Supervisory Governance, Capture and Non‑Performing Loans

Abstract

Scholars have long believed the governance of banking supervision to affect financial stability. Although the literature has identified at length the pros and cons of having either a central bank or a separate agency responsible for microprudential banking supervision, the advantages of having this task shared by both institutions (shared supervision) have received considerably less attention. This paper fills this void by comparing the impact of three supervisory governance models-supervision by the central bank, by an agency or by both of them-on bank non-performing loans. Using a new database on supervisory governance in 116 countries from 1970 to 2016, it finds that supervisory governance per se does not significantly affect non-performing loans. However, it also finds that, where the risk of capture is high, shared supervision is associated with a significant reduction in non-performing loans. This is in line with the supervisory capture theory, whereby it is more costly to capture two supervisors rather than one. Overall, these results provide new evidence in support of the relevance of supervisory governance in hampering supervisory capture from the banking sector.

Global Post-Crisis Banking Supervision: Supervisory Powers and Institutional Changes in the Banking Sector

“…The third and fourth dependent variables are the averaged scale indexes of the overall limitations of banks' activities and capital regulatory stringency determined by extending the data from J. R. Barth, Caprio, and Levine (2013a) based on (Sohn and Vyshnevskyi, 2020). The second is a binary indicator of changes in a central bank's involvement in bank supervision (where one indicates that a central bank is either uninvolved or shares involvement, or that a central bank was turned into a monopoly after GFC) based on Fraccaroli (2019). These variables allow us to determine whether institutional changes in supervision are significantly connected to changes in banking supervision powers.…”

“…Furthermore, it was noted that in the absence of a shock, a country may still reform its banking supervision architecture by following peer countries that implemented reforms after they experienced crises (i.e., peer effect) (Masciandaro & Romelli, 2018). Fraccaroli (2019) stated that sharing bank supervision between a central bank and a special supervisory body may have a greater impact on financial stability than other supervisory governance models such as a single central bank or supervisory body. However, in economic theory, whether allocating supervisory duties to central banks or other independent bodies is socially optimal remains undetermined (Peia & Romelli, 2019).…”

“…In addition, we utilize banking sector and macroeconomic data from the World Bank's Global Financial Development Database (November 2021 version) (World Bank, 2019b), data on central banks' involvement in bank supervision (Fraccaroli, 2019) and the IMF Financial Development Index database (Sahay et al, 2015;Svirydzenka, 2016). In addition, we used information on the classification of supervisory frameworks obtained from Sohn and Vyshnevskyi (2020).…”

“…The study of bank supervision and its main features was intensified after GFC, though the main focus was on bank regulation. A vast number of studies examined bank supervision empirically, at both single and multiple country levels, and identified key debates around banking supervision from various perspectives (Doumpos et al, 2015;Fraccaroli, 2019;Hirtle, 2020).…”

“…To analyze these factors, we utilized the five-round survey of the World Bank's Bank Regulation and Supervision Survey (World Bank, 2019a), the database on bank regulation and supervision by Barth, Caprio, and Levine (Barth et al, 2013b) including our extension to it, and the November 2021 version of the World Bank's Global Financial Development Database (World Bank, 2019b). We also used central banks' involvement in bank supervision data (Fraccaroli, 2019) and the International Monetary Fund (IMF) Financial Development Index database (Sahay et al, 2015;Svirydzenka, 2016). In addition, we applied our data from the classification of supervisory frameworks (Sohn & Vyshnevskyi, 2020).…”