{
  "title": "Structural Reforms and Economic Growth: A Machine Learning Approach",
  "publication": "IMF Working Papers, September 16, 2022",
  "sourceUrl": "https://www.imf.org/en/publications/wp/issues/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396",
  "canonical": "https://www.imf.org/en/publications/wp/issues/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396",
  "overlayPath": "/en/publications/wp/issues/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396/index.md",
  "summary": "The qualitative and granular nature of most structural indicators and the variety in data sources poses difficulties for consistent cross-country assessments and empirical analysis.",
  "sections": [
    {
      "heading": "Methodology",
      "content": "- Applied a machine learning approach: the partial least squares method (PLS).\n- Combined a broad set of cross-country structural indicators into a small number of synthetic scores corresponding to key structural areas.\n- Synthetic scores designed for consistent quantitative comparisons across countries and time."
    },
    {
      "heading": "Dataset and Scope",
      "content": "- Newly constructed dataset of synthetic structural scores in 126 countries between 2000-2019.\n- Dataset enables establishment of stylized facts about structural gaps and reforms and analysis of reform impacts on economic growth."
    },
    {
      "heading": "Key Findings on Growth Impact",
      "content": "- Structural reforms in the area of product, labor and financial markets as well as the legal system have a significant impact on economic growth in a 5-year horizon.\n- A one standard deviation improvement in one of these reform areas raises cumulative 5-year growth by 2 to 6 percent.\n- The analysis establishes stylized facts about structural gaps and reforms across the sample."
    },
    {
      "heading": "Synergies Between Reform Areas",
      "content": "- Evidence of synergies between different structural areas.\n- In particular, synergies identified between product and labor market reforms."
    },
    {
      "heading": "Policy Implications and Recommendations",
      "content": "- Prioritize reforms in product markets, labor markets, financial markets, and the legal system to achieve measurable gains in cumulative 5-year growth.\n- Consider sequencing and combination of reforms to exploit synergies, notably between product and labor market reforms.\n- Use synthetic structural scores for consistent cross-country benchmarking and to guide reform prioritization over time.\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/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396"
    }
  ],
  "bullets": [
    "[Markdown version](/en/publications/wp/issues/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396/index.md)",
    "[Structured JSON version](/en/publications/wp/issues/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396/index.json)",
    "[Bundle manifest](/en/publications/wp/issues/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396/bundle-manifest.json)",
    "Authors: Anil Ari, Gabor Pula, Liyang Sun",
    "Published: September 16, 2022",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9798400219955.001",
    "Applied a machine learning approach: the partial least squares method (PLS).",
    "Combined a broad set of cross-country structural indicators into a small number of synthetic scores corresponding to key structural areas.",
    "Synthetic scores designed for consistent quantitative comparisons across countries and time.",
    "Newly constructed dataset of synthetic structural scores in 126 countries between 2000-2019.",
    "Dataset enables establishment of stylized facts about structural gaps and reforms and analysis of reform impacts on economic growth.",
    "Structural reforms in the area of product, labor and financial markets as well as the legal system have a significant impact on economic growth in a 5-year horizon.",
    "A one standard deviation improvement in one of these reform areas raises cumulative 5-year growth by 2 to 6 percent.",
    "The analysis establishes stylized facts about structural gaps and reforms across the sample.",
    "Evidence of synergies between different structural areas.",
    "In particular, synergies identified between product and labor market reforms.",
    "Prioritize reforms in product markets, labor markets, financial markets, and the legal system to achieve measurable gains in cumulative 5-year growth.",
    "Consider sequencing and combination of reforms to exploit synergies, notably between product and labor market reforms.",
    "Use synthetic structural scores for consistent cross-country benchmarking and to guide reform prioritization over time.",
    "**Working Paper**"
  ],
  "related": [
    {
      "title": "Working Paper",
      "role": "paper",
      "sourceUrl": "https://www.imf.org/-/media/files/publications/wp/2022/english/wpiea2022184-print-pdf.pdf",
      "summary": {
        "path": "/-/media/files/publications/wp/2022/english/wpiea2022184-print-pdf.pdf.md",
        "mime": "text/markdown"
      },
      "binary": {
        "path": "/-/media/files/publications/wp/2022/english/wpiea2022184-print-pdf.pdf",
        "mime": "application/pdf"
      }
    }
  ],
  "alternates": {
    "markdown": "/en/publications/wp/issues/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396/index.md",
    "json": "/en/publications/wp/issues/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396/index.json",
    "bundleManifest": "/en/publications/wp/issues/2022/09/15/structural-reforms-and-economic-growth-a-machine-learning-approach-523396/bundle-manifest.json"
  },
  "generatedAtUtc": "2026-09-16T21:38:22.814Z"
}