CREAT: Census Research Exploration and Analysis Tool

The Relationship of Personal and Neighborhood Characteristics to Immigrant Fertility

August 2002

Working Paper Number:

CES-02-20

Abstract

We find that fertility varies by immigrant generation, with significant declines between the first and subsequent generations for groups with large immigrant population. However, we find that personal characteristics--such as educational attainment, marital status, and income levels--are much more important than immigrant generation in understanding fertility outcomes. In fact, generations are not independently important once these personal characteristics are controlled for. We maintain that declining fertility levels among the descendants of Mexican and Central American immigrants are primarily the result of higher educational attainment levels, lower rates of marriage, and lower poverty. For example, a four-year increase in educational attainment decreases children ever born (CEB) by half a child. We conclude that immigrant generation serves as a proxy for changes in other personal characteristics that decrease fertility. Neighborhood characteristics have some bearing on fertility, but the correlations are relatively weak. Among Mexican and Central American immigrants and their descendants, the most consistent predictor of children ever born (CEB) at the neighborhood level is the percentage of Hispanic adults. However, no neighborhood characteristics bear any statistical relationship to current fertility, the measure that emphasizes recent births. This pattern of evidence suggests that the observed relationships between neighborhood characteristics and fertility are based on selection into the neighborhood rather than on neighborhood influences as such.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
hispanic, ethnicity, ethnic, mexican, immigrant, segregation, population, household, racial, immigration, native, generation, ancestry, poverty, socioeconomic, neighborhood, birth, fertility, immigrant populations

Tags Tags are automatically generated using a pretrained language model from spaCy, which excels at several tasks, including entity tagging.

The model is able to label words and phrases by part-of-speech, including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are identified to contain references to specific institutions, datasets, and other organizations.
:
Center for Economic Studies, Ordinary Least Squares, Current Population Survey, Decennial Census

Similar Working Papers Similarity between working papers are determined by an unsupervised neural network model know as Doc2Vec.

Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the capture of semantic meaning in a way that relates to the context of words within the document. The model learns to associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as document classification, clustering, and similarity detection by preserving the order and structure of words. The document vectors are compared using cosine similarity/distance to determine the most similar working papers. Papers identified with 🔥 are in the top 20% of similarity.

The 10 most similar working papers to the working paper 'The Relationship of Personal and Neighborhood Characteristics to Immigrant Fertility' are listed below in order of similarity.