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The Role of Nongovernmental Activities
in Immigration Studies
Many government agencies and organizations produce data about
immigration, as detailed in the two preceding chapters. These data
reflect a large, cumbersome, and poorly coordinated official immigration
statistics "system." In addition to the government data, however, many
unofficial data sources exist. Moreover, most of the current analysis of
immigration data is done outside government, by university researchers,
foundations, private firms, and others in the private sector. The
immigration statistics system is thus even larger (and less systematic)
than our discussion has so far indicated.
"Unofficial" data consist mainly of those collected by individual
researchers and not-for-proĢit institutions or for-profit firms. There
are some grey definitional areas in this classification, however. In
some cases, government agencies finance the collection of data by
nongovernment organizations and individuals: for example, the General
Social Survey is conducted by the National Opinion Research Center with
support from the National Science Foundation, and its data have been used
to compare immigrants with the native-born. Although such programs are
funded by the government, the government usually disclaims responsibility
for the data, so we classify them as unofficial. There are also data
collected by foreign governments or quasi-governmental agencies, such as
the United Nations High Commission for Refugees. These data, although
official in some contexts, are unofficial as they are used within the
United States.
There are large numbers of small-scale data collection activities in
the area of immigration carried out by individual researchers,
substantial numbers of larger-scale activities carried out by
institutions and companies, and large-scale operations carried out by
foreign governments and international organizations. It is beyond the
scope of this study to attempt to review the quality and relevance of all
these unofficial data sets, even for a representative sample of them.
Thus in this chapter we do not attempt to review in detail the
information collected and the collection processes involved. Instead, we
examine what the role of unofficial data should be in an overall system
of immigration statistics: what sorts of data collection are best left
to nongovernmental bodies, and how needed data collection can be
stimulated and financed. A new departure in this chapter is the explicit
discussion of data analysis and its implications for data collection.
101
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Good analysis is an essential link in the chain from raw data to policy
decision and is a topic suitable for this nongovernmental chapter
because, with the exception of the Census Bureau's research activities,
most analysis of migration data is conducted outside government.
DATA PRODUCTION AND ANALYSIS
Data production and data analysis are separate activities, although
analysis may be constrained by the ways in which data are produced, and
collection may be tailored to the intended analysis. Data production
refers to the collection, compilation, coding, and storage of basic data
concerning immigration. Data are generally produced intentionally, but
the intentions of the producer may not coincide with the requirements of
the analyst. To take an example, most of the data collected by the INS
are collected for programmatic and administrative purposes rather than
for policy analysis, but some of them can be used for analytical
purposes, sometimes in ways never dreamt of by those establishing the
collection process.
The production of immigration statistics is very decentralized. As
we have already noted, a number of federal agencies regularly produce
data on immigrants or refugees, either as a primary objective or as a
by-product of their other activities. Furthermore, the states provide at
least some information on vital events occurring to immigrants, refugee
program use, bilingual education, and other topics that vary by state.
Outside government, there is, if anything, even greater diversity and
decentralization. Unofficial data are produced by intensive ethnographic
studies of immigrants and of communities of both origin and destination
of migrants, local surveys and compilations of local data,
reconstructions of historical series from existing but unsystematized
data, and many other collection processes. In addition, as noted, there
are also data from foreign governments and international agencies.
However, data quantity does not compensate for data quality. Existing
nongovernmental data sets are often inadequate in terms of coverage,
validity, and reliability of the data they contain, or because they are
impossible to compare or to integrate with other official or unofficial
data. Analysts have tried to solve some of these problems with more
creative uses of the existing data, but the root of the problem lies in
the decentralized nature of this nonofficial data production system.
Data analysis includes both primary analysis (that is, to examine the
questions for which the data were collected) and secondary analysis (that
is, to examine questions for which the data are relevant, though not the
purpose for which they were collected). Though data are generally
subjected to primary analysis, secondary analysis is even more widespread
because of the high cos ts of data collection.
