Peru’s fiscal framework embedded in the Fiscal Responsibility and Transparency Law (FRTL) has proved to be effective in reducing debt. The FRTL embodies some countercyclical elements in response to output or commodity price shocks. The combination of a provision for a moderate deficit on the downside, and a current expenditure cap on the upside, allows for some countercyclical policy. It still has pockets of procyclicality in the face of large shocks to output or commodity prices.

Abstract

Peru’s fiscal framework embedded in the Fiscal Responsibility and Transparency Law (FRTL) has proved to be effective in reducing debt. The FRTL embodies some countercyclical elements in response to output or commodity price shocks. The combination of a provision for a moderate deficit on the downside, and a current expenditure cap on the upside, allows for some countercyclical policy. It still has pockets of procyclicality in the face of large shocks to output or commodity prices.

I. Towards a Structural Fiscal Framework1

A. The Current Fiscal Framework

1. The current fiscal framework—embedded in the Fiscal Responsibility and Transparency Law (FRTL)—has been effective in reducing debt. It has imposed fiscal discipline by limiting the deficit in lower phases of the cycle and curbing expenditures growth on the upside, allowing Peru to reduce its debt and accumulate significant financial assets. Public sector gross debt was reduced from 44 percent of GDP in 2004 to 24 in 2010 (Figure 1). Similarly, a sound debt management strategy successfully reduced debt vulnerabilities in terms of currency and interest rate risks. While very successful in terms of fiscal discipline, the framework can be further reviewed, particularly when debt levels are more comfortable

Figure 1.
Figure 1.

Public Sector Debt

(In percent of GDP)

Citation: IMF Staff Country Reports 2012, 027; 10.5089/9781463940423.002.A001

2. The FRTL has not prevented procyclicality in specific years. For example, fiscal policy was pro-cyclical in 2008 due to increased spending beyond the limits imposed by the FRTL, while turning countercyclical in the following two years as a response to the financial crisis (Figure 2). In 2009, with considerable fiscal space, the government reacted to the global crisis by providing a fiscal stimulus of 3.5 percent of GDP. The stimulus—mainly based on spending measure—shifted the budget into a deficit of 1.6 percent of GDP resulting in a temporary relaxation of the FRTL targets (Box 1). However, fiscal policy was considerably expansionary in 2010, despite the rapid recovery of output and emerging signs of overheating. The procyclical bias left a large part of the burden of the macroeconomic adjustment to monetary policy.

Figure 2.
Figure 2.

Cyclicality of Fiscal Policy

(In percent of potential GDP)

Citation: IMF Staff Country Reports 2012, 027; 10.5089/9781463940423.002.A001

3. FRTL does not rule out discretional changes in tax rates, raising the risk of procyclical measures. In 2011, the authorities reduced several tax rates; the most important being the reduction of one point in VAT tax rate. Despite these procyclical measures, the fiscal impulse dissipated in the second half of 2011 mainly due to expense restraining at the central government and low execution rates of capital spending at the subnational level.

4. The FRTL embodies some countercyclical elements in response to output or commodity price shocks. The combination of a provision for a moderate deficit on the down-side, and a current expenditure cap on the up-side, allows for some countercyclical policy. However, it still has pockets of procyclicality in the face of large shocks to output or commodity prices. In particular, it has no direct mechanism for saving high-cycle mineral revenues. Although, part of the revenues windfalls is accumulated in the Fiscal Stabilization Fund (FEF), rigidities in its withdrawal rules have prevented it to function effectively as a macroeconomic stabilization fund (see Box 2).

5. Coverage of the FRTL has not been applied consistently, either over time or across subsectors, hindering the transparency of the rule. Expenditures caps have changed several times since the FRTL was introduced (see Box 1). Changes include not only the use of deflators and targets for real growth rates, but most importantly, the transactional coverage used to set the cap (i.e., from current to consumption expenditures). Moreover, the institutional coverage of the rule is not applied consistently across subsectors. While expenditure caps apply only to central government, the overall deficit limit covers the nonfinancial public sector. In addition, subnational governments are constrained by a different set of rules.

