## 1. ANZIMF – The Australia-New Zealand Integrated Monetary and Fiscal Model ## Source details **Canonical URL:** [1. ANZIMF – The Australia-New Zealand Integrated Monetary and Fiscal Model](https://www.imf.org/-/media/files/publications/cr/2018/cr1845.pdf) ## Other formats - [Markdown version](/-/media/files/publications/cr/2018/cr1845.pdf.md) - [Structured JSON version](/-/media/files/publications/cr/2018/cr1845.pdf.json) --- ### Overview and purpose - Examines risks to China during its transition to a services-driven, consumer-led economy and focuses on spillovers to Australia. - Uses ANZIMF, a version of the IMF’s GIMF: a micro-founded, overlapping generations dynamic stochastic general equilibrium (DSGE) model with detailed bilateral trade flows and two additional sectoral distinctions: services (tourism and education) and metals and coal. - Analytical emphasis: real GDP in Australia shows only small changes across scenarios, while substantial shifts occur in the composition of GDP (between domestic and external demand, and across sectors). ### Model structure and key mechanisms - Multi-region, annual, micro-founded general equilibrium model with seven regions: Australia, New Zealand, China, Advanced Asia, Emerging Asia, the United States, and a bloc of remaining countries. - Sectors explicitly modeled: coal/iron ore/metals and tourism/education services. - Consumption: - Two household types: saving households and liquidity-constrained (LIQ) households. - Saving households: OLG framework (Blanchard (1985), Weil (1989), Yaari (1962)); treat government bonds as wealth → non-Ricardian; endogenizes long-term global real interest rate. - LIQ households: consume all income each period, amplifying short-term non-Ricardian dynamics. - Investment: - Private investment follows the Bernanke-Gertler-Gilchrist (1999) financial accelerator; firms face monitoring costs and corporate risk premia are endogenously determined. - Nominal-real linkages: - Core price: CPI; wage inflation drives CPI inflation implicitly. - Monetary policy: inflation-forecast-targeting regime using an interest rate reaction function reliant on expected inflation. - Fiscal policy: detailed government sector aims to maintain a debt target (expressed as a deficit target) using at least one of seven instruments (government consumption, infrastructure spending, lump-sum transfers, targeted LIQ transfers, GST, PIT, CIT). - Trade, commodities, and services: - Bilateral trade reacts to demand, supply, terms of trade, and bilateral real exchange rates. - Commodities: coal, iron ore, other minerals; short- and long-term price elasticities of supply = 0.05. - Services: tourism (travel, accommodation, food services) and education; services exclusively part of consumption and relatively inelastic vis-à-vis consumption goods. - Key calibration/assumptions: - All agents have perfect foresight. - Non-linearities in financial accelerator; otherwise approximately linear for small shocks. - Baseline calibration uses parameter values consistent with 2015 for major ratios to GDP and 2015–2016 for services data. - Real exchange rate is a “jumper” adjusting immediately in the first year following forward-looking, risk-adjusted uncovered interest rate parity. - China: flexible exchange rate with no capital controls. - No substantial financial market channels beyond the financial accelerator; complete domestic ownership of firms; all net foreign asset positions denominated in U.S. dollars. - Annual frequency model; reduced within-year investment detail. ### Table of selected key ratios (as presented) - Share of Global GDP (%) — Australia: 2.1; China: 10.3; Other Asia: 16.0 - Domestic Demand (Percent of GDP) — Household Consumption: 57.253.5 59.0 - Domestic Demand — Private Investment: 20.025.0 20.1 - Domestic Demand — Government Absorption: 22.8 24.0 21.0 - Trade (Percent of GDP) — Non-Commodity Exports: 13.225.7 29.6 - Trade — Final Goods: 5.018.416.3 - Trade — Consumption Services: 3.5 2.0 2.6 - Trade — Intermediate Goods: 4.8 5.2 10.8 - Trade — Non-Commodity Imports: 22.2 23.3 28.6 - Trade — Final Goods (imports): 13.9 9.2 12.7 - Trade — Consumption Services (imports): 2.6 2.6 1.9 - Trade — Intermediate Goods (imports): 5.7 11.5 14.0 - Net Commodities: 9.0 -2.4 -1.0 - Partner 2/ (Net Commodities by partner): 5.3 -1.1 -0.5 ### Stylized facts on Australia–China linkages - Linkages driven by China’s demand for commodities (coal and iron ore used in intermediate industries like steel) and services (tourism and education). - Australia expanded iron ore and coal production capacity after the mining investment boom; services (tertiary education, tourism) continue to expand. ### Scenario design (three illustrative macro scenarios) — high-level descriptions - Upside Scenario 1 — Increased services demand in China (upside for Australia): - Households substitute away from saving toward consumption; government reforms boost productivity. - Australia’s service sector benefits; other Australian sectors can be disadvantaged by higher Chinese productivity. - Takeaway: Shock structure in China matters as much as outcome for Australian spillovers. - Upside Scenario 2 — Increased foreign commodities demand from China (upside for Australia): - China restricts domestic production of iron ore, coal and associated goods while demand remains strong. - Australia exports more commodities; mild slowdown in Chinese growth triggers mild contraction elsewhere in Australia, driven mainly by an Australian dollar appreciation. - Takeaway: Australia’s flexible exchange rate and diversified economy moderate shocks. - Downside Scenario — Disorderly rebalancing in China (downside for Australia): - Rebalancing derailed: broad-based slowdown, lower productivity, weaker steel activity, lower housing prices, increased corporate risk. - Australia’s net commodity exports fall, with rebalancing between domestic and external demand and among trading partners that can stimulate Australia’s exports and services on net. - Takeaway: Interactions across commodities sector and multiple trading partners produce unexpected feedback effects. ### Four principal takeaways from scenarios - Small changes in Australia’s real GDP can mask large shifts in demand composition (domestic vs external) and sectoral composition (commodities, services, other tradables, nontradables). - For a services-driven shock in China, identifying shock components is crucial to interpret Australian spillovers. - For a commodities-driven shock, Australia’s flexible exchange rate and diversified economy act as important buffers. - For a disorderly Chinese rebalancing, Australia’s outcomes depend on interactions across multiple trading partners beyond China alone. ### Detailed scenario results (selected exact figures) Upside Scenario 1 — Higher Chinese Household Spending on Tourism and Education - China direct effects: - Private saving decline: 1 percent of GDP. - China’s REER appreciation: 1.5 percent (immediate). - Consumption: 1 percent higher relative to baseline. - Trade and China imports: - Imports of services increase about 7 percent in the medium term and settle at 4 percent in the long term (about half of the increase in consumption). - Spillovers to Australia: - Australia’s services exports grow by 2 percent in the first five years; long-term supply effect 0.9 percent. - Australia’s REER: depreciates slightly by 0.2 percent followed by a 0.2 percent long-term appreciation. - Short-term Australian final exports increase about 0.45 percent; intermediate goods almost 0.3 percent. - Long-term Australian final and intermediate exports each decline about 0.4 percent relative to baseline. - Short-term consumption: 0.2 percent lower; long term 0.1 percent higher. - Australian real GDP: less than 0.1 percent higher short term → -0.1 percent in the long term relative to baseline. - Current account: unambiguously stronger, primarily due to services exports. Upside Scenario 2 — Improved Opportunities for Foreign Commodities Suppliers in China - China direct effects: - Steel capacity reduced by 10 percent (about -0.4 percent of GDP). - Domestic supply of coal and iron ore reduced by 5 percent. - Global commodity price rises by 3 percent permanently (with higher short-term increases). - China real GDP permanently lowered by 0.6 percent; consumption falls about 1 percent. - China’s REER depreciates permanently. - Spillovers to Australia: - China demand for tourism and education services falls by about 1.2 percent permanently; imports decline slightly more. - Australia’s services exports decline by 1.5 percent. - Australia’s REER appreciates by 0.7 percent on impact and 0.5 percent in the long term. - Net commodity exports rise in value; initial supply increase is short lived. - Increased commodity wealth allows permanently higher consumption in Australia. - Overall Australian real GDP slightly lower, with a compositional shift: stronger domestic (commodity) sector but weaker external sector from lower services exports. Downside Scenario — A Disorderly Rebalancing in China - China shocks and outcomes: - Productivity growth lower by 1 percent of GDP over 5 years (productivity shock equals 1 percent of GDP over 5 years). - Commodities demand reduced permanently by 10 percent. - Housing wealth falls by 10 percent permanently. - Corporate risk premium for SOEs increases permanently by 1 percent. - Short-term impact on growth: 2 percent worse-than-expected on impact. - China’s real GDP permanently 10 percent lower (4 percent lower on impact); 60 percent of the decline attributable to productivity revision. - Consumption falls by same amount as GDP; China’s REER appreciates. - Australia implications (selected figures from model figures and text): - Tourism and education services fall by about 10 percent in China; imports of these services decline by 6 percent on impact, 4 percent after 10 years, and 3 percent in the long term relative to baseline. - Domestic production of coal and iron ore declines by about 0.5 percent short term; long-term supply decline around 0.7 percent. - Global commodity price falls around 12 percent permanently. - Australian real GDP falls at first by about 0.4 percent and rebounds by an equivalent amount in the long term. - Australian net commodity exports as a share of GDP permanently decline by 1 percentage point in value terms. - Commodity supply declines by 0.7 percent in volume terms. - Services exports to China decline by roughly 3 percent. - Real final goods exports increase by 5 percent in the long term. - Real exports of intermediates increase by over 4 percent in the long term. - Australia’s REER depreciates by 3.5 percent. - Consumption almost 3 percent lower due to lower household wealth from weaker commodity prices and higher cost of imported goods. - Wealth transfer: from commodity exporters (Australia) to commodity importers; Australia’s household wealth loss exceeded only by China’s loss. ### Scenario dependencies and caveats - Outcomes conditional on: - Lack of financial contagion from China. - Unimpeded adjustment of China’s REER. - A scenario with substantial financial turmoil would dampen outcomes for Australia. ### Key scenario shock constructions (China-origin shocks) - Upside Scenario 1 (three shocks combined): - Lower private saving: permanent reduction of 1 percent of baseline GDP phased in over nine years. - Higher consumption of services: increased household bias to services over goods over 5 years (imports of tourism/education roughly half of aggregate consumption increase). - Higher productivity: permanent increase phased in over 25 years (starting in sixth year) yielding permanent 1 percent increase in real consumption with lower private saving. - Upside Scenario 2 (two shocks): - Lower commodity supply: permanent 5 percent reduction in domestic supply of commodities, phased over 3 years. - Decrease in steel supply: permanent 10 percent reduction in steel production (roughly -0.4 percent of GDP), phased over 3 years. - Downside Scenario (four shocks): - Lower productivity: permanent 5 percent reduction in tradables and nontradables productivity, phased as -2 percentage points in year 1 and -1 percentage point in years 2–4. - Lower commodities demand: permanent 10 percent reduction, phased -4 percentage points in year 1 and -2 percentage points in years 2–4. - Lower housing wealth: 10 percent decline on impact in year 1 in nontradable sector net worth. - Increased corporate risk premia: permanent 1 percentage point increase after a 2 percentage point increase on impact in year 1. --- ### Infrastructure investment gap and ANZIMF simulations — methodology and headline figures - Global Infrastructure Outlook (forecast period 25 years, starting 2016 → until 2040); covers seven sectors (roads, rail, airports, ports, electricity, telecoms, water) for 50 countries (>85 percent of global GDP). - Global infrastructure investment gap (2016–2040): 2015 US$94 trillion. - Gap as share against current trend investment extrapolated to 2040: 19 percent. - Average annual gap: 2015 US$3.7 trillion per year. - Implied desired global infrastructure spending as share of GDP: 3.5 percent, versus 3.0 percent now. - Australia overall gap (2016–2040): 10 percent of GDP. - Cumulative infrastructure investment needs for Australia: 2015 US$1.7 trillion. - Current cumulative trend spending for Australia: 2015 US$1.54 trillion. - Implied additional infrastructure investment spending for Australia: almost 0.4 percent of GDP per year until 2040. - Two most important Australian gaps (post-2018): rail (just over 0.1 percent of GDP per year) and ports (almost 0.15 percent of GDP per year). ### ANZIMF model elements relevant to infrastructure - Government absorption: exogenously determined government consumption and infrastructure investment that cumulates into infrastructure capital with permanent productivity effects. - Calibrated output elasticity of public capital: 0.122 (Bom and Ligthart, 2014). - Fiscal instruments: government consumption, infrastructure spending, lump-sum transfers, targeted LIQ transfers, GST, PIT, CIT. - PPP assumptions: competitively-tendered private firms build projects, recoup via committed