A Business Survey on Job Vacancies: Integration with Other Sources and Calibration

2012 ◽  
pp. 139-152
Author(s):  
Diego Bellisai ◽  
Stefania Fivizzani ◽  
Marina Sorrentino
Keyword(s):  
Business Survey

Measuring the Impact of COVID-19 on Businesses and People: Lessons from the Census Bureau’s Experience

2021 ◽  
Vol 111 ◽  
pp. 312-316
Author(s):  
Catherine Buffington ◽  
Jason Fields ◽  
Lucia Foster
Keyword(s):  
Current Population Survey ◽  
Population Survey ◽  
Census Bureau ◽  
Community Survey ◽  
American Community Survey ◽  
Annual Business ◽  
Data Products ◽  
Business Survey ◽  
The Impact ◽  
Existing Data

We provide an overview of Census Bureau activities to enhance the consistency, timeliness, and relevance of our data products in response to the COVID-19 pandemic. We highlight new data products designed to provide timely and granular information on the pandemic's impact: the Small Business Pulse Survey, weekly Business Formation Statistics, the Household Pulse Survey, and Community Resilience Estimates. We describe pandemic-related content introduced to existing surveys such as the Annual Business Survey and the Current Population Survey. We discuss adaptations to ensure the continuity and consistency of existing data products such as principal economic indicators and the American Community Survey.

scholarly journals Bayesian small area estimation for skewed business survey variables

2017 ◽  
Vol 67 (4) ◽  
pp. 861-879
Author(s):  
Enrico Fabrizi ◽  
Maria Rosaria Ferrante ◽  
Carlo Trivisano
Keyword(s):  
Small Area ◽  
Small Area Estimation ◽  
Area Estimation ◽  
Business Survey

scholarly journals Accounting for rainfall and the length of growing season in technical efficiency analysis

2018 ◽  
Vol 20 (4) ◽  
pp. 2583-2608
Author(s):  
Yiorgos Gadanakis ◽  
Francisco José Areal
Keyword(s):  
Technical Efficiency ◽  
Physical Environment ◽  
Farming Systems ◽  
Growing Season ◽  
Efficiency Analysis ◽  
Performance Measurements ◽  
East Anglia ◽  
Dea Model ◽  
Efficiency Ranking ◽  
Business Survey

Abstract The physical environment of farming systems is rarely considered when conducting farm level efficiency analysis, which is likely to lead to bias of performance measurements based on benchmarking methods such as Data Envelopment Analysis (DEA). We incorporate variations of the physical environment (rainfall and length of growing season) through the specifications of the linear programming in DEA to investigate performance measurement bias. The derived technical efficiency estimates are obtained using a sub-vector DEA which ensures farms are compared in a homogenous environment (i.e. accounting for differences in rainfall levels amongst distinct farm units). We use the Farm Business Survey to analyse a representative sample of 245 cereal farms in the East Anglia region between 2009 and 2010. Efficiency rankings obtained from a standard DEA model and a non-discretionary DEA model that incorporates the variations in the physical environment. We show that incorporating rainfall and the length of the growing season as non-discretionary inputs into the production function had significantly altered the farm efficiency ranking between the two models. Hence, to improve extension services to farmers and to reduce biased estimates of farm technical efficiency, variations in environmental conditions need to be integral to the analysis of efficiency.

scholarly journals Advanced Technologies Adoption and Use by U.S. Firms: Evidence from the Annual Business Survey

2020 ◽  
Author(s):  
Nikolas Zolas ◽  
Zachary Kroff ◽  
Erik Brynjolfsson ◽  
Kristina McElheran ◽  
David Beede ◽  
...  
Keyword(s):  
Annual Business ◽  
Advanced Technologies ◽  
Business Survey
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