Data Description | RDP 2023-05: The Impact of Interest Rates on Bank Profitability: A Retrospective Assessment Using New Cross-country Bank-level Data

RDP 2023-05: The Impact of Interest Rates on Bank Profitability: A Retrospective Assessment Using New Cross-country Bank-level Data 5. Data Description

Callan Windsor, Terhi Jokipii and Matthieu Bussiere

June 2023

Download the Paper 1.3MB

The current project is conducted under the auspices of the IBRN, a network of central bank researchers who focus on global banking. To examine the impact of interest rates on banks' profitability, we rely on confidential bank-level data. Each country's data are only available to subject matter experts from that country's central bank and we rely on the expert judgement of each contributor to construct the most appropriate sample for their jurisdiction.

Details of the sample for each country are provided in Table 1. Around 1,500 banks across the 10 jurisdictions are examined, with a bank broadly defined as an institution whose business is to receive deposits and/or close substitutes and grant credits or invest in securities on their own account. Most jurisdictions use data at a quarterly frequency, although some use semiannual and annual data. Seven countries use unconsolidated banking data, with the decision to rely on consolidated versus unconsolidated data left to subject matter experts from each central bank. While most data series start in the early 2000s or earlier, for Sweden they start only in 2010.

Table 1: Key Statistics for the Country Samples
	AUS^(a)	CAN	CHL	CZE	FRA	DEU	NOR	POL	SWE	CHE
Start date	2003	1994	2004	2002	2000	2000	2000	2000	2010	2000
Frequency	QoQ	QoQ	QoQ	QoQ	HoH	YoY	YoY	QoQ	YoY	YoY
No of banks	181	76	13	21	562	203	221	23	56	104
No of time periods	68	104	62	72	40	20	20	80	10	20
Consolidation	C	C	UC	UC	UC	UC	UC	UC	C	C
Low-rate threshold	2.0	1.2	2.8	0.5	1.2	1.2	1.6	1.9	0.9	0.2
Negative rates	No	No	No	No	Yes	Yes	No	No	Yes	Yes
Windsorisation (%)	1	1	1	1	10	1	0.5	1	5	1
Notes: International Monetary Fund country abbreviations: AUS: Australia; CAN: Canada; CHL: Chile; CZE: Czech Republic; FRA: France; DEU: Germany; NOR: Norway; POL: Poland; SWE: Sweden; CHE: Switzerland. (a) Sample includes banks, credit unions and building societies, foreign branches and foreign subsidiaries. Source: Contributing central banks

Table 2 provides a full list of variables used in our analysis. Unlike previous studies, our definition of a ‘low-rate environment’ is country-specific, defined as the 25th percentile of each country's historical rate distribution. In choosing the most appropriate time period over which to define ‘low’ rates we again rely on our participating subject matter experts, with the sample period not necessarily the same as that shown in Table 1. The low-rate threshold for each central bank is plotted in Figure 1.

Table 2: Definitions
Term	Definition
Panel A: Dependent variables
Return on assets (ROA)	The ratio of net income expressed as a percentage of average total assets (ATA).
Net interest margin (NIM)	The ratio of net interest income (NII) expressed as a percentage of average interest earning assets (AEA). NII includes gross interest and dividend income minus total interest expense. AEA is the sum of total loans, total securities, investments in property and earning assets not otherwise categorised, including non-current assets held for sale which are not loans.
Non-interest income (Non-II)	The ratio of Non-II expressed as a percentage of ATA. Non-II is the value of operating income from continuing operations for the reporting period, excluding the value of interest income and interest expense.
Loan-loss provisions (LLP)^(a)	The ratio of LLPs (or impairment expenses) to cover non-performing loans expressed as a percentage of ATA. This is a flow item from the income statement.
Panel B: Variables of interest
Short-term interest rate	Three-month interbank rate.
Spread	Difference between the 10-year sovereign bond yield and the 3-month interest rate.
Low-rate dummy variable	Equal to 1 when the 3-month interbank rate is in the first quartile of the country-specific historical rate distribution.
Lower-for-longer variable	The number of consecutive years that a country's 3-month interest rate is in the ‘low’ period.
Large bank dummy^(b)	Equal to 1 if the bank is in the group of global banks that made the main G-SIB assessment sample.
Panel C: Baseline bank controls
Deposits over liabilities	The ratio of deposits and short-term funding (STF) expressed as a percentage of total liabilities. Deposits and STF include total customer deposits, deposits from banks, money market instruments, certificates of deposit and other deposits.
Liquid assets over total assets	The ratio of cash, liquid assets and securities expressed as a percentage of ATA. Securities include reverse repos and cash collateral, trading securities, all in-the-money trading derivatives and derivatives recognised for hedging (less the value of netting arrangements), available for sale securities, held to maturity securities, at-equity investments, and other securities.
Equity ratio	The ratio of total equity expressed as a percentage of ATA. Total equity includes common equity, non-controlling interest, securities revaluation reserves, foreign exchange revaluation reserves, and other revaluation reserves.
Panel D: Baseline macro controls
Real GDP growth	Year-on-year growth in real GDP.
CPI growth	Year-on-year inflation.
Housing price growth	Year-on-year growth in housing prices (apartments and houses).
Notes: (a) Canada uses the stock of provisions. (b) For Poland the large bank dummy variable is equal to 1 for Polish subsidiaries of G-SIB banks. For Sweden a bank is classified as a large bank if it is included in main assessment sample at least once during the time period 2014–18. For Germany and the Czech Republic the dummy is equal to 1 for all domestic systemically important banks. Source: Contributing central banks

Trends in profitability for the mean and median banking systems in the sample are plotted in Figure 2. Despite the broad-based decline in short-term interest rates over the sample, on average across the countries examined in this paper, banks' ROAs were largely unchanged over the sample, although volatile around the financial crisis in 2008. By contrast, the median NIM has been declining over the past decade, consistent with the decline in policy rates. For both the NIM and ROA the median is more volatile than the mean, suggesting there is substantial heterogeneity in country experiences.

Figure 2: Trends in Bank Profitability

Average of contributing central banks

For a cursory and preliminary look at the association between changes in interest rates and profitability, Figures 3 and 4 plot the period-to-period change in NIMs and ROAs against the change in interest rates for the mean bank in all countries. There appears to be a positive association between changes in interest rates and banks' NIMs; however, there is no equivalent relationship for banks' ROAs. This preliminary evidence, along with the trends presented in Figure 2, is consistent with the idea that banks' may have shielded the impact of lower rates on overall profitability by increasing fee-based business and reducing costs. This notwithstanding, these bivariate associations fail to control for a host of relevant factors, including country and bank fixed effects as well as other relevant balance sheet controls, motivating our much more careful assessment of these relationships in the next section.