future revenue streams; infrastructure assumed government-owned but privately maintained. ### Financing options simulated for closing Australia’s gap - Four financing variants to close the gap by 2040: - Deficit financing by Commonwealth and/or States/Territories. - Full financing by Commonwealth using personal income tax (PIT). - 50/50 financing: Commonwealth via PIT and States/Territories via goods and services tax (GST). - Funding by PPPs exclusively. ### Simulation results — selected exact figures and outcomes - Long-term: - Real GDP would be as much as 0.7 percent higher than otherwise in the long term. - Long-term multiplier: about 2. - Consumption: between 0.1 to 0.4 percent higher in the long term. - Real effective exchange rate: - Slight long-term depreciation with higher productivity; initial short-term appreciation when closing the gap stimulates demand and draws foreign saving. - Government debt dynamics: - Deficit financing causes a permanent 6.5 percent increase in the government debt to GDP ratio in the baseline run before accounting for growth effects. - Cumulative deficits required over 25 years: closer to 9.6 percent of GDP. - Growth from infrastructure investment reduces government debt to GDP ratio in the long term by 3.1 percentage points relative to counterfactual (after economic feedback). - PPP funding prevents the permanent 6.5 percent increase in debt-to-GDP, slightly reduces crowding out of private investment, and yields slightly higher long-term GDP gains relative to deficit financing. - Relative effectiveness: - Deficit financing and PPP funding provide greatest GDP gains overall. - Deficit financing most advantageous short term. - PPP funding slightly exceeds deficit financing in long term due to lower permanent government debt buildup and less crowding out. - PIT and/or GST financing reduce GDP gains; PIT financing alone reduces gains the most as PIT crowds out consumption and labor productivity. - Fiscal context: - FY2016/17 and FY2017/18 budgets increased those years’ spending on average 0.4 percent of GDP, closing the gap in 2016 and 2017; FY2017/18 budgets do not sustain increases past FY2019/20. - Gap construction uses IMF WEO April 2017 GDP forecasts and Global Infrastructure Outlook; gap set to zero for 2016 and 2017. ### Timing, acceleration, and alternative scenarios - Closing over 25 years (benchmark) or over 10 years (acceleration): - Accelerating to 10 years (phased from roughly 0.3 percent of GDP to 0.7 percent of GDP over four years): - Long-term real GDP gains around 0.8 percentage points (similar to benchmark long-term). - If PPPs used for part of acceleration, government debt accumulates 4 percent of GDP instead of 6.5 percent (difference vs deficit-financing only). - Short term: real GDP lifts much more rapidly; adds twice as much to growth over first 10 years relative to benchmark. - Deficit-financing only leads to greater crowding out of private business investment in first several years. - PPP funding avoids additional crowding out, allowing stronger consumption rise in first five years. - Practical constraints: not all projects can be compressed (e.g., western Sydney airport); economy must have spare capacity to absorb faster expansion (as of 2017 Australia had spare capacity). - Alternative Scenario 1 (quality): achieve Singapore infrastructure quality via conversion factor 1.38 → Real GDP almost 0.9 percent higher long term (additional ~one-third over benchmark) without additional government spending. - Alternative Scenario 2 (breadth): broaden gap to include structures and other inputs → Real GDP 0.8 higher long term (about a quarter over benchmark) but amplifies crowding out and weaker short-term GDP vs benchmark. ### Limitations and caveats - Uncertainty in pass-through from infrastructure investment and stock to productivity. - Model limitations inherent in ANZIMF/GIMF (e.g., under-responsiveness of trade flows). - Gap construction methodological concerns; technological innovations could change role/provision of infrastructure. - Closing the gap increases GDP which could change demand for infrastructure; feedback ignored in gap construction. --- ### Housing market developments, diagnosis, and policy responses — major findings Diagnosis of the Housing Boom - Regional concentration: - Boom concentrated in Sydney and Melbourne over past six years. - Inner-city apartments in Sydney and Melbourne integrated with global high-end real estate market. - Domestic and external drivers: - Boom broadly coincided with monetary easing cycle starting November 2011. - Narrowing of interest differentials across maturities lowered mortgage financing costs. - Population growth in Sydney and Melbourne above national rate of 1.5 percent. - Growing foreign investor interest, particularly from East Asia. - Valuation assessment: - Reduced-form house price equation (Igan and Loungani (2012)) suggests average house prices as of 2017Q3 are moderately stronger than fundamentals by some 5 percent to 15 percent (depending on specification). - Estimates based on national prices; local variation and estimation uncertainty exist. Price elasticity of housing supply in Australia — key quantitative results - Residential investment modeled via Tobin’s Q; econometric estimation 1988Q3–2017Q3. - Full-sample elasticities (national level): - Simple OLS: log(Housing prices/Construction Costs) coefficient = 0.593***. - DOLS(1,1): 0.551***. - DOLS(2,2): 0.528***. - Observations: 84 (OLS), 81 (DOLS(1,1)), 79 (DOLS(2,2)). - R-squared: 0.791, 0.808, 0.800 respectively. - Average national elasticity about 0.56. - Regional elasticities: - Sydney elasticity estimated at 0.21. - Melbourne elasticity estimated at 0.61. - Time variation: - Long-term price elasticity > 1 before 2000s; fell significantly between 2001-08 and 2012-14; recently increased again. - Supply constraints drivers: policy, planning, zoning, infrastructure provision/funding, land ownership patterns, geographic constraints, attitudes to density (Hsieh and others (2012)). Urbanization, housing supply, and growth - Australia urbanization: share in urban areas rose from 82 percent in 1960 to about 90 percent in 2016. - Five larger capital cities contributed ~two-thirds of national real GDP growth in the 1990s; in 2015-2016 this share increased to four-fifths. - Sydney and Melbourne house some two-fifths of population and generate more than half of value added. - Affordability tensions: agglomeration raises productivity/wages but limited land and high density raise housing prices and rents. - Prospects: demand shocks beginning late 2011 appear to have run course; population growth not expected to change after mid-/late-2000s increases; rebalancing away from mining likely nearly complete; affordability issues may persist. Policy response to housing market imbalances - Approach relied more on credit-supply (prudential) measures than some demand-side interventions. - Prudential measures (APRA/ASIC 2014–2017) sought to strengthen mortgage underwriting, cap interest-only lending flows, and cap investor lending growth. - Selected prudential/regulatory timeline and measures: - Late-2014: Prudential Practice Guide; supervisors alert to annual growth in investor housing lending above 10 percent; serviceability buffers at least 2 percentage points above effective variable rate; minimum floor assessment rate at least 7 percent. - Early-2015: APRA increased scrutiny of underwriting; strengthened household income definitions/discounts. - Early-2016: Countercyclical capital buffer (Basel III) into capital standards. - Late-2016: ASIC review of mortgage broker practices; formalized tightened standards on serviceability buffers and interest-only lending. - Early-2017: Limit on flow of new interest-only lending to 30 percent of new residential mortgage lending; strict internal limits for interest-only at LVR > 80 percent; scrutiny for LVR > 90 percent. - Early-2017: Lending to investors to remain below 10 percent growth benchmark. - Outcomes: - Share of riskier mortgages in new lending decreased. - Borrowers have built buffers; housing leverage (value of housing stock over mortgage debt) declined. - Banks more resilient with increased capital; four largest banks' capital adequacy in lower end of upper quartile internationally. - ASIC investigated interest-only loan responsible lending compliance (2014). Demand-side and tax policy considerations - Demand-side: first-time buyer relief (stamp duty exemptions and grants in NSW and Victoria from July 2017); foreign buyer stamp duty/land tax surcharges in Victoria, NSW, Queensland. - Foreign buyers: ~5 percent of housing sales nationwide (Kearns, 2017); in some local markets (new apartments in Melbourne and Sydney) foreign buyers may account for ~25 percent of sales. - Tax policy recommendations: - Replace stamp duties with systematic land tax on all residential and commercial properties to avoid transaction distortions; transition challenges acknowledged (stamp duties important State revenue). - Federal settings that encourage home ownership and leveraged investment noted: unlimited main residence capital gains tax exemption; 50 percent capital gains discount if owned >1 year; unlimited negative gearing. - Such incentives may encourage leveraged investment in upswings; other countries have more limited forms. Supply-side policies - Commonwealth and State measures to increase supply elasticity: - Release of federal land in Melbourne; Government Property Register to encourage alternative uses. - States changed zoning rules to allow higher density. - Increased infrastructure spending (precondition for developable land). - Streamlining zoning/planning/regulatory standards across councils/States recommended. Summary policy recommendation for housing - Multi-pronged approach: - Continue infrastructure investment and zoning/planning regulatory reform to increase developable land and enable efficient use. - Maintain prudential policies to manage financial-sector risks from housing. - Complement with housing tax reform to strengthen overall policy effectiveness. --- ### Australia’s current account prospects and macro trends — selected figures and findings - Historical current account: - Deficit around 1–2 percent of GDP in 1960s–1970s; widened from early 1980s averaging around 4 percent of GDP for ~3 decades. - Sharply decreased after GFC and again in 2016–17. - Phase drivers of narrowing: - Phase 1 (GFC to end of commodity price boom ~end 2011): narrowing from favorable terms of trade and higher non-financial corporate savings. - Phase 2 (post-2011): further narrowing mainly from real trade balance improvement due to end of mining investment boom and weaker consumption. - Five developments explaining narrowing: 1. Larger slowdowns in domestic demand growth vs major trading partners (domestic demand dropped around 7 percentage points in Australia vs 4 percentage points for weighted average of major trading partners during 2007–09). 2. Household saving ratios sharply increased around GFC. 3. Non-financial corporates reduced net borrowing; debt-to-equity ratio adjusted for price changes reduced by almost half. 4. Financial corporations increased saving; banks lowered dividend payouts from 60 percent to 40 percent of gross operating surplus. 5. Interest payments to non-residents fell from about 3 percent of GDP to 1.5 percent. - Projection: - Improvement in terms of trade in 2017 relative to previous year should result in a current account deficit of around 2 percent of GDP, given developments to 2017Q3. - Underlying current account deficit likely to remain lower than pre-GFC period. --- ### Inflation dynamics, Phillips-curve decomposition, and scenarios — core results and numerical specifics - Background: - Headline CPI inflation below target range 2-3 percent for nearly three years; core goods inflation weaker than core services; tradable inflation particularly weak. - Component means: - Core goods sample mean: 1.9 percent (1992Q1-2017Q1). - Core services sample mean: 2.7 percent (1999Q1-2017Q1). - Housing services sample mean: 3.9 percent (1999Q1-2017Q1). - Empirical approach: - Separate Phillips curves estimated for core goods, core services (excluding housing services), housing services; explanatory variables include output/unemployment gaps, inflation expectations (market-based and survey-based), relative import prices, oil prices, net migration, price-to-rent gap. - Historical decomposition (2014Q1–2017Q1) — selected table totals (contributions in percentage points to deviation from sample mean): - Core Goods total deviation: -0.26 - Core Services total deviation: -1.62 - Housing Services total deviation: -1.67 - Table 1 (Market-Based Expectations; selected contributions): - Core Goods: Inflation expectations -0.51; Relative Import Prices 0.23; Shock 0.05. - Core Services: Inflation expectations -0.37; Net Migration Gap -0.15; Shock -1.18. - Housing Services: Inflation expectations -0.36; Net Migration Gap -0.15; Shock -1.17. - Table 2 (Survey-Based Expectations; selected contributions): - Core Goods: Inflation expectations -0.16; Unemployment Gap -0.30; Relative Import Prices 0.26; Shock 0.02. - Core Services: Unemployment Gap -0.90; Shock -0.62. - Housing Services: Unemployment Gap -1.08; Net Migration Gap -0.09; Shock -0.64. - Key interpretations: - Core goods inflation: more responsive to standard cyclical and external factors; residuals smaller. - Core services inflation: large and consistently negative residuals, reflecting structural changes (labor market flexibility, reduced bargaining power, increased competition). - Housing services inflation: influenced by net migration and price-to-rent dynamics. - Scenario analysis for aggregate core inflation (baseline and alternatives): - Baseline: survey-based expected inflation moves to mean; gap variables close gradually; core inflation returns to 2-3 percent by 2019Q1 (near lower bound). - Alternative Scenario I (unemployment gap closing): unemployment must decline to NAIRU by 2018Q1 → core inflation 2.5 percent in 2018Q3 and remains inside target thereafter. - Alternative Scenario II (exchange rate depreciation): AUD depreciation needed relative