6. The use of exceptional clauses has proved to be challenging in the past. Although the FRTL includes an “exceptional clause”, authorities have had difficulties in using it on a timely manner mainly due to imprecision in the specification of the circumstances activating the emergency. During the 2009 financial crisis, the conditions triggering the use of the clause comprised: negative real GDP growth for two consecutive quarters, and increase in international interest rates. None of these conditions materialized during the crisis, delaying the policy response that was finally implemented through an urgent decree.

7. Finally, the implementation of the FRTL at the subnational level has been problematic, with high and increasing rates of non-compliance. This has resulted in frequent changes in the parameters of the fiscal rules to accommodate the growing spending pressures at the subnational level, hindering predictability.

8. Going forward, there is a case for Peru’s fiscal policy to limit procyclical possibilities, include more countercyclicality in case of extreme shocks, while continue generating surpluses. As a small open natural resource-exporting economy, Peru would benefit from a comprehensive fiscal framework which converts current windfalls into higher government savings, so they could be available to cushion the economy when growth falters, prices fall, or mineral resources are exhausted. Moreover, a cautious fiscal policy stance is warranted given the need for ensuring faster progress to reduce poverty and inequality and minimizing the threats of contingent claims and natural disasters.

Fiscal Responsibility and Transparency Law

Legal status of the rule. The “Ley de Responsabilidad y Transparencia Fiscal” (FRTL) was enacted in December 1999 as a permanent institutional device to promote fiscal discipline in a credible, predictable, and transparent manner. In 2003 the Fiscal Management Responsibility Act, supplemented the FRTL, with a clear objective of debt consolidation.

Rationale for the fiscal rule. The FRTL included a combination of a nominal deficit target and real current expenditure ceiling for the nonfinancial public sector and central government respectively, as well as debt ceilings for subnational governments. The main features of the Peruvian FRTL can be summarized as follows:

  • The government must prepare the Multi-Annual Macroeconomic Framework (MMM) containing three-year macroeconomic projections of revenue, expenditure, public investment, and public debt.

  • Numerical fiscal targets are embedded in the law (see Table below).

  • Escape clauses allow deviations from numerical targets during periods of low growth.

  • Cyclical considerations are taken into account by establishing fiscal stabilization funds to mitigate spending cyclical variations (see Box 2).

Historical compliance with the rule. The numerical targets have been changed over time, such as in 2003, 2007 and 2009. The following table summarizes the main changes introduced to the FRTL.

Numerical Targets of the FRTL

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Sources: Fund staff estimates.(*) Exceptional clause in application.

Numerical rules for subnational governments are not included in this table.

According to the national definition, consumption comprises spending on wages and salaries, goods and services, and pensions. Deflacted by GDP deflactor.

Deflacted by inflation target of BCRP (2 percent).

Ad-hoc response to 2009 global financial crisis. The impact of the 2008-09 global financial crisis was significant, which called for countercyclical monetary and fiscal policies. Escape clauses in the law were not applicable for this particular shock. However, the FRTL includes an exceptional escape clause that allows for a temporary relaxation of the targets with Congressional approval. The relaxation of the FRTL targets was approved in May 2009 for the following two years to allow a deficit of 2 percent of GDP.

Return to the rule in 2011. The rule became bidding since May 2011, even though additional rules for the subnational levels where simplified.

Fiscal Stabilization Fund

The FRTL comprises a fiscal stabilization fund (FEF). Resources of the FEF include any fiscal surpluses generated by the Treasury, 10 percent of privatization proceeds, and 10 percent of concessional fees. These assets are deposited at the central bank or abroad but under similar management criteria as with international reserves. The FEF is subject to a cap of 4 percent of GDP, with any excess allocated to debt reduction. FEF resources may only be used when revenues are at least 0.3 percent of GDP lower than the average ratio of the last 3 years. However, no more than 40 percent of total funds can be used in a given year, except when the escape clauses contained in the LRTF (article 5) apply.

