## POTENTIAL GROWTH AND DEMOGRAPHIC DIVIDEND ## Source details **Canonical URL:** [POTENTIAL GROWTH AND DEMOGRAPHIC DIVIDEND](https://www.imf.org/-/media/files/publications/cr/2024/english/1phlea2024002-print-pdf.pdf) ## Other formats - [Markdown version](/-/media/files/publications/cr/2024/english/1phlea2024002-print-pdf.pdf.md) - [Structured JSON version](/-/media/files/publications/cr/2024/english/1phlea2024002-print-pdf.pdf.json) --- ### Recent Developments - Real GDP fell by 9.5 percent in 2020 due to COVID-19; unemployment rose to 10.3 percent in 2020. - Recovery: real GDP growth peaked at 7.6 percent in 2022 and moderated to 5.5 percent in 2023. - Unemployment averaged 4.4 percent in 2023. - Labor productivity remains below pre-pandemic trends despite employment recovering; productivity particularly weak in agriculture and below pre-pandemic level in services. - Under current policy settings, medium-term potential growth is estimated at 6.0-6.3 percent. - An upside scenario with ambitious, well-sequenced structural reforms could raise growth to 7.0-7.5 percent over a longer horizon. ### Demographic Trends - By end-2024, the Philippines' dependency ratio (population ages 0-14 plus 65+ divided by population 15-64) is projected to fall below 50 percent. - Working-age population projected to continue growing until around 2045 (UN population forecasts). - Between 2060 and 2070 the dependency ratio is expected to exceed 50 percent, with national population beginning to decline around 2060. - Job creation requirement to harvest dividend: at least 12 million new jobs between now and 2050, or about 450 thousand per year. - Historical context: during 2005-2019 the Philippines created on average 700 thousand jobs per year. - If labor force participation rises (particularly female participation), the number of jobs needed would increase. ### Structural Gaps (Benchmarking and Findings) - Benchmarking across eight dimensions against ASEAN-6, G20 EMs, and OECD-EMs: trade regulation and barriers; business regulation and infrastructure; economic complexity and openness; credit market regulation and financial inclusion; governance; labor markets; human capital; human development, health, and demographics. - Indicators normalized 0 to 1 (higher = better); gaps computed relative to comparator group median. - Key structural shortfalls identified: - Trade: less open than OECD EMs on trade restrictions, trade facilitation, and external sector regulation reform. - Business environment and infrastructure: lags on economic openness, business regulation reform, electricity access, and logistics. - Digital infrastructure: fixed broadband cost about four times higher than in Vietnam and more than twice the Southeast Asia average (World Bank). - Education infrastructure: facility and equipment gaps reduce learning opportunities. - Physical infrastructure: road gaps, especially in poor or remote communities. - Financial markets: credit provision and financial market regulation operate at least as well as, or better than, upper-middle-income countries but less well than ASEAN peers. ### Trade Openness and Investment Environment - Philippines ranks middle among ASEAN peers on most trade openness measures but trails OECD EMs. - Authorities identify maritime shipping as an area for cost and ease-of-doing-business improvements. - Ongoing policy efforts include legislative reforms, PPPs for physical and digital infrastructure, and green lanes to fast-track strategic investment. ### Governance - Gaps relative to ASEAN peers in anti-corruption, legal system, regulatory quality, and rule of law. - Performs better than G20EM countries and relatively closer to peers on regulatory quality, accountability, and effectiveness. - Strengthening anti-corruption, legal certainty, regulatory quality, and rule of law would support private investment through fair contract enforcement and property rights protection. ### Labor Markets and Human Capital Development - Labor market regulations are relatively pro-growth, but labor productivity and labor force participation lag. - Female labor force participation lags male participation by almost 20 percent. - Women in paid jobs earn more on average than men, reflecting higher tertiary education and concentration in high-skill jobs; when accounting for human capital differences the gender wage gap rises to close to 30 percent in favor of men. - Education outcomes: primary and higher education completion compare favorably to ASEAN and G20EM peers, but learning outcomes are weak and were further hurt by the pandemic. - Share of population with secondary education remains low and heavily skewed to the wealthiest decile; skills mismatch between graduates and employer demands persists. ### Potential Growth: Methodology and Projections - Potential growth estimated using the production function approach with a Cobb-Douglas specification. - Data sources: Penn World Table (PWT) 10.0 (latest observation 2019); 2020-2023 data from PSA, Haver, World Bank WDI, and UN Population Projections. - Baseline assumptions for projection period: - Capital: historical elasticity between capital service growth and capital stock growth used; capital stock based on WEO projections for fixed capital investment and a 2 percent depreciation rate; capital share set to 0.5 (2019 PWT). - Labor: effective labor = employment × hours worked; PSA working-age population projections through 2023; assumed labor force participation rate and employment rate equal to their 2023 values (64.9 percent and 95.7 percent, respectively); hours worked projected to reverse pandemic decline in medium term; labor share set to 0.5 (2019 PWT). - TFP: historical relationship between TFP and labor productivity estimated; elasticities applied to projected labor productivity (based on projected employment growth and WEO nominal GDP) with adjustors for planned investments expected to affect TFP. - Human capital: proxied by years of schooling following PWT method with assumed rate of return (Psacharopouls (1994) and Caselli (2005)); years of schooling assumed to rise by 1.5 years from the 2019 value of 8.9 years through the medium term. - Medium-term potential growth estimated at 6.0-6.3 percent (down from pre-pandemic estimate of 6.5 percent) due to pandemic scarring, slow labor productivity recovery, and long-lasting education impacts. - Contribution details: - Capital services contribution peaked in the five years prior to the pandemic at around 4½ percentage points. - Capital's contribution expected to gradually rise to about 3.3 percent by the medium term given current investment projections. - Labor contribution: pre-pandemic average contribution was 1.1 percentage points; projected to be around the same in the