Data and Code for: Cultural Affinity, Regulation and Market Structure: Evidence from the Canadian Retail Banking Industry
Principal Investigator(s): View help for Principal Investigator(s) Hector Perez Saiz, International Monetary Fund; Hongyu Xiao, Bank of Canada
Version: View help for Version V1
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Project Description
Summary:
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We estimate a perfect information static entry game to study the effect of cultural entry
barriers on entry and competition in the retail banking industry. Canada provides a favorable setting for analysis due to its high linguistic diversity, concentrated market, and regulatory entry barriers. We find that cultural affinity between customers and financial institutions that share a common cultural origin plays an important role in explaining the comparative advantages of these institutions in certain markets. Using several counterfactual experiments and additional empirical evidence, we show that the effectiveness of regulations intended to foster competition are significantly limited by cultural barriers, which is a key determinant that shapes the competitive landscape of the industry.
Scope of Project
Subject Terms:
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Commercial banks
JEL Classification:
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G21 Banks; Depository Institutions; Micro Finance Institutions; Mortgages
G28 Financial Institutions and Services: Government Policy and Regulation
L13 Oligopoly and Other Imperfect Markets
L51 Economics of Regulation
G21 Banks; Depository Institutions; Micro Finance Institutions; Mortgages
G28 Financial Institutions and Services: Government Policy and Regulation
L13 Oligopoly and Other Imperfect Markets
L51 Economics of Regulation
Geographic Coverage:
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Canada
Universe:
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1. Census subdivisions in Canada
2. Main financial institutions in Canada
3. Employees of main financial institutions in Canada, by category
2. Main financial institutions in Canada
3. Employees of main financial institutions in Canada, by category
Data Type(s):
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census/enumeration data;
geographic information system (GIS) data;
survey data
Collection Notes:
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Part of the data has been manually collected by the authors.
Methodology
Response Rate:
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For census subdivisions data, Statistics Canada collects information for the entire universe of census subdivisions in Canada. The authors only use small and rural census subdivisions.
For job offers data, the authors manually compile and identify language requirements from all job postings for customer-facing employees of all Canadian financial institutions on
For job offers data, the authors manually compile and identify language requirements from all job postings for customer-facing employees of all Canadian financial institutions on
a major Canadian job search website (ca.indeed.com).
Table 1 uses a sample of 12,000 households per year, compiled by Ipsos Reid for the Canadian Financial Monitor data base (CFM).
Table 1 uses a sample of 12,000 households per year, compiled by Ipsos Reid for the Canadian Financial Monitor data base (CFM).
Sampling:
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For census subdivisions data, the authors select subdivisions that have between 200 and 250,000 inhabitants, that are separated by at least 10 km, and eliminate those located less than 30 km away from any major urban center.
Data Source:
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1. Census , geographic information, and other information from Statistics Canada
2. Financial Services Canada
3. Office of the Superintendent of Financial Institutions
4. Canadian Financial Monitor (Ipsos Reid)
5. Job postings from Indeed.com
6. BoardEx data base from WRDS
7. Online service NamePrism
8. Bank directory Canada (1972 edition)
2. Financial Services Canada
3. Office of the Superintendent of Financial Institutions
4. Canadian Financial Monitor (Ipsos Reid)
5. Job postings from Indeed.com
6. BoardEx data base from WRDS
7. Online service NamePrism
8. Bank directory Canada (1972 edition)
Collection Mode(s):
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mail questionnaire;
other;
record abstracts
Unit(s) of Observation:
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Individuals (job listings),
Census subdivisions,
Households
Geographic Unit:
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Individuals (job listings)
Related Publications
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