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Table 3 Regression results: Search activities and tightness

From: Cyclicality of labour market search: a new big data approach

 

Dependent variable

\(I^{JS}\)

\(I^{F}\)

\(I^{EA}\)

SP

Constant

0.74

(0.51)

− \(1.41{***}\)

(0.46)

\(1.38{***}\)

(0.24)

\(3.76{***}\)

(0.06)

\(\theta _{t}\)

− 0.67

(1.33)

\(2.75{**}\)

(1.38)

\(5.29{***}\)

(1.36)

0.22

(0.29)

\(\theta _{t-1}\)

− \(2.28{*}\)

(1.28)

− 0.74

(2.01)

− \(6.81{*}\)

(3.84)

− \(0.32{**}\)

(0.12)

\(\theta _{t-2}\)

0.50

(3.07)

− 2.19

(3.26)

\(5.79{*}\)

(2.98)

− 0.04

(0.25)

\(\theta _{t-3}\)

2.32

(3.67)

0.50

(2.74)

− \(3.20{**}\)

(1.58)

0.11

(0.13)

trend

\(0.94{**}\)

(0.41)

− 0.08

(0.38)

− \(0.96{***}\)

(0.16)

− 0.01

(0.06)

R-squared

0.6050

0.1214

0.6863

0.2784

  1. Estimated effects from OLS regressions with heteroscedasticity- and autocorrelation-robust standard errors (in parentheses). *, **, *** denote significance at the 10, 5, 1% level, respectively. \(I^{JS}\), \(I^{F}\), \(I^{EA}\): Search intensity of job seekers/firms/employment agencies. SP: Average search perimeter of job seekers in kilometers. \(\theta\): labour market tightness. All variables enter the regressions in logarithms