**The rest of the paper focuses on economic mobility and aims at disentangling the observed net poverty changes and identifying correlates of upward economic mobility in Moldova** . Given that observed net poverty changes can mask gross movements in and out of poverty, analysis on economic mobility can help determine if this was the case in Moldova during the 2000s. Second, this paper identifies correlates of upward economic mobility both during the periods of strong poverty reduction, as well as in the more recent periods. This can help us understand which characteristics are associated with households’ ability to improve their living standards, and how have they changed as the pool of poor in Moldova becomes smaller.

# **3. Economic Mobility: Concepts and Methods**

**Economic mobility refers to the transformation of an initial welfare distribution (e.g., income or consumption) into another.** Measures of mobility can be studied in the intra- or inter-generational domain, depending on whether we are focusing on distributions of welfare across generations - for a parent and a child - (inter-generational mobility) or for the same individual or household in two time periods (intra-generational mobility).  This study focuses on **intra-generational mobility** by analyzing consumption movements for households in Moldova over time, looking at both upward mobility (e.g. households escaping poverty) and downward mobility (e.g., households falling into poverty). Analyzing economic mobility can provide valuable information, particularly on churning and vulnerability (movements in and out of poverty), that traditional net poverty changes cannot. The concept of mobility used in this study allows for the construction of poverty transition matrices that can be associated with other relevant and interrelated household or individual dynamics, such as labor market profiles and demographic characteristics. In addition, the analysis can go beyond a poverty focus to provide insights into the complete welfare distribution, particularly movements into the middle class.

**One of the main limitations of studying intra-generational mobility is data availability.** Understanding economic mobility requires longitudinal welfare data since findings relate to mobility patterns of one and the same household over time.  In particular, the dearth of panel data has been a barrier to the mobility literature and presented a considerable challenge to advancing our knowledge of these dynamic processes. The recent methodology developed by Dang et al. (2014), using a variant of small-area estimation techniques, proposes an alternative to panels by creating “synthetic panels” out of repeated cross-sectional data. The “synthetic panel” method is an imputation methodology of welfare that uses two rounds of cross-sections and time invariant individual and household characteristics to explore mobility at a more disaggregated level than cohorts. It is based on assumptions on error correlation across periods, which at the extreme are either zero correlation (upper bound: high mobility scenario) or full correlation (lower bound: low mobility scenario). Therefore, the method provides bounds of economic mobility. Previous studies have relied on the lower-bound estimate of economic mobility as a “conservative” estimate of economic mobility in a country (see World Bank 2013).<sup>5</sup>

> 5 The lower bound builds on the assumption that positive (negative) consumption shocks in the first period repeat during the second period. Thus movements across the welfare distribution are limited and in the extreme society becomes extremely immobile.

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