to baseline: 2018 about 7 percent; 2019 about 5.5 percent; 2020 about 3 percent → would generate on average 1.1 percentage points higher core goods inflation from 2018–2020. - Alternative Scenario III (persistent unidentified shocks): shocks decay at rate 0.9 per quarter; example core services average shock -1.2 percentage points → -1.1 in 2017Q2, -1.0 in 2017Q3; core inflation returns to midpoint only in early 2020. - Policy implication: - Given uncertainty and structural drags, a cautious approach to unwinding accommodative monetary stance is appropriate. - Returning inflation to midpoint earlier would require faster unemployment gap closure and/or AUD depreciation. --- ### Conclusions and policy-relevant takeaways (selected) - Real GDP in Australia can show only small net changes to China-origin shocks while large compositional shifts occur between domestic and external demand and across sectors. - Correct assessment of spillovers requires understanding structure of China shocks and sectoral ramifications (consumption/saving rebalancing, tourism and education flows, commodity trade). - Australia’s flexible exchange rate and diversified economy moderate commodity-origin shocks. - Australia’s diversified trade relationships with rest of Asia help mitigate effects from widespread shocks to China. - Infrastructure policy: - Closing Australia’s infrastructure investment gap (estimated average around 0.35 percent of GDP per year) can yield long-term real GDP gains ranging from 0.4 to 0.7 percent relative to Australia’s WEO outlook. - Financing choice matters: PIT and/or GST financing is least productive (crowds out consumption); deficit financing crowds out some private investment and could increase sovereign risk premia; PPPs are the most productive if fully privately delivered with reimbursement via future income streams. - Accelerating closure (e.g., by 2027 rather than 2040) can generate higher short-term gains without loss of long-term gains, subject to scaling capability. - Quality improvements and broader definition of infrastructure (including human-capital investments) yield larger gains. *International Monetary Fund — excerpt from cr1845 PDF chapter* ### 1. ANZIMF – The Australia-New Zealand Integrated Monetary and Fiscal Model __________ 8 ### 1. ANZIMF – The Australia-New Zealand Integrated Monetary and Fiscal Model ### Overview and purpose - Examines risks to China during its transition to a services-driven, consumer-led economy and focuses on spillovers to Australia. - Uses ANZIMF (Australia-New Zealand Integrated Monetary and Fiscal model), a version of the IMF’s GIMF (Global Integrated Monetary and Fiscal model). - ANZIMF is a micro-founded, overlapping generations dynamic stochastic general equilibrium (DSGE) model with a detailed bilateral trade flows structure and two additional sectoral distinctions to better track China–Australia links: services (tourism and education) and metals and coal. - Analytical emphasis: while real GDP in Australia shows only small changes across scenarios, substantial shifts occur in the composition of GDP (between domestic and external demand, and across sectors). ### Model structure and key mechanisms (Box 1) - Multi-region, annual, micro-founded general equilibrium model comprising seven regions: Australia, New Zealand, China, Advanced Asia, Emerging Asia, the United States, and a bloc of remaining countries. - Sectors explicitly modeled: coal/iron ore/metals and tourism/education services. - Consumption: - Two household types: saving households and liquidity-constrained (LIQ) households. - Saving households follow an overlapping generations (OLG) framework (Blanchard (1985), Weil (1989), Yaari (1962)), treat government bonds as wealth, rendering the model non-Ricardian and endogenizing the long-term global real interest rate. - LIQ households consume all income each period, amplifying short-term non-Ricardian dynamics. - Investment: - Private investment follows the Bernanke-Gertler-Gilchrist (1999) financial accelerator. - Firms face monitoring costs; corporate risk premia are endogenously determined as financial conditions change. - Real exchange rate adjusts countries’ saving positions (current account and net foreign assets) relative to the global pool. ### Scenario design (three illustrative macro scenarios) - Increased services demand in China (upside for Australia): - Households substitute away from saving toward consumption; government reforms boost productivity. - Australia’s service sector benefits, but Australia’s other sectors can be disadvantaged by higher Chinese productivity. - Takeaway: The structure of the shock in China matters as much as its outcome for spillovers to Australia. - Increased foreign commodities demand from China (upside for Australia): - China restricts domestic production of iron ore, coal and associated goods (e.g., steel), while demand remains strong. - Australia exports more commodities, but a mild slowdown in Chinese growth triggers a mild contraction elsewhere in Australia, driven mainly by an Australian dollar appreciation. - Takeaway: Australia’s flexible exchange rate and diversified economy moderate shocks. - Disorderly rebalancing in China (downside for Australia): - Rebalancing is derailed: broad-based slowdown, lower productivity, weaker-than-expected steel activity, lower housing prices, increased corporate risk. - Australia’s net commodity exports fall, but there is a rebalancing between domestic and external demand and between China and Australia’s other trading partners, stimulating Australia’s exports and services sector on net. - Takeaway: Interactions among Australia’s commodities sector and multiple trading partners can produce unexpected feedback effects. ### Four principal takeaways from scenarios - Small changes in Australia’s real GDP can mask large shifts in demand composition (domestic vs external) and sectoral composition (commodities, services, other tradables, nontradables). - For a services-driven shock in China, identifying shock components is crucial to interpret Australian spillovers. - For a commodities-driven shock, Australia’s flexible exchange rate and diversified economy act as important buffers. - For a disorderly Chinese rebalancing, Australia’s outcomes depend on interactions across multiple trading partners beyond China alone. ### Stylized facts on Australia–China linkages (selected) - Linkages driven by China’s demand for commodities (coal and iron ore used in intermediate industries like steel) and services (tourism and education). - Australia expanded capacity for iron ore and coal production after the mining investment boom; services (tertiary education, tourism) continue to expand. ### Table 1: Selected key ratios in ANZIMF (preserve exact figures as presented) - Share of Global GDP (%) — Australia: 2.1; China: 10.3; Other Asia: 16.0 - Domestic Demand (Percent of GDP) — Household Consumption: 57.253.5 59.0 - Domestic Demand — Private Investment: 20.025.0 20.1 - Domestic Demand — Government Absorption: 22.8 24.0 21.0 - Trade (Percent of GDP) — Non-Commodity Exports: 13.225.7 29.6 - Trade — Final Goods: 5.018.416.3 - Trade — Consumption Services: 3.5 2.0 2.6 - Trade — Intermediate Goods: 4.8 5.2 10.8 - Trade — Non-Commodity Imports: 22.2 23.3 28.6 - Trade — Final Goods (imports): 13.9 9.2 12.7 - Trade — Consumption Services (imports): 2.6 2.6 1.9 - Trade — Intermediate Goods (imports): 5.7 11.5 14.0 - Net Commodities: 9.0 -2.4 -1.0 - Partner 2/ (Net Commodities by partner): 5.3 -1.1 -0.5 *cr1845 - 1. ANZIMF – The Australia-New Zealand Integrated Monetary and Fiscal Model* ### Box 1. ANZIMF – The Australia-New Zealand Integrated Monetary and Fiscal Model ### Box 1. ANZIMF – The Australia-New Zealand Integrated Monetary and Fiscal Model ### Model structure and nominal-real linkages - Government absorption consists of exogenously determined spending on consumption goods and infrastructure investment; both affect aggregate demand. - Infrastructure spending cumulates into an infrastructure capital stock (subject to constant but low rate of depreciation). A permanent increase in the infrastructure capital stock permanently raises the economy-wide level of productivity. - The nominal side of the economy depends on implicit Phillips’ curves and monetary policy. - The core price is the consumer price index, CPI. - Wage inflation is implicitly a key driver for CPI inflation. - Monetary policy is usually an inflation forecast targeting regime that uses an interest rate reaction function reliant on expected inflation; interest rate effects bring inflation back to target within several years. - Fiscal policy is represented by a detailed government sector that reproduces simplified fiscal accounts and aims to maintain a debt target (expressed as a deficit target, in flow space) using at least one of seven policy instruments. - Spending-side instruments: government consumption; infrastructure spending; general lumpsum transfers to all households (such as pensions, aged care provisions, unemployment insurance); lumpsum transfers targeted to LIQ households (such as welfare, certain pensions). - Revenue-side instruments: taxes on consumption (the goods and services tax, GST), personal income (PIT) and corporate income (CIT). ### Trade, commodities, and services sectors - Trade is tracked bilaterally between all regions; flows react to demand, supply and pricing (terms of trade and bilateral real exchange rates) conditions. - Trade differentiation: - Commodities trade and related demand/supply equations are based on coal and metals (especially iron ore). - Non-commodities trade is broken into final goods (consumption and investment), consumption services, and intermediate goods. - Sectoral scope relative to standard GIMF: - Commodities sector defined narrowly to coal, iron ore, and other minerals. - Services sector defined narrowly to tourism (mostly travel, accommodation, and food services) and education (mostly travel and correspondence courses). - Commodities sector specifics: - The U.S. dollar global commodities price is determined in a global market where producing countries sell and all countries compete for demand on the basis of price. - Countries produce commodities from their endowment. - Supply moves in the short term with the gap between the current and medium-term average global price, and reacts (optionally) to demand-driven long-term changes in the global price. - Both the short- and long-term price elasticities of supply are 0.05. - Net export flows are explicitly tracked; commodities are inputs to both tradable and non-tradable intermediate goods production, with the majority flowing to tradables. - Services sector specifics: - Services are produced from tradable and nontradable goods. - Services are priced as an input for consumption in Australia, or exported to be consumed by foreigners. - Services are exclusively part of consumption, and their demand vis-à-vis consumption goods is relatively inelastic. - Consumption of services is a combination of services provided domestically or abroad; the final price of services enters the CPI alongside consumption of goods. ### Scenario analysis — overview - The model is used to analyze spillovers from alternative China restructuring scenarios to Australia, highlighting channels through services demand, commodities prices, REER movements, and compositional shifts in GDP and trade. ### Upside Scenario 1 — Higher Chinese Household Spending on Tourism and Education - Takeaway: Structure of the shock in China is as important as its outcome for spillovers to Australia and other countries. - Shock design and direct China effects: - Household preference shift away from saving leads to a decline in private saving by 1 percent of GDP. - Accommodated by an immediate 1.5 percent appreciation of China’s real effective exchange rate (REER). - Accelerated restructuring brings forward productivity growth. - Consumption is 1 percent higher relative to baseline (driven by private saving short term and higher productivity long term). - Trade and commodity implications: - Higher Chinese consumption increases demand for services with no substantive effects on commodities. - Imports of services increase about 7 percent in the medium term and settle at 4 percent in the long term, accounting for about half of the increase in consumption. - Spillovers to Australia: - Australia’s services exports grow by 2 percent in the first five years; long-term supply effect is 0.9 percent. - Australia’s REER mirrors China: depreciates slightly by 0.2 percent followed by a 0.2 percent long-term appreciation. - Short-term Australian exports increase: about 0.45 percent for final goods and almost 0.3 percent for intermediate goods. - Long-term Australian final and intermediate exports each decline by about 0.4 percent relative to baseline. - Short-term consumption is 0.2 percent lower, but 0.1 percent higher in the long term. - Australian real GDP moves from less than 0.1 percent higher in the short term to -0.1 percent in the long term, relative to baseline. - The current account is unambiguously stronger, primarily due to services exports, though the real trade volume is more variable because of REER and terms-of-trade effects. ### Upside Scenario 2 — Improved Opportunities for Foreign Commodities Suppliers in China - Takeaway: Australia’s flexible exchange rate regime and open economy moderate effects of shocks. - Shock design and direct China effects: - Government restructures and closes inefficient steel firms, reducing capacity by an additional 10 percent (about -0.4 percent of GDP). - Domestic supply of coal and iron ore reduced by 5 percent. - Global price of these commodities rises by 3 percent, permanently, with higher short-term increases. - China’s real GDP is permanently lowered by 0.6 percent relative to baseline; consumption falls about 1 percent. - China’s REER depreciates permanently, encouraging exports. - Spillovers to Australia: - Demand for Chinese tourism and education services falls by about 1.2 percent permanently; imports decline slightly more. - Australia’s services exports decline by 1.5 percent. - Australia’s REER appreciates by 0.7 percent