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1 23
Population Research and Policy
Review
in cooperation with the Southern
Demographic Association (SDA)
ISSN 0167-5923
Popul Res Policy Rev
DOI 10.1007/s11113-013-9311-8
Hurricane Katrina, a Construction Boom,
and a New Labor Force: Latino Immigrants
and the New Orleans Construction
Industry, 2000 and 2006–2010
Blake Sisk & Carl L.Bankston
1 23
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Hurricane Katrina, a Construction Boom, and a New
Labor Force: Latino Immigrants and the New Orleans
Construction Industry, 2000 and 2006–2010
Blake Sisk •Carl L. Bankston III
Received: 13 February 2013 / Accepted: 6 November 2013
ÓSpringer Science+Business Media Dordrecht 2013
Abstract Disasters provide opportunities to study the social and economic
dimensions of large-scale shifts. Drawn by the surge in demand for low-skill con-
struction workers in the aftermath of Hurricane Katrina in 2005, Latino immigrants
represented a substantial share of the New Orleans reconstruction workforce.
Scholars, however, have yet to examine how the increased presence of immigrants
affected U.S.-born workers in New Orleans. In this analysis, we investigate how the
influx of Latino immigrant construction workers shaped the demographic compo-
sition and occupational-wage structure of the New Orleans construction sector.
Using IPUMS-U.S.A. data from the 2000 and 2006–2010 periods for the New
Orleans MSA, we employ logistic and multinomial logistic regression models to
analyze a sample of 3,206 foreign-born Latinos, U.S.-born whites, U.S.-born blacks,
and others employed in the construction industry. Our analysis indicates that the
probability of U.S.-born workers being employed in construction remained stable
from the pre- to post-storm period, even as we find evidence of an emerging
immigrant employment niche in the post-Katrina construction industry. After the
storm, however, Latino immigrants were much more heavily concentrated in
occupations at the bottom end of the construction industry’s wage structure, while
the relative position of U.S.-born workers improved across the two periods.
Together, these findings show that disasters, like other structural shifts, can yield the
conditions that produce immigrant employment niches. Moreover, our results
indicate that while employment niches provide economic opportunities for the
foreign-born, they can also intensify the disadvantage experienced by immigrant
workers.
B. Sisk (&)
Department of Sociology, Vanderbilt University, PMB 351811, Nashville, TN 37235-1811, USA
e-mail: blake.sisk@vanderbilt.edu
C. L. Bankston III
Department of Sociology, Tulane University, New Orleans, LA, USA
123
Popul Res Policy Rev
DOI 10.1007/s11113-013-9311-8
Author's personal copy
Keywords International migration Labor market stratification Immigrant
niches Disasters
Introduction
Disasters are profoundly social events that often reveal and reinforce the existing
stratification of social institutions (Merton 1969; Elliott and Pais 2006; Tierney
2007). The size and scope of the damage inflicted on New Orleans by Hurricane
Katrina in August of 2005 brought the social and economic dimensions of disasters
into sharp relief (Elliott and Pais 2006; Brunsma et al. 2007; Fussell 2009b). One
major demographic change that occurred as a result of Katrina was the
‘‘institutionalization’’ of a Latino immigrant labor niche in the New Orleans
construction industry (Donato et al. 2007, p. 217). Drawn by the immediate surge in
demand for workers to clean up and rebuild the city, Latino immigrants were
heavily represented among construction workers in post-Katrina New Orleans
(Fletcher et al. 2006; Fussell 2007,2009a,b). The visibility of these immigrant
workers in the post-storm period fueled fears that their arrival would reduce
economic prospects for the residents of New Orleans (Fletcher et al. 2006; Trujillo-
Paga
´n2007); however, it is unclear how the rapid growth in the immigrant labor
supply after Katrina affected the city’s construction industry.
Although previous studies have examined how an increased presence of
immigrants shapes the labor market outcomes of the U.S.-born in a variety of
contexts, scholars have paid less attention to the role of immigrants in the
restructuring of local industries after a disaster. Economic research finds either
positive or negative effects of immigrant workers on the employment outcomes of
the U.S.-born, depending on the assumptions made about the substitutability of
immigrants for U.S.-born workers (Borjas 2003;Card2005). Nonetheless, scholars
studying immigrant employment niches find that the development of a niche—
which is often concentrated at the bottom end of an industry’s wage structure—may
provide opportunities for U.S.-born workers to move up the occupational hierarchy
within that industry (Waldinger 1994). At the same time, the low-wage nature of
immigrant niche employment may limit the economic prospects for immigrant
workers (Model 1993). In this analysis, we investigate the consequences of
Hurricane Katrina—and of the arrival of Latino immigrants that occurred as a
result—for the demographic composition and occupational-wage structure of the
New Orleans construction industry.
Literature Review
In the following subsections, we first highlight studies that assess the effects of
immigrants on the employment outcomes of the U.S.-born. Then, we discuss
immigrant employment niches and the role of those niches as industries restructure.
Lastly, we examine prior research on the social and economic consequences of
disasters, with a focus on the changes experienced by New Orleans due to Katrina.
B. Sisk, C. L. Bankston III
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Immigration and U.S.-Born Workers
There is a debate in the economics literature regarding the consequences of
immigration for the employment outcomes of the U.S.-born. Researchers on each
side of the debate often use cross-sectional data from the U.S. Census to estimate the
aggregate effects that immigrants have on the wages and employment of other
workers within metropolitan areas. The key point of divergence in the debate is the
assumption made about the substitutability of immigrants and U.S.-born workers:
Researchers that assume perfect substitutability between U.S.-born and immigrant
workers find that rising immigration reduces employment opportunities for U.S.-
born workers, while those that assume imperfect substitutability find negligible or
positive effects.
Scholars have reached differing conclusions on the influence of immigrants on
U.S.-born worker participation in labor markets and industries. Using the 1980 U.S.
Census, Filer (1992) examines the internal migration patterns of workers across
metropolitan areas and finds that U.S.-born workers tend to avoid living in metro
areas with large, recently arrived immigrant populations. According to Filer, this
effect is the strongest for workers at the lowest skill levels, suggesting that
competition between low-skilled U.S.-born workers and immigrant workers may
cause some U.S.-born workers to move. Similarly, Frey (1995) and Borjas et al.
(1996) argue that, on average, an increase in the foreign-born labor supply in a local
labor market is correlated with the out-migration of U.S.-born workers, particularly
for workers at the bottom end of the educational distribution. This line of analysis
suggests that the in-migration of immigrant workers into a local labor market will
act as a push mechanism that increases competition for employment and
incentivizes the out-migration of the U.S.-born.
On the other hand, Card (2001) concludes that recent immigrants do not displace
older immigrants and U.S.-born workers. Analyzing data from the 2000 U.S.
Census, Card (2005) finds that when looking within skill levels, there is often a
positive relationship between the inflows of immigrants and U.S.-born workers into
a local labor market. Likewise, using Census data from 1960 to 2005 for the state of
California, Peri (2011a) concludes that the inflow of immigrant workers into the
state did not displace any U.S.-born workers from employment. In fact, Peri finds
some evidence for a net positive effect of immigration on employment for the U.S.-
born, particularly for those in low-skill sectors, and no evidence to suggest that
immigration reduced the job prospects of the U.S.-born. Under the assumption that,
even at the lowest of skill levels, there are substantial differences between how
U.S.-born and foreign-born workers interact with the labor market, these findings
suggest that there is little evidence that U.S.-born workers are crowded out by
immigrants.
