Data and Code for: Local Economic Conditions and Fertility from the Great Depression through the Great Recession
Principal Investigator(s): View help for Principal Investigator(s) Jessamyn Schaller, Claremont McKenna College; Price Fishback, University of Arizona; Kelli Marquardt, University of Arizona
Version: View help for Version V1
Name | File Type | Size | Last Modified |
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rawdata_infile | 08/06/2020 04:44:PM | ||
SFMAnalysis_PublicData.dta | application/x-stata | 10.6 MB | 01/09/2020 10:32:AM |
SFMAnalysis_code.do | text/x-stata-syntax | 4.8 KB | 01/09/2020 09:11:AM |
SFM_Data_README.docx | application/vnd.openxmlformats-officedocument.wordprocessingml.document | 15.7 KB | 01/07/2020 11:08:AM |
SFM_Data_README.pdf | application/pdf | 99.2 KB | 10/12/2020 09:54:AM |
Project Citation:
Schaller, Jessamyn, Fishback, Price, and Marquardt, Kelli. Data and Code for: Local Economic Conditions and Fertility from the Great Depression through the Great Recession. Nashville, TN: American Economic Association [publisher], 2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-10-13. https://doi.org/10.3886/E120558V1
Project Description
Summary:
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In this study, we use newly compiled data on county-level birthrates in the continental United States spanning eight decades to generate new estimates of the association between local economic conditions and birthrates. Our dataset— the longest US panel dataset ever used to study fertility—allows us to estimate the response of fertility to economic shocks by using variation across local areas in the timing and severity of as many as 13 aggregate US recessions that have occurred since the Great Depression. Our area-study approach controls for potentially confounding aggregate factors such as the baby boom and advances in contraceptive technology, exploiting local deviations from aggregate time patterns for identification.The length of our panel permits us to make two additional novel contributions to the literature on economic conditions and fertility. First, we use distributed lag models to estimate midrun dynamic responses of birthrates to economic shocks—responses that are not well identified in time series and short-panel analyses. Second, we are able to document changes in the responsiveness of fertility to local economic conditions over the past 80 years. We do so systematically by using the same data and estimation model and varying the sample time frame.
Scope of Project
Subject Terms:
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fertility;
income;
business cycles;
birth rates
JEL Classification:
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E32 Business Fluctuations; Cycles
J11 Demographic Trends, Macroeconomic Effects, and Forecasts
J13 Fertility; Family Planning; Child Care; Children; Youth
E32 Business Fluctuations; Cycles
J11 Demographic Trends, Macroeconomic Effects, and Forecasts
J13 Fertility; Family Planning; Child Care; Children; Youth
Geographic Coverage:
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United States
Time Period(s):
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1937 – 2016
Data Type(s):
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administrative records data;
aggregate data
Collection Notes:
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The data used in the paper also included restricted data from the US Vital Statistics Natality Data for 2008-2016. These data are available to interested researchers here: https://www.cdc.gov/nchs/nvss/dvs_data_release.htm (application required).
All other data are collected from public sources.
All other data are collected from public sources.
Methodology
Data Source:
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Bailey et al. (2018) – US County-Level Natality and Mortality Data, 1915-2007 (ICPSR 36603)
US Vital Statistics natality restricted data with county and state identifiers for 2008-2016. Interested researchers can apply for access here: https://www.cdc.gov/nchs/nvss/dvs_data_release.htm.
National Cancer Institute's Surveillance, Epidemiology and end Results (SEER) population data by county from 1969 forward. Source (public): https://seer.cancer.gov/popdata/download.html
Bureau of Labor Statistics current price index: CPI-U annual average available at: data.bls.gov
Bureau of Economic Analysis state and county per capita income at bea.gov - Tables SA1 and CA1
US Vital Statistics natality restricted data with county and state identifiers for 2008-2016. Interested researchers can apply for access here: https://www.cdc.gov/nchs/nvss/dvs_data_release.htm.
National Cancer Institute's Surveillance, Epidemiology and end Results (SEER) population data by county from 1969 forward. Source (public): https://seer.cancer.gov/popdata/download.html
Bureau of Labor Statistics current price index: CPI-U annual average available at: data.bls.gov
Bureau of Economic Analysis state and county per capita income at bea.gov - Tables SA1 and CA1
Unit(s) of Observation:
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US County
Geographic Unit:
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US County
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