brandeis university heller graduate school sustainable
TRANSCRIPT
Brandeis University
Heller Graduate School Sustainable International Development
Effect of the remittances received at municipal level on the population living in
poverty in Mexico for the years 2000 and 2005
Master Paper Presented by:
J. Eloy Palacios-Sanchez
A paper submitted in partial fulfillment of the requirements for the
Master of Arts Degree in
Sustainable International Development
Academic Advisor _________________________________Date ___________________
Director, Program in _______________________________Date ___________________
Sustainable International Development
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Table of Contents
Abstract…………………………………………………………………………………………………………………………………………………2
Executive Summary…………………………………………………………………………………………………………………………..….3
Acknowledgements………………………………………………………………………………………………..…………………………….6
Abbreviations………………………………………………………………………………………………………………………………….......6
I. Introduction……………………………………………………………………………………………………………………………………….7
II. Background and Problem Statement…………………………………………………………………………………………..…10
III. Methods………………………………………………………………………………………………………………………………………..14
IV. Literature Review………………………………………………………………………………………………………………………..…19
V. Findings and Substantive Discussion………………………………………………………………………………………………29
VI. Conclusions and Implications……………………………………………………………………………………………………..…36
VII. Tables……………………………………………………………………………………………………………………………………………38
VIII. List of References…………………………………………………………………………………………………………………………42
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Abstract
How effectively do remittances sent by Mexican immigrants in U.S. contribute to reduce municipal
poverty in Mexico?
This master paper endeavors to answer this question estimating the effects of the amount of
remittances received at municipal level in Mexico on the percentage of the population living in
poverty.
The present study comprises the totality of municipalities in Mexico for the years 2000 and 2005.
Although the phenomenon of migration from Mexico to the United States is strongly concentrated just
in some states and municipalities of Mexico the present study attempts to find disparities among the
municipalities receiving remittances and those without them; for this purpose an econometric model is
included in the study using the percentage of people living in poverty as the dependent variable and
the amount of remittances received at municipal level as the main independent variable.
In 2000 the states having their municipal poverty levels reduced are: Guerrero, Oaxaca, Chiapas,
Veracruz and Tabasco for the three income-poverty categories and Querétaro, Estado de México,
Distrito Federal, Morelos, Hidalgo, Tlaxcala and Puebla in the case of assets-poverty.
In 2005 the reduction in poverty accounts for all the municipalities except for those in the states of
Campeche, Yucatán and Quintana Roo. Additionally the capabilities-poverty and assets poverty is
reduced in the municipalities of the states of Baja California, Baja California Sur, Sonora, Sinaloa and
Nayarit. The States of Guerrero, Oaxaca and Chiapas reduced their assets-poverty as well.
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Executive Summary
Income remittances by migrants contribute to incomes of households in migrant-source
municipalities; if remittances are substantial and well oriented to poor households then may reduce
poverty.
The present study comprises the totality of municipalities in Mexico for the years 2000 and 2005.
Although the phenomenon of migration from Mexico to the United States is strongly concentrated just
in some states and municipalities of Mexico the present study attempts to find disparities among the
municipalities receiving remittances and those without them; for this purpose, an econometric model
is included in the study using the percentage of people living in poverty as the dependent variable and
the amount of remittances received at municipal level as the main independent variable.
The literature concerning the effects of remittance on poverty provided split conclusions. On one hand
some studies supported the negative correlation between remittances and poverty differentiating its
effects by regions inside a country, whereas others found no correlation when there was no distinction
by region and the country was taken as a whole entity.
In this paper I provided the results of two econometrics models, one including region-remittance
interactions and the other without the interactions with the purpose to provide additional evidence
supporting or rejecting what prior studies have contributed.
The main findings of the study allow us to observe different correlations between remittances and
poverty across 8 regions obeying to different patterns of migration from Mexico to US. At national
level the total amount of remittances received grew from 6,572 million dollars in 2000 to 21,688
million dollars in 2005, a percentage increase equivalent to 230% in 5 years or 46% average increase
annually.
When including the “region” as a control variable in the econometric model the effect of remittances
on poverty is better disentangled and then is possible to observe to those municipalities getting the
best from remittances.
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In 2000 the states having their municipal poverty levels reduced are: Guerrero, Oaxaca, Chiapas,
Veracruz and Tabasco for the three income-poverty categories and Querétaro, Estado de México,
Distrito Federal, Morelos, Hidalgo, Tlaxcala and Puebla in the case of assets-poverty.
In 2005 the reduction in poverty accounts for all the municipalities except for those in the states of
Campeche, Yucatán and Quintana Roo. Additionally the capabilities-poverty and assets poverty is
reduced in the municipalities of the states of Baja California, Baja California Sur, Sonora, Sinaloa and
Nayarit. The States of Guerrero, Oaxaca and Chiapas reduced their assets-poverty as well.
The net-largest recipients of remittances are not the only states reducing their municipal
poverty rates.
Not all the municipalities receiving high-per capita remittances reduced their poverty rates, in
some cases municipalities with high level of remittances per capita reduced poverty in 2000 but
not in 2005 and others performed the other way around.
In 2005 almost all the municipalities reduced alimentary-poverty and this reduction is
coincident with the large net-increase of remittances from 2000 to 2005.
As a general conclusion the amount of remittances received by municipalities reduces the percentage
of people living in poverty but selectively by regions, not everywhere and not uniformly.
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Acknowledgements
This Masters paper is dedicated to Nancy for being such supportive, patient and loving wife throughout
this amazing two-year master’s program.
I express my sincere thanks to Professor Barry Friedman for his willingness, support and guidance
throughout this project.
I am eternally grateful for the Heller School for Social Policy and Management’s Professors and Staff for
giving me this great opportunity in life to pursue a master’s program, it is been such a wonderful
experience.
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Abbreviations
1. BANXICO: Central Bank of Mexico (Banco Nacional de México)
2. CONAPO: National Population Council (Consejo Nacional de Población)
3. CONEVAL: National Council for the Evaluation of Social Development Policy (Consejo Nacional
de Evaluación de la Política de Desarrollo Social)
4. ENIGH: Household Income and Expenditure National Survey (Encuesta Nacional de Ingresos y
Gastos de los Hogares)
5. INEGI: National Institute of Statistics and Geography (Instituto Nacional de Estadística Geografía
e Informática)
6. SEDESOL: Ministry for Social Development (Secretaría de Desarrollo Social)
7. UNDP: United Nations Development Program
8. U.S.: United States of America
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I. Introduction
1.1 The Development Question
How effectively do remittances sent by Mexican immigrants in U.S. contribute to reduce municipal
poverty in Mexico?
This master paper endeavors to answer this question estimating the effects of the amount of
remittances received at municipal level in Mexico on the percentage of the population living in
poverty.
According to Esquivel et. al. (2005. pp. 8) the percentage of the population living in extreme poverty in
Mexico is 20.3%, to say they cannot afford a minimum basket of food, 26% of the population lives in
poverty, to say they cannot afford food, health and education and 51.7% of the population cannot
afford food, health, education, dressing, home and public transportation.
Income remittances by migrants contribute to incomes of households in migrant-source municipalities.
If remittances are substantial and well oriented to poor households then may reduce poverty (Taylor et
al. 2005. pp.3). Furthermore an increase in the amount of remittances received would have a larger
effect in a region where a large share of households have migrants in U.S. than in a region in which
households with international migrants are rare (Taylor et al. 2005. pp.4).
1.2 The Case Study
This study includes the totality of municipalities in Mexico for the years 2000 and 2005 (2452 and 2454
municipalities respectively). Although the phenomenon of migration from Mexico to the United States
is strongly concentrated just in some states and municipalities of Mexico the present study attempts to
find disparities among the municipalities receiving remittances and those without them. Historically
the States with highest levels of migration to USA are: Durango, Guanajuato, Michoacán, Nayarit,
Zacatecas, Aguascalientes, Colima, Jalisco y San Luis Potosí (CONAPO, 2002).
Relying on the information available and making some estimations for missing data, the study will
include information for the years 2000 and 2005 given that in the decade between 1990 and 2002 both
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urban and rural Mexico has experienced a massive outflow of labor to the United States where the
share of the working population rose from 7% to 14% (Taylor et al. 2005. pp.6).
1.3 Contribution of the study to development
Most of the literature reviewed concerning migration and remittances supports that family
remittances by migrants contribute to incomes of households in migrant-source areas. However what
is not clear is whether remittances indeed can reduce the percentage of people living in poverty at
municipal level.
