Despite three decades of economic growth, Peru’s tax-to-GDP ratio remains low and not has not increased, fluctuating instead within a relatively narrow band of 15-19%. To bring Peru’s tax-to-GDP ratio onto a convergence path with LAC and OECD countries, it is necessary to improve tax buoyancy, which measures the translation of economic growth into tax revenue growth. This chapter’s analysis decomposes tax buoyancy by tax and by economic sector to indicate potential areas for reform. Additionally, mineral prices appear to introduce significant volatility into Peru’s tax-to-GDP ratio, and this chapter proposes strategies to better manage this volatility.
OECD Tax Policy Reviews: Peru 2026
Abstract
Peru has not been successful in translating its economic growth into higher tax revenues as a percentage of GDP. Since the early 2000s, GDP per capita in constant prices has more than doubled; however, the tax-to-GDP ratio has not exhibited a sustained upward trend, instead fluctuating within a 15% to 19% range (World Bank, 2024[1]; OECD, 2025[2]).1 Reflecting the weak long-run relationship between economic growth and tax revenue growth, Peru’s tax-to-GDP ratio is not on a trajectory to converge towards the current averages observed in LAC and the OECD.
Variations in the tax-to-GDP ratio appear to be more strongly associated with movements in mineral prices than with changes in the rate of economic growth, resulting in revenue volatility rather than sustained increases in the tax-to-GDP ratio over time. In Peru, tax buoyancy2 fluctuated above and below unity in line with changes in mineral prices, particularly the price of copper (see Figures 1.4 and 1.5 in Chapter 1). Over the past two decades, increases in the tax-to-GDP ratio have largely coincided with periods of rising copper prices, while subsequent declines in prices have reversed these gains. Between 2002 and 2014, the tax-to-GDP ratio rose from 15% to 19% alongside an 80% increase in GDP per capita in constant prices. This coincided with a period of rising copper prices. However, as copper prices fell over the next 3 years, the tax-to-GDP ratio fell back to the 15% level of 2002 despite continuing economic growth. The 2014 peak in the tax-to-GDP ratio was not exceeded until copper prices rose again in 2021 and 2022; and even then, only temporarily, with the tax-to-GDP ratio dropping to the 16-17% range in 2023 and 2024 (OECD, 2025[2]; World Bank, 2024[1]). In a counterfactual scenario in which long‑run tax buoyancy had not fallen below unity during the mid‑2010s mineral price downturn, Peru’s tax-to-GDP ratio would have been persistently higher. All else equal, it is estimated that the ratio could have been approximately 3.7 percentage points higher, reaching 22.8% in 2022, thereby exceeding the LAC average3 (OECD et al., 2025[3]).
The short-run volatility of Peru’s tax-to-GDP ratio associated with fluctuations in copper prices does not imply that the tax system functions as an automatic stabiliser. In general, tax revenues that fall proportionally more than GDP during economic downturns can act as automatic stabilisers. By contrast, tax revenue declines linked to lower mineral prices do not appear to stabilise economic activity in Peru to the same extent. First, episodes of low mineral prices have generally not been associated with economic contractions, as GDP growth has remained positive, supported by activity in non‑extractive sectors. Second, reductions in tax liabilities stemming from lower mineral prices are likely to be concentrated on the profits of mining companies, which operate largely as price takers in international markets. As a result, lower tax payments by the mining sector during price downturns do not appear to translate into higher domestic demand or additional economic activity when mineral prices are weak.
The positive impact of mineral price increases on tax buoyancy appears to have weakened in recent years. Despite mineral prices remaining at historically high levels, overall tax buoyancy declined to around unity over the period 2023-2024 (see Chapter 1, Figure 1.3). This development suggests that elevated mineral prices may no longer be sufficient to temporarily offset broader structural weaknesses in the transmission of economic growth into sustained revenue growth even during periods of high mineral prices (see also the sectoral tax analysis below). Whether this trend has continued in 2025 and 2026 remains to be seen, but it is an observation that requires the attention of policymakers in Peru.