medium term. - Human capital contribution slightly higher due to assumed longer years of schooling. - TFP contribution expected to be 1.6 percentage points versus 1.0 percentage points in the five years pre-pandemic, reflecting assumed improvements in public infrastructure, digitalization, and greater foreign investment. ### Policy Implications and Reform Priorities (Objectives reflected in source) - Close structural gaps to harness demographic dividend and boost potential growth toward the upside scenario (7.0-7.5 percent). - Strengthen areas identified in benchmarking: - Trade facilitation and reduction of tariff and non-tariff barriers. - Business regulation reform, logistics, electricity access, and digital infrastructure cost and coverage. - Education quality improvements, addressing facility and equipment gaps, and reducing skills mismatches. - Anti-corruption measures, legal system enhancements, regulatory quality, and rule of law to foster private investment. - Policies to raise female labor force participation and reduce underemployment to increase labor contribution to growth. - Leverage PPPs and green lanes to crowd in private investment and boost capital’s contribution to growth. ### Section 14 — Objective and approach - Aim: Support the Philippine authorities’ growth target for 2026-28 of 6.5-8.0 percent. - Method: Use estimates from IMF (2024) and Budina and others (2023) of potential gains in output from major structural reforms. Reforms considered include external sector, business regulation, governance, labor market, credit market regulation, and human development. - Estimation note: Estimates are from local projections models which regress either real GDP at Purchasing Power Parity or employment (for labor market regulation) on aggregate reform indices constructed as averages of sub-variables. Major reforms are defined as episodes with an improvement in the relevant indicator of at least two standard deviations. Sample covers 1996-2022 and includes AE and EM countries. ### Impact of first-generation reforms (governance, human development, external sector, business regulation) - Governance and human development (when implemented alone): - Governance: increase of around 1 percent following a two standard deviation shock to the reform index. - Human development: increase of around 5 percent following a two standard deviation shock to the reform index. - Given the Philippines’ initial conditions, the country would need a shock 2-3 times this size to catch up to ASEAN-6 and emerging market peers in these categories. - External sector and business regulation: - Estimated increase of 1.5-2.0 percent after 4-6 years following a two standard deviation shock. - With only the two standard deviations shock, the Philippines would achieve close to the average of ASEAN-6 and upper middle income emerging market peers for these reforms. - Combined first-generation package: - Could raise output by around 1.5 to 2 percent after 2 years. - Conditional on implementing all reforms simultaneously, output could increase by as much as 3 percent after four years. ### Impact of other (second-generation) reforms (credit market, labor market) - Credit market regulation reforms: - More gradual impact, with maximum impact around 4-6 years after the reform. - Estimated impact: 1.5-2.0 percent. - Labor market reforms: - Positive albeit not significant impact on employment, possibly due to high informality. - The two standard deviation shock from the model to credit reforms and labor markets would bring the Philippines above or very close to the median of ASEAN-6 and upper middle income emerging market peers. ### Policy recommendations and priority reform actions (Section 14) - Implement remaining first-generation reforms to remove bottlenecks constraining economic activity, including: - Investment in critical infrastructure: electrical grids, enhancing power supply through renewable energy investments, transport, digital infrastructure. - Reform business regulation and open the telecommunications sector to greater competition. - Improve maritime trade management: more efficient management of Philippine ports, lower shipping and customs clearance fees, and reduced freight charges. - Agriculture improvements: increased investment, improved access to credit and insurance, lower tariff and non-tariff barriers (e.g., through the 2019 Rice Tariffication Law), policies to address high vulnerability to multidimensional shocks, expand long term PPPs, value chain upgrading, and promote land consolidation. - Note: The Philippine Digital Infrastructure Project aims to boost connectivity in remote areas and improve cybersecurity. - Improve governance, particularly at the local government level: - Strengthen oversight of government-owned and controlled corporations and of PPPs; support by legislating the Progressive Budgeting for Better and Modernized Governance and the National Government Rightsizing Program. - Continue digitalization of the Public Financial Management (PFM) system, procurement processes, frontline services, and the courts. - Prioritize efforts to reduce corruption and improve contract and property rights enforcement. - Education and human capital reforms: - Boost learning outcomes and increase education attainment among lower income households. - Review basic education to strengthen foundational skills; expand technical and vocational training aligned with job market needs through PPPs. - Improve equitable access to tertiary education and provide lifelong learning opportunities for professional development. - Support recent initiatives developing opportunities for teachers and integrating technical and vocational education and training into senior high school curricula (State of the Nation Address, 2024). - Labor market reforms to increase female participation: - Increase childcare options, address social norms confining women to domestic roles, leverage work from home opportunities in the BPO sector and e-commerce. - Expand access to technical and vocational education in ICT and STEM-related fields. ### How reforms boost growth channels - First-generation reforms, plus boosting female employment and closing gender wage gaps, will: - Support greater crowding in of private sector investment and FDI. - Help boost the capital stock and TFP’s contribution to growth. - Increase labor productivity. - Given the Philippines’ demographic transition, improvements in education outcomes and skills training are critical in the near term to capitalize on a relatively younger population. ### Upside growth scenario and quantitative assumptions - Scenario result: The Philippines can reach 7.0-7.5 percent growth over a medium- to long-term horizon under the reform package. - Assumptions