Selected Issues


Selected Issues

Toward Second-Generation Fiscal Rules in Sri Lanka1

Since their inception in 2003, fiscal rules in Sri Lanka have largely been unsuccessful in achieving the objective of reducing “government debt to prudent levels.”2 Over this same period the number of countries using fiscal rules has increased as have the number of design features. Techniques for rule selection and calibration have similarly evolved. This note utilizes the latest methods to select and calibrate second-generation fiscal rules for Sri Lanka and draws on cross-country experiences to highlight best practices for enhancing monitoring and enforcement. This could ensure that hard won gains from recent consolidation will be locked over the medium term.

A. Background

Fiscal rules in Sri Lanka

1. The Fiscal Management (Responsibility) Act was legislated in 2003 and subsequently revised in 2013 and 2016. The FM(R)A contains rules on debt, budget deficit and government guarantees (text table). However, the Act contains few enforcement mechanisms and does not prescribe corrective action in the event any of the targets are breached—it only requires that the government explain to Parliament the reason for the departure, steps the government plans to take to “overcome the causes necessitating such departure,” and the amount of the time the departure will last. Although the Act allows for departure from the requirements of the Act only under “exceptional circumstances” and only with the approval of Parliament, no formal escape clauses are specified and in practice the thresholds are serially breached with little consequence.

Summary of Key Provisions in Fiscal Management (Responsibility) Act

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2. The rules have not been effective in achieving their objectives. While the central government debt ratio fell from around 106 percent in 2002 to around 88 percent of GDP by 2006,3 it never met the original objective of the rule. Debt was around 72 percent of GDP in 2013 but nearly 80 percent of GDP by 2017. The overall deficit has never been less than 5 percent of GDP over the period from 1990 to 2017.

3. Achievement of the targets specified by the rule was made difficult in the early years of its operation by a string of economic shocks. Sri Lanka experienced a devastating Tsunami in December 2004 which directly impacted the economy. Corresponding reconstruction costs increased deficits and debt. Rising commodity prices and the global financial crisis in 2007–08, and increased military spending at the end of the civil war (followed by resettlement, reconstruction and rehabilitation costs in 2008–09) further exacerbated the fiscal situation likely contributing to the relaxation of the targets in 2013 (Ehelepola, 2017). Deviations from targets since then are more difficult to pin on macroeconomic surprises reinforcing the view that there are few political consequences for breaking fiscal rules. This could be also due to the perception that the existing targets are unrealistic making misses by successive governments “reasonable.”


Historical Debt and Overall Balance

(In percent of GDP)

Citation: IMF Staff Country Reports 2018, 176; 10.5089/9781484362358.002.A005

Source: IMF Staff Estimates, 2016 CBSL Annual Report

B. Principles Underpinning Effective Fiscal Rules

4. Effective fiscal rules should be able to correct policy biases in an efficient manner according to country-specific preferences. Key criteria are listed below (IMF 2018a). Partly in response to the Global Financial Crisis, second-generation fiscal rules tend to place a greater emphasis on flexibility, operational clarity, and enhanced monitoring and enforcement (IMF 2018c).

  • Sustainability. Compliance with the rule should ensure long-term debt sustainability.

  • Stabilization. Following the rule should not increase economic volatility. Economic stabilization requires that the rule let automatic stabilizers operate and/or allows discretionary countercyclical changes in taxes or expenditures.

  • Simplicity. The rule should be easily understood by decision makers and the public.

  • Operational Guidance. It should be possible to translate the rule into clear guidance in the annual budget process. Budget aggregates targeted by the rule should be largely under the control of the policymaker.

  • Resilience. A rule should be in place for a sustained period to build credibility, and it should not be easily abandoned after a shock.

  • Ease of monitoring and enforcement. Compliance with the rule should be easy to verify and there should be costs associated with deviations from targets.

5. Best practices suggest building fiscal frameworks around two pillars: a fiscal anchor linked to the country-specific objective of fiscal policy, and an operational rule on fiscal aggregates (IMF, 2018b). The debt-to-GDP ratio provides a natural fiscal anchor; however, it does not offer operational guidance in the short-run so fiscal frameworks should also include shorter-term operational rule(s) which are under the direct control of governments and have a close and predictable link to debt dynamics. The text table below provides the pros and cons of the most common operational rules.