Insufficient tax buoyancy in the non‑extractive economy represents a key factor underlying the long‑term stagnation of Peru’s tax-to-GDP ratio. While it is common for resource‑exporting economies to experience cyclical fluctuations in tax revenues in response to changes in commodity prices, such cycles would ideally occur around an upward long‑term trend in the tax-to-GDP ratio. In Peru, weak revenue responsiveness in the non‑extractive economy has limited the extent to which overall tax revenues have risen in line with long‑term economic growth.
Managing the volatility of mining-related tax revenue, given its central role in financing subnational public investment, is key to supporting stable economic growth and strengthening the tax-to-GDP ratio. Volatility that weakens the translation of sustained economic growth into stable revenue growth, driven by international mineral price movements, can undermine medium‑ and long‑term public investment planning and execution. The need for revenue stability is particularly acute in Peru, where a substantial share of mineral‑related revenues is earmarked for subnational governments to finance public investment. In this context, the volatility of mineral revenues may contribute to investment projects being postponed or cancelled, particularly those with long planning horizons. Alternatively, local governments may prioritise smaller public investment projects. Nevertheless, mineral revenue volatility is just one possible cause of weak public investment by sub-central governments. Limited capacity and institutional constraints are other factors that may contribute to public investment having a low impact.
The buoyancy analysis points at sector‑ and tax‑specific weaknesses in the transmission of economic growth into tax revenue growth. By examining buoyancy by sector and by tax type (see Box 2.1), the analysis highlights interactions between the tax system and the structure of the economy that contribute to Peru’s long run tax buoyancy below 1 and to volatility in the tax-to-GDP ratio. These findings inform policy options to strengthen the long‑run responsiveness of revenues to growth and to better manage downside volatility linked to mineral price fluctuations.
Potential strategies to enhance fiscal resilience could include strengthening the taxation of the tourism and agro‑export sectors. The agro‑export and tourism sectors currently contribute relatively little in tax revenue, accounting for approximately 3% and 6% of their value added, respectively, compared with an economy‑wide average of around 17% (Figure 2.7). This gap reflects a combination of factors, including sector informality and the tax incentives that these sectors benefit from, profit margins and the fact that, in particular the agro-export sector, is export oriented which implies that their sales are zero-rated for VAT. Nonetheless, there appears to be scope to increase tax revenues from these sectors by rationalising TEs and strengthening the formalisation of these sectors. Strengthening taxation in these fast‑growing sectors would help ensure that ongoing economic expansion is accompanied by commensurate growth in tax revenues. Moreover, as the drivers of growth in agro‑exports and tourism appear largely uncorrelated with mineral prices (Figure 2.10. ), enhanced revenue mobilisation in these sectors could help offset mineral‑related revenue volatility.
An important element of a strategy to increase the tax-to-GDP ratio over time, while safeguarding economic growth, would be identifying and addressing the structural factors underpinning low long-run tax revenue buoyancy in the main domestic sectors; namely services, manufacturing, and commerce. Together, these sectors account for approximately 57% of GDP, but they have long‑run buoyancy ratios close to or below one (Figure 2.7 and Figure 2.8.), which indicates that tax revenues have at most kept pace with underlying economic growth. The weak tax revenue responsiveness of these sectors is closely linked to high levels of informality and tax non‑compliance. In this context, policies that promote formalisation, such as strengthened enforcement and improvements in the coverage and quality of social protection, could help to broaden the tax base and improve revenue performance without undermining growth dynamics.
Strengthening the long-run relationship between economic growth and revenue mobilisation would require addressing structural constraints across all main tax types, including the CIT, VAT, PIT and SSCs. Despite approximately 16 years of robust economic growth, revenues from each of these taxes, expressed as a share of GDP, have remained broadly unchanged over time: PIT and SSC revenues have been largely flat, while CIT and VAT revenues have fluctuated within relatively narrow bands of around 3-5% and 6-7% of GDP, respectively (Figure 2.2. ) As a result, the contribution of each major tax to GDP in 2023 is broadly comparable to that observed in 2007, implying long-run buoyancy close to unity for each tax type (Figure 2.1). This pattern indicates that the persistent stagnation of the tax-to-GDP ratio in Peru reflects economy-wide challenges affecting all major taxes, rather than weaknesses confined to any single revenue source, and that it is more structural than just a revenue challenge with respect to mineral resources.
