Migrant Remittances During a Global Shock: Evidence From the COVID-19 Pandemic in Mexico
02 nov 2023
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Publicado en línea: 02 nov 2023
Recibido: 25 nov 2022
DOI: https://doi.org/10.2478/izajodm-2023-0002
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© 2023 Christian Ambrosius et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1

Figure 2

Online Appendix 2:

Remittances and electronic payments_ Non-instrumented OLS
Level of remittances (log) | 0.80 |
0.69 |
0.34 |
0.28 |
0.03 |
0.01 [0.02] |
Decrease in workplace mobility | 0.72 [0.55] | |||||
Decrease in out-of-home events | 0.44 |
0.29 |
||||
Level of aggregation | state | state | municipal | municipal | municipal | municipal |
Quarters covered | Q1, Q2 | Q1, Q2 | Q1, Q2 | Q1, Q2 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 |
0.89 | 0.91 | 0.47 | 0.57 | 0.66 | 0.70 | |
F-stat | 116 | 106 | 167 | 144 | 562 | 299 |
No. of observations | 62 | 62 | 772 | 772 | 1544 | 1544 |
Data description
Remittances | Inflow of total amount of remittances, in millions of USD. |
state | 284.24 [248.65] | 298.88 [258.78] | 321.47 [258.48] | 320.73 [272.49] |
municipal | 15.48 [19.09] | 16.26 [20.21] | 17.68 [22.38] | 17.49 [21.29] | ||
MX employment levels | Number of formally employed persons registered with the Mexican Institute for Social Security IMSS, as a share of the adult population. |
state | 0.23 [0.10] | 0.22 [0.10] | 0.22 [0.10] | 0.22 [0.10] |
municipal | 0.18 [0.16] | 0.17 [0.15] | 0.17 [0.15] | 0.17 [0.15] | ||
US unemployment exposure | Average exposure of migrants from each Mexican administrative entity |
state | 0.04 [0.00] | 0.13 [0.01] | 0.09 [0.01] | 0.07 [0.00] |
municipal | 0.04 [0.00] | 0.13 [0.01] | 0.09 [0.01] | 0.07 [0.00] | ||
Electronic payments | Total amount of electronic payments made via debit or credit card, geo-located at its point of sale. In millions of current Mexican Pesos. |
state | 8845.12 [7268.58] | 6737.49 [5437.24] | 9170.64 [7452.55] | 9656.16 [7660.82] |
municipal | 675.79 [1541.01] | 509.52 [1160.97] | 651.06 [1480.99] | 785.08 [1772.43] | ||
Decrease in workplace mobility | Percentage drop in mobility between residence and workplace using location history from Google accounts on people's mobile devices, with respect to a median value for baseline days in the five-week period from January 3 to February 6, 2020. |
state | −0.04 [0.02] | −0.36 [0.06] | −0.26 [0.04] | −0.20 [0.03] |
Migrants’ exposure to decrease in workplace mobility | Average exposure of migrants from each Mexican administrative entity |
state | −0.13 [0.00] | −0.36 [0.01] | −0.32 [0.00] | −0.27 [0.01] |
municipal | −0.13 [0.00] | −0.36 [0.01] | −0.32 [0.01] | −0.27 [0.01] | ||
Decrease in out-of-home events | Drop in the number of out-of-home events of cell-phone users, relative to the baseline data (March 2). The indicator first calculates the daily median for out-of-home events of all cell phone users, and then calculates the median over quarterly periods. Data before March 1 is set to zero and the fourth quarter ends on November 30. |
municipal | 0.00 [0.00] | −0.21 [0.17] | −0.28 [0.15] | −0.32 [0.15] |
Financial development | Number of bank accounts (sight deposits or “ |
state | 7.5 [10.6] | 6.9 [9.4] | 7.0 [9.5] | 7.1 [9.5] |
municipal | 11.9 [21.2] | 10.7 [20.4] | 10.7 [20.1] | 10.6 [22.0] | ||
Distance | Weighted average of direct distance in km from state capitals in Mexico to the state capital in the US state where migrants reside using the haversine formula. For exposure to unemployment, the average (weighted) distances between origin and destination is calculated depending on the distribution of migrants across the US. |
state | 2016.13 [526.60] | |||
municipal | 2183.45 [589.86] |
Elasticity of remittances with respect to mobility drops_ State-level regressions_