6. Golden rules and adjusted budget balance rules are likely less well suited to Sri Lanka. A golden rule, which excludes capital spending from the deficit limit, is well suited for protecting capital spending but does not provide and effective speed limit on debt accumulation, as additional borrowing can take place to finance the public investment. Adjusted budget balances (e.g., adjusted for the cycle, or structural component of the economy like commodity revenues) are also less appropriate for Sri Lanka. Operating these rules requires estimating the output gap which is inherently uncertain in a small open economy subject to external shocks like Sri Lanka and communicating changes in the rule due to changes in the cycle can be difficult.

7. Expenditure rules can improve fiscal stability but have weaker links to debt sustainability. Expenditure rules, typically defined as caps on real expenditure growth, are easy to communicate with clear operational guidance and are typically used for their enhanced stabilization properties as they constrain spending when revenues are high. Such rules do not necessarily strengthen debt sustainability as they do not cover budget revenues. In countries undergoing fiscal consolidation, such as Sri Lanka, an expenditure rule could shift the burden of adjustment unnecessarily towards needed infrastructure and social spending. In expansionary periods, such a rule could hamper revenue mobilization by encouraging reductions in taxes or increase in exemptions. Similarly, a revenue rule could outline a path for increased revenues over the medium term. This may not ensure debt sustainability given lack of constraints on spending. They also tend to be heavily pro-cyclical.

Advantages of Select Operational Rules

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8. Sri Lanka’s current fiscal rule appropriately uses the overall budget deficit as the operational target. The simplicity of the budget deficit together with its direct link to debt dynamics makes it a good choice for an operational rule. On the downside, overall balance rules are poor at enhancing economic stabilization as they tend to be procyclical and the desire to satisfy the rule can lead to excessive cuts in capital spending, which are politically easier to pass than current spending or tax increases. A variant of the overall balance rule, called the “primary balance rule,” excludes interest payments from the balance – appealing as it is more directly under the control of policymakers. But this exclusion can weaken the link to debt sustainability and financing needs, especially in high-debt cases, if the rule threshold is not reassessed regularly.

C. Rule Calibration

9. Once an appropriate fiscal policy anchor and operational rule have been selected, it is important that they be calibrated to achieve the objectives set out by the rules. This section follows the methodology of the IMF’s How-to Note on calibrating fiscal rules (IMF, 2018b) which outlines four general principles:

  • Calibration should be comprehensive and consistent. To minimize risks of inconsistency and conflict between rules, the fiscal framework should be assessed as a whole and the thresholds should be calibrated in a consistent manner. In particular, there should be a clear relationship between the debt and fiscal balance ceilings.

  • Calibration should be sequenced. The framework should be structured around two types of rules – a fiscal anchor (with debt-to-GDP being a natural candidate) and an operational rule. The debt ceiling should preferably be set first, taking into account debt sustainability and the need to protect the country against adverse shocks followed by the operational rule.

  • Calibration should be prudent. Governments should take account of fiscal risks in setting fiscal targets and preserve buffers to accommodate shocks.

  • Calibration should be updated regularly but not too frequently. Fiscal rules are designed to be robust to macroeconomic shocks but conditions may evolve over time necessitating periodic updates.

Calibrating the Debt Ceiling

10. The debt limit and debt ceiling can be calibrated using stochastic simulations. The method followed in this section takes a cautious approach by identifying a debt ceiling that ensures debt remains below a known “debt limit” with high probability even when negative macroeconomic and contingent liability shocks occur. The calibration is done in two steps following IMF (2018b).4 The first step is to identify the debt limit. Second, the distribution of macroeconomic and fiscal shocks is estimated and used to simulate potential debt trajectories over a medium-term projection horizon. A debt ceiling is computed such that debt will remain below a debt limit over the medium term with high probability, despite the potential for negative shocks.

Step 1: Setting a Debt Limit

11. For the purposes of this simulation we have assumed a debt limit for Sri Lanka of 70 percent of GDP over the medium term. This corresponds to the target announced in the recently published Vision 2025 document and the debt distress threshold for emerging market economies, as also identified by the current IMF Debt Sustainability Analysis (DSA) methodology (IMF, 2013).

