Migrant Remittances During a Global Shock: Evidence From the COVID-19 Pandemic in Mexico

Christian Ambrosius; Raymundo M. Campos-Vázquez; Gerardo Esquivel

doi:10.2478/izajodm-2023-0002

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Migrant Remittances During a Global Shock: Evidence From the COVID-19 Pandemic in Mexico

IZA Journal of Development and Migration

Volume 14 (2023): Issue 1 (January 2023)

By: Christian Ambrosius, Raymundo M. Campos-Vázquez and Gerardo Esquivel

Open Access

|Nov 2023

Figures & Tables

Trends in key variables during the pandemic year 2020.
*Notes*: Authors’ calculations. See Online Appendix 1 for a description of variables.

Remittances and employment situations in the US and Mexico (2020-Q2).
*Notes*: Authors’ calculations. Data on employment levels in Mexico (left) is based on data on formal employees from the Mexican Institute for Social Security (IMSS). Exposure to unemployment in the US is calculated from a weighted portfolio of migrants from each of the 31 Mexican states (not including Mexico City) across their destination in the US (right).

Table 1

Elasticity of remittances with respect to employment. State-level regressions

	Level of remittances (log)
	I	II	III	IV	V	VI
US unemployment exposure (log)	−1.02^*** [0.20]	−1.00^*** [0.21]	−0.50^** [0.20]	−0.55^*** [0.21]	−0.55^*** [0.20]	−0.60^* [0.32]
MX employment (log)		0.19 [0.30]		−1.13^*** [0.26]	−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
R²	0.43	0.44	0.51	0.55	0.56	0.58
No. of observations	62	62	124	124	120	120

[i] Notes: Authors’ calculations. Heteroscedasticity robust standard errors clustered at the state level in parenthesis. State−level regressions are run on 31 Mexican states (excluding Mexico City). Columns V and VI also exclude the state of Quintana Roo, a strong outlier in terms of employment and remittances. Stars denote significance at the 10% (^*), 5% (^**) and 1% (^***) level. All results with municipality and quarter fixed effects.

Table 2

Elasticity of remittances with respect to employment. Municipal-level regressions

	Level of remittances (log)
	I	II	III	IV	V	VI
US unemployment exposure (log)	−0.98^*** [0.17]	−0.98^*** [0.17]	−0.58^*** [0.14]	−0.58^*** [0.14]	−0.58^** [0.25]	−0.52^** [0.17]
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
R²	0.21	0.22	0.24	0.24	0.27	0.22
No. of observations	770	770	1540	1540	1540	1540

[i] Notes: Authors’ calculations. Heteroscedasticity robust standard errors clustered at the municipal level in parenthesis. Municipal regressions are run on 385 municipalities with at least 50 thousand inhabitants. Stars denote significance at the 10% (^*), 5% (^**) and 1% (^***) level. All results with municipality and quarter fixed effects.

Table 3

Effect of remittances on the amount of electronic payments. Two-stage least squares

	Amount of electronic payments (log)
	I	II	III	IV	V	VI
Amount of remittances (log)	1.2^*** [0.3]	1.3^*** [0.39]	0.73^*** [0.24]	0.70^*** [0.23]	0.5^** [0.2]	0.55^** [0.27]
Drop in workplace mobility (Google)		0.0038 [0.0078]
Drop in out-of-home events (GranData)				0.40^*** [0.12]		0.32^*** [0.067]
Financial development		−0.017 [0.12]		0.28 [0.42]		−0.29^* [0.16]
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

[i] Second-step results instrumenting for remittances using migrants’ exposure to unemployment at the level of US states as an exogenous instrument. Heteroscedasticity robust standard errors clustered at the group level in parenthesis. Stars denote significance at the 10% (^*), 5% (^**) and 1% (^***) level. All results with municipality (state) and year fixed effects. Limited information maximum likelihood estimates are provided in Online Appendix 6.

Online Appendix 1:

Data description

Variable	Data Description	Level	Q1	Q2	Q3	Q4
Remittances	Inflow of total amount of remittances, in millions of USD.^a)	state	284.24 [248.65]	298.88 [258.78]	321.47 [258.48]	320.73 [272.49]
Remittances		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.^{b) c)}	state	0.23 [0.10]	0.22 [0.10]	0.22 [0.10]	0.22 [0.10]
MX employment levels		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 i during quarter q using the weighting formula $\sum_{k = 1}^{K} {Unempl}_{i, q}^{⋆} D_{k, i}$ , where D denotes the share of diaspora from i in destination states k, and Unempl is the unemployment rate in destination state k. Data on migration corridors between Mexican municipalities of origin and US states of residence obtained from consular documents that register Mexican municipality of birth and US state of residence of all applicants.^{d) e)}	state	0.04 [0.00]	0.13 [0.01]	0.09 [0.01]	0.07 [0.00]
US unemployment exposure		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.^f)	state	8845.12 [7268.58]	6737.49 [5437.24]	9170.64 [7452.55]	9656.16 [7660.82]
Electronic payments		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.^g)	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 i to the drop in workplace mobility in their US states of residence k, using the same weighting formula as for exposure to unemployment.^{g) d)}	state	−0.13 [0.00]	−0.36 [0.01]	−0.32 [0.00]	−0.27 [0.01]
Migrants’ exposure to decrease in workplace mobility		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.^h)	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 “depósitos a la vista”) relative to the adult population.ⁱ⁾	state	7.5 [10.6]	6.9 [9.4]	7.0 [9.5]	7.1 [9.5]
Financial development		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.^{c) d)}	state	2016.13 [526.60]
Distance		municipal	2183.45 [589.86]

Sources:

a) Banxico (2021),

b) IMSS

c) INEGI (2021),

d) IME (2020),

e) USBLS (2021a),

f) Banxico (confidential data),

g) Google LLC (2021),

h) Grandata (2021).

i) CNBV (2022).