The agenda for analysis is set by current intellectual issues, policy
debates, theoretical developments in one or more of the social sciences,
or simply the curiosity of an investigator. Such studies, usually
published in professional journals, monographs, or the popular press, may
not achieve their full potential impact because their audiences are
specialized along political, interest, or disciplinary lines. To the
public or the policy maker, the resulting debates and controversies,
especially those centering on issues of data adequacy, may seem partisan
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103
or merely arcane. Just as diverse motivations underlie the collection of
data by unofficial sources, so too the analysis of data by unofficial
analysts responds to many goals. A lack of consensus about important
issues among analysts may be a sign not of factionalism, but rather of
healthy diversity.
Primary analyses of official data may be guided by official or
quasi-official perceptions of what is required and of the frequency with
which they are required. The Census Bureau is an example of a
statistical agency that both produces data and publishes analyses of
these data, many at regular intervals, others as occasional papers.
Comparisons of official data sources may occasionally be undertaken to
provide statistical benchmarks. However, analyses of immigration data
under official auspices have been relatively rare. The intellectual
division of labor has allocated this task, often by default, to
indiviudal researchers outside government.
A considerable volume of recent social science research about
immigration has been secondary analysis of official, census-type survey
data, most important the 1960 and 1970 census public-use samples and the
1976 Survey of Income and Education. Reliance on such data, however,
greatly restricts the range of substantive issues that can be addressed
and the analytical approaches that can be pursued. Given the limited
social and economic variables available in census files and the virtual
absence of cultural indicators, it is not surprising that most
immigration studies relying on census data focus on the socioeconomic
characteristics of the foreign-born population, usually differentiated by
national origin and occasionally by period of arrival. Census micro data
encourage the use of individuals or households as units of analysis, but
analysis by aggregates such as area of residence could portray the macro
dimensions of social phenomena. Multilevel analyses combining person and
place variables are less common, but not entirely absent from the
literature. The extensive reliance of researchers on official data is
evident in the studies noted in the major bibliographies on immigration
(see Appendix F.), although the coverage of small-scale and ethnographic
studies by the bibliographies is not entirely complete.
It can thus be seen that the analysis of immigration data has been
profoundly affected by the collection of data. Researchers face the
choice of either collecting their own data, which for reasons of cost
will be restricted in general to surveys collecting extensive information
from small numbers of people, or using official data generally collected
for other purposes and thus of limited analytical potential. It should
be noted, however, that the dearth of quality research studies in the
field of immigration should not be blamed entirely on data deficiencies.
Even the limited data available from official sources offer a potential
for analytical study that has not been fully exploited. Even the
analysis of large data sets is expensive, and funding for immigration
research in the recent past has not been sufficient to support extensive
analysis or to attract research analysts to the immigration field.
TYPES OF UNOFFICIAL DATA
An important distinction must be made between studies based on
statistical data (e.g., social surveys) and those based on nonstatistical
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data (e.g., ethnographic, archival, and historical material). The data
collection processes involved should be viewed as dif ferent parts of a
continuum, from the quick, extensive (in terms of population coverage)
yet limited ~ in terms of topics covered and questionnaire length)
collection process of the traditional survey to the slow, limited (in
terms of population coverage) and intensive ~ in terms of interview length
and topics covered) collection process of the ethnographic study. The
survey typically collects information about respondent status, either at
the time of the survey ~ age, marriage, income, and education, for
example) or at some specified earlier time (place of residence five years
before the survey, for example) for a statistically representative sample
of the study population. The ethnographic survey, on the other hand,
collects a wealth of additional info`Q.ation about opinions, motivations,
and community context, often through the use of open-ended questions, but
the survey population is generally selected purposively and cannot be
taken as representative of any larger population of interest. Each data
type has its relative strengths. However, the potential for
complementarily among various types of unof f icia 1 data is af fee ted by the
problems that arise when combining data from dif ferent sources and by the
analytical approaches that have been used to address specific questions.
