Will Matthews

Will Matthews is a partner at Knight Frank

The sense of déjà vu is palpable – we might fight about the numbers, but few would contest the notion that we’re into another phase of economic uncertainty. In the abridged story, rising inflation must be defeated, albeit by central bankers using tools so blunt that serious collateral damage to economic output is an increasing risk.

However, in contrast to the wild volatility of pandemic-era growth, current events are unfolding at a slightly slower pace. We should use this relative luxury to reflect on lessons learned – if any. In particular, we might take greater heed of some of our human biases, which behavioural scientists tell us tend to creep in during downturns.

Behavioural science is a deep and fascinating subject which seeks to understand, among other things, how people make decisions under conditions of uncertainty. It has been brought to life through many practical experiments and ground-breaking studies over the past 70 years. The focus of the subject’s pioneering researchers has roved from equity markets and investment committees to personal finance and games of chance – in short, all areas in which people grapple with a thorny mix of choice, allocation, risk and social influence.

One of the great insights of behavioural science is simply that people do not always act in strictly ‘rational’ ways. For all the knowledge, expertise and experience that we may amass, our decisions can still be influenced by trivial factors – the time of day, what our friends or colleagues are doing, or the last piece of information we heard. Sometimes we make consistent, predictable errors in our estimations or judgements. When faced with a difficult question, we may subconsciously answer an easier one. People are not machines and all this is human nature. But, having recognised this, we are in a better position to seek to counterbalance some of our most dangerous behavioural biases.

For anyone even vaguely familiar with commercial real estate, the underlying assertion that financial markets are not always as straight forward or efficient as the economics textbooks make out will come as absolutely no surprise. Economists have struggled to shoehorn the sector into traditional theoretical models. The surprise, perhaps, is that commercial real estate markets have received such little attention from behavioural scientists, or behavioural economists more specifically.

In fact, commercial real estate has many characteristics that make it a profoundly interesting case study for unwanted biases. Unlike many other financial markets, each asset is unique. Pricing is opaque and transaction costs are high. There is a prevalence of industry-accepted but unproven rules of thumb, or heuristics. And, of course, there is the undeniable emotional and aesthetic appeal of tangible assets – feelings that, one imagines, investors in sovereign debt or grain futures can rarely appreciate.

Where behavioural economists have studied commercial real estate markets, their focus has, perhaps understandably, been concerned with aspects of investment. This mirrors the much larger body of research in other financial markets. However, as behavioural economics is essentially about understanding how people make decisions under uncertainty, there is no reason for the concepts not to apply equally to the construction, leasing or occupation of buildings.

Psychologists have identified literally hundreds of different types of behavioural biases, and it turns out that many of them are directly relevant to commercial real estate. However, given the prevailing economic situation, a few appear especially prominent:

  • Herding – the tendency for market participants to do the same thing at the same time. It’s not necessarily that following the crowd is a poor strategy, nor that contrarianism for the sake of it is better. However, at best, following the herd might, for example, lower returns for investors through increased competition, or raise costs for real estate occupiers. At worst, it is notoriously difficult to time market peaks. From tulips to railways, and yes, real estate too, history is littered with examples of markets that rise and rise on the back of investor excitement, until they implode with dire consequences.
  • Framing – how terms such as ‘prime’ can obscure assets’ true characteristics. Real estate is a complex asset class in which every asset is unique. Mental shortcuts in the form of labels, such as prime or secondary, or geographic and sector distinctions, such as South East offices, are often helpful in conversation when we want to avoid unnecessary levels of complexity. However, there are clearly times when it is vital to understand assets at an individual level. The danger arises when decision makers are not able to switch modes and continue to analyse the ‘frame’ or the label, rather than the asset or the situation itself.
  • Anchoring – how people become fixated on maximising the ‘wrong’ metrics. In real estate investment, there is typically a larger focus on yield, or price movement, than on income. This is despite the fact that income tends to account for a larger share of return over most time horizons. In occupational markets, corporates might overemphasise the significance of headline real estate costs when choosing a new office location, while failing to apply enough weight to less tangible metrics such as the potential employee wellbeing or attractiveness to talent.
  • Loss aversion – the idea that for most people losing a given amount is a greater hit than the upside of gaining the same amount. This is one of the most famous areas of behavioural science, because it clearly shows how ‘real’ people differ from strictly ‘rational’ people. In practice, it explains why people tend to hold on to underperforming assets for longer than they should, because facing up to a loss is painful.
  • Overconfidence – how people overestimate upside and care too little about risk. Conviction is required for anyone taking decisions with sizeable implications, as is often the case in real estate. However, that conviction should follow a strict analysis of the facts, rather than come ahead of it.

Nobody is suggesting that awareness of these biases alone confers special decision making powers. In fact, many will claim that they are already aware of behavioural biases anyway and act in ways to mitigate them – it’s not for nothing that funds have developed ruthless investment committees, for example. On the other hand, real estate is often characterised as a ‘people business’. How strange would it appear to a casual observer if, at times of uncertainty like these, we failed to adequately consider the idiosyncrasies of people, one of the biggest variables in our industry.

At least three corollaries arise:

  1. It is hard to envisage a downside for anyone in real estate from becoming more familiar with common behavioural biases.
  2. This is undoubtedly a rich area of future study for those so inclined, with real estate-specific contributions so far high in quality but low in number.
  3. Most importantly, knowledge of biases should support a growing and widely shared body of mitigating strategies, whether acquired through detailed research or battle-hardened experience.