CREAT: Census Research Exploration and Analysis Tool

Smart Cafe Cities: Testing Human Capital Externalities in the Boston Metropolitan Area

October 2005

Written by: Shihe Fu

Working Paper Number:

CES-05-24

Abstract

Existing studies have explored either only one or two of the mechanisms that human capital externalities percolate at only macrogeographic levels. This paper uses the 1990 Massachusetts Census data and tests four mechanisms at the microgeographic levels in the Boston metropolitan area labor market. We propose that individual workers can learn from their occupational and industrial peers in the same local labor market through four channels: depth of human capital stock, Marshallian labor market externalities, Jacobs labor market externalities, and thickness of the local labor market. We find that all types of human capital externalities are significant across Census blocks. Different types of externalities attenuate at different speeds over distances. For example, the effect of human capital depth decays rapidly beyond three miles away from block centroid. We conclude that knowledge spillovers are very localized within microgeographic scope in cities that we call Smart Caf' Cities.

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.
:
market, economist, econometric, metropolitan, area, spillover, geographically, industry concentration, occupation, urban, urbanization, city, externality, geography, worker demographics, labor markets, geographic

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.
:
Metropolitan Statistical Area, Consolidated Metropolitan Statistical Areas, Geographic Information Systems

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 'Smart Cafe Cities: Testing Human Capital Externalities in the Boston Metropolitan Area' are listed below in order of similarity.