Borjas et al. (1996) and Borjas (2003) argue that one of the primary factors that
can push U.S.-born workers out of a metropolitan area experiencing an increase in
immigrant labor is the downward pressure that immigrants put on earnings. Using
the assumption that immigrant and U.S.-born workers within a particular skill level
are perfectly substitutable, Borjas (2003) estimates that, overall, a 10 % increase in
the immigrant labor supply decreases wages of U.S.-born workers by 3–4 %.
Latino Immigrants and the New Orleans Construction Industry
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Borjas’ (2003, p. 1370) estimates vary by skill level, as wages fell 8.9 % for high
school dropouts, 2.6 % for high school graduates, and 4.9 % for college graduates.
However, other researchers find little evidence that immigrants put downward
pressure on the wages of the U.S.-born. Primarily, these studies argue that, even
among workers with low skill levels, immigrant workers are imperfect substitutes
for U.S.-born workers, such that foreign-born and U.S.-born workers with the same
level of education do not fill the same structural position in the U.S. labor market.
Research based on this assumption finds that increased immigrant labor supply had
a negligible effect on the wages of low-skill U.S.-born workers from 1990 to 2004
(Ottaviano et al. 2006). Peri (2011b) examines the effect of immigration on U.S.-
born wages from 2000 to 2009 by state and metropolitan area and finds that the
main beneficiaries of increased immigration are U.S.-born workers with the lowest
levels of education. Nationally, Peri finds, the effects of immigrants on the wages of
the U.S.-born during the 2000s were mainly positive; U.S.-born workers without a
college degree earned between 0.7 and 1.6 % more as a result of immigration from
2000 to 2009.
As the studies reviewed here make clear, the economic literature regarding the
effect of immigration on the out-migration and wages of U.S.-born workers is
ambiguous, and the conclusions of these studies are largely dependent on
assumptions made about the substitutability of immigrant and U.S.-born workers.
To provide further context for our analysis, in the next section, we discuss the
sociological literature on immigrant employment niches.
Immigrant Employment Niches
The Effects of Immigrant Niches
Social scientists refer to an industry or occupation where a particular racial, ethnic,
or national-origin group is overrepresented beyond its overall labor market share as
a niche (Wilson 1999). Employment niches often develop as a result of blocked
opportunities in the labor market; as members of a minority group encounter
discrimination or lack of access to resources that restricts employment prospects in
the broader economy, niches are environments where social capital can help to
secure jobs through referrals from co-ethnics and information passed through social
networks (Logan and Alba 1999; Waldinger and Der-Martirosian 2001; Morales
2008). In the case of immigrants, in particular, employment niches provide a place
for workers to gain a foothold in the local economy upon arrival in the United States
(Nee et al. 1994).
However, it is uncertain if participation in an employment niche is positive for
the long-term prospects of workers. Model (1993) argues that while niches do
provide access to employment opportunities, niches in the post-industrial context
are predominantly located in low-skill industries that relegate workers to low wages
with little hope of upward mobility. This is supported by evidence that occupational
prestige and wages tend to be lower in industries with high concentrations of
Latinos, Asians, and blacks (Wilson 2003). Moreover, the employment niches of
B. Sisk, C. L. Bankston III
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Mexican immigrants tend to be concentrated in occupations that are physically
demanding and have adverse working conditions (Waldinger and Der-Martirosian
2001). Thus, while the niche may provide initial help in gaining employment,
working in a niche can also reduce the likelihood of future advancement.
Using the case study of the emergence of an immigrant employment niche in
New York City government jobs, Waldinger (1994) conceptualizes workers within a
local labor market as being ordered in a queue, where the group considered by
employers to be the most desirable is first in line, and so on. During periods of
economic expansion or restructuring when new jobs are produced in an industry, the
existing workforce is best positioned to fill positions created higher up in the wage
structure. This upward movement, however, creates openings at the bottom end of
the hierarchy, thus fueling demand for a new group of workers to enter that
industry’s labor queue and fill those positions. As a result of industrial restructuring,
then, opportunities emerge for immigrants to enter into the bottom of the labor
queue. In the process that Waldinger describes, it is the opening up of positions at
the bottom of the wage distribution that attracts immigrants to a newly restructured
industry. In this case, the immigrants are neither displacing existing workers in that
industry nor reducing the wages of the U.S.-born, but rather providing a needed
boost to the available supply of labor.
While Rosenfeld and Tienda’s (1999) analysis of niches in Los Angeles,
Chicago, and Atlanta from 1970 to 1990 broadly reflects the kind of process that
Waldinger (1994) describes, the authors also argue that there is some displacement
of low-skilled, U.S.-born workers at the bottom end of the occupational hierarchy.
They find that some U.S.-born workers experienced upward mobility when
immigrants entered into the labor queue, but those at the very bottom of the skills
hierarchy continued to face disadvantage. Focusing specifically on the outcomes of
U.S.-born blacks, Grant et al. (1996) find similar results using data from Los
Angeles. Further, Adelman et al. (2005) use Census data for 150 metropolitan areas
in the U.S. to examine the effect of immigration on the labor market outcomes of
U.S.-born blacks; this analysis finds that while the median earnings of blacks grow
with increased immigration, a larger immigrant population may also contribute to
higher poverty and lower rates of labor force participation for blacks. This suggests
that while the emergence of immigrant employment niches may not improve the
employment outcomes of all U.S.-born workers, the presence of immigrant workers
can lead to occupational mobility for the U.S.-born.
Industrial Change and Immigrant Niches
Examples of restructuring sectors where immigrants played a crucial role in filling a
new demand for low-skill labor include the meat processing and carpet manufac-
turing industries (Griffith 1990,1999; Herna
´ndez-Leo
´n and Zu
´n
˜iga 2006). Kandel
and Parrado (2005) provide a detailed discussion of how the restructuring of the
meat processing industry led to the arrival and settlement of Latino immigrants in
rural areas of the United States that had previously experienced little migration. In
particular, Kandel and Parrado point to a number of changes in the industry that
reduced the attractiveness of meat processing jobs for U.S.-born workers; moreover,
Latino Immigrants and the New Orleans Construction Industry
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the physical demands and work conditions of meat processing employment relative
to other employment with comparable wages, particularly in labor-short rural areas,
helped to foster recruitment practices focused on Latino immigrants. As a result, the
industry began to hire more immigrants, with the proportion of immigrants rising
from 8 % of workers in meat processing plants in 1980 to 35 % in 2000 (Kaushal
et al. 2007). Correspondingly, the development of an immigrant niche in the carpet
manufacturing industry followed a similar trajectory, with Mexican immigrants
moving into the industry on a large scale during the 1990s (Zu
´n
˜iga and Herna
´ndez-
Leo
´n2001; Herna
´ndez-Leo
´n and Zu
´n
˜iga 2006).
Like the sectors discussed above, the construction industry also experienced
large-scale transformations that led to a growing presence of immigrant workers.
Allen (1989) documents a decline in unionism in the U.S. construction industry
during the 1970s and identifies the erosion of the productivity gap between union
and non-union contractors as the key factor in this decline. Thieblot (2002) argues
that technological change in construction diminished the need for highly skilled
workers and increased demand for semi-skilled laborers, creating a profusion of
semi-skilled job categories not widely represented in traditional union structures.