used in growth accounting: - Capital: Growth in capital services is assumed to rise 1.5 percentage points higher than its pre--pandemic average, reflecting greater crowding in of private and foreign investment following reforms to boost infrastructure investment. - Labor: Labor force participation rate is assumed to rise from 64.9 percent to 67 percent. - This could be achieved by increasing the female labor force participation rate from the current 50 percent to just under 60 percent. - TFP: Growth in TFP is assumed to rise to 1.8-2.0 percent per year (from 1.6 percent in the baseline). - Human capital: Assumed to rise such that the majority of the population would either finish secondary school or engage in upskilling or reskilling; requires simultaneous implementation of first-generation reforms that create productive opportunities. ### Data and measurement (indices and components) - Structural indices and variables draw from multiple sources (examples listed): - Trade regulations and barriers: Measure of Aggregate Trade Restrictions (MATR), IMF External sector reform index, OECD Trade Facilitation Performance Index, Taxes on International trade (% of revenues), Tariff rate (simple mean on all products). - External sector openness and trade structure: Economic openness, FDI (share of GDP), Hausman Complexity Outlook Index (COI), Herfindahl-Hirschman Prod. Concentration Index. - Governance: Control of Corruption, Government Effectiveness, Political Stability, Regulatory Quality, Rule of Law, Voice and Accountability; IMF Governance reform index. - Credit market regulation and financial inclusion: IMF Credit market regulation index, Domestic credit to private sector (% of GDP), Private credit by deposit money banks (% of GDP), Financial inclusion indicators. - Labor market: Unemployment rate, Labor force participation rate, weekly worked per employee, output per worker, share of informal employment, vulnerable employment. - Human capital: Primary school enrollment rate, compulsory education duration, share of 25+ that completed at least prim. education, adult literacy rate. - Business regulation and infrastructure: Mobile cellular subscriptions, Access to electricity, Access to drinking water, Logistics performance index. - Note on indices: The Governance reform index is a simple average of the six WGI indices. The External sector index averages four indicators on tariffs, non-tariff trade barriers, black-market exchange rate, and controls on movement of capital and people. The Credit Market regulation index comprises ownership of banks, size of private sector borrowing, interest rate controls. The Labor Market regulation index incorporates hiring and firing regulation and degree of centralized collective wage bargaining. The Business regulation index averages bureaucracy costs, administrative requirements, and impartial public administration. Except for the External sector index, subcomponents are sourced from the Fraser Institute and are scaled 0 to 1 (higher = higher degree of freedom). ### Priority summary for policy sequencing - Implement first-generation reforms (trade, business regulation, governance, human development) to remove immediate bottlenecks. - Scale up infrastructure investment via PPPs and green lanes to crowd in private and foreign investment. - Complement with second-generation reforms (credit market regulation, labor market measures to raise participation and formalization) to sustain medium-term growth. - Target education and skills reforms to ensure human capital gains translate into productivity improvements during the demographic window. *Source: POTENTIAL GROWTH AND DEMOGRAPHIC DIVIDEND (IMF staff prepared chapter; November 15, 2024).* --- ### SUPPLY- AND DEMAND-DRIVEN INFLATION: SECTORAL DECOMPOSITION FOR THE PHILIPPINES ### Objective and scope - Quantify the relative importance of supply- and demand-driven inflation in the Philippines using a sectoral decomposition. - Provide a high-frequency indicator applicable to new price data as published. - Assess robustness through alternative decomposition methodologies and examine reasons for the Philippines’ susceptibility to supply- and demand-driven inflation. ### Methodology: supply-demand decomposition (Shapiro (2022) approach) - Data: quarterly personal consumption expenditure (PCE) data for 12 categories/sectors. - Core premise: demand shifts move prices and quantities in the same direction along an upward-sloping supply curve; supply shifts move prices and quantities in opposite directions along a downward-sloping demand curve. - Estimation: - Sector-level vector autoregression (VAR) with one equation per variable. - For each expenditure item i, the vector y_it = (Δp_it, Δq_it) contains first differences in the (log) deflator (Δp_it) and real consumption (Δq_it). - Baseline specification uses H = 4 lags. - Residuals v_it = (v_it^p, v_it^q) are used to identify shocks. - Classification rule (following Shapiro (2022)): - An item is “demand driven” if v_it^p * v_it^q ≥ 0. - An item is “supply driven” if v_it^p * v_it^q < 0. - Aggregation: - Demand-driven inflation π_t^d = sum_{i ∈ D_t} ω_i,t π_i,t (weights ω_i,t are year-to-date expenditure shares). - Supply-driven inflation π_t^s = sum_{i ∈ S_t} ω_i,t π_i,t. - Aggregate inflation π_t = π_t^d + π_t^s. ### Methodological caveats and alternatives - Assumption: in any given period a sector is categorized as either demand- or supply-shocked; simultaneous shocks within a sector are not identified. - Persistence not explicitly identified: model distinguishes a persistent component via autoregressive terms and a surprise (residual) used for supply/demand identification, but does not separately identify persistent supply or demand drivers. - Alternative approaches (not used here) include SVARs with sign/narrative restrictions and principal component analyses that can identify multiple concurrent contributions and persistence but typically operate at aggregate rather than sectoral level. - Monthly-based persistence measures (e.g., identifying shocks lasting at least 11 consecutive months) are less applicable given quarterly data. ### Key results: aggregate and historical summary - Over the 23-year sample period: - Supply driven inflation accounted on average for 2.3 percentage points of the average 3.8 percent inflation rate. - Average share of supply driven inflation: 62 percent. - Supply-driven inflation has been more volatile on average than demand-driven inflation. - Episodes of global shocks (e.g., global recessions, commodity price shocks) generally overlapped with higher supply-driven inflation: - Global financial crisis (GFC) period: supply-driven inflation 5.4 percent versus demand-driven inflation 1.4 percent. - COVID pandemic