Broadening the PIT base and strengthening PIT progressivity would contribute to increasing tax buoyancy. PIT revenues have remained at around 2% of GDP since 2012 (Figure 2.2. ), despite sustained growth in income per capita (see Chapter 1). Under a progressive PIT system, PIT revenues would be expected to grow more rapidly than aggregate income, which can provide an important source of endogenous tax buoyancy (if tax rate brackets are adjusted by less than nominal income growth, for example only by inflation). While Peru’s schedular PIT applies a progressive rate structure to labour income, different types of capital income are taxed separately at a low flat rate. Enhancing the progressivity of the PIT, including through reforms to the taxation of capital income, could strengthen revenue buoyancy (see Chapter 5). These design reforms could be complemented by strengthened enforcement to improve capital income tax compliance. The buoyancy of the PIT is further constrained by its narrow tax base, reflecting both high levels of labour informality and a large standard tax allowance that applies to labour income. Strengthening the buoyancy of the PIT would require a reduction in the standard tax allowance, alongside the prioritisation of a whole‑of‑government approach to reducing labour informality (see Chapter 1).
Tax base protection measures could reduce revenue volatility of the mineral sector. Tax base protection measures would include rules that limit the ability of firms to offset losses from one project with the profits of another project. These measures can be designed to address broader base erosion and profit shifting (BEPS) risks, which are often pronounced in extractive industries due to their capital intensity, use of complex corporate structures, and exposure to international transactions. Without adequate safeguards, multinational firms may shift profits across jurisdictions through transfer pricing practices, intra-group financing, or the strategic allocation of costs, further increasing revenue volatility and reducing the effective tax contribution of the sector. To mitigate these risks, governments can complement loss ring-fencing rules with targeted BEPS countermeasures, such as strengthening transfer pricing regulations, introducing thin capitalization or earnings-stripping rules, and enhancing transparency through country-by-country reporting and beneficial ownership disclosure.
There is a positive correlation between VAT revenues and mineral prices (Figure 2.1 and Figure 2.2. ). While VAT receipts are notably less volatile than CIT revenues, they nonetheless appear to increase with higher mineral prices. From a conceptual perspective, this relationship is not straightforward, as VAT levied on mineral outputs destined for export is, in principle, refunded4, implying that higher mineral prices should not mechanically translate into higher net VAT revenues. The positive correlation observed may therefore reflect indirect transmission channels rather than direct taxation effects. Several hypotheses could be explored in this regard. These include spillovers from the mineral sector to non‑extractive activities that are subject to VAT, changes in VAT compliance behaviour such as variations in refund claims or evasion patterns along supply chains linked to mining, and demand-side effects, including higher private consumption associated with increased profit distribution and increased employment during periods of elevated mineral prices. In addition, pro-cyclical public expenditure financed by higher mineral-related revenues may raise aggregate consumption and, in turn, VAT receipts. Further empirical analysis would be required to assess the relevance and relative importance of these potential channels.
Note: The tax buoyancy indicator is defined as the five-year moving average (lagged) of the annual tax buoyancy indicators. In order to exclude the impact of one-off events such as the 2009 great recession, the value for the year 2009 is omitted and replaced with an average of the surrounding years.
Source: OECD Revenue Statistics, London Metal Exchange.
Source: OECD Revenue Statistics.
Calculation of sectoral tax revenue across all tax types
Tax revenues across all major tax types, including CIT, royalites and certain mining taxes, PIT, SSCs, excises and VAT, can be allocated by economic sector using industry classification data provided by Peru’s tax administration (SUNAT). The tax revenue data across economic sectors does not include revenues from recurrent taxes on immovable property, local taxes, taxes on rental income and capital gains reported by natural persons who do not carry out a business activity.
PIT and SSCs are withheld and remitted on behalf of the employee by the firm and classified according to the firm’s industry code. The self-employed are also assigned to a particular industry, and their PIT and SSC payments are categorised accordingly. In addition, VAT payments and VAT refunds are classified by industry code of the firm remitting VAT or receiving refunds. This enables the calculation of total tax revenues contributed by each economic sector to the central government across all tax types, net of refunds.