Construction also shifted in the late twentieth and early twenty-first centuries from
public buildings to private homes, which contributed to the housing boom that
collapsed during the deep recession of the late 2000s; as a result of this shift, the
industry became more volatile and seasonal and attracted more immigrant workers
(Mullins 2006; Hadi 2011).
Due in part to these developments, the construction industry has emerged as what
Waldinger (1995, p. 577) refers to as the ‘‘quintessential ethnic niche’’ for foreign-
born Latinos. Latino immigrants presently comprise 7 % of the total labor force, but
20 % of the construction labor force (Kochhar 2007). Moreover, while only 8 % of
the total U.S. workforce was employed in the construction industry in 2005, 1 in 5
Latino immigrant workers were employed in construction. However, Latino
immigrants experience structural disadvantage within the construction industry, as
foreign-born Latinos are overwhelmingly concentrated in low-skill, low-wage
occupations in the industry and earn less, on average, than other construction
workers (Kochhar 2007; Catanzarite and Trimble 2008).
As the examples from the meat processing, carpet manufacturing, and
construction industries illustrate, immigrant employment niches often develop in
response to industrial transformations that create demands for a new, low-skilled
workforce. In the case of these industries, immigrants responded to industrial
changes by filling a structural need for workers at the bottom of the labor queue.
While the examples of industrial restructuring we reference here took place over
a period of years, our analysis focuses on changes in the New Orleans
construction industry that occurred in a much shorter time frame due to
Hurricane Katrina. However, we argue that Katrina acted much in the same way
that changes in labor management and technology did for industries like meat
processing and carpet manufacturing: A new demand for low-skill labor was
created and Latino immigrants took advantage of the economic opportunity to
establish a niche.
B. Sisk, C. L. Bankston III
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The Socioeconomic Consequences of Disasters
This analysis is part of a larger body of prior literature that explores the social and
economic effects of Hurricane Katrina on New Orleans and the Gulf Coast region
(Hartman and Squires 2006; Brunsma et al. 2007; Potter 2007; Brunsma and Picou
2008; Fussell et al. 2010). As scholars of disasters note, the negative consequences
of contemporary disasters tend to expose and reinforce existing social inequalities
(Tierney 2007). For instance, researchers have found that black workers from New
Orleans were more likely than whites to lose their jobs after the hurricane (Elliott
and Pais 2006), and that New Orleans’ black residents were less likely to return to
the city post-Katrina than whites (Elliott et al. 2009; Groen and Polivka 2010).
Disasters also shape social inequality through the in-migration of new workers
attracted by the ‘‘recovery machine’’ (Donner and Rodrı
´guez 2008; Pais and Elliott
2008, p. 1415). Overall, hurricanes negatively affect local economies by slowing
growth rates and reducing employment (Strobl 2011). The construction industry,
however, undergoes increases in earnings and employment as labor supplies
diminish and demand for construction workers surges in the aftermath of a hurricane
(Tierney 2007; Belasen and Polachek 2008). As part of an effort to meet the sudden
demand for construction workers in the Gulf region following Katrina, the federal
government temporarily relaxed sanctions against employers that hired unautho-
rized immigrant workers and lifted the Davis-Bacon Act—which guarantees
construction workers the prevailing local wage when paid with federal funds—
providing employers more flexibility in recruiting their workforce (Fussell 2007).
Together, the relaxing of labor standards and the strong demand for workers
provided a structural opening for Latino immigrants to enter the New Orleans
construction labor force.
In order to produce a demographic portrait of the post-Katrina construction
workforce, researchers at Tulane University collaborated with human rights experts
from the University of California, Berkeley, in early 2006 using key informant
interviews, targeted sampling, and random sampling to survey reconstruction
workers (Fletcher et al. 2006). Their valuable report was released in 2006 and later
published in a peer-reviewed journal (Vinck et al. 2009). The team described the
reconstruction workforce of New Orleans as nearly half Latino and comprising
many workers who had been previously employed in construction elsewhere in the
U.S. The immigrants surveyed by Fletcher et al. were concentrated in roofing and
carpentry, painting and sheetrock work, gutting houses, and debris removal; these
are jobs that were both in high demand after the storm and most likely to expose
workers to health risks and unsafe conditions. Moreover, the vulnerable position of
many of the immigrant workers was compounded by immigration status, as the
survey found that half of the Latino immigrants in New Orleans after the storm were
unauthorized; on average, unauthorized immigrant workers earn lower wages and
experience more adverse working conditions relative to legal immigrants (Donato
and Sisk 2012).
Employing an innovative methodological design that surveyed respondents at the
mobile consulates set up by foreign governments in New Orleans following the
storm, Fussell (2009a) collected data from Mexicans, Brazilians, and Nicaraguans
Latino Immigrants and the New Orleans Construction Industry
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5–7 months after Katrina to produce another detailed demographic profile of
immigrant workers. Fussell (2009a, p. 375; b, p. 458) describes the Latino
immigrants who arrived to work in New Orleans as a ‘‘rapid response labor force,’’
in that they arrived right after the hurricane and did not have plans to stay in the area
beyond 2 years. Like Fletcher et al. (2006), Fussell finds that the immigrant workers
faced considerable barriers to social mobility, as they were largely unauthorized,
had few family ties in the United States, and possessed low levels of education and
English proficiency. Moreover, the economic prospects of immigrant workers in
post-Katrina New Orleans were also diminished by widespread wage theft and
robbery, as Latino immigrant workers were susceptible to targeting from criminals
and exploitation at the hands of employers (Fussell 2011; Drever and Blue 2011;
Trujillo-Paga
´n2012; Warren forthcoming). Thus, Latino immigrant workers in
post-Katrina New Orleans faced considerable barriers to economic integration, as
they lacked access to institutions and infrastructure, were targeted for crime, and
lacked adequate labor protection (Drever and Blue 2011; Trujillo-Paga
´n2012).
Despite these barriers, however, reconstruction employment represented an
economic opportunity for immigrants: Fussell (2009b) finds that the average
earnings of immigrant reconstruction workers were nearly two hundred dollars more
per week than comparable Mexican immigrants working elsewhere. Thus, although
foreign-born workers in the post-Katrina period were a vulnerable population that
experienced significant disadvantage in the New Orleans construction industry
(Fletcher et al. 2006), for the Latino immigrants who arrived after the storm, the
rebuilding of New Orleans represented an economic opportunity (Fussell 2009a,b).
Summary
Disasters provide opportunities to examine the social and economic dimensions of
large-scale structural shifts (Tierney 2007). Following Hurricane Katrina, the New
Orleans construction industry experienced a surge in demand for low-skill workers,
and Latino immigrants responded to this increased demand in large numbers. In this
analysis, we examine the consequences of this influx of Latino immigrant labor for
the New Orleans construction industry. Broadly speaking, economic research is
ambiguous regarding the effect of immigrants on the employment outcomes of the
U.S.-born, with much of the debate hinging on assumptions about the substitut-
ability of immigrant and U.S.-born workers (Borjas 2003; Card 2005). However,
surveys taken directly after the storm indicate that immigrants were disproportion-
ately employed in the riskiest and lowest-paying reconstruction jobs, suggesting that
immigrants were filling a gap in the labor force not filled by U.S.-born workers
(Fletcher et al. 2006; Fussell 2009b). Under this scenario, it is possible that the
arrival of immigrants may have actually boosted the employment prospects of U.S.-
born construction workers in New Orleans.