period: inflation was mainly supply driven. ### Cross-country comparisons (selected Asia-Pacific and advanced economies) - Full-sample share of supply-driven inflation: - Australia and Korea: around 60 percent (similar to the Philippines). - New Zealand and Indonesia: around 40 percent. - Thailand: around 50 percent. - Post-pandemic surge: large share of inflation was supply driven in Australia, Korea, and New Zealand, suggesting a role for global supply constraints. - Country-specific factors: price subsidies, administered prices, and supply policies (especially for imported commodities like food or fuel) can affect both the level and share of supply-driven inflation. ### Role of external factors and global integration - Correlation between import deflator and supply-driven inflation from 2010-2023: 0.48. - Foreign content of final demand (2022): about 30 percent for the Philippines relative to most other Asia-Pacific countries. - Within total final demand, about 75 percent is consumption demand and the share of foreign content is approximately the same as in the aggregate. - Interpretation: significant exposure to global factors helps explain supply-driven pressures in Philippine inflation. ### Inflation volatility and supply-driven episodes - Inflation volatility tends to increase when inflation is supply driven. - Correlation between the annual standard deviation of headline CPI inflation and the share of supply-driven inflation: 33 percent. ### Demand-driven inflation and the output gap - Historical correlation between identified demand-driven inflation and the Philippines’ output gap (2001Q4-2023Q4): around 20 percent (notwithstanding measurement uncertainty). - Correlations during stress periods: - GFC period (2008Q1-2009Q2): 96 percent. - COVID and post-COVID commodity shock period (2020Q1-2023Q4): 50 percent. - Note: the correlation is not always positive (e.g., 2010-2012); it rises to 21 percent with one-quarter lagged inflation and declines below 20 percent with further lags. - Literature evidence: estimates of the Phillips Curve for the Philippines have flattened over time. ### Sectoral decompositions: food, goods, and services - Food: - Food comprises 38 percent of the overall CPI basket. - Decomposition shows supply factors were a large driver of aggregate food inflation during episodes of high overall inflation. - Recent episode drivers: global supply chain disruptions and food-related protectionist measures raised costs of transporting and importing food, contributing significantly to high food inflation. - Cross-country patterns: food inflation largely supply driven in Australia, New Zealand, and Korea during post-pandemic and GFC periods; Indonesia and Thailand saw more demand-driven food inflation in the most recent period. - Goods and services: - Decompositions for goods and services are provided sectorally; the Philippines’ goods and services inflation include notable supply-driven components during major global shocks. ### Goods versus services inflation: key findings - Goods inflation in the Philippines has been more balanced between supply and demand, especially during high inflation episodes. - During the pandemic, supply drivers accounted for most of goods inflation, while demand factors were also present in the post-pandemic period, possibly due to pent-up demand. - Services inflation in the Philippines has been almost entirely demand driven and this pattern holds for most other countries in Asia-Pacific. - Services have limited import content and are largely produced with domestic factors, making them less vulnerable to global supply shocks that drive supply-driven inflation. ### Alternative decompositions: overview and findings - Chau, Conesa, Kim, and Spray (2024) decomposition: - Uses sectoral producer price inflation (PPI) and input-output linkages; Bartik shift-share design; data up to 2022. - Finds lock-down induced supply shocks along with fiscal and monetary policy would have pushed inflation higher than observed if not for a lower demand factor. - In the post-pandemic period: rebound in demand helped push inflation higher while lock-down induced supply factors unwound and producer price pressures eased. - Caveats: uses PPI (manufactured goods) whereas consumer food inflation (a strong supply component) is less present in PPI; model PPI inflation does not exactly match actual inflation. - Other approaches: - Redl (2023) applies Shapiro-like method to the GDP deflator and finds a larger role for demand factors. - Guo, Karam, and Vlcek (2019) use a semi-structural model and find the elevated inflation period in 2018 was mainly supply driven due to commodity-price shocks, with demand and monetary policy also important. ### Conclusion and policy implications - Multiple methods consistently find an important role for supply-driven inflation in the Philippines. - Supply-driven inflation stems mainly from supply-driven inflation in food and goods, whereas services inflation is more demand driven. - Empirical evidence (Firat and Hao, 2023) suggests: - Supply-driven inflation tends to be more responsive to external factors such as oil shocks and supply chain pressures. - Demand-driven inflation exhibits a more pronounced response to monetary policy shocks. - Policy implications and open questions: - These distinctions have significant implications for effective policy design and central bank communication. - Important questions remain about the optimal inflation target and the estimation and impact of second-round effects when aggregate inflation is supply driven. - It is unclear whether “looking through” supply shocks is optimal for central banks in a world with more severe and frequent supply shocks (for instance due to climate change and geopolitics), because this could change how firms and households form inflation expectations. *Source: IMF staff estimates and analysis as presented in the chapter.