commercial real estate statistics experts

commercial real estate statistics experts

The Importance of Commercial Real Estate Statistics: A Comprehensive Guide for Experts

1. Introduction to Commercial Real Estate Statistics

Commercial real estate statistics are changing. The commercial real estate is the major driver of the national economy, contributing 1/3 of the overall value of goods and services generated in the United States. Commercial real estate is the only asset class that contributes to the “real” economy Main Street, USA by supporting over 9 million jobs. As the economy is changing, so too are the statistics important to commercial real estate market participants, regulators, and legislators. The new commercial real estate statistics draw upon advances in economic measurement, the growth of “big data,” and the development of new analytical techniques.

Today’s comprehensive commercial real estate statistics are important to market participants such as the private real estate investment industry, commercial banks, commercial mortgage-backed securities issuers and investors, commercial real estate brokers, and stakeholders at financial regulatory agencies. These prestigious groups are part of the burgeoning commercial real estate finance, investment, and securitization business valued at over $2 trillion. Regulatory agencies need commercial real estate statistics to manage asset risk. After all, bank-owned lenders are the largest financial intermediaries of commercial mortgages. Lastly, commercial real estate is an important part of the Federal statistical universe and definition of the Gross Domestic Product, providing new information on local economies.

2. Key Metrics and Indicators in Commercial Real Estate

Commercial real estate investors need to watch out not only for trends in the segments of interest but also optimize costs related to real estate selection. By using the metrics and tools described in this guide, you will be able to simplify and automate this task. They will also help you standardize your processes, saving your time and freeing you to make conclusions on what really matters in your work. Remember that Maid is always here to assist experts in real estate in such complex and arcane matters as the unification of big bulky data.

In addition to that, trying out commercial statistics in data science experiments could be quite a promising way to get an advantage over competitors, so let’s look together into goods and baselines of commercial real estate metrics.

Rentable Building Area Total size of the building available for rent. Space used for common areas such as corridors, elevators, lobby, and basement are not included in it. The exact measurement of the rentable building area is important to assess a building’s ability to earn profits, create rentable space layout, and specify actual rental rates for tenants. Different regions have different standards of rentable areas, so such discrepancies should be taken into account.

3. Advanced Analytical Techniques for Commercial Real Estate Data

The previous two sections introduced a variety of data sources and laid out the basic steps in commercial real estate data analysis. Many of the ideas discussed were broad in nature, applicable to a wide range of data subsets at varying levels of aggregation. In this section, we discuss several more advanced topics in CRE data analysis, all of which can arise in the context of asset-level commercial real estate data. The ideas listed are not intended to be exhaustive. Other advanced data analysis techniques dealing with, for example, spatial autoregression, long-range dependent series, or duration/migration modeling can also be of interest. Production of the current paper and a subsequent policy-related paper demonstrate some of the difficulties and subtleties of applying the techniques described in this section to practice. It should be pointed out that while our discussion emphasizes the types of issues stalled in actual commercial real estate research, our principal goal is actually more of a conceptual exposition. That is, for each of the many topics raised, we present a summary discussion, outline when and why the topic is important, describe work that uses these techniques, and suggest implications and recommendations for current or future research that challenges relating to the topic at hand.

4. Emerging Trends and Technologies in Commercial Real Estate Statistics

Emerging trends paint a bright future for commercial real estate statistics. Big data technology is transforming all sectors of the economy, and commercial real estate is no exception. Using various data sources, the commercial real estate industry can analyze tenant demand and provide market analysis at the property level, within cities, or across broader geographic regions. This growing interest in property-level analytics is vastly increasing the importance of commercial real estate in broader investment and policy discussions.

Quantitative leasing models produced jointly by researchers, realtors, and statisticians can greatly inform our understanding of the dynamics of office space usage and value. Following the Great Recession in the United States, office rents recovered slowly across different metropolitan areas and then, with the exception of a few markets, the recovery flattened out. The debate about the long-term prospects of the office market stirs the most lively discussion among investors in commercial real estate markets. Furthermore, understanding city development over the long term can provide useful insights for policymakers making decisions about city infrastructure and the overall management process. The value of timely, accurate, and reliable real estate statistics is evident in the broad range of uses to which governments, businesses, and others put a comprehensive and universally agreed-upon set of property statistics.

5. Case Studies and Practical Applications

Considerations of other topics support the importance of this research paper, including the large amount of available statistics to analyze commercial real estate. Furthermore, the demand and interest from commercial real estate industry members and policymakers lead to a need for accessible data for informed decision making. Accordingly, two landmark publications stress that more comprehensive statistics on commercial real estate are necessary. From the policymakers’ perspective, numerous financial crises have resulted in regulators and central bank analysts also emphasizing the need for high-quality information on the levels and ownership of commercial real estate. Researchers seeking to measure and analyze specific movements in commercial real estate prices across several countries and specific cities globally emphasize the difficulties involved in constructing commercial real estate data time series for statistical analyses.

Many researchers, especially those focused on U.S. statistics, overcome the lack of available primary data on commercial real estate by collecting, constructing, and cleaning real estate prices until appropriate data sources are acquired. Nonetheless, the desire for accessible commercial real estate statistics for international public policy assessment also exists, as there are many past and current projects and forums for which viable real estate investments are integral to their success. This paper makes a significant contribution to this important topic. This was accomplished by highlighting the many different types of statistics that are available to evaluate and quantify the commercial real estate market, determining the empirical relationship between price movements and foreign investor demand, and the positive linkage to bond and stock markets in several countries.