## Unpacking Macroeconomic Impacts of Climate Events and Policy Implications in the Philippines

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### A. Introduction
- The Philippines is highly exposed to natural hazards intensified by climate change: stronger typhoons, heavier rainfall, higher temperatures, and rising sea levels.
- World Bank cumulative cost estimates: 7.6 percent of GDP by 2030; 13.6 percent by 2040.
- Climate resilience embedded in national plans: Development Plan (PDP 2023-2028) and National Adaptation Plan (NAP 2023-2050), aligned with SDG 13 (targets 13.1 and 13.2).

### B. Climate trends and typhoon exposure
- Historical and projected changes:
  - Historical temperature increase: approximately 1.1°C with respect to 1901-1930 (most recorded after 1960).
  - Projected precipitation change: +150mm/year in the north (modest, not statistically significant).
  - Sea level: historically rising and projected to continue rising.
- Typhoon frequency and geographic concentration:
  - Category-5 typhoons: average occurrence twice per year.
  - Lower-intensity typhoons (Categories 3 and 4) occur more frequently.
  - A single Category-5 typhoon can inflict agriculture-sector losses ≈ 0.1 percent of GDP.
  - Seven regions: >15 percent annual probability of experiencing Category-5 typhoons; four regions: >25 percent likelihood.

### C. Macroeconomic impacts of climate shocks and long-term trends
- Short-run (typhoon) impacts:
  - Category-5 typhoons increase regional headline CPI ≈ 0.4 percent and regional food CPI ≈ 0.7 percent (peak ~one quarter after event).
  - Regional real GDP falls ≈ −0.4 percent on impact.
  - Agricultural labor productivity declines −2.5 percent.
  - Sectoral labor-productivity impacts used for calibration: Utilities, Mining, Manufacturing, Transportation ≈ 2 percent; Construction ≈ 4 percent.
  - Approximate average aggregate GDP impact of typhoons: around 0.2-0.3 percent of GDP.
- Long-run climate-change risks:
  - SSP3-7.0 warming: 3.1°C above pre-industrial; gradual warming can produce a 1 to 5 percent real GDP loss in 2100 compared to continuing present trends.
  - Sea-level rise costs: up to 1.8 percent annually without adaptation.
  - CIAM simulations: optimal mix of protection and retreat can reduce sea-level rise costs by as much as 95 percent, from 2.1 to 0.1 percent of GDP annually.
  - Adaptation-timing assumptions: adaptation over 30 years; adaptation in 20 years reduces losses by 50%; without adaptation losses would double (per Centorrino et al. (2025) assumptions).

### D. Monetary-policy implications and model insights
- Monetary-policy challenge: severe climate events raise inflation and lower output, complicating inflation-targeting.
- GDN model features:
  - 16-sector, 2-country model calibrated to the Philippines and the rest of the world using Philippine IO tables and the 2018 GLORIA MIRO database.
  - Distinguishes agriculture-specific capital; includes investment adjustment costs, limited substitutability of intermediate inputs, sectoral pricing frictions, and “food price salience” in expectation formation.
  - Food price salience: inflation expectations react strongly to food price spikes; slow adjustment prolongs medium-term inflation.
- Scenario and trade-off findings:
  - Single typhoon: unlikely macro-critical; multiple consecutive strong typhoons can become macro-critical by lowering GDP and raising prices.
  - Philippine-specific food price salience heightens inflationary persistence and affects tradeoffs between anchoring expectations and supporting recovery.
  - Recommended policy stance: support rebuilding while maintaining credibility to keep expectations anchored.
- Central bank reaction rule (as presented):
  - 푖푖_t = 0.7 × 푖푖_{t−1} + 0.3 × ( 푟̅ + CCttr rttrtt + 2.5 × ( CC CIIC tt i IIC tt + 3 − CC tt rttrtt ) + 0.3 × OOO tt OO tt GG tt OO tt )
  - 푖푖_t is the nominal interest rate and 푟̅ is the neutral rate of interest (formula preserved verbatim).

### E. Model calibration, downside (“bad year”) scenario, and quantitative performance
- Calibration approach:
  - Match empirical typical-year typhoon impacts using capital destruction and productivity shocks.
  - Data sources: NDRRMC damage data; local projections for sectoral productivity impacts.
- Downside scaling:
  - Downside scale: ratio ≈ 3-to -1 between Super Typhoon Pablo (2012) damage and average Category-5 typhoon.
  - Example: Super Typhoon Pablo ≈ 0.3 percent of GDP agriculture damage vs average Category-5 ≈ 0.1 percent of GDP.
- Shock sizes (Table I.2; Typical Category 5 / Bad Year — In percent):
  - Agricultural Capital: -0.79 / -2.41
  - Other Capital: -0.01 / -0.04
  - Labor Productivity: Agriculture: -0.39 / -1.20
  - Labor Productivity: Mining: -1.59 / -4.67
  - Labor Productivity: Manufacturing: -0.49 / -1.49
  - Labor Productivity: Utilities: -0.82 / -2.49
  - Labor Productivity: Construction: -1.63 / -4.92
  - Labor Productivity: Transportation: -0.97 / -2.95
- Model performance (Typical Category 5 Typhoon; Data vs Model — In percent):
  - Damages in Agriculture/GDP: 0.2583 / 0.2583
  - Damages in Infrastructure/GDP: 0.0771 / 0.0898
  - Value-added per worker in Agriculture: -0.7315 / -0.7310
  - Value-added per worker in Mining: -0.6357 / -0.6281
  - Value-added per worker in Manufacturing: -0.3934 / -0.3857
  - Value-added per worker in Utilities: -0.4766 / -0.4711
  - Value-added per worker in Construction: -1.0304 / -1.0258
  - Value-added per worker in Transportation: -0.6968 / -0.6876
- Model performance (Bad Year of Typhoons; Data vs Model — In percent):
  - Damages in Agriculture/GDP: 0.7900 / 0.7898
  - Damages in Infrastructure/GDP: 0.2357 / 0.2707
  - Value-added per worker in Agriculture: -2.2373 / -2.2377
  - Value-added per worker in Mining: -1.9442 / -1.9221
  - Value-added per worker in Manufacturing: -1.2031 / -1.1795
  - Value-added per worker in Utilities: -1.4578 / -1.4408
  - Value-added per worker in Construction: -3.1512 / -3.1387
  - Value-added per worker in Transportation: -2.1310 / -2.1032
- Key model sensitivities:
  - Approximately 50 percent of the CPI response in the downside scenario stems from agricultural capital losses.
  - Most RGDP response stems from agricultural capital losses rather than productivity declines.
  - Productivity shocks modeled as AR(1) with persistence 0.4; reducing persistence to zero leaves simulations largely unchanged.
  - Food price salience linking slow-moving inflation expectations to food prices increases inflation persistence and weakens the economy.

