empirical analysis using data for 21 emerging market economies and a panel vector autoregression approach.

The aforementioned studies have focused on different aspects of the impact of exchange rate regimes on macroeconomic dynamics in recipient economies, none of which directly addresses the economic growth consequences, although their results do carry some implications for that. Thus, the focus of this study is to examine directly, how exchange rate flexibility influences the way remittances affect economic growth. Notably, it departs from studies by Guliano and Ruiz-Arranz (2009) and Lartey (2013) which focus on the impact of remittances on economic growth without consideration for the role of exchange rate regimes.

The next section explores the data and considers an empirical examination of the extent to which exchange rate flexibility affects the relationship between remittances and economic growth. Section 4 discusses the results and the policy implications thereof, and section 5 presents some concluding remarks.

# 3 Data and Methodology

## 3.1 Characteristics of the data

The data set used constitutes annual observations that span the period, 1970-2007, for 135 developing and transition countries.<sup>2</sup> The data for exchange rate regimes is based on the Reinhart and Rogoff de-facto exchange rate regime (COARSE) classification, whereas the data for remittances and all other variables are from the World Bank’s World Development Indicators (WDI) database. Table 2 presents a description of the exchange rate regime classification scheme. Table 3 provides some basic descriptive statistics for the data on the main variables used in the analysis. The exchange rate regime varies between categories 1 and 5, with an increase indicating a movement towards a more flexible exchange rate regime. GDP per capita growth rate is highly variable across countries over the sample period, ranging between about -50 percent to about 91.7 percent, with a mean of about 7 percent. Remittances are characterized by a low of US$9,980 and a high of US$37.2 billion, with an average of US$687 million. When expressed as a share of GDP, remittances receipts amounted to the tune of about 5 percent of GDP on average.

Table 4 presents correlation coefficients between remittances and GDP per capita growth across the five exchange rate regime classes. With the exception of regime 2, all other regimes classes show a positive correlation between remittances and growth, of which only regimes 1 and 3 are statistically significant. The estimates further show that when regime classes are combined into two groups only, then for regimes 1 through 3, there is a positive and statistically significant correlation between

> 2 The following are noteworthy: a. The choice of countries was guided by availability of data for remittance recipients, and particularly for exchange rate regimes. b. Although the data spans 38 years, the time dimension is in the range, 13 -15 years, across the various estimations due to missing observations. c. Annual observations are used primarily in the estimations, because the literature documents that remittances may affect growth by enhancing macroeconomic stability via consumption smoothing over the business cycle, in addtion to the potential impact through an investment channel. Refer to Lartey (2013) for further details.

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