Looking for a break: Identifying transitions in growth regimes

Kar, Sabyasachi; Pritchett, Lant; Raihan, Selim; Sen, Kunal

doi:10.1016/j.jmacro.2013.09.022

Cited by 56 publications

(73 citation statements)

References 19 publications

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“…In this paper, we embrace the basic definition of trend growth as a medium/long term average growth rate and therefore think about the trend as evolving discretely. This section develops a simple iterative algorithm that builds on the "Fit and Filter" (FF) approach proposed in KPRS [29] and extracts trend growth by first identifying economically significant trend shift dates. We start with a precise definition of trend growth in our context, then motivate and describe the trend extraction method, and finally discuss several examples of what it gives in practice.…”

Section: Extracting Trend Growthmentioning

confidence: 99%

“…In this paper, we employ the filter proposed in KPRS [29], which sets F = 2 for a first shift, then distinguishes between a trend shift in the same direction (e.g. up-shift after up-shift) with F = 1, and a trend shift in the opposite direction (e.g.…”

Section: Extracting Trend Growthmentioning

confidence: 99%

“…A recent paper by Kar, Pritchett, Raihan and Sen [29] summarizes the shortcomings of both approaches and proposes to combine them in order to overcome their limitations while preserving their advantages. The authors call the result "Fit & Filter" (FF) because the approach "involves the best fit of the BP method to the data in the first stage, and the application of a filter to the breaks identified in the first stage in the second stage."…”

Section: The Original Fit and Filter (Ff)mentioning

confidence: 99%

“…This issue is rarely addressed explicitly, and averages are often taken over subjectively defined periods of time, decades, the whole sample of data that one has access to, etc., thereby ignoring the large empirical growth literature that started in the 1990s with the seminal contributions of Easterly et al [15] and Pritchett [33], and which shows that employing "arbitrarily chosen long-run average growth rates fails to take account of a very important 'stylised fact' of economic growth, i.e., while the growth process of "developed" economies is well characterized by such a single long run average growth rate (with a "business cycle" around this trend) this is not true of most countries in the world, many of whom exhibit multiple structural breaks in growth rates" (Kar, Pritchett, Raihan, and Sen [29], henceforth KPRS).…”

Section: Introductionmentioning

confidence: 99%

“…This method, called the "iterative Fit and Filter" (iFF), generalizes the "Fit and Filter" (FF) approach developed in KPRS [29] to identify breaks in growth time series. iFF preserves the merits of the original FF, in particular, the ability to identify a much larger number of breaks in the presence of high growth volatility than purely statistical methods (Bai-Perron [9,8]), but overcomes the problem of having to postulate a somewhat arbitrary maximum number of breaks in the first step and the fact that, unlike in purely statistical methods, the final break dates identified by the original FF are not necessarily optimally located.…”

Section: Introductionmentioning

confidence: 99%

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Trend Growth Durations & Shifts

Grinis

2016

SSRN Journal

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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.

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Section: Extracting Trend Growthmentioning

confidence: 99%

Section: Extracting Trend Growthmentioning

confidence: 99%

Section: The Original Fit and Filter (Ff)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Trend Growth Durations & Shifts

Grinis

2016

SSRN Journal

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Identifying structural breaks and growth regimes in middle eastern economies

2020

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This study is an attempt to empirically determine structural breaks in economic growth of selected Middle Eastern countries. We combined the statistical approach with a subjective approach to identify break points in the growth process during the period 1970-2016. Thereby, we try to classify breaks into up-breaks and down-breaks resulting into different regimes ranging from stagnation to strong growth. In a sample of 17 countries examined, 15 countries exhibited significant breaks in trend function of growth process as per the fit and filter approach. We found total 41 plausible breaks -19 up breaks and 22 down breaks. Moreover, the spatial distribution of breaks shows that over 68% of the breaks are reported from oil-rich countries while as 31% from nonoil. The paper highlights the key point that growth performance of the Middle Eastern countries is very volatile and gambles in the alternating cycles of collapse, stagnation, moderate, rapid and strong growth.

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Is this time different? Social capability and catch‐up growth in Ethiopia, 1950–2020

Till

2022

J of Intl Development

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This paper explores whether Ethiopia's rapid economic growth is transformative enough for the country to eventually catch up with high‐income countries. It does so by exploring the change and continuity of four elements of social capability from 1950 to 2020: structural transformation, economic inclusion and the state's autonomy and accountability. It finds that Ethiopia's social capability modestly strengthened until the mid‐1970s, then weakened until the early 2000s, and has since strengthened again. However, the level of inclusion has been persistently low. In conclusion, although there are grounds for optimism, limited economic inclusion is a key concern for future catch‐up growth.

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Looking for a break: Identifying transitions in growth regimes

Cited by 56 publications

References 19 publications

Trend Growth Durations & Shifts

Trend Growth Durations & Shifts

Identifying structural breaks and growth regimes in middle eastern economies

Is this time different? Social capability and catch‐up growth in Ethiopia, 1950–2020

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