Step 2: Estimating the Effect of Shocks on Debt

12. Stochastic simulations were used to gauge the potential impact of macroeconomic and fiscal shocks on debt over the medium term. This requires estimating the joint distribution of macroeconomic variables (see Annex I for details). The set of variables used in the joint distribution include GDP growth, interest rates on government debt (foreign and domestic), exchange rate and contingent liabilities. To be consistent with the medium-term path under the EFF-supported program, the initial year chosen for the simulations was 2021 with the assumption that all macroeconomic projections presented in the Debt Sustainability Analysis for the IMF Staff Report for the 2018 Article IV Consultation and the EFF 4th Review (“May 2018 DSA”) will materialize up to 2020 (text table below).5

Assumptions used for Simulations6

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13. Each simulation produces a path for the macroeconomic variables over a medium-term projection horizon, where the variables have been subject to shocks in each period. Then, medium-term debt trajectories consistent with each simulated path of macroeconomic variables are obtained from the system of simultaneous equations formed by the debt accumulation equation (i.e., government budget constraint) and a fiscal reaction function in which the level of the primary balance may respond to the level of debt and realizations of macroeconomic variables (see Annex III for derivation of the fiscal reaction function). The fiscal reaction function includes a fiscal shock realized each period.7

14. Debt trajectories produced using stochastic simulations are summarized in a fan chart. The simulations suggest that a debt anchor of 50 percent is sufficient to ensure that debt stays below the debt limit of 70 percent with 90 percent certainty.


Estimated Debt Anchor for Sri Lanka

(In percent of GDP)

Citation: IMF Staff Country Reports 2018, 176; 10.5089/9781484362358.002.A005

Source: IMF Staff CalculationsNotes: Assumptions underlying estimates follow DSA projections up to 2020 as in Table 3.
Step 3: Calibrating the Operational Rule

15. Debt and deficits are tied through an accounting identity. A country’s debt is the cumulative stock of past deficit flows, while the (overall) deficit captures the annual change in the country’s debt.8 Mathematically the relationship between gross debt and the overall balance is an accounting identity:


where Dt is the nominal level of debt at the end of period t, γt is the nominal growth rate of GDP, with small letters denoting a variable as a share of GDP. The debt dynamics equation is then


with obt denoting the overall balance ratio in period t, λt0=γt/(1+γt) denoting the growth-adjusted interest rate.

16. A variety of overall deficit limits are analyzed to assess the implications for the year of convergence to the targeted debt level. The initial year is set at 2021 and the initial debt level is set conservatively at 79.5 percent of GDP, which is equal to the level of central government debt and debt guaranteed by the central government projected in the May 2018 DSA. The baseline scenario assumes unchanged policy with an overall deficit of 3.5 percent of GDP from 2021 onwards.9

17. Text table below shows that under the baseline scenario, Sri Lanka’s public debt will reach the debt anchor (50 percent of GDP) only by 2034. Sensitivity analysis shows that with higher nominal growth (12 percent versus 10 percent in the baseline) the convergence to the debt anchor could happen 5 years sooner. However, with slower growth or larger operating deficits, convergence would be beyond 2050.

18. Pivoting to a smaller overall deficit after the initial ceiling is reached would accelerate convergence and reduce risks to debt sustainability. Under an active policy scenario that gradually transitions from a 3.5 percent overall deficit in 2020 to 2 percent, debt would reach 50 percent of GDP by 2029 – five years faster than under the baseline.

Sri Lanka: Convergence Scenarios for the Debt Ratio10

(In percent of GDP, unless otherwise noted)

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Note: The smaller deficit scenario assumes gradual reduction in deficits from 3.5 percent in 2021 to 2 percent in 2025.

Sri Lanka: Fiscal Deficit and Public Debt Paths

(In percent of GDP)

Citation: IMF Staff Country Reports 2018, 176; 10.5089/9781484362358.002.A005

Sources: Ministry of Finance; and IMF staff estimates.

D. Additional Design Features for Effective Fiscal Rules

19. The mere introduction of fiscal rules does not guarantee success. Sri Lanka’s second-generation fiscal rule should draw on other countries’ experiences with rule design and enforcement. Best practices suggest fiscal rules should have broad institutional and economic coverage, contain escape clauses to deal with unforeseen events automatic correction mechanisms to define what should be done in the case of a breach. Effective monitoring of fiscal rules is also often carried out by an independent fiscal council.