As Waldinger (1994) outlines, immigrants often gain access to an industry when
it is experiencing some kind of disruption, as restructuring industries often create a
new structural demand for low-skill labor that provides the conditions for an
immigrant niche to emerge. At the same time, however, some researchers are
B. Sisk, C. L. Bankston III
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pessimistic about the prospects of immigrants working in employment niches, due
to the fact that niche jobs tend to be at the bottom of the wage distribution and have
few opportunities for advancement (Model 1993). Thus, much like the emergence of
immigrant niches in meat processing, carpet manufacturing, and the national
construction industry, the restructuring of the New Orleans construction industry
after Katrina is an important opportunity to investigate the effect that immigrant
workers have on local labor markets. We now turn to our analysis of the
demographic composition and occupational-wage structure of the New Orleans
construction industry before and after Hurricane Katrina.
Data and Methods
Data
The analysis uses data from the Integrated Public Use Microdata Series (IPUMS-
U.S.A.). IPUMS-U.S.A. is a project conducted by the Minnesota Population Center
at the University of Minnesota, and is a collection of fifty samples from 1850 to
2011 compiled from the U.S. Census and the American Community Survey (ACS).
IPUMS-U.S.A. data are specifically designed to facilitate analyses over time, as all
of the variables are harmonized across samples; this provides uniform measures for
each variable across all available years of the data (Ruggles et al. 2010).
For our analysis, we use IPUMS-U.S.A. samples from the 2000 U.S. Census
(which represents the pre-Katrina period) and a pooled sample of the ACS from
2006 to 2010 (which represents the post-Katrina period). The 2000 sample is a 5 %
national random sample of the U.S. population taken from the 2000 Census. The
2006–2010 pooled sample is calibrated by IPUMS-U.S.A to reflect the population
over the entire 5-year period and contains respondents from the 2006, 2007, 2008,
2009, and 2010 1 % American Community Surveys. Collectively, the pooled
2006–2010 sample represents 5 % of the U.S. population. Because our analysis is
focused on the New Orleans metropolitan area, the one-year ACS samples from any
given year are too small to sustain the analysis. Taking advantage of the IPUMS-
U.S.A 5-year sample, however, provides us with the necessary sample size. The
pooled samples designed by IPUMS-U.S.A, then, are an excellent resource for
researchers interested in small populations in specific geographic areas.
The sample is restricted to respondents residing in the New Orleans metropolitan
statistical area (MSA) who are between the ages of 18 and 65, not enrolled in
school, and employed. We classify respondents as construction workers if they
reported employment in the construction industry. Respondents are categorized into
one of four race/ethnicity/nativity groups: foreign-born Latinos, U.S.-born whites,
U.S.-born blacks, and ‘‘others’’ (please refer to Table 2for the sample sizes of each
group by period). Foreign-born Latinos are respondents born in Mexico, Central
America, South America, or the Caribbean, and the category includes both non-
citizens and naturalized citizens. A majority of the foreign-born Latino sample is
made up of Hondurans (39 %) and Mexicans (25 %), but there also Brazilians,
Salvadorans, Nicaraguans, and Guatemalans. U.S.-born whites are non-Hispanic
Latino Immigrants and the New Orleans Construction Industry
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respondents born in the United States who report their race as white. U.S.-born
blacks are non-Hispanic respondents born in the United States who report their race
as black. The ‘‘other’’ category comprises all respondents who do not fall into the
three previous categories. This includes U.S.-born Latinos, U.S.-born Asians or
Pacific Islanders, multi-racial U.S.-born respondents, non-Hispanic white immi-
grants, non-Hispanic black immigrants, etc. Because the ‘‘other’’ category
comprises only 5 % of construction workers, we do not have the sample size to
examine each of these groups individually; however, we include these workers in
the analysis in order to account for changes occurring across the entire construction
industry.
We analyze two dependent variables. The first dependent variable indicates
whether the respondent is employed in the construction industry; the variable is
dichotomous and is coded 1 if the respondent is employed in the construction
industry (as classified by the industry variable in the 2000 Census and the
2006–2010 ACS), and 0 otherwise. The second dependent variable applies only to
respondents who report employment in the construction industry and is an indicator
of the position of workers in the occupational-wage structure of the New Orleans
construction industry. To construct this variable, we follow a method developed by
Wright and Dwyer (2003), who used a similar classification of occupations to
examine patterns of job growth in the United States from 1960 through the 1990s.
First, we calculated hourly wages for all employed workers in the construction
industry in both the 2000 and 2006–2010 periods. To do this, we divided each
respondent’s yearly income from their job by the number of weeks worked to
calculate a weekly average wage; then, we divided the weekly wage by the number
of hours worked per week to calculate the respondent’s hourly wage rate. These
hourly wages were then adjusted for inflation and converted to constant 2010 dollars
and top coded at $250 an hour. For both the 2000 and 2006–2010 periods, we then
calculated the median hourly wage for each occupation within the construction
industry. Then, these median hourly wages for each occupation were used to
construct occupational-wage quintiles, where occupations with the lowest median
wages are located in the first quintile and construction occupations with the highest
median wages are located in the fifth quintile.
Table 1provides the wage cutoffs for each occupational-wage quintile by year.
For example, construction occupations with a median hourly wage of $12.29 or less
in the 2000 period are designated as first quintile occupations. Construction
occupations with hourly median wages ranging from $12.30 to $14.75 in the 2000
period fall into the second occupational-wage quintile, and so on. Based on their
occupation, then, workers in the New Orleans construction industry are categorized
into occupational-wage quintiles for both the 2000 and 2006–2010 periods, which
provide a measure of where a respondent is positioned within the sector’s
occupational hierarchy. The occupational-wage quintile is treated as a nominal
categorical variable ranging from 1 to 5 (corresponding to the particular
occupational-wage quintile of the respondent).
Our multivariate models include a number of independent variables. To account
for race/ethnicity/nativity, we include three dichotomous variables representing
foreign-born Latinos, U.S.-born blacks, and others, with U.S.-born non-Hispanic
B. Sisk, C. L. Bankston III
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whites as the reference category; these are coded 1 if the respondent belongs to the
race/ethnicity/nativity category, and 0 otherwise. A dichotomous variable differen-
tiates between the pre- and post-Katrina periods, and is coded 1 for the 2006–2010
period and 0 for the 2000 period. Dichotomous variables for educational attainment
include a variable coded 1 if the respondent has less than a high school degree and 0
otherwise, a variable coded 1 if the respondent has a high school diploma and 0
otherwise; the reference group is respondents with more than a high school degree.
We include controls for gender, age and age-squared, marital status, being the
household head, having a child under the age of 5 in the family, and residing in the
central city of the metro area.
