## 1. After the Storm: Examples of LTV and DTI Limits as Macro-Prudential Tools after the Global Financial Crisis

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---

### I. Introduction — context and research question
- Financial crisis of 2007-08 triggered by downturn in U.S. residential real estate; loosened lending standards (low down-payments, back-loading features, negative amortization) contributed to defaults and losses.
- Pre-crisis policy tenet: “benign neglect” (Bernanke and Gertler, 2001); post-crisis shift toward pre-emptive policy interventions to stop or contain asset price booms.
- Monetary policy viewed as too blunt for real estate booms; macroprudential tools (maximum LTV and DTI limits) advocated as targeted instruments.
- Empirical evidence on mandatory, actively-managed LTV/DTI limits limited; few countries (Korea, Hong Kong SAR, Singapore, Malaysia) have such frameworks in practice.
- Core research questions:
  - What happens when LTV/DTI limits are adjusted in response to perceived risks?
  - Can the impact of LTV and DTI limits on housing and mortgage activity be quantified?

### Research design and data
- Two empirical approaches:
  - Regional dataset exploiting variation across regions with different LTV/DTI limits at different times (monthly frequency; time coverage 2002–10; aggregate series from Bank of Korea and Korea National Statistical Office).
  - Household-level dataset: annual surveys by Kookmin Bank (Survey on Mortgages and Housing Demand), roughly 3000 households each year, covering 2001–2009; matching estimator used to address non-random treatment.
- Policy-change dummy (Phi_r,t) set to 1 in the six months following announcement; additional windows of one or three months after and one, three, or six months before rule change used to assess anticipation and horizon of effects.
- Total interventions in sample: 13 (6 LTV-related and 7 DTI-related); 3 loosened rules; 10 tightening interventions (five LTV and five DTI).

### Key empirical findings — aggregate (macro-level)
- Transaction activity:
  - Average drop in transaction activity in the three-month period following a tightening of loan eligibility criteria: 16 percent for LTV and 21 percent for DTI (aggregate/household-level finding).
  - Regression evidence: At announcement (Transactions, Metro) for DTI: 15.889** [7.816]; One month later (Transactions, Metro): -25.757*** [5.769]; Three months later (Transactions, Metro): -21.163*** [4.860]; Six months later (Transactions, Metro): -10.543* [5.440].
- House price appreciation:
  - Appreciation rates decrease by a monthly rate of 0.5 percent against a historical monthly change of 0.4 percent in the six-month window following a tightening of LTV (aggregate finding).
  - Regression evidence (LTV interventions, Metro):
    - Six months prior (House Prices, Metro): -0.171 [0.260]
    - Three months prior (House Prices, Metro): 0.526** [0.247]
    - At announcement (House Prices, Metro): 0.903* [0.512]
    - One month later (House Prices, Metro): -1.133** [0.463]
    - Three months later (House Prices, Metro): -0.715** [0.319]
    - Six months later (House Prices, Metro): -0.537** [0.248]
  - Event-specific LTV estimates (House Prices, Metro):
    - LTV, September 2002: -1.917*** [0.505]
    - LTV, June 2003: -0.808** [0.358]
    - LTV, October 2003: -0.750** [0.300]
    - LTV, June 2005: -0.688** [0.294]
    - LTV, July 2009: 0.100 [0.250]
  - DTI event-specific price estimates (House Prices, Metro):
    - DTI, August 2005: -0.022 [0.291]
    - DTI, March 2006: -0.292 [0.477]
    - DTI, November 2006: -1.297** [0.509]
    - DTI, February 2007: -0.353 [0.449]
    - DTI, September 2009: -0.171 [0.216]
- Mortgage originations and household debt:
  - Limited evidence of strong effects on growth rates of mortgage loan originations and household debt over studied horizons.
  - DTI appears more closely linked to household debt evolution; loosening DTI shows symmetric effects.
  - Possible mechanism: DTI calculations include payments on non-mortgage loans, inducing debt consolidation to qualify for mortgages and reducing overall household debt despite rising outstanding mortgages.
- Market dynamics:
  - Growth in number of transactions spikes at announcement of tightening then plunges in following months; twelve-month window regressions show the announcement spike disappears.
  - Evidence that markets become more seller-dominated following both tightening and loosening of loan eligibility criteria; DTI tightening particularly effective in shifting market to seller-dominated.

### Key empirical findings — household-level (matching estimator)
- Matching setup:
  - Treated households (subject to rule change) matched to untreated households using income level, financial assets, debt, and price of property; robustness tests with several observables yield similar results.
- Effects on expectations and demand:
  - Both LTV and DTI tightening effective in delaying property purchase decisions.
  - LTV tightening lowers price expectations; DTI tightening does not lower expectations and may raise them in some subsamples.
- Selected household treatment estimates (Table 6):
  - Demand (SATE): -0.045*** [0.015]
  - Upward price expectation (SATE): -0.056** [0.024]
  - Expected price appreciation (SATE, expressed in percent): -1.005** [0.459]
  - Corresponding SATTs:
    - Demand: -0.021 [0.0137]
    - Upward price expectation: -0.065*** [0.021]
    - Expected price appreciation: -1.613*** [0.430]
- Heterogeneous effects (Table 7, selected):
  - Young versus Old, Upward price expectation (LTV, SATE): -0.121** [0.050]
  - DTI, Young, SATT (Upward price expectation): 0.143*** [0.037]
  - First-time home buyers versus speculators, Demand (DTI, SATE): -0.062*** [0.016]
  - Expected price appreciation (First-time buyers, LTV, SATT): -1.862*** [0.569]
- Interpretation of heterogeneity:
  - Older households and speculators show larger responses in expectations and demand than young households and potential first-time buyers.
  - Suggests LTV/DTI limits curb speculative incentives more than they block first-time buyers; limits can be tailored (e.g., by income) to protect certain households.

### Magnitude interpretation and market mechanism
- Larger immediate impact on transaction quantities than on prices:
  - Macroprudential tools primarily affect market quantity (transactions) first; prices adjust more slowly (price discovery concerns).
  - Quantity-first response may either impair price discovery or reflect typical real estate adjustment dynamics.
- Macroprudential tools may work through expectations rather than purely mechanical one-to-one effects proportional to regulatory strength.

### Policy implications and caveats
- Encouraging evidence:
  - Limits on LTV and DTI can tame real estate booms and contain associated financial-sector risks by dampening expectations and speculative incentives.
  - LTV tightening more responsive in price dynamics; DTI tightening more effective on transactions and debt evolution.
- Caveats:
  - Analysis is partial; broader housing policies (supply constraints, expectations of steady appreciation) interact with macroprudential outcomes.
  - Lack of effect on mortgage debt growth suggests LTV/DTI limits may not fully prevent excess leverage if other policies encourage borrowing.
  - Individual welfare costs of excluding households from housing markets need weighing against aggregate welfare gains from preventing bubbles.
  - Detecting bubbles is difficult; policy effectiveness depends on correct identification and timing.

