Spatial financeWhere capital meets hazard, exposure and transition
Econometrics for public finance and sovereign debt
Econometrics estimates relationships from fiscal and macroeconomic data and tests whether they hold. On this platform it supports estimates of revenue volatility, fiscal reaction functions, efficiency gaps and the effects of shocks on public debt.
Econometrics applies statistical methods to economic data to estimate relationships, test theories and forecast. It provides empirical evidence on how shocks and policies affect economic outcomes. In sovereign and public finance, development finance and disaster and crisis, econometric evidence estimates how disasters, pandemics and financial shocks affect output, employment and prices. It informs the economic case forrisk reduction. The canonical description is onthe STEM Commons.
Fiscal reaction functions
Estimates of how governments adjust primary balances in response to debt levels inform judgements about fiscal space and credibility.
Revenue volatility
Commodity and tax revenue series are modelled to estimate volatility and its relationship with prices and output, informing buffer sizing.
Disaster effects on public finance
Panel data on past disasters estimate average effects on revenue, spending and debt, with heterogeneity across countries reported.
03Çavdêrî bike
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
Public finance and sovereign debt · Econometrics for public finance · Run R-5003
Estimates stableGRA · Public Finance and Sovereign Debt
Estimates
robust standard errors
Public debt
0.03
0.19
[−0.4, 0.2]
Erê
Gross financing needs
0.29
0.12
[−0.2, 0.4]
Erê
Interest to revenue
0.20
0.13
[0.0, 0.5]
Na
Share of FX debt
0.33
0.05
[0.1, 0.9]
Erê
Method card
Rêbaz
Ekonometrî
Sample
1642 obs
Sêwirandin
panel, fixed effects
Nîşan
MODELKIRÎ
Residuals by group
Econometric model: the screen’s structure, terms and states for Public finance and sovereign debt.Nav û nirxên nimûneyî; sêwiran e, ne qeyd an pergaleke zindî ye.
04Dane
What the method consumes.
Datasets and records used by econometrics on this platform, with the role each plays and the label its values carry. Sources are listed inthe source register.
Dane
Rol
Nîşan
Fiscal time series
Estimation
Statîstîkên weşandî
Commodity price series
Revenue drivers
ÇAVDÊRÎKIRÎ
Disaster databases
Event data
REPORTED
05Scenario model
Sovereign debt paths and the odds of breaching a threshold.
The distribution of debt paths, and the share above a threshold of concern at the horizon, that sovereign investors and rating analysts read from a fan chart. Teaching model with stated illustrative values, not a prediction.
Median, 25% to 75% and 10% to 90% bands
No shocks
Kontrol
Debt today
70% of GDP
Effective nominal interest rate
5.0%
Nominal GDP growth
4.5%
Primary balance
−0.5% of GDP
Volatility of growth
2.0 points
Volatility of the interest rate
1.0 points
Salên pêş
10 years
Threshold of concern
90% of GDP
Xwendin
Median debt at the horizon
79% of GDP
Paths above the threshold at the horizon
3%
Primary balance that stabilises debt
0.3% of GDP
Jimar, rêbaz û çavkanî
Sal
10%
25%
Median
75%
90%
0
70.0
70.0
70.0
70.0
70.0
1
68.8
69.7
70.9
72.0
73.1
2
68.6
70.1
71.5
73.1
74.6
3
68.9
70.7
72.5
74.3
76.1
4
69.2
71.3
73.3
75.5
77.5
5
69.4
71.8
74.5
76.7
79.2
6
69.9
72.7
75.3
77.7
80.8
7
70.6
73.1
76.2
79.0
81.9
8
71.2
74.0
77.1
80.2
83.3
9
71.9
74.8
77.8
81.2
84.4
10
72.0
75.2
78.7
82.0
85.7
Rêbaz
Debt dynamics and the interest-growth differentialBlanchard (2019), Public debt and low interest rates, American Economic Review 109
Stochastic fan chartsCelasun, Debrun and Ostry (2006), IMF Staff Papers 53
Sovereign risk and debt sustainability frameworkIMF (2022), Staff Guidance Note on the SRDSF
Dane
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
Sovereign debt paths and the odds of breaching a threshold. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: Debt dynamics and the interest-growth differential (Blanchard (2019), Public debt and low interest rates, American Economic Review 109); Stochastic fan charts (Celasun, Debrun and Ostry (2006), IMF Staff Papers 53); Sovereign risk and debt sustainability framework (IMF (2022), Staff Guidance Note on the SRDSF).