Since the existent literature about the effects of remittances on poverty is insufficient to
unquestionably support a positive or negative statement the present master paper contributes to
sustain or refute the findings obtained by prior authors with the case study of the Mexican
municipalities. However the undeniable fact is the massive impact that remittances from US have in
the Mexican municipalities, which in any case remittances may not embody a change in the poverty
rates but represent a great dependency of the Mexican municipalities on foreign remittances.
The main purpose of this paper is to arouse concern regarding in-progress Mexican and US social
policies and programs directed to provide support to poor municipalities of Mexico. If remittances can
effectively reduce poverty in the Mexican municipalities, then new social policies may be created in
order to funnel and harness enhanced government expenditure combined with remittances received
by municipalities, promoting consequently the sustained development of poor regions. Nonetheless
this master paper will be limited to obtain a generalized statement regarding the net effect of
remittances on poverty and will not embrace the social implication of its effects but rather may
reinforce the platform for further studies emphasizing its social policy implications.
1.4 Context of the Study
The information used to address the development question is obtained from official government
institutions as secondary sources of information.
The dataset analyzed contain information at the municipal level for the years 2000 and 2005 including
2452 and 2454 municipalities respectively. Although most of the information is obtained from official
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government institutions some data set estimations were done based on the official sources of
information.
1.5 Professional Background
The author of the present paper has a bachelor degree in economics and his experience has been
acquired working during 8 years in the Ministry for Social and Economic Development of the state of
Puebla, Mexico. His development work consisted in the implementation of projects in the poorest
municipalities of Puebla intended to improve their socio-economic conditions, dealing especially with
those municipalities ranked among the highest-migration areas from Mexico to US.
The second-year in Heller, besides to be an amazing experience in life, mainly focused the courses
work on the Analysis of the Causes and Consequences of the International Migration and the
acquisition of statistical tools to measure the effect of remittances on poverty with courses as
Household Economics and Measurement of Inequality.
Additionally, another courses complemented the holistic vision of development with courses as
Integrated Conservation and Development, Food and Security Nutrition, Sustainable Use of Renewable
Energy Sources, to mention just the most relevant.
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II. Background and Problem Statement
2.1 Background
The importance of migration is evident in the continued and increasing movement of people from
south to north and east to west (Castles and Miller, 2003; Massey et al., 1998). Whether we study
Mexicans migrating to the United States or Pakistanis moving to England, there is little doubt that
migration brings opportunities and challenges (Cohen, 2005. pp. 89).
To understand remittances, it is important to differentiate between voluntary and forced migration
given that voluntary migration is motivated by economics and is typically tied to local and international
issues in economic growth; forced migration is tied to neither growth nor development (Cohen, 2005.
pp. 89). At times, these moves become so regular as to create a “transnational community” that
transcending geographic limits and comes to exist among various locations (Cohen, 2005. pp. 90).
Research on international migration tends to support the hypothesis that migration can lead to long-
term remittance practices, rather than the traditional expectation that remittances will decline or as
migration flows mature (Stark 1978). This process, whereby remittances continue over the long-term,
is evident among Mexicans moving between migrant-sending regions in the central states of the
country to the United States (dela Garza and Szekely, 1997; Massey et al., 1994).
Most studies of voluntary migration, whether national, international, or transnational, argue that the
high wages motivates most decisions to move. For example Gonzalez and Escobar (2001), working in
Jalisco, Mexico, they note that 93% of all remittances went to household expenses. In Cohen and
Rodriguez (2004) they found that in rural communities of Oaxaca, Mexico 92% of remittances went to
daily and household expenses, with only about 8% of remittances going to business start-ups or
investments.
Proponents of dependency theory argue that the seductive pull of wages and the rise of receiving-
household incomes that remittances bring addicts rural Mexicans to migration and leads to what
Reichert coined the “migrant syndrome” (1981). This syndrome ensnares rural migrants in a vicious
cycle of repeat migrations, because they face few opportunities for work in home communities.
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The history of migration between Mexico and United States is strongly enrooted in a private-public
collaboration between U.S. farmers and the U.S. and Mexican governments: the Bracero Program of
imported Mexican agricultural workers, which lasted from 1942 to 1964 (Rodriguez, 2004. pp. 457).
The Bracero Program was originally organized as a wartime measure to replenish the agricultural
workforce that had lost workers to the armed forces and to wartime industries in the cities (Calavita,
1992; Craig, 1971). In response to requests from large farmers in California, Texas, and Arizona and a
few railroad companies, the U.S. government obtained a labor import agreement with the Mexican
government in 1942 (Rodriguez, 2004. pp. 457).
In 1942, the program started when 4,203 braceros arrived to work in U.S. and by the end of the
program in 1964, 4.9 million braceros had gone through the program (Barrera, 1979).
For the agricultural employers, a much-desired economic advantage was to have a large supply of
workers to keep wages down. Bracero labor allowed agricultural employers to reduce operating costs
by about 50% (Rodriguez, 2004. pp. 458). This advantage increased for employers when U.S.
government agents arrested thousands of undocumented workers for illegal entry into the United
States and then converted them into bracero workers for U.S. farmers.
The Bracero Program had become a preferred labor supply of agricultural employers and some railroad
corporations. One large agricultural employer described the attitude toward bracero labor as follows:
“We used to own our slaves, now we rent them from the U.S. government” (Moquin & Van Doren,
1971, p. 344).
When World War II ended in 1945, a total of 168,000 braceros had been imported from Mexico to U.S.
for temporary work, but 4.7 million more would be imported by the end of the program in 1964. The
braceros program peak in the period from 1956 to 1960, when more than 400,000 workers were
imported annually (Barrera, 1979).
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2.2 Problem Statement
In the past decade rural Mexico has experienced a massive outflow of rural labor to Mexican urban
centers and to the United States. Between 1990 and 2002, the share of Mexico’s rural population
working in the United States rose from 7% to 14%, and the share at internal-migrant destinations rose
from 11% to 15%; however, the share varies widely across regions (Mora and Taylor, 2005).
Mexico is the second-largest recipient of remittances in the world. Its Diaspora is unusual in that,
compared to other countries it is so heavily concentrated in the United States (Newland, 2004. pp. 12).
The interactions between migration and poverty are among the least researched and understood
topics in economics (Taylor et al; 2005. pp. 3).
The possible impacts of migration on poverty are presented under to “optimistic” and “pessimistic”
scenarios. The optimistic scenario is that migration reduces poverty in source areas by shifting
population from the low-income rural sector to the relatively high-income urban (or foreign) economy
and then reducing poverty through the availability of remittances (Taylor et al; 2005. pp. 3).
The pessimistic view is that poor households face liquidity, and risk that limit their access to migrant
labor markets which is the case of international migration entailing high transportation costs and other
fees like bribes, payment to smugglers etc. (Taylor et al; 2005. pp. 4).
However, beneficiaries of migration may not include the rural poor when is costly and risky and initially
may come from middle or upper segments of the source-area income distribution and not from the
poorest locations (Taylor et al; 2005. pp. 4).
Initially, when few households have access to migrant labor markets abroad, international-migrant
remittances are likely to flow primarily to middle and upper-income families. If this is the case, then
changes in remittances will have little effect on poverty.
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However with an equal opportunity to reach international labor markets, international migration
eventually becomes diffused downward through the income distribution and poverty may become
increasingly sensitive to changes in remittances benefiting to everyone (Taylor et al; 2005. pp. 4).
2.3 Hypothesis
The implication of international migration of Mexicans and specially to the U.S. raise the interest of the
present paper in the migration effects on poverty through the increasing and sustained patterns of
remittances received in Mexican home communities from immigrants in US and then the main interest
of this paper is to analyze the effect of the amount of remittances received at municipal level on the
percentage of the population living in poverty for the years 2000 and 2005. Then we can state the
hypothesis:
Hypothesis: On average and holding everything else constant, the amount of remittances received by
municipalities reduces the percentage of people living in poverty at its three different categories: food,
capabilities and assets-poverty.
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III. Methodology
3.1 Data
The dataset analyzed in the present paper contain information at the municipal level for the years
2000 and 2005 including 2452 and 2454 municipalities respectively. Most of the information included
is obtained from official government institutions; nonetheless some data estimations were done given
the need to include additional information, but even so the estimated variables were based on the
official information available.
3.2 Variables in the Model
3.2.1 The Econometric model
One econometric model is proposed for each year using the same variables; the regressions are run
separate and then there is no need to correct for inflation in every period.
