errors, caused by either sampling or non-sampling issues, are a problem that could arise when projecting future income growth. Given that income statistics and poverty measures depend on Census and household survey data, mistakes made when collecting this information might skew the recovered statistics, for example, Gini coefficients and income averages.

Another significant concern to model the dynamics of the income distribution is related to the causality between inequality and economic growth. When we think about the forces interacting between wealth inequality and economic growth, we might be hesitant to make conclusions regarding the magnitudes and even directions. In the specific case of wealth inequality affecting growth, there is a strand of the economic literature highlighting that inequality is suitable for incentives and therefore for growth in market-oriented economies, whereas another strand argues that inequality has a direct adverse effect on economic growth (Aghion, Caroli, and GarciaPenalosa 1999).<sup>10</sup> Recent empirical research finds that the presence of weak instruments, using a system generalized method of moments (GMM) procedure, is in detriment of robust conclusions about the effect of inequality on growth in either direction (Kraay 2015). Likewise, by making use of robust GMM estimations, Ferreira, Lakner, Lugo, and Özler (2018) find no significant result of total income inequality affecting economic growth. Lastly, Marrero and Serven (2018) develop a model where the impact of inequality on growth can be positive or negative, as it combines two types of effects—indirect and direct—that could be mutually opposing. Poverty is used to identify the indirect impact of inequality on growth. The effect of inequality on the aggregate investment of non-poor individuals can explain the direct outcome. The authors find that the sign and immediate impact of inequality on growth are fragile; this impact can take a positive or negative sign depending on the specific model used and the econometric approach employed. The authors   also find that the indirect effect of inequality and growth via poverty is negative and significant   at high but not extremely high poverty rates, whereas it is nonsignificant at low poverty rates.

> 10 Aghion, Caroli, and Garcia-Penalosa (1999) discuss that there are at least three reasons why inequality might have a direct adverse impact on growth in economies with heterogeneous wealth or human capital endowments and imperfect capital markets: i) inequality reduces investment opportunities; ii) inequality deteriorates borrowers’ incentives; and iii) inequality generates macroeconomic volatility. In contrast, the same authors discuss three views of why inequality can be growth-enhancing: i) Kaldor’s hypothesis that the marginal propensity of the rich to save is higher than that of the poor; ii) investment indivisibilities for setting new industries: in the absence of a broad and well-functioning market for shares, wealth needs to be sufficiently concentrated to be able to cover large sunk costs; and iii) incentive and moral hazard considerations: the trade-off between output efficiency and (wage) equality.

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