on impact and 0.5 percent in the long term. - Appreciation dampens all exports; net commodity exports rise in value with an initial supply increase that is short lived. - Increased commodity wealth allows permanently higher consumption in Australia, aided by a cheaper consumption basket because of appreciation. - Overall Australian real GDP is slightly lower, with a compositional shift: stronger domestic (commodity) sector but weaker external sector, primarily from lower services exports. ### Downside Scenario — A Disorderly Rebalancing in China - Takeaway: Australia depends on the interaction of its commodities sector with multiple trading partners beyond China; disorderly rebalancing has large negative effects. - Shock design and direct China effects: - Restructuring of SOEs, including steel, is not successful; a number of firms fail. - Productivity growth follows a 5-year lower-than-expected path, lower by 1 percent of GDP (i.e., productivity shock equals 1 percent of GDP over 5 years). - Disorderly restructuring reduces commodities demand in China by 10 percent permanently. - Housing wealth falls by 10 percent permanently relative to baseline. - Corporate risk premium for SOEs increases permanently by 1 percent. - Short-term impact on growth is 2 percent (worse than expected because of shock severity). - Aggregate China outcomes: - China’s real GDP is permanently 10 percent lower (4 percent lower on impact). - 60 percent of the decline is attributable to the downward revision in productivity. - Consumption falls by the same amount as GDP, driven by lower labor income and the negative housing wealth shock. - China’s REER appreciates because the fall in productivity makes exports more expensive, reducing foreign demand. - Implication for Australia: - (Illustrated in model figures) the disorderly rebalancing produces substantial negative spillovers through reduced commodity demand, lower services demand, tighter financial conditions for SOEs, and adverse REER and trade channel interactions. *Source: IMF staff calculations as presented in Box 1. ANZIMF – The Australia-New Zealand Integrated Monetary and Fiscal Model (concluded).* ### 25. Because consumption declines substantially, there is a direct pass-through to tourism ### Because consumption declines substantially, there is a direct pass-through to tourism ### Impact on services, tourism, and education - Tourism and education services fall by about 10 percent. - Imports of these services decline by 6 percent on impact. - With the appreciating REER, the negative impact is reduced over time: - Services imports are only 4 percent lower after 10 years relative to baseline. - Services imports are only 3 percent weaker in the long term beyond 10 years. ### Commodities, production, and global prices - Failed restructuring focused in the steel industry directly reduces demand for iron ore and coal. - Net imports of commodities fall as a share of GDP by 1 percent, despite an offsetting REER appreciation. - Domestic production of coal and iron ore declines by about 0.5 percent in the short term. - The global price of commodities falls around 12 percent permanently. - In the long term, domestic commodity supply declines by around 0.7 percent. ### Australia — macro and sectoral outcomes - Real GDP: - Falls at first by about 0.4 percent. - Rebounds by an equivalent amount in the long term. - Commodity trade and supply: - Australian net commodity exports as a share of GDP permanently decline by 1 percentage point in value terms. - Commodity supply declines by 0.7 percent in volume terms. - Services: - Services exports to China decline by roughly 3 percent. - Real final goods exports increase by 5 percent in the long term. - Real exports of intermediates increase by over 4 percent in the long term. - Exchange rate and consumption: - Australia’s REER depreciates by 3.5 percent. - Consumption is almost 3 percent lower due to lower wealth from weaker global commodity prices and higher cost of imported goods. - Wealth transfer and exchange-rate dynamics: - Weak global commodity prices produce a wealth transfer from commodity exporters (Australia) to commodity importers (its main trading partners). - Australia’s loss of household wealth (primarily commodities-induced) is exceeded only by China’s loss, driven by productivity and housing wealth shocks. - Australia depreciates strongly against China, and—considering cross-exchange rates—also depreciates against advanced and emerging Asia and the United States. - Australia’s depreciation against other trading partners makes its services cheaper abroad, partially offsetting declines in services to China. ### Regional spillovers and comparative effects - For Australia’s trading partners (especially the rest of Asia), two competing effects operate: - Negative (weaker): Lower Chinese demand for goods. - Positive (stronger): Large decline in global commodities prices encourages demand for commodities and stimulates GDP in most of the rest Asia as net commodity importers. - Net commodity importers in the region benefit, producing positive spillovers to the rest of Asia. ### Scenario dependencies and caveats - Outcomes are conditional on: - Lack of financial contagion from China. - An unimpeded adjustment of China’s REER. - A scenario with substantial financial turmoil would dampen the otherwise optimistic outcome for Australia. ### Key scenario constructions (shocks originating in China) - Upside Scenario 1 (three shocks combined): - Lower private saving: permanent reduction of 1 percent of baseline GDP phased in over nine years. - Higher consumption of services: increased household bias to services over goods over 5 years (increase in consumption of imported tourism and education services will be roughly half of the entire increase in aggregate consumption). - Higher productivity: permanent increase phased in over 25 years (starting in the sixth year) that yields a permanent 1 percent increase in real consumption in presence of lower private saving. - Upside Scenario 2 (two shocks): - Lower commodity supply: permanent 5 percent reduction in domestic supply of commodities, phased in evenly over 3 years. - Decrease in steel supply: permanent 10 percent reduction in steel production (roughly translating into -0.4 percent of GDP), phased in over 3 years. - Downside Scenario (four shocks; first two presented in combination): - Lower productivity: permanent 5 percent reduction in tradables and nontradables productivity, phased as -2 percentage points on productivity growth in year 1 and -1 percentage point on growth in years 2 through 4. - Lower commodities demand: permanent 10 percent reduction in demand for commodities, phased as -4 percentage points in year 1 and -2 percentage points in years 2 through 4. - Lower housing wealth: 10 percent decline on impact in year 1 in nontradable sector net worth. - Increased corporate risk premia: permanent 1 percentage point increase after a 2 percentage point increase on impact in year 1. ### Model assumptions relevant to interpretation - All agents have perfect foresight. - Model includes non-linearities in the financial accelerator; otherwise approximately linear for small shocks. - Countries share the same economic structure, differing only by parameterization and calibration. - Baseline calibration uses parameter values consistent with 2015 for major ratios to GDP and 2015–2016 for services data. - The real exchange rate is a “jumper” adjusting immediately in the first year to shocks, following forward-looking, risk-adjusted uncovered interest rate parity. - China has a flexible exchange rate with no capital controls. - No substantial financial market channels are modeled beyond the financial accelerator; complete domestic ownership of firms is assumed; all net foreign asset positions are denominated in U.S. dollars. - The model operates at an annual frequency, reducing detail for dynamics within the first year for investment. ### Conclusions and policy-relevant takeaways - Real GDP in Australia can show only small net changes in response to China shocks, while large compositional shifts occur within GDP between domestic and external demand and across sectors. - Correct assessment of spillovers to Australia requires understanding the structure of shocks in China and their sectoral ramifications (e.g., consumption/saving rebalancing, tourism and education flows, commodity trade). - Australia’s flexible exchange rate and diversified economy moderate shocks from China, particularly those originating in the commodities sector. - Australia’s diversified trade relationships with the rest of Asia (advanced and emerging) help mitigate effects from widespread shocks to China. - Policy implication from infrastructure analysis: - Closing Australia’s infrastructure investment gap (estimated as an average of around 0.35 percent of GDP per year) can yield long-term real GDP gains ranging from 0.4 to 0.7 percent relative to Australia’s WEO outlook. - Financing choice matters: PIT and/or GST financing is least productive (crowds out consumption), deficit financing crowds out some private investment and could increase sovereign risk premia, while PPPs are the most productive source of financing if implemented with full private-partner delivery and reimbursement via future income streams. - Accelerating closure of the gap (e.g., closing by 2027 rather than 2040) can generate higher short-term gains in real GDP without loss of long-term gains, subject to the ability to scale up infrastructure investment quickly. - Improvements also derive from better quality infrastructure and a broader definition of infrastructure that includes human-capital-related investments. *International Monetary Fund — excerpt from cr1845 PDF chapter* ### 3. The Global Infrastructure Hub is the primary source for the baseline infrastructure ### The Global Infrastructure Hub is the primary source for the baseline infrastructure investment gap ### Methodology and scope of the Global Infrastructure Outlook - Forecast period: a 25-year period, starting in 2016, forecasting until 2040. - Coverage: seven sectors — roads, rail, airports, ports, electricity, telecoms and water — for 50 countries, comprising over 85 percent of global GDP. - Sectors excluded: structures (such as hospitals, police stations, schools) and capital equipment (for example, ambulances and police cars, and military equipment). - Key methodological steps (Box 1, Six Step Methodology): - Compute the seven infrastructure stocks on a per capita basis for 2015 for all countries in an income group. - Estimate single-equation models for each sector using panel estimation with explanatory variables drawn from a subset of GDP per capita, the manufacturing and agricultural shares of GDP, population density, urban share of population, plus country-specific fixed factors. - Forecast infrastructure stocks per capita to 2040 using forecasts of explanatory variables; convert to current trend investment using perpetual inventory equations of the form Kt = Kt−1(1−δ)+It. - Estimate the expected infrastructure stock per capita in 2015 using the single-equation models. - Quality-adjust the expected infrastructure stock per capita using infrastructure quality measures from the World Economic Forum’s Global Competitiveness Report 2014-15. - Determine the 75th percentile of quality-adjusted expected infrastructure stock per capita within each country grouping to derive country-specific investment needs; then compute Infrastructure investment gap = investment needs – current trends in investment. ### Global infrastructure investment gap — headline figures - Global infrastructure investment gap (2016–2040): 2015 US$94 trillion. - Gap as share against current trend investment extrapolated to 2040: 19 percent. - Average annual gap: 2015 US$3.7 trillion per year. - Implied desired global infrastructure spending as a share of GDP: 3.5 percent, versus 3.0 percent now. - Sectoral note: All seven infrastructure sectors have higher needs than current trends, with roads being the greatest. ### Australia: gap size and sectoral profile - Australia overall gap (2016–2040): 10 percent of GDP. - Cumulative infrastructure investment needs for Australia: 2015 US$1.7 trillion. - Current cumulative trend spending for Australia: 2015 US$1.54 trillion. - Implied additional infrastructure investment spending for Australia: almost 0.4 percent of GDP per year until 2040. - International comparison: gap similar in scope to New Zealand, but larger than other key advanced economies and China. - Sectoral differences for Australia: - Roads: extensive investment historically; current trends match investment needs. - Rail: stronger needs exist due to historically weak rail linkages. - Ports: stronger needs, reflecting reliance on sea transportation and trade linkages. - Electricity: recognized need to upgrade and expand power grid; not all needs met by current trends. - Two most important Australian gaps (post-2018): rail (just over 0.1 percent of GDP per year) and ports (almost 0.15 percent of GDP per year). ### ANZIMF model and simulation framework - Model: ANZIMF — an annual, multi-region, micro-founded general equilibrium model based on the IMF’s GIMF. - Key structural features: - Households: saving households (OLG-type, treat government bonds as wealth, non-Ricardian) and liquidity-constrained (LIQ) households who consume all income each period. - Private investment: financial accelerator (Bernanke-Gertler-Gilchrist 1999); capital-to-GDP ratio inversely related to cost of capital; endogenous corporate risk premia. - Government absorption: exogenously determined government consumption and infrastructure investment; infrastructure cumulates to a capital stock with a permanent productivity effect. - Calibrated output elasticity of public capital: 0.122 (Bom and Ligthart, 2014). - Fiscal instruments: government can adjust government consumption, infrastructure spending, lumpsum transfers, targeted transfers to LIQ households, GST, PIT, CIT to meet a deficit/debt target. - Private sector role: nontradable firms can divert investment into infrastructure capital (treated as PPP funds in national