Do Adjustments for Equivalence Scales Affect Poverty Dynamics? Evidence from the Russian Federation during 1994–2017

• Published date: 01 April 2022
• Author: Kseniya Abanokova,Hai‐Anh H. Dang,Michael Lokshin
• Date: 01 April 2022
• DOI: http://doi.org/10.1111/roiw.12559

© 2021 International Association for Research in Income and Wealth

S167

DO ADJUSTMENTS FOR EQUIVALENCE SCALES AFFECT POVERTY

DYNAMICS? EVIDENCE FROM THE RUSSIAN FEDERATION DURING

1994– 2017

by Kseniya abanoKova

National Research University Higher School of Economics

Hai-anH H. Dang*

World Bank

International School, Vietnam National University, Hanoi

Indiana University

AND

MicHael loKsHin

World Bank

Hardly any literature exists on the relationship between equivalence scales (ESs) and poverty dynam-

ics for transitional countries. We analyze ESs constructed from subjective wealth and more than 20

waves of household panel survey data from the Russia Longitudinal Monitoring Survey between

1994 and 2017. We find that the ES elasticity is sensitive to household demographic composition and

ES adjustments result in lower estimates of poverty lines. We decompose poverty into chronic and

transient components and find that chronic poverty is positively related to the adult scale parameter.

However, chronic poverty is less sensitive to the child scale factor compared with the adult scale factor.

Interestingly, the direction of income mobility might change depending on the specific scale parameters

that are employed. The results are robust to different measures of chronic poverty, income expectations,

reference groups, functional forms, and various other specifications.

JEL codes: I30, J10, O15

Keywords: poverty, poverty dynamics, equivalence scale, Russia, panel survey

1. introDuction

Obtaining comparable measures of household incomes across households

of different sizes and composition— or converting these incomes on a common

Note: We would like to thank the editor Ilya Voskoboynikov, two anonymous reviewers, Conchita

D’Ambrosio, Sam Freije- Rodriguez, Rostislav Kapeliushnikov, Ambar Narayan, Sergey Roshchin,

Jacques Silber, Ruslan Yemtsov, and seminar participants at IARIW conferences, Centre for Labour

Market Studies, and World Bank for useful feedback on earlier versions. We are grateful to Martin Biewen

for sharing his Stata code. We would also like to thank the UK Foreign Commonwealth and Development

Office (FCDO) and NRU- HSE Basic Research Program for additional funding assistance.

*Correspondence to: Hai- Anh H. Dang, Data Production and Methods Unit, Development Data

Group, World Bank, Washington, DC 20433, USA (hdang@worldbank.org).

[Corrections made on 14th April 2022, after first online publication: Author order has been revised

in this version.]

Review of Income and Wealth

Series 68, Number S1, April 2022

DOI: 10.1111/roiw.12559

bs_bs_banner

Review of Income and Wealth, Series 68, Number S1, April 2022

S168

© 2021 International Association for Research in Income and Wealth

(equivalence) scale— is a crucial task for welfare measurement. Indeed, a large

body of literature has demonstrated that there are substantial effects of scale

adjustments on poverty and profiles of the poor for various countries at different

income levels (Lanjouw and Ravallion, 1995; Peichl and Pestel, 2012; Bishop et

al., 2014). Equivalence scales are often estimated based on expenditure data; one

major disadvantage of this method is that it requires strong identifying assump-

tions (Deaton and Paxson, 1998).

In this paper, we make several contributions to the literature on equivalence

scales (ESs) and poverty measurement. First, we estimate ESs using an alternative

source of data, subjective well- being data. While a growing literature has followed

this approach using panel data, these studies mostly rely on life satisfaction and

income satisfaction questions.1 We analyze a subjective well- being question where

individuals are asked to evaluate their own level of material welfare on a nine- point

scale from “poor” to “rich.” This question arguably better captures the multidi-

mensional nature of welfare and is closely related to household welfare than satis-

faction variables (Ravallion and Lokshin, 2001, 2002).

Second, we offer new and interesting findings regarding the dynamics of pov-

erty given ES adjustments (scaling) on long- run household panel data from the

Russian Longitudinal Monitoring Surveys (RLMS). It is well- known that policies

to address short- term static poverty are quite different from those for long- ter m

chronic poverty.2 Yet, while these dynamics, by definition, require an analysis that

must be based on panel data, the data used in the existing literature to investigate

the effects of scaling on poverty measurement typically come from cross- sectional

surveys (e.g. Newhouse et al., 2017).3 Such data do not provide a good understand-

ing of how household demographics impact transient or chronic poverty, or to put

it differently, how employing different scaling parameters affects household pov-

erty dynamic patterns. To our knowledge, we offer the first study to investigate the

impacts of scale adjustments on poverty dynamics. As discussed later, we employ

several different definitions of poverty dynamics for a more robust analysis.

Furthermore, the RLMS offers a longer panel compared to most existing

studies. Such data allow us to extend our analysis to broader definitions of

households— including multigenerational households— and to better capture

demographic changes related to the formation of extended families.4

Finally, the more affluent countries examined in existing studies, such as

Germany, Switzerland, or the United Kingdom, have, on average, a smaller

1Two main types of subjective well- being data have been analyzed in the economic literature. The first

type asks respondents about a hypothetical minimum income level that is required to reach a specified level

of well- being (e.g. Garner and Short, 2004), and the second type asks respondents to evaluate their level of

satisfaction with life or income (e.g. Biewen and Juhasz, 2017; Borah et al., 2019). Our paper is more related

to the second approach and we also offer robustness checks using life satisfaction outcomes.

2We employ two popular approaches in the literature to decompose poverty into chronic and tran-

sient components. Jalan and Ravallion (2000) define individuals as chronically poor if their permanent

incomes are below a specified poverty line, while Foster (2009) considers individuals to be chronically

poor if they spend some specified time below the poverty line.

3But see Dang et al. (2019) for a review of alternative poverty measurement methods in contexts

where no panel data exist.

4Only Borah et al. (2019) used longer panel data to analyze equivalence scales but their analysis

was restricted to “classical households,” which consist of either a single adult or two partnered adults,

with or without children for Germany.