Studies based on both ethnographic and survey data have generated
useful insights into immigration as a social phenomenon. Both survey and
ethnographic data sources can be tailored to specific substantive
questions about immigration as a social process whose causes and
consequences extend from individuals to communities of origin and
destination. Their scope, depth, and the generalizability of the
information differ considerably, however, as a result of the qualitative
nature of ethnographic data and the quantitative.nature of survey data,
as well as the manner of solic iting, recording, and coding informal ion .
Ethnographic data benefit from greater respondent flexibility but often
at the cost of generalizability; survey data often sacrifice the richness
of open-ended responses to facilitate coding and to obtain a standardized
data set.
Ethnographic Data
The main strengths of ethnographic data lie in their depth and
comprehensive coverage of an immigrant community or a specific aspect of
the immigration process. Ethnographic data provide a great deal more
information about social processes and interactions that structure
immigration flows than do conventional survey data. Of course, the
comprehensiveness of information produced depends on the amount of time
spent in the field and the number of field sites. Ethnographic data are
generally not exchangeable between analysts, so they are not easily
subjected to secondary analysis, integration with other data sets , or
verif iciest ion except through restudy by dif ferent invest igators . However,
the ethnographic practice of soliciting information from multiple
sources--participant observation, key community informants, and
respondent interviews--provides some basis for internal data consistency
checks and for response validation.
The major drawbacks of ethnographic information are the limits on
exchange of information among researchers, the limited generalizability
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of the results beyond the population or locality of study, and the
difficulty of subjecting the data to rigorous hypothesis testing using
multivariate statistical techniques. The major advantages of
ethnographic data are the depth of study they permit into the reasons for
and process of migration; survey data on the social and economic
characteristics of immigrants can provide only a partial, and possibly
misleading, view of such reasons and processes.
Survey Data
The strengths of unofficial survey data complement the weaknesses of
ethnographic data and vice versa. The primary strengths of unofficial
surveys relative to official sources are their flexibility in selecting
the number and scope of topics to be included and their ability to ask
sensitive questions; relative to ethnographic studies, their strengths
are that the population universe can be clearly and explicitly defined,
that they adhere to statistical standards permitting the evaluation of
possible sampling errors, and that they are amenable to rigorous
empirical analysis. None of these strengths is absolute, for compromises
in scope, representativeness, population coverage, and quantifiability
are imposed by cost and time considerations. Moreover, some aspects of
immigration are difficult to capture using random sampling survey
techniques. The obvious example to date is that of illegal immigration.
Nonrandom sampling methods, such as network samples, whereby one member
of the study population is asked to provide names and addresses of other
members of the population, who are then in turn interviewed and asked to
provide more names, have been used with limited success, but the process
of statistical inference is seriously impaired. (Such samples are
sometimes also called snowball samples.) Other concerns not easily
pursued with survey--or ethnographic--data are the macro-structural
properties of the immigration process, including the changing nature,
direction, and composition of aggregate flows; fortunately, official data
sources are especially well suited to such issues.
Despite the many virtues of survey data for addressing questions
about immigration, these unofficial data sets suffer from several
drawbacks. Most surveys give a one-time static snapshot of social and
economic status that provides only limited information about the process
of arriving at that status. Thus, most cross-sectional surveys of
immigrants are limited in their ability to address questions about
process or to establish clearly causal relationships. The exceptions are
those few surveys that have collected retrospective histories of the
timing of various events, such as migration, employment, and
childbearing. The dating of changes in social and demographic status
permits a more effective study of process, although events in the more
distant past may not be representative of their time period, since the
sample is representative of the present, and event intervals in the
period shortly before the survey may be affected by censoring and
truncation biases.