Methods
We first provide a descriptive overview of our sample in Table 2. Then, we examine
how the demographics of the construction industry changed across time periods in
Table 3, and then explore shifts in the distribution of the occupational-wage quintile
in Table 4. The multivariate portion of the analysis first uses a logistic regression
model to predict being employed in the construction industry, where the sample
includes all respondents who report being employed in any industry (displayed in
Table 5). Table displays results from a second multivariate model, which is a
multinomial logistic regression predicting the occupational-wage quintile of
construction workers; for this model, the sample is restricted to only respondents
employed in the construction industry. In both multivariate models, we introduce
interactions between race/ethnicity/nativity and period to account for differential
Table 1 Hourly wage range ($2010) and two most common occupations by New Orleans MSA con-
struction industry occupational-wage quintile, 2000 and 2006–2010
Occupational-
wage quintile
2000 2006–2010
Hourly wage
range
Two most common
occupations
Hourly wage
range
Two most common
occupations
1st $0.00–12.29 Construction laborers;
roofers and slaters
$0.00–12.09 Construction laborers;
painters, construction,
and maintenance
2nd $12.30–14.75 Painters, construction,
and maintenance;
equipment operators
$12.10–14.03 Drywall installers;
roofers and slaters
3rd $14.76–16.22 Carpenters; masons,
tilers, and carpet
installers
$14.04–16.86 Carpenters; heating, air
conditioning, and
refrigeration
4th $16.23–21.83 Plumbers and pipefitters;
electricians
$16.87–23.51 Electricians; plumbers
and pipe fitters
5th $21.84–250.00 Managers and
administrators;
supervisors
$23.52–250.00 Managers and
administrators;
supervisors
Data IPUMS-U.S.A. 2000 (U.S. Census) and 2006–2010 (pooled 5-year ACS file).
Note: Wages adjusted for inflation and converted to 2010 constant dollars
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Table 2 Means and standard deviations of variables used in analysis, 2000 and 2006–2010
Variable Total FB Latinos USB Whites USB Blacks Others
2000 2006–2010 2000 2006–2010 2000 2006–2010 2000 2006–2010 2000 2006–2010
Demographics
Female 0.10 (0.30) 0.11 (0.32) 0.08 (0.28) 0.05 (0.22) 0.11 (0.32) 0.14 (0.35) 0.06 (0.24) 0.07 (0.25) 0.12 (0.32) 0.12 (0.32)
Age 39.7 (11.4) 40.9* (11.9) 36.1 (11.5) 34.6 (10.1) 39.7 (11.4) 42.2* (11.8) 40.7 (11.4) 42.5 (12.2) 38.3 (11.8) 39.6 (11.3)
Married 0.58 (0.49) 0.53* (0.50) 0.60 (0.49) 0.44* (0.50) 0.61 (0.49) 0.58 (0.49) 0.51 (0.50) 0.46 (0.50) 0.51 (0.50) 0.48 (0.50)
Household head 0.64 (0.48) 0.53* (0.50) 0.55 (0.50) 0.45 (0.50) 0.67 (0.47) 0.57* (0.49) 0.59 (0.49) 0.45* (0.50) 0.64 (0.48) 0.51 (0.50)
Has child under age of 5 0.12 (0.33) 0.12 (0.32) 0.16 (0.37) 0.15 (0.36) 0.12 (0.33) 0.12 (0.32) 0.12 (0.32) 0.097 (0.30) 0.10 (0.31) 0.099 (0.30)
Resides in Central City 0.22 (0.42) 0.13* (0.33) 0.21 (0.41) 0.17 (0.38) 0.10 (0.30) 0.097 (0.30) 0.54 (0.50) 0.21* (0.40) 0.25 (0.43) 0.12* (0.32)
Education level
Less than HS Degree 0.23 (0.42) 0.18* (0.39) 0.39 (0.49) 0.34 (0.47) 0.20 (0.40) 0.14* (0.34) 0.26 (0.44) 0.20 (0.40) 0.25 (0.43) 0.16 (0.37)
HS Degree 0.49 (0.50) 0.48 (0.50) 0.43 (0.50) 0.49 (0.50) 0.50 (0.50) 0.47 (0.50) 0.51 (0.50) 0.48 (0.50) 0.43 (0.50) 0.48 (0.50)
More than HS Degree 0.28 (0.45) 0.34* (0.47) 0.18 (0.39) 0.16 (0.37) 0.30 (0.46) 0.39* (0.49) 0.23 (0.42) 0.32* (0.47) 0.32 (0.47) 0.36 (0.48)
N1,539 1,667 98 261 985 1,018 379 277 77 111
Data IPUMS-U.S.A. 2000 (U.S. Census) and 2006-2010 (pooled 5-year ACS file)
Note: Standard deviations provided in parentheses; sample restricted to workers employed in the construction industry, ages 18–65, not enrolled in school, and residing in
the New Orleans metropolitan area; ‘‘other’’ refers to any worker not categorized as foreign-born Latino (FB Latinos), U.S.-born white (USB Whites), or U.S.-born black
(USB Black)
* Statistically significant (p\0.05, two-tailed test) within-group difference in mean across time periods
B. Sisk, C. L. Bankston III
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effects of time across the race/ethnicity/nativity groups. Finally, using the results
from the multinomial logistic regression model, we generate predicted probabilities
to demonstrate the changes in the occupational-wage quintile distribution of the
New Orleans construction labor force across time periods.
Results
Descriptive Results
We first document the extent to which Hurricane Katrina created a demand for
construction workers in New Orleans. Figure 1displays the employment data from
the U.S. Bureau of Labor Statistics’ Quarterly Census of Employment and Wages
(QCEW) for the New Orleans metropolitan area from 2000 to 2010.
Figure 1indicates that the number of employed workers in New Orleans
decreased sharply as a result of Hurricane Katrina, as employment fell from 500,000
in the pre-storm period to a low of 350,000 in the 4th quarter of 2005 immediately
after the storm. Even though the New Orleans economy recovered somewhat in the
following years, by 2010, there were still 80,000 fewer jobs in the New Orleans
metropolitan area compared to the pre-storm period. However, construction
employment remained consistent, as there were around 30,000 construction workers
accounted for by the QCEW in both the pre- and post-storm periods. Moreover, the
relative size of the construction industry grew in the post-storm period as the overall
economy shrank; while construction jobs accounted for 6 % of all jobs in 2000, that
share grew to 8.5 % by 2006 and remained above 7 % in 2010. The data provided in
Table 3 Number of workers employed in New Orleans MSA construction industry, 2000 and
2006–2010
Employment Ratio of employment relative
to USB whites
2000 2006–2010 2000 2006–2010
Panel A. All workers
FB Latinos 2,226 9,600 0.10 0.44
USB Whites 22,170 21,898 – –
USB Blacks 8,918 8,657 0.40 0.40
Others 1,810 2,628 0.08 0.12
Panel B. Workers with less than HS
FB Latinos 820 3,607 0.19 1.12
USB Whites 4,335 3,220 – –
USB Blacks 2,288 1,584 0.53 0.49
Others 431 460 0.10 0.14
Data IPUMS-U.S.A. 2000 (U.S. Census) and 2006–2010 (pooled 5-year ACS file)
Note: Weighted data shown; ratio is the employment for the respective group divided by the employment
of USB Whites for each period
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Fig. 1indicate that even as Hurricane Katrina dramatically reduced the number of
jobs available in the New Orleans metropolitan area, there was a strong and
persistent demand for construction labor in the post-Katrina period.
Table 2provides a descriptive portrait of our sample of New Orleans construction
workers across the two time periods. Although our data do not allow us to directly
observe if and how the selective return migration of construction workers in the post-
storm period affects our findings, Table 2provides insight into the extent to which
patterns of return influenced the composition of the industry over time.