Mean values and standard deviations in squared brackets for 31 states excluding the capital city of Mexico or 385 municipalities with a population of at least 50 thousand persons.

Decrease in mobility relative to baseline (left axis) and decrease in electronic transactions relative to previous year (right axis) during 2020 (daily values, smoothed)
See Online Appendix 1 for a description of variables.

Online Appendix 3:

Elasticity of remittances with respect to mobility drops. State-level regressions.

	Level of remittances (log)
	I	II	III	IV	V	VI	VII
Migrants exposure to decrease in workplace mobility	8.33^*** [2.19]		8.11^*** [2.10]	3.30^** [1.58]		3.28^* [1.63]	3.24 [2.35]
Decrease in workplace mobility		0.52^* [026]	0.48^* [0.27]		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
R²	0.35	0.26	0.40	0.50	0.49	0.50	0.52
No. of observations	62	62	62	124	124	124	124

[i] Heteroscedasticity robust standard errors clustered at the group level in parenthesis. State-level regressions are run on 31 Mexican states (excluding Mexico City). Stars denote significance at the 10% (^*), 5% (^**) and 1% (^***) level. All results with state and year fixed effects.

Online Appendix 4:

Elasticity of remittances with respect to mobility drops. Municipality-level regressions.

	Level of remittances (log)
	I	II	III	IV	V	VI
Migrants exposure to decrease in workplace mobility	7.93^*** [1.16]		8.24^*** [1.16]	2.76^*** [0.87]	2.76^*** [0.87]	−0.47 [1.47]
Decrease in out-of-home events		0.09 [0.06]	0.12^* [0.06]		0.20^*** [0.07]	0.19^** [0.07]
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
R²	0.18	0.09	0.20	0.23	0.24	0.27
No. of observations	772	772	772	1544	1544	1544

[i] Heteroscedasticity robust standard errors clustered at the group level in parenthesis. Regressions are run on 385 municipalities with a population of at least 50 thousand. Stars denote significance at the 10% (^*), 5% (^**) and 1% (^***) level. All results with municipality and year fixed effects.

Online Appendix 5:

Remittances and electronic payments. Non-instrumented OLS

	Amount of electronic payments (log)
Level of remittances (log)	0.80^*** [0.17]	0.69^*** [0.14]	0.34^*** [0.06]	0.28^*** [0.06]	0.03^** [0.01]	0.01 [0.02]
Decrease in workplace mobility		0.72 [0.55]
Decrease in out-of-home events				0.44^*** [0.07]		0.29^*** [0.04]
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
R²	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

[i] Heteroscedasticity robust standard errors clustered at the group level in parenthesis. Stars denote significance at the 10% (^*), 5% (^**) and 1% (^***) level. All results with municipality and year fixed effects.

Online Appendix 6:

Effect of remittances on the amount of electronic payments. LIML estimation

	Amount of electronic payments (log)
Amount of remittances (log)	1.16^*** [0.21]	1.17^*** [0.21]	0.73^*** [0.17]	0.72^*** [0.16]	0.50^*** [0.17]	0.50^*** [0.167]
Decrease in workplace mobility		0.48 [0.51]
Decrease in out-of-home events				0.40^*** [0.08]		0.16^** [0.06]
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

[i] Second-step results instrumenting for remittances using migrants exposure to unemployment at the level of US states as an exogenous instrument. Heteroscedasticity robust standard errors clustered at the group level in parenthesis. Stars denote significance at the 10% (^*), 5% (^**) and 1% (^***) level. All results with municipality (state) and year fixed effects. Weak instruments confidence intervals clustered at the group level in brackets estimated as in Mikusheva and Poi (2006).

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Articles in this issue

DOI: https://doi.org/10.2478/izajodm-2023-0002 | Journal eISSN: 2520-1786

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Language: English

Submitted on: Nov 25, 2022

Published on: Nov 2, 2023

Published by: Sciendo

In partnership with: Paradigm Publishing Services

Keywords:

JEL:

F22,

F24,

J23,

O54

Related subjects:

Business and economics,

Mathematics and statistics for economists,

Econometrics

© 2023 Christian Ambrosius, Raymundo M. Campos-Vázquez, Gerardo Esquivel, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 14 (2023): Issue 1 (January 2023)

Migrant Remittances During a Global Shock: Evidence From the COVID-19 Pandemic in Mexico

Figures & Tables

Figure 1

Figure 2

Table 1

Table 2

Table 3

Online Appendix 1:

Online Appendix 2:

Online Appendix 3:

Online Appendix 4:

Online Appendix 5:

Online Appendix 6:

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