### F. GDN downside scenario results (selected)
- Downside scenario headline impacts:
  - Quarterly GDP falls by 0.25 percent.
  - Quarter-on-quarter inflation rises by 0.4 percentage points (1.7 percentage points annualized).
  - Initial GDP-decline composition: Consumption ≈ one-third; Net exports ≈ two-thirds (imports rise temporarily; exports fall more sharply and persistently).
  - After year one: output decline shifts toward Investment and Consumption (larger contributions); Net exports: lower contribution.
  - Interest-rate responses: nominal rates rise; real rates fall by 50 basis points (bps) in the first year (temporary stimulus).
  - Food-price dynamics: temporary spike has disproportionate impact on expectations and can have lasting inflation effects.

### G. Monetary policy trade-offs and counterfactuals
- Three monetary rules compared under downside scenario:
  - BSP’s PAMPh rule (blue).
  - Strict CPI targeting (green): CPI inflation always kept at target.
  - “Dovish” rule with a one-quarter delay in tightening (red).
- Outcomes:
  - PAMPh and dovish rules: support activity and rebuilding; real interest rates fall on impact; output remains above potential while CPI remains elevated.
  - Strict CPI targeting: neutralizes typhoon impact on inflation but causes a large decline in real GDP and a negative output gap.
- Policy priorities:
  - Anchor inflation expectations, especially when food prices are volatile.
  - Ensure financial conditions support investment and capital rebuilding.
  - Incorporate climate-related risk scenarios into policy frameworks.
- Recommended approach:
  - Balanced stance supporting rebuilding while maintaining credibility to keep expectations anchored; BSP’s PAMPh rule as a starting point with data-dependent adjustments.
  - Clear communication to reduce food-price salience and foster broader expectation formation.

### H. Fiscal policy, adaptation spending, and DIGNAD model scenarios
- Climate adaptation spending and projections:
  - Actual adaptation spending averaged 1.7 percent of GDP annually during 2022-2024.
  - Annual average during 2015-2021: 1.0 percent of GDP.
  - Programmed climate change adaptation expenditure for 2025: 3.9 percent of GDP.
  - Proposed spending for 2026: 2.7 percent of GDP.
- World Bank (2022) estimate: cost of new climate-resilient infrastructure ≈ 0.6 percent of GDP (conservative; excludes retrofitting).
- DIGNAD model features:
  - Natural disasters as shocks to public/private capital, productivity, and public investment efficiency; distinction between standard and adaptation infrastructure (adaptation costlier, higher returns, lower depreciation); fiscal adjustment and private sector response.
- DIGNAD calibration highlights (values in percent unless noted):
  - Trend per capita growth rate in absence of natural disasters: 5.0
  - Imports to GDP ratio: 35.8
  - Remittances to GDP ratio: 8.8
  - Consumption tax (VAT) rate: 12.0
  - Labor income tax rate: 24.4
  - Public domestic debt to GDP ratio: 41.3
  - Public concessional debt to GDP ratio: 8.7
  - Public external commercial debt to GDP ratio: 10.7
  - Private external debt to GDP: 11.3
  - Public investment to GDP ratio: 5.9
  - Cost ratio adaptation vs standard investment: 25.0
  - Return to standard infrastructure: 30.0
  - Return to adaptation infrastructure: 50.0
  - Depreciation rate of standard public infrastructure: 7.5
  - Depreciation rate of resilient public infrastructure: 3.0
  - Public investment efficiency: 53.0
- Scenario comparisons (active resilient-investment scenarios vs BAU):
  - BAU: no increase in adaptation investment; recurrent typhoons reduce GDP and worsen fiscal position.
  - Active scenarios: resilient infrastructure investment eventually raises output above BAU; investment in 2025 mitigates losses starting 2026.
  - Financing scenarios under active case:
    - Government borrowing: 80 percent domestic, 20 percent external borrowing; private investment crowding-out reduces positive growth effects; public debt-to-GDP ratio increases.
    - Tax reform: revenue mobilization funds resilient investment; initial largest negative impact on consumption; yields relatively favorable growth impact and reduces public debt-to-GDP ratio.
    - Rationalizing spending: similar GDP impact to borrowing scenario; higher private investment than borrowing scenario (no crowding out) offset by lower current public spending.
  - Cross-scenario takeaway: resilient infrastructure can offset recurring climate-shock impacts on GDP over time; revenue mobilization achieves higher GDP levels by avoiding crowding out; borrowing-only financing could increase debt burden.

### I. Energy sector findings (selected)
- Installed capacity and dependency:
  - One of the lowest installed energy capacities in ASEAN (absolute, % of GDP, per capita).
  - Dependence on fossil-fuel imports: approximately 6.1 percent of GDP in 2022 and 50.6 percent of total primary energy supply in 2022.
  - Baseline projection of fossil-fuel reliance: could increase to 61.1 percent by 2050.
  - Electricity generation accounted for 89 percent of total GHG emissions in 2023.
  - Peak electricity demand projection: 16.6 GW in 2022 → 68.5 GW by 2050.
- Renewable potential and current status:
  - Estimated combined potential (solar + wind): approximately 1,200 gigawatts.
  - Untapped hydropower potential: 13.097 GW.
  - Geothermal potential: 4.064 GW.
  - Installed renewable energy capacity: around 9.5 gigawatts (2024).
  - Government RE targets (CES2): 30.5 gigawatts by 2030; 115.2 gigawatts by 2050.
- Generation mix and trajectories:
  - 2024 power generation: fossil fuels 78 percent; renewables 22 percent.
  - Within fossil fuels (2024): coal 63 percent; natural gas 14.2 percent.
  - Under PEP scenarios to 2050:
    - REF: RE share → 35.5 percent.
    - CES1: RE share → 50 percent.
    - CES2: RE share → >50 percent; OSW capacity scaled to 50 GW.
  - Fossil-fuel supply change by 2050: +110 percent under REF; +54 percent under CES1; +43 percent under CES2.
- Emissions and NDC timing:
  - NDC accumulated target reduction (2020–2030): 587 mtCO2e.
  - Timing to reach NDC energy-sector target: as early as 2033 under CES2; by 2037 under CES1.
- Electricity prices and LCOE:
  - Average electricity prices (IEMOP): PHP 4.14 per kWh in H1 2025; PHP 5.58 per kWh in 2024.
  - GEAP potential: could lower average prices by about 32 percent to ≈ PHP 3.36 per kWh in Luzon by 2029.
  - LCOE (2023 USD/kWh): solar PV 0.044; onshore wind 0.033; offshore wind 0.075; oil-fired power 0.3568.
- Investment needs and private sector dynamics:
  - Estimated investment requirement 2029-2050: PHP 10.67 trillion (40 percent of 2024 GDP).
  - CES1: PHP 7.39 trillion (28 percent of GDP).
  - CES2: PHP 10.67 trillion (40 percent of 2024 GDP), driven largely by offshore wind.
  - RE investments growth: average annual growth 163 percent (2022–2024).
  - 2023 RE investments: PHP 987.12 billion (4.1 percent of GDP).
  - 2024 RE investments: PHP 1.38 trillion.
  - Solar farm investments: PHP 462 million in 2024; projected PHP 905 million in 2025.
  - Green Lane total investments PHP 5.93 trillion (22.4 percent of GDP); RE accounted for PHP 5.07 trillion (85.5 percent).
- Employment impacts:
  - DOE estimate: every USD 1 million in renewables → 4,862 job-years.
  - RE sector jobs (2009–2022): ≈ 357,000 jobs (solar 203,378; hydropower 94,835; wind 27,340; biomass 21,495; geothermal 10,261).
  - Workforce projections by 2050: Solar up to 388,600 jobs; Wind 767,300 jobs; Hydropower 13,300 jobs; Geothermal 6,100 jobs; Biomass 8,700 jobs.

