# **6. Did remittances cause the increase in real unit labor costs?**

Can the rise in domestic currency real unit labor costs that characterized many of the high remittance recipient economies since the early 2000s be attributed to the remittances themselves? Although there are theoretical reasons for suspecting that high remittance receipts were a causal factor, as discussed in section 2, there are also other possible causes; for example, a fall in the capital intensity of production. To evaluate the influence of remittance receipts on the evolution of domestic currency real unit labor costs, we estimate panel data regressions using data from the countries in table 2. The regression equation that we estimate is as follows. log (RULC(LC))i = β1RMTi + β2KYi + β3ODAi i (6) The dependent variable is the log of local currency real unit labor costs for each country in each + εε year while the regressors are remittances as a share of GDP, the capital output ratio and net receipts of official development assistance (ODA) as a share of GDP. The subscripts i and t denote the country and year, respectively. The expected sign of the coefficient on remittances is positive and that on the capital output ratio is negative, for the reasons discussed in sections 2 and 3. The theoretical impact of aid is most likely to be positive. Aid inflows could have positive effects on aggregate demand and therefore potentially also on labor demand, although that depends upon what sectors benefit the most from the increased aggregate demand. It is difficult to envisage other variables which would have a systematic effect on RULC, as this would require that the variable has a systematic effect on real wages which is different to that of its effect on labor productivity. There are many variables which would affect labor productivity, such as improvements in human capital, but these variables would also tend to have similar effects on real wages leaving RULC unchanged.

The data are annual observations. For most of the 28 countries in the sample, the data cover the period 2000 to 2017. However, for five of the countries, the time period is shorter because of missing observations, mostly on remittances in some of the years in the first half of the 2000s. The real unit labor cost data are the same as those used in table 2. The capital output data are taken from the Penn World Tables. The ODA data are taken from the WDI. However, for more than a third of the transition economies, there are no entries for ODA in the WDI, presumably because they did not receive any aid as they were not eligible given their income per capita. For these countries we have entered a zero for the relevant observation.

We use two methods of econometric estimation. First, we estimate a country fixed effects regression using OLS, which includes 27 dummy variables for the countries. The fixed effects regression controls for unobserved differences between countries which are constant over time (time invariant country specific characteristics). Second, we run generalized least squares (GLS) regressions which is a more efficient estimator than OLS when the regression errors are heteroscedastic.

A potential problem for these regressions is endogeneity and in particular the potential reverse causality from the dependent variable to the regressors. It is unlikely that there is contemporaneous causality running from RULC to the capital output ratio. The latter changes only slowly over time as a result of investment decisions taken, for the most part, several years in the past and of the depreciation of the existing capital stock. As such it is unlikely that the 18