Comparing the overall demographic characteristics of construction workers
across the two periods, workers in the post-storm period were older, less likely to be
married, less likely to reside in the central city, and were less likely to be high
school dropouts relative to the pre-storm period. For Latino immigrants, the only
significant change across the two periods was a decrease in the percent of workers
that were married, which fell from 60 to 44 %; this is consistent with Fussell’s
(2009a,b) description of the newly arrived workers as having less social and family
attachments. Latino immigrants were a low-skilled group in both periods, with
Table 4 Percent Change in New Orleans MSA Construction Industry Employment by Occupational-
Wage Quintile, 2000 and 2006–2010
Occupational–Wage quintile
1 2 3 4 5 Total
Total
2000 7,123 4,636 8,973 6,550 7,718 35,000
2006–2010 12,636 2,717 12,133 6,450 8,791 42,727
% Change 77.4 -41.4 35.2 -1.5 13.9 22.1
FB Latinos
2000 600 404 746 312 164 2,226
2006–2010 4,903 1,103 2,884 97 587 9,574
% Change 717.2 173.0 286.6 -68.9 257.9 330.1
USB Whites
2000 3,180 2,248 6,270 4,462 5,930 22,090
2006–2010 3,941 1,106 6,347 3,958 6,516 21,868
% Change 23.9 –50.8 1.2 -11.3 9.9 -1.0
USB Blacks
2000 2,961 1,808 1,457 1,424 1,224 8,874
2006–2010 2,907 415 2,225 2,004 1,106 8,657
% Change -1.8 -77.0 52.7 40.7 -9.6 -2.4
Others
2000 382 176 500 352 400 1,810
2006–2010 885 93 677 391 582 2,628
% Change 131.7 -47.2 35.4 11.1 45.5 45.2
Data IPUMS-U.S.A. 2000 (U.S. Census) and 2006–2010 (pooled 5-year ACS file)
Note: Weighted data shown; percent change refers to percent change across periods from 2000 to
2006–2010
B. Sisk, C. L. Bankston III
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roughly a third of the immigrant sample lacking a high school degree. In the case of
the U.S.-born samples, it does appear that the post-storm workers were more
educated than the pre-storm workers. Compared to before the storm, U.S.-born
whites in the post-Katrina period were more likely to have education beyond a high
school degree and less likely to be high school dropouts, and the percentage of U.S.-
born black workers with more than a high school degree increased from 23 to 32 %
across the time periods. Overall, then, the post-storm construction industry labor
force was somewhat more educated than before, although the demographic
composition of the Latino workers remained stable over time.
Table 3shows the weighted total of workers in the construction industry in the 2000
and 2006–2010 time periods, as well as the ratio of each race/ethnicity/nativity group
to U.S.-born whites. Panel A indicates that the overall Latino immigrant construction
workforce surged from 2,200 to 9,600 from the pre-storm to post-storm periods, while
the number of workers in the white, black, and other categories remained stable.
Further, while the ratio of black to white workers remained steady at 0.40, we find that,
Table 5 Selected results of logistic regression models predicting employment in the New Orleans MSA
construction industry
Variable Model 1 Model 2
b
Coef. SE
a
Coef. SE
a
Year
2000 (ref.) ––––
2006–2010 0.217** 0.042 0.218** 0.051
Race/ethnicity/nativity
FB Latinos 0.932** 0.081 0.621** 0.142
USB Whites (ref.) – – – –
USB Blacks -0.301** 0.054 -0.196** 0.071
Others -0.236** 0.089 -0.302* 0.134
Year * race/ethnicity/nativity
FB Latinos * 2006–2010 – – 0.477** 0.175
USB Whites * 2006–2010 (ref.) – – – –
USB Blacks * 2006–2010 – – -0.225* 0.102
Others * 2006–2010 0.123 0.178
Constant -2.688** 0.235 -2.693** 0.236
N37,518 37,518
Pseudo R
2
0.151 0.152
Log likelihood -9,292.31 -9,282.85
v
2
2,093.40** 2,101.69**
Note: Models also include controls for level of education, age/age-squared, gender, marital status, edu-
cation, being the household head, having children under the age of 5, and central city residence
** p\0.01; * p\0.05 (two-tailed tests)
a
Robust standard errors adjust for within-household cluster correlation
b
Likelihood ratio test indicates interactions in Model 2 significantly (p\0.001) increase explained
variance from Model 1
Latino Immigrants and the New Orleans Construction Industry
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consistent with our finding that the overall number of Latino immigrant workers
increased, the ratio of foreign-born Latinos to U.S.-born whites increased from 0.10 to
0.44. This finding is accentuated in Panel B, which provides results for only those with
less than high school. Here, we find that the black–white and other–white ratios did not
experience much change across the two time periods, while the ratio of foreign-born
Latino to white workers increased from 0.19 to 1.12. In summary, the findings in
Table 3indicate that the relative size of other groups of workers remained the same
across periods, and that the post-storm period was characterized by the addition of a
large number of low-skilled, Latino immigrant workers.
Here, we return to Table 1, which displays the wage cutoffs and two most
common occupations for the construction industry occupational-wage quintiles
across the time periods. The wage cutoffs for the occupational quintiles remain
stable across periods, indicating that the wage structure of the industry was
relatively unchanged even as the sector was undergoing a large increase in low-
skilled workers. This continuity in the wage structure of the industry is also visible
in the most common occupations, as occupations are similarly sorted across
quintiles in each period. In both periods, managers and skilled trades like plumbers
and electricians are concentrated at the high end of the wage distribution, while less-
skilled occupations like painters and maintenance workers and construction laborers
are concentrated in the 1st and 2nd quintiles.
Table 4shows the overall distribution of construction workers by occupational-
wage quintile and the percent change in that quintile across periods by the race/
ethnicity/nativity group. Note that the total number of workers in the construction
industry in the 2000 period is, at 35,000, is very similar to the estimate of 32,000
provided by the Quarterly Census of Employment and Wages provided in Fig. 1;
5%
6%
7%
8%
9%
0
100,000
200,000
300,000
400,000
500,000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Percent Construction
Number Employed
Construction Industry All Other Industries % Constructi on (right axis)
Data: Bureau of Labor Statistics, Quarterly Ce nsus of Employment and Wages, New Orleans Metropolitan Statistical Area (MSA), 2000-2010
Note: Shaded region indicates post-Hurricane K atrina period (Katrina occurred during midway through the 3
rd
quarter of 2005); quarterly data
displayed; gray bars display number of w orkers employed in New Orleans MSA construction industry; white bars display number of workers
employed in all New Orleans MSA jobs except construction; dot ted black line displays the share of all employment in the construc tion industry in
each
q
uarter
Post-Katrina Period
Fig. 1 New Orleans MSA quarterly employment for construction industry and all other industries, and
construction industry employment as percent of total employment: 2000–2010
B. Sisk, C. L. Bankston III
123
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however, in the post-Katrina period, the American Community Survey indicates that
total employment in the construction industry increased by 22 % to 42,000, while
the QCEW estimates indicate that employment in the industry remained constant
from 2000 to 2010. We suspect that this discrepancy is due to differences in survey
design; the QCEW collects information from employer payroll reports, while the
ACS is an individual-level, household survey. Given the off-the-books nature of
reconstruction work following Katrina (Donato et al. 2007; Vinck et al. 2009), we
posit that the QCEW missed a subset of informal construction workers captured by
the ACS.
Table 4indicates that job growth in the New Orleans construction industry across
periods was heavily concentrated in the bottom end of the sector’s wage
distribution. Foreign-born Latinos, in particular, experienced a 717 % increase in
the number of workers in the lowest-paying jobs in the construction industry, as the
number of Latino immigrants in the bottom quintile increased from 600 to nearly
5,000; this reflects the findings from Table 3, which indicated that there was an
increased presence of immigrants without a high school degree following the storm.