Li seranserê şeş stûnan, bi pêşengiya Nexus Consortium
Models are assessed through specification tests, robustness checks and out-of-sample performance. Results are compared across datasets and methods.
Kontrol bikin
How it is done
Robustness
Results are checked across specifications and samples
Endogeneity
Methods to address reverse causality are stated
Out-of-sample
Models are tested on periods not used in estimation
Endogeneity, measurement error and structural change can bias estimates. Relationships may shift under extreme conditions.
07Exposure, loss and capital
What it 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.
Capital, solvency and fiscal indicators
The indicators a risk officer, supervisor or ministry of finance reads first on econometrics for public finance and sovereign debt.
Indicator
Unit
Who reads it
Framework
Public debt
% of GDP
Ministries of finance, IMF
Debt Sustainability Framework
Gross financing needs
% of GDP per year
Ministries of finance, investors
Debt Sustainability Framework
Contingent liabilities
% of GDP, by source
Ministries of finance
Fiscal risk statements
Interest to revenue
% of revenue
Ministries of finance, rating users
Public finance statistics
Sovereign spread
basis points over a benchmark
Investors, debt managers
Market data
CET1 ratio
% of risk-weighted assets
Banks, supervisors
Basel framework
Liquidity coverage ratio
% of stressed outflows
Banks, central banks
Basel framework
Source: the frameworks named in each row. Indicator names, units and frameworks only; values belong to each institution’s own reporting and are never shown here.
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 econometrics in this field?
Endogeneity, measurement error and structural change can bias estimates. Relationships may shift under extreme conditions.
How are results checked?
Models are assessed through specification tests, robustness checks and out-of-sample performance. Results are compared across datasets and methods.
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.
rêzeya Pergalên Stratejîkis 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 AllianceDarayiya giştî û deynê serwerîAmadebûna fînans û sîgortayêXetera pergalan û berxwedana welatan
Tu carî daneyên şexsî, hûrgiliyên binesaza hesas an tiştekî ku mafê we yê parvekirinê tune ne neşînin. Beşdarî berî bikaranînê tê nirxandin; şandina wê nivîskarî an mafên edîtorî nade û sponsorî tu carî encamekê nakire.
Darayiya giştî û deynê serwerî
Bring an exposure or capital question to the Alliance.
Agahî û pirs îro vekirî ne. Pirsek referansekê distîne û gava piştî wê dide nasîn; serlêdan, drav, veqetandina hesabkirinê û tomarkirin tenê dema ku tîm, mercên wê û kapasîteya vekolînê hebin vedibin.
Nexşe, dane û jimarên vê malperê ji bo çarçoveyê û agahiyên giştî têne nîşandan. Ew ne şîret, ne pêşbînî û ne hişyarî ne; sînorên agahiyê di Daxuyaniyên Berpirsiyariyê û Daxuyaniyên Daneyê de hatine diyarkirin.
Editors and the expert reviewers named on each article decide what we publish. Funders and partners do not review or approve articles before publication.
Privacy choices · Public Finance and Sovereign Debt
This site uses only strictly necessary cookies to work and to remember your privacy choices. Nothing loads from other companies, and we never sell or share your personal information.
Details
This site uses only strictly necessary cookies to work and to remember your privacy choices. Nothing loads from other companies, and we never sell or share your personal information. We run no advertising. You can review your choices at any time through Privacy choices at the foot of every page.