* ### References ____________________________________________________________________________ 15 ### POTENTIAL GROWTH AND DEMOGRAPHIC DIVIDEND ### Recent Developments - Real GDP fell by 9.5 percent in 2020 due to COVID-19; unemployment rose to 10.3 percent in 2020. - Recovery: real GDP growth peaked at 7.6 percent in 2022 and moderated to 5.5 percent in 2023. - Unemployment averaged 4.4 percent in 2023. - Labor productivity remains below pre-pandemic trends despite employment recovering; productivity particularly weak in agriculture and below pre-pandemic level in services. - Under current policy settings, medium-term potential growth is estimated at 6.0-6.3 percent. - An upside scenario with ambitious, well-sequenced structural reforms could raise growth to 7.0-7.5 percent over a longer horizon. ### Demographic Trends - By end-2024, the Philippines' dependency ratio (population ages 0-14 plus 65+ divided by population 15-64) is projected to fall below 50 percent. - Working-age population projected to continue growing until around 2045 (UN population forecasts). - Between 2060 and 2070 the dependency ratio is expected to exceed 50 percent, with national population beginning to decline around 2060. - Job creation requirement to harvest dividend: at least 12 million new jobs between now and 2050, or about 450 thousand per year. - Historical context: during 2005-2019 the Philippines created on average 700 thousand jobs per year. - If labor force participation rises (particularly female participation), the number of jobs needed would increase. ### Structural Gaps (Benchmarking and Findings) - Benchmarking against ASEAN-6, G20 EMs, and OECD-EMs across eight dimensions: trade regulation and barriers; business regulation and infrastructure; economic complexity and openness; credit market regulation and financial inclusion; governance; labor markets; human capital; human development, health, and demographics. - Indicators normalized 0 to 1 (higher = better); gaps computed relative to comparator group median. - Key structural shortfalls identified: - Trade: less open than OECD EMs on trade restrictions, trade facilitation, and external sector regulation reform. - Business environment and infrastructure: lags on economic openness, business regulation reform, electricity access, and logistics. - Digital infrastructure: fixed broadband cost about four times higher than in Vietnam and more than twice the Southeast Asia average (World Bank). - Education infrastructure: facility and equipment gaps reduce learning opportunities. - Physical infrastructure: road gaps, especially in poor or remote communities. - Financial markets: credit provision and financial market regulation operate at least as well as, or better than, upper-middle-income countries but less well than ASEAN peers. ### Trade Openness and Investment Environment - Philippines ranks middle among ASEAN peers on most trade openness measures but trails OECD EMs. - Authorities identify maritime shipping as an area for cost and ease-of-doing-business improvements. - Ongoing policy efforts include legislative reforms, PPPs for physical and digital infrastructure, and green lanes to fast-track strategic investment. ### Governance - Gaps relative to ASEAN peers in anti-corruption, legal system, regulatory quality, and rule of law. - Performs better than G20EM countries and relatively closer to peers on regulatory quality, accountability, and effectiveness. - Strengthening anti-corruption, legal certainty, regulatory quality, and rule of law would support private investment through fair contract enforcement and property rights protection. ### Labor Markets and Human Capital Development - Labor market regulations are relatively pro-growth, but labor productivity and labor force participation lag. - Female labor force participation lags male participation by almost 20 percent. - Women in paid jobs earn more on average than men, reflecting higher tertiary education and concentration in high-skill jobs; when accounting for human capital differences the gender wage gap rises to close to 30 percent in favor of men. - Education outcomes: primary and higher education completion compare favorably to ASEAN and G20EM peers, but learning outcomes are weak and were further hurt by the pandemic. - Share of population with secondary education remains low and heavily skewed to the wealthiest decile; skills mismatch between graduates and employer demands persists. ### Potential Growth: Methodology and Projections - Potential growth estimated using the production function approach with a Cobb-Douglas specification. - Data: Penn World Table (PWT) 10.0 (latest observation 2019); 2020-2023 data from PSA, Haver, World Bank WDI, and UN Population Projections. - Baseline assumptions for projection period: - Capital: historical elasticity between capital service growth and capital stock growth used; capital stock based on WEO projections for fixed capital investment and a 2 percent depreciation rate; capital share set to 0.5 (2019 PWT). - Labor: effective labor = employment × hours worked; PSA working-age population projections through 2023; assumed labor force participation rate and employment rate equal to their 2023 values (64.9 percent and 95.7 percent, respectively); hours worked projected to reverse pandemic decline in medium term; labor share set to 0.5 (2019 PWT). - TFP: historical relationship between TFP and labor productivity estimated; elasticities applied to projected labor productivity (based on projected employment growth and WEO nominal GDP) with adjustors for planned investments expected to affect TFP. - Human capital: proxied by years of schooling following PWT method with assumed rate of return (Psacharopouls (1994) and Caselli (2005)); years of schooling assumed to rise by 1.5 years from the 2019 value of 8.9 years through the medium term. - Medium-term potential growth estimated at 6.0-6.3 percent (down from pre-pandemic estimate of 6.5 percent) due to pandemic scarring, slow labor productivity recovery, and long-lasting education impacts. - Contribution details: - Capital services contribution peaked in the five years prior to the pandemic at around 4½ percentage points. - Capital's contribution expected to gradually rise to about 3.3 percent by the medium term given current investment projections. - Labor contribution: pre-pandemic average contribution was 1.1 percentage points; projected to be around the same in the medium term. - Human capital contribution slightly higher due to assumed longer years of schooling. - TFP contribution expected to be 1.6 percentage points versus 1.0 percentage points in the five years pre-pandemic, reflecting assumed improvements in public infrastructure, digitalization, and greater foreign investment. ### Policy Implications and Reform Priorities (Objectives reflected in source) - Close structural gaps to harness demographic dividend and boost potential growth toward the upside scenario (7.0-7.5 percent). - Strengthen areas identified in benchmarking: - Trade facilitation and reduction of tariff and non-tariff barriers. - Business regulation reform, logistics, electricity access, and digital infrastructure cost and coverage. - Education quality improvements, addressing facility and equipment gaps, and reducing skills mismatches. - Anti-corruption measures, legal system enhancements, regulatory quality, and rule of law to foster private investment. - Policies to raise female labor force participation and reduce underemployment to increase labor contribution to growth. - Leverage PPPs and green lanes to crowd in private investment and boost capital’s contribution to growth. *Source: POTENTIAL GROWTH AND DEMOGRAPHIC DIVIDEND (IMF staff prepared chapter; November 15, 2024).