Table 5 Regression results: controlling for compositional effects
From: Cyclicality of labour market search: a new big data approach
Dependent variable | ||||||||
|---|---|---|---|---|---|---|---|---|
\(I^{JS}\) | \(I^{F}\) | \(I^{EA}\) | SP | |||||
Constant | \(78.01{***}\) | (27.87) | \(50.75{*}\) | (28.18) | − 8.69 | (24.00) | \(3.55{***}\) | (1.06) |
\(GDP_{t}\) | − 0.40 | (1.01) | − 1.16 | (1.27) | − 1.66 | (0.97) | 0.12 | (0.08) |
\(GDP_{t-1}\) | − \(7.16{**}\) | (2.90) | − 5.54 | (3.95) | 0.47 | (2.62) | 0.02 | (0.12) |
\(GDP_{t-2}\) | − 3.53 | (2.25) | − 3.48 | (2.62) | 3.05 | (3.65) | − 0.02 | (0.12) |
\(GDP_{t-3}\) | − \(3.31{*}\) | (1.64) | \(4.09{*}\) | (2.33) | 1.46 | (2.48) | − \(0.24{**}\) | (0.12) |
\(\theta _{t}\) | 0.33 | (1.54) | − 0.99 | (1.63) | \(7.29{***}\) | (2.35) | \(0.36{***}\) | (0.11) |
\(\theta _{t-1}\) | 0.02 | (1.74) | \(5.06{**}\) | (2.20) | − \(9.74{*}\) | (4.01) | − \(0.34{*}\) | (0.18) |
\(\theta _{t-2}\) | 0.60 | (3.87) | − 2.55 | (3.59) | 5.24 | (3.72) | 0.00 | (0.17) |
\(\theta _{t-3}\) | − 0.70 | (3.28) | − 0.82 | (2.86) | − 1.63 | (3.00) | − 0.02 | (0.14) |
trend | − 0.38 | (1.02) | 0.06 | (1.70) | − \(2.65{**}\) | (0.97) | 0.14 | (0.12) |
R-squared | 0.7668 | 0.3986 | 0.7968 | 0.6271 | ||||