### II. Background: Korean housing and mortgage markets — basic facts and structural characteristics
- Administrative/economic geography:
  - Korea categorized into nine provinces; economically characterized by three areas: Seoul, Metropolitan Area excluding Seoul (including Incheon and remainder of Gyeonggi), and Non-Metropolitan Area (remaining five Gwangyeok cities and rural areas).
  - Seoul subdivided by the Han River into Gangbuk and Gangnam; “Gangnam Three” (Seocho-gu, Gangnam-gu, Songpa-gu) notable for high median home prices and large price fluctuations.
- Structural housing changes and supply:
  - Government-built two million new dwellings between 1988 and 1992.
  - Ratio of housing units to households increased from 72 percent in 1990 to 109.9 percent in 2008.
  - Consumption of housing space per capita rose from 13.8 square meters in 1990 to 22.8 in 2005.
  - Urbanization: 68 percent of households live in urban areas, with almost 70 percent of these in the metropolitan area.
  - Housing stock majority: apartments rather than single-family homes.
  - Homeownership rate: around 55.6 percent as of 2005.
  - Gross value added by the construction industry: about 6.6 percent of total value added.
  - Affordability improved relative to 1980s and 1990s, but regional mismatches persist (notably southern Seoul).
- Housing finance evolution:
  - Deregulation in the second half of the 1990s: commercial banks entered mortgage business in 1996; Korean Housing Bank (KHB) privatized in 1997.
  - Before deregulation, more than 80 percent of mortgage loans held by National Housing Fund (NHF).
  - Outstanding mortgage debt grew from roughly 12 percent in 1996 to slightly more than 30 percent of GDP (contextual figure in source).
- Market structure and mortgage features:
  - Prevalent mortgage features: adjustable rate and 56 percent LTV at origination; maturities up to 20 years are common; majority are “bullet loans” requiring full payment or refinancing after a 3-year period.
  - Banks dominate the mortgage market with a market share exceeding 80 percent.
  - Deposit-based financing remains the norm.
  - Mortgage-backed-security issuance grown to 5.8 percent of total mortgage debt outstanding in 2010.
  - KHFC established in 2004; KHFC purchases long-term mortgages from commercial banks to provide liquidity and increase loan duration availability.
- Macroprudential supervision developments:
  - FSS intervened in real estate markets starting in late 2002.
  - LTV limits introduced in September 2002; DTI limits introduced in August 2005.
  - FSS created the Macroprudential Supervision Department in 2005.

### LTV and DTI regulation timeline, indices, and selected regulatory parameters
- Selected LTV regulatory milestones (preserved exactly):
  - Sept. 6, 2002 – Oct. 14, 2002: 60 (various maturity buckets listed in source)
  - Oct. 14, 2002 – May 23, 2003: 60 (under 3 years / 3~10 years / over 10 years rows)
  - May 23, 2003 – Oct. 29, 2003: under 3 years 50 50 50 50 60 60 (table rows)
  - Oct. 29, 2003 – Mar. 24, 2004: under 3 years 50 40 50 50 60 60; Amortized payment 70 70 70 70 70 70
  - Mar. 24, 2004 – July 4, 2005: Amortized payment 70 70 70 70 70 70
  - July 4, 2005 – Present: over 10 years Over 600mil won 60 40 60 60 60 60; Under 600mil won 60 60 60 60 60 60
  - July 4, 2009 – Present: 3~10 years 60 40 60 50 60 60; Amortized payment over 10 years 70 70 70 70 70 70
- Regulation index construction (method preserved exactly):
  - A score of 1, 1.5, or 2 is assigned for a ratio limit of 60, 50, and 40 percent, respectively. The score is set at 0 for other levels.
  - The index is calculated as the weighted average of these scores where the weights are the measures related to the coverage of the rule in terms of type of lender, loan, and property, and regions.
  - Weights include: the ratio of mortgage loans by banks; the ratio of the number of households in Seoul Metropolitan Area; ratio of number of households in the speculative zones in Seoul; the ratio of mortgage loans with a maturity less than three years; and the ratio of the number of households who own a house valued over 600 million won.
  - When regulations are loosened, only Gangnam Three is kept as the area for which the rules are applicable and an adjustment factor of 0.1 is used to multiply the weighted average.
- Selected LTV index snapshot entries (preserved exactly where given):
  - LTV0 before: 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
  - LTV1 Sep. 2002: 0.6 ...
  - LTV2 June 2003: 0.5 0.5 0.6 0.6 ...
  - LTV3 Oct. 2003: 0.4 0.4 0.4 0.4 0.6 0.6 ...
  - LTV4 June 2005: 0.4 0.4 0.4 0.4 0.6 0.4 0.6 0.6 ...
  - LTV5 Nov. 2006: 0.4 0.4 0.4 0.4 0.6 0.4 0.6 0.6 ...
  - LTV6 Nov. 2008: 0.4 0.4 0.4 0.4 0.6 0.4
  - LTV7 July 2009: 0.4 0.4 0.4 0.4 0.6 0.4 0.6 0.5 0.6 0.5 0.6 0.5
  - LTV8 Oct. 2009: 0.4 0.4 0.4 0.4 0.6 0.4 0.6 0.5 0.6 0.5 0.6 0.5
- Selected DTI index snapshot entries (preserved exactly where given):
  - DTI0 before: 000000 000000
  - DTI1 Aug. 2005: 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4
  - DTI2 Mar. 2006: 0.4 0.4 0.4 0.4 0.4 0.4
  - DTI3 Nov. 2006: 0.4 ...
  - DTI4 Feb. 2007: 0.5 0.4 0.5 0.4 0.5 0.4 0.5 0.4 0.5 0.4 0.5 0.4
  - DTI5 Aug. 2007: 0.5 0.4 ...; 0.6 0.4 0.6 0.4 0.7 0.4 0.7 0.4 0.7 0.4
  - DTI6 Nov. 2008: 0.5 0.4 ...; 0.6 0.4 ... 0.7 0.4 ...
  - DTI7 Sep. 2009: 0.4 0.4 ...; 0.6 0.4 ... 0.7 0.4 ...
  - DTI8 Aug. 2010: 0.40.40.40.40.40.4 0.40.40.40.40.40.40.40.40.40.40.40.4