accounts); government can provide equity injections converting to private investment that contributes to infrastructure capital stock. - PPP assumptions: competitively-tendered private firms build projects, cover construction costs, recoup via committed future revenue streams; infrastructure assumed government-owned but privately maintained. ### Financing options for closing Australia’s gap (policy scenarios) - Four financing variants simulated for closing the Australian gap by 2040: - Deficit financing by the Commonwealth and/or the States and Territories. - Full financing by the Commonwealth using personal income tax (PIT). - 50/50 financing: Commonwealth via PIT and States/Territories via goods and services tax (GST). - Funding by PPPs exclusively. ### Simulation results — macroeconomic effects and distribution - Long-term GDP: - Real GDP would be as much as 0.7 percent higher than otherwise in the long term. - Long-term multiplier: about 2. - Consumption: - Consumption is between 0.1 to 0.4 percent higher in the long term. - Real effective exchange rate: - Slight long-term depreciation with higher productivity, supporting stronger exports; initial short-term appreciation when closing the gap stimulates demand and draws foreign saving. - Government debt dynamics and financing trade-offs: - Deficit financing would cause a permanent 6.5 percent increase in the government debt to GDP ratio in the baseline run before accounting for growth effects. - Cumulative deficits required over the 25 years: closer to 9.6 percent of GDP. - Growth from infrastructure investment reduces the government debt to GDP ratio in the long term by 3.1 percentage points relative to the counterfactual (after economic feedback). - PPP funding prevents the government from facing the permanent 6.5 percent increase in government debt to GDP ratio, slightly reducing crowding out of private business investment and yielding slightly higher long-term GDP gains relative to deficit financing. - Relative effectiveness of financing options: - Deficit financing and PPP funding provide the greatest GDP gains overall. - Deficit financing is most advantageous in the short term. - PPP funding slightly exceeds deficit financing in the long term due to lower permanent government debt buildup and less crowding out of private investment. - Financing with PIT and/or GST reduces GDP gains: - PIT financing alone reduces gains the most because PIT reduces consumer buying power and taxes a factor of production directly, lowering labor productivity and counteracting infrastructure benefits. - Using PIT/GST financing produces a smaller short-term appreciation of the real effective exchange rate and less demand for foreign financing than deficit or PPP scenarios. ### Fiscal context and timing - The Global Infrastructure Outlook dataset was built contemporaneously with FY2015/16 budget paths. - FY2016/17 and FY2017/18 fiscal budgets increased those years’ spending on average 0.4 percent of GDP, closing the gap in 2016 and 2017. - FY2017/18 budgets do not appear to sustain these increases past FY2019/20. - The constructed aggregate infrastructure investment gap for Australia (2018–2040) uses IMF WEO April 2017 GDP forecasts and Global Infrastructure Outlook infrastructure investment; the gap is set to zero for 2016 and 2017 to reflect higher FY2016/17 and FY2017/18 outturns. ### Limitations and caveats - Uncertainty in quantifying pass-through from infrastructure investment and stock to productivity growth. - Model limitations inherent in ANZIMF/GIMF (e.g., under-responsiveness of trade flows common to many DSGE models). - Methodological concerns in constructing the gap itself can produce misleading results if the gap is quantified incorrectly; technological innovations over the forecast period could fundamentally change the role and provision of infrastructure. - Closing the gap would increase GDP which could change demand for infrastructure and thus the investment needs and gap; this feedback is ignored in the gap construction but may not be large for Australia given its small gap. *International Monetary Fund — excerpt from PDF chapter.* ### 17. Closure of the infrastructure ### 17. Closure of the infrastructure ### Timing and objectives of closing the gap - Closing the infrastructure investment gap can be used as a tool to further fiscal policy goals by altering the timing of spending to maximize short-term benefits while preserving the same long-term infrastructure stock. - Two timing choices illustrated: - Close the gap over 25 years (benchmark). - Close the gap over 10 years to kick-start short-term growth (Figure 6 and Figure 7). ### Fiscal financing options and immediate fiscal mechanics - Two financing cases for the 10-year acceleration: - Deficit-financing only (red line). - Maintain the same deficit-financing path as the 25-year case and add additional financing (red line with green bars), including PPPs. - Phasing assumption: moving from roughly 0.3 percent of GDP to 0.7 percent of GDP for infrastructure is phased in over four years (procurement and implementation constraints). ### Macroeconomic effects: short-term vs long-term - Long-term: - Long-term real GDP gains are around the same as in the benchmark scenario, at 0.8 percentage points. - If PPPs are used to fund part of the accelerated build-up, government debt accumulates 4 percent of GDP instead of 6.5 percent of GDP (difference vs deficit-financing only). - Short-term: - Shortening the horizon moves economic gains forward and provides more fiscal stimulus in the short term. - Real GDP lifts much more rapidly in the short term, adding twice as much to growth over the first 10 years relative to the benchmark scenario. - Consumption lifts more strongly, particularly if additional funding is provided by PPPs. - Deficit-financing only leads to greater crowding out of private business investment in the first several years, crowding out labor demand and income, and therefore consumption. - If additional funding is provided by PPPs, there is no additional crowding out, allowing consumption to rise more strongly in the first five years before moderating. - Both financing forms increase demand for foreign financing through the current account, producing a stronger short-term appreciation of the real exchange rate, although permanent productivity effects still lead to a long-term depreciation of the real effective exchange rate. - Overall implication: changing the speed at which the gap closes can provide short-term benefits to growth, and fiscal policy can have a more prominent role in short-term demand management when spending is productive. ### Practical considerations and constraints - Not all projects can be compressed into a shorter horizon (example: western Sydney airport project). - If the economy is already expansionary, attracting required resources (government or PPP) could be difficult. - As of 2017, Australia still had spare capacity in labor and capital markets and was most likely able to absorb a faster expansion of infrastructure investment. ### Other considerations when closing the gap: quality and broader definition - Two alternative scenarios assess the effects of (1) higher-quality infrastructure and (2) a broader definition of infrastructure. - Alternative Scenario 1 (quality): Australia achieves the infrastructure quality of Singapore. The investment gap (amount to spend) is unchanged, but gains are larger because of better quality outcomes and technology. - Alternative Scenario 2 (breadth): The infrastructure gap is broadened to include the rest of infrastructure capital outside the seven sectors. - Table of quality scores (range 1 to 7; 7 is best) used in comparisons: - Energy: Australia 5.7, Singapore 6.9 - Airports: Australia 5.2, Singapore 6.9 - Ports: Australia 4.9, Singapore 6.7 - Rail: Australia 4.1, Singapore 5.9 - Roads: Australia 4.1, Singapore 6.3 ### Quantified outcomes of alternative scenarios - Alternative Scenario 1 (higher-quality investment): - Real GDP almost 0.9 percent higher in the long term — an additional gain of almost a third over the benchmark scenario. - These higher-quality gains do not require additional government spending and therefore do not increase government debt. - Alternative Scenario 2 (broader definition): - Real GDP 0.8 higher in the long term — a gain of about a quarter over the benchmark scenario. - The broader definition amplifies the crowding out effect of government debt, including a weaker current account and slightly lower GDP in the short term relative to the benchmark scenario. ### Methodologies for the alternative scenarios (Box 3) - Alternative Scenario 1 (quality): - A “conversion factor” is built from Singapore and Australia quality scores from the World Economic Forum’s Global Competitiveness Report 2017-18. - The conversion factor is the weighted sum of the ratio of Singapore quality score to Australia’s for five sectors (energy, airports, ports, rail, roads), with weights based on average share of each sector in Australia’s infrastructure capital stock. - The conversion factor is assumed valid for water and telecommunications as well. - Conversion factor used: 1.38. - The conversion factor is multiplied with the coefficient that governs the pass-through of new infrastructure capital into Australian productivity; the new pass-through coefficient is used in simulations. Results likely represent an upper limit because the approach assumes percentage changes in quality map directly to percentage changes in productivity pass-through. - Alternative Scenario 2 (breadth): - Expand the narrow seven-sector gap to include structures and other minor inputs (still excluding military infrastructure). - Adjust the narrow gap for the broad definition being consistent with an average depreciation rate of 4 percent rather than 5 percent. - Multiply the adjusted gap by the ratio of the IMF WEO’s long-term forecast of broad infrastructure investment in Australia (roughly 4.2 percent of GDP) to the narrow definition of current-trends infrastructure investment (roughly 3.5 percent of GDP). - The resulting broad-definition gap is used for simulations; results likely represent an upper limit because they assume needs and current trends are directly scalable based on WEO-based flows. ### Conclusions and policy implications - Summary findings: - Closing the gap yields quantifiable benefits: short-term stimulus and longer-lived productivity effects benefiting all sectors. - The form of funding matters: for the small amounts required, financing by deficits and PPPs are preferable to tax financing in the long term; if needs were much greater, tax financing would likely be preferred to avoid excessive debt and potential sovereign risk premia. - Altering the time horizon for closing the gap can be used to provide additional short-term stimulus; pairing a shorter horizon with PPPs can limit short-term government debt accumulation and lower government debt relative to a deficit-financing-only acceleration. - There is uncertainty in magnitudes; two alternative scenarios illustrate some uncertainty but additional model and parameter uncertainties remain. - Prospective gains: - Australia has improved infrastructure spending in recent years and has scope to expand further to reduce its infrastructure gap relative to other advanced economies. *Source: IMF staff chapter "Closure of the infrastructure" (cr1845).* ### 4. Against this background, this paper surveys housing market developments, prospects, ### 4. Against this background, this paper surveys housing market developments, prospects, ### B. Diagnosis of the Housing Boom - Regional concentration: - The housing boom over the past six years has been regional, concentrated in Sydney and Melbourne. - The average real price of existing houses in the 8 capital cities increased when the boom began, but much of the increase has been driven by prices in the two major capital cities. - Inner-city apartments in Sydney and Melbourne are part of the integrated global market for high-end real estate. - Domestic and external drivers: - Domestic demand fundamentals explain much of the price increase; the boom broadly coincided with the current monetary easing cycle, which began in November 2011 when commodity prices started declining. - A substantial narrowing of interest differentials across the entire maturity spectrum relative to major advanced economies contributed to lowering mortgage financing costs. - Geographic shift in demand followed the rebalancing of the economy after the end of the mining investment boom around 2011-12, with greater metropolitan Sydney and Melbourne seeing stronger economic activity and population growth above the national rate of 1.5 percent. - Both cities have seen growing foreign investor interest, particularly from dynamic economies in East Asia. - Valuation assessment: - Using a reduced-form house price equation (following Igan and Loungani (2012)) and Australian time-series data, fitted values imply equilibrium real house prices. - This approach suggests that average house prices as of 2017Q3 are moderately stronger than fundamentals would suggest, by some 5 percent to 15 percent, depending on econometric specifications and sample period. - Limitation: estimates are based on national house prices, so individual urban areas might be more or less overvalued; estimation uncertainty is another potential limitation. ### C. The Price Elasticity of Housing Supply in Australia - Modelling approach: - Residential investment is modelled using Tobin’s Q framework (Tobin, 1969): investment-to-stock ratio (I/K) is an increasing function of the ratio of market price of capital (house price HP) to replacement cost (producing costs RC). - Econometric specification (log form) estimated for 1988Q3 to 2017Q3. - Key empirical results: - Estimates indicate a low price elasticity of supply in Australia in international comparison. - Full-sample estimations using Simple OLS, DOLS(1,1), and DOLS(2,2) yield an average elasticity of about 0.56 at the national level. - All variables in the equation are integrated of order one; co-integration tests indicate the existence of one co-integrating vector. - Time