{
  "title": "Dissecting Medium-Term Growth Prospects for Asia",
  "publication": "IMF Working Papers, August 22, 2025",
  "sourceUrl": "https://www.imf.org/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540",
  "canonical": "https://www.imf.org/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540",
  "overlayPath": "/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540/index.md",
  "summary": "This paper explores Asia-Pacific's medium-term growth prospects using two approaches. First, growth accounting analysis and machine-learning estimation reveal how demographics, capital deepening, productivity, and human capital shaped Asia's growth.",
  "sections": [
    {
      "heading": "Overview",
      "content": "- Title: Dissecting Medium-Term Growth Prospects for Asia\n- Authors: Natasha X Che, Federico J Diez, Anne Oeking, Weining Xin\n- Publication type: IMF Working Papers\n- Date: August 22, 2025\n- Summary (as presented): This paper explores Asia-Pacific's medium-term growth prospects using two approaches. First, growth accounting analysis and machine-learning estimation reveal how demographics, capital deepening, productivity, and human capital shaped Asia's growth. Second, an innovative algorithm forecasts growth by matching countries' current conditions with historically analogous periods using Dynamic Time Warping (DTW). Comparing pattern-based forecasts with traditional projections highlights economic convergence and demographic headwinds. Results show that without ambitious reforms, Asia's growth will likely moderate, though remaining the world's fastest growing region. The paper offers data-driven tools for policymakers to identify growth drivers and generate robust forecasts."
    },
    {
      "heading": "Analytical Approaches and Methods",
      "content": "- Growth accounting analysis and machine-learning estimation are used to quantify contributions of:\n  - demographics\n  - capital deepening\n  - productivity\n  - human capital\n- Forecasting approach:\n  - An algorithm that matches countries' current conditions with historically analogous periods using Dynamic Time Warping (DTW).\n  - Pattern-based forecasts are compared with traditional projections."
    },
    {
      "heading": "Key Findings and Projections",
      "content": "- Comparison of approaches highlights:\n  - economic convergence\n  - demographic headwinds\n- Principal conclusion:\n  - Without ambitious reforms, Asia's growth will likely moderate, though remaining the world's fastest growing region.\n- The paper emphasizes data-driven tools to:\n  - help policymakers identify growth drivers\n  - generate robust forecasts"
    },
    {
      "heading": "Policy Implications and Recommendations (as stated)",
      "content": "- Ambitious reforms are implied as necessary to sustain higher growth relative to the moderation projected without such reforms.\n- Policymakers are provided with data-driven tools to prioritize and target reforms by identifying key growth drivers."
    },
    {
      "heading": "Subject Areas and Keywords",
      "content": "- Subject: Capital productivity, Economic growth, Growth accounting, Human capital, Labor, Population and demographics, Production, Total factor productivity\n- Keywords: Asia and Pacific, Asia-Pacific, Capital productivity, demographics, driver estimation, DTW method project growth, Dynamic Time Warping, economic convergence, Global, growth accounting, growth accounting analysis, growth forecasting, Human capital, income group, machine learning, machine-learning estimation, productivity, robust growth forecast, time series, Total factor productivity\n\n---\n\n Content in this bundle\n\n- Working Paper\n  - Working Paper (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - Working Paper (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540"
    }
  ],
  "bullets": [
    "[Markdown version](/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540/index.md)",
    "[Structured JSON version](/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540/index.json)",
    "[Bundle manifest](/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540/bundle-manifest.json)",
    "Authors: Natasha X Che, Federico J Diez, Anne Oeking, Weining Xin",
    "Published: August 22, 2025",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9798229018418.001",
    "Title: Dissecting Medium-Term Growth Prospects for Asia",
    "Authors: Natasha X Che, Federico J Diez, Anne Oeking, Weining Xin",
    "Publication type: IMF Working Papers",
    "Date: August 22, 2025",
    "Summary (as presented): This paper explores Asia-Pacific's medium-term growth prospects using two approaches. First, growth accounting analysis and machine-learning estimation reveal how demographics, capital deepening, productivity, and human capital shaped Asia's growth. Second, an innovative algorithm forecasts growth by matching countries' current conditions with historically analogous periods using Dynamic Time Warping (DTW). Comparing pattern-based forecasts with traditional projections highlights economic convergence and demographic headwinds. Results show that without ambitious reforms, Asia's growth will likely moderate, though remaining the world's fastest growing region. The paper offers data-driven tools for policymakers to identify growth drivers and generate robust forecasts.",
    "Growth accounting analysis and machine-learning estimation are used to quantify contributions of:",
    "Forecasting approach:",
    "Comparison of approaches highlights:",
    "Principal conclusion:",
    "The paper emphasizes data-driven tools to:",
    "Ambitious reforms are implied as necessary to sustain higher growth relative to the moderation projected without such reforms.",
    "Policymakers are provided with data-driven tools to prioritize and target reforms by identifying key growth drivers.",
    "Subject: Capital productivity, Economic growth, Growth accounting, Human capital, Labor, Population and demographics, Production, Total factor productivity",
    "Keywords: Asia and Pacific, Asia-Pacific, Capital productivity, demographics, driver estimation, DTW method project growth, Dynamic Time Warping, economic convergence, Global, growth accounting, growth accounting analysis, growth forecasting, Human capital, income group, machine learning, machine-learning estimation, productivity, robust growth forecast, time series, Total factor productivity",
    "**Working Paper**"
  ],
  "related": [
    {
      "title": "Working Paper",
      "role": "paper",
      "sourceUrl": "https://www.imf.org/-/media/files/publications/wp/2025/english/wpiea2025168-print-pdf.pdf",
      "summary": {
        "path": "/-/media/files/publications/wp/2025/english/wpiea2025168-print-pdf.pdf.md",
        "mime": "text/markdown"
      },
      "binary": {
        "path": "/-/media/files/publications/wp/2025/english/wpiea2025168-print-pdf.pdf",
        "mime": "application/pdf"
      }
    }
  ],
  "alternates": {
    "markdown": "/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540/index.md",
    "json": "/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540/index.json",
    "bundleManifest": "/en/publications/wp/issues/2025/08/22/dissecting-medium-term-growth-prospects-for-asia-569540/bundle-manifest.json"
  },
  "generatedAtUtc": "2026-09-17T02:10:24.799Z"
}