### J. Policy recommendations and conclusions
- Monetary policy:
  - Integrate climate risks into macroeconomic and monetary policy frameworks.
  - Balance anchoring inflation expectations (food-price salience) with supporting post-disaster rebuilding to avoid deeper, persistent output losses.
  - Use sectoral, granular models (e.g., GDN) to capture supply-chain propagation and calibrate policy trade-offs.
- Fiscal policy and adaptation:
  - Prioritize sector-specific resilience (notably agriculture) and investment in adaptation measures (coastal protection and managed retreat) to materially reduce long-term sea-level costs.
  - Create fiscal space via stronger revenue mobilization and more efficient spending to finance resilience without excessive borrowing.
  - Consider public-private partnerships to mobilize private investment for resilient infrastructure.
  - Strengthen green public financial management consistent with Public Investment Management Assessment Update and Climate PIMA recommendations.
- Analytical and institutional priorities:
  - Continue and scale climate-informed stress testing, model development (GDN, DIGNAD), and capacity building for central bank and financial-sector resilience assessments.
  - Improve communication to reduce food-price salience and anchor expectations during transient food-price shocks.

*IMF Selected Issues Paper chapter: “Unpacking Macroeconomic Impacts of Climate Events and Policy Implications in the Philippines” (content as provided).*

### References ____________________________________________________________________________ 36

### UNPACKING MACROECONOMIC IMPACTS OF CLIMATE EVENTS AND POLICY IMPLICATIONS IN THE PHILIPPINES

### A. Introduction
- The Philippines is highly exposed to natural hazards intensified by climate change, including stronger typhoons, heavier rainfall, higher temperatures, and rising sea levels.
- World Bank estimates: cumulative economic costs of climate change could reach 7.6 percent of GDP by 2030 and 13.6 percent by 2040.
- The Philippines has embedded climate resilience in the Development Plan (PDP 2023-2028) and National Adaptation Plan (NAP 2023-2050), aligned with SDG 13 (targets 13.1 and 13.2).

### B. Climate Trends and Shocks
- Historical and projected changes:
  - Average historical temperature increase of approximately 1.1°C with respect to 1901-1930 (most recorded after 1960).
  - Country-wide precipitation historically stable; projected modest increase in the north of the country (+150mm/year).
  - Sea level has continued to rise historically and is projected to continue increasing.
- Typhoon exposure and frequency:
  - The Philippines experiences, on average, the most intense Category-5 typhoons twice per year.
  - Lower-intensity typhoons (Categories 3 and 4) occur more frequently.
  - A single Category-5 typhoon can inflict losses equivalent to about 0.1 percent of GDP in the agriculture sector alone.
  - Geographic concentration of risk: seven regions have more than 15 percent probability of experiencing Category-5 typhoons in a year; four regions face more than 25 percent likelihood.

### C. Macroeconomic Impact of Climate Shocks and Trends
- Typhoons act as adverse supply shocks with inflationary and contractionary effects:
  - Category-5 typhoons increase regional headline CPI by around 0.4 percent and regional food CPI by around 0.7 percent, with peak impact about one quarter after the event.
  - Regional real GDP falls by approximately 0.4 percent on impact.
  - Agricultural labor productivity declines by 2.5 percent.
  - Sectoral labor-productivity impacts: Utilities, Mining, Manufacturing and Transportation around 2 percent; Construction around 4 percent (used for model calibration).
  - Approximate average aggregate GDP impact of typhoons: around 0.2-0.3 percent of GDP.
- Long-term climate change risks:
  - Under high-warming SSP3-7.0 scenario (average temperatures 3.1°C above pre-industrial), gradual warming can reduce real GDP growth, resulting in a 1 to 5 percent real GDP loss in 2100 compared to continuing present trends.
  - Sea-level rise costs could be as large as 1.8 percent annually without adaptation.
  - CIAM simulations: with an optimal mix of protection and retreat, cost of sea-level rise can be reduced by as much as 95 percent, from 2.1 to 0.1 percent of GDP annually.
  - Assumptions on adaptation timing: adaptation over 30 years; adaptation in 20 years reduces losses by 50%; without adaptation losses would double (per Centorrino et al. (2025) assumptions).

### D. Policy Implications — Monetary Policy
- Climate shocks complicate the BSP’s inflation-targeting objective because severe events raise inflation and lower output.
- The IMF’s GDN model is used to assess sectoral transmission and monetary tradeoffs:
  - The GDN model is a 16-sector, 2-country model calibrated to the Philippines and the rest of the world using Philippine IO tables and the 2018 GLORIA MIRO database.
  - Calibration distinguishes agriculture-specific capital from other capital to capture disproportionate typhoon damage to agriculture.
  - Model features: investment adjustment costs, limited substitutability of intermediate inputs, sectoral pricing frictions, and “food price salience” in expectation formation.
  - Food price salience: inflation expectations react strongly to food price spikes; slow adjustment of expectations prolongs medium-term inflationary effects.
- Scenario results and monetary tradeoffs:
  - A single typhoon is unlikely to be macro-critical, but a year with multiple, consecutive, strong typhoons can become macro-critical by lowering GDP and raising prices.
  - Philippine-specific factors (notably food price salience) heighten the inflationary persistence and influence tradeoffs between anchoring expectations and supporting recovery.
  - On balance, a monetary policy reaction function that supports rebuilding while maintaining credibility to keep expectations anchored is judged most appropriate.

### E. Model Calibration, Simulations, and Downside Scenario
- Calibration approach:
  - Match empirical estimates of typical-year typhoon impacts using capital destruction and productivity shocks in the model.
  - Use National Disaster Risk Reduction and Management Council data for damages and local projection estimates for sectoral productivity impacts.
- Downside (“bad year”) scenario:
  - Scale baseline by ratio between a category-5 typhoon causing more damage than 90 percent of observed typhoons (e.g., Super Typhoon Pablo in 2012) and the average category-5 typhoon: ratio approximately 3-to -1.
  - Example damage contrast: Super Typhoon Pablo about 0.3 percent of GDP damage to the agriculture sector versus an average category-5 typhoon about 0.1 percent of GDP.
- Central bank reaction rule used in simulations (notation preserved):
  - 푖푖_t = 0.7 × 푖푖_{t−1} + 0.3 × ( 푟̅ + CCttr rttrtt + 2.5 × ( CC CIIC tt i IIC tt + 3 − CC tt rttrtt ) + 0.3 × OOO tt OO tt GG tt OO tt )
  - where 푖푖_t is the nominal interest rate and 푟̅ is the neutral rate of interest.
  - (Formula included as presented in source to preserve exact specification.)