The FEF has worked de facto as a savings fund. It accumulated 1.4 percent of GDP (at end-2010). Its rules proved too stringent for it to be used for stabilization—mainly because two quarters of declining GDP are needed before funds can be used, and they are capped. As a result, funds that were not allocated to the FEF and those deposited were barely used. The FEF was not used for the fiscal stimulus package, mainly because discretion regarding the timing of inflows to the FEF allowed the government to apply the previous year Treasury surplus to the stimulus rather than transferring it to the FEF.

The authorities recapitalized the FEF at the beginning of 2011. The authorities added up to the fund US$3.5 billion from a combination of the Treasury surplus at end-2010, 50 percent of central government bank balances, and proceeds arising from the bank account consolidation process being undertaken to improve coverage of the treasury single account. Taken together, the fund is expected to accumulate around US$6 billion or 3.5 percent of GDP by end-2011.

B. Structural Guidance for Peru’s Fiscal Policy

9. The current fiscal framework could be enhanced by introducing a structural measure as a reference value or “guidance” for fiscal policy. Structural measures could provide a useful policy anchor by helping the policy discussion by identifying its discretionary component. By purging nominal fiscal balances of the cyclical and abnormal commodity price components of taxation and spending, structural measures can be used to limit procyclicality. Albeit with some institutional differences, Chile’s experience is particularly relevant, given its success in applying a structural rule, taking into account both the economic cycle and the copper cycle. By focusing on a structural measure “a la Chile”, pressures for potential tax changes—as the one observed in early 2011—could be contained. Similarly, a structurally-based fiscal framework could provide better guidance regarding the level of fiscal savings that should be targeted, both in terms of revenues and commodity price booms. Finally, a structurally-based fiscal framework would also facilitate coordination of monetary and fiscal policies.

10. Yet, benefits of incorporating structural measures into policy discussion should be carefully evaluated relative to its implementation difficulties. While structural measures are regularly used by international organizations and national institutions, weaknesses in their implementation have been well documented. This reflects in part the relative complexity of the techniques used for the estimation of output gaps, long-term commodity prices, and budgetary elasticities, as well as the need of some judgment. To the extent that technical difficulties in the computation of these measures affect their accuracy and reliability, discussing them is warranted.

11. There are four main concerns in estimating structural fiscal balances: (i) different methods for estimating structural measures can yield different results, particularly for the structural balance level; (ii) forecasts and outturns of structural measures can be subject, respectively, to large errors and to significant revisions, regardless of the specific method used; (iii) structural measures require strong institutions to implement them; and (iv) selecting the right timing for introducing a structurally-based fiscal framework is crucial for its success. These issues are discussed below.

Estimation methods

12. Main difficulties regarding methodologies arise from: (i) different techniques for estimating trend output and output gap produce different results; (ii) the same concern holds for commodity prices; and (iii) accurate estimation of budgetary elasticities is not always feasible given the information requirements.

13. There are various techniques available for computing potential or trend output. Although they can provide different estimates of output gap—and related structural measures—results obtained with different methods display strong short-term correlations, although the range level estimates is wide.2 When output gap is very volatile or subject to structural breaks, this problem is likely to be more acute.

14. Estimation of long-term commodity prices is particularly challenging. Commodity prices impact the budget directly through tax income revenues and royalties, as well as indirectly through their impact on output.3 However, adjusting nominal balances for deviations from current commodity prices to their benchmark levels requires a transparent and analytically sound methodology for assessing long-term trends in such prices. This has proved to be challenging.

15. Reliable estimates of budget elasticities can be data intensive. Elasticities are often estimated econometrically using macro variables. However, its accuracy depends on adequately controlling for discretionary policy, while it requires detailed institutional knowledge. In the absence of detailed information, the used of international benchmarks is a common practice.

Forecasting errors and data revisions

16. Structural measures are affected by errors in calculating the unobserved trend output and commodity prices. While forecasts for the actual nominal balance depend on estimates of actual GDP and commodity prices, forecasts for structural balances depend on estimates of trend GDP and commodity prices. Yet, it is impossible to say a priori which of the two estimates is subject to greater error, in which case, forecasts of structural measures would be as accurate as (or no more inaccurate than) forecast of corresponding nominal balances.