Tax revenue by economic sector from internal taxes was downloaded from Cuadro A6 from the SUNAT’s statistics, and supplemented with data on refunds, SSCs, and import taxes by economic sector provided by SUNAT. A number of caveats need to be considered. First, taxpayers who operate across multiple industries are classified under a single industry category, typically the industry in which the business earns the largest share of its income. Second, taxpayers whose activities evolve over time might not promptly update their industry classification with SUNAT. Third, the datasets reflect taxes paid rather than tax liability accrued.
Ratio of sectoral tax to sectoral value added
Definition
The sum of revenues across tax types within a particular sector can be expressed as a percentage of that sector’s value-added. Note that value-added includes both salaries and profits and is the difference between output and intermediate consumption. When this ratio is calculated for each economic sector, the weighted average of the different ratios per sector (applying weights calculated as each sector’s value-added as a share of Peru’s GDP) equals the national tax-to-GDP ratio.
Interpretation
The sectoral tax revenues to sectoral value-added statistic can be used to compare the tax revenue collected across economic sectors in a particular year or within an economic sector across years. Further, the ratio informs how tax collection from different sectors is affecting the national tax-to-GDP ratio, and what implications shifts in the sectoral composition of the economy will have on the evolution of the tax-to-GDP ratio over time.
Buoyancy by sector
Definition
The concept of tax buoyancy is typically applied at the national level, but it can also be applied at the sectoral level using the ratio of annual changes over time in sectoral tax revenue to changes over time in sectoral value-added. Tax buoyancy can also be calculated by sector within a particular tax type. For instance, the CIT buoyancy of a particular sector is calculated as the annual change in CIT revenues paid by that sector divided by the annual change in the sector’s value-added.
Interpretation
This ratio can be interpreted as the degree to which the tax system is effective at translating value-added growth in a particular sector into tax revenue growth. A sectoral buoyancy ratio greater than 1 indicates that tax revenue across a particular tax or the sum of all tax types is growing faster than a sector’s value-added. Sectors with high sectoral tax buoyancy may nevertheless make only a limited contribution to aggregate tax buoyancy when their economic weight is small.
Ratio of sectoral tax to national GDP
Definition
For each economic sector, the sum of tax revenues across all tax types can be expressed as a share of national GDP. When calculated on this basis for all sectors, the sum of these sectoral shares corresponds to the national tax-to-GDP ratio.
Interpretation
The ratio of sectoral tax revenues to (national) GDP does not control for differences in sector size. As such, it does not measure the intensity of taxation within a sector, but rather the contribution of each sector to the total tax-to-GDP ratio. This measure is therefore particularly informative for decomposing changes over time in the national tax-to-GDP ratio into sectoral components. Notably, a sector with a relatively small share of value added may simultaneously exhibit a high ratio of tax revenues to sectoral value added and a low contribution to the tax-to-GDP ratio.
Caveat with respect to the incidence of the VAT
Note that the sectoral tax revenue numbers reflect VAT remittance but not VAT incidence. In other words, VAT is attributed to the remitting economic sector, while the VAT incidence ultimately falls on final consumers.
The sectoral tax revenue to sectoral value-added ratio will depend on a wide range of factors that might affect tax collection in a given sector. These include not only the design of the tax system, but also the role of businesses in that sector as withholding agents, the degree of non-compliance, the level of informal activity, etc. As a result, the ratio of sectoral tax revenue to sectoral value-added should be interpreted with caution when it is used to infer the tax burden borne by a particular sector. For instance, the comparatively high tax to sectoral value-added ratio of the commerce sector is biased upwards as the sector collects VAT that is ultimately paid by final consumers. Hence, this ratio is not a reliable proxy for the tax burden on the commerce sector.
For the minerals, tourism, and agriculture sectors, the design of the VAT has an impact on the sectoral tax to sectoral value-added ratios. For the agricultural sector (particularly crop production), both outputs and inputs benefit from a VAT exemption, which keeps the ratio low. As the tourism sector predominantly provides services to final consumers, the VAT it collects is borne by final consumers and not the tourism sector itself. As a result, the sectoral tax revenue paid by the tourism sector overstates the effective tax burden borne by the sector.
