2022-08-02-莱坊-Industrial_Land_Values_2022_10页_5mb

Summary of Industrial Land Values (2022 Research)

Core Content

Industrial land values in the UK have experienced significant growth over the past few years. This report analyzes the reasons behind this increase, quantifies the growth, and outlines future expectations and risks.

Main Points

• Land Value Growth:

  • Industrial land values rose 60% in the year to Q1 2022.
  • Over the past three years, land values have more than doubled, with a 163% increase.
  • Between Q1 2020 and Q1 2022, land values almost tripled, showing a 196% increase.

• Drivers of Growth:

  • Rental income is the key determinant of land values.
  • Capital growth expectations have also gained importance, with 58% of the value increase attributed to rising rental income and growth assumptions, and 42% to capital growth and forecast revisions.
  • Rental growth has increased from 1.9% per annum in Q1 2019 to 5% per annum in Q1 2022.
  • Capital growth expectations have risen from 1.6% over five years to 5.6% per annum (2022-2026).

• Location Analysis:

  • London Boroughs have seen the strongest growth, particularly Inner London.
  • Kensington & Chelsea, Tower Hamlets, Westminster, Camden, and Ealing are the top London areas for land value increases.
  • Brent, Enfield, Havering, and Merton also showed strong growth due to capital growth and forecast revisions.
  • Non-London areas such as Spelthorne, Watford, and Aylesbury Vale have seen significant growth, with some locations experiencing 238% increases.

• Investor-Developer Partnerships:

  • These partnerships allow investors to consider long-term growth in rents and capital values beyond the development horizon.
  • This structure enables higher land values by incorporating longer hold periods and future income streams.

• Model Assumptions and Application:

  • The model uses standard assumptions for 20,000 sq m warehouses, site density, lease terms, and investment hold periods.
  • It does not account for micro locational factors, unique developments, or sustainability standards.
  • The model was applied to 377 local authorities across the UK, with results from Q1 2019 to Q1 2022 and a three-year forecast.

• Future Expectations:

  • London Boroughs of Newham and Tower Hamlets are expected to see the highest growth in land values over the next three years, at 40%.
  • Rental and capital growth will continue to be the main drivers of future land value increases.

• Downside Risks:

  • A 50bps softening of prime yields could reduce land values by 10% in certain areas.
  • A 20% downward revision in rental growth forecasts could lower growth expectations in Newham from 40% to 37%.
  • Markets with negative land values may still be viable for development, but not necessarily from an investment standpoint.

• Viable Markets:

  • Several areas, including Mansfield, Newark & Sherwood, Corby, and Salford, have moved from negative to positive land values, indicating they have crossed the viability threshold for development.

Key Information

• Prime Land Values:

  • The highest prime land values were in Park Royal, West London at £22.7 million per acre, followed by Greenford, Ealing at £20.8 million per acre, and Bow, Tower Hamlets at £19.8 million per acre.
  • Outside of London, Birmingham had the highest prime land values at £2.6 million per acre, followed by Manchester at £2.2 million per acre and Northampton at £2.0 million per acre.

• Model Limitations:

  • The model does not adjust for changing market conditions or unique site characteristics.
  • It is based on average rents and capital values, which may not reflect prime site values or specific development requirements.

• Conclusion:

  • Industrial land values have surged due to strong rental and capital growth expectations.
  • London remains the strongest market, with Newham and Tower Hamlets as top growth areas.
  • While the model provides insights into future trends, it highlights the need to consider prime site factors and market-specific conditions when evaluating land values.