κ²½μ )μ κ·Έλ μ§ μμ κ΅κ°λ€ (λΉ AFC κ²½μ )λ‘ λΆλ₯ν ν, (i) AFC κΈ°κ°μ AFC κ²½μ , (ii) GFC κΈ°κ°μ AFC κ²½μ , (iii) GFC κΈ°κ°μ λΉ AFC κ²½μ λΌλ μΈ κ°μ μμ§λ¨μ λν΄ λ² μ΄μ§μ ν¨λ 벑ν°μκΈ°νκ· λͺ¨ν (Bayesian panel VAR model)μ μΆμ νμλ€. μΆμ κ²°κ³Ό AFC κ²½μ μμ μμλ³Έ μ μΆ μΆ©κ²©μ΄ κ²½μ μ±μ₯λ₯ μ λ―ΈμΉλ λΆμ μ μΈ μν₯μ AFC κΈ°κ°μμ GFC κΈ°κ°μΌλ‘ κ°λ©΄μ μ½νλ κ²μΌλ‘ λνλ¬λ€. GFC κΈ°κ° λμ μμλ³Έ μ μΆ μΆ©κ²©μ κ²½μ μ±μ₯λ₯ μ λν λΆμ μ μΈ μν₯ μμ AFC κ²½μ μμ λΉ AFC κ²½μ μ λΉν΄ λ μ§μμ μΈ κ²μΌλ‘ λνλ¬λ€. μ΄μμ κ²°κ³Όλ μΈνμκΈ° μ΄ν κΈμ΅ κ°νμ΄ κ΅μ μλ³Έ νλ¦μ λ³λμ±μ μννλλ° ν¨κ³Όμ μ΄μμμ μμ¬νλ€.Chapter 1. The effects of monetary policy during leveraged housing booms 1
1.1. Introduction 1
1.2. Data and Empirical Methodologies 6
1.2.1. Data and Empirical Methodologies 6
1.2.2. Reduced-Form Threshold VAR (TVAR) model 11
1.2.3. Structural Identification 14
1.3. Empirical Results 15
1.3.1. Identified Regimes 15
1.3.2. State-Dependent Impulse Response Function 17
1.3.3. Extended models with private consumption and fixed capitals 23
1.4. Robustness Tests 27
1.4.1. Using the household credit gap alone 27
1.4.2. Using the house price gap alone 30
1.4.3. Using the adjusted one-sided HP filter 33
1.5. Conclusion 35
References 38
Appendix 1.A. Data and Sources 40
Appendix 1.B. Model Specification for section 1.4.1 (Household credit gap only) 41
Appendix 1.C. Model Specification for section 1.4.2 (House price gap only) 41
Appendix 1.D. Model Specification for section 1.4.3 (One-sided HP filter) 41
Chapter 2. Homeownership Channels, Rent Stickiness, and Monetary Policy Transmission Mechanisms 42
2.1. Introduction 42
2.2. Data and Empirical Methodologies 47
2.2.1. Data 47
2.2.2. Panel VARX (PVARX) model 50
2.2.3. Responses of Real House Prices and Housing Rents After Monetary Policy Shocks 53
2.2.4. Responses of Nominal House Prices and Housing Rents After Monetary Policy Shocks 55
2.3. The Model and Calibration 56
2.3.1. Unconstrained Households 57
2.3.2. Constrained Households 58
2.3.3. Entrepreneurs and Retailors 60
2.3.4. Housing Supply 62
2.3.5. Interest Rate Rule 64
2.3.6. Equilibrium 64
2.3.7. Calibration 65
2.4. Simulation Results 69
2.4.1. The Role of Rent Stickiness in Different Responses of Housing Rents and House Prices 69
2.4.2. The Role of Homeownership channels in the Monetary Policy Transmission Mechanism 71
2.4.3. The Role of Rent Stickiness in Homeownership Channels 75
2.5. Concluding Remarks 77
References 78
Appendix 2.A. Data and Sources 81
Appendix 2.B. Responses of real housing rents and housing prices under the alternative specification 82
Chapter 3. International Capital Flow Shocks and Economic Crisis in East Asian Countries 83
3.1. Introduction 83
3.2. Related Literature 86
3.3. Data and summary statistics 88
3.4. Cross-country and cross-period difference in the effects of international capital flow shocks for AFC economies 94
3.4.1. Methodology 95
3.4.2. Impulse response to net capital outflow shocks on different sub-groups 98
3.4.3. Impulse response to negative shocks on each component of capital inflows 101
3.5. Conclusion 106
References 109
Appendix 3.A. Data and Sources 111
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Timing dependent Trade-offs in monetary policy shocks
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Όλ¬Έ (μμ¬) -- μμΈλνκ΅ λνμ : μ¬νκ³Όνλν κ²½μ νλΆ, 2020. 8. κΉμμ.This paper estimates a nonlinear SVAR model to study the trade-offs in leaning against the wind in regimes characterized by the Bubble vs Normal housing market. This is achieved by combining TVAR approach and SVAR Identification. I find that in the Bubble regime where house price to income ratio shows an upward trend, leaning against wind policy faces more stronger and prolonged trade-offs between output and house prices. In particular, one year after one percentage point monetary policy shock, the percentage point change in house price growth rate(%p) per percentage loss in output(%) is 3.54 in the Normal regime and 1.53 in the Bubble regime. That is, central banks should take more output loss to curb house prices during house price peaks. Meanwhile, I find that the ratio of house price loss relative to output is 2.58 in a single regime model which does not allow a regime shift. This implies that if one dose not consider the threshold effect in leaning against the wind, there is a serious risk of either under or over estimation.λ³Έκ³ λ λΆλμ° μμ₯μ λ²λΈ μ 무μ λ°λ₯Έ μνμ μ±
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νμ΄λ°μ κ³ λ €νμ§ μλ κ²½μ° κ³Όμ/κ³Όλνκ°μ μνμ΄ μ‘΄μ¬ν¨μ μμ¬νλ€.1 Introduction 2
2 Literature Review 6
3 Methodology 12
3.1 Threshold Vector Autoregression 12
3.2 SVAR Identification 13
3.2.1 Choice of variables 13
3.2.2 Identification 15
4 Empirical Results 21
4.1 Data Description 21
4.2 Effects of a monetary policy shock 23
5 Robustness Check 29
5.1 Single Regime Model 29
5.2 Cholesky Decomposition 33
6 Conclusion 39
Appendix A 48
Appendix B 49
Appendix C 51Maste
Fake News and Fact Check News Differences: Focusing on News Usage, Perception, and Literacy in Multi-Media Environments
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