2018年-FCA英国金融行为监管局_ms16_2_2_annex_8_8页_781kb

Summary of MS16/2.2: Annex 8 - Econometric Analysis for Assessing the Impact of Commercial Relationships

Core Content

This document presents an econometric analysis to evaluate the potential impact of commercial relationships between mortgage intermediaries and other entities (such as estate agencies, developers, and ancillary service providers) on the prices and fees of mortgages. The study focuses on first-time buyers and home movers in the UK, using data from the Product Sales Data 001 (PSD001), a regulatory dataset collected quarterly by the FCA.

The analysis is conducted using a regression model that controls for borrower, product, and property characteristics, as well as regional and time fixed effects. The goal is to determine whether intermediaries with commercial ties recommend more expensive mortgage products, and whether these relationships influence the fees charged to consumers.

Main Methodology

1. Baseline Regression Model

The regression model is structured as follows:

$$
\text {Price}_{\text{libt}} = \theta X_i + \phi Y_p + \beta \text{Commercial Ties}b + \gamma B_b + \epsilon Z_d + f_t + f_a + e{\text{iblt}}
$$

• Price$_{\text{libt}}$: The price of the mortgage provided by lender $l$, sold to borrower $i$ by intermediary $b$ at time $t$.
• $X_i$: Borrower characteristics (e.g., age, credit score, income basis).
• $Y_p$: Product characteristics (e.g., LTV bands, mortgage terms, loan value).
• $Z_d$: Property characteristics.
• $f_t$: Year-month fixed effects.
• $f_a$: Regional area fixed effects (based on outward postcode).
• $\beta$: The coefficient of interest, indicating whether intermediaries with commercial ties recommend more expensive products.

The model is estimated using Ordinary Least Squares (OLS) with standard errors clustered at the intermediary level to account for correlated behaviors among borrowers using the same intermediary.

Key Findings

1. Impact on Mortgage Prices

• Commercial ties with developers: The coefficient for the dummy variable (indicating commercial ties) is not statistically significant at 5%. This suggests no evidence that intermediaries with ties to developers charge higher mortgage prices, even after controlling for borrower, product, and property characteristics.
• Commercial ties with estate agents: Similarly, the coefficient for the dummy variable is not statistically significant. There is no evidence that such ties lead to higher mortgage prices.
• Commercial ties with ancillary service providers (valuation and conveyancing): Again, the coefficient is not statistically significant, indicating no evidence of higher mortgage prices due to these ties.

2. Impact on Intermediary Fees

• Commercial ties with estate agents: The coefficient for the dummy variable is not statistically significant, suggesting that intermediaries with ties to estate agents do not charge significantly higher fees on average.
• Other factors influencing fees:
  • Credit score: Borrowers with lower credit scores pay higher intermediary fees, possibly due to more complex applications.
  • LTV band:
    • 65%-75%: Lower fees (significant at 10%).
    • 75%-85%: No significant effect.
    • 85-95%: Higher fees (significant at 5%).

    • 95%: Higher fees (significant at 1%).

  • LTI band:
    • 2-3.5: Lower fees (significant at 10%).
    • 3.5-4.5: No significant effect.

    • 4.5: Higher fees (significant at 5%).

  • Age:
    • 30-40 years: Higher fees (significant at 1%).
    • 40-50 years: Higher fees (significant at 1%).

    • 50 years: Higher fees (significant at 1%).

  • Impaired credit history: Borrowers with impaired credit history pay higher fees (significant at 1%).
  • Home movers: Pay lower fees (significant at 1%).
  • Loan value (log): Higher loan values are associated with lower fees (significant at 1%).

Sample Construction

• Data source: Product Sales Data 001 (PSD001), which includes all regulated first-charge mortgage transactions in the UK.
• Sample focus: Mortgages sold in 2015, targeting first-time buyers and home movers.
• Exclusions: Specialist mortgages such as equity release, bridging loans, and mortgages for high net worth individuals.
• Borrower characteristics: Restricted to full-time employed individuals.
• Product characteristics: Only 2-year fixed interest rate mortgages with capital and interest repayment are included.
• Commercial ties identification: Based on merging PSD001 with data from the Mortgage Market Study survey.

Conclusion

The econometric analysis of commercial relationships between intermediaries and developers, estate agents, and ancillary service providers does not provide evidence that these relationships lead to higher mortgage prices or fees. The study finds that other factors, such as borrower characteristics, LTV and LTI bands, and credit history, have a more significant impact on mortgage prices and intermediary fees. The results suggest that commercial ties do not appear to harm consumers in terms of price or fee, when controlling for relevant variables.

The analysis was conducted using a robust model that accounts for regional and temporal variations, and the findings are consistent across different types of commercial relationships.