Evolution of Fiscal Rules Around the World

20. The number of countries using fiscal rules has increased steadily over the last 25 years rising from just a handful in 1990 to around 90 in 2015 (Fiscal Rules Database). The rules themselves have also evolved and now commonly contain features to improve their effectiveness and flexibility. Many countries have adopted rules that adjust for the economic cycle, have well defined escape clauses, and formal enforcement procedures. Monitoring has also greatly improved as nearly 30 countries now use fiscal councils to independently monitor fiscal rules.


Adoption of Fiscal Rules

(Number of countries)

Citation: IMF Staff Country Reports 2018, 176; 10.5089/9781484362358.002.A005

Source: IMF Fiscal Rule Dataset
Enhancing Compliance

21. Compliance can be improved through the introduction of correction mechanisms which stipulate what policy makers should do in the event a particular rule is breached. Mechanisms typically have two parts—the trigger and the correction action (IMF, 2018c). Triggers can be designed such that they are activated after a fiscal rule has been breached or when there is an elevated risk of a rule being breached in the future.11 Assessing when a rule has been breached can be done either quantitatively (e.g. when a threshold has been crossed) or qualitatively when a fiscal council or policymakers determine a significant breach has occurred. While the quantitative trigger prevents the use of discretion by policy makers to avoid potentially painful corrective action, the qualitative trigger prevents potentially burdensome corrective actions for insignificant deviations from target. The period over which compliance or deviation from the rule is assessed is also important. Some countries have corrective mechanisms that are triggered by deviations from target in a single year, others use an average over two previous years (Finland, Ireland and Italy) or cumulative deviations (Germany).

22. The corrective actions prescribed under the mechanism should restore compliance with the rule. There are many considerations for achieving this, including:

  • Size of the corrective action. The mechanism can merely force the operational target back below the threshold or require policy makers to fully compensate for the deviation by undershooting the threshold by the amount of the breach in subsequent years. Fully offsetting the size of the breach ensures that there is little to no impact on the permanent level of the debt stock from breaches in the operational target.

  • Timeframe for correction. The time given to complete the corrective action can range from immediate correction (in-year for the preemptive trigger or next year’s budget) to several years. The time to correct an operational target could also vary depending on how close the country is to its debt limit (i.e., a shorter correction horizon could be defined for cases when the country is near its debt limit).

  • Policy mix. Some corrective actions give full discretion to policy makers on achieving consolidation (e.g., either through revenue measures or expenditure cuts) while others prescribe a specific action (e.g., across the board expenditure cuts).

23. Fiscal rules coverage should also be broad based to counter the risk that rules are circumvented by fiscal or quasi-fiscal activities taking place outside the rule (e.g., through the activities of state-owned enterprises). As noted above, a broad rule could be one that covers the largest portion of fiscal activities that impact the rule’s objective (e.g., a budget balance rule is more comprehensive than revenue or expenditure rules) but it could also mean covering particularly risky state enterprises under the rule.12 Brazil, for example, has a fiscal rule that covers the nonfinancial public sector (e.g., federal government, social security, states and municipalities, state and local enterprises and the central bank).

Escape Clauses

24. Escape clauses can formalize the circumstances when fiscal targets could be breached for justifiable reasons (e.g., natural disaster events, recessions). Indeed, the widespread breaches of existing fiscal rules following the Global Financial Crisis led many countries to consider and implement escape clauses into their second-generation fiscal rules. Well-designed escape clauses should have:

  • A limited and clearly defined set of events that can trigger the clause. These should not include cyclical events.

  • Time limits on how long fiscal policy can deviate from the targets laid out in the rule under the escape clause.

  • A requirement for fiscal policy to return to the targets after the operation of the escape clause is terminated.

Improving Monitoring

25. Even the best-designed fiscal rules can still be ineffective if they are not underpinned by strong fiscal forecasting capabilities and monitored by a credible entity. Dedicated macro-fiscal units with strong forecasting abilities aid in the coordination of macroeconomic and fiscal projections and ease the monitoring and assessment of progress against a given rule. After the Global Financial Crisis, a number of countries assigned the responsibility of monitoring fiscal rules to fiscal councils (Beetsma and others, 2018), to increase the political incentive to adhere to rules by raising the cost of non-compliance. It is important that such institutions be truly independent and credible. While fiscal councils have been common in Europe, countries outside the EU that have created fiscal councils to monitor fiscal rules include Brazil, Chile, Colombia, and Peru.

