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Houston researcher tries to crack the code on the Fed's data to determine economic outlook

There's no crystal ball, but this researcher from Rice University is trying to see if some metrics work for economic forecasting. Photo via Getty Images

Research by Rice Business Professor K. Ramesh shows that the Fed appears to harvest qualitative information from the accounting disclosures that all public companies must file with the Securities and Exchange Commission.

These SEC filings are typically used by creditors, investors and others to make firm-level investing and financing decisions; and while they include business leaders’ sense of economic trends, they are never intended to guide macro-level policy decisions. But in a recent paper (“Externalities of Accounting Disclosures: Evidence from the Federal Reserve”), Ramesh and his colleagues provide persuasive evidence that the Fed nonetheless uses the qualitative information in SEC filings to help forecast the growth of macroeconomic variables like GDP and unemployment.

According to Ramesh, the study was made possible thanks to a decision the SEC made several years ago. The commission stores the reports submitted by public companies in an online database called EDGAR and records the IP address of any party that accesses them. More than a decade ago, the SEC began making partially anonymized forms of those IP addresses available to the public. But researchers eventually figured out how to deanonymize the addresses, which is precisely what Ramesh and his colleagues did in this study.

"We were able to reverse engineer and identify those IP addresses that belonged to Federal Reserve staff," Ramesh says.

The team ultimately assembled a data set containing more than 169,000 filings accessed by Fed staff between 2005 and 2015. They quickly realized that the Fed was interested only in filings submitted by a select group of industry leaders and financial institutions.

But if Ramesh and his colleagues now had a better idea of precisely which bellwether firms the Fed focused on, they still had no way of knowing exactly what Fed staffers had gleaned from the material they accessed. So the team decided to employ a measure called "tone" that captures the overall sentiment of a piece of text – whether positive, negative, or neutral.

Building on previous research that had identified a set of words with negatively toned financial reports, Ramesh and his colleagues examined the tone of all the SEC filings accessed by Fed staff between one meeting of the Federal Open Markets Committee (FOMC) and the next. The FOMC sets interest rates and guides monetary policy, and its meetings provide an opportunity for Fed officials to discuss growth forecasts and announce policy decisions.

The researchers then examined the Fed's growth forecasts to see if there was a relationship between the tone of the documents that Fed staff examined in the period between FOMC meetings and the forecasts they produced in advance of those meetings.

The team found close correlations between the tone of the reports accessed by the Fed and the agency’s forecasts of GDP, unemployment, housing starts and industrial production. The more negative the filings accessed prior to an FOMC meeting, for example, the gloomier the GDP forecast; the more positive the filings, the brighter the unemployment forecast.

Ramesh and his colleagues also compared the Fed's forecasts with those of the Society of Professional Forecasters (SPF), whose members span academia and industry. Intriguingly, the researchers found that while the errors in the SPF's forecasts could be attributed to the absence of the tonal information culled from the SEC filings, the errors in the Fed’s forecasts could not. This suggests both that the Fed was collecting qualitative information that the SPF was not—and that the agency was making remarkably efficient use of it.

"They weren’t leaving anything on the table," Ramesh says.

Having solved one mystery, Ramesh would like to focus on another; namely, how does the Fed identify bellwether firms in the first place?

Unfortunately, the SEC no longer makes IP address data publicly available, which means that Ramesh and his colleagues can no longer study which companies the Fed is most interested in. Nonetheless, Ramesh hopes to use the data they have already collected to build a model that can accurately predict which firms the Fed is most likely to follow. That would allow the team to continue studying the same companies that the Fed does, and, he says, “maybe come up with a way to track those firms in order to understand how the economy is going to move.”


This article originally ran on Rice Business Wisdom and was based on research from K. Ramesh is Herbert S. Autrey Professor of Accounting at Jones Graduate School of Business at Rice University.

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A research team housed out of the newly launched Rice Biotech Launch Pad received funding to scale tech that could slash cancer deaths in half. Photo via Rice University

A research funding agency has deployed capital into a team at Rice University that's working to develop a technology that could cut cancer-related deaths in half.

Rice researchers received $45 million from the National Institutes of Health's Advanced Research Projects Agency for Health, or ARPA-H, to scale up development of a sense-and-respond implant technology. Rice bioengineer Omid Veiseh leads the team developing the technology as principal investigator.

“Instead of tethering patients to hospital beds, IV bags and external monitors, we’ll use a minimally invasive procedure to implant a small device that continuously monitors their cancer and adjusts their immunotherapy dose in real time,” he says in a news release. “This kind of ‘closed-loop therapy’ has been used for managing diabetes, where you have a glucose monitor that continuously talks to an insulin pump. But for cancer immunotherapy, it’s revolutionary.”

Joining Veiseh on the 19-person research project named THOR, which stands for “targeted hybrid oncotherapeutic regulation,” is Amir Jazaeri, co-PI and professor of gynecologic oncology at the University of Texas MD Anderson Cancer Center. The device they are developing is called HAMMR, or hybrid advanced molecular manufacturing regulator.

“Cancer cells are continually evolving and adapting to therapy. However, currently available diagnostic tools, including radiologic tests, blood assays and biopsies, provide very infrequent and limited snapshots of this dynamic process," Jazaeri adds. "As a result, today’s therapies treat cancer as if it were a static disease. We believe THOR could transform the status quo by providing real-time data from the tumor environment that can in turn guide more effective and tumor-informed novel therapies.”

With a national team of engineers, physicians, and experts across synthetic biology, materials science, immunology, oncology, and more, the team will receive its funding through the Rice Biotech Launch Pad, a newly launched initiative led by Veiseh that exists to help life-saving medical innovation scale quickly.

"Rice is proud to be the recipient of the second major funding award from the ARPA-H, a new funding agency established last year to support research that catalyzes health breakthroughs," Rice President Reginald DesRoches says. "The research Rice bioengineer Omid Veiseh is doing in leading this team is truly groundbreaking and could potentially save hundreds of thousands of lives each year. This is the type of research that makes a significant impact on the world.”

The initial focus of the technology will be on ovarian cancer, and this funding agreement includes a first-phase clinical trial of HAMMR for the treatment of recurrent ovarian cancer that's expected to take place in the fourth year of THOR’s multi-year project.

“The technology is broadly applicable for peritoneal cancers that affect the pancreas, liver, lungs and other organs,” Veiseh says. “The first clinical trial will focus on refractory recurrent ovarian cancer, and the benefit of that is that we have an ongoing trial for ovarian cancer with our encapsulated cytokine ‘drug factory’ technology. We'll be able to build on that experience. We have already demonstrated a unique model to go from concept to clinical trial within five years, and HAMMR is the next iteration of that approach.”

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