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A multivariate unobserved components model to estimate potential output in the euro area: a production function based approach

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  • Tóth, Máté

Abstract

This paper builds an unobserved components model that combines a multivariate filter approach with a Cobb-Douglas production function. This combination allows potential output estimates to incorporate more economic structure than the traditional production function approach, while retaining the ability to conduct growth accounting exercises. The model is a backward-looking state space model estimated with Bayesian methods employing the Kalman filter to jointly decompose six key observable variables (real GDP, unemployment rate, labour force participation rate, hours worked per person, a measure of core inflation and wage inflation) into trend and cyclical components. To do so, it relies on several reduced form relationships across the cyclical components, such as a wage and a price Phillips curve and an Okun's law type relationship, while it also assumes common trends for a few variables and allows for hysteresis effects. The model is estimated on aggregate euro area data with Bayesian methods. The paper finds that the resulting output gap estimates have good revision properties and reasonable forecasting performance in particular in terms of GDP and core inflation vis-a-vis a set of benchmarks. JEL Classification: C32, D24, E32, E37

Suggested Citation

  • Tóth, Máté, 2021. "A multivariate unobserved components model to estimate potential output in the euro area: a production function based approach," Working Paper Series 2523, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20212523
    Note: 2510084
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    Cited by:

    1. Matteo Barigozzi & Claudio Lissona & Matteo Luciani, 2024. "Measuring the Euro Area Output Gap," Finance and Economics Discussion Series 2024-099, Board of Governors of the Federal Reserve System (U.S.).
    2. Pönkä, Harri & Sariola, Mikko, 2021. "Output gaps and cyclical indicators: Finnish evidence," BoF Economics Review 6/2021, Bank of Finland.

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    More about this item

    Keywords

    Bayesian estimation; production function; state-space model;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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