measures to alleviate poverty might instead emphasize unemployment insurance or other components of a social safety net that aim to protect against falling into poverty. Thus, data on poverty dynamics at the micro-level can inform our understanding of the drivers of poverty and provide insights into the kind of anti-poverty policies that are needed.

Unfortunately, evidence about such poverty dynamics is scarce in developing countries; this also holds for Malaysia. In general, panel surveys that follow the same households over time are needed in order to make statements about whether poverty is chronic or transitory. Such surveys are typically complex and costly, and as a result they are rare and often involve relatively small sample sizes. In addition, attrition can be a problem as households drop out of the sample for a variety of reasons. To the extent that attrition is non-random, it has consequences for the validity of results. Still, it is notable that in Southeast Asia, both Indonesia and Vietnam conduct panel surveys on household income or expenditure.

A variety of approaches that aim to overcome the constraints posed by the lack of panel data have been explored in the literature. The idea is to draw inferences about poverty dynamics via analysis of far more widely available cross-sectional data. One line of research focuses on pseudo-panel methods, in which insights about poverty transitions are gleaned through scrutiny of cohort averages in cross-sectional surveys.<sup>3</sup> Another approach constructs synthetic panels from cross-sectional surveys through econometric models estimated on the basis of time-invariant household characteristics (Dang, Lanjouw, Luoto and McKenzie, 2014). The empirical analysis in this paper is based on the latter approach. While the method does not permit true panel analysis—in which the trajectories of individual households can be followed over time—it does yield upper- and lower-bound estimates of transitions into or out of poverty at an aggregate level.<sup>4</sup> An appealing feature of the method is that it also allows for delving deeper into the data to construct profiles of the groups who experience the various poverty transitions. We will focus specifically on the composition of the group of chronically poor, comparing the likelihood of chronic poverty along several dimensions, such as ethnicity and geography. The synthetic panel bounds approach has been validated against actual panel data for a range of countries and regions with good results (Dang et al. 2014, Cruces et al. 2015, Perez 2015). In this paper we focus on poverty dynamics in Malaysia as observed over intervals between adjacent survey rounds in the 2004-2016 period.

> 3 See Deaton (1985) for the initial setup of the approach, and Bourguignon et al. (2004) for an application to poverty. Kraay and van der Weide (2019) explore the feasibility of drawing inferences about intragenerational mobility from aggregate macro data.

> 4 We note that a different variant of the synthetic panel method produces point estimates, but applying it was not feasible in our case. We refer to Garces-Urzainqui et al. (2021) for further discussion of the two variants.

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