Non-mineral sector CIT liabilities are positively correlated with mineral prices
The volatility of mineral prices results in volatility in CIT paid by the non-extractive sector. Although less sensitive than mining-sector CIT, the buoyancy of CIT revenues collected from non‑extractive activities, which account for at least around two-thirds of total CIT receipts (Figure 2.3. ), also appears to co-move with mineral prices. This pattern extends beyond CIT alone. When all tax types are considered jointly, total tax buoyancy in the non-extractive sector tends to fall below one during periods of declining copper prices, while exceeding one during periods of elevated mineral prices and stronger revenue performance in the extractive sector (Figure 2.4. ). These correlations may reflect indirect linkages between the mineral sector and the broader economy. In particular, periods of high mineral prices may generate positive spillover effects for non‑extractive activities, including increased demand for intermediate inputs such as transport services, manufactured equipment and financial services, as well as geographic spillovers benefiting service providers located near mining operations. Further analysis would be useful to better understand the magnitude and transmission mechanisms of these spillovers, and their implications for revenue volatility across the tax base.
Recent evidence suggests an emerging weakening in the relationship between mineral price upswings and tax revenue buoyancy that extends beyond the extractive sector, raising a number of hypotheses that could be examined in future analytical work. One possible explanation is that the nature of economic linkages between the mineral sector and non‑extractive activities has evolved, such that growth in the extractive sector no longer translates as strongly into an expanding tax base elsewhere in the economy. Developments in formalisation may be particularly relevant in this context. During the period of elevated copper prices in the early 2010s, labour informality and VAT non‑compliance in the non‑extractive economy declined steadily, whereas more recent periods of high mineral prices have not been accompanied by similar improvements in compliance indicators (see Chapter 1). Further in‑depth analysis would be needed to assess these potential explanations and to better understand the changing transmission mechanisms between mineral price cycles, economic activity and tax revenue buoyancy.
Note: The numerator is the CIT revenue collected from each sector, while the denominator is the GDP of Peru, see scale on left hand side. The scale on the right-hand side displays copper prices. Mining royalties are added to the mining CIT.
Source: Sunat, London Metals Exchange, Central Bank of Peru.
Note: Buoyancy is computed in 5-year lagging averages, representing the ratio of annual sectoral tax revenue growth to annual sectoral value-added growth averaged over 5 years. The left-hand axis displays the buoyancy ratio. The right-hand axis is the price of copper. All major tax types are included, specifically, PIT, CIT, SSCs, VAT, and Excises. Mining royalties are also included. See Box 2.1 for methodological details.
Source: SUNAT, London Metals Exchange, Central Bank of Peru.
The ratio of tax revenues to sectoral value added in the mining sector has declined markedly over time and is now low by historical standards. While value added in the mining sector has more than doubled since 2011, tax revenues from the sector have remained broadly stagnant. As a result, the share of sectoral value added collected in taxes has fallen by more than half over this period (Figure 2.7). In the early 2010s, the mining sector contributed a higher proportion of its value added in tax revenues, around 22-23%, than the non‑extractive economy, which averaged around 20%. By contrast, in 2023 and 2024, the tax‑to‑value‑added ratio in the mining sector had declined to around 10%, compared with approximately 19% in the non‑extractive economy, despite historically high mineral prices (Figure 2.7). This decline has important implications for aggregate revenue mobilisation. Illustratively, if the mining sector had contributed the same share of its value added in taxes in 2024 as it did in 2011, Peru’s overall tax‑to‑GDP ratio would have been approximately 1.4 percentage points higher - an amount equivalent to nearly half of the fiscal deficit recorded in that year (Figure 2.6.) (Ministry of Economy and Finances of Peru, 2025[4]). If current trends persist, continued expansion of the mineral sector will not contribute to increasing the tax‑to‑GDP ratio over time. This development underscores the importance of examining the drivers of the low effective tax burden in the mining sector and assessing whether current tax policy and administrative settings remain aligned with the sector’s capacity to contribute to public finances over the commodity price cycle, as discussed in the mining subsection of Chapter 1.
Note: The graph decomposes the national tax to GDP ratio into its sectoral components. CIT, VAT, Excises, PIT, SSCs, and mining royalties are all included, but recurrent local property taxes excluded, see Box 2.1 for methodological details. Commerce denotes wholesale and retail trade.
Source: SUNAT, Central Bank of Peru.