* ### 14. This section examines how structural reforms could support achieving the Philippine ### 14. This section examines how structural reforms could support achieving the Philippine ### Objective and approach - Aim: Support the Philippine authorities’ growth target for 2026-28 of 6.5-8.0 percent. - Method: Use estimates from IMF (2024) and Budina and others (2023) of potential gains in output from major structural reforms. Reforms considered include external sector, business regulation, governance, labor market, credit market regulation, and human development. - Estimation note: Estimates are from local projections models which regress either real GDP at Purchasing Power Parity or employment (for labor market regulation) on aggregate reform indices constructed as averages of sub-variables. Major reforms are defined as episodes with an improvement in the relevant indicator of at least two standard deviations. Sample covers 1996-2022 and includes AE and EM countries. ### Impact of first-generation reforms (governance, human development, external sector, business regulation) - Governance and human development (when implemented alone): - Governance: increase of around 1 percent following a two standard deviation shock to the reform index. - Human development: increase of around 5 percent following a two standard deviation shock to the reform index. - Given the Philippines’ initial conditions, the country would need a shock 2-3 times this size to catch up to ASEAN-6 and emerging market peers in these categories. - External sector and business regulation: - Estimated increase of 1.5-2.0 percent after 4-6 years following a two standard deviation shock. - With only the two standard deviations shock, the Philippines would achieve close to the average of ASEAN-6 and upper middle income emerging market peers for these reforms. - Combined first-generation package: - Could raise output by around 1.5 to 2 percent after 2 years. - Conditional on implementing all reforms simultaneously, output could increase by as much as 3 percent after four years. ### Impact of other (second-generation) reforms (credit market, labor market) - Credit market regulation reforms: - More gradual impact, with maximum impact around 4-6 years after the reform. - Estimated impact: 1.5-2.0 percent. - Labor market reforms: - Positive albeit not significant impact on employment, possibly due to high informality. - The two standard deviation shock from the model to credit reforms and labor markets would bring the Philippines above or very close to the median of ASEAN-6 and upper middle income emerging market peers. ### Policy recommendations and priority reform actions - Implement remaining first-generation reforms to remove bottlenecks constraining economic activity, including: - Investment in critical infrastructure: electrical grids, enhancing power supply through renewable energy investments, transport, digital infrastructure. - Reform business regulation and open the telecommunications sector to greater competition. - Improve maritime trade management: more efficient management of Philippine ports, lower shipping and customs clearance fees, and reduced freight charges. - Agriculture improvements: increased investment, improved access to credit and insurance, lower tariff and non-tariff barriers (e.g., through the 2019 Rice Tariffication Law), policies to address high vulnerability to multidimensional shocks, expand long term PPPs, value chain upgrading, and promote land consolidation. - Note: The Philippine Digital Infrastructure Project aims to boost connectivity in remote areas and improve cybersecurity. - Improve governance, particularly at the local government level: - Strengthen oversight of government-owned and controlled corporations and of PPPs; support by legislating the Progressive Budgeting for Better and Modernized Governance and the National Government Rightsizing Program. - Continue digitalization of the Public Financial Management (PFM) system, procurement processes, frontline services, and the courts. - Prioritize efforts to reduce corruption and improve contract and property rights enforcement. - Education and human capital reforms: - Boost learning outcomes and increase education attainment among lower income households. - Review basic education to strengthen foundational skills; expand technical and vocational training aligned with job market needs through PPPs. - Improve equitable access to tertiary education and provide lifelong learning opportunities for professional development. - Support recent initiatives developing opportunities for teachers and integrating technical and vocational education and training into senior high school curricula (State of the Nation Address, 2024). - Labor market reforms to increase female participation: - Increase childcare options, address social norms confining women to domestic roles, leverage work from home opportunities in the BPO sector and e-commerce. - Expand access to technical and vocational education in ICT and STEM-related fields. ### How reforms boost growth channels - First-generation reforms, plus boosting female employment and closing gender wage gaps, will: - Support greater crowding in of private sector investment and FDI. - Help boost the capital stock and TFP’s contribution to growth. - Increase labor productivity. - Given the Philippines’ demographic transition, improvements in education outcomes and skills training are critical in the near term to capitalize on a relatively younger population. ### Upside growth scenario and quantitative assumptions - Scenario result: The Philippines can reach 7.0-7.5 percent growth over a medium- to long-term horizon under the reform package. - Assumptions used in growth accounting: - Capital: Growth in capital services is assumed to rise 1.5 percentage points higher than its pre--pandemic average, reflecting greater crowding in of private and foreign investment following reforms to boost infrastructure investment. - Labor: Labor force participation rate is assumed to rise from 64.9 percent to 67 percent. - This could be achieved by increasing the female labor force participation rate from the current 50 percent to just under 60 percent. - TFP: Growth in TFP is assumed to rise to 1.8-2.0 percent per year (from 1.6 percent in the baseline). - Human capital: Assumed to rise such that the majority of the population would either finish secondary school or engage in upskilling or reskilling; requires simultaneous implementation of first-generation reforms that create productive opportunities. ### Data and measurement - Structural indices