### Selected descriptive and regional statistics (Appendix highlights)
- Regional concentration:
  - Seoul Metropolitan Area (SMA) occupies 11.8 percent of the geographical area but accounts for 48.1 percent of the population and 56.4 percent of households.
  - SMA accounts for 48.2 percent of GDP and 63.8 percent of housing wealth (value of land stock).
- Housing tenure (2005; units and percentages preserved exactly for selected rows):
  - Korea (Total households 15,887,128):
    - Owned: 8,828,100 (55.6%)
    - Chonsei: 3,556,760 (22.4%)
    - Rented: 3,011,855 (19.0%)
  - SMA (7,462,090 households):
    - Owned: 3,744,978 (50.2%)
    - Chonsei: 2,172,612 (29.1%)
    - Rented: 1,379,158 (18.5%)
  - Seoul (3,309,890 households):
    - Owned: 1,475,848 (44.6%)
    - Chonsei: 1,100,175 (33.2%)
    - Rented: 679,980 (20.5%)
  - Gangnam (subset, 1,660,324 total):
    - Owned: 721,034 (43.4%); Chonsei: 556,352 (33.5%); Rented: 357,092 (21.5%)
- Chonsei rental system (2005 prevalence and mechanism):
  - Chonsei requires a “key money deposit” of about 50 to 90 percent of market value instead of monthly rent; deposit returned in entirety at contract end (usually two or three years).
  - Prevalence in 2005: 22.4 percent of Korean households lived in Chonsei.
  - Ratio of Chonsei contracts: Gangnam area 33.5 percent; rural provinces 13.2 percent.
- Notable price and policy episodes (Figure and timeline highlights preserved):
  - Real house price cycle peaks/troughs: Peak: Nov. 2003; Trough: Jan. 2005; Peak: Jan. 2007; Trough: Apr. 2009.
  - 60 percent LTV limit introduced in September 2002; house price appreciation decelerated from more than 20 percent year-on-year to 9 percent in six months following the policy action.

### Examples of LTV/DTI regulatory choices in other jurisdictions (excerpted table entries)
- "Introduction of maximum LTV of 112 percent with the portion exceeding 100 percent being redeemed in 7 years"
- "Norway Guidelines to limit LTV to 90 percent"
- "Singapore Tightening of rules on LTV that have been in effect since the early 2000s"
- "Sweden Introduction of the maximum LTV of 85 percent"

### Conclusions (preserved exact quantitative and qualitative findings)
- Tightening LTV and DTI regulations is associated with a large drop in transaction activity in the three-month period following tightening; price appreciation slows more in a six-month window.
- Price dynamics appear more responsive to LTV tightening than DTI tightening.
- Survey evidence: LTV tightening lowers expected future house price increases and delays purchase plans—effects concentrated among older households and speculators rather than young or first-time buyers.
- Policy implications:
  - Limits on LTV can curb expectations and speculative incentives, offering an effective tool to tame real estate booms and contain associated risks.
  - Macroprudential tools may work through expectations rather than purely via mechanical strength; they can be tailored to protect targeted households (e.g., by income) while preserving financial stability.

*Source: _wp11297 - 1. After the Storm: Examples of LTV and DTI Limits as Macro-Prudential (PDF chapter/section).*

### 1. After the Storm: Examples of LTV and DTI Limits as Macro-Prudential

### 1. After the Storm: Examples of LTV and DTI Limits as Macro-Prudential Tools after the Global Financial Crisis

### I. Introduction — context and research question
- Financial crisis of 2007-08 was triggered by downturn in U.S. residential real estate; loosened lending standards (low down-payments, back-loading features, negative amortization) contributed to defaults and losses carried into mortgage-backed securities valuations.
- Pre-crisis policy tenet: “benign neglect” (Bernanke and Gertler, 2001); post-crisis shift toward pre-emptive policy interventions to stop or contain asset price booms.
- Monetary policy viewed as too blunt a tool for real estate booms (Posen, 2009); macroprudential tools (maximum LTV and DTI limits) advocated as targeted instruments (Crowe et al., 2011a).
- Empirical evidence on the effectiveness of mandatory, actively-managed LTV/DTI limits is limited; only a few countries (Korea, Hong Kong SAR, Singapore, Malaysia) have such frameworks in practice.

### Research design and data
- Two complementary empirical approaches:
  - Regional dataset exploiting variation across regions with different LTV/DTI limits in effect at different points in time.
  - Household-level dataset from annual surveys conducted by Kookmin Bank, complemented with Bank of Korea data: roughly 2000 households each year, covering 2001 to 2009.
- Two core questions:
  - What happens when LTV/DTI limits are adjusted in response to perceived risks?
  - Can the impact of LTV and DTI limits on housing and mortgage activity be quantified?

### Key empirical findings (aggregate and household-level)
- Transaction activity:
  - Average drop in transaction activity in the three-month period following a tightening of macroprudential regulations on loan eligibility criteria is 16 percent for LTV and 21 percent for DTI.
- House price appreciation:
  - Appreciation rates decrease by a monthly rate of 0.5 percent against a historical monthly change of 0.4 percent in the six-month window following a tightening of LTV.
  - Price appreciation slows in a six-month window rather than the immediate three-month window seen for transactions.
  - Price dynamics appear to be reined in more after LTV tightening than after DTI tightening.
- Mortgage originations and household debt:
  - No strong effect found on growth rates of mortgage loan originations and household debt levels over the studied horizons—possibly due to slow-moving nature of these variables.
- Household survey evidence (matching estimator framework):
  - Expected future house price increases become lower after policy intervention; this effect is more prevalent among older households.
  - Plans to purchase a home are more likely to be postponed by those who already own a property (potential speculators) but not by those who do not own a property (potential first-time buyers).
  - Suggests tighter LTV/DTI limits curb expectations and speculative incentives, with LTV having a more pronounced effect.

### Magnitude interpretation and market mechanism
- Larger immediate impact on transaction quantities than on prices:
  - May indicate macroprudential tools primarily affect market quantity (transactions) first, with prices adjusting more slowly.
  - Raises concerns that price discovery may be impaired if buyers and sellers temporarily exit the market.
  - Alternatively, this quantity-first response may reflect typical real estate market adjustment dynamics.

### Policy implications and caveats
- Encouraging evidence that limits on LTV and DTI can tame real estate booms and contain associated financial-sector risks by dampening expectations and speculative incentives.
- Caveats:
  - Analysis provides only a partial assessment of LTV and DTI regulations; broader housing policies (supply-demand mismatches, expectations of steady appreciation) interact with macroprudential outcomes.
  - Lack of effect on mortgage debt growth suggests LTV/DTI limits may not fully prevent excess leverage buildup if other policies continue to encourage borrowing.
  - Individual welfare costs of excluding some households from housing markets need to be weighed against potential aggregate welfare gains from preventing or curbing bubbles.
  - Detecting bubbles remains difficult; policy effectiveness depends on correct identification and timing.