Y^Poverty2000= α - β1 lnMun_Remittim2000 - β2 lnMun_Expim2000 + β3 lnMun_popim2000 - β4 lnMun_Icomeim2000 +
β5Margim2000 + β6Mun_unem2000 - β7REG1 - β8REG2 -β9REG3 - β10REG4- β11REG5 - β12REG5 - β13REG5 -
β14(REG1*lnMun_Remitt2000) -β15 (REG2*lnMun_Remitt2000) -β16 (REG3*lnMun_Remitt2000) - β17
(REG4*lnMun_Remitt2000)- β18 (REG5*lnMun_Remitt2000) - β19 (REG6*lnMun_Remitt2000) - β20
(REG7*lnMun_Remitt2000) - µ
Y^Poverty2005= α - β1 lnMun_Remittim2005 - β2 lnMun_Expim2005+ β3 lnMun_popim2005 - β4 lnMun_Icomeim2005+
β5Margim2005 + β6Mun_unem2005 - β7REG1 - β8REG2 -β9REG3 - β10REG4- β11REG5 - β12REG5 - β13REG5 -
β14(REG1*lnMun_Remitt2005) -β15 (REG2*lnMun_Remitt2005) -β16 (REG3*lnMun_Remitt2005) - β17
(REG4*lnMun_Remitt2005)- β18 (REG5*lnMun_Remitt2005) - β19 (REG6*lnMun_Remitt2005) - β20
(REG7*lnMun_Remitt2005) - µ
3.2.2 Dependent Variable: Poverty in three different categories
Poverty Categories are defined as an Index (CONEVAL, 2000 and 2005):
Food-Based Poverty: Percentage of the total population whose income is insufficient to cover
the basic needs of food
Capabilities-Based Poverty: Percentage of the total population whose income is insufficient to
cover the basic needs of education and health
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Assets-Based Poverty: Percentage of the total population whose income is insufficient to cover
the basic needs of housing, transportation, clothes, shoes and other.
3.2.3 Independent Variable
lnMun_Remittim: Total amount of remittances received at the municipal level for the years 2000 and
2005.
The total amount of remittances received in Mexico is available from official sources at national and at
state level; nonetheless the amount received by every municipality is not available from any official
sources in Mexico and then the first step for the inclusion of this variable of the study is the estimation
of the amount of remittances received at the municipal level.
For the calculation of the amount of remittances received at the municipal level I followed the
methodology proposed by Barcelata (2010) for the estimation of municipal level of remittances;
however Barcelata’s estimated the municipal amount of remittances of the state of Veracruz (210
municipalities) and just for the year 2007; on the other hand the present paper estimates the amount
of remittances received by every Mexican municipality in 2000 and 2005.
First, the official amount of remittances received by every state of the Mexican Republic (31 states and
1 federal district) is obtained from BANXICO (2000 and 2005) for the years of the study.
Second, the total number of rural and urban households in every municipality is obtained from the
INEGI (2000 and 2005).
Third, through the CONAPO (2000 and 2005) and the ENIGH (2000 and 2005) is obtained the average
percentage of rural and urban households who received remittances and then we obtain the number
of households receiving remittances in every municipality.
Fifth, we have the total number of households receiving remittances by every municipality and state,
and also we have the total amount of remittances received by state, then is possible to estimate the
amount of remittances received by municipality as a percentage of its total number of households.
Sixth, by adding up the amount of remittances received in urban and rural households we obtain the
total amount of remittances received in every municipality.
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Finally, the core independent variable is converted to Mexican pesos (exchange rate, 2000: 9.4556
pesos/dollar, 2005: 10.8959 pesos/dollar: BANXICO) and expressed in log natural in order to read any
increase or decrease of the amount of remittances as a percentage.
The expected sign of this variable is negative since a 1% increase in the amount of remittances received
at the municipal level is likely to reduce the percentage of people living in poverty in its three different
categories.
3.2.4 Control Variables
1.- lnMun_Expim: Total Government Expenditure at the municipal level for the years 2000 and 2005.
The municipal total expenditure is obtained from the INEGI. This variable includes the total amount of
money invested by the government in every municipality in social programs, infrastructure, roads,
provision of basic services, etc.
This variable is expressed in natural log in order to read any increase or decrease of the government
expenditure as a percentage.
The expected sign of this variable is negative since a 1% increase in the amount of municipal
expenditure received is likely to reduce the percentage of people living in poverty in its three different
categories.
2.- lnMun_popim: Total population in the municipality.
This variable is obtained for every municipality from the INEGI and is expressed in log natural in order
to read any increase or decrease of the municipal population as a percentage.
The expected sign for this variable is positive since a 1% increase in the municipal population may
increase the percentage of people living in poverty.
3.- lnMun_Icomeim: Total Municipal Income.
This variable is obtained for every municipality from the PNUD (2000 and 2005) and converted to
Mexican pesos (BANXICO 2000 and 2005) and expressed in log natural in order to read any increase or
decrease in the municipal income as a percentage.
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The expected sign for this variable is negative since a 1% increase in the municipal income is associated
with a decrease in the percentage of poor people.
4.- Margim: Marginality Index at municipal level (CONAPO, 2000 and 2005).
Index compounded by 4 core social-exclusion indicators:
a) percentage of Illiterate population and percentage of the population without primary schooling,
b) percentage of the population without provision of basic services in the household (potable water,
sewer, electricity), percentage of the population with ground floor in household and household
overcrowding,
c) percentage of the population earning less than twice minimum wage and
d) percentage of the population living in communities with less than 5000 inhabitants.
Since the provision of basic services and education in rural communities (less than 5000 inhabitants) is
the responsibility of the Mexican government at its three levels (federal, state and municipal) this
variable is included in the model as a determinant of the percentage of the population living in
poverty, assuming that income poverty (food-based, capabilities-based and assets-based) per se can
not influence directly the provision of services by government and then attenuating the problem of
edogeneity between these variables without getting rid of it though.
The expected sign of this variable is positive since an increase in the Marginality Index is assumed to
increase the income poverty rate at municipality level.
5.- Mun_unem: Municipal Unemployment Rate
This variable provides the percentage of the population unemployed for the years of the study (INEGI,
2000 and 2005). Since the information for the rate of municipal unemployment was unavailable the
unemployment rate by state is included instead as a proxy variable in every municipality.
The expected sign for this variable is positive since a larger unemployment rate is associated with an
increase in the percentage of population living in poverty at municipal level.
3.2.5 Dummy Variables
The last part of the econometric model includes 7 dummy variables equivalent to 8 geographical
regions of Mexico including 32 states. The regionalization has been done arbitrarily but the states in
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each region are clustered according with their geographical location, vicinity and socio-economic
status: North, north-east, north-west, center-west, center-east, east, south and Yucatán Peninsula.
To generate the dummy variables is necessary to exclude one region. The omitted region (the richest)
will be the North-East Region comprised of the states of Nuevo León y Tamaulipas. Hence the dummy
variables are:
1.- REG1: Taking the value of 1 if it’s REG1 and 0 if other region. (Baja California, Baja California Sur,
Sonora, Sinaloa and Nayarit).
2.- REG2: Taking the value of 1 if it’s REG2 and 0 if other region. (Chihuahua, Coahuila, Durango,
Zacatecas and San Luis Potosí).
3.- REG3: Taking the value of 1 if it’s REG3 and 0 if other region. (Jalisco, Aguascalientes, Colima,
Michoacán, Guanajuato).
4.- REG4: Taking the value of 1 if it’s REG4 and 0 if other region. (Querétaro, Estado de México, Distrito
Federal, Morelos, Hidalgo, Tlaxcala and Puebla).
5.- REG5: Taking the value of 1 if it’s REG5 and 0 if other region. (Guerrero, Oaxaca and Chiapas).
6.- REG6: Taking the value of 1 if it’s REG6 and 0 if other region. (Veracruz and Tabasco).
7.- REG7: Taking the value of 1 if it’s REG7 and 0 if other region. (Campeche, Yucatán and Quintana
Roo).
3.2.6 Interactive Dummy Variables
Remi*REGi (i= 1, 2…7). In order to obtain a better defined explanatory variable, every Dummy variable
“Region” is multiplied by the “amount of remittances received” by every municipality obtaining a
combined variable that allows effect of remittances to vary by region.
The expected sign in every combined dummy variable is a priori expected to be negative since poverty
in every region is assumed to be reduced as the amount of remittances increases.