17. Estimate revisions can significantly affect structural measures. Revisions to past structural measures are influenced by the realization of new data; whereas, nominal balances are not. This is so since, estimates of trend output and commodity prices are usually some form of weighted averages of realized data and forecasts for a number of periods ahead. As time passes, subsequent computation of structural measures for a given period can give different results. This is a significant challenge in commodity price forecasts, as there may not be consensus on its long-term values.

18. The impact of new data on changes in structural measures—i.e., fiscal impulse indicator—is less significant. This is primarily because the revisions generally affect estimates for contiguous years in roughly similar manner, leaving the change in trend between years relatively unaffected. Thus, focusing on changes in structural measures (fiscal impulse) would reduce the risks of an imprecise estimation of the level of trend output and commodity prices.

Institutional requirements

19. Structural fiscal frameworks require strong institutions. This entails strong commitment to transparency, well-established policy credibility, and good governance structure and quality of institutions. All these elements are, in various degrees, present in Peru. Recent technical assistance has identified significant progress in most of these areas, and the authorities are working to improve further.4

Timing issues

20. Selecting the appropriate timing for introducing a structurally-based framework is crucial for its success. Adopting a structural framework requires that important economic and institutional pre-conditions be met. Caution suggests that changes should preferably be introduced when macro stability is achieved, any significant fiscal stimulus from previous periods has been withdraw, and the output gap is close to zero. According to staff estimates, Peru seems to have achieved most of such prerequisites.

21. Care should be taken to avoid different interpretation of data. Given the potential debate regarding some factors entailed in the computation of these measures, it is particularly important to have transparency in the estimation procedures. This is especially so when output and commodity prices volatility complicate the task of estimating long-term trends. The authorities have taken initial steps in this direction, incorporating in the MMM an estimation of the structural fiscal position. Yet, further efforts are needed to refine the methodology for the structural calculations, as well as to agree on a medium-term target.

C. Structural Balance Estimates for Peru

22. There are three main structural balance estimates for Peru. Both the Ministry of Economy and Finance (MEF) and the Central Reserve Bank of Peru (BCRP) disseminate their estimates of the structural fiscal position—albeit differences in the methodologies persist. Similarly, IMF uses structural measures to assess discretional fiscal policy, which, in turn, differ from the official figures.

23. This section aims at outlying main features of the different methodologies. It is not intended to be an exhaustive analysis; instead, its purpose is to explore main methodological issues that may explain discrepancies in the results obtained by the MEF, BCRP, and IMF, with information collected so far.

Main Results

24. Because any methodology has some analytical judgment, it is not surprising that the results differ. Table 1 presents the three different estimations. Discrepancies observed for the 2003–2010 period are fully explained by differences in methodologies; whereas, discrepancies for the 2011–2013 period are also caused by different underlying projections of the fiscal stance.

25. Discrepancies are marginal at the beginning of the sample period, but turn to be significant from 2006 onwards (Figure 3). For example, while the methodology used by the IMF and the BCRP suggest that a structural surplus is achieved by 2006–07, the MEF still estimates a structural deficit of around 1 percent of GDP.

Figure 3.
Figure 3.

Overall and Structural Balance

(Nonfinancial Public Sector, in percent of GDP)

Citation: IMF Staff Country Reports 2012, 027; 10.5089/9781463940423.002.A001

Figure 4.
Figure 4.

Fiscal Impulse

(Nonfinancial Public Sector, in percent of GDP)

Citation: IMF Staff Country Reports 2012, 027; 10.5089/9781463940423.002.A001

26. Discrepancies in terms of fiscal impulse are smaller (Figure 4). As discussed in the previous section, focusing on changes in structural measures (fiscal impulse) reduces the risks of an imprecise estimation of the level of trend output and commodity prices. Yet, in 2011 results vary significantly, mainly due to differences in the underlying fiscal projections.

27. The factors behind these discrepancies can be decomposed in three components: (i) adjustment for the impact of the business cycle; (ii) adjustment for the impact of changes in commodity prices; and (iii) one-off adjustments. For illustrative purposes, we present below such decomposition for the staff estimates in Table 2.