Note: Each yellow diamond represents the net annual shift in the tax-to-GDP ratio, equal to the sum of all of the coloured bars in its year, which decompose the annual change in national tax-to-GDP by sector. For instance, in 2023, the tax-to-GDP ratio decreased by two percentage points (from 19% to 17%), and approximately half of this decrease (a full percentage point) was due to reduced tax collection from the mining sector. Each sector’s contribution to the annual change in national tax-to-GDP is equal to the annual change in that sector’s ratio of sectoral tax to national GDP. In this ratio, the numerator sums sectoral tax revenue across all tax types (SSCs, CIT, PIT, VAT, excise taxes) and the denominator is national GDP. Mining royalties are included in tax revenues. The vertical axis shows the change in national GDP, expressed in percentage points. The “net change” bars on the right sum the displayed annual changes across the denoted span of years, decomposing the net change in tax to national GDP across the timespan into the amount attributable to each sector. Note that mining royalties are included; see Box 2.1 for further methodological details.
Source: SUNAT, Central Bank of Peru.
Note: The percentages written in the data labels display the sectoral tax to sectoral value-added ratio across all tax types in 2024, indicating the relative burden of the tax system on each sector. The sizes of the dots are scaled to the sectoral tax to sectoral value-added ratios for 2024. The graph displays the sectoral tax revenue growth (y axis) across all tax types (including VAT, CIT, SSCs, PIT, excises, and mining royalties as well as other special mining taxes, see Box 2.1 for methodology) and the sectoral value-added growth (x axis) within each sector of the economy, during the period of 2011 to 2024. Sectors towards the upper left of the graph are those where tax revenue grew faster than value-added between 2011 and 2024 (i.e. buoyancy greater than 1), while sectors towards the bottom right are those where tax revenue grew slower than value-added between 2011 and 2024 (i.e. buoyancy less than 1). See Box 2.1 for further methodological details. Note that tax revenue for the mining sector also includes royalties, even though the OECD revenue statistics database does not consider them tax revenues.
Source: SUNAT, Central Bank of Peru.
Manufacturing, services and commerce currently display sectoral tax-to-value added ratios that are above the economy-wide tax-to-GDP ratio, which implies that if these sectors continue to grow, they will support a gradual increase in the tax-to-GDP ratio. In 2024, the tax burden in manufacturing, services and commerce amounted to approximately 22%, 20% and 33% of sectoral value added, respectively5, exceeding the national tax-to-GDP ratio (Figure 2.7). The manufacturing, services, and commerce sectors grew by 80%, 150% and 130%, respectively, in current prices, and their tax-to-value-added ratios have remained roughly unchanged. This suggests that continued growth in these sectors would support an increase in the tax-to-GDP ratio in line with these sectors’ tax ratio. Any further increase in the taxes paid by these sectors would also increase the tax-to-GDP ratio over time. As these sectors together account for 57% of GDP in 2024 and are expected to continue growing, raising their long-run tax buoyancy could be a key component of a strategy to increase Peru's overall tax-to-GDP ratio over time (Figure 2.8.).
Note: The chart situates each sector according to its share of total tax revenue in Peru (y axis) and its share of Peru’s total GDP (x axis), as of 2024. Sectors above the diagonal line contribute a higher percentage of Peru’s total tax revenue than their share in Peru’s total GDP. Sectors below the diagonal line contribute a lower percentage of Peru’s total tax revenue than their share in Peru’s total GDP. Tax revenue across tax types (CIT, PIT, VAT, SSCs, and excises) is attributed to each sector according to the methodology explained in Box 2.1. Royalties and other special taxes are included in mining sector tax revenue.