An alternative to the use of retrospective questions in sample
surveys involves reinterviewing a sample of respondents several times,
for example every six months or every year. This longitudinal, panel
approach may be preferable to that of repeated cross-sections for making
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inferences about process because it permits control for previous events
in a sequence without being subject to major event-dating errors that
al feet life-history reports. However, cost factors have inhibited
individual researchers from undertaking truly longitudinal surveys of
immigrants. Moreover, immigrants often have a high propensity to move,
which usually increases sample attrition and can, over time, impair the
representativeness of the sample. Complexity and cost factors aside, it
is noteworthy that there does not currently exist a nationally
representative longitudinal study of recent immigrants. Longitudinal
studies of the general population do not include a suf ficient number of
immigrants to permit separate analysis even at the aggregate level and
still less for nationality or other subgroups.
The strategy used to define a universe and devise a sampling scheme
may limit the usefulness of multipurpose surveys for studying
immigrants: for example, the General Social Survey includes only the
English-speaking population over age 18. Furthermore, even leaving aside
the special problem of studying the illegal immigrant population, it is.
not obvious how to design a survey to study the determinants and
consequences of migration for the community and country of both origin
and destination. With few exceptions, most sample surveys of immigrants
have defined the universe on the basis of those who actually move across
international boundaries and settle in a specific locality or who cross
at a specific time. Such strategies for limiting the universe are
appropriate for addressing questions about the experiences of immigrants
in the destination country, but these samples limit interpretations of
the causes and consequences of international migration in at least two
important ways. First, by excluding those who decide not to emigrate,
studies based on samples of individuals who have migrated across
international boundaries distort our understanding of the determinants of
migration and lead to potentially erroneous conclusions about the nature
of migrant selectivity. Second, universes defined by time and locality,
especially the latter, exclude an unknown number of immigrants who may
have returned to their place of origin or moved on to another
destination. This latter problem can be partly resolved by inquiring
about past migration history, intended moves, and the existence of
friends and relatives in other localities, but it introduces selection
problems of unknown magnitude in the statistical analysis of the survey
data and may ultimately distort conclusions about the individual,
familial, and locational structure of aggregate flows. Survey design may
al so at fee t the potent ial to study impact, since it is c [early neces sary
in such a case to have information not only on migrants themselves but
also on the rest of the community and on other communities.
To summarize, the main advantages of survey data reside in their
generalizability, their amenability to rigorous statistical analysis, and
their high degree of exchangeability among researchers. In practice,
however, the access to and distribution of data from specialized surveys
about immigrants is not extensive, and there is no central clearinghouse
that receives, classifies, and distributes data sets containing
information about immigrants to interested researchers. The
generalizability, substantive content, and amenability of unofficial
surveys to rigorous secondary analyses of immigration issues varies with
the objectives and design of the original data collection. Although
cross-sectional surveys can be designed to deal with the timing of events
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through the use of retrospective questions or through repeated surveys,
and longitudinal surveys can be designed to examine processes, each
strategy poses different problems of cost, sample attrition, recall
error, and analytical limitation.
Immigrant Case Records
One relatively unexplored avenue for immigrant studies is the use of case
records collected by private voluntary agencies that assist immigrants or
refugees. These files provide a basis for following immigrants for a
period of time and for noting their adaptation to life in the United
States. Assuming that the necessary standards for confidentiality could
be met, such data would offer many of the advantages of a longitudinal
survey at a fraction of the cost.
Potential Complementarities Among Unofficial Data Sources
Although there are a number of possible combinations of data types, three
particular combinations are promising for research. We term these three
combinations multilevel studies, multimethod studies, and multi-data-set
validations. A multilevel study uses combinations of data aggregated at
different levels to establish a finding: for example, individual or
household data might be used to confirm or enhance conclusions based on
aggregate data. A multimethod study combines fundamentally different
types of data: an example is the way ethnographic and sample survey data
are used to complement each other in the study of Mexican migration to
California undertaken by Massey (see Appendix C). Such studies
frequently combine official and unofficial data, exploiting the relative
strengths of each. The third category involves the cross-validation of a
finding using different data sets that cover the same population or
variable of interest. For example, U.S. estimates of immigration from a
country might be compared with that country's estimated emigration to the
United States. Such studies also typical ly require combinations of
official and unof ficial data. Even given current data production
systems, these strategies appear underexploited and offer scope for
useful research effort.