Table 1.

Comparison of Different Estimations of the Structural Balance

(Nonfinancial Public Sector, in percent of GDP)

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Sources: MEF, BCRP, and Fund’s estimates.

Projections.

Change in the structural balance (+ expansionary)

Table 2.

Staff Estimates of the Structural Balance

(Nonfinancial Public Sector, in percent of GDP)

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Sources: Fund’s estimates.

Projections for 2011-2013

Corresponds to advance accrual of expenditures in 2009 corresponding to 2010.

+ = expansionary.

Adjustment for the business cycle

28. Adjusting for the business cycle entails the following steps: (i) identifying the revenue base; (ii) estimating the elasticities; and (iii) estimating the output gap.

29. The revenue base for the business cycle adjustment is the non-commodity related revenues for the nonfinancial public sector. While theoretically the three methodologies use the same revenue base, in practice, differences exist. These differences derive from the definition of commodity-related revenues (see discussion below). None of the three methodologies adjusts spending for the impact of the business cycle.

30. Assessing the impact of the business cycle requires the use of elasticities to output gap. This can be achieved via an aggregated method (when elasticities are used to measure the sensitivity of total revenue and spending to the output gap), or via a disaggregated method (with elasticities specific to various revenue and spending components). For example, the BCRP estimates that the weighted average of the elasticities of the main revenue components is 1.09.5 The MEF uses a similar approach and arrives to similar results. IMF staff assumes revenue elasticity to output gap equal to one.6

31. Trend output estimates can take several forms. Two main groups include: (i) statistical filters based on the properties of the GDP time serie; and (ii) a model-based approach. In measuring output gaps, the staff uses a simple statistical procedure (i.e., the Hodrick-Prescott filter). The MEF uses an average of several methods (Table 3). The BCRP uses a production-function approach assuming that the country’s aggregate output can be modeled by a Cobb-Douglas function.7

Table 3.

Estimates of Potential GDP Growth

(Average real change)

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Sources: MEF estimates.

32. There are differences on the estimates of potential growth. The authorities use a potential GDP growth rate of 6.4 percent. This implies a considerable increase (twofold) relative to estimates for the period 1994–2002. While the MEF and the BCRP uses a potential growth rate of 6.4 percent, staff uses 6.0 percent. According to staff estimates, output gap would be close by end 2011 (Figure 5). Yet, the MEF and the BCRP estimates suggest that the output gap would be closed later, around 2013.

Figure 5.
Figure 5.

Output Gap

(In percent of potential GDP)

Citation: IMF Staff Country Reports 2012, 027; 10.5089/9781463940423.002.A001

33. The business cycle adjustment has been considerable in the last years. According to staff estimates, the adjustment for the business cycle reaches its peak in 2008 and 2009 (0.9 and -0.5, respectively), both purging revenues from the impact of the economic boom and the subsequent global financial crisis, respectively (Table 2).

Adjustment for commodity prices

34. Adjustments beyond the output gap are warranted when changes in commodity prices are significant, they have a temporary component, and they have a relevant impact in the overall balance. Commodity prices could rise temporarily because of surges in global demand. If the fiscal revenue derived from these sources is significant, an adjustment is needed to determine the underlying fiscal position.

35. The revenue base for this adjustment comprises commodity-related revenues of the general government, which are significant and have been increasing. Total revenues from the mining and oil sector are presented in Table 4. This includes both taxes and other revenues such as special contributions (i.e., cannon) and royalties.

36. There are differences in the revenue base used by each methodology. The MEF and the IMF adjustment is base on total revenues from the mining and oil sectors (both taxes and other revenues)8; whereas the BCRP only adjusts income taxes and other revenues. Moreover, the BCRP’s adjustment includes a correction to account for the fact that income taxes collected this year not only depend on current commodity prices, but also on prices of the previous year. This lag in revenue collection is not considered by the other two methodologies. In turn, these discrepancies have implications for the estimation of the adjustment for the business cycle, since non-commodity related revenues—the base for such adjustment—are calculated as residual.

