<mark>features of remittances and aid flows imply that they can support activity in the face of economic adversity and help facilitate better risk sharing outcomes.</mark><sup>6</sup> Our paper relates to some other strands of the literature that focus on the behavior of different types of capital flows. For example, it is related to the seminal work by Lucas (1990) on the capital allocation puzzle that considers why so little capital flows from rich to poor countries. Many studies provide explanations for the puzzle: institutional underdevelopment and expropriation risk leading to capital flowing uphill (Alfaro, Kalemli-Ozcan and Volosovych 2008; Bai and Zhang 2010; Benhima 2013); investors overreacting to signs of trouble in EMDEs (Chinn, Dooley and Shrestha 1999; Chinn and Kletzer 2001).<sup>7</sup> Recent research considers the links between remittances and aid flows and illicit capital outflows. While flows such as development aid are found to be positively correlated with illicit outflows in the presence of capital controls, remittances are negatively correlated with illicit outward capital flight (Steinkamp and Westermann, 2021). Aid may be susceptible to being diverted by the recipient governments, but a similar behavior is unlikely to be tolerated by foreign workers supporting their families back home through remittances.

The remainder of the paper is structured as follows. The next section briefly describes the database and empirical framework. Section 3 analyzes the linkages between different types of capital flows and international risk sharing, and undertakes a battery of robustness tests. Section 4 offers a few concluding remarks.

# 2. Database and Empirical framework

# 2.1. Database

We examine the relationship between cross-border capital flows and international risk sharing using a database that includes a large sample of EMDEs. Real consumption and real GDP data are drawn from the World Bank’s World Development Indicators (WDI). Population statistics are from the United Nations’ National Accounts Main Aggregates Database. It is widely known that aggregate output and consumption data are nonstationary, whereas first differences of these variables are stationary. Hence, we follow the standard practice and carry out the analysis using first differenced series.

Total remittances include personal transfers, defined as all current transfers in cash or in kind received by resident households from nonresident households, and compensation of employees, defined as gross earnings of workers residing abroad. Remittance inflows are drawn from the IMF’s

> 6 A few previous studies have investigated the ability of remittances to reduce macroeconomic volatility. Balli and Rana (2015) follow a methodology pioneered by Asdrubali, Sørensen and Yosha (1996) and show that remittances help delink national income from domestic output fluctuations. Our paper studies how remittance inflows affect measures of international risk sharing. <mark>Differences in institutional quality and stages of development between countries that receive remittances and aid flows and those that send these flows can boost the risk sharing potential of remittances (</mark> Callen, Imbs and Mauro 2015; Parsley and Popper 2021).

> 7 Other studies document that faster growing developing countries tend to receive more private capital inflows, but experience even more public capital outflows (Aguiar and Amador 2011; Alfaro, Kalemli-Ozcan and Volosovych 2014; Kim and Zhang 2020).

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