CREAT: Census Research Exploration and Analysis Tool

Establishment and Employment Dynamics in Appalachia: Evidence from the Longitudinal Business Database

December 2003

Written by: Lucia Foster

Working Paper Number:

CES-03-19

Abstract

One indicator of the general economic health of a region is the rate at which new jobs are created. The newly developed Longitudinal Business Database has been used in this paper to develop a detailed portrait of establishment formation and attrition and job creation and destruction in the Appalachian Region. The foremost finding is that the pace of reallocation in Appalachia is lower than it is for the U.S.. This is evident in Appalachia's relatively lower establishment birth and death rates and job creation and destruction rates. For example, on average over the study time period, the U.S. job creation rate exceeds 45 percent, while the Appalachian job creation rate is 43 percent. Similarly, the U.S. job destruction rate is about 35 percent, while the Appalachian job destruction rate is about 33 percent. Even when controlling for other differences, job creation rates are 1.2 percentage points lower and job destruction rates are 3.4 percentage points lower in Appalachia relative to the rest of the U.S. Another indicator of the general economic health of a region is the quality of its jobs. The quality of jobs is measured in this paper by the average wage paid at the establishment. Here too there is cause for concern about the economic health of Appalachia. The analysis shows that wages are about 10 percent lower in Appalachia than in the U.S. even when controlling for differences in other characteristics across the two areas. This wage discrepancy has not narrowed over the time of the study. Moreover, new establishments have a similar wage gap. Employees at new establishments earn wages 10 percent less than at new establishments in the rest of the U.S.

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.
:
econometric, employ, entrepreneurship, sector, recession, regional, state, metropolitan, rural, geography, poverty, 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.
:
Center for Economic Studies, Bureau of Economic Analysis, National Establishment Time Series, Financial, Insurance and Real Estate Industries, Longitudinal Business Database, Retail Trade, Wholesale Trade

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 'Establishment and Employment Dynamics in Appalachia: Evidence from the Longitudinal Business Database' are listed below in order of similarity.