37. Elasticities of commodity-related revenues to the price gap are other sources of discrepancies between methodologies. Following the same conservative approach as in the case of elasticities to output gap, staff assumes a unitary elasticity of revenues to changes in commodity prices. The MEF and the BCRP calculate such elasticity using econometric regressions that result in values significantly higher than one (e.g., close to 2 in the case of the BCRP).

38. Identifying deviations of commodity prices from their “norm” is a critical but slippery input when estimating structural balances. Standard filtering techniques used for arriving at the output gap may not be suitable for commodity prices. Given their high volatility, estimated trends may be influenced heavily by the sample chosen. Moreover, the fact that Peru exports multiple commodities (i.e., copper, gold, silver, zinc, lead, oil, among others) complicates the adjustment. In this regard, all three methodologies calculate a weighted commodity price index, based on the participation of each commodity in total commodity-related exports.

Table 4.

Commodity-related Revenues

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Sources: MoF, Sunat, and Funds estimates.

39. Alternatives approaches are used to estimate “benchmark” prices for relevant commodities. Benchmarks can be estimated using past and future information on prices. For example, the IMF methodology estimates long-term prices of commodities using a moving average of 8 periods (5 backwards and 3 forwards). The projection for the 3 periods ahead corresponds to the WEO estimations for each commodity. If projections are adequate, this method incorporates valuable information to assess the structural position. However, because WEO uses future contracts as base for forecast, current prices may be overrepresented and significant updates can occur. An alternative is to use prices that prevailed in the recent past. In this vein, the MEF and the BCRP estimate long-term commodity prices using the average of the last 10 years.9 Finally, guidance on specific benchmarks may also exist from independent experts (e.g., Chile’s independent copper price board sets a benchmark level for the long-run price of copper).

40. Results obtained for alternatives methods of estimating “benchmark” prices vary significantly. Figure 6 illustrates different benchmarks for copper prices.10 For example, in 2011 the moving average of 8 years seems to be the most optimist guess (based on WEO projections for 2012 to 2014)11, followed by the moving average of the last 5 years, and the Chilean reference price. The moving average of the last ten years—the alternative used by the MEF and BCRP—seems to be the most conservative approach, when prices are abnormally high, thus resulting in a higher adjustment in revenues, and therefore a lower structural balance. This partially explains the different structural results between methodologies for 2011.

Figure 6.
Figure 6.

Alternative Benchmarks for Copper Prices

Citation: IMF Staff Country Reports 2012, 027; 10.5089/9781463940423.002.A001

Other Adjustments

41. In the case of Peru, the impact of changes in oil prices on the expenditures may also need to be taken into account. The stabilization fund for the price of oil (i.e. Fondo de Estabilization del Precio de Combustible, FEPC) was introduced as a mechanism to smooth the impact of oil price volatility. When oil prices increase beyond a threshold, the authorities transfer resources from the budget to retail companies to compensate them for not being able to increase retail prices. On the contrary, when oil price goes below a threshold, retail companies should made transfers to the fund. Cash transfers to private companies—netted out of cash payments to public corporations—are recorded as government spending. The BCRP includes an adjustment for the impact of the FEPC on government spending (comprising accrued expenditures and not yet paid). Such concept accounted for adjustments to up 0.2 percentage points of GDP between 2007 and 2009, but has lost significance recently mainly due to the authorities efforts in aligning retail prices to international prices. Neither the MEF methodology, nor the IMF one incorporates such adjustment.

42. Finally, large, non-recurrent fiscal operations may distort the analysis of the underlying fiscal position and should be excluded from structural balance estimates. This adjustment should be carried out before proceeding to any form of adjustment to avoid biased elasticity estimates and ensure correct identification of the cyclical component. In the case of Peru, such an adjustment is related to accrued expenditures recorded in 2009 but that corresponds to 2010, which accounts for 0.4 percentage points of GDP (see Table 2). Both staff’s and MEF’s methodologies include this adjustment, while the BCRP’s estimate of these transactions is smaller.

D. Main Challenges and Recommendations

43. There is space to formalize a more robust fiscal framework. While maintaining public finances on a sustainable path, fiscal policy could allow for further output smoothing and promote savings to cushion against adverse shocks and long-term risks.