and variables draw from multiple sources (examples): - Trade regulations and barriers: Measure of Aggregate Trade Restrictions (MATR), IMF External sector reform index, OECD Trade Facilitation Performance Index, Taxes on International trade (% of revenues), Tariff rate (simple mean on all products). - External sector openness and trade structure: Economic openness, FDI (share of GDP), Hausman Complexity Outlook Index (COI), Herfindahl-Hirschman Prod. Concentration Index. - Governance: Control of Corruption, Government Effectiveness, Political Stability, Regulatory Quality, Rule of Law, Voice and Accountability; IMF Governance reform index. - Credit market regulation and financial inclusion: IMF Credit market regulation index, Domestic credit to private sector (% of GDP), Private credit by deposit money banks (% of GDP), Financial inclusion indicators. - Labor market: Unemployment rate, Labor force participation rate, weekly worked per employee, output per worker, share of informal employment, vulnerable employment. - Human capital: Primary school enrollment rate, compulsory education duration, share of 25+ that completed at least prim. education, adult literacy rate. - Business regulation and infrastructure: Mobile cellular subscriptions, Access to electricity, Access to drinking water, Logistics performance index. - Note on indices: The Governance reform index is a simple average of the six WGI indices. The External sector index averages four indicators on tariffs, non-tariff trade barriers, black-market exchange rate, and controls on movement of capital and people. The Credit Market regulation index comprises ownership of banks, size of private sector borrowing, interest rate controls. The Labor Market regulation index incorporates hiring and firing regulation and degree of centralized collective wage bargaining. The Business regulation index averages bureaucracy costs, administrative requirements, and impartial public administration. Except for the External sector index, subcomponents are sourced from the Fraser Institute and are scaled 0 to 1 (higher = higher degree of freedom). *Italic: Source — 1phlea2024002-print-pdf - 14. This section examines how structural reforms could support achieving the Philippine* ### 3. Against this background, this note seeks to quantify the relative importance of supply- ### 3. Against this background, this note seeks to quantify the relative importance of supply- and demand-driven inflation in the Philippines ### Objective and scope - Quantify the relative importance of supply- and demand-driven inflation in the Philippines using a sectoral decomposition. - Provide a high-frequency indicator applicable to new price data as published. - Assess robustness through alternative decomposition methodologies and examine reasons for the Philippines’ susceptibility to supply- and demand-driven inflation. ### Methodology: supply-demand decomposition - Approach: Shapiro (2022) methodology applied to quarterly personal consumption expenditure (PCE) data for 12 categories/sectors. - Core premise: demand shifts move prices and quantities in the same direction along an upward-sloping supply curve; supply shifts move prices and quantities in opposite directions along a downward-sloping demand curve. - Estimation: - Sector-level vector autoregression (VAR) with one equation per variable. - For each expenditure item i, the vector y_it = (Δp_it, Δq_it) contains first differences in the (log) deflator (Δp_it) and real consumption (Δq_it). - Baseline specification uses H = 4 lags. - Residuals v_it = (v_it^p, v_it^q) are used to identify shocks. - Classification rule (following Shapiro (2022)): - An item is “demand driven” if v_it^p * v_it^q ≥ 0. - An item is “supply driven” if v_it^p * v_it^q < 0. - Aggregation: - Demand-driven inflation π_t^d = sum_{i ∈ D_t} ω_i,t π_i,t (weights ω_i,t are year-to-date expenditure shares). - Supply-driven inflation π_t^s = sum_{i ∈ S_t} ω_i,t π_i,t. - Aggregate inflation π_t = π_t^d + π_t^s. ### Methodological caveats and alternatives - Assumption: in any given period a sector is categorized as either demand- or supply-shocked; simultaneous shocks within a sector are not identified. - Persistence not explicitly identified: model distinguishes a persistent component via autoregressive terms and a surprise (residual) used for supply/demand identification, but does not separately identify persistent supply or demand drivers. - Alternative approaches (not used here) include SVARs with sign/narrative restrictions and principal component analyses that can identify multiple concurrent contributions and persistence but typically operate at aggregate rather than sectoral level. - Monthly-based persistence measures (e.g., identifying shocks lasting at least 11 consecutive months) are less applicable given quarterly data. ### Key results: aggregate and historical summary - Over the 23-year sample period: - Supply driven inflation accounted on average for 2.3 percentage points of the average 3.8 percent inflation rate. - Average share of supply driven inflation: 62 percent. - Supply-driven inflation has been more volatile on average than demand-driven inflation. - Episodes of global shocks (e.g., global recessions, commodity price shocks) generally overlapped with higher supply-driven inflation: - Global financial crisis (GFC) period: supply-driven inflation 5.4 percent versus demand-driven inflation 1.4 percent. - COVID pandemic period: inflation was mainly supply driven. ### Cross-country comparisons (selected Asia-Pacific and advanced economies) - Full-sample share of supply-driven inflation: - Australia and Korea: around 60 percent (similar to the Philippines). - New Zealand and Indonesia: around 40 percent. - Thailand: around 50 percent. - Post-pandemic surge: large share of inflation was supply driven in Australia, Korea, and New Zealand, suggesting a role for global supply constraints. - Country-specific factors: price subsidies, administered prices, and supply policies (especially for imported commodities like food or fuel) can affect both the level and share of supply-driven inflation. ### Role of external factors and global integration - Correlation between import deflator and supply-driven inflation from 2010-2023: 0.48. - Foreign content of final demand (2022): about 30 percent for the Philippines relative to most other Asia-Pacific countries. - Within total final demand, about 75 percent is consumption demand and the share of foreign content is approximately the same as in the aggregate. - Interpretation: significant exposure to global factors helps explain supply-driven pressures in Philippine inflation. ### Inflation volatility and supply-driven episodes - Inflation volatility tends to increase when