### F. Key Quantitative Findings (preserved)
- World Bank cumulative cost estimates: 7.6 percent of GDP by 2030; 13.6 percent by 2040.
- Historical warming: approximately 1.1°C since 1901-1930 baseline.
- Northern precipitation projection: +150mm/year (modest, not statistically significant).
- Category-5 typhoon frequency: twice per year (average).
- Agriculture sector damage from one Category-5 typhoon: about 0.1 percent of GDP.
- Regional CPI responses to Category-5 typhoon: headline CPI ≈ 0.4 percent; food CPI ≈ 0.7 percent (peak ~one quarter after event).
- Regional real GDP impact on impact: ≈ −0.4 percent.
- Agricultural labor productivity impact: −2.5 percent.
- Aggregate GDP impact of typhoons: around 0.2-0.3 percent of GDP.
- SSP3-7.0 warming: 3.1°C above pre-industrial; projected 1 to 5 percent real GDP loss in 2100 (relative to continued present trends).
- Sea-level rise costs: up to 1.8 percent annually without adaptation; optimal protection/retreat can reduce costs by up to 95 percent (from 2.1 to 0.1 percent of GDP annually).
- Downside damage scaling ratio for extreme typhoon events: approximately 3-to -1 (Super Typhoon Pablo ∼0.3 percent of GDP agriculture damage vs average ∼0.1 percent).

### G. Policy Recommendations and Implications (summarized)
- Strengthen integration of climate risks into macroeconomic and monetary policy frameworks, given rising frequency and intensity of climate shocks.
- Calibrate monetary policy to balance anchoring inflation expectations (especially given food price salience) with support for post-disaster rebuilding to avoid deeper, persistent output losses.
- Prioritize sector-specific resilience (notably agriculture) and investment in adaptation measures (coastal protection and managed retreat), which can materially reduce long-term costs of sea-level rise.
- Continue and scale climate-informed stress testing, model development, and capacity building for central bank analysis and financial-sector resilience assessments.

*IMF Selected Issues Paper chapter: “Unpacking Macroeconomic Impacts of Climate Events and Policy Implications in the Philippines” (content as provided).*

### 13. A shock from a single category 5 typhoon has modest impacts on the overall economy

### 13. A shock from a single category 5 typhoon has modest impacts on the overall economy

### GDN model estimates: baseline vs downside scenario
- Scenarios analyzed:
  - Baseline: a single typical category 5 typhoon (red line).
  - Downside: more severe/macroeconomically relevant typhoon (blue line).
- Key macro impacts in the downside scenario:
  - Quarterly GDP falls by 0.25 percent.
  - Quarter-on-quarter inflation rises by 0.4 percentage points (1.7 percentage points annualized).
  - Initial GDP decline composition:
    - Consumption: about one-third of the decline.
    - Net exports: two-thirds of the decline (imports temporarily rise to compensate for destroyed capital and food; exports fall more sharply and persistently).
  - After the first year, output decline shifts toward:
    - Investment and consumption (larger contributions).
    - Net exports: lower contribution.
  - Interest rate responses:
    - Nominal interest rates rise.
    - Real interest rates fall by 50 basis points (bps) in the first year (temporary stimulus).
  - Food price spike dynamics:
    - Temporary spike has disproportionate impact on inflation expectations due to salience.
    - Lasting impact on inflation expectations and on inflation itself as expectations adjust only gradually.

### Sectoral output and price responses (downside scenario)
- Sectoral ordering of labor productivity declines (largest to smaller): construction, mining (as per calibrated shock in Table 2).
- Price and output mechanics:
  - Negative supply shocks raise marginal costs and relative prices.
  - Agriculture and mining are the two most flexible-price sectors; prices immediately increase after climate impact.
  - Agriculture: production contracts and prices rise due to agricultural capital destruction.
  - Other sectors: relatively lower prices induce substitution away from agriculture, increasing demand and production.
  - Mining: upstream position yields a very large boost in demand; flexible pricing causes its prices to rise more than in other sectors.

### Role of shock nature and model assumptions
- Drivers of responses (downside scenario):
  - About 50 percent of the CPI response stems from agricultural capital losses (Figure 8, column A).
  - Most of the RGDP response stems from agricultural capital losses rather than productivity declines.
- Productivity shock persistence:
  - Productivity shocks modeled as AR(1) with persistence parameter 0.4.
  - Reducing persistence to zero (Figure 8, Column B) leaves simulations largely unchanged, implying persistence of productivity losses is not key to macro impact.
- Food price salience in inflation expectations:
  - Linking slow-moving inflation expectations to food prices increases persistence of inflation and weakens the economy (Figure 8, column C).
  - Temporary food price rises can become partly self-fulfilling via expectations.

### Monetary policy trade-offs and counterfactuals
- Three monetary policy rules compared under the downside scenario (Figure 9):
  - BSP’s PAMPh rule (blue).
  - Strict CPI targeting: CPI inflation always kept at target (green).
  - “Dovish” rule with a one-quarter delay in tightening (red).
- Outcomes:
  - PAMPh and dovish rules:
    - Support activity and rebuilding because real interest rates fall on impact.
    - Output remains above potential GDP while CPI inflation remains elevated.
  - Strict CPI targeting:
    - Neutralizes typhoon impact on inflation.
    - Accompanied by large decline in real GDP and a negative output gap.
- Interpretation:
  - Monetary policy faces a trade-off between anchoring inflation expectations and supporting reconstruction.
  - PAMPh rule and dovish rule assume BSP focuses on medium-term inflation and output relative to steady state; nominal rate rises but less than 1-quarter ahead inflation, causing real rates to fall on impact.

### Policy implications (monetary)
- Priorities:
  - Anchor inflation expectations, especially when food prices are volatile.
  - Ensure financial conditions remain supportive of investment and capital rebuilding.
  - Incorporate climate-related risk scenarios into policy frameworks.
- Trade-offs:
  - Strict CPI targeting: keeps inflation expectations low / reduces de-anchoring risk, but causes deeper output losses and slower rebuilding.
  - Accommodative stance (e.g., short delay in tightening): sustains activity above potential but yields higher and more persistent inflation.
- Recommended approach:
  - Balanced approach that supports rebuilding while maintaining credibility to keep expectations anchored.
  - BSP’s PAMPh rule as a starting point, with data-dependent adjustments as shock dissipates and persistence of inflation becomes clearer.
- Behavioral channel:
  - Food price salience prolongs the policy trade-off; suggests importance of clear communication and credible policy actions to reduce salience bias and foster broader expectation formation.

