Return migration is linked to both agricultural and non-agricultural investments

Return migration can also affect the agricultural sector in many of the same ways as remittances, since the migrants may return with savings, as well as their labour and new skills and contacts (human capital). Of the 258 households with return migrants, 137 (13%) were from farming households while 121 (10%) were from non-farming households, a statistically significant difference. looking specifically only at migrant households (those with current emigrants or return migrants), the difference in rate between farming and non-farming households is even wider (29% vs. 24%).

looking at the same outcomes as for the analysis on remittances above finds that households with return migrants perform better than households with no return migrant for several outcomes (making agricultural expenditures and investing in non-agricultural businesses; Figure 5.4). Moreover, the difference between return migrant and non-return migrant households was statistically significant for agricultural expenditures (4.4% vs. 1.7%), as well as for operating a non-agricultural business (8% vs. 2%). In addition, those households with return migrants that had made agricultural expenditures, had spent more in the previous 12 months than agricultural households without return migrants

(GEL 775 vs. 284). As was the case earlier, the results come with the caveat that the analysis was based on only 22 households.

Figure 5.4. Households with return migrants are more likely to invest in agriculture and to own a non-agricultural business

Household asset expenditures and business ownership, by whether household has a return migrant

Note: Statistical significance calculated using a chi-squared test is indicated as follows: ***: 99%, **: 95%, *: 90%.

Source: Authors’ own work based on IPPMD data.

Sta.tLink^^2 http://dx.doi.org/10.1787/888933457931

A similar regression analysis as the one described in Box 5.2 was used to explore whether return migrant households invest their savings in agriculture. The probability of receiving remittances is replaced in the equation with the probability of having a return migrant in the household. The results found no relationship between having a return migrant in a household and making an agricultural expenditure. However, as for remittances, return migrant households that have made agricultural expenditures spend more than households without return migrants, and the link is strongly statistically significant (Table 5.5). While return migration is not statistically significantly linked with running activities in both arable farming and animal rearing, there was also no evidence that it is linked with specialising in one of the two activities in particular. In addition, return migrant households are also more likely to operate a non-agricultural business, suggesting that the human, financial and social capital brought back by return migrants is channelled towards productive use, but outside of the sector.

Table 5.5. Return migration is positively linked with investing in agriculture and running a non-farming business

Dependent variable: Investment outcomes Main variables of interest: Household has a return migrant Type of model: Probit/OLS Sample: Agricultural households

Variables of interest

Dependent variables

(1)

Household has made agricultural expenditures (equation 3)

(2)

Logged amount spent on agricultural asset expenditures (equation 4)

(3)

Household has activities in both farming and animal rearing (equation 3)

(4)

Household operates a non-agricultural business (equation 3)

Household has a return migrant

0.020

1.78***

0.038

0.024*

(0.016)

(0.219)

(0.047)

(0.013)

Number of observations

1 066

22

1 079

1 076

Note: Results that are statistically significant are indicated as follows: ***: 99%, **: 95%, *: 90%. Standard errors are in parentheses and robust to heteroskedasticity. Coefficients from probit model estimations reflect marginal effects.

Migration therefore seems to have a positive impact overall on the agricultural sector in Georgia, through emigration, remittances received by households and return migration. In addition, return migration seems to be a catalyst for a greater diversification of activities outside of the sector. On the other hand, public policies in the agricultural sector are also likely to have an impact on migration outcomes, such as the decision to emigrate, remit, return, and stay in the country. This dynamic is investigated in the next section.

 
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