OBSTACLES TO DATA ANALYSIS
The bulk of analysis of immigration data, whether collected under
official or unofficial auspices, is done by the private sector, but
accessible data can be analyzed. Except for the U.S. Census Bureau,
agencies that produce official data either have been largely unaware of
or unresponsive to the data needs of the research community. Problems of
accessibility and ease of use represent an obstacle to data analysis.
Many data sources remain inaccessible for reasons that cannot be
explained by privacy or confidentiality concerns alone. Even for the
data that are accessible, documentation is often sketchy or unavailable.
Coding protocols are not explained, so that the effects of coding
practices that differ from one source to another, or even within sources,
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may be overlooked. With better access to existing data, the research
community could produce more relevant and higher-quality analyses. The
existence of such analyses is essential to better policy formation, since
data per se, in the absence of any examination of implications, give no
guidance for policy. The analysis is impossible without the data, but
the data, to be useful, must be analyzed.
Greater interaction with ache research community would provide a
mechanism for improving the policy relevance of of ficially produced
data. Given an understanding of analytical needs, data could be produced
in more convenient forms . The expert advisory panel and the fellows
program, recommended in Chapter 4, would provide the INS with an
important source of expertise and feedback in improving its data
collection. Contact with users need not be expensive and does not
necessarily require the establishment of a permanent users service.
Annual meetings of the professional associations of the research
disciplines offer an opportunity to disseminate information about data
products and services. The foundations and journals active in the
immigration field can serve a similar function. Regular INS publications
could also provide information about data availability and changes in
data produc t ion prac tices .
A second obstacle to analysis is the shortage of funding for
immigration studies. This shortage has been particularly severe for
unofficial data collection, which is generally expensive, but has also
restricted the analysis of official data and professional interest in the
field. Skepticism about data quality may have made immigration studies
less attractive to such major grant-giving agencies as the National
Science Foundation or the National Institutes of Health, even though data
evaluation alone would represent a worthwhile outcome. Once again, the
problems of data production haunt data analysis, although indirectly in
this case. It should be noted, however, that the National Institutes of
Health, through the National Institute of Child Health and Human
Development, have been making efforts recently to encourage the
submission of research proposals in the immigration field and to increase
the funding allotted to it.
The INS also could support a program for immigration studies
channeled through the conventional funding agencies, which would apply
their usual peer review and grant procedures. This approach would
provide a mechanism for the contract research program already recommended
in Chapter 4. The Office of Refugee Resettlement and other agencies
concerned with refugees might enter into similar agreements to support
research on refugees.
SUMM,9RY AND RECOMMENDATIONS
Unofficial data complement official data in important ways. Furthermore,
most studies of immigration are now carried out by nongovernment
researchers. However, problems of accessibility and quality of official
data, and shortage of funds for unofficial data collection and analysis
in general have severely limited the contribution of the nongovernment
sector to the policy formation process.
To improve this contribution, the panel recommends:
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o Insofar as is feasible, official government data on immigrants and
refugees should be made available to researchers outside the government;
o The proposed Division of Immigration Statistics in the INS should
establish and maintain contacts with the research community and keep it
informed about the availability of data and changes in procedures. This
recommendation also applies to all other agencies that produce
immigrat ion data; and
o Government agencies that provide funds for research should be
encouraged to stimulate the submission of research proposals in the
immigration field and to give particular attention to sound proposals for
relevant research studies in the area.
Representative terms from entire chapter:
official data