### Fiscal policy and adaptation spending
- Strategic plans and tools:
  - Philippine Development Plan (2023-2028) incorporates climate change as cross-cutting strategic area.
  - National Climate Change Action Plan (NCCAP) (2011-2028).
  - National Adaptation Plan (NAP) (2023-2050).
  - Philippine Sustainable Finance Taxonomy Guidelines (SFTG).
- Climate adaptation spending trends and projections:
  - Actual adaptation spending averaged 1.7 percent of GDP annually during 2022-2024.
  - Annual average during 2015-2021: 1.0 percent of GDP.
  - Programmed climate change adaptation expenditure for 2025: 3.9 percent of GDP.
  - Proposed spending for 2026: 2.7 percent of GDP.
  - Main strategic priorities: water sufficiency, sustainable energy, climate smart industries and services.
- Cost estimates and trade-offs:
  - World Bank (2022) estimate: cost of new climate-resilient infrastructure about 0.6 percent of GDP (conservative; excludes retrofitting existing infrastructure).
  - Financing resilience via borrowing risks higher public debt and complications for Medium-Term Fiscal Framework consolidation.
  - Alternatives if avoiding additional debt: revenue mobilization and/or expenditure rationalization.
  - Model-based approaches can analyze trade-offs for growth and debt sustainability.

### Model-based scenario analysis (DIGNAD application)
- Model: Debt-Investment-Growth and Natural Disasters (DIGNAD) model (Marto, Papageorgiou, and Klyuev, 2018).
  - Features: natural disasters as shocks to public/private capital, productivity, and public investment efficiency during reconstruction; standard and adaptation infrastructure (adaptation costlier, higher returns, lower depreciation); investment-growth nexus; fiscal adjustment; private sector response.
- Calibration highlights (Table 1: values in percent unless noted):
  - Trend per capita growth rate in absence of natural disasters: 5.0
  - Imports to GDP ratio: 35.8
  - Remittances to GDP ratio: 8.8
  - Consumption tax (VAT) rate: 12.0
  - Labor income tax rate: 24.4
  - Public domestic debt to GDP ratio: 41.3
  - Public concessional debt to GDP ratio: 8.7
  - Public external commercial debt to GDP ratio: 10.7
  - Private external debt to GDP: 11.3
  - Public investment to GDP ratio: 5.9
  - Cost ratio adaptation vs standard investment (i.e., adaptation is % expensive than standard): 25.0
  - Return to standard infrastructure: 30.0
  - Return to adaptation infrastructure: 50.0
  - Depreciation rate of standard public infrastructure: 7.5
  - Depreciation rate of resilient public infrastructure: 3.0
  - Public investment efficiency: 53.0
- Baseline natural disaster representation:
  - Recurring annual shocks of average magnitude destroy public and private capital and reduce TFP.
  - Leads to permanent downward level shift in GDP relative to counterfactual without shocks.
  - Assumes recurrent typhoons reduce output by 0.1 percent of GDP every year, with persistent effects (about 4 years).
  - Output impact arises from public/private capital destruction, productivity shocks, and reduced public investment efficiency.
- Active scenario: resilient infrastructure investment assumed at 0.3 percent of GDP (half the size suggested by World Bank (2022)).
- Three financing/reform scenarios under the active scenario:
  - Government borrowing scenario:
    - Resilient infrastructure financed by borrowing.
    - Borrowing composition: 80 percent domestic, 20 percent external (in line with borrowing strategy).
  - Tax reform scenario:
    - Government tax reforms create fiscal space to fund resilient infrastructure investments.
  - Rationalizing spending scenario:
    - Finance resilient infrastructure through expenditure prioritization and shifting composition toward resilient infrastructure while keeping total expenditure envelope unchanged.

*Source: IMF staff calculations.*

### 29. We also compare these active scenarios to a passive “business-as-usual” (BAU)

### 29. We also compare these active scenarios to a passive “business-as-usual” (BAU) scenario.

### Results: Macroeconomic impacts and scenario comparisons
- BAU assumption: the government does not increase its adaptation investment despite the recurring shocks.
- Main simulation insight:
  - Recurrent typhoons reduce GDP relative to the steady state baseline with no climate shocks.
  - The fiscal position deteriorates due to lower revenues from output losses, higher reconstruction spending, and a lower denominator for the debt-to -GDP ratio.
  - In active scenarios with government investment in adaptation infrastructure, output eventually rises above the BAU scenario as resilient infrastructure investment exceeds the negative impact of typhoons on output. (Note: In the active scenarios, investment to adaptation made in 2025 will only mitigate the losses in 2026.)
- Government borrowing scenario:
  - Positive effects of resilient infrastructure investment are less pronounced because of crowding-out of private investment.
  - Public debt-to -GDP ratio increases over time and relative to the BAU scenario.
- Tax reform scenario:
  - Produces the initial largest impact on consumption (largest negative impact on consumption initially).
  - Yields a relatively more favorable overall impact on growth because mobilizing revenue yields a smaller multiplier effect compared to cuts in public spending.
  - Dampens private consumption but has a relatively benign effect on private investment.
  - Public debt-to -GDP ratio decreases since investment in resilience no longer requires financing through borrowing.
- Rationalizing spending scenario:
  - Yields similar impact on GDP as the government borrowing scenario.
  - Private investment is higher than in the borrowing scenario because there are no crowding-out effects; this is offset by lower current public spending.
- Cross-scenario takeaway:
  - Resilient infrastructure has potential to offset recurring climate-shock impacts on GDP over time, regardless of financing strategy.
  - Revenue mobilization helps achieve a higher level of GDP because it does not crowd out private investment and other public spending.
  - Relying solely on borrowing to finance resilient investment could increase the debt burden over time.

### E. Conclusion: Policy implications for the Philippines
- Climate change is a structural macroeconomic risk for the Philippines, requiring a whole-of-government response.
- Monetary policy implications:
  - Findings highlight the balance between anchoring inflation expectations and supporting post-disaster economic recovery.
  - Severe weather events cause sector-specific disruptions; models with sectoral granularity (e.g., the GDN model) better capture propagation through supply chains.
  - The salience of food prices amplifies macroeconomic impacts by turning temporary food price shocks into more persistent inflationary pressures.
  - Counterfactuals under BSP’s PAMPh rule, strict CPI targeting, and a “dovish” rule show trade-offs: PAMPh and “dovish” rules support activity, strict CPI targeting tames inflation but all entail costs in terms of output and inflation.
  - Recommendation: adopt a policy stance that supports post-disaster rebuilding while maintaining credibility in inflation expectations; the BSP’s inflation-targeting framework, with clear public communication and data-dependent adjustments, is well-suited.
- Fiscal policy implications:
  - Investment in climate-resilient infrastructure is central to mitigating macro impacts of natural disasters.
  - DIGNAD model evidence: resilient investment has higher upfront fiscal costs but delivers higher long-term returns by mitigating productivity losses, safeguarding capital, and sustaining growth.
  - Creating fiscal space via stronger revenue mobilization and more efficient spending is critical to finance resilience without increasing public debt.
  - Mobilizing private investment through public-private partnership modalities could also finance resilient infrastructure (not modeled).
  - Enhancing green public financial management, aligned with Public Investment Management Assessment Update and Climate PIMA recommendations, will improve adaptive investment effectiveness and accountability.

