Spatial financeWhere capital meets hazard, exposure and transition
Financial economics of regulation
Financial economics explains why regulation is needed and what it costs: how leverage, maturity transformation and interconnection create externalities that firms do not price, and how capital, liquidity and macroprudential rules change lending, pricing and risk-taking across the cycle.
What financial economics and macro-finance does here.
Financial economics and macro-finance study how asset prices, credit and financial institutions interact with the real economy. They explain how shocks are amplified or absorbed through balance sheets and markets. In financial stability, governance and institutions and capital markets and investment, financial economics traces how physical, health or cyber shocks transmit to credit, sovereign debt and markets. It informs macroprudential policy and the pricing of risk. The canonical description is on the STEM Commons.
Costs and benefits of capital requirements
Higher capital lowers the probability and cost of crises but may raise funding costs. Studies combine crisis histories, bank funding data and macroeconomic models to inform calibration, with every assumption stated.
Tracing leakage of macroprudential measures
Loan-level and cross-border data show whether lending moves to non-banks or foreign branches after a measure, which tells authorities whether reciprocity or wider coverage is needed.
Measuring systemic importance
Indicators of size, interconnection, substitutability, complexity and cross-border activity are combined to identify systemically important firms, and market-based measures are used as a cross-check.
03Monitor
Econometric model.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Econometric model
Financial regulation · Financial economics of regulation · Run R-4216
Estimates stableGRA · Financial Regulation Nexus
Estimates
robust standard errors
Firms under enhanced supervision
0.71
0.19
[−0.5, 0.9]
Yes
Supervisory findings open
0.29
0.13
[0.1, 0.9]
Yes
Consultations open
0.44
0.11
[−0.2, 0.9]
No
Climate expectations met
0.35
0.17
[−0.4, 0.3]
No
Method card
Method
Financial economics and macro-finance
Sample
8889 obs
Design
panel, fixed effects
Label
MODELLED
Residuals by group
Econometric model: the screen's structure, terms and states for Financial regulation.Example names and illustrative values; a design, not a record or a live system.
04Data
What the method consumes.
Datasets and records used by financial economics and macro-finance on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
How three families of instruments change a risk outcome over time with adoption lags, coverage and compliance, the policy scenarios behind transition and physical risk assessments. Scenario: named assumptions about the future, not a forecast.
Controls
Baseline trend of the outcome
2.0% a year
Coverage of the instrument
70%
Compliance
75%
Effect size, against the teaching value
100%
Years ahead
20 years
Readouts
Largest reduction at the horizon
Regulation
Its reduction against the baseline
21%
Numbers, methods and sources
Year
Baseline
Regulation
Economic incentive
Information and capacity
0
100.0
99.5
98.8
99.1
1
102.0
101.2
100.1
99.8
2
104.0
102.5
101.1
99.9
3
106.1
103.5
101.6
100.0
4
108.2
103.7
101.8
100.7
5
110.4
103.2
101.7
102.1
6
112.6
102.0
101.6
103.9
7
114.9
100.4
101.6
105.9
8
117.2
99.2
102.1
108.0
9
119.5
98.6
102.9
110.1
10
121.9
98.9
104.2
112.3
11
124.3
99.7
105.7
114.5
12
126.8
101.1
107.4
116.8
13
129.4
102.7
109.4
119.2
14
131.9
104.5
111.4
121.6
15
134.6
106.5
113.5
124.0
16
137.3
108.5
115.7
126.5
17
140.0
110.7
118.0
129.0
18
142.8
112.9
120.4
131.6
19
145.7
115.1
122.8
134.2
20
148.6
117.4
125.2
136.9
Methods
Tools of government Hood (1983), The Tools of Government, Macmillan
Carrots, sticks and sermons Bemelmans-Videc, Rist and Vedung (1998), Transaction
Diffusion of innovations Rogers (2003), Diffusion of Innovations, Free Press
Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page's map can draw:
Borders Natural Earth
Cities Natural Earth
Policy paths and what they do to the risk. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: Tools of government (Hood (1983), The Tools of Government, Macmillan); Carrots, sticks and sermons (Bemelmans-Videc, Rist and Vedung (1998), Transaction); Diffusion of innovations (Rogers (2003), Diffusion of Innovations, Free Press).
Models are back-tested against historical market episodes and crises. Results are compared with supervisory data and alternative specifications.
Check
How it is done
Out-of-sample episodes
Models are tested on crises not used in estimation, and results reported for those episodes
Identification
Each causal claim names how the effect of the rule is separated from other changes at the same time
Specification sensitivity
Results are shown across alternative models, samples and definitions
Supervisory reconciliation
Estimates from public data are compared with published supervisory aggregates
Relationships estimated in calm periods may break down in stress. Hidden leverage and interconnections are often unobserved.
07Exposure, loss and capital
What financial economics of regulation means for exposure, loss and capital.
The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.
Disclosure crosswalk
Where evidence on financial economics of regulation fits the disclosure and prudential frameworks institutions report against.
Pillar
TCFD
ISSB IFRS S2
Prudential (BCBS, IAIS)
Evidence this page can hold
Governance
Board oversight of climate-related risks
Governance requirements
Governance and risk appetite principles
Who owns the risk and how it is escalated
Strategy
Risks, opportunities and resilience
Scenario analysis and resilience
Strategy and business model principles
Scenario design and transmission paths
Risk management
Identify, assess, manage
Risk management processes
Internal control and ICAAP or ORSA
Exposure maps and loss views
Metrics and targets
Metrics used and targets set
Cross-industry and industry metrics
Data, metrics and reporting principles
Indicator definitions and units
Sources: the TCFD recommendations, ISSB IFRS S2 and the BCBS and IAIS principles, cited by name; the framework texts are the authority. A crosswalk by pillar. It is not a compliance assessment.
NGFS climate scenarios · Network for Greening the Financial SystemIFRS S2 Climate-related Disclosures · ISSBTCFD recommendations · Financial Stability Board TCFDPrinciples for the effective management of climate-related financial risks · Basel Committee on Banking Supervision
What are the limits of financial economics and macro-finance in this field?
Relationships estimated in calm periods may break down in stress. Hidden leverage and interconnections are often unobserved.
How are results checked?
Models are back-tested against historical market episodes and crises. Results are compared with supervisory data and alternative specifications.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
Global Risks AllianceFinancial Regulation NexusFinance and Insurance ReadinessMethods and Technical
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