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IV. Literature Review
5.1 Remittances: Definition
The definition of remittances has been stretched by social science analysts to include elements that are
not strictly economic (Vertovec, 2000). Peggy Levitt (1998) used the term social remittances to
describe various types of social practices, ideas and values, mainly to migrant-sending areas, which
accompany the migration process. Nichols (2002) emphasized the importance of knowledge, skills and
technology brought back by returning migrants, being called technical or technological remittances.
Others have focused on changes in political identities, demands and practices associated with
migration (Fitzgerald, 2000; Goldring, 1992b, 1998a, 2002; Moctezuma, 2000; Rivera-Salgado, 2000;
Smith, 1998, 1999) which one could refer to as political remittances. Identifying various kinds of non-
economic remittances would be consistent with approaches that analyze migration as a complex and
multi-dimensional process (Massey et al., 1993).
On his work, Jorge Durand (1988) identify three types of remittances: (1) traditional individual or family
cash remittances which might be transferred through a courier, via money orders, or some other
method; (2) savings invested in houses or businesses; and (3) durable goods or products that migrants
brought back upon their return (trucks, televisions, and so forth).
Goldring (2004) argues that family remittances can be understood as having a social meaning that
involves expressions or claims of membership in a family or social network, nonetheless the fact that
family remittances are embedded in social relations of kinship means that as long as people have
relatives overseas they will remit money but migrants tend to remit less over time, and much less once
their immediate family members have joined them, or relatives living abroad have migrated or died.
Durand (1994) identified three types of remittances based on their use or function. The first was
remittances as wages or salary sent by circular migrants sent to support close relatives. These migrants
tended to be from areas characterized by limited investment opportunities because of monopoly or
else low-yield agriculture. The second type was remittances as investment: these remittances could be
20
sent during a trip, or brought back upon return. Third were remittances as capital: this was money
saved specifically to invest in a productive venture.
Goldring (2004) identify three peculiarities between households receiving remittances. First, both
households receiving remittances and those that do not, use almost the same proportion of their
income (about 80 per cent) to cover recurrent expenses, leaving less than 20 per cent for other uses.;
second, remittance receiving households are not homogeneous, and include groups with an absent
family member who sends money and those where a relative who is no longer a central member of the
household sends the money. Corona (2001) concludes that in these two types of households there will
be little opportunity to use remittances for productive investments. Third, there are remittance-
receiving households without migrants and households with migrants that do not receive remittances
(Lozano, 2001). The former receive relatively small amounts of remittance money, while the latter
receive none.
Goldring’s study (2004) concludes that in Mexico, remittances are largely used as income, most income
is used to cover recurrent expenses and education, and only a small share goes to savings and
investments. There is now a consensus that the highest share of remittances is spent supporting
households’ recurrent costs, including education and health (Delgado and Rodríguez, 2001; Suro, 2003;
Waller, 2000).
Durand (1994) identified and defined the key differences between family, collective and
entrepreneurial remittances. Family remittances tend to be used to cover basic needs as they act as a
source of income; entrepreneurial remittances represent savings with the potential to become
investment and finally collective remittances are associated with organizations with considerable social
and political leverage in recent years.
The positive reading would argue that remittances do contribute to development through multiplier
effects, and investment in human capital and health, while the negative position would stress the
regional and macro-economic constraints that limit the possibility of using remittances as anything else
besides income (Goldring, 2004).
21
5.2 Remittances and Poverty
Remittances to developing countries have been growing relatively fast in recent years. In many
countries they are now the most important source of external financing. Furthermore, remittances
from abroad seem to be more stable than other types of external inflows and they even seem to be
countercyclical. Notwithstanding the growing importance of remittances for the developing world,
their effects on the recipient economies are relatively unknown. Indeed, there are relatively few
studies that investigate the effects of remittances on these economies (Esquivel et al; 2006. pp. 1).
One of the areas that have received less attention in the research agenda is the relationship that may
exist between remittances and poverty (Esquivel et al; 2006. pp. 1). For some authors, the existence of
a positive relation between these two variables is somehow obvious and may not deserve further
discussion meanwhile other authors assert the relationship between remittances and poverty is
affected by certain characteristics of the migration process. Some authors express the fact that since
migration is costly should not belong to the poorest people in the sending economies. For that reason,
remittances might not have an immediate and direct effect on poverty (Esquivel et al; 2006. pp. 1).
This position is well represented by Kapur (2004): “The fact that migrants are not drawn from the
poorest households in their country of origin means that while remittances are poor-friendly, their
direct effects on the poorest groups may be limited. Instead, the effects on structural poverty are likely
to occur through substantial indirect effects … ” Similarly, Adams and Page (2003) conclude that
“because of the considerable travel costs associated with international migration, international
migrants come from those income groups which are just above the poverty line in middle-income
developing countries”.
Other authors have also suggested that the poorest people may lack the appropriate skills to benefit
from international migration, and therefore they tend to have lower emigration rates. This argument
also implies that remittances may not have a direct impact on poverty (Esquivel et al; 2006).
In the most extensive literature on this topic, Adams and Page (2003) analyze the relationship between
poverty and remittances in a sample of seventy-four developing countries. They find that international
22
remittances have a strongly statistical negative impact on poverty. Specifically, they find that a 10
percent increase in the share of remittances in a country’s GDP, leads to a reduction of 1.6 percent in
the share of people living in poverty. On the other hand, Adams (1991), Adams (2004) and López-
Cordova (2005) analyze the relation between remittances and poverty indicators at a country level, in
Egypt, Guatemala, and Mexico, respectively. Adams (1991) finds that in Egypt the number of rural
households in poverty drops in 9.8 percent when household’s income includes international
remittances. In Guatemala, poverty gap measure declines by 19.8 percent when international
remittances are included as part of total household income. This occurs, according to the author,
because the income status of households at the lowest decile changes considerably when they receive
remittances.
López-Cordova (2005) finds that remittances have a statistically and economically significant impact in
reducing poverty in Mexico at the municipal level. He estimates that a one percentage point increase in
the fraction of remittance-receiving households in a municipality significantly reduces the fraction of
the population earning relatively low income.
International remittances have traditionally been an important source of foreign exchange resources
for the Mexican economy. In recent years, however, remittances have become a growing source of
external funds. The amount of remittances flowing into Mexico has increased monotonically since
1991 and they are now more than twice the inflows from tourism-related activities. In recent years,
remittances have even been as large as foreign direct investment inflows to Mexico. In terms of the
importance of remittances relative to the size of the economy, remittances in Mexico are now close to
3 percent of GDP and they have become particularly important since 2000.
Mexico is already the country that receives the second largest amount of remittances around the
world (India is the first) (Esquivel et al; 2006. pp. 5).
In terms of their regional distribution, remittances-receiving households in Mexico are not uniformly
distributed across the country. Remittance-receiving households are concentrated in a few Mexican
states and that they tend to be located in the center-north part of the country. Indeed, more than one
third of all remittances-receiving households in Mexico are concentrated in only four states
(Michoacán, Durango, Guanajuato and Zacatecas. Similarly, in seven Mexican states 10 percent or
23
more of their total households receive remittances from abroad (Michoacan, Durango, Guanajuato,
Zacatecas, San Luis Potosí, Jalisco and Aguascalientes). It is interesting to note that the poorest
Mexican states, such as Chiapas, Guerrero, Oaxaca, Puebla or Veracruz, do not belong to this list,
although the recent pattern of migration may change this distribution in the future (Esquivel et al;
2006. pp. 9-10).
Esquivel et al (2006) estimated in his paper through the construction of a propensity score the
probability of Mexican households of being in poverty situation in 2002 where the dependent variable
is 1 if the household receives international remittances and 0 otherwise.
The effect of receiving remittances on the probability of being in a poverty situation using three
alternative, officially-defined, measures of poverty (food-based, capabilities-based and assets-based).
The empirical results show that receiving remittances from abroad reduces the probability of being in
food-based and capabilities-based poverty in 8 and 6 percentage points, respectively. Given the
observed poverty rates at the household level using nationally representative data (15.8% and 21.1%,
respectively), this effect, depending on who actually migrates, could be equivalent to a reduction of
around 50 and 30% in the corresponding poverty rates for remittance receiving households vis á vis
non remittance receiving households. However, receiving remittances does not seem to affect a
household’s probability of being in assets-based poverty. In that sense, we may conclude that
remittances contribute to the reduction in the level and depth of poverty, but only up to a certain
point.