### Annex I. Technical Annex — Methods, calibration, and model performance
- Data and sample:
  - Region- and sector-level data from PSA cover 17 regions and the period from 2000 to 2022.
  - NDRRMC provides damage-cost data by cyclone intensity categories 1–5; event dates from EM-DAT.
  - Damage costs disaggregated into: agriculture (output and capital losses), infrastructure (non-agricultural capital), and others.
- Local projections specification:
  - Uses Jorda local projections to estimate impulse response functions; specification provided formally (equation (1) in the source).
  - Controls include time and region fixed effects (FE_t and FE_r).
  - Robustness: results robust to clustering standard errors at the regional level, except for the impact on agricultural GDP.
- IMF GDN model calibration and price adjustment frequencies:
  - Where CPI data exist, peak inflation response of a sector to a 100-basis point monetary shock is estimated via local projections and matched in the GDN model by adjusting price adjustment frequencies.
  - For 9 of 16 sectors with data, Table I.1 shows model responses, data responses, and price adjustment frequencies. For 7 sectors without Philippines data, parameter values from Pasten, Schoenle & Weber (2020) are used.
- Shock sizes and model performance:
  - Calibration matches economic losses in agriculture and infrastructure and value-added in 6 sectors; Table I.2 shows shock sizes in percent for a Typical Category 5 Typhoon and a Bad Year.
  - Table I.2 (Shock: Typical Category 5 / Bad Year — In percent):
    - Agricultural Capital: -0.79 / -2.41
    - Other Capital: -0.01 / -0.04
    - Labor Productivity: Agriculture: -0.39 / -1.20
    - Labor Productivity: Mining: -1.59 / -4.67
    - Labor Productivity: Manufacturing: -0.49 / -1.49
    - Labor Productivity: Utilities: -0.82 / -2.49
    - Labor Productivity: Construction: -1.63 / -4.92
    - Labor Productivity: Transportation: -0.97 / -2.95
  - Model performance in matching data:
    - Table I.3. Typical Category 5 Typhoon (In percent) — Impact: Data vs Model
      - Damages in Agriculture/GDP: 0.2583 / 0.2583
      - Damages in Infrastructure/GDP: 0.0771 / 0.0898
      - Value-added per worker in Agriculture: -0.7315 / -0.7310
      - Value-added per worker in Mining: -0.6357 / -0.6281
      - Value-added per worker in Manufacturing: -0.3934 / -0.3857
      - Value-added per worker in Utilities: -0.4766 / -0.4711
      - Value-added per worker in Construction: -1.0304 / -1.0258
      - Value-added per worker in Transportation: -0.6968 / -0.6876
    - Table I.4. Bad Year of Typhoons (In percent) — Impact: Data vs Model
      - Damages in Agriculture/GDP: 0.7900 / 0.7898
      - Damages in Infrastructure/GDP: 0.2357 / 0.2707
      - Value-added per worker in Agriculture: -2.2373 / -2.2377
      - Value-added per worker in Mining: -1.9442 / -1.9221
      - Value-added per worker in Manufacturing: -1.2031 / -1.1795
      - Value-added per worker in Utilities: -1.4578 / -1.4408
      - Value-added per worker in Construction: -3.1512 / -3.1387
      - Value-added per worker in Transportation: -2.1310 / -2.1032
- Price adjustment frequency examples (from Table I.1; Model Response / Data Response / Price Adjustment Frequency):
  - Education: -0.79 / -0.58 / 0.03
  - Agriculture: -4.92 / -5.83 / 1.00
  - Energy and Water: -1.42 / -1.84 / 0.30
  - Real Estate: -1.98 / -1.84 / 0.37
  - Manufacturing: -1.27 / -1.25 / 0.50
  - Human Health: -1.52 / -1.78 / 0.35
  - Transport: -3.14 / -4.35 / 1.00
  - IT & Communications: -0.75 / -0.10 / 0.01
  - Arts, Entertainment and Other Services: -2.60 / -2.22 / 0.45
  - For sectors without Philippines data, values sourced from Pasten, Schoenle & Weber (2020) are noted in the table (e.g., Mining & Quarrying 0.97*, Construction 0.42*, Accommodation & Restaurants 0.21*, Professional, Scientific & Technical 0.09*, Wholesale and Retail 0.39*, Finance 0.31*, Public Administration 0.19*).
- Notes on figures and model output:
  - Figures I.2–I.5 present full responses (percent deviations from steady state real GDP for most variables; nominal and real interest rates shown in percentage points).
  - Figure annotations: all variables in the first row show percent deviation from steady state real GDP; nominal and real interest rate changes are linear and shown in percentage points.

*Source: IMF staff calculations (from the provided chapter/section).*

### 1. The Philippines has one of the lowest installed energy capacities in the ASEAN region

### 1. The Philippines has one of the lowest installed energy capacities in the ASEAN region

### Key findings: capacity, reliance, and emissions
- The Philippines exhibits one of the lowest installed capacities in ASEAN in absolute terms, as a percentage of GDP, and on a per capita basis.
- Dependence on fossil fuel imports: approximately 6.1 percent of GDP in 2022 and comprising 50.6 percent of the country’s total primary energy supply in 2022.
- Baseline projection of fossil fuel reliance: could increase to 61.1 percent by 2050.
- Electricity generation accounts for 89 percent of the country’s total greenhouse gas emissions (GHG) in 2023.
- Peak electricity demand projection: increase from 16.6 GW in 2022 to 68.5 GW by 2050.

### Renewable energy potential and current status
- Estimated combined potential (open-field solar, rooftop solar, offshore and onshore wind): approximately 1,200 gigawatts (Climate Analytics 2023).
- Untapped hydropower potential: 13.097 GW (Department of Energy).
- Geothermal estimated potential capacity: 4.064 GW (Energy Tracker Asia); Philippines is the third largest producer of geothermal energy next to the United States and Indonesia.
- Installed renewable energy capacity: around 9.5 gigawatts (2024).
- Government RE targets (Clean Energy Scenario 2): 30.5 gigawatts of installed generating capacity by 2030 and 115.2 gigawatts by 2050.

### Current generation mix and trajectories
- As of 2024: fossil fuels comprise 78 percent of total power generation; renewable energy contributes 22 percent.
- Within fossil fuels (2024): coal 63 percent of power generation; natural gas 14.2 percent.
- Under the Philippine Energy Plan (PEP) scenarios:
  - Reference Scenario (REF): RE share projected to reach 35.5 percent by 2050.
  - Clean Energy Scenario 1 (CES1): projects RE share of 50 percent by 2050 (includes offshore wind, nuclear, improved efficiency).
  - Clean Energy Scenario 2 (CES2): scales OSW capacity from 19 GW to 50 GW and increases RE share to more than 50 percent by 2050.
- Fossil fuels supply change by 2050: increase by 110 percent under REF, 54 percent under CES1, and 43 percent under CES2.