26. Governments rarely want to tie their own hands by limiting discretionary fiscal policy and performance against binding fiscal rules. Sri Lanka’s mixed experience with the enforcement of fiscal rules since 2013 is no different. There seems to be significant scope to upgrade the existing rule, by adding correction mechanisms and effective monitoring, while at the same time improving flexibility to deal with justifiable macroeconomic shocks. These enhancements would provide an important signal to the markets that rules will now be taken seriously, with benefits in terms of improved credit worthiness and lower financing costs. Furthermore, fiscal rules can be effective in ringfencing the conduct of fiscal policy from political cycle considerations—ensuring electoral promises by ruling and opposition parties alike are bound by the same rules.

E. Conclusions

27. Focusing on the principles of simplicity and operational guidance, a fiscal rule that is anchored by the debt ratio and utilizes the overall balance as an operational target seems appropriate for Sri Lanka. The latest calibration techniques suggest that over the medium to long term a debt anchor of 50 percent of GDP would be appropriate to ensure debt stays below 70 percent of GDP with 90 percent probability. Achieving the fiscal consolidation path outlined in the May 2018 DSA up to 2020 and then gradually reducing the overall deficit from 3.5 percent of GDP to 2 percent over the period from 2021 to 2026 would accelerate convergence to the debt anchor by 2029 and reduce risks to debt sustainability. To improve compliance with the rule and enhance flexibility in the event of unforeseen events, a second-generation fiscal rule for Sri Lanka should include appropriately designed enforcement mechanisms and escape clauses. Consideration should also be given to strengthening macro-fiscal forecasting through a dedicated unit and utilizing a fiscal council to independently monitor compliance with the rule.

Annex I. Deriving the Debt Ceiling Threshold

This Annex reproduces Method 1 of rule calibration contained in the How-to Note (see IMF 2018a for details). This method requires the characterization of the joint distribution of the macroeconomic variables needed to project the public debt ratio. For advanced and emerging market economies, these variables are growth, the average interest rate on debt and the exchange rate. Characterizing the joint distribution is done by directly calibrating a joint multivariate distribution where only annual data are available.

Direct Calibration of a Multivariate Distribution

A multivariate normal (or student-t) distribution of key macroeconomic variables can be calibrated based on historical co-movements of macroeconomic variables. N sequences of 6-year projections can be obtained by drawing repeatedly from this distribution.

A multivariate normal distribution of a k-dimensional vector of macroeconomic variables can be written as:

xNk(μ,Σ)withthe k-dimensional mean vectorμ=(E[X1],E[X2],...,E[Xk])and the k×kcovariance matrixΣ=(cov(Xi,Xj)),foralli=1,2,....,k;j=1,2,...,.k

The parameters μ, Σ can be calibrated based on the historical mean, variance and co-variance of macroeconomic variables.

Calibrating the Debt Ceiling

The debt ceiling is calibrated as follows:

  • A set of macroeconomic variables are forecast over a 6-year projection horizon N times by drawing directly from the calibrated multivariate distribution of macroeconomic variables each year.

  • The N sets of macroeconomic variable forecasts are used to generate N trajectories of the primary balance, using a fiscal reaction function and the previous year level of debt. The distribution of fiscal shocks is calibrated based on estimated deviations between actual fiscal responses observed (i.e., actual levels of the primary balance) and the fiscal response predicted by the fiscal reaction function within the sample.

  • The N corresponding trajectories of debt (starting at the current debt level) are obtained by the system of simultaneous equations formed by the debt accumulation equation (government budget constraint) and the fiscal reaction function. The debt accumulation equation is:
    where dt is debt (as a ratio of GDP), rt is the average effective real interest rate on debt, gt is the real GDP growth rate, pbt is the primary balance (as a ratio of GDP) and SFAt is the stock-flow adjustment (as a ratio of GDP). The debt accumulation equation includes a constant stock flow adjustment (SFA) each period, that could potentially account for realization of contingent liabilities.
  • If the 95th debt percentile (or other chosen percentile) of the debt ratio distribution in any year over the projection horizon is not sufficiently close to the maximum debt limit (MDL), the “starting level” of debt is adjusted by a small amount (0.4 percent or below) and steps 1–3 are repeated based on this new “starting level” of debt.