### II. Background: Korean housing and mortgage markets — basic facts and structural characteristics
- Administrative and economic geography:
  - Korea categorized into nine provinces; economically characterized by three areas: Seoul, Metropolitan Area excluding Seoul (including Incheon and remainder of Gyeonggi), and Non-Metropolitan Area (remaining five Gwangyeok cities and rural areas).
  - Seoul subdivided by the Han River into northern part (Gangbuk) and southern part (Gangnam); “Gangnam Three” (Seocho-gu, Gangnam-gu, Songpa-gu) notable for high median home prices and large price fluctuations.
- Structural housing changes and supply:
  - Government-built two million new dwellings between 1988 and 1992.
  - Ratio of housing units to households increased from 72 percent in 1990 to 109.9 percent in 2008.
  - Consumption of housing space per capita rose from 13.8 square meters in 1990 to 22.8 in 2005.
  - Urbanization: 68 percent of households live in urban areas, with almost 70 percent of these in the metropolitan area.
  - Housing stock majority: apartments rather than single-family homes.
  - Homeownership rate: around 55.6 percent as of 2005.
  - Gross value added by the construction industry: about 6.6 percent of total value added.
  - Affordability (price-to-income) improved compared to 1980s and 1990s, but regional mismatches persist (notably southern Seoul).
- Housing finance deregulation and mortgage market evolution:
  - Deregulation in the second half of the 1990s: commercial banks entered mortgage business in 1996; Korean Housing Bank (KHB) privatized in 1997.
  - Before deregulation, more than 80 percent of mortgage loans held by National Housing Fund (NHF).
  - Outstanding mortgage debt grew from roughly 12 percent in 1996 to slightly more than 30 percent of GDP (date of latter figure appears in source context).

*Source: _wp11297 - 1. After the Storm: Examples of LTV and DTI Limits as Macro-Prudential*

### 1997. H&CB merged with Kookmin Bank in 2001.

### _wp11297 - 1997. H&CB merged with Kookmin Bank in 2001.

### Regulatory approach and institutional changes
- The NHF continues to offer services to lower-income households by securing money through bond issuance and housing subscription savings for building rental homes, helping people take out housing loans, and improving the residential environment.
- Prevalent mortgage features:
  - adjustable rate and 56 percent LTV at origination.
  - maturities up to 20 years are common.
  - majority of mortgages are “bullet loans”, which require full payment or refinancing after a 3-year period.
- Market structure and funding:
  - Banks dominate the mortgage market with a market share exceeding 80 percent.
  - Deposit-based financing remains the norm.
  - mortgage-backed-security issuance has grown to 5.8 percent of total mortgage debt outstanding in 2010 since the establishment of the Korean Housing Finance Corporation (KHFC) in 2004.
  - KHFC purchases long-term mortgages from commercial banks to provide liquidity and increase loan duration availability.
- Macroprudential supervision developments:
  - Following the 1997–98 crisis and the 2003 credit card bubble bust, authorities emphasized monitoring systemic risk and macroprudential supervision.
  - Financial Supervisory Service (FSS) intervened in real estate markets starting in late 2002.
  - LTV limits introduced in September 2002; DTI limits introduced in August 2005.
  - FSS created the Macroprudential Supervision Department in 2005 with a mandate to assess systemic risk using early warning systems and stress tests.
- Policy objectives and toolkit:
  - Overarching policy objective: stable house prices (defined as annual house price appreciation rates within the zero and nominal GDP growth rate band), along with assisting urbanization and providing affordable housing to low-income households.
  - Policy tools include adjustments in LTV and DTI limits, moral suasion on lenders, subsidies to housing finance, tax changes, direct support for private construction, and government supply or purchase of housing units.
  - Strict regulations on land use and redevelopment limit prompt supply response.

### Recent market developments and policy responses (2001–2010)
- Two major housing cycles in the 2001–2010 sample period, split by the trough in March 2005.
- House prices and mortgage loan growth generally move together, indicating a two-way feedback loop.
- Policy-induced restraints on lending standards materially influenced price and credit dynamics; responses varied across geographic regions.
- LTV and DTI limits changed multiple times since launch, varying by level, applicable areas, and types of financial institutions.
- First cycle (post-IT bubble burst):
  - Monetary easing and banks’ household lending contributed to high housing returns.
  - 60 percent LTV limit introduced in September 2002.
  - House price appreciation decelerated from more than 20 percent year-on-year to 9 percent in six months, then accelerated again, prompting two further LTV tightenings.
- Second cycle:
  - Monetary accommodation after the credit card debacle, competition among lenders, and release of large land compensation funds pushed prices up.
  - Higher capital gains taxes and shortage of homes for sale contributed to price increases.
  - Policy responses in early 2007 and October 2009 reined in prices; measures loosened in August 2010 as concerns shifted to “excessive cooling”.
- Timeline and interactions:
  - Since the last trough in April 2009, prices bounced back quickly but started declining again in July 2010, at least in part due to tightening of LTV/DTI limits and moral suasion; policy response reversed in August 2010 and mortgage lending and house prices resumed ascent in late 2010.

### Empirical analysis framework
- Data:
  - Macro-level: house prices, transaction volumes, mortgage loans from Bank of Korea and Korea National Statistical Office; Realtors Association data on “dominance of selling”. Monthly frequency; time coverage 2002–10.
  - Micro-level: Survey on Mortgages and Housing Demand by Kookmin Bank, annual 2001–2009, ~3000 households per year.
- Regional policy designation:
  - “Speculative zones” designated when:
    - monthly nominal house price index (HPI) rose more than 1.3 times nationwide inflation rate (CPI) during the previous month, and
    - either (i) the average of the HPI appreciation rates in the previous two months was higher than 1.3 times the average of the national HPI appreciation rates in the previous two months, or (ii) the average of the month-on-month HPI appreciation rates over the previous year was higher than the average of the month-on-month national HPI appreciation rates over the previous three years.
- Empirical specifications:
  - Baseline OLS regressions of regional housing/mortgage outcomes (house price appreciation rate, number of transactions, mortgage loan growth rate, dominance of selling) on policy-change dummies and control variables (economic activity, monetary policy stance, housing market tightness and expectations).
  - Policy-change dummy (Phi_r,t) set to 1 in the six months following announcement; additional windows of one or three months after and one, three, or six months before rule change used to assess anticipation and horizon of effects.
  - Interventions split into tightenings and loosenings:
    - 13 interventions total in sample: 6 LTV-related and 7 DTI-related.
    - 3 interventions loosened rules (one LTV-related and two DTI-related).
    - 10 tightening interventions (five LTV, five DTI) analyzed first; 3 loosening interventions analyzed separately.
  - Index construction (S_r,t) to capture scope and strength of each intervention based on regions, lender type, borrower type, property, and loan characteristics.