Source: SUNAT, Central Bank of Peru
Strengthening the taxation of the tourism and agro-export sectors could contribute to increasing Peru’s tax-to-GDP ratio in the long run
The agriculture and tourism sectors exhibit relatively high revenue buoyancy, but they continue to make only a limited contribution to overall tax revenues. Since 2011, value added in agriculture and tourism has grown by approximately 150% and 180% in current prices, respectively, among the fastest growth rates across economic sectors in Peru. Over the same period, tax revenues from these sectors have increased at a faster pace than sectoral output, particularly in agriculture, resulting in buoyancy well above unity (Figure 2.7). Despite this strong revenue responsiveness, the impact on aggregate revenue mobilisation has remained modest, reflecting the low starting ratio of tax paid to value added. In 2011, agriculture and tourism contributed only around 2% and 5% of their respective value added in taxes. In 2024, agriculture and tourism accounted for approximately 7% and 4% of GDP, respectively (Figure 2.8.), yet each generated tax revenues equivalent to only around 0.25% of GDP. This corresponds to sectoral tax‑to‑value‑added ratios of roughly 3% in agriculture and 6% in tourism. Significantly higher increases in these ratios will be required in order for the growth in the tourism and agro-export sector to support an increase in the overall tax‑to‑GDP ratio (Figure 2.5. and Figure 2.7).
The limited contribution of the agriculture and tourism sectors to overall tax revenues reflects a combination of structural and tax policy-related factors, including high levels of informality, low productivity, and the presence of generous TEs. In the tourism sector, labour and business informality remains widespread, constraining the tax base. In addition, the application of a reduced VAT rate results in forgone revenues from formal tourism operators that otherwise exhibit taxable capacity. In agriculture, family farming and small‑scale producers continue to account for a substantial share of sectoral value added, yet these activities are characterised by low productivity, very high informality, and limited capacity to pay taxes. At the same time, the analysis suggests that large and rapidly expanding agro‑export firms display significantly higher productivity and profitability, and therefore a greater ability to pay tax. However, a range of sector‑specific TEs limits effective revenue mobilisation from these firms. This indicates scope to reassess the design and targeting of TEs in the agro‑export segment to better align taxation with taxable capacity, as discussed further in Chapter 3.
Recent growth in agricultural value added has been driven predominantly by large, highly productive agro‑exporting firms. Between 2011 and 2024, the value of agricultural exports increased by approximately 363%, with large enterprises accounting for around 98.5% of this expansion.6 By 2024, close to 95% of total agricultural exports originated from large companies (exceeding 2 300 UIT in annual turnover) operating in the crop subsector, rather than in livestock or forestry. Despite these developments, the net contribution of the crop subsector to the tax system has been negative in five of the past six years (Figure 2.9. ). This stands in contrast to the rapid growth and increasing economic weight of the subsector. By comparison, livestock and forestry appear to account for most of the observed buoyancy in aggregate agricultural tax revenues, despite much lower export intensities (approximately 0.1% and 4% of value added, respectively) and more modest growth in value added. The high export orientation of the crop subsector, combined with the refund mechanism inherent in the VAT system, mechanically limits its net VAT contribution. However, after more than a decade of sustained expansion, amounting to over 180% growth in value added since 2011, largely driven by large‑scale agro‑exporters, the crop subsector appears to exhibit a level of profitability and scale that indicates that the sector could pay a higher share of taxes than it currently does. An assessment of the tax treatment and effective taxation of large agro‑export firms, with a view to assessing whether current policy settings remain consistent with their taxable capacity, is left for further work.
Note: Each dot represents an annual point-in-time snapshot of the cumulative value-added growth in each subsector since 2011 (x axis) and of the annual sectoral tax to sectoral value-added ratio (y axis). See Box 2.1 for methodological details. Note that revenue from social security contributions is omitted here. The largest dots in each subsector’s line represent the 2024 values; each subsector’s line traces the annual dots for that subsector in chronological order from 2011-2024. Dots in the bottom left of the graph represent point in time snapshots of subsectors with little value-added growth (since 2011) and a very low sectoral tax to sectoral value-added ratio. Dots in the bottom right of the graph represent point-in-time snapshots of subsectors with relatively high sectoral value-added growth, but a very low sectoral tax to sectoral value-added ratio. Dots in the top left represent point-in-time snapshots of subsectors with a comparatively higher sectoral tax to sectoral value-added ratio, but very low cumulative value-added growth.
Source: SUNAT, Central Bank of Peru.