### Emissions and NDC alignment
- NDC accumulated target reduction between 2020 and 2030: 587 mtCO2e.
- Estimated timing to reach NDC energy-sector target: as early as 2033 under CES2 and by 2037 under CES1.
- REF scenario: projected to reduce energy emissions by more than half but does not fully achieve the NDC accumulated target by 2030.

### Electricity prices and cost trends
- Average annual electricity prices (IEMOP): PHP 4.14 per kWh in the first half of 2025, down from PHP 5.58 per kWh in 2024.
- Successful Green Energy Auction Program (GEAP) rounds could lower average electricity prices by about 32 percent to approximately PHP 3.36 per kWh in Luzon by 2029, with similar reductions projected in the Visayas and Mindanao grids.
- Levelized Cost of Energy (LCOE) (2023 USD/kWh): solar PV 0.044; onshore wind 0.033; offshore wind 0.075; oil-fired power 0.3568.

### National and regional supply gaps; grid considerations
- RE penetration varies regionally due to archipelagic geography and constrained centralized grid development, creating regional disparities in electrification.
- Decentralized RE-based hybrid grid systems are viable, especially for islands, but hampered by high upfront capital costs (expected to ease as RE and battery storage costs decline).
- Regional generation characteristics:
  - Luzon: primarily hydropower, increasing solar contribution.
  - Visayas: relies heavily on geothermal (Tongonan, Ormoc City).
  - Mindanao: relies on hydropower with Agus and Pulangi Power Plant Complexes supplying more than 50 percent of the island’s electricity.

### Recent policy measures and regulatory reforms
- Law allowing 100 percent foreign ownership of renewable energy projects enacted in 2022; resulted in awarding 65 RE contracts totaling 17.84 GW to fully foreign-owned companies for offshore and onshore wind, and solar projects.
- Green Energy Auction Program (GEAP) components:
  - Green Energy Auction (GEA) and Green Energy Tariff (GET).
  - Three GEAP rounds provided a combined total of 12GW RE capacities expected to provide RE generation from 2025-2035.
  - GEA rounds: GEA 1 (June 2022) – 1.9 GW; GEA 2 (July 2023) – 3.4GW; GEA 3 (February 2025) – 6.7GW.
- Revised omnibus guidelines allow developers to commence permit processing and feasibility activities before official 25-year contract terms begin.
- As of May 2025, DOE issued 104 certificates of authority (COA), total potential capacity of 20.42 GW.
- Strengthening of Energy Virtual One-Stop Shop (EVOSS) to speed permit approvals.
- Bangko Sentral ng Pilipinas (BSP) measures:
  - Increased Single Borrower’s Limit (SBL) for financing green or sustainable projects by 15 percent.
  - Gradual reduction of reserve requirement for sustainable bonds from current 3 percent to 0 percent over a two-year period.
  - Adoption of Philippine Sustainable Finance Taxonomy Guidelines (SFTG).
- Philippines ranked second-largest issuer of ASEAN-labelled GSS+ Bonds as of end-July 2025 (SEC 2025).

### Private investments and market developments
- Average annual growth in total RE investments: 163 percent (2022 to 2024).
- Surge in RE investments beginning 2022: 225 percent growth from 2021 to 2022 (BOI data).
- 2023 RE investments: PHP 987.12 billion (4.1 percent of GDP), 231 percent growth; wind farms totaling PHP 804 billion (3.3 percent of GDP).
- 2024 total RE investments: PHP 1.38 trillion.
- Investment by investor type:
  - Domestic investors: PHP 651 billion (2.7 percent of GDP) in 2023; by 2024 domestic investments expanded to 3.7 percent of GDP.
  - Foreign investments: PHP 330 billion in 2023 and PHP 314 billion in 2024.
- Solar farm investments: reached PHP 462 million in 2024 and projected to reach PHP 905 million in 2025.
- Green Lane for Strategic Investments (Executive Order No. 18) since February 2023 facilitated total investments PHP 5.93 trillion (22.4 percent of GDP); RE accounted for PHP 5.07 trillion (85.5 percent of the total).
  - Domestic share under Green Lane: PHP 3.43 trillion (71.7 percent).
  - Foreign share under Green Lane: PHP 1.35 trillion (28.2 percent).

### Employment impacts and projections
- DOE estimate: every USD 1 million invested in renewables leads to an average of 4,862 job-years from project development to construction (ILS - DOLE 2024).
- RE sector jobs generated 2009–2022: approximately 357,000 jobs (solar 203,378; hydropower 94,835; wind 27,340; biomass 21,495; geothermal 10,261).
- Workforce projections by 2050 based on RE targets and investments:
  - Solar: up to 388,600 jobs.
  - Wind: 767,300 jobs.
  - Hydropower: 13,300 jobs.
  - Geothermal: 6,100 jobs.
  - Biomass: 8,700 jobs.

### Public investments and PPP involvement
- Public Investment Program (PIP) 2023-2028: medium-term budget for small-scale renewable energy projects rose substantially to support missionary and underserved areas (DOE Missionary Electrification Development Plan (MEDP) 2024–2028).
- DENR Integrated Water Resources Management Plan 2024: NIA water rights converted to multipurpose use enabling bulk water supply and hydropower projects using existing NIA facilities.
- PPP pipeline (as of October 2025): 251 PPP projects with estimated total cost approximately PHP 2.61 trillion (9.9 percent of GDP).
  - PPPs for RE projects: PHP 98.5 billion, or 3.8 percent of the total PPP cost (under development and under implementation).
- Smart and Green Grid Plan (SGGP): priority under PEP 2023–2050; expected to be largely financed through PPPs and anchor rollout of transmission facilities by TransCo for RE projects.
- DOE collaboration with Philippine Ports Authority and PPP Center to repurpose and modernize port infrastructure to support offshore wind installations via PPPs.

*Source: 1phlea2025002-source-pdf - 1. The Philippines has one of the lowest installed energy capacities in the ASEAN region*

### 16. The Philippines receives a marginal share of public bilateral investments in RE from

### 16. The Philippines receives a marginal share of public bilateral investments in RE from within Asia

### International public investments in renewable energy (RE)
- The number of international public investments in RE from within Asia to selected ASEAN destinations has increased by an average of 15 percent per year (Zero Analytics 2025).
- China has recorded the highest total public investment—USD 2.7 billion.
- Between 2013 and 2023, Indonesia received the largest share of public bilateral investment at USD 3.54 billion, followed by Thailand, Vietnam, and the Philippines.
- By RE type, Japan is the region’s largest public investor in geothermal energy while China leads in hydro and wind power.