Migrants exposure to decrease in workplace mobility | 8.33 |
8.11 |
3.30 |
3.28 |
3.24 [2.35] | ||
Decrease in workplace mobility | 0.52 |
0.48 |
0.08 [0.24] | 0.05 [0.26] | 0.04 [0.28] | ||
Level of aggregation | state | state | state | state | state | state | State |
Quarters covered | Q1, Q2 | Q1, Q2 | Q1, Q2 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 |
Interaction between weighted distance to diaspora and time | No | No | No | No | No | No | Yes |
0.35 | 0.26 | 0.40 | 0.50 | 0.49 | 0.50 | 0.52 | |
No. of observations | 62 | 62 | 62 | 124 | 124 | 124 | 124 |
Elasticity of remittances with respect to employment_ State-level regressions
US unemployment exposure (log) | −1.02 |
−1.00 |
−0.50 |
−0.55 |
−0.55 |
−0.60 |
MX employment (log) | 0.19 [0.30] | −1.13 |
−0.73 [0.60] | −0.56 [0.59] | ||
Level of aggregation | state | state | state | state | state | state |
Quarters covered | Q1, Q2 | Q1, Q2 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 |
Interaction between weighted distance to diaspora and time | No | No | No | No | No | Yes |
0.43 | 0.44 | 0.51 | 0.55 | 0.56 | 0.58 | |
No. of observations | 62 | 62 | 124 | 124 | 120 | 120 |
Effect of remittances on the amount of electronic payments_ Two-stage least squares
Amount of remittances (log) | 1.2 |
1.3 |
0.73 |
0.70 |
0.5 |
0.55 |
Drop in workplace mobility (Google) | 0.0038 [0.0078] | |||||
Drop in out-of-home events (GranData) | 0.40 |
0.32 |
||||
Financial development | −0.017 [0.12] | 0.28 [0.42] | −0.29 |
|||
Level of aggregation | state | state | municipal | municipal | municipal | municipal |
Weighted by diaspora size | no | no | no | no | no | yes |
Quarters covered | Q1, Q2 | Q1, Q2 | Q1, Q2 | Q1, Q2 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 |
Weak instrument F-stat | 12 | 12 | 66 | 67 | 16 | 28 |
# Observations | 62 | 62 | 772 | 772 | 1544 | 1544 |
Elasticity of remittances with respect to mobility drops_ Municipality-level regressions_
Migrants exposure to decrease in workplace mobility | 7.93 |
8.24 |
2.76 |
2.76 |
−0.47 [1.47] | |
Decrease in out-of-home events | 0.09 [0.06] | 0.12 |
0.20 |
0.19 |
||
Level of aggregation | municipal | municipal | municipal | municipal | municipal | municipal |
Quarters covered | Q1, Q2 | Q1, Q2 | Q1, Q2 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 |
Interaction between weighted distance to diaspora and time | No | No | No | No | No | Yes |
0.18 | 0.09 | 0.20 | 0.23 | 0.24 | 0.27 | |
No. of observations | 772 | 772 | 772 | 1544 | 1544 | 1544 |
Effect of remittances on the amount of electronic payments_ LIML estimation
Amount of remittances (log) | 1.16 |
1.17 |
0.73 |
0.72 |
0.50 |
0.50 |
Decrease in workplace mobility | 0.48 [0.51] | |||||
Decrease in out-of-home events | 0.40 |
0.16 |
||||
Level of aggregation | state | state | municipal | municipal | municipal | municipal |
Quarters covered | Q1, Q2 | Q1, Q2 | Q1, Q2 | Q1, Q2 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 |
Weak instrument F-stat LIML CI | 12 [0.75, 1.56] | 14 [0.76, 1.58] | 66 [0.39, 1.06] | 67 [0.41, 1.04] | 16 [0.17, 0.83] | 16 [0.18, 0.83] |
No. of observations | 62 | 62 | 772 | 772 | 1544 | 1544 |
Elasticity of remittances with respect to employment_ Municipal-level regressions
US unemployment exposure (log) | −0.98 |
−0.98 |
−0.58 |
−0.58 |
−0.58 |
−0.52 |
MX employment (log) | 0.08 [0.16] | −0.02 [0.12] | −0.02 [0.12] | −0.10 [0.99] | ||
Level of aggregation | municipal | municipal | municipal | municipal | municipal | municipal |
Quarters covered | Q1, Q2 | Q1, Q2 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 | Q1, Q2, Q3, Q4 |
Interaction between weighted distance to diaspora and time | No | No | No | No | Yes | No |
Weighted by diaspora size | No | No | No | No | No | Yes |
0.21 | 0.22 | 0.24 | 0.24 | 0.27 | 0.22 | |
No. of observations | 770 | 770 | 1540 | 1540 | 1540 | 1540 |