variation: - Rolling regressions (40-quarter windows) show the long-term price elasticity was higher than unity before 2000s, fell significantly between 2001-08 and 2012-14, and recently increased again. - Policy, planning, zoning restrictions, infrastructure provision and funding, land ownership patterns, geographical constraints, and attitudes toward higher density construction have constrained supply (Hsieh and others (2012)). - Regional elasticities: - State-level estimates: Sydney elasticity estimated at 0.21; Melbourne elasticity estimated at 0.61. - Sydney’s elasticity is at the lower end of ranges found in some more densely populated OECD countries, consistent with limiting zoning restrictions, geographical constraints, and underinvestment in infrastructure. - Tabulated regression highlights (Table 1, national-level estimates): - log(Housing prices/Construction Costs): 0.593*** (OLS), 0.551*** (DOLS(1,1)), 0.528*** (DOLS(2,2)) - Constant: 9.905***, 9.921***, 9.922*** - Observations: 84 (OLS), 81 (DOLS(1,1)), 79 (DOLS(2,2)) - R-squared: 0.791, 0.808, 0.800 ### D. Urbanization, Housing Supply, and Long-term Growth - Urbanization context: - Australia is highly urbanized, with some three-fourths of the population living along the eastern coast. - The share of the population living in urban areas rose from 82 percent in 1960 to about 90 percent in 2016. - Contribution to growth: - The five larger capital cities (Sydney, Melbourne, Brisbane, Adelaide, and Perth) contributed about two-thirds to national real GDP growth in the 1990s; in 2015-2016 this share increased to four-fifths. - Sydney and Melbourne together house some two-fifths of Australia’s population and generate more than half of the country’s value added. - With economic rebalancing after the mining boom, Sydney and Melbourne became the main engines of growth and experienced population growth above the national rate. - Affordability tensions: - Agglomeration benefits raise productivity and wages but higher density and limited urban land increase housing prices and rents relative to other goods. - Rising costs of living can conflict with housing affordability and challenge social preferences (e.g., high home ownership, detached single family houses). - Prospects and adjustment dynamics: - Prospects for housing market imbalances depend on demand shifters and longer-term resolution of demand-supply imbalances. - Demand shocks beginning in late 2011 appear to have run their course; interest rates seem broadly bottomed out. - Population growth is not expected to change after mid- to late-2000s increases linked to the mining boom and higher student visa arrivals. - Economic rebalancing away from mining will likely be completed soon, and activity and recent increases in population growth in Sydney and Melbourne will likely slow somewhat. - Internal migration patterns may shift, with interstate migration (e.g., from Sydney to Melbourne) and moves to second-tier cities, but accommodating continued population growth in major cities depends on the ability to supply housing at costs commensurate with productivity and incomes. - Policy implication: - Affordability and supply will likely remain policy issues even with a soft landing, as relocation is costly and takes time; housing affordability and long-term growth are linked. ### E. The Policy Response to Housing Market Imbalances - Overview: - Commonwealth and eastern States’ governments intensified efforts in FY2017/18 budgets to address housing market imbalances and improve housing affordability (measures can be classified into supply and demand-side). - These housing affordability packages were preceded by prudential policy measures to address risks to domestic financial stability from increased banking sector exposure to housing. - Macroeconomic policies are seen as too blunt or involving undesirable tradeoffs between regional housing objectives and economy-wide stabilization objectives. - Prudential policies and outcomes: - Rising housing imbalances coincided with higher household debt and bank exposure; declining interest rates raised equilibrium house prices and household mortgage debt. - Concerns: speculative dynamics, myopic expectations, slow supply responses, borrowing or collateral constraints, negative shock feedback loops between house prices, household and bank balance sheets, and aggregate demand. - The four large systemically important Australian banks have substantial exposure to these risks, posing risks to domestic financial stability. - APRA guidance (December 2014, December 2016, March 2017) asked banks to strengthen mortgage loan underwriting standards (loan-to-value ratios and debt serviceability), applied caps on new interest-only loans, and caps on total domestic lending to private housing investors. - Following these measures: - The share of riskier mortgages in new lending has decreased, gradually improving asset quality of the stock of mortgage credit while decreasing the riskiness of the stock of household debt, everything else equal. - Borrowers have used savings from lower interest rates to build up buffers and housing leverage (value of housing stock over mortgage debt) has declined. - Banks have become more resilient due to increased capital; capital adequacy ratios place the four largest banks at the lower end of the upper quartile among international peers. - ASIC has scrutinized lending practices, including investigating in 2014 whether interest-only loans were consistent with responsible lending conduct. *Source: IMF staff analysis in the provided chapter.* ### 22. Australia’s strategy to lower housing risks to household balance sheets and domestic ### 22. Australia’s strategy to lower housing risks to household balance sheets and domestic ### Overview - Australia’s strategy has relied more on credit supply measures (prudential measures) than on demand-side measures used in some other countries. - Prudential measures operate through credit supply—tighter lending underwriting standards reduce the amounts of riskier loans in new mortgage lending and refinancing, everything else remaining the same. - Such prudential tightening can also reduce actual credit growth, but such reductions tend to be temporary amid strong demand fundamentals. - Other countries have applied macro‑prudential instruments that directly affect household demand for housing and related credit (example: Hong Kong SAR uses different stamp duty rates by buyer type). ### Policies to Affect the Demand for Housing - Domestic demand-side focus: - Tax-relief and grants to first-time home buyers to support purchases in light of strong social preference for home ownership. - New South Wales and Victoria have exempted first-time home buyers from stamp duties since July 2017; first-time buyers also receive a grant (a subsidy). - External demand-side measures: - Victoria, New South Wales, and Queensland have levied stamp duty surcharges on foreign buyers. - Victoria and New South Wales have levied land tax surcharges on foreign owners. - At the Commonwealth level, CFMs include limits on sales for foreign investors by developers (but not individual owners). - Classification under IMF policy: - Measures that differentiate between residents and nonresidents are classified as capital flow management measures (CFMs) under the IMF’s Institutional View. - Redistribution and ambiguity of demand-side effects: - Demand-side measures are first-instance redistributive—improving or worsening affordability for specific groups, not necessarily overall affordability. - Measures for first-time buyers lower after-tax purchase price for that group; with unchanged supply in the short term, prices before taxes might increase for other buyers. - Role of foreign buyers: - Nationwide, foreign buyer interest accounts for around 5 percent of housing sales (Kearns, 2017). - In some local markets (newly built apartments in Melbourne and Sydney), foreign buyers are believed to account for around 25 percent of sales. - With such market share, foreign buyers can be among marginal buyers influencing prices, but this does not automatically imply need for targeted policy. - Possible rationales for measures targeting foreign buyers: - Pecuniary externalities where foreign demand raises prices in presence of constraints for other buyers (borrowing constraints due to tighter lending standards). - Supply constraints and social considerations (affordability and home ownership). - Macro-financial externalities (e.g., fire sale externalities) or price pro-cyclicality from uninformed foreign buyers. - Prudential measures are unlikely to influence foreign buyers, since foreign buyers rarely borrow from Australia’s banking system. ### Supply-Side Policies - Recent Commonwealth and State measures expected to increase housing supply elasticity over time: - Commonwealth announced release of some federal land in Melbourne as part of the FY2017/18 housing affordability package, and established a Government Property Register owned by non-corporate Commonwealth entities to encourage alternative uses. - States changed zoning rules to allow higher density building in urban areas. - Commonwealth and States have increased infrastructure spending recently; infrastructure is a precondition for developable land. - Streamlining zoning, planning, and regulatory standards across local councils or common standards in States can lower building costs and speed supply response. - Longer-term planning provides more certainty for developers, investors, and potential home owners on where to build and settle. ### Tax Policy - Housing tax reforms could complement recent policies to address housing market imbalances; current policy packages have not involved changes to tax policy settings. - Stamp duties: - States’ stamp duty regimes are inefficient with narrow tax bases (only transactions) and discourage transactions in existing properties that could have more productive alternative uses. - Recommendation: Replace stamp duties with a systematic land tax regime applying to all residential and commercial properties. - A land tax is an efficient tax on a largely fixed factor, but transition issues are challenging given stamp duties’ importance as State revenue. - Transition can be gradual (example: recent reform in the Australian Capital Territory); cash flow problems for low-income homeowners can be addressed through deferment and other options. - Commonwealth housing tax settings: - Current federal settings provide strong tax incentives for home ownership and for leveraged housing investment. - Examples of features that may encourage excess demand or leveraged investment: - Capital gains tax exemption for main residence is not limited. - Capital gains tax concession: 50 percent discount if owned for more than one year. - Unlimited negative gearing (deductibility of interest payments and other expenses against other income). - These incentives may encourage leveraged real estate investment in market upswings; similar incentives exist in other countries but tend to be more limited. ### Prudential and Regulatory Measures (2014–2017) - Key supervisory and regulatory actions and dates: - Late-2014: Introduction of Prudential Practice Guide outlining APRA’s expectations for sound mortgage lending practices; supervisors alert to annual growth in a bank's investor housing lending above a benchmark of 10 percent; supervisors alert to high levels of higher-risk mortgage lending (high LVR and/or loan-to-income ratio and lending to owner-occupiers with lengthy interest-only periods). - Late-2014: Serviceability assessments for new mortgage lending should include interest rate buffers of at least 2 percentage points above the effective variable rate applied for the term of the loan, and a minimum floor assessment rate of at least 7 percent. - Late-2014: ASIC undertook a loan review on interest-only housing lending compliance with responsible lending obligations. - Early-2015: APRA increased analysis of lenders' underwriting standards, including strengthening household income definitions and discounts to some income such as bonuses and overtime. - Early-2015: Additional scrutiny of underwriting for interest-only loans and onsite reviews of loan documents (APRA). - Early-2016: Countercyclical capital buffer (Basel III) incorporated into capital standards for banks and other ADIs. - Late-2016: ASIC reviewed large mortgage broker lending practices; Revisions to Prudential Practice Guide formalized tightened standards on serviceability buffers and interest-only lending. - Early-2017: Introduction of a limit on the flow of new interest-only lending to 30 percent of new residential mortgage lending, with: - Strict internal limits on the volume of interest-only lending at loan-to-valuation ratios (LVRs) above 80 percent. - Strong scrutiny and justification of any instances of interest-only lending at an LVR above 90 percent. - Early-2017: Lending to investors to remain below the benchmark of 10 percent growth (first introduced in 2014). - Early-2017: Serviceability metrics, including interest rate and net income buffers, to be set at appropriate levels for current conditions. - Early-2017: Lending growth in higher risk segments (e.g., high LTI loans, high LVR loans and very long-term loans) to be constrained. ### Summary and Conclusions - The recent housing boom in Australia is primarily a regional boom, driven by demand shifts and amplified by legacy imbalances and a slow supply response. - Much of the real house price rise above the OECD average has been driven by Sydney and Melbourne, though some demand drivers (e.g., lower interest rates) have been national. - In denser urban settings, supply constraints amplify the price impact of demand shocks, especially in Sydney. - The boom may be over soon, but affordability issues may persist given prospects for further growth in the eastern capitals and low short- and long-term price elasticities of supply. - Recommended multi-pronged approach: - Continue infrastructure investment and zoning and planning regulatory reform to increase supply of developable land and enable more efficient use. - Maintain prudential policies to manage financial