On the other hand a study carry out by Lopez-Córdova (2005) looks at a cross-section of Mexican
municipalities and analyzes whether development indicators improve as the fraction of remittance
receiving households in a municipality rises. He pays particular attention to schooling and health
status, with a secondary focus on poverty and a marginalization index that summarizes several welfare
measures.
The results suggest that an increase in the fraction of households receiving remittances reduces infant
mortality and illiteracy among children aged six to fourteen years, while at the same time alleviating
some dimensions of poverty and improving living conditions. Remittances seem to improve school
attendance among young children, although the opposite seems to be the case among teenagers.
24
To assess whether remittances reduce poverty, he uses use as dependent variables the fraction of the
population whose income is equivalent to the minimum wage or less, which he label extreme poverty,
and the fraction whose income is at most two minimum wages, which he label poverty. He shows that
remittances do not seem to dent the incidence of extreme poverty in a statistically significant way. This
might reflect the fact that migration is a costly endeavor, and households at very low income levels
might not be able to defray the costs. In other words, only households with income above some given
level are able to emigrate and remit.
Although most studies recognize that the impact of remittances is a question that must be analyzed in
each case, multi-government institutions and initiatives such as the Berne initiative, the World Bank
and the Inter-American Development Bank, the GCIM, the Puebla process and others, state clearly that
most remittances are directed at poor households (Escobar, 2009. pp. 77).
Since remittances are treated as net income, analyses conclude that remittances tend to increase the
income of the poor, and to consider this a developmental impact of migration. According to this
argument, remittances must be protected because they are private transactions, the poor depend on
them to survive, and they reduce poverty (Escobar, 2009. pp. 77).
The OECD (2008) published a position paper that summarizes a situation may exist today. In their view,
lowest-income countries export mostly high-skilled labour, while middle–income labour exporters tend
to export mostly low–skill workers. High-skill workers tend to migrate legally, which entitles them to
take their family along and significantly reduces remittances. Lower-skilled workers, on the contrary,
tend to migrate illegally, and this increases remittances. As a result, very low-income countries would
seem to be investing large portions of their GDP in the training of high-skill individuals, and then lose
these workers with very modest remittances in exchange (Escobar, 2009. PP. 78). On the contrary,
medium– income countries export persons in which the country has invested little in the way of private
or public funds, and they tend to remit larger relative amounts, which would produce a significant net
income for their families, thus reducing poverty and possibly furthering development (Escobar, 2009.
pp. 77).
Because of its proximity to the United States, which lessens the cost of migration, and the cumulative,
social-networking effect of a century of low-skill migration, Mexico would be among those most
25
favored by this situation. It is a medium–income country exporting low-skill workers who migrate
illegally and therefore tend to remit more often than other migrants. As a result, poverty should
diminish markedly in Mexico due to migration, and this is considered a developmental effect (Escobar,
2009. pp. 77-78).
Other analyses point at improvements resulting from migration. Unger (2005) showed that poor
municipalities with significant emigration converge upwards in terms of their per capita income over
time. Adelman and Taylor (1990) find that the largest multiplier impact of remittances is obtained in
very poor isolated communities. Cruz (2008) finds that incomes have risen dramatically (and poverty
fallen) as a result of recent international migration in the Chatino community (south-eastern Oaxaca
indigenous group) he studies, although he sees dependence on remittances, and rapidly decreasing
agricultural self-sufficiency, as negative consequences of emigration (Escobar, 2009. pp. 79).
Rural emigration and the dependence of rural households on remittances are clear. But other facts
seem harder to reconcile. The propensity of the poor to migrate is lower than that of other groups,
although almost one-half of the rural young of 1995 have already left rural areas. Remittances to the
poor are growing (400% from 1992 to 2006, and by a smaller but significant 40% between 2000 and
2002), but Mexico does not benefit from remittances as much as other Latin American countries
(Escobar, 2009. pp. 79).
The finding of a close connection between rural poverty and migration is in agreement with studies by
Tuirán (2002), which stress that a majority of the municipalities receiving highest per-capita
remittances are high–marginality (and high poverty) municipalities. Remittances are most significant
for the rural poor, but they still are not a major source of income to them, although some families
depend on them. Wage income and government transfers are more important. Therefore, migration is
not a significant factor lowering rural poverty or explaining rural economic growth (Escobar, 2009. pp.
89).
In a recently published study, Escobar (2008) has argued that the rural poor migrate in specific ways
due to three factors: their financial constraints, the recent nature of their migration, which means they
have little access to legal migration and their networks are only beginning to consolidate, and the
specific nature of the social capital used to migrate.
26
In this context, Escobar (2008) emphasize that successful migrants have significant incentives to flee, or
to break-up from their families and communities of origin, further lowering the social capital of their
relatives. Continuity of membership involves investing large resources and helping poor relatives and
community members. Communities slow this process through identity-reinforcing mechanisms, lists of
members in the United States, extending debt to family members remaining in the community, and
control of the marriage market: in many indigenous communities, participation (and sponsorship) in
the local festivities is a necessity, if a migrant member wishes to marry someone from the same
community.
The impact of remittances on poverty and inequality can be summarized thus:
1) Remittances make a significant contribution to GDP.
2) Remittances, however, do not compensate the labour force lost to migration
3) A preliminary approximation to the impact of remittances on poverty is provided by census evidence
of low migration rates in poor areas, and among poor households, but this analysis could
underestimate the emigration rates of poor households in particular.
4) The proportion of households receiving remittances is higher among low-income strata (which
qualifies the evidence from 3).
5) Non-poor households receive larger absolute remittances than poor households, but poor
households receive a larger share of their total income from remittances.
6) Remittances reduce income inequality, but poverty and inequality are lower in a no-migration
counterfactual scenario.
7) The above could be related to the specific social process of migration among the poor, which does
yield remittances, but does so in more difficult conditions than those obtaining for non-poor migrants.
Escobar (2008) concludes saying that the conclusions are mixed is not useful. From a development
perspective, however, it is possible to state that, in the current context, migration may represent a net
loss for Mexico. It seems to have a positive impact on poor, high-emigration areas, but the potential
impact of this labour force in Mexico is greater.
27
Adams et al (2005) calculates the effect of Migrant Remittances on Poverty in rural communities. A
modification of the Foster-Greer-Thorbecke (1984) poverty index was used to analyze the poverty
implications of remittances.
According with his work a poverty line, z, is required in order to estimate the effects of changes in
migrant remittances on poverty. The poverty line used is the per-capita income required to purchase a
basic basket of food and nonfood items in rural areas estimated by SEDESOL (2000).
The incidence of poverty ranges from 35 percent in the Northwest region to 81 percent in the South-
Southwest. His results showed that overall, poverty decreases when migrant remittances go up.
Nationally, the rural poverty effect is substantially greater for international remittances than for
remittances from internal migrants.
Another interesting finding in Adams et al (2005) is that poverty elasticity of remittances from migrants
abroad vary sharply across regions. The sensitivity of poverty to international remittances is greatest in
the high migration, West-Center region, and it is smallest in the low migration, South-Southwest
region. Other things being equal, a 10-percent increase in international remittances reduces poverty by
1.64 percent in the West-Center compared with only 0.11 percent in the South-Southwest; poverty
decreases by 1.68 percent in the West-Center, but there is no change in poverty in the South-
Southwest.
These findings suggest that the ameliorative effect of international remittances on rural poverty
increases with the prevalence of migration and that the distributional effects of migration become
more equal as increasing numbers of households gain access to foreign labor markets.
Finally on the revisión of Barcelata (2010. pp. 110) is observed that for the period between 2003-2008
the states with larger remittances reception and migration are the states with low state GDP growth
(LSGDP) compared with the rest of the states in the Mexican Republic. For the case of Guanajuato,
Oaxaca, Hidalgo, Guerrero, Michoacán y Distrito Federal presented a growth rate between 12 and 16%
compared with the 10 states with larger growth of 26%.
There is another group of states with strong remittances reception, showing higher GDP growth rates
but still lower than the highest GDP states: Jalisco, Veracruz y Puebla (19.8; 19.5, y 18.5%); just the
state of Mexico presented an income-growth rate of 26%.
28
In the same way Barcelata (2010. pp. 110) estimates the per capita GDP for every state. The states
with strong migration patterns are ranked as those with less per capita GDP growth.