### Macro-level empirical findings
- Aggregate patterns:
  - Average appreciation rate in house prices and growth of transactions and household debt drop considerably following a tightening in LTV and/or DTI; decline in number of transactions particularly striking.
  - Metropolitan areas exhibit different experiences than non-metropolitan areas; tighter rules more likely applicable in metropolitan areas.
- House prices:
  - Price appreciation rates are significantly lower following implementation of an LTV rule tightening (effect observable only in metropolitan areas).
  - DTI tightening coefficients are negative across windows but not statistically significant.
  - Some positive association between price appreciation prior to LTV tightening and implementation of the rule change (could reflect anticipation or reverse causality).
  - Loosening rules: response in appreciation rates is less visible; some negative associations between house price changes and lax rules possibly due to policy decisions reacting to market conditions and price inertia.
- Transaction activity:
  - Growth in number of transactions spikes at announcement of tightening and plunges in following months.
  - DTI tightening appears to affect transactions more than prices.
  - Twelve-month window regressions (not reported) show the transaction spike effect disappears.
- Household debt / mortgage loans:
  - Limited evidence of expected negative association between household leverage growth and tightening of macroprudential rules.
  - DTI appears more closely linked to household debt evolution; loosening DTI shows symmetric effects.
  - Explanation: DTI calculations include payments on non-mortgage loans, possibly forcing debt consolidation to qualify for mortgages, reducing overall household debt despite rising outstanding mortgages.
- Dominance of selling:
  - Evidence that markets become more seller-dominated following both tightening and loosening of loan eligibility criteria.
  - DTI tightening more effective in shifting market to seller-dominated; LTV loosening appears to have stronger effect in creating seller-dominated markets.
- Index-based analysis:
  - Constructed index with higher values for tighter regulation; results not significant.
  - Insignificance may reflect index construction issues or that macroprudential tools work through expectations rather than a one-to-one impact proportional to strength.

### Micro-level empirical findings (household survey, matching estimator)
- Data and methods:
  - Survey covers 2001–2009, ~3000 households annually; disproportional stratified sampling by region.
  - Matching estimator used to address non-random treatment: treated households (subject to rule change) matched to untreated households using income level, financial assets, debt, and price of property.
  - Robustness tests using several sets of observables yield virtually the same results.
- Effects on expectations and demand:
  - Both LTV and DTI tightening are effective in delaying property purchase decisions.
  - Policy intervention pushes down price expectations for LTV tightening but not for DTI tightening.
  - Interpretation:
    - Lowering LTV limits curbs agents’ expectations about future house price gains and alters housing tenure and investment choices, reducing demand.
    - DTI tightening may raise expectations because it signals that those who can still qualify are richer and can pay more.
- Heterogeneity of effects:
  - Common concern: LTV and DTI may disproportionately target young couples or first-time home buyers (those with little savings or income).
  - Split-sample results:
    - Households below age 35 labeled “young”; others “old”.
    - Households who already own property labeled “speculators”; those who do not labeled “first-time home buyers” (may have owned before).
    - Findings indicate older households and speculators are influenced more by policy interventions (expectations and demand) than young households and potential first-time buyers.
    - DTI shows opposite effects on expectations but similar patterns on demand: limits on DTI lead to postponement by older households and speculators but not by young households or potential first-time buyers.
  - Notes:
    - These findings may be specific to Korea and the time period studied.
    - LTV and DTI limits can be tailored (e.g., by income levels) to protect certain households while achieving macroprudential goals.

### Key quantitative points preserved exactly
- 56 percent LTV at origination.
- maturities up to 20 years are common.
- bullet loans require full payment or refinancing after a 3-year period.
- Banks’ market share exceeding 80 percent.
- mortgage-backed-security issuance grown to 5.8 percent of total mortgage debt outstanding in 2010.
- KHFC established in 2004.
- 60 percent LTV limit introduced in September 2002.
- house price appreciation decelerated from more than 20 percent year-on-year to 9 percent in six months.
- Sample period 2001–2010; macroprudential active period 2002–10.
- Two main geographic areas: Seoul Metropolitan Area and Non-Metropolitan Area.
- Matching estimator household survey period 2001–2009, around 3000 households each year.
- Total interventions in sample: 13 (6 LTV-related and 7 DTI-related); 3 loosened rules; 10 tightening interventions (five LTV and five DTI).

### Conclusions and policy implications
- Tightening LTV and DTI regulations is associated with a large drop in transaction activity in the three-month period following tightening; price appreciation slows more in a six-month window.
- Price dynamics appear to be more responsive to LTV tightening than DTI tightening.
- Survey evidence suggests the channel of impact is partly through expectations: LTV tightening lowers expected future house price increases and delays purchase plans—effects concentrated among older households and speculators rather than young or first-time buyers.
- Policy implications:
  - Limits on LTV can curb expectations and speculative incentives, offering an effective tool to tame real estate booms and contain associated risks.
  - Macroprudential tools may work through expectations rather than purely via mechanical strength; they can be tailored to protect targeted households (e.g., by income) while preserving financial stability.

