IMF Working Papers

Estimating Potential Output in Chile: A Multivariate Filter for Mining and Non-Mining Sectors

By Patrick Blagrave, Marika Santoro

October 14, 2016

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Patrick Blagrave, and Marika Santoro. Estimating Potential Output in Chile: A Multivariate Filter for Mining and Non-Mining Sectors, (USA: International Monetary Fund, 2016) accessed September 26, 2024
Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

Using a multivariate filter, we estimate potential growth rates in Chile’s mining and non-mining sectors. Estimates for the mining sector incorporate information on copper prices, whereas estimates for non-mining reflect information on inflation and unemployment rates. To better understand the drivers of potential growth, we decompose estimates into capital, labor (adjusted for human-capital and hours worked), and total-factor productivity using a production-function. Our estimates of potential output in Chile suggest that an important part of the recent growth slowdown has been structural, with potential-output growth slowing to 2½ percent in recent years, although it plausibly could be higher in the medium-term.

Subject: Economic sectors, Metal prices, Mining sector, Output gap, Potential output, Prices, Production, Total factor productivity

Keywords: Copper-price gap, Gap shock, Global, Macroeconomic Modeling, Metal prices, Mining sector, Mining-sector output gap, MVF estimate, MVF estimation result, Output gap, Output-gap equation, Potential Output, Price change, Production Function, Production-function accounting, Total factor productivity, Trend copper-price movement, Trend output, WP

Publication Details

  • Pages:

    32

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2016/201

  • Stock No:

    WPIEA2016201

  • ISBN:

    9781475544923

  • ISSN:

    1018-5941

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