The states of Guerrero, Oaxaca, Veracruz, Distrito Federal, Hidalgo, México y Michoacán presented per
capita GDP growth rates of 11, 13 y 16% for the firsts in the period of 1995-2005; and 23; 24.5; 24.7 y
26% for the four latter while the states with highest growth reached a 38% per captia GDP growth for
the same period. Nonetheless the states of Guanajuato and Puebla with strong remittances reception
grew in 36% and 37% respectively.
According with Barcelata (2005), we can not establish for sure a strong correlation between low GDP
growth / low-GDP per capita growth and migration.
Concluding with Barcelata study, he did not find any relationship between poverty reduction and the
magnitude of remittances received at municipal level, for the state of Veracruz. He found that for the
period 2004-2005 the municipalities with larger poverty reduction were those with a moderate
remittances reception. On the other hand the municipalities concentrating just 23% of the remittances
reduced their poverty on 9.8% average whereas the reduction in poverty was of 3.9% for the
municipalities getting the 38% of the total amount of remittances of the state of Veracruz.
29
V. Results
As anticipated in the methodology chapter, I obtain two OLS multiple regressions for the years 2000
and 2005 in a model which includes region-remittance interactions. The rationale to run this model is
to find, based on some literature, substantive differences in effects of remittances by region.
On the other hand some literature did not find an effect of remittances, but these studies tended to
look at the country as a whole, hence to try to reproduce these results I obtain the regressions of a
model without region-remittance interactions.
Comparing these models is possible to see that selectively remittances had an effect, but not
everywhere and not uniformly.
The table 1 summarizes the results obtained for the years of the study for the 2452 and 2454
municipalities of Mexico respectively. It’s important to mention that missing data (in both years 2000
and 2005) for the variable “municipal expenditure” in more than 200 municipalities caused a marginal
decrease in the total number of observations relative to the total number of municipalities (10%
decrease).
5.1 Main Findings
5.1.1 Regionalization of states
On the table 1 is possible to appreciate the interactive effect of the variable “region” and remittances
on the percentage of people living in poverty.
In every case on the table 1, the coefficient of ln_remitt now should be read as the coefficient of the
omitted region (the richest region) when the dummy variables are equal to zero (region 1 to 7).
As observed on this table, the coefficient of the omitted variable is positive and statistically significant
at a 99% of confidence level for the year of 2000, pointing out a positive correlation between
remittances and poverty. Nonetheless for the year 2005 the poverty categories “capabilities and
assets” are statistically non significant and the alimentary poverty though statistically significant
changes its sign indicating a negative correlation between remittances and the percentage of people
living in alimentary poverty.
30
Then for the omitted variable (the richest region of Mexico) ceteris paribus every 1% increase in the
amount of remittances received at municipal level increases in 1.7% the alimentary-poverty, increases
in 2.5% the capabilities-poverty and increases in 4.8% the assets-poverty in2000. In 2005 the omitted
region indicates that ceteris paribus every 1% increase in the amount of remittances at municipal level
indeed reduces in 1.9% the alimentary-poverty, hence supporting the hypothesis stated on this
paper.
Now, let’s analyze the coefficients obtained in the seven regions left.
Given that the omitted region is the “base category” the interpretation of the coefficient obtained in
every region should be read as a comparison to this base category.
For the interactive variable lnRem_REG1 (Region 1) in the year 2000 the coefficient of the three
poverty categories is negative as expected in the hypothesis nonetheless is non statistically significant
meaning that the coefficient obtained in Region 1 is not statistically different to the coefficient
obtained in the omitted category and then in average for Region is 1 is obtained the same
interpretation than the omitted category regarding the sign and effect of remittances on poverty at its
three categories.
In the year 2005 the effect of remittances for the Region 1 seems to have a negative larger effect on
the percentage of people in poverty.
The coefficient of the three poverty categories in Region 1 ceteris paribus, point out that every 1%
increase in the amount of remittances received at municipal level may reduce the percentage of
people living in alimentary-poverty in 3.27% (coefficient of the base category + coefficient of Region 1=
(-1.96) + (-1.32)=-3.27%), may reduce in 1.38% the percentage of people living in capabilities poverty
and may reduce in 2% the amount of people living in assets-poverty.
For the interactive variable lnRem_REG2 in the year 2000 the three categories of poverty showed a
positive correlation again between remittances and poverty, but especially a larger effect that the base
category in the case of alimentary, and capabilities. Ceteris paribus for the Region 2 a 1% increase in
the amount of remittances received by the municipality increased the percentage of people living in
alimentary-poverty in 3.47% (coefficient of the base category + coefficient in REG1), capabilities-
poverty in 4.45% and assets-poverty in 4.84% (the same as the base category given that coefficient was
31
not statistically significant). However for 2005 the alimentary-poverty is diminished in 1.9% (as well as
the base category).
The interactive variable lnRem_REG3 indicates a positive correlation in alimentary-poverty and
capabilities increasing the level of poverty in 3.5% and 4.58% respectively for 2000. For 2005 the
variable indicates a negative correlation just for the alimentary-poverty reducing it in 1.96% as the
base category.
The interactive variable lnRem_REG4 present the same positive correlation and coefficient that the
base category for alimentary and capabilities poverty in 2000. For 2005 the coefficient are the same as
the base category.
For the variable lnRem_REG5 is observed a strong negative correlation between remittances and
poverty rates. For 2000 the poverty rates show a decrease in the three categories of poverty of 3.2%,
3% and 3.1% respectively and in 2005 the alimentary-poverty and assets poverty are reduced by 1.96%
and 2.1 respectively.
The coefficients of the variable lnRem_REG6 suggest that municipal poverty is reduced at every
category in 2.3%, 2.1% and 2.2% respectively in 2000. In 2005 the reduction of poverty is just observed
for the alimentary-poverty category.
Finally in the Region 7 we can see that in 2000 is observed an increase in poverty as the remittances
received increased at municipal level in 1.7%, 2.54% and 4.84% respectively (same as the base
category) and in 2005 and increase in poverty for every 1% increase in remittances of 3%, and 2.89%
for alimentary and capabilities poverty respectively.
The interpretation of the coefficients in the control variables changed slightly after including the
regionalization and hence they will be explained following the information obtained from the table 2.
The control variable ln_totEx (log natural of municipal expenditure) presents the opposite expected
sign in 2000 and is significant just for the alimentary-poverty, which means that ceteris paribus, a 1%
increase in the amount of expenditure received at municipal level increase the percentage of people in
alimentary poverty in 0.82%; for 2005 a negative pattern is observed, reducing capabilities-poverty in
1.07% and assets-poverty in 2.26%.
32
The control variable ln_totInc (municipal income) is significant for every category of poverty for both
years and presents the expected negative sign which indicates that ceteris paribus every 1% increase in
the municipal income reduces in 9.6% the percentage of people living in alimentary poverty, in 9.3%
the capabilities-poverty and in 7.9% the assets-poverty at municipal level for the year 2000. In 2005
the same patter is observed but with a larger effect, reducing the percentage of people living in
alimentary poverty in 29.6%, capabilities-poverty in 34% and assets-poverty in 37%.
The other control variable ln_totPop shows the expected positive sign and its coefficient is statistically
significant for every poverty category in both years. Then ceteris paribus every 1% increase in the total
population increases the percentage of people living in alimentary-poverty in 9.2%, capabilities poverty
in 8.6% and assets-poverty in 6.2% at municipal level. For 2005 the effect is similar but of larger impact
increasing in 39% the alimentary-poverty, in 44% the capabilities poverty and in 46% the assets-
poverty.
The control variable margin (marginality index) also shows the expected positive sign and its coefficient
is statistically significant for every of the two years for every poverty category, indicative of a positive
correlation between marginality and poverty; hence ceteris paribus every 1% increase in marginality
index results in an increase of 15% the percentage of people in alimentary-poverty, 14.9% for
capabilities-poverty and 12.2% for assets-poverty. For 2005 the same pattern is observed with a 12.7%
increase in the alimentary-poverty, 12.5% in capabilities poverty and 46% increase of assets-poverty.
The last control variable mun_Unem (municipal unemployment) is statistically significant for all the
categories in 2000 but just presents the positive expected sign in 2005 in the assets-poverty category;
the other categories show the opposite sign and hence ceteris paribus every 1% increase in the
municipal unemployment is associated with a 3.9% decrease of alimentary poverty, 3.8 decrease in
capabilities-poverty, and 11.6% decrease in assets-poverty in 2000. For 2005 the correlation becomes
positive for the assets-poverty with a 1.9% increase in poverty for every 1% increase of unemployment.