In the case of U.S.-born blacks and whites, their occupational-wage quintile
distribution remained quite stable across the two periods. The results in Table 4
indicate that, after the hurricane, Latino immigrants entered the construction labor
force at newly created positions in the reconstruction effort that were overwhelm-
ingly located at the bottom of the labor queue; this is consistent with Card’s (2005)
argument that immigrant and U.S.-born workers occupy different structural roles in
the U.S. economy, as Latino immigrants in post-Katrina New Orleans filled the low-
paying and riskier jobs created by the reconstruction effort (Fletcher et al. 2006).
Collectively, Tables 1,3, and 4provide evidence that the hurricane reconstruction
effort in New Orleans did not reduce the presence of U.S.-born workers in the sector
or place downward pressure on the industry’s wage structure. It did, however, create
more jobs at the lower end of the wage distribution that were disproportionately
filled by Latino immigrant labor.
Multivariate Results
Table 5provides the results of logistic regression models predicting employment in
the New Orleans metropolitan area construction industry. We find that workers were
much more likely to work in the construction sector in the post-storm period, which
reflects our descriptive findings that the construction industry experienced
substantial growth across time periods. This increased likelihood of construction
work is present in Model 1 before we introduce the interactions between race/
ethnicity/nativity and period in Model 2. A likelihood ratio test indicates that Model
2 significantly increases the amount of variance explained compared to Model 1
(p\0.001), which confirms that there are statistically significant changes by group
in the probability of employment in the construction industry across time periods.
To illustrate these changes across time periods, we now turn to Fig. 2.
Figure 2displays the predicted probability of employment in the construction
industry generated from Model 2 in Table 5holding all other variables at their
means. We find that the probability of foreign-born Latinos working in construction
Latino Immigrants and the New Orleans Construction Industry
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nearly doubled across the two periods. Before Katrina, a Latino immigrant had an
8.5 % chance of employment in the construction industry; after the storm, this
probability had increased to 15.7 %, and this change in probabilities is statistically
significant (p\0.05, two-tailed test). While the probability of construction
employment for U.S.-born whites and those in the other category increased slightly
(to 6 and 5 %, respectively), the propensity of U.S.-born blacks to work in
construction remained at 4 %. While our data do not allow us to evaluate whether
the presence of immigrants in the industry reduced the likelihood that U.S.-born
whites and blacks would return to New Orleans in order to seek construction work,
our findings indicate that the relative presence of other groups of workers in the
industry was not reduced in the post-Katrina period even as many more Latino
immigrants were employed in the sector.
Furthermore, the findings in Fig. 2indicate that the expansion of the construction
industry in the post-Katrina period was largely associated with a Latino immigrant
niche emerging in New Orleans. While Latino immigrants were slightly overrepre-
sented in the construction industry prior to Katrina, the heavy concentration of
immigrants in the sector after the storm—combined with the stability of the presence
of the other racial/ethnic/nativity groups—indicates that Hurricane Katrina had the
effect of creating an immigrant employment niche in the New Orleans construction
industry. We now turn to additional multivariate results that examine the occupational
position of workers in the construction industry across time periods.
Table 6displays the results from a multinomial logistic regression model that
predicts the occupational wage of New Orleans construction industry workers. Like
Model 2 in Table 5, the model displayed in Table 6includes interactions between
period and race/ethnicity/nativity to capture differential effects of time period across
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
FB Latinos* USB Whites* USB Blacks Others*
2000
2006-2010
* denotes statistically significant within-group c hange from the 2000 to 2006-2010
period in the predicted proba bility of worki ng in construction industry (p<.05,
two-tailed test)
Note: Probabilities generated from logistic regression Mode l 2 in Table 5 that
contains interactions between ra ce/ethnicity/nativity and year, as well as controls
for demo
g
ra
p
hic and human ca
p
ital characteristics
Fig. 2 Predicted probability of employment in New Orleans MSA construction industry, 2000 and
2006–2010
B. Sisk, C. L. Bankston III
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Table 6 Selected results of multinomial logistic regression model predicting occupational-wage quintile in the New Orleans MSA construction industry
Variable 1st Quintile 2nd Quintile 3rd Quintile 4th Quintile 5th Quintile
Coef. SE
a
Coef. SE
a
Coef. SE
a
(base outcome) Coef. SE
a
Year
2000 (Ref.) – – – – – – – – –
2006–2010 0.283 0.159 –0.763** 0.222 0.119 0.138 – 0.223 0.139
Race/ethnicity/nativity
FB Latinos 1.12** 0.373 1.19** 0.452 0.769* 0.373 – -0.467 0.468
USB Whites (Ref.) – – – – – – – – –
USB Blacks 1.04** 0.210 0.911** 0.233 -0.290 0.212 – -
0.680**
0.240
Others 0.308 0.408 0.081 0.484 -0.101 0.375 – -0.099 0.358
Year * race/ethnicity/nativity
FB Latinos * 2006–2010 2.07** 0.604 2.00** 0.702 1.66** 0.610 – 1.66* 0.696
USB Whites * 2006–2010 (Ref.) – – – – – – – – –
USB Blacks * 2006–2010 -
0.763**
0.287 -0.950* 0.418 -0.062 0.288 – -0.226 0.326
Others * 2006–2010 0.338 0.509 0.067 0.717 0.197 0.494 – -0.120 0.492
N3,206
Pseudo R
2
0.105
Log likelihood -
4468.88
v
2
769.01**
Note: Models also include controls for level of education, age/age-squared, gender, marital status, education, being the household head, having children under the age of 5,
and central city residence; likelihood ratio test indicates interactions significantly (p\0.001) increase explained variance from model without interaction effects
** p\0.01; * p\0.05 (two-tailed tests)
a
Robust standard errors adjust for within-household cluster correlation
Latino Immigrants and the New Orleans Construction Industry
123
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groups. Further, a likelihood ratio test indicates that including interaction terms
significantly (p\0.001) increases the amount of variance explained by the model.
We now turn to Fig. 3, which displays the predicted probabilities of employment in
each occupational-wage quintile by race/ethnicity/nativity by period.
Figure 3a–d provides the results for each respective race/ethnicity/nativity group
across periods, holding all other variables at their means. Even prior to the storm, a
Latino immigrant was relatively unlikely to work in the 4th or 5th occupational-
wage quintiles, but this disadvantage was heightened in the post-storm period. For
Latino immigrants, the predicted probability of working in the 1st occupational-
wage quintile increased from 25 to 43 % from the 2000 to 2006–2010 period, and
that change is statistically significant (p\0.05, two-tailed test). The predicted
probability of working in the 2nd, 3rd, and 5th quintiles did not change for Latino
immigrants, but the probability of working in the 4th quintile decreased from 12 to
2%(p\0.05, two-tailed test). Thus, the position of Latino immigrants in the New
Orleans construction industry appears to have deteriorated across periods, as
foreign-born Latinos were even more heavily concentrated in the lowest-paying jobs
at the same time that their presence in the industry was increasing.
