Key geolocation attributes of logistics rents
In this note we evaluate the importance of geolocation specific attributes of logistics real estate assets on rents achieved at asset level. Understanding geolocation attributes is critical in estimating fair value rents at more granular level compared to general markets rents, valuations and pricing of assets as well as guiding investment and operational decisions in managing logistics assets.
In our previous note, (Pricing geolocation attributes in logistics assets — Kania (kaniaadvisors.com) we showed how road traffic activity might impact risk characteristics and pricing of logistics real estate by monitoring the volatility of traffic flows, using data for Germany as the largest European economy. We have also published several notes on the importance of freight volumes and road transport activity across markets and geolocations as main drivers of demand and rental growth in the sector. Here we present the impact of those geolocation attributes as key determinants of rents achieved for individual assets.
We use data for a portfolio of over 100 assets in the US for which we have full property level information such as rents, vacancy levels, location, size of the asset, valuations and if the asset is classified as logistics warehouse or industrial. The assets are spread geographically throughout the US which provides a good level of market diversification as well as representative ranges of property specific metrics. We combine this information with economic and demographic data such as population within 30min and 60min drive time of the asset, distance to main road network, flow of goods through main freight handling locations within the relevant market and road transport activity in the vicinity of the asset. Combined, these metrics capture both structural and cyclical factors that impact logistics activity both at market level and at specific asset geolocations. We use the data to estimate an econometric model, the output of which is shown below along with the significance of factors on rents achieved. The correlation between actual rents and model predicted rents is ca 70%. In addition, all the geolocation specific factors are highly significant in explaining logistics rents for specific assets.
The results illustrate the importance of incorporating geolocation data across business functions to optimise location selection, cash flow generation and value from logistics real estate exposures and allocations.
Also, while population catchment areas are relatively structural and stable, the cyclical nature of freight volumes across markets and road transport activity in the vicinity of logistics assets reflect dynamic economic and consumer conditions and provide a 1-1.5 year leading indicator of demand and rental growth. Investors can utilise geolocation specific data to optimize investment processes, identify opportunities as well as ongoing asset and risk management.
Note: t-statistics for the attributes used are
population catchment: 4.85, highly significant
freight volumes: 5.34, highly significant
road transport activity: 2.72, highly significant
access to major road network: -2.45, highly significant, the negative sign implies as expected that locations further from major distribution roads have a negative impact on rents
logistics warehouse/industrial: 3.07, highly significant, dummy variable to indicate asset type
t-statistics are not sensitivities and do not illustrate the impact of a variable, if you would like to discuss any aspects of this note please contact info@kaniaadvisors.com.
Geolocation attributes are critical metrics for investors to incorporate in their decision process to gain detailed insights, monitor changing market conditions for their assets and to improve outcomes across business functions.
Data and analytics
Freight volumes and road transport activity are a leading indicator of logistics rental growth with ca 1-1.5 year lead time, see previous notes.
Kania Advisors logistics analytics is built to provide allocators and investors with live access to monitor logistics activity that drives market rents and asset values from macroeconomic conditions to specific geolocation. Our analytics and data tracks any market, any location and any asset (or potential asset such as land plots), across Europe and the US, and provides;
- information of logistics activity at cargo handling locations across the continents,
- information on volume of goods flowing across any market
- road transport activity of how goods are distributed across markets and main distribution road network
- road transport activity and longer term trends in the vicinity of any asset
- asset level competitive metrics such as population reach within 30min and 60min drive times, drive time weighted distance to cargo handling locations, access and density of transport distribution routes
- overlay with macroeconomic and demographic data and/or user specific data
- ML algorithms to identify clusters and tail risks across portfolios
- ability to benchmark an assets' competitive position compared to institutional quality logistics assets across markets
About Kania Advisors
Kania Advisors is an independent research and advisory firm focused exclusively on institutional real assets allocations and investment programmes. We provide advice and solutions to improve outcomes in real assets investment programmes. We conduct detailed industry research and custom studies typically focused on quantitative analysis and provide insights which form a critical part of a client's decision process.