scholarly journals Assessing health gradient with different equivalence scales for household income – A sensitivity analysis

2021 ◽  
pp. 100892
Author(s):  
Sakari Karvonen ◽  
Pasi Moisio ◽  
Kristian Vepsäläinen ◽  
Joonas Ollonqvist
2018 ◽  
Author(s):  
Caspar Kaiser

Do people adapt to changes in income? In contradiction to much of the previous literature, I find no evidence of adaptation to income in GSOEP (1984-2015) and UKHLS (1996-2017) data. Furthermore, I find that people also do not adapt to changes in reference income. Instead, reference income effects may be subject to reinforcement over time. Following the empirical approach of Vendrik (2013), I obtain these findings by estimating life satisfaction equations in which contemporaneous and lagged terms for a respondent’s own household income and their estimated reference income are simultaneously entered. Additionally, I instrument for own income and include lags of a large set of controls. What was found to be adaptation to raw household income in previous studies turns out tohave been driven by reinforcement of an initially small negative effect of household size that grows large over time. Implications of this result for the estimation of equivalence scales with subjective data are discussed.


2016 ◽  
Vol 43 (12) ◽  
pp. 1300-1314 ◽  
Author(s):  
Maneka Savithri Jayasinghe ◽  
Christine Smith ◽  
Andreas Chai ◽  
Shyama Ratnasiri

Purpose The purpose of this paper is to test whether household preferences satisfy the assumption of base-independence, to examine the effects of household income on equivalence scales and thereby food consumption economies of scale and to examine how far conventional poverty rates require adjustment when scale economies in food consumption are taken into consideration. Design/methodology/approach To achieve these aims, the authors use a Pendakur (1999) adaptation of the test of base-independence, and income dependent Engel (1895) equivalence scales. Findings In Sri Lanka, the hypothesis of base-independence is rejected: the equivalence scales increase with household income both at the national and the sectoral level, that is urban, rural and estate sectors. This suggests that low-income households enjoy greater scale economies. After adjusting for scale economies, urban, rural and estate poverty headcount ratios decline by 3.2, 8.8 and 13.7, respectively, while at the national level the decline is about 8.3. Research limitations/implications The results are based on the assumption that all of the adults in the households have identical tastes, irrespective of their gender and age. Furthermore, the survey data exclude three districts in the northern province of Sri Lanka due to resettlement activities took place after the civil war. Practical implications Higher scale economies among the poor imply that poverty among low-income households is overstated when using traditional measures of poverty rates. Originality/value The novelty of this paper is that it provides insights on the effect of income on food consumption economies of scale and implications of this phenomenon on poverty estimates in the context of a developing country like Sri Lanka.


2017 ◽  
Vol 237 (2) ◽  
pp. 115-141 ◽  
Author(s):  
Christian Dudel ◽  
Jan Marvin Garbuszus ◽  
Notburga Ott ◽  
Martin Werding

Abstract: Empirically analyzing household behavior usually relies on informal data preprocessing. That is, before an econometric model is estimated, observations are selected in such a way that the resulting subset of data is sufficiently homogeneous to be of interest for the specific research question pursued. In the context of estimating equivalence scales for household income, we use matching techniques and balance checking at this initial stage. This can be interpreted as a non-parametric approach to preprocessing data and as a way to formalize informal procedures. To illustrate this, we use German micro-data on household expenditure to estimate equivalence scales as a specific example. Our results show that matching leads to results which are more stable with respect to model specification and that this type of formal preprocessing is especially useful if one is mainly interested in results for specific subgroups, such as low-income households.


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