inflation is supply driven. - Correlation between the annual standard deviation of headline CPI inflation and the share of supply-driven inflation: 33 percent. ### Demand-driven inflation and the output gap - Historical correlation between identified demand-driven inflation and the Philippines’ output gap (2001Q4-2023Q4): around 20 percent (notwithstanding measurement uncertainty). - Correlations during stress periods: - GFC period (2008Q1-2009Q2): 96 percent. - COVID and post-COVID commodity shock period (2020Q1-2023Q4): 50 percent. - Note: the correlation is not always positive (e.g., 2010-2012); it rises to 21 percent with one-quarter lagged inflation and declines below 20 percent with further lags. - Literature evidence: estimates of the Phillips Curve for the Philippines have flattened over time. ### Sectoral decompositions: food, goods, and services - Food: - Food comprises 38 percent of the overall CPI basket. - Decomposition shows supply factors were a large driver of aggregate food inflation during episodes of high overall inflation. - Recent episode drivers: global supply chain disruptions and food-related protectionist measures raised costs of transporting and importing food, contributing significantly to high food inflation. - Cross-country patterns: food inflation largely supply driven in Australia, New Zealand, and Korea during post-pandemic and GFC periods; Indonesia and Thailand saw more demand-driven food inflation in the most recent period. - Goods and services: - Decompositions for goods and services are provided sectorally; the Philippines’ goods and services inflation include notable supply-driven components during major global shocks (visualized in Figures 13 and 14). *Source: IMF staff estimates and analysis as presented in the chapter.* ### 16. Goods inflation in the Philippines has been more balanced between supply and ### 16. Goods inflation in the Philippines has been more balanced between supply and demand ### Goods versus services inflation: key findings - Goods inflation in the Philippines has been more balanced between supply and demand, especially during high inflation episodes. - During the pandemic, supply drivers accounted for most of goods inflation, while demand factors were also present in the post-pandemic period, possibly due to pent-up demand (Figure 13). - Services inflation in the Philippines has been almost entirely demand driven and this pattern holds for most other countries in Asia-Pacific (Figure 14). - Services have limited import content and are largely produced with domestic factors, making them less vulnerable to global supply shocks that drive supply-driven inflation. ### Alternative decompositions: overview and purpose - Alternative decomposition approaches are used to assess robustness and provide additional insights into inflation drivers in the Philippines. - The method of Chau, Conesa, Kim, and Spray (2024) decomposes sectoral producer price inflation (PPI) and identifies separate roles for fiscal and monetary policy, in addition to supply and demand factors. - That method uses: - A harmonized dataset of sectoral producer price inflation and input-output linkages for more than 1000 sectors in 53 countries. - A Bartik shift-share design where shares reflect heterogeneous sectoral exposure to shocks and are derived from a macroeconomic model of international production networks. - Data for the Chau et al. exercise is available up to 2022. ### Findings from the Chau et al. (2024) alternative decomposition - The decomposition indicates that lock-down induced supply shocks along with both fiscal and monetary policy would have pushed inflation higher than observed if not for a lower demand factor (Figure 15). - In the post-pandemic period: - The rebound in demand helped push inflation higher, likely due to pent-up demand amid reopening. - Lock-down induced supply factors had an offsetting effect as they unwound, and producer price pressures eased. - Caveats noted in interpreting these results: - This exercise uses producer prices while earlier analyses used consumer prices. Recent aggregate inflation has been driven largely by food (consumer price category) which is supply-driven; this strong supply-side component is less present in PPI, which largely covers manufactured goods. - The model’s estimated PPI inflation has not followed actual inflation exactly (Figure 15), so there may be some degree of error in decomposition components. - The Chau et al. model performs well at the global level and for major economies (United States, India, Germany, and China). See Chau and others (forthcoming) for further details. ### Other decomposition approaches and comparisons - Redl (2023) applies a version of the Shapiro (2022) method to the GDP deflator rather than PCE inflation; results (Figure 16) show a larger role for demand factors. - The GDP deflator does not cover the price of imports, unlike PCE inflation; the deflator being more demand driven is consistent with external supply factors being an important driver of PCE inflation. - Guo, Karam, and Vlcek (2019) use a semi-structural model to classify shocks as supply or demand and find that the elevated inflation period in 2018 was mainly driven by supply factors associated with commodity-price shocks, while demand factors and monetary policy intervention also played important roles. ### Conclusion and policy implications - Multiple methods consistently find an important role for supply-driven inflation in the Philippines. - Supply-driven inflation stems mainly from supply-driven inflation in food and goods, whereas services inflation is more demand driven, reflecting both demand and supply factors. - Empirical evidence (Firat and Hao, 2023) suggests: - Supply-driven inflation tends to be more responsive to external factors such as oil shocks and supply chain pressures. - Demand-driven inflation exhibits a more pronounced response to monetary policy shocks. - Policy implications and open questions: - These distinctions have significant implications for effective policy design and central bank communication. - Important questions remain about the optimal inflation target and the estimation and impact of second-round effects when aggregate inflation is supply driven. - It is unclear whether “looking through” supply shocks is optimal for central banks in a world with more severe and frequent supply shocks (for instance due to climate change and geopolitics), because this could change how firms and households form inflation expectations. *Source: IMF staff estimates, Chau, Conesa, Kim, and Spray (2024) methodology and related IMF analyses (data available up to 2022).* --- _Source: https://www.imf.org/-/media/files/publications/cr/2024/english/1phlea2024002-print-pdf.pdf_