### Investment requirements and scenarios to meet energy transformation targets
- Estimated investment requirement: PHP 10.67 trillion (40 percent of 2024 GDP) during 2029-2050.
- Projected investment requirements rise significantly between 2023 and 2050 under all three scenarios of the PEP.
- By 2029-2050:
  - CES1: investment requirements reaching PHP 7.39 trillion (28 percent of GDP).
  - CES2: investment requirements reaching PHP 10.67 trillion (40 percent of 2024 GDP), driven largely by offshore wind, followed by solar, hydropower and emerging technologies.
- Meeting targets requires strong public and private participation, particularly in capital-intensive industries, and prompt, comprehensive solutions to barriers impeding project implementation and investor confidence.

### Grid infrastructure capacity and coverage
- Limited capacity and coverage of the national transmission and distribution system; inadequate capacity to integrate intermittent RE sources such as solar and wind.
- The Philippine grid, managed primarily by the National Grid Corporation of the Philippines (NGCP), is not yet fully equipped to oversee intermittent generation or to transmit electricity from remote renewable resource areas (e.g., offshore wind sites or upland solar farms) to demand centers.
- DOE indicates the energy sector requires a transmission system that can provide automated control to quickly respond to grid condition changes and maintain integrity and reliability.
- Department of Economy, Planning and Development emphasizes locating abundant resources that may be in remote or protected areas not covered by existing transmission networks; these circumstances must be considered in upgrading the national transmission and distribution network.

### Financing, market structure, and supply-chain vulnerabilities
- RE development requires extensive exploration and site-specific assessments, contributing to high upfront capital costs and longer investment horizons that challenge private sector financing.
- The Department of Finance notes underutilization of the capital market and continued reliance on debt in bridging the RE financing gap.
- Financing instruments such as sustainable bonds and blended financing are still at the nascent stage with less uptake by most small and local players.
- Power generation markets in the Philippines are considered oligopolistic with approximately 53 percent of the market share dominated by three private firms (PIDS 2023).
- Lack of RE manufacturing exposes the sector to price volatility of imported technologies: solar panels, batteries, inverters, and critical components for offshore wind (turbine blades, subsea cables, and specialized installation vessels).
- Offtake mechanisms remain limited; while GEAP and GEOP are implemented, ceiling prices under GEAP are considered too low by some developers, especially for solar and offshore wind. Challenges remain in ensuring viable, long-term power purchase agreements (PPA).

### Land acquisition and permitting
- Land acquisition for RE projects remains slow, complex and contentious, causing delays and reducing the scale of large RE projects such as solar farms and onshore wind developments.
- Land use is characterized by fragmented and multiple systems granting legislative authority to carve out public land for specific uses, often leading to conflicts.
- Existing mechanisms for reserving land include Presidential proclamations and sector-specific laws, while land zoning, land reclassification and land use conversion are under local government units (Local Government Code of 1991).
- The National Land Use Committee (NLUC) facilitates national discussions and conflict resolutions but has no enforcement power or authority to impose sanctions or penalties (PIDS 2023).
- Republic Act (RA) 12289, Accelerated and Reformed Right-of-Way Act (ARROW), aims to expedite property acquisition for infrastructure projects through streamlined procedures; the impact is yet to be observed.
- DOE and DENR signed a Memorandum of Agreement granting rights to use offshore areas covered by offshore wind energy service contracts, including auxiliary areas to accelerate offshore wind development.

### Workforce and skills constraints
- The Philippines has the largest RE development pipeline in the region but faces a substantial gap in the skilled RE workforce (ILO 2025).
- DOLE ILS survey: 75 percent of RE company representatives find it difficult to hire qualified candidates for vacant technical positions, especially in the higher-skilled category followed by technicians and associate professionals.
- Managers also face shortages linked to demand for technical knowledge and soft skills such as leadership and project management (DOLE ILS 2024).
- ILO flagged absence of formal apprenticeships and systems for forecasting future skill needs as major constraints affecting RE project quality.
- Government initiatives to upskill and reskill the workforce include: UNFCCC Just Transition Work Program; DOE-ILO collaboration on Green Jobs and Just Transition Framework; Right-Skilling the Philippine Workforce initiative (global certifications); Affiliated Renewable Energy Centers (ARECs) program with SUCs to develop specialized RE hubs.

### Government initiatives supporting RE expansion (Annex I summary highlights)
- Policy and regulatory measures (selected):
  - Amendments to the RE Act of 2008 (2022): 100% foreign ownership in solar, wind, and tidal projects.
  - CREATE MORE Act (2024): Alternative incentives such as income tax holiday, duty-free imports, VAT exemption.
  - Renewable Portfolio Standards (RPS) (2025): increased minimum RPS annual percentage increment from 1.0 to 2.52%; in 2025 mandated entities required to source at least 13.9% of their supply portfolio from renewables, with an annual increase of 2.52%.
  - Energy Virtual One-Stop Shop (EVOSS) Act (2019): centralized online platform for coordinated processing and approval of permits.
  - Green Energy Auction Program (GEAP) (2020) and Green Energy Option Program (GEOP) (2018).
  - Executive Order No. 21 (2021): Establishment of the Policy and Administrative Framework for Offshore Wind Development.
  - Microgrid Systems Act (2022), Preferential Dispatch of All RE-Generating Plants (2022), Expanded Roof-Mounted Solar Program (2023), Revised Omnibus Guidelines Governing the Award of RE Contracts and Registration of RE Developers (2024).
  - BSP Circular No. 1149, s. 2022; BSP Circular No. 1185, s. 2023; BSP Circular No.1187 Series of 2024: measures to integrate sustainability in banking and provide incentives such as top-up 15 percent Single Borrower’s Limit (SBL) for eligible green loans and temporary RRR reductions for sustainable bonds.
  - SEC POWERS (2025) to secure and expand capital for powergen operators and wholesale/retail services.
  - DENR administrative orders for Offshore Wind ECC (2024) and floating photovoltaic guidelines (2023).
- Government-financed project plans (2023-2025, selected):
  - Transmission Development Plan (TDP) 2025-2050 (for publication) — National Grid Corporation of the Philippines: realigning targets with updated RES targets and integration of smart grid technologies; Approx. 5,145 km of transmission lines and 63,625 MVA of transformation capacity.
  - Smart and Green Grid Plan (SGGP) — DOE: modernize the grid to meet the 2050 peak demand, enable over 50% RE share by 2040, and support up to 50 gigawatts of offshore wind.
  - Missionary Electrification Development Plan (MEDP) 2024-2028 — DOE: achieve universal, sustainable, and inclusive energy access in off-grid and underserved areas.
  - PPP Code of the Philippines (RA 11966) — PPP Center: streamline evaluation, approval, and monitoring of RE and energy efficiency PPP projects.
  - DOE and Philippine Ports Authority collaboration: repurpose and modernize port infrastructure to handle installation, commissioning, and operations of OSW projects; support high-potential offshore wind energy service contracts totaling 56 as of 2024.

*International Monetary Fund*

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_Source: https://www.imf.org/-/media/files/publications/cr/2025/english/1phlea2025002-source-pdf.pdf_