*Source: _wp11297 - 1997. H&CB merged with Kookmin Bank in 2001.*

### Appendix Table 1. Basic Charateristics by Regions in Korea

### _wp11297 - Appendix Table 1. Basic Charateristics by Regions in Korea

### Regional population, household, housing, and land stock characteristics (As of 2005)
- Size of Area (%) — 100.0; 11.8 0.6 --11.2 88.2 3.8 84.4
- Population (10 thousand) — 4,704; 2,262.1 976.3 487.2 489.0 1,285.9 2,442.0 986.6 1,455.5
- Population Ratio by Region (%) — 100.0; 48.1 20.8 10.4 10.4 27.3 51.9 21.0 30.9
- Population Growth Rate (%) — 0.2; 0.7 -0.3 --1.2 -0.1 -0.2 -0.0
- Population Density (Person/Km2) — 474.5; 1,941.9 16,221.0 --1,164.0 278.9 2,641.8 173.6
- Number of Households (10 thousand) — 1,588.7; 746.2 331.0 165.0 166.0 415.2 842.5 327.9 514.6
- Household Ratio by Region (%) — 100.0; 56.4 25.0 12.5 12.6 31.4 63.7 24.8 38.9
- Number of House Units — 1,562.3; 716.5 310.2 --406.3 845.8 318.1 527.7
- House Supply Rate (%) — 98.3; 96.0 93.7 --98.3 100.2 97.0 102.1
- House Ownership Rate (%) — 55.6; 50.2 44.6 45.8 43.4 54.6 60.3 55.1 63.7
- Type of Housing (Apartments) (%) — 52.7; 58.2 54.2 48.9 59.6 60.8 48.4 61.6 41.2
- Median Apartment Price (10 Thousand Won) — 23,470.4; 35,388.5 51,177.0 38,773.7 61,530.7 26,864.8 11,277.15 13,381.5 9,172.8
- Value of Land Stock (billion won) — 2,753,001; 1,757,436 867,136 --890,300 995,565 360,886 634,679
- Ratio by Region (%) (land stock) — 100.0; 63.8 31.5 --32.3 36.2 13.1 23.1
- GDP (billion won) — 869,304; 418,612 208,899 --209,713 450,691 157,448 293,243
- GDP Ratio by Region (%) — 100.0; 48.2 24.0 --24.1 51.8 18.1 33.7
- Median Household Income (Gross) (10 thousand won) — 3,035.9; 3,132.3 3,501.4 --2,947.8 2,800.6 2,928.9 2,720.3
- Ratio of College Graduates (%) — 35.5; 41.4 46.0 40.5 51.4 37.7 30.4 36.2 26.6
- Median Age — 34.8; 33.9 34.1 --33.8 35.7 33.9 36.8
- Age of Household Head — 47.9; 46.2 46.6 47.2 46.0 45.9 49.4 47.6 50.6

- Key descriptive findings from the table:
  - Seoul Metropolitan Area (SMA) occupies only 11.8 percent of the geographical area but accounts for 48.1 percent of the population and 56.4 percent of households.
  - SMA accounts for 48.2 percent of GDP and 63.8 percent of housing wealth (value of land stock).
  - Compared to the Non-Metropolitan Area (NMA), unemployment rate and household gross incomes are higher by 1.3 percentage points and 11.8 percent, respectively (as stated in the source text).
  - In Gangnam, median apartment price is 2.6 times the median price in the country and 6.7 times higher than the median apartment price in rural provinces (as stated in the source text).

### Chonsei rental system (descriptive summary and 2005 prevalence)
- Mechanism and features:
  - Chonsei requires the renter to make a “key money deposit” of about 50 to 90 percent of the market value of the rental space instead of paying monthly rent.
  - Deposit is returned in its entirety at the end of the contract (usually two or three years).
  - Early termination requires another renter to replace the outgoing renter.
  - Owners can invest the deposit during the contract period; high interest rates and owners’ faithful return of deposits are necessary for the system to function.
  - In the past decades interest rates in Korea were relatively high, supporting Chonsei profitability for owners; rising house prices enabled some owners to use Chonsei deposits as leverage for additional property purchases.
- Prevalence in 2005:
  - 22.4 percent of Korean households lived in Chonsei.
  - Ratio of Chonsei contracts: Gangnam area 33.5 percent; rural provinces 13.2 percent (Appendix Table 2 reference in source).

### Housing tenure breakdown (Appendix Table 2, 2005; Unit: # of Household, %)
- Korea (Total households 15,887,128):
  - Owned: 8,828,100 (55.6%)
  - Chonsei: 3,556,760 (22.4%)
  - Rented: 3,011,855 (19.0%)
  - etc: 490,413 (3.1%)
- SMA (7,462,090 households):
  - Owned: 3,744,978 (50.2%)
  - Chonsei: 2,172,612 (29.1%)
  - Rented: 1,379,158 (18.5%)
  - etc: 165,342 (2.2%)
- Seoul (3,309,890 households):
  - Owned: 1,475,848 (44.6%)
  - Chonsei: 1,100,175 (33.2%)
  - Rented: 679,980 (20.5%)
  - etc: 53,887 (1.6%)
  - Gangbuk (subset) — 1,649,566 total; Owned 754,814 (45.8%); Chonsei 543,823 (33.0%); Rented 322,888 (19.6%); etc 28,041 (1.7%)
  - Gangnam (subset) — 1,660,324 total; Owned 721,034 (43.4%); Chonsei 556,352 (33.5%); Rented 357,092 (21.5%); etc 25,846 (1.6%)
- Incheon & Gyeonggi (4,152,200 households):
  - Owned: 2,269,130 (54.6%)
  - Chonsei: 1,072,437 (25.8%)
  - Rented: 699,178 (16.8%)
  - etc: 111,455 (2.7%)
- NMA (8,425,038 households):
  - Owned: 5,083,122 (60.3%)
  - Chonsei: 1,384,148 (16.4%)
  - Rented: 1,632,697 (19.4%)
  - etc: 325,071 (3.9%)
  - 5 Major Cities — Total 3,279,013; Owned 1,806,645 (55.1%); Chonsei 702,559 (21.4%); Rented 686,506 (20.9%); etc 83,303 (2.5%)
  - Rural Area — Total 5,146,025; Owned 3,276,477 (63.7%); Chonsei 681,589 (13.2%); Rented 946,191 (18.4%); etc 241,768 (4.7%)