sector risks from housing. - Complement with housing tax reform to strengthen overall policy effectiveness. *Source: cr1845 - 22. Australia’s strategy to lower housing risks to household balance sheets and domestic* ### References ### References ### Key references cited - Australian Government, 2014, “The Evolution of Australian Towns”, Report 136, Department of Infrastructure and Regional Development. - Berger-Thompson L. and L. Ellis, 2004, “Housing construction cycles and interest rates”. RBA Research Discussion Paper 08. - Caldera, A. and A. Johansson, 2013, “The Price Responsiveness of Housing Supply in OECD Countries” Journal of Housing Economics 22, 231–249. - Follain, J., 1979, “The Price Elasticity of the Long-Run Supply of New Housing Construction,” Land Economics 54 (2), 190-199. - Gitelman, E., and G. Otto, 2012, “Supply Elasticity Estimates for the Sydney Housing Market” Australian Economic Review 45 (2), June, 176-190. - Glaeser, E., R. La Porta, Fl. Lopez-de-Silanes, and A. Shleifer, 2004, “Do Institutions Cause Growth?” NBER Working Paper No. 10568, June. - Green, R., S. Malpezzi, and S. Mayo, 2005, “Metropolitan-Specific Estimates of the Price Elasticity of Supply of Housing, and Their Sources,” American Economic Review 95, 334-339. - Grimes, A. and A. Aitken, 2010, “Housing Supply, Land Cost and Price Adjustment,” Real Estate Economics 38, 325-353. - Hsieh W., D. Norman and D. Orsmond, 2012, “Supply-Side Issues in the Housing Sector,” RBA Bulletin, September, 11–19. - Hsieh, C. and E. Moretti, 2015, “Housing Constraints and Spatial Misallocation,” NBER Working Paper No. 21154. Issued in May, revised 2017. - Igan, D., and P. Loungani, 2012, “Global Housing Cycles,” IMF Working Paper No. 12/217 (Washington: International Monetary Fund). - International Monetary Fund, 2016, “Capital Flows—Review of Experience with the Institutional View,” IMF Policy Paper. - International Monetary Fund, 2017, People’s Republic of China—Hong Kong Special Administrative Region: 2016 Article IV Consultation—Staff Report, IMF Country Report No. 17/11. - Kearns, J., 2017, “Australian Property—Financial Stability and Foreign Involvement,” Speech given at the Aus-China Property Developers, Investors and Financiers, Sydney, November 20, 2017. - Krugman, P., 1991, ”Increasing Returns and Economic Geography,” Journal of Political Economy 99, 3 (Jun), 483-499. - Saiz, A, 2010, “The Geographic Determinants of Housing Supply” Quarterly Journal of Economics, August, 1253-96. - Stock, J., and M. Watson, 1993, “A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems”, Econometrica 61, 783–820. - Tobin, J., 1969, “A General Equilibrium Approach to Monetary Theory,” Journal of Money, Credit and Banking 1(1), 15–29. - Vermeulen, W. and J. Rouwendal, 2007, “Housing Supply and Land Use Regulation in the Netherlands,” Tinbergen Institute Discussion Paper 07-058/3, CPB Netherlands Bureau of Economic Policy Analysis and VU University Amsterdam. - Belkar, R., L. Cockerell, and C. Kent, 2007, “Current Account Deficits: The Australian Debate”, Research Discussion Paper 2007-02 (Reserve Bank of Australia). - Bishop, J. and N. Cassidy, 2012, “Trends in National Saving and Investment,” Bulletin, March, 9-18 (Reserve Bank of Australia). - Blanchard, O., and G-M. Milesi-Ferretti, 2009, “Global Imbalances: In Midstream?” IMF Staff Position Note SPN/09/29 (International Monetary Fund). - Edey, M. and L. Gower, 2000, “National Saving: Trends and Policy” in Reserve Bank of Australia (ed.), The Australian Economy in the 1990s, (Reserve Bank of Australia). - Finlay, R., and F. Price, 2014, “Household Saving in Australia”, Research Discussion Paper 2014-03 (Reserve Bank of Australia). - Garton, P., M. Sedgwick, and S. Shirodkar, 2010, “Australia’s Current Account Deficit in a Global Imbalances Context,” Economic Roundup, Issue 1-2010 (1). Australia: The Treasury. - Kearns, J. and P. Lowe, 2011, “Australia’s Prosperous 2000s: Housing and the Mining Boom” in Reserve Bank of Australia (ed.), The Australian Economy in the 2000s, (Reserve Bank of Australia). ### Prospects for Australia’s Current Account Deficit: lower for longer? — Main findings - Australia’s current account has been in deficit for most of its history; in the 1960s and 1970s the deficit fluctuated around 1-2 percent of GDP (Edey and Gower, 2000). - The deficit widened from the early 1980s and averaged around 4 percent of GDP for around 3 decades thereafter (Kearns and Lowe, 2011). - The current account deficit sharply decreased immediately after the Global Financial Crisis (GFC) and again in 2016-17. - Two phases of narrowing over the past decade: - Phase 1 (GFC to end of commodity price boom, roughly end of 2011): substantial narrowing driven primarily by favorable terms of trade and higher savings in non-financial corporates. - Phase 2 (post-2011): further but smaller narrowing, largest positive contribution from the real trade balance driven by the end of mining investment boom and weaker consumption; improvements in primary income balance also contributed. - Five key developments explaining the narrowing: 1. Larger slowdowns in domestic demand growth relative to major trading partners (domestic demand dropped by around 7 percentage points in Australia vs 4 percentage points for weighted average of major trading partners during GFC period 2007-09). 2. Household saving ratios sharply increased around the GFC; increase partly reflects transfers during fiscal stimulus of 2008-09 and higher share of cash and deposits in total financial assets. 3. Non-financial corporates reduced net borrowing and cut leverage: debt-to-equity ratio adjusted for price changes reduced by almost half. 4. Financial corporations increased saving; banks lowered dividend payouts from 60 percent to 40 percent of gross operating surplus, raising retained earnings and capital adequacy ratios. 5. Interest payments to non-residents as a percent of GDP decreased from about 3 percent before the GFC to 1.5 percent, aided by a shift in external debt composition toward general government and lower risk premia on Australian bonds. ### Sectoral developments and indicators (exact figures preserved) - Household behavior and housing: - Household saving and investment (% GDP) series showed elevated saving post-GFC but narrowed in recent years as saving-to-GDP decreased and dwelling investment increased during the housing market boom. - Share of cash/deposits in household financial assets depicted in Figure 8 (percent levels in chart). - Non-financial corporates: - Debt-to-equity ratio adjusted for price changes declined by almost half (Figure 10). - Investment composition (Figure 11): Investment excluding mining and dwelling, Mining, Dwelling series presented as % GDP. - Financial sector: - Saving and investment (% GDP) trends shown (Figure 13). - Share of dividends to gross operating surplus fell from 60 percent to 40 percent (Figure 14). - External interest burden: - Interest payments to non-residents fell from about 3 percent of GDP to 1.5 percent (Figure 15). - Share of gross external debt: general government share increased nearly fourfold while banks’ share dropped by 20 percentage points (Figure 16). ### Prospects and projections for the current account (exact text and figures) - Australia’s underlying current account deficit is likely to remain lower than pre-GFC period. - The improvement in the terms of trade in 2017 relative to the previous year should result in a current account deficit of around 2 percent of GDP, given developments to 2017Q3. - Projected output gap (Figure 17) displays values for 2016, 2017, and 2018–2022 for Australia and weighted output gap of Top 10 exporting countries (Percent). - Supporting considerations for continued lower deficit: - Mining investment expected to remain lower with industry focusing on maintaining capital stock after recent expansion. - Non-mining business investment forecast to strengthen but a substantial pick-up relative to GDP is less likely. - Household saving expected to remain around current levels with continued higher precautionary saving and some deleveraging; dwelling investment likely to moderate toward longer-term averages. - Government saving expected to improve as the economy recovers and the government commits to return its budget to balance. - Interest spreads in Australia relative to other major advanced economies expected to remain low, contributing to a continued lower primary income deficit. ### Insights into recent inflation dynamics in Australia — summary findings and scenarios - Core observation: - Australia’s inflation has been below the 2-3 percent inflation target range for nearly three years, despite a recent turnaround in the economy with rising employment growth. - Inflation component dynamics: - Core goods inflation generally lower than core services inflation due to greater impact of global pressures on goods. - Tradable inflation particularly weak; non-tradable inflation also declined with a small reversal in the past year due mostly to increases in utilities prices. - Phillips curve estimation approach: - Separate Phillips curves estimated for core goods, core services (excluding housing services), and housing services inflation. - Standard factors—economic slack, inflation expectations, non-oil import prices, and oil prices—are generally significant drivers, with differing relative importance across components. - Non-oil import and oil prices are more significant for core goods; unemployment gap plays a more significant role for core services. - Results robust to alternative measures of inflation expectations and slack. - Role of residuals and special factors: - Decomposition since 2014 shows residuals (special factors) are large and consistently negative for core services inflation, likely reflecting: - Increased flexibility in labor markets in Australia (less hiring on standard, full-time contracts). - Reduced workers’ bargaining power. - Increased global and domestic competition. - Core goods inflation responds more to standard factors and less to residuals compared to core services. - Scenario analysis using Phillips curves (starting 2017Q4): - Baseline: inflation gradually returning to target range of 2-3 percent by 2019. - Alternative scenarios: - Faster closing of slack or depreciation of the Australian dollar (due to U.S. policy tightening and rising long-term interest rates) could bring inflation to target earlier. - More persistent shocks could delay return to target range. - Policy implication: - Given uncertainty, a cautious approach to unwinding Australia’s accommodative monetary stance remains appropriate. - Decomposition-oriented inflation analyses could help determine timing and extent of monetary policy decisions. *International Monetary Fund: cr1845 - References (excerpts and related report content provided in the supplied PDF).* ### 1. Australia’s inflation has been on a slight ### 1. Australia’s inflation has been on a slight ### Inflation trend and headline context - Australia’s inflation broadly rose during the terms-of-trade boom and broadly declined after the Global Financial Crisis and, especially, after the turnaround in the terms of trade and the end of the mining investment boom. - Tradable inflation has been particularly weak in recent years; non-tradable inflation also declined—its reversal over the past year was mostly due to increases in tobacco excise and utilities prices. - Headline CPI inflation has been below Australia’s target range for nearly three years; CPI inflation is still below the lower bound of the 2-3 percent inflation target range. - Early signs of economic turnaround: rising employment growth and falling unemployment, but price pressures remained weak. ### Special supply-side factors contributing to disinflation - Supply factors identified as contributors: - Technology-driven quality and productivity improvements in telecommunications and computing equipment and some services. - Increased labor market flexibility and reduced bargaining powers of workers and unions. - Increased competitive pressures and more intense competition in the retail sector. - Firms’ efforts to reduce costs along supply chains. - These factors (and import price declines in a weak global economy) help explain why inflation declined more than expected from post-mining boom slack alone. ### Stylized facts by CPI component - Within core CPI: goods represent 52 percent of the consumption basket; core services and housing are 31 and 17 percent, respectively. - Core goods inflation has generally been lower than core services inflation, reflecting greater impact of global pressures and weak non-oil import price inflation. - Core and housing services inflation: - Declined through 2001-2007, spiked above 6 percent before the Global Financial Crisis, then fell significantly. - Recovered to an average of close to 2.5 percent until 2014 before dropping below target starting in 2015. - Core services (excluding housing services) oscillated between below 1 and 7 percent from 2001 until the Global Financial Crisis, then declined, rose to about 3 percent on average until 2013, and declined toward zero before recently beginning to rise. - Labor costs account for 40 percent of final nontradable prices; labor costs/wages have remained a key driver for domestic market services inflation and appear to have stabilized in recent quarters. Early signs of market services inflation lifting would correspond to labor costs lifting. ### Empirical approach (methodology) - Phillips curve models estimated separately for: overall inflation, core goods inflation, core services inflation (core services excludes housing services), and housing services inflation. - Explanatory variables include: - Cyclical variables (output gaps or unemployment gaps). - Inflation expectations (market-based and survey-based). - Relative price shifts (non-oil import prices and oil prices). - Housing-specific variables for housing services: net migration, price-to-rent ratio, rental vacancy rates, mortgage interest rates. - Many explanatory variables are defined in gap terms (deviations from trend). - Robustness checks done using alternative measures of inflation