44. To achieve such objective the current fiscal framework could be strengthened by: (i) incorporating discretional changes in taxes within the framework; (ii) applying spending caps on a more consistent way, covering total primary spending of general government; and (iii) refining exceptional clauses to make them more clear and timely.

45. While the authorities are already working on some of these areas, and improvements have been significant, further refinements could be considered. Extending the coverage of the spending cap to total primary expenditures would add teeth to the rule, and seems a step in the right direction given the level achieved in capital spending. Similarly, extending the institutional coverage of the cap to general government would improve spending control, even though its implementation may be politically challenging. Exceptional clauses could be enhanced by better specifying the extraordinary circumstances activating them to allow for a timely response. This could be achieved, for example, by better defining the conditions of an economic crisis looking forward, instead of the current backward looking version of the clause. Similarly, the type of shocks that would call for policy action could be clearly stated (e.g., a severe earthquake) together with their minimum related fiscal cost.

46. In turn, there is a need to gradually introduce structural measures in the policy discussion as an additional instrument to help anchor medium-term fiscal policy. This would help to avoid procyclicality by building up political support to target fiscal balances aligned with medium-term fiscal policy objectives. Yet, benefits of this approach should be carefully evaluated against implementation challenges.

47. Structural measures should be calibrated with caution. As discussed in previous sections, structural measures are sensitive to changes in main parameters and revisions of estimated trends of main macro variables. While differences in MEF, BCRP and IMF methodologies can be broadly justified and reconciled, there is scope for better understanding what these various methodologies do and how they can be refined and extended.

48. To maximize their potential gains, structural measures should be introduced and used in a transparent way. To prevent unnecessary debate regarding some factors entailed in the computation of these measures, it is particularly important to have transparency in estimation procedures. In this regard, there is a need to refining and harmonizing official estimates of the structural position of the public sector disseminated by the MEF and the BCRP. The authorities have taken steps in such direction.

References

  • BCRP, 2008, “Metodología de Cálculo del Resultado Estructural”, Nota de Estudios del BCRP No. 51, September 2008, BCRP.

  • IMF, 2011, “When and How to Adjust Beyond the Business Cycle? A Guide to Structural Fiscal Balances’”, Technical Notes and Manuals, Fiscal Affairs Department, IMF, 2011.

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  • Girouard, Nathalie, and Christophe Andre, 2005, “Measuring Cyclically Adjusted Budget Balances for OECD Countries,OECD Economic Department, Working Paper No. 434 (Paris: OECD).

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  • Montoso, Carlos and Moreno, Eduardo, Reglas Fiscales y la Volatilidad del Producto”, Estudios Económicos, BCRP.

  • Orphanides, Athanasios, and Simon Van Norden, 2002, “The Unreliability of Output Gap Estimates in Real-time,Review of Economics and Statistics, Vol. 84, No. 4 (November), pp. 56983 (Cambridge, Massachusetts: MIT Press).

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1

Prepared by Isabel Rial (FAD).

3

In Peru, expenditures are also affected due to the Fondo de Estabilizacion del Precio de Combustible.

4

These areas include: (i) the budgetary process; (ii) the financial management information system; and (iii) treasury management.

5

BCRP, 2008. Elasticities are estimated econometrically for each main type of revenues of the general government.

6

Empirical evidence points to aggregated one-zero elasticity assumptions (for revenue and spending, respectively) as being a good approximation of the weighted average of disaggregated elasticity estimates (Girouard and Andre, 2005).

7

BCRP, 2008, Appendix 1.

8

Source data corresponds to estimates of tax collections by sectors of the economy published by the SUNAT. These estimates comprise all taxes: income tax, VAT, excise taxes, etc.

9

The BCRP used to estimate long-term commodity prices as the average of the last 20 years; while, the MEF used an average of the last 5 years. Recently, the two converged to an average of the last 10 years.

10

The same smoothing techniques are applied to the rest of export commodity prices.

11

As of WEO estimates of September 2011.

Peru: Selected Issues Paper
Author: International Monetary Fund