### LTV and DTI regulation timeline and index construction (Appendices 3–5)
- LTV limits across loan classes and regions (selected timeline entries preserved exactly):
  - Sept. 6, 2002 – Oct. 14, 2002: under 3 years N/A N/A 60 60 N/A N/A; 3~10 years N/A N/A 60 60 N/A N/A; over 10 years N/A N/A 60 60 N/A N/A
  - Oct. 14, 2002 – May 23, 2003: under 3 years 60 60 60 60 60 60; 3~10 years 60 60 60 60 60 60; over 10 years 60 60 60 60 60 60
  - May 23, 2003 – Oct. 29, 2003: under 3 years 50 50 50 50 60 60; 3~10 years 60 60 60 60 60 60; over 10 years 60 60 60 60 60 60
  - Oct. 29, 2003 – Mar. 24, 2004: under 3 years 50 40 50 50 60 60; 3~10 years 60 40 60 60 60 60; over 10 years 60 60 60 60 60 60
  - Mar. 24, 2004 – July 4, 2005: under 3 years 50 40 50 50 60 60; 3~10 years 60 40 60 60 60 60; over 10 years Balloon payment 60 60 60 60 60 60; Amortized payment 70 70 70 70 70 70
  - July 4, 2005 – Present: under 3 years 50 40 50 50 60 60; 3~10 years 60 40 60 60 60 60; over 10 years Over 600mil won 60 40 60 60 60 60; Under 600mil won 60 60 60 60 60 60; Amortized payment over 10 years 70 70 70 70 70 70
  - July 4, 2009 – Present (Seoul / non-speculative zone and Gyeongi Province / Other Areas breakdown preserved):
    - under 3 years 50 40 50 50 60 60
    - 3~10 years 60 40 60 50 60 60
    - over 10 years Over 600mil won 60 40 60 50 60 60
    - Under 600mil won 60 60 60 60 60 60
    - Amortized payment over 10 years 70 70 70 70 70 70
- Regulation index construction (key method notes and preserved scoring rules):
  - A score of 1, 1.5, or 2 is assigned for a ratio limit of 60, 50, and 40 percent, respectively. The score is set at 0 for other levels.
  - The index is calculated as the weighted average of these scores where the weights are the measures related to the coverage of the rule in terms of type of lender, loan, and property, and regions.
  - These weights include: the ratio of mortgage loans by banks, the ratio of the number of households in Seoul Metropolitan Area, ratio of number of households in the speculative zones in Seoul, the ratio of mortgage loans with a maturity less than three years, and the ratio of the number of households who own a house valued over 600 million won.
  - When regulations are loosened, only Gangnam Three is kept as the area for which the rules are applicable and an adjustment factor of 0.1 is used to multiply the weighted average.
- Selected LTV index values (as presented in the table rows, preserved exactly where given):
  - LTV0 before: 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
  - LTV1 Sep. 2002: 0.6 ... (values repeated across categories in source table)
  - LTV2 June 2003: 0.5 0.5 0.6 0.6 ...
  - LTV3 Oct. 2003: 0.4 0.4 0.4 0.4 0.6 0.6 ...
  - LTV4 June 2005: 0.4 0.4 0.4 0.4 0.6 0.4 0.6 0.6 ...
  - LTV5 Nov. 2006: 0.4 0.4 0.4 0.4 0.6 0.4 0.6 0.6 ...
  - LTV6 Nov. 2008: 0.4 0.4 0.4 0.4 0.6 0.4
  - LTV7 July 2009: 0.4 0.4 0.4 0.4 0.6 0.4 0.6 0.5 0.6 0.5 0.6 0.5
  - LTV8 Oct. 2009: 0.4 0.4 0.4 0.4 0.6 0.4 0.6 0.5 0.6 0.5 0.6 0.5
- DTI index entries and timeline (selected preserved entries):
  - DTI0 before: 000000 000000
  - DTI1 Aug. 2005: 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4
  - DTI2 Mar. 2006: 0.4 0.4 0.4 0.4 0.4 0.4
  - DTI3 Nov. 2006: 0.4 ... (values repeated across categories)
  - DTI4 Feb. 2007: 0.5 0.4 0.5 0.4 0.5 0.4 0.5 0.4 0.5 0.4 0.5 0.4
  - DTI5 Aug. 2007: 0.5 0.4 0.5 0.4 0.5 0.4 0.5 0.4 0.5 0.4 0.5 0.4; 0.6 0.4 0.6 0.4 0.6 0.4 0.7 0.4 0.7 0.4 0.7 0.4
  - DTI6 Nov. 2008: 0.5 0.4 ...; 0.6 0.4 ... 0.7 0.4 ...
  - DTI7 Sep. 2009: 0.4 0.4 ...; 0.6 0.4 ... 0.7 0.4 ...
  - DTI8 Aug. 2010: 0.40.40.40.40.40.4 0.40.40.40.40.40.40.40.40.40.40.40.4

### Speculative zone designations (Appendix Table 4)
- Notable points preserved from the source:
  - Gangnam Three (consisting of three boroughs: Seocho-gu, Gangnam-gu, Songpa-gu) has been the only speculative zone since December 2008 (source text statement).
- Appendix Table 4 provides a time series marking areas designated speculative zone status across periods from 2001.1 through 2010.12 with O and X markers in the source table (preserved as a structured timeline in the original).

*Source: _wp11297 - Appendix Table 1. Basic Charateristics by Regions in Korea (PDF chapter content provided).*

### Introduction of maximum LTV of 112 percent

### Introduction of maximum LTV of 112 percent

### Examples of LTV and DTI limits after the Global Financial Crisis
- "Introduction of maximum LTV of 112 percent with the portion exceeding 100 percent being redeemed in 7 years"
- "NorwayGuidelines to limit LTV to 90 percent"
- "Singapore Tightening of rules on LTV that have been in effect since the early 2000s"
- "SwedenIntroduction of the maximum LTV of 85 percent"
- Sources cited in the table: Crowe et al. (2011), IMF (2011), and references therein.

### Timeline of LTV regulations (selected entries from Table 2a)
- Sept. 2002: Introduced the LTV ceiling as 60 percent; Range of Application: Banks & Insurance Companies; Direction: Inception
- June 2003: Reduced the LTV from 60 to 50 percent for loans of 3 years and less maturity to buy houses in the speculative zones; Range of Application: Banks & Insurance Companies; Direction: Tighten
- Oct. 2003: Reduced the LTV from 50 to 40 percent for loans of 10 years and less maturity to buy houses in the speculative zones; Range of Application: Banks & Insurance Companies; Direction: Tighten
- March 2004: Raised the LTV from 60 to 70 percent for loans of 10 years or more maturity and less than one year of interest-only payments; Range of Application: All Financial Institutions; Direction: Loosen
- June 2005: Reduced the LTV from 60 to 40 percent for loans of 10 years and less maturity to buy houses worth 600 million won and more in the speculative zones; Range of Application: Banks & Insurance Companies; Direction: Tighten
- Nov. 2006: Set the LTV ceiling as 50 percent for loans of 10 years and less maturity to buy houses worth 600 million won and more in the speculative zones and originated by nonbank financial institutions such as mutual credits, mutual savings banks, and credit-specialized financial institutions; Range of Application: Extended to Nonbank Financial Institutions; Direction: Tighten
- Nov. 2008: Removed all areas except the three Gangnam districts off the list of speculative zones; Range of Application: All Financial Institutions; Direction: Loosen
- July 2009: Reduced the LTV from 60 to 50 percent for loans to buy houses worth 600 million won and more in the metropolitan area; Range of Application: Banks; Direction: Tighten
- Oct. 2009: Expand the LTV regulations to all financial institutions for the metropolitan area; Range of Application: Nonbank Financial Institutions; Direction: Tighten