For U.S.-born whites (displayed in Fig. 3b), the probability of working in the 2nd
quintile decreased from the pre- to post-Katrina period, but there are no significant
changes for the other quintiles; the comparatively advantaged position of whites,
then, remained stable across time periods. In the case of U.S.-born blacks (displayed
0%
10%
20%
30%
40%
50%
1st 2nd* 3rd* 4th* 5th
1st 2nd* 3rd 4th 5th
0%
10%
20%
30%
40%
50%
1st* 2nd 3rd 4th* 5th
2000
2006-2010
Panel C: USB Blacks
Panel A: FB Latinos Panel B: USB Whites
* denotes statistically significant within-group change from the 2000 to 2006-2010 period in the predicted probability of working in respective
occupational-wage quintile (p<.05, two-tailed test)
Note: Probabilities generated from multinomial logit model (presented in Table 6) that contains interactions between race/ethnicity/nativity and year,
as well as controls for demo
g
raphic and human capital characteristics
1st 2nd 3rd 4th 5th
Panel D: Others
Fig. 3 Predicted probability of occupational-wage quintile in New Orleans MSA construction industry,
2000 and 2006–2010
B. Sisk, C. L. Bankston III
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in Fig. 3c), there is evidence of advancement in the industry, as black construction
workers in the post-Katrina period were less likely to work in the 2nd quintile (down
to 5 from 21 %). Moreover, the predicted probability of blacks working in the 3
rd
and 4th quintiles both increased from 17 to 25 % from before to after the storm.
Overall, then, the position of blacks in the New Orleans construction industry
improved across the two time periods. We find no statistically significant changes in
the predicted probabilities for workers in the ‘‘other’’ category (displayed in
Fig. 3d).
Discussion and Conclusions
Economic studies are inconclusive regarding how immigrants impact U.S.-born
workers (Borjas 2003;Card2005); but, under the assumption that immigrants and
U.S.-born workers are not perfectly substitutable for one another—which seems apt in
the case of post-Katrina New Orleans given the descriptions of the harsh conditions
endured by immigrant workers following the storm (Fletcher et al. 2006; Fussell
2009b)—there is evidence that the presence of immigrants has a small positive effect
on the employment outcomes of the U.S.-born (Peri 2011b). Moreover, while
immigrant niches provide employment opportunities for immigrants that might not
exist otherwise, immigrant niches are also concentrated in low-wage sectors, which
can limit the future mobility of immigrant workers (Model 1993; Waldinger and Der-
Martirosian 2001). While prior studies have examined the implications of Hurricane
Katrina along a number of social and economic dimensions, in this analysis, we
investigate the consequences of a new immigrant labor force attracted by post-storm
economic opportunities for the demographic composition and occupational-wage
structure of the New Orleans construction industry.
Our analysis of IPUMS-U.S.A. data from 2000 and 2006–2010 indicates that,
relative to the pre-storm period, U.S.-born workers were just as likely or more likely
to work in the construction industry after Katrina, even as the number of foreign-
born Latino workers increased precipitously across the two time periods. Further,
our findings indicate that as the number of jobs at the bottom end of the
occupational hierarchy of the construction industry swelled in the post-Katrina
period, the workers that filled those low-paying—and often hazardous (Fletcher
et al. 2006; Vinck et al. 2009)—jobs were overwhelmingly Latino immigrants. The
position of U.S.-born white workers remained in relative stasis across the two
periods, despite the fact that the construction industry was undergoing massive
changes and incorporating a large number of low-skilled workers; further, the
position of blacks in the industry improved over time, as they were more likely to
work in the higher-paying occupations in the post-storm period.
Thus, our analysis indicates that the ‘‘recovery machine’’ in post-Katrina New
Orleans created a new structural demand for low-skill workers, and in so doing,
provided an opportunity for Latino immigrants to enter the metropolitan area’s
construction labor force in numbers not seen previously (Pais and Elliott 2008,
p. 1415). Although the changes we observe in the New Orleans construction industry
are consistent with Waldinger’s (1994) explanation of how immigrant niches emerge
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through labor queues, they also reflect the pessimism expressed by other researchers
regarding the disadvantaged status of many immigrant employment niches (Model
1993). In this case, Latino immigrants entered the New Orleans construction industry
at the very bottom of the sector’s labor queue, while the labor market position of some
U.S.-born workers in the industry has improved.
In line with previous analyses examining the social dimensions of disasters
(Elliott and Pais 2006; Brunsma et al. 2007; Fussell 2009b), we find that Hurricane
Katrina had significant implications for the social and economic contours of the
New Orleans labor market. In so doing, we highlight the extent to which disasters—
like new technologies or changes in labor management—can serve as a mechanism
of industrial restructuring that produces the conditions for immigrant niches to
emerge. Going forward, future research should explore how structural shifts and
industrial changes shape demand for immigrant workers in other contexts.
Further, although the initial intent of the ‘‘rapid response labor force’’ was not to
remain in New Orleans (Fussell 2009b, p. 458), there is evidence that settlement is
indeed occurring. An article from the New York Times in December of 2006, under
the headline ‘‘Katrina Begets a Baby Boom by Immigrants,’’ describes the
unexpected and unprecedented rise in births to Latino immigrant women in New
Orleans following the hurricane, suggesting many of the immigrant reconstruction
workers were accompanied by families (Porter 2006). Further, using data from the
U.S. Census Bureau, Ortiz and Plyer (2012) find that the percent of Latinos of the
New Orleans metropolitan area nearly doubled from 4.4 to 8 % from 2000 to 2011.
If this growth in the Latino population continues, New Orleans could join other
metropolitan areas in the southern United States as a new immigrant destination
(Singer 2004). Yet, the fact that the post-hurricane period has reinforced the
disadvantaged status of foreign-born construction workers raises questions about the
future prospects of socioeconomic mobility for Latino immigrants in New Orleans.
Future research, then, should continue to track the labor market outcomes of
immigrants in New Orleans and other emerging immigrant destinations.
One possible limitation to our analysis here is that Hispanics and blacks
experience a higher undercount rate than the general population in the U.S. Census
and the American Community Survey (U.S. Census Bureau 2000; Lowenthal 2006).
The tendency for the American Community Survey to undercount Hispanics, in
particular, may have been exacerbated immediately after Hurricane Katrina in New
Orleans, given that many of the foreign-born workers in the post-storm period were
newcomers to the metropolitan area and a substantial portion were unauthorized
immigrants (Fletcher et al. 2006; Fussell 2009b). However, this is likely mitigated
given that we use data spanning from 2006 to 2010 to represent our post-Katrina
period; in so doing, we capture not only the initial surge in immigrant construction
workers in New Orleans immediately after the storm but also the beginning of the
settlement process.
Further, we are also limited by our data in that, although previous research
indicates that Latino immigrants were often the victims of wage theft at the hands of
employers in post-Katrina New Orleans, we are unable to measure this type of labor
market disadvantage. Given estimates that nearly 80 % of Latino immigrant
reconstruction workers experienced wage theft during their time working in New
B. Sisk, C. L. Bankston III
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Orleans, it is possible that we are underestimating the economic marginalization
experienced by these workers after the storm (Trujillo-Paga
´n2012; Warren
forthcoming).
Lastly, although our analysis is limited in that it only examines a single industry
in one metropolitan area, it has important implications for the debate regarding the
effects of immigrants on U.S.-born workers. In this instance, the old adage that
‘‘immigrants do the jobs that Americans won’t do’’ is reflected in our findings, as
immigrants provided a crucial labor force doing hard and hazardous work at a time
when New Orleans urgently needed workers (Fletcher et al. 2006; Fussell 2007).
Thus, the case of foreign-born Latino construction workers in post-Katrina New
Orleans is yet another illustration of immigrants contributing to the social and
economic vitality of the United States.
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