Understanding the Delayed Impact of M2 Money Supply on Apartment Prices

Understanding the Delayed Impact of M2 Money Supply on Apartment Prices



Key Highlights

  • A nuanced positive correlation is observed between M2 Money Supply and the Apartment Price Index, with the most significant impact seen at a 5-quarter lag.
  • The analysis suggests that fluctuations in the M2 Money Supply have a delayed but increasingly influential effect on apartment prices.
  • These insights offer valuable foresight for real estate investors and policymakers, highlighting the predictive value of monetary trends.


Ponte Vedra, FL - This article will be a slight departure from the norm. We typically look for interesting correlations between economic variables that impact multifamily real estate. That’s how we started this week’s research - by looking for a correlation between M2 money supply and the Apartment Price Index. Put simply, the theory was that an increased money supply should boost economic activity, leading to higher real estate prices. However, our analysis paints a different picture. While there is a correlation, it is not as immediately strong or straightforward as one might anticipate. The most significant connection, albeit milder than expected, emerges with a five-quarter lag (only .25). This interesting finding challenges conventional wisdom and invites a deeper exploration into the nuanced effects of monetary policy on the real estate sector. Below you can see a time series chart of the 2 variables. The green line traces the M2 Money Supply's annual changes, while the blue line tracks the Apartment Price Index. The alignment, particularly evident with the considered time lag, underscores the somewhat delayed impact of monetary policy on real estate prices.

Methodology

Our analysis pulled data from the Federal Reserve Bank of St. Louis for a time-series approach. By examining the year-over-year changes in M2 Money Supply against the Apartment Price Index over an extended period, we sought to uncover latent patterns. Special emphasis was placed on exploring various lag periods, to discern how shifts in money supply can eventually echo in the real estate sector. This is also known as looking for leading indicators, or indicators that can help predict how a different data point will be affected in the future.?

M2 Money Supply & Apartment Price Index

Initially, the correlation between these indices appeared mild (less than 0.2). Since we expected money supply to have a delayed effect, we introduced time-lags. The strongest correlation was a 5-quarter lag, but even this was only 0.27. This suggests that changes in the M2 Money Supply can be seen as fairly unreliable early indicators of subsequent movements in apartment prices. If you recall from our previous research, we typically only like to write about correlations when the correlation is stronger than 0.5 (the correlation scale is -1 to +1). The closer to 1 (or negative 1), the stronger the correlation (or negative correlation).

The next chart showcases the correlation coefficients across various lags, with the peak correlation at a 5-quarter lag. This peak exemplifies the strongest delayed influence of the money supply on apartment prices.



Conclusion

This trend suggests a lagged transmission mechanism where monetary expansions or contractions influence real estate markets after a certain period. The rationale likely lies in the time it takes for monetary policy changes to percolate through the economy, affecting lending rates, investment appetites, and ultimately, real estate demand and pricing. The more surprising finding to us was that the delayed impact was relatively small. The main takeaway for multifamily investors may be that apartment prices are relatively stable and do not rely heavily on the total amount of money in circulation. This is a positive finding if you’re not in the business of guessing what the Federal Reserve or Treasury will do next. In future research, we’ll dive into the Velocity of the money supply, or how quickly the money is circulated throughout the economy, to see if we find a stronger correlation.?


by Brian Underdahl, Chief Analytics Officer & Jackson Burks, Economic Analyst Intern

Nuvo Capital Partners

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