¿CÓMO SE BUSCA Y OFRECE TRABAJO EN INTERNET? Presentación de Resultados
Benjamín Villena-Roldán, Profesor / Investigador Departamento de Ingeniería Industrial Universidad de Chile, DII, CEA, SMAUG, MIPP
Julio 19, 2018
Primera Investigación Académica realizada en Chile
con datos aportados por trabajando.com sobre cómo las personas y las empresas buscan y ofrecen trabajo en internet
¿CÓMO SE BUSCA Y OFRECE TRABAJO EN INTERNET? Informe de Resultados
Benjamín Villena-Roldán, Profesor / Investigador Departamento de Ingeniería Industrial Universidad de Chile, DII, CEA, SMAUG, MIPP
Julio 19, 2018
Primera Investigación Académica realizada en Chile
con datos aportados por trabajando.com sobre cómo las personas y las empresas buscan y ofrecen trabajo en internet
Deconstructing Job Search BehaviorStefano Banfi , Ministry of Energy, Chile
Sekyu Choi, University of Bristol
Benjamín Villena-Roldán, CEA, DII, University of Chile, SMAUG, MIPP
June 16, 2018
Abstract
We use an unusually rich data from a Chilean job board to document various theoretically
relevant facts regarding job search. We show how application behavior is in uenced by (1)
demographics such as gender, age, and marital status, (2) alignment between applicant wage
expectations and wage o ers, (3) applicant t into ad requirements such as education, experience,
job location and occupation (4) timing variables, including unemployment duration, job tenure
(for on-the-job searchers) and business cycle conditions. Our paper provides novel evidence that
can discipline current and future search-theoretical frameworks.
Keywords: Online job search, Applications, Search frictions, Unemployment, On-the-job search,
Networks.
Sorting On-line and On-timeStefano Banfi , Ministry of Energy, Chile
Sekyu Choi, University of Bristol
Benjamín Villena-Roldán, CEA, DII, University of Chile, SMAUG, MIPP
April 22, 2018
Abstract
Using proprietary data from a Chilean online job board, we nd
strong, positive assortative matching at the worker-position level, both
along observed dimensions and on unobserved characteristics (OLS Min-
cer residual wages). We also nd that this positive assortative match-
ing is robustly procyclical. Then, we use the generalized deferred-
acceptance algorithm to simulate ex post matches to compare our re-
sults to the existing empirical literature. Under all considered scenarios
of our simulations, positive assortative matching is preserved from the
application stage to the realized matches.
Keywords: Online search, assortative matching, labor markets.
Do High-Wage Jobs Attract more Applicants?Stefano Banfi , Ministry of Energy, Chile
Benjamín Villena-Roldán, University of Chile, Department of Industrial Engineering,
Center for Applied Economics
April 1, 2018
Abstract
Labor markets become more efficient in theory if jobseekers direct their search. Using
online job board data, we show that high-wage ads attract more applicants as in
directed search models. Due to distinctive data features, we also estimate significant
but milder directed search for hidden (or implicit) wages, suggesting that ad texts and
requirements tacitly convey wage information. Since explicit-wage ads often target unskilled
workers, other estimates in the literature ignoring hidden-wage ads may suffer
from selection bias. Moreover, job ad requirements are aligned with their applicants’
traits, as predicted in directed search models with heterogeneity.