Accounting for Sri Lanka's Expenditure Inequality 1980–2002: Regression‐based Decomposition Approaches

Abstract

Sri Lanka liberalized its economy in 1977, paving the way for more rapid economic growth and higher rates of job creation. But tensions over distributional issues still plague the body politic. This paper investigates the evolution of Sri Lanka's expenditure distribution in the period 1980-2002 and uses three decomposition methodologies-the Fields, the Shapley value decomposition, and Yun's unified method-to determine underlying causes. The study finds that while average adjusted expenditure rose across strata, the rich experienced more rapid expenditure growth leading to greater inequality. Inequality change was driven by differential access to infrastructure, education, and occupation status. Demographic factors, including ethnicity, and spatial factors contributed very little. The study recommends policies that ensure more equitable access to income earning assets such as education and infrastructure services, and that contain the rise in inequality along sectoral, regional, and ethnic fault lines. Copyright 2009 The Authors. Journal compilation International Association for Research in Income and Wealth 2009.

Factor decomposition of the wealth distribution in the euro area

“…9 See e.g. Gunatilaka andChotikapanich (2009), Firpo et al (2007), Mookherjee and Shorrocks (1982), Fiorio (2006) as well as Yun (2006). 10 Using the techniques explained and derived e.g.…”

“…7 Without in any special ordering see for example Okamoto (2011), Chernozhukov et al (2009), Firpo et al (2007, Yun (2006), Fields (2003, Juhn et al (1993) for the USA; Machado and Mata (2005) for Portugal; Paul (2004) for Australia; Celestin and Clovis (2012) for Cameroon; Fournier (2001) for Taiwan; Mookherjee and Shorrocks (1982) for the UK; Fiorio (2006) for Italy; Morduch and Sicular (2002) for China; Fräßdorf et al (2011) for a comparison of the UK, Germany and the USA; Bourguignon et al (2008) for a comparison of Brazil and the USA; Gunatilaka and Chotikapanich (2009) for Sri Lanka; and López-Feldman et al (2006) for Mexico.…”

Effects of growth and reduction of income inequality on poverty in Northeastern Brazil, 2003-2008

“…The decomposition method based on regression allows the inclusion of any explanatory variables, including economic, social and demographic variables (Gunatilaka & Chotikapanich 2009). According to Wan & Zhou (2005), the procedure for its application depends on an earning equation (income generating function), which can be written as:…”

“…To calculate the levels of inequality, the three main measures were used, namely, the Gini index and the two indices of the generalized entropy class: Theil-L and Theil-T. Similar to the work of Gunatilaka & Chotikapanich (2009), this study also used some aggregate variables. Therefore, inequality was decomposed into six components: Education (Educ), Age (age and age squared), Gender, Race (Color) and Occupation (Ocup1 and Ocup2).…”

Decomposing Spatial Inequality in Sri Lanka: A Quantile Regression Approach

“…The decomposition of inequality using regression provides a neat solution for this (Wan 2007). The regression-based decomposition allows for the inclusion of control variables as well as other socioeconomic determinants of inequality rather than the geographical location (Gunatilaka and Chotikapanich 2009). Furthermore, regression-based decomposition analysis enables identification and quantification of the determinants of inequality (Wan 2002) which are important and of interest to economists and policy makers.…”