expectations and slack. ### Key empirical results - Aggregate and core goods Phillips curves: - Lagged inflation, long-term inflation expectations, domestic slack, and relative prices of imports and oil are key drivers; coefficients have expected signs and are generally significant. - Impact of unemployment gap in core goods inflation is half the size of that in core services inflation. - Coefficient on import price gap is larger in core goods than aggregate equation. - Core services Phillips curve: - Unemployment gap coefficient is larger relative to core goods; a 1 percentage point increase in the unemployment gap is estimated to result in an increase in core services prices by over 1 percentage point after one quarter. - Relative import and oil prices are not significant for services. - Housing services Phillips curve: - Lagged output gap, inflation expectations, and import prices gap (imported material in construction costs) are significant. - Lagged net migration and price-to-rent ratio gaps are significant drivers. - Coefficients are robust to alternative expectations and slack measures; sector-specific drivers matter for housing. ### Historical decomposition of contributions since 2014 (2014Q1–2017Q1) - Method: in-sample explanatory variables multiplied by estimated coefficients to measure contributions; residuals are the unexplained dynamics (predicted minus actual). - Core goods: - Residuals did not persistently drag core goods inflation negatively. - Domestic slack weighed mildly on inflation; relative import prices pushed inflation up during 2015Q1-2016Q3 (about 0.5 percentage points on average) due to AUD depreciation, then turned negative since 2016Q4 as AUD appreciated by close to 5 percent during 2015Q4-2017Q1. - High relative oil prices supported inflation in 2014; 2015Q1-2016Q3 oil price drop subtracted on average 0.2 percentage points; oil prices added 0.2 percentage points in 2017Q1. - Table 1 (column 1): total deviation of core goods inflation from its sample mean was -0.26 percentage points; market-based inflation expectations contributed -0.51; relative import prices contributed 0.23; shock contributed 0.05. - Core services: - Residuals were large and consistently negative, likely capturing reduced workers’ bargaining power, labor market institutional changes, and increased competition. - Declining market-based inflation expectations dragged core services inflation down; largest negative contribution from residuals between 2015Q1 and 2016Q1. - Average core services inflation over 2014Q1-2017Q1 was 1.6 percentage points below the sample mean of 2.7 percent. - Table 1 (column 2): total deviation -1.62 percentage points; inflation expectations -0.37; shock -1.18. - Alternative model with survey-based expectations and unemployment gap shows larger drag from unemployment gap (-0.90) and reduced shock effect (-0.62) (Table 2, column 2). - Housing services: - Residuals behaved similarly to core services—negative supply shocks notably between 2015Q3 and 2016Q2 and in the last two quarters examined. - Low inflation expectations and net migration declines slowed housing services inflation; net migration picked up mid-2015 diminishing the drag and pushing up inflation in 2017Q1 after a sharp uptick in late 2016. - Average housing services inflation in 2014Q1-2017Q1 fell by 1.7 percentage points below the sample mean of 3.9 percent. - Table 1 (column 3): total deviation -1.67 percentage points; shock -1.17; inflation expectations -0.36; net migration gap -0.15; price-to-rent gap 0.09. - Alternative specification with survey expectations and unemployment gap shows unemployment gap contribution -1.08 and shock -0.64 (Table 2, column 3). ### Quantitative contributions (selected exact figures from Tables) - Sample averages (periods stated): - Core goods sample mean: 1.9 percent (1992Q1-2017Q1). - Core services sample mean: 2.7 percent (1999Q1-2017Q1). - Housing services sample mean: 3.9 percent (1999Q1-2017Q1). - Table 1 (Market-Based Expectations; contributions in percentage points to deviation from sample mean): - Core Goods: Lag -0.04; Inflation expectations -0.51; GDP Gap 0.04; Relative Import Prices 0.23; Relative Oil Prices -0.02; Shock 0.05; Total deviation -0.26. - Core Services: Lag -0.11; Inflation expectations -0.37; GDP Gap 0.02; Net Migration Gap -0.15; Price-to-Rent Gap 0.09; Shock -1.18; Total deviation -1.62. - Housing Services: Lag -0.11; Inflation expectations -0.36; GDP Gap 0.03; Net Migration Gap -0.15; Price-to-Rent Gap 0.09; Shock -1.17; Total deviation -1.67. - Table 2 (Survey-Based Expectations; contributions in percentage points): - Core Goods: Lag -0.03; Inflation expectations -0.16; Unemployment Gap -0.30; Relative Import Prices 0.26; Relative Oil Prices -0.05; Shock 0.02; Total deviation -0.26. - Core Services: Lag -0.13; Inflation expectations 0.01; Unemployment Gap -0.90; Shock -0.62; Total deviation -1.62. - Housing Services: Lag -0.07; Inflation expectations 0.01; Unemployment Gap -1.08; Net Migration Gap -0.09; Price-to-Rent Gap 0.19; Shock -0.64; Total deviation -1.67. ### Interpretation and outlook - Core goods inflation is more responsive to standard cyclical and external factors; residuals played a smaller and less persistent role. - Core services inflation shows a large role for residuals, consistent with structural changes: labor market institutions, contract and pay arrangements, and increased international competition—these factors weighed on wage-price dynamics. - As the labor market tightens, compositional shifts abate, and structural factors stabilize, wages are expected to accelerate and inflation should rise back into the target range. - Uncertainty remains about how high trend labor productivity growth will be and how much improved labor market slack will feed through to wages; persistent increases in competition could keep core services inflation (and overall inflation) at an average below pre-Global Financial Crisis levels. *Source: cr1845 - 1. Australia’s inflation has been on a slight (IMF staff analysis, 2014Q1–2017Q1; tables and figures as reported in the source).* ### 21. The three equations for the components of inflation (based on Regression 3 in each ### 21. The three equations for the components of inflation (based on Regression 3 in each case) ### Scenario analysis methodology and forecasting approach - The three component equations (based on Regression 3 in each case) are used to project each inflation component and construct a trajectory for aggregate core inflation in a baseline scenario; alternative scenarios vary that baseline. - Shortcoming: approach based on Phillips curves assumes movements across inflation components are independent and there is no feedback from them to other macroeconomic variables and policy stance; unlike a general equilibrium structural macroeconomic model, it does not capture interactions. - Gap variables that enter Phillips curves are forecasted using simple autoregressive models for stationary processes: - x̂t = α1 x̂t−1 + ... + αn x̂t−n + ... + etx - Future predicted values: Et x̂t+i = α1 Et x̂t+i−1 + ... + αn Et x̂t+i−n, with Et x̂t+i−n = x̂t+i−n for i ≤ n. - In the baseline scenario: - A survey-based measure of expected inflation moves to its mean level and all gap variables gradually close. - Slack in the economy remains relatively large. - Core goods, core services and housing services inflation run below their mean values of 1.9, 2.7 and 3.9 percent respectively. - Total core inflation returns in the 2-3 percent target range by 2019Q1, but remains near its lower bound. ### Alternative Scenario I — unemployment gap closing - Objective: How quickly unemployment should return to NAIRU for inflation to rise from its current trough and reach the midpoint of the 2-3 percent target range by mid-2018; all other explanatory variables follow baseline trajectories. - Required path: - Unemployment would need to decline to NAIRU by 2018Q1 to ensure core inflation returns to 2.5 percent in 2018Q3 and remains inside the target range thereafter. ### Alternative Scenario II — exchange rate depreciation and import/oil prices - Objective: What depreciation of the Australian dollar is needed so resulting movement in import and oil prices drives inflation to 2.5 percent in 2018; other explanatory variables follow baseline trajectories. - Back-of-the-envelope results: - Australian dollar would need to depreciate by about 7 percent in 2018 relative to the baseline scenario. - About 5.5 percent depreciation in 2019 relative to the baseline. - About 3 percent depreciation in 2020 relative to the baseline. - This depreciation path would generate on average 1.1 percentage points higher core goods inflation from 2018 to 2020 compared to the baseline scenario, bringing core inflation close to 2.5 percent. - Note: A richer structural model capturing indirect exchange rate channel and monetary transmission would provide a fuller analysis; nominal depreciation should also make aggregate monetary conditions more accommodative, stimulate demand and generate additional inflationary pressures. ### Alternative Scenario III — persistent unidentified shocks - Assumption: Average value of a shock to each inflation component, estimated over 2016Q2-2017Q1, is assumed to decay at a rate of 0.9 in subsequent quarters. - Example: average shock to core services inflation = -1.2 percentage points → shock imposed in first out-of-sample quarter = -1.1 percentage points in 2017Q2, -1 percentage points in 2017Q3, and so on. - Other explanatory variables follow baseline trajectories. - Outcome: Shocks drag down inflation for most components and core inflation returns close to the midpoint of the target range only in the beginning of 2020, slower than in the baseline. ### Aggregate findings from scenario analysis and summary - Inflation is likely to remain subdued going forward. - Inflation is likely to be suppressed by persistent economic slack. - Returning core inflation to the midpoint of the inflation target range earlier would require: - A faster closing of the unemployment gap by early in 2018, and/or - A depreciation of the Australian dollar. - Greater persistence in the unidentified shocks would delay a return of core inflation to its target range. ### Empirical conclusions and policy implications - Structural factors affected core inflation differently across goods and services: - Core goods inflation responds primarily to standard factors. - Core services inflation is substantially influenced by structural forces, reflected in the residual term. - Historical decomposition since 2014: - Large and consistently negative residuals for core services point to significant structural factors contributing to prolonged decline in headline inflation. - These factors are believed to be embedded in reduced bargaining power of workers and unions, employment contracts and pay arrangements pointing to less full-time employment and smaller and less frequent price increases, in an environment of rising domestic and global competition. - Outlook and policy stance: - Considering scenario analysis, inflation is likely to gradually return to the target range of 2-3 percent by 2019. - Returning inflation to the midpoint earlier would require faster closing of the unemployment gap by early in 2018 and/or depreciation of the Australian dollar. - Persistence of competitive forces could keep core services inflation (and inflation more generally) at an average level below that experienced before the Global Financial Crisis. - This supports a continuing cautious approach to unwinding Australia’s accommodative monetary stance. - Transmission from labor market: - As the labor market tightens, compositional shifts abate, and long-run competition forces stabilize, wage and price growth are expected to rise. - How much of improved labor market slack feeds through to wages is important for increased core services inflation. ### Key numerical values and statistics preserved from the analysis - Mean values: core goods = 1.9 percent; core services = 2.7 percent; housing services = 3.9 percent. - Target range: 2-3 percent; midpoint cited as 2.5 percent. - Baseline return to target range: by 2019Q1. - Alternative Scenario I requirement: unemployment decline to NAIRU by 2018Q1 → core inflation = 2.5 percent in 2018Q3. - Alternative Scenario II required depreciations relative to baseline: - 2018: about 7 percent. - 2019: about 5.5 percent. - 2020: about 3 percent. - Effect of Alternative Scenario II: on average 1.1 percentage points higher core goods inflation from 2018 to 2020. - Alternative Scenario III shock decay rate: 0.9 per quarter. - Example shock to core services: average -1.2 percentage points → -1.1 percentage points in 2017Q2, -1 percentage points in 2017Q3. - Regression and model statistics (selected): - Aggregate Phillips Curve (Annex Table I.1) R2: Regression 1 = 0.683, Regression 2 = 0.655, Regression 3 = 0.653. - Core Goods Phillips Curve (Annex Table I.2) R2: Regression 1 = 0.631, Regression 2 = 0.657, Regression 3 = 0.649. - Core Services Phillips Curve (Annex Table I.3) R2: Regression 1 = 0.688, Regression 2 = 0.641, Regression 3 = 0.651. - Housing Services Phillips Curve (Annex Table I.4) R2: Regression 1 = 0.780, Regression 2 = 0.638, Regression 3 = 0.741. - Notable estimated coefficients (Annex summaries, exact values preserved): - Aggregate Phillips Curve (Annex Table I.1): πt−2 core coefficient examples: Regression 1 = 0.155 (0.058)**; market-based expectations coefficient = 0.845 (0.058)** in Regression 1. - Core Goods (Annex Table I.2): lagged inflation πt−3 coefficient examples: Regression 1 = 0.174 (0.066)**; output gap ŷt−3 = 0.391 (0.130)** in Regression 1. - Core Services (Annex Table I.3): output gap ŷt coefficient examples: Regression 1 = 0.815 (0.484)*; dummy d2000q3 = 15.403 (1.774)**. - Housing Services (Annex Table I.4): market-based expectations coefficient = 0.905 (0.056)** in Regression 1; net migration gap coefficient = 0.059 (0.020)**. *Source: cr1845 - 21. The three equations for the components of inflation (based on Regression 3 in each case).* --- _Source: https://www.imf.org/-/media/files/publications/cr/2018/cr1845.pdf_