5.1.2 Without Regionalization of states
The table 2 explains the effect of remittances on poverty without region-remittance interactions.
The core explanatory variable ln_remitt (log natural of remittances received at municipal level)
presents a positive signs and its coefficient is significant at 99% confidence level. The same situation
33
can be observed for the three different categories of poverty for 2000 and 2005. Nonetheless the sign
observed is the opposite of that expected and rejects the hypothesis stating that ceteris paribus (in
average and holding everything else constant) a 1% increase in the amount of remittances reduces the
percentage of people living in poverty.
Further more the coefficient showed in the table 2 suggest a positive correlation between the amount
of remittances and the percentage of people living in poverty, which means that ceteris paribus, a 1%
increase in the amount of remittances received at municipal level indeed increases the percentage of
people in alimentary-poverty in 1.1%, capabilities-poverty in 1.5% and poverty assets in 2 % at
municipal level for the year 2000; in the year 2005 the situation is not far different showing an increase
in alimentary-poverty of 1.2%, capabilities poverty of 1.2% and 0.88% for assets-poverty in every
municipality.
The control variable ln_totEx (log natural of municipal expenditure) presents the expected sign and is
significant for every category of poverty (except for alimentary-poverty in 2000), which means that
ceteris paribus, a 1% increase in the amount of expenditure received at municipal level reduces the
percentage of people in capabilities poverty in 1.1% and in 1.7% for assets-poverty; for 2005 the same
pattern is observed, but reducing alimentary-poverty in 1.1%, capabilities poverty in 2% and assets-
poverty in 3.7%.
The control variable ln_totInc (municipal income) is significant for every category of poverty for both
years and presents the expected negative sign which indicates that ceteris paribus every 1% increase in
the municipal income reduces in 12% the percentage of people living in alimentary poverty, in 11.8%
the capabilities-poverty and in 10% the assets-poverty at municipal level for the year 2000. In 2005 the
same patter is observed but with a larger effect, reducing the percentage of people living in alimentary
poverty in 29.7%, capabilities-poverty in 35% and assets-poverty in 39%.
The other control variable ln_totPop shows the expected positive sign and its coefficient is statistically
significant for every poverty category in both years. Then ceteris paribus every 1% increase in the total
population increases the percentage of people living in alimentary-poverty in 12.5%, capabilities
poverty in 12.4% and assets-poverty in 11.5% at municipal level. For 2005 the effect is similar but of
larger impact increasing in 34% the alimentary-poverty, in 44.5% the capabilities poverty and in 49.3%
the assets-poverty.
34
The control variable margin (marginality index) also shows the expected positive sign and its coefficient
is statistically significant for the two years for every poverty category, indicative of a positive
correlation between marginality and poverty; hence ceteris paribus every 1% decrease in the
marginality index results in an decrease of 14% the percentage of people in alimentary-poverty, 14%
for capabilities-poverty and 12% for assets-poverty. For 2005 the same pattern is observed with a 12%
decrease in the alimentary-poverty, 12.5% in capabilities poverty and 9% decrease of assets-poverty.
The last control variable mun_Unem (municipal unemployment) is statistically significant for almost all
the categories (except for assets-poverty in 2005) but just presents the positive expected sign in 2000
for the assets-poverty category; the other categories show the opposite negative sign and hence
ceteris paribus every 1% increase in the municipal unemployment is associated with a 3.9% decrease of
alimentary poverty, 3.8 decrease in capabilities-poverty, and 11.6% increase in assets-poverty in 2000.
For 2005 the negative correlation is consistent for the alimentary-poverty with a 0.63% decrease and
0.5% decrease in capabilities poverty.
5.2 Discussion
The different correlations observed between remittances and poverty across the 8 regions seem to
obey to different patterns of migration from Mexico to US given that the net amount of remittances
received increased in the spam of 5 years. At national level the total amount of remittances received
grew from 6,572 million dollars in 2000 to 21,688 million dollars in 2005 a percentage increase
equivalent to 230% in 5 years or 46% average increase annually.
When including region-remittance interactions in the econometric model the effect of remittances on
poverty is disentangled and then the correlation is neater identifying the states most benefited from
migration and remittances of US.
This is not clear the reason why some regions present a positive correlation between remittances and
poverty and may exist additional “omitted factors” having an influence on the net effect of poverty.
Nonetheless the focus on the present paper is focused on testing the hypothesis stating a negative
correlation between remittances and poverty and then is just emphasized its negative and significant
correlation. However in the chapter of conclusion some reasons of this observed phenomenon are
going to be exposed.
35
In summary the Mexican Regions supporting the hypothesis that an increase in the amount of
remittances received at municipal level indeed reduces the percentage of people in poverty are:
For 2000
Alimentary-poverty: Region 5 and 6
Patrimonial-poverty: Region 5 and 6
Assets-poverty: Region 4, 5 and 6.
For 2005
Alimentary-poverty: the omitted Region, Region 1, 2, 3, 4, 5, 6 (except for Region 7)
Capabilities-poverty: just Region 1
Assets-poverty: Region 1 and 5
36
VI. Conclusions
The literature concerning the effects of remittance on poverty provided split conclusions. On one hand
some studies supported the negative correlation between remittances and poverty differentiating its
effects by regions inside a country, whereas others found no correlation when there was no distinction
by region and the country was taken as a whole entity.
In this paper I provided the results of two econometrics models, one including region-remittance
interactions and the other without the interactions with the purpose to provide additional evidence
supporting or rejecting what prior studies have contributed.
The model with region-remittance interactions provided far different results to those provided with
the model without region-remittance interactions. The prior presented a negative correlation between
remittances and poverty while the latter tended to sub-estimate the regional negative correlation that
remittances have on poverty and in some cases even to show a positive correlation.
Comparing these models is possible to see that selectively remittances reduce poverty, but not
everywhere and not uniformly.
The tables 3 and 6 show the states with the largest reception of remittances for the years 2000 and
2005.
The states of Michoacán, Guanajuato, Jalisco, México, Veracruz, Puebla, Guerrero and Oaxaca
concentrate the 59% of the amount of remittances received at national level in 2000.
For 2005 the same states with the exception of Oaxaca concentrated exactly the same percentage. In
this year the Distrito Federal surpassed the amount of remittances received by Oaxaca State becoming
one with the largest number of remittances received.
In the same tables we can observe that the amount of remittances received by states changes when
divided by the total population. Nonetheless by far three states seem to keep taking the first ranking in
both years 2000 and 2005: Michoacán, Guanajuato and Guerrero; further more these states
concentrate 26% and 25% of the total amount of remittances in 2000 and 2005.
37
Comparing these data with the results obtained in the econometric regressions a priori one should
expect a reduction in poverty in the municipalities of the states receiving more remittances or at least
the largest effect. However my results show for the 2000 the states having their poverty levels
reduced are: Guerrero, Oaxaca, Chiapas, Veracruz and Tabasco for alimentary, capabilities and
assets-poverty and Querétaro, Estado de México, Distrito Federal, Morelos, Hidalgo, Tlaxcala and
Puebla in the case of assets-poverty.
For the year 2005 the reduction in poverty accounts for all the municipalities except for the
municipalities of Campeche, Yucatán and Quintana Roo. Additionally the capabilities-poverty and
assets poverty is reduced for the municipalities of Baja California, Baja California Sur, Sonora, Sinaloa
and Nayarit. The States of Guerrero, Oaxaca and Chiapas reduced as well their assets-poverty.
Whit these results as a general conclusion the hypothesis stated at the beginning of the document is
supported: on average and holding everything else constant, the amount of remittances received by
municipalities reduces the percentage of people living in poverty at its three different categories: food-
poverty, capabilities-poverty and assets-poverty, nonetheless selectively remittances reduce poverty,
but not everywhere and not uniformly.
The table 7 summarizes additional information to state that:
The net-largest recipients of remittances are not the only states reducing their municipal
poverty rates.
Not all the municipalities receiving high-per capita remittances reduced their poverty rates, in
some cases municipalities with high level of remittances per capita reduced poverty in 2000 but
not in 2005 and others performed the other way around (table 7).
In 2005 almost all the municipalities reduced alimentary-poverty and this reduction is
coincident with the large net-increase of remittances from 2000 to 2005 (table 4 and 6).
Remittances reduce poverty rates certainly but given the complexity of the migratory phenomenon
and its factors involved it is difficult to disentangle the process by which remittances and migration
may effectively reduce poverty in every municipality and state.
