Trend Growth Durations & Shifts

Abstract

Policymakers and investors often conceptualize trend growth as simply a medium/long term average growth rate. In practice, these averages are usually taken over arbitrary periods of time, thereby ignoring the large empirical growth literature which shows that doing so is inappropriate, especially in developing countries where growth is highly unstable. This paper builds on this literature to propose an algorithm, called "iterative Fit and Filter" (iFF), that extracts the trend as a sequence of medium/long term growth averages. iFF separates important countryspecific historical episodes and trend growth durations -number of years between two consecutive trend growth shifts, vary substantially across countries and over time. We relate the conditional probabilities of up and down-shifts in trend growth next year to the country's current growth environment, level of development, demographics, institutions, economic management and external shocks, and show how both iFF and the predictive model could be employed in practice. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means without the prior permission in writing of the publisher nor be issued to the public or circulated in any form other than that in which it is published.Requests for permission to reproduce any article or part of the Working Paper should be sent to the editor at the above address. © Inna Grinis submitted 2017 TREND GROWTH DURATIONS & SHIFTSINNA GRINIS* Abstract. Policymakers and investors often conceptualize trend growth as simply a medium/long term average growth rate. In practice, these averages are usually taken over arbitrary periods of time, thereby ignoring the large empirical growth literature which shows that doing so is inappropriate, especially in developing countries where growth is highly unstable. This paper builds on this literature to propose an algorithm, called "iterative Fit and Filter" (iFF), that extracts the trend as a sequence of medium/long term growth averages. iFF separates important countryspecific historical episodes and trend growth durations -number of years between two consecutive trend growth shifts, vary substantially across countries and over time. We relate the conditional probabilities of up and down-shifts in trend growth next year to the country's current growth environment, level of development, demographics, institutions, economic management and external shocks, and show how both iFF and the predictive model could be employed in practice.

What Role Has Structural Change Played in Growth Accelerations for the Indian States? An Analysis for Pre- and Post-liberalization Periods

“…Our objective in this article is to measure sectors’ contribution to accelerations and/or decelerations in aggregate productivity. We have used the standard methodology as used in the existing literature (see e.g., the works of de Vries et al 2021; Hausmann et al, 2005, Timmer & de Vries, 2009; ) to see the structural change in the economy. The analysis is in the spirit of structural change model given by Lewis (1954) and further elaborated by Chenery (1979).…”

“…As mentioned before, a shift-share analysis is performed to locate the sectors defining the growth accelerations and decelerations of the selected states in India. First, the filter introduced by Hausmann et al (2005) is used to determine the periods of accelerations and decelerations in growth of GSDP per worker. Next, using the shift-share analysis, we decompose the labour productivity growth into those aided by productivity improvements ‘within sectors’ and those due to reallocation of labour ‘between sectors’.…”

“…Following Timmer and de Vries (2009), we employed the filter developed by Hausmann et al (2005) to arrive at the accelerations and decelerations in GSDP per worker. We constructed the filter in the following way.…”

“…Recent literature on economic growth has shifted the discipline’s course of enquiry from analysing just long-term growth trends to locating the factors that explain the accelerations and decelerations in growth (Arizala et al, 2017; Grinis, 2017; Hausmann et al, 2005; Timmer & de Vries, 2009). This is considered important, as there exists significant variation in growth rates across regions as well as within regions.…”

“…Using the standard shift-share analysis, we quantify the sectoral contributions to productivity growth via these two routes. This article first provides the periods of acceleration, deceleration and moderate growth for the 15 major states over the 1980–1981 to 2010–2011 period, based on a filter developed by Hausmann et al (2005). We then do a decomposition exercise where the sectoral contributions to productivity growth are decomposed into ‘within’ and ‘between’ effects.…”