The agriculture and tourism sectors tend to exhibit comparatively higher revenue buoyancy during periods of low mineral prices. As the main drivers of agricultural output are relatively weakly correlated with developments in international mineral markets, the agricultural sector frequently records higher buoyancy than other sectors during periods of low copper prices (Figure 2.10. ), as observed, for example, in 2016 and 2018. A similar pattern is apparent in the tourism sector, where growth is largely influenced by trends in international travel and tourist departures, which are likewise not closely linked to mineral price dynamics. As a result, tourism revenues tend to display relatively strong buoyancy in years when mineral‑related revenues decline, often remaining at or above unity while buoyancy in other sectors falls below this threshold (Figure 2.10. ). Nevertheless, despite the stronger buoyancy in these sectors, they are subject to relatively low tax collection as a share of value added, meaning their growth does not translate into an upward pressure on the tax-to-GDP ratio.
Note: Buoyancy is calculated as 5-year moving average (lagged) of the ratio of annual change in total sectoral tax revenue to annual change in sectoral value-added. CIT, VAT, PIT, SSCs, excise taxes, and mining royalties are included in the total sectoral tax revenue, see Box 2.1 for methodological details.
Source: SUNAT, Central bank of Peru.
Over time, the agriculture and tourism sectors have the potential to match and eventually exceed the tax revenue contribution of the mineral sector. By 2024, combined value added in agriculture and tourism had already surpassed that of the extractive sector, and both activities are projected to continue expanding at a faster pace than mining. This underscores the potential role of these sectors in supporting medium‑term revenue mobilisation, provided that policy and administrative reforms strengthen their effective contribution to the tax system. By contrast, measures that further increase the generosity of tax benefits for agro‑exporters and tourism‑related activities, against the backdrop of already low sectoral tax‑to‑value‑added ratios, would run counter to the objective of broadening the tax base and increasing overall tax revenues.
References
[6] INEI (2022), Producción y Empleo Informal en el Perú: Cuenta Satélite de la Economía Informal 2007–2021, Instituto Nacional de Estadística e Informática, Lima, Perú, https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1878/libro.pdf.
[4] Ministry of Economy and Finances of Peru (2025), Marco Macroeconomic Multianual, MEF, Lima, https://cdn.www.gob.pe/uploads/document/file/8563935/7091414-marco-macroeconomico-multianual-2026-2029.pdf?v=1756399214 (accessed on 24 April 2026).
[2] OECD (2025), Global Revenue Statistics Database, OECD Publishing, https://www.oecd.org/en/data/datasets/global-revenue-statistics-database.html (accessed on 27 April 2026).
[3] OECD et al. (2025), Revenue Statistics in Latin America and the Caribbean 2025, OECD Publishing, Paris, https://doi.org/10.1787/7594fbdd-en.
[5] SUNAT (2026), Estadísticas y estudios, https://www.sunat.gob.pe/estadisticasestudios/ (accessed on 27 April 2026).
[1] World Bank (2024), GDP per capita (constant LCU) | Data, https://data.worldbank.org/indicator/NY.GDP.PCAP.KN (accessed on 27 April 2026).
← 1. If informal economic activity is not fully captured in the GDP estimates, the true tax-to-GDP ratio would be lower than the estimates quoted in this report. Currently, 18% of GDP is estimated to be informal (INEI, 2022[6]).
← 2. Tax buoyancy measures the extent to which economic growth translates into tax revenue growth. Tax buoyancy is defined as the ratio of tax revenue growth to GDP growth. To increase the tax-to-GDP ratio, Peru would need to achieve a tax buoyancy ratio greater than 1 over time.
← 3. Between 2014 and 2017, the tax-to-GDP ratio of Peru declined by 3.7 percentage points, according to OECD Revenue Statistics, and did not surpass its 2017 level until 2022. Aside from a one-year drop in tax-to-GDP associated with the 2009 great recession, this was the first sustained significant drop in Peru’s tax-to-GDP since 2000. The 22.8% potential figure for 2022 comes from adding 3.7 percentage points to the recorded tax-to-GDP ratio of 19.1% of 2022. The LAC average tax-to-GDP ratio was 21.5% in 2022 (OECD et al., 2025[3]).
← 4. Note that the VAT revenue displayed in the figures reflects collections minus refunds.
← 5. Note that the commerce tax to sectoral value-added ratio is elevated because of how final VAT collected from end-consumers is attributed to the retail subsector even though in practice it is paid by end consumers.
← 6. See “SUNAT Estadisticas Cuadro G1: Exportacion Definitiva por Sector Economico” (SUNAT, 2026[5]).