38
VII. Tables.
Table 1. Effect of the amount of remittances received at municipal level, municipal expenditure, municipal income, total population, marginality, municipal unemployment AND the interactive effect of the remittances and geographical region on the percentage of people living in poverty: Results of OLS multiple regressions
Variables
Year 2000 Year 2005
Alimentary Poverty
Capabilities Poverty
Assets Poverty
Alimentary Poverty
Capabilities Poverty
Assets Poverty
ln_remitt 1.783* (1.96)
2.542* (2.75)
4.846*** (5.40)
-1.965** (-2.89)
-1.278 (-1.75)
1.165 (1.47)
lnRem_REG1 -1.130 (-1.34)
-1.112 (-1.30)
-1.463 (-1.76)
-1.327** (-2.03 )
-1.382** (-1.97 )
-2.003*** (-2.63)
lnRem_REG2 1.692* (1.95)
1.913** (2.18)
1.474 (1.72)
0.857 (-1.28)
1.170 (1.63)
1.230 (1.58)
lnRem_REG3 1.805** (2.03)
2.045** (2.26)
1.685 (1.92)
-0.085 (-0.13)
0.137 (0.19)
0.452 (0.58)
lnRem_REG4 -1.074 (-1.35)
-1.382 (-1.70)
-2.448*** (-3.11)
0.377 (-0.63)
0.077 (0.12)
-1.264 (-1.80)
lnRem_REG5 -3.264***
(-4.23) -3.076***
(-3.93) -3.181***
(-4.18) 0.128 (-0.22)
-0.394 (-0.63)
-2.151*** (-3.19)
lnRem_REG6 -2.325**
(-2.4) -2.155**
(-2.19) -2.226**
(-2.33) -0.244 (-0.33)
-0.344 (-0.43)
-1.217 (-1.41)
lnRem_REG7 1.065 (1.09) .730
(t=0.74 ) -1.174 (-1.22)
3.095*** (-4.23)
2.898*** (3.69 )
0.790 (0.93)
ln_totExp 0.822** (2.19)
.532 (1.39)
.055 (0.15)
-0.422 (-1.05)
-1.074** (-2.48)
-2.266*** (-4.83)
ln_totInc -9.629***
(-11.9) -9.364***
(-11.40) -7.941***
(-9.94) -29.638***
(-17.83) -34.291*** (-19.20)
-37.331*** (-19.29)
ln_totPop 9.236***
(9.15) 8.602***
(8.40) 6.236***
(6.26) 39.103***
(19.68 ) 44.105***
(20.65) 46.076***
(19.91)
margin 15.082***
(35.4) 14.976***
(34.64) 12.215***
(29.05) 12.751***
(36.54) 12.513***
(33.37) 46.076***
(23.17)
mun_Unem -3.950***
(-7.05) -3.794***
(-6.67 ) -2.453***
(-4.43) 0.185 (0.59)
.628 (1.85)
1.912*** (5.21)
N 2228 2228 2228 2182 2182 2182
Adjusted R-squared
0.85 0.85 0.81 0.84 0.84 0.78
* Significant at <0.10 ** Significant at <0.05 *** Significant at <.01
t ratios in parentheses
39
Table 2. Effect of the amount of remittances received at municipal level, municipal expenditure, municipal income, total population, marginality and municipal unemployment on the percentage of people living in poverty: Results of OLS multiple regressions
Variables
Year 2000 Year 2005
Alimentary Poverty
Capabilities Poverty
Assets Poverty
Alimentary Poverty
Capabilities Poverty
Assets Poverty
ln_remitt 1.170***
(3.34 ) 1.502***
(4.19) 2.038***
(5.74) 1.268***
(4.69) 1.280***
(-4.45) 0.887** (2.86)
ln_totExp -0.634* (-1.77)
-1.126** (-3.06)
-1.735*** (-4.75)
-1.137** (-2.88)
-2.057** * (-4.89)
-3.733*** (-8.22)
ln_totInc -12.192 ***
(-15.33) - 11.849***
(-14.56) -10.455***
(-12.95) -29.709***
(-17.44) -35.051***
(-19.32) -39.196***
(-20.03)
ln_totPop 12.491***
(13.98) 12.438***
(13.60) 11.534 ***
(12.71) 34.335***
(18.16) 44.558***
(20.64) 49.303***
(22.71)
margin 14.141***
(33.06 ) 14.195***
(32.42 ) 12.215***
(29.05) 12.316***
(34.98) 12.513***
(33.37) 9.361*** (23.15)
mun_Unem -3.919***
(-10.26) -3.819***
(-9.76) 11.689***
(26.91 ) -0.634** (-3.01)
-0.528** (-2.35)
0.048 (0.20)
N 2228 2228 2228 2182 2182 2182
Adjusted R-squared
0.83 0.82 0.77 0.82 0.82 0.75
* Significant at <0.10
** Significant at <0.05
*** Significant at <.01
t ratios in parentheses
Table 3. States of Mexico with the largest reception of remittances in 2000
Absolute (million dollars) Relative (percentage) Per captia (dollars)
Michoacán 694 11 195
Guanajuato 603 9 131
Jalisco 524 8 92
México 524 8 37
Veracruz 420 6 63
Puebla 393 6 73
Guerrero 371 6 124
Oaxaca 368 6 100
Total 3,897 59 -
6,573
Amount Received
State
Total amount of remittances received in Mexico (million)
40
TOTAL 1,194,317.84 TOTAL 6,572.74 TOTAL 100
MEAN 489.27 MEAN 2.69 MEAN 1.31
MAX 16,899.40 MAX 116.03 MAX 60.69
MIN 3.27 MIN 0.02 MIN 0.01
ST. DEV 1,182.09 ST. DEV 6.53 ST. DEV 3.6
VARIANCE 1,397,332.24 VARIANCE 42.70 VARIANCE 12.97
NUMBER OB 2,441 NUMBER OB 2,441.00 OBS 2,441
Households receiving remittances (percentage)
Remittances per municipality/state
(percentage)
Number of Households:
Number of households receiving remittances per
municipality
Amount of remittances received per state
(million dollars)
Table 4. Number of households receiving remittances; amount and percentage of remittances received per state and municipality
in 2000
22,268,126
5.4
Absolute (million dollars) Relative (percentage) Per captia (dollars)
Michoacán 2,462 11 621
Guanajuato 1,905 9 389
Mexico 1,792 8 128
Jalisco 1,723 8 255
Veracruz 1,364 6 192
Distrito Federal 1,334 6 153
Puebla 1,133 5 211
Guerrero 1,117 5 359
Total 12,830 59 -
21,689
Table 5. States of Mexico with the largest reception of remittances in 2005
Total amount of remittances received in Mexico (million)
State
Amount Received
TOTAL 1,480,865 TOTAL 21,688.80 TOTAL 100
MEAN 603.45 MEAN 8.84 MEAN 1.3
MAX 17,151.41 MAX 315.99 MAX 55.7
MIN 4.49 MIN 0.07 MIN 0.01
ST. DEV 1,288.12 ST. DEV 20.14 ST. DEV 3.41
VARIANCE 1,659,249.33 VARIANCE 405.72 VARIANCE 11.65
NUMBER OB 2,454 NUMBER OB 2,454 OBS 2,454
Households receiving remittances (percentage)
Number of Households: 24,803,625
6.0
Number of households receiving remittances per
municipality
Amount of remittances received per state
(million dollars)
Remittances per municipality/state
(percentage)
Table 6. Number of households receiving remittances; amount and percentage of remittances received per state and municipality
in 2005
41
Alimentary-
poverty
Capabilities-
povertyAssets-poverty
Remittances per
capita (dollars)
Alimentary-
poverty
Capabilities-
povertyAssets-poverty
Remittances per
capita (dollars)
Guerrero Guerrero Guerrero 124
All except
Campeche,
Yucatán and
Quintan Roo
Baja California Baja California 93
Oaxaca Oaxaca Oaxaca 100Baja California
Sur
Baja California
Sur49
Chiapas Chiapas Chiapas 48 Sonora Sonora 126
Veracruz Veracruz Veracruz 63 Sinaloa Sinaloa 175
Tabasco Tabasco Tabasco 20 Nayarit Nayarit 325
Querétaro 88 Guerrero 359
Estado de México 37 Oaxaca 300
Distrito Federal 41 Chiapas 180
Morelos 104
Hidalgo 118
Tlaxcala 67
Puebla 73
Tabla 7. States with municipal poverty reduction through remittances
Year 2000 Year 2005
42
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