FinTech online lending to consumers has grown rapidly in the post-crisis era. As argued by its advocates, one key advantage of FinTech lending is that lenders can predict loan outcomes more accurately by employing complex analytical tools, such as machine learning (ML) methods. This study...

FinTech online lending to consumers has grown rapidly in the post-crisis era. As argued by its advocates, one key advantage of FinTech lending is that lenders can predict loan outcomes more accurately by employing complex analytical tools, such as machine learning (ML) methods. This study...

Banks are compensated primarily through the net interest margin (NIM), which is the difference between the interest earned on their investments and the interest paid to their depositors and other creditors. In the low interest rate environment that has persisted since the Great Recession, banks...

The anemic pace of the recovery of the U.S. economy from the Great Recession has frequently been blamed on heightened uncertainty, much of which concerns the nation's fiscal policy. Intuition suggests that increased policy uncertainty likely has different impacts on industries with different...

Labor productivity (LP) in the United States has gone from being procyclical to acyclical since the mid-1980s. Using industry-level data, this paper first shows that total factor productivity (TFP), which is LP net of capital deepening, has also become much less correlated with output as well as...

The Main Street Lending Program (MSLP) was established by the Federal Reserve to supply credit to small and, especially, midsize businesses so they could weather COVID-19-induced disruptions. This study uses Dun & Bradstreet (D&B) data on the financial condition and overall viability of firms to...

This policy brief examines the impact of student loan debt on individuals' homeownership status and wealth accumulation, employing a rich set of financial and demographic variables that are not available in many of the existing studies that use credit bureau data. It is important to understand...

Rather than charging direct fees, banks often charge implicitly for their services via interest spreads. As a result, much of bank output has to be estimated indirectly. In contrast to current statistical practice, dynamic optimizing models of banks argue that compensation for bearing systematic...

The measurement of bank output, a difficult and contentious issue, has become even more important in the aftermath of the devastating financial crisis of recent years. In this paper, we argue that models of banks as processors of information and transactions imply a quantity measure of bank...

Financial institutions often do not charge explicit fees for the services they provide, but are instead compensated by the spread between interest rates on loans and deposits. The lack of explicit fees in lending makes it difficult to measure the output of banks and other financial institutions....