### Timeline of DTI regulations (selected entries from Table 2b)
- Aug. 2005: Introduced the DTI ceiling as 40 percent for loans used to buy houses in the speculative zones only if the borrower is single and under the age of 30 or if the borrower is married and the spouse has debt; Range of Application: All Financial Institutions; Direction: Inception
- Mar. 2006: Set the DTI ceiling as 40 percent for loans to buy houses worth 600 million won and more in the speculative zones; Range of Application: All Financial Institutions; Direction: Tighten
- Nov. 2006: Extended the range of application of DTI regulation to the overheated speculation zones in the metropolitan area; Range of Application: All Financial Institutions; Direction: Tighten
- Feb. 2007: Set the DTI ceiling as 40~60 percent for loans to buy houses worth 600 million won and less; Range of Application: Banks; Direction: Tighten
- Aug. 2007: Set the DTI ceiling as 40~70 percent for loans originated by nonbank financial institutions such as insurance companies, mutual savings banks, and credit-specialized financial institutions; Range of Application: Extended to Nonbanking Institutions; Direction: Tighten
- Nov. 2008: Removed all areas except the three Gangnam districts off the list of speculative zones (so, the DTI regulation does not apply to the metropolitan areas); Range of Application: All Financial Institutions; Direction: Loosen
- Sept. 2009: Extended the range of application of DTI regulation to the non-speculative zones in Seoul and the metropolitan area (Gangnam Three 40 percent, non-speculative zones in Seoul 50 percent, the other metropolitan areas 60 percent); Range of Application: Banks; Direction: Tighten
- Aug. 2010: Exempted the loans to buy houses in the non-speculative zones of the metropolitan area if the debtor owns less than two houses (set to expire by end-March 2011); Range of Application: All Financial Institutions; Direction: Loosen

### Empirical impacts of interventions on housing and mortgage market activity (Tables 3a, 3b, 4a, 4b — selected reported estimates)
- Regression setup notes:
  - Data are at monthly frequency. Sample period: January 2000 to December 2010.
  - Dependent variables include log change in real house prices, number of transactions, seller dominance, and household debt level.
  - LTV and DTI intervention variables are dummy variables for respective periods before/following the intervention.
  - Controls include lagged house price change, mortgage loan rate, log changes in M2, unsold inventory of properties, composite index of coincident indicators, and KOSPI.
  - 'Metro' refers to the Seoul Metropolitan Area. 'Non-Metro' are all remaining areas.
  - Newey-West standard errors, with maximum lag of 2, are in square brackets. ***, **, and * denote significance at the 1, 5, and 10 percent level, respectively.

- Selected point estimates and significance (LTV interventions, Metro vs Non-Metro):
  - Six months prior (House Prices, Metro): -0.171 [0.260]
  - Three months prior (House Prices, Metro): 0.526** [0.247]
  - At announcement (House Prices, Metro): 0.903* [0.512]
  - One month later (House Prices, Metro): -1.133** [0.463]
  - Three months later (House Prices, Metro): -0.715** [0.319]
  - Six months later (House Prices, Metro): -0.537** [0.248]

- Selected point estimates and significance (DTI interventions, Metro vs Non-Metro):
  - Three months prior (Seller Dominance, Non-Metro): 0.220* [0.116]
  - One month prior (Seller Dominance, Metro): 0.351*** [0.075]
  - At announcement (Transactions, Metro): 15.889** [7.816]
  - One month later (Transactions, Metro): -25.757*** [5.769]
  - Three months later (Transactions, Metro): -21.163*** [4.860]
  - Six months later (Transactions, Metro): -10.543* [5.440]

- Selected LTV event-specific estimates (Table 4a, separate dummies):
  - LTV, September 2002 (House Prices, Metro): -1.917*** [0.505]
  - LTV, June 2003 (House Prices, Metro): -0.808** [0.358]
  - LTV, October 2003 (House Prices, Metro): -0.750** [0.300]
  - LTV, June 2005 (House Prices, Metro): -0.688** [0.294]
  - LTV, July 2009 (House Prices, Metro): 0.100 [0.250]

- Selected DTI event-specific estimates (Table 4a, separate dummies):
  - DTI, August 2005 (House Prices, Metro): -0.022 [0.291]
  - DTI, March 2006 (House Prices, Metro): -0.292 [0.477]
  - DTI, November 2006 (House Prices, Metro): -1.297** [0.509]
  - DTI, February 2007 (House Prices, Metro): -0.353 [0.449]
  - DTI, September 2009 (House Prices, Metro): -0.171 [0.216]

### Household-level survey results (Tables 5, 6, 7 — selected statistics and treatment effects)
- Table 5 summary statistics before and after matching (selected mean comparisons; p-values shown):
  - Income: Treated 2.99, Untreated 2.76, p-value 0.00
  - Financial assets: Treated 62.54, Untreated 47.25, p-value 0.00
  - Debt: Treated 36.79, Untreated 28.17, p-value 0.00
  - Property price (mean): Treated 144.53, Untreated 111.93, p-value 0.00

- Table 6: Effect of policy tightening on household decisions (selected SATE and SATT estimates)
  - Demand (SATE): -0.045*** [0.015]
  - Upward price expectation (SATE): -0.056** [0.024]
  - Expected price appreciation (SATE, expressed in percent): -1.005** [0.459]
  - Corresponding SATTs: Demand -0.021 [0.0137], Upward price expectation -0.065*** [0.021], Expected price appreciation -1.613*** [0.430]

- Table 7: Heterogeneous effects by household groups (selected entries)
  - Young versus Old, Upward price expectation (LTV, SATE): -0.121** [0.050]; (DTI, Young, SATT): 0.143*** [0.037]
  - First-time home buyers versus speculators, Demand (DTI, SATE): -0.062*** [0.016]
  - Expected price appreciation (First-time buyers, LTV, SATT): -1.862*** [0.569]
  - Notes: Young defined as age of head of household <= 35. First-time buyers vs speculators defined by current property ownership status. Standard errors in square brackets.

### Descriptive figures and trends (selected highlights)
- Figure 1. House Price Cycles in Korea: 2001-2010
  - Real house prices (Index, Jan. 2005=100)
  - Peaks and troughs reported: Peak: Nov. 2003; Trough: Jan. 2005; Peak: Jan. 2007; Trough: Apr. 2009
  - Source: Bank of Korea.

- Figure 2. Policy Interventions: LTV and DTI Adjustments
  - Plots real house prices (Year-on-year change, percent, LHS) and real house prices (Index, Jan. 2005=100)
  - Intervention legend: Intervention: Tighten; Intervention: Loosen
  - Sources: Bank of Korea and Financial Supervisory Service.

- Figure 3. Housing and Mortgage Market Activity following Policy Interventions
  - Shows differences between average growth rate during the six-month period before and after the LTV rule change and DTI rule change for Prices, Transactions, Mortgages, Seller dominance, across Whole country, Metropolitan, Non-metropolitan
  - Sources: Bank of Korea, Financial Supervisory Service, Korea Realtors' Association, authors' calculations.

_Italic: Source: _wp11297 - Introduction of maximum LTV of 112 percent (PDF chapter/section)._

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2011/_wp11297.pdf_