Steps 1–4 are repeated until the 95th percentile of the debt level falls into a small interval around the MDL in any year over the medium-term projection horizon: Debt95 ∈ [MDL – 0.4;MDL + 0.4]. The “starting level” of debt satisfying this criterion is called the debt ceiling, i.e., the level of debt from which its projection does not exceed the MDL with 95 percent likelihood over the medium-term projection horizon. The safety margin is computed as the MDL minus the debt ceiling.

Annex II. Fiscal Reaction Function1

A Fiscal Reaction Function (FRF) is a rule linking a particular level of the primary balance to prevailing macroeconomic and fiscal conditions. The FRF applicable for emerging market economies is based on the specification of Bohn (1998). Other research on fiscal reaction functions in advanced or emerging market economies includes Abiad and Ostry (2005), Celasun and Kang (2006), and IMF (2003a).

The coefficients of the FRF are estimated econometrically to capture historical fiscal behavior. The specification to be estimated is:


Where pbit is the primary balance (as a ratio of GDP) of country i in year t, dit is debt (as a ratio of GDP), ygapit is the output gap, Dit is an indicator variable taking the value of one when the output gap is positive, αi is the country specific intercept term (fixed effect) and εit is a random error term, εit ~ N(0, σ2). The FRF allows for an asymmetric response to the output gap, so that the primary balance may deteriorate more when the output gap is negative, than it improves when positive (β3 > β2). The output gap is projected over the forecast horizon using GDP growth forecasts obtained from simulations (based on the joint distribution of macroeconomic variables) combined with an HP filter to estimate potential output.

The FRF used in the simulations has been estimated in a cross-country regression including 25 EMs.2 Coefficient estimate are as follows:


Annex III. Estimating the Stock-Flow Adjustment

The stock-flow adjustment can be estimated as the difference between fitted values of the debt equation and actual debt data (expressed as ratios to GDP)1:


d is the debt-to-GDP ratio, g is the real growth rate, αd and αf are the ratios of domestic and foreign currency denominated to total debt, and rtdandrtf are the real interest rates on domestic and foreign currency denominated loans, respectively; Δε is the real exchange rate depreciation.


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Prepared by Jeff Danforth.


Fiscal Management (Responsibility) Act, No. 3 of 2003.


The figures prior to 2010 are based on the historical debt statistics published by the central bank (Annual Report, statistical appendix Table 7) which, unlike debt ratios contained in the World Economic Outlook, do not adjust historical GDP levels when GDP is rebased.


This method was developed by Debrun and others (2017) and Baum and others (2017). Earlier research on stochastic simulations of debt trajectories includes IMF (2003), Ferrucci and Penalver (2003), Garcia and Rigobon (2004), and Celasun and others (2007).


This allows us to abstract away from uncertainty related to projections assumed under the program and also corresponds to the year that could conceivable be the first year of operation of a second-generation fiscal rule.


Consistent with the May 2018 DSA. The debt-to-GDP ratio is equal to central government debt plus guaranteed debt.


The distribution of fiscal shocks is calibrated based on deviations between actual fiscal responses observed (i.e. actual levels of the primary balance) and the fiscal response predicted by the fiscal reaction function over the sample.


In practice the link between debt and deficits can be influenced by accumulation of financial assets, currency fluctuations, and non-debt financing of deficits but these effects tend to temporary.


Since the overall balance would be a target for the central government this is equivalent to the SOE sector running balanced budget throughout the project.


The initial debt level is the 2020 figure from the May 2018 DSA.


For example, if in-year spending outturns suggest a risk of breaching a budget balance or expenditure rule, budget allocations could be scaled back. Such a mechanism requires efficient and timely monitoring of budget execution and spending commitments.


This is the approach taken simulations contained in the section on calibrating the rule.


Reproduced from IMF (2018b).


Countries included: Brazil, Bulgaria, Chile, China, Colombia, Egypt, Hungary, India, Indonesia, Kazakhstan, Kenya, Latvia, Lithuania, Malaysia, Mexico, Pakistan, Peru, Philippines, Poland, Romania, Russia, South Africa, Thailand, Turkey, and Ukraine.


For a derivation of this equation, See IMF (2013), Annex I.

Sri Lanka: Selected Issues
Author: International Monetary Fund. Asia and Pacific Dept