Table 5.

The impact of robot exposure across industries

Long difference of total employment, OLS
(1)(2)(3)(4)(5)(6)(7)(8)
DenmarkFinlandGermanyItalyNorwaySpainSwedenUnited Kingdom
Panel A. Automotive industry
Exposure to robots−0.2431.038−0.082−0.476***0.7040.117−0.204−0.217
(0.667)(0.666)(0.065)(0.154)(1.244)(0.116)(0.190)(0.175)
R-squared0.1740.5860.1810.6490.2900.8640.3100.435
Panel B. All Industries excluding automotive
Exposure to robots1.308−2.791***−0.286−0.734−3.642***−0.916−0.442−1.028*
(1.285)(0.784)(0.178)(0.639)(0.941)(0.626)(0.612)(0.524)
R-squared0.1890.6310.1770.6260.4470.8670.3050.440
Panel C. Highly exposed manufacturing industries
Exposure to robots0.456−0.245−0.099−0.524***−1.904***0.090−0.296−0.361*
(0.751)(0.734)(0.066)(0.151)(0.708)(0.119)(0.189)(0.184)
R-squared0.1770.5710.1850.6550.3480.8630.3220.439
Observations99703191107449100352
Regional FE
Baseline controls
Long difference of total employment, OLS
(1)(2)(3)(4)(5)(6)(7)(8)
DenmarkFinlandGermanyItalyNorwaySpainSwedenUnited Kingdom
Panel A. Automotive industry
Exposure to robots−0.2431.038−0.082−0.476***0.7040.117−0.204−0.217
(0.667)(0.666)(0.065)(0.154)(1.244)(0.116)(0.190)(0.175)
R-squared0.1740.5860.1810.6490.2900.8640.3100.435
Panel B. All Industries excluding automotive
Exposure to robots1.308−2.791***−0.286−0.734−3.642***−0.916−0.442−1.028*
(1.285)(0.784)(0.178)(0.639)(0.941)(0.626)(0.612)(0.524)
R-squared0.1890.6310.1770.6260.4470.8670.3050.440
Panel C. Highly exposed manufacturing industries
Exposure to robots0.456−0.245−0.099−0.524***−1.904***0.090−0.296−0.361*
(0.751)(0.734)(0.066)(0.151)(0.708)(0.119)(0.189)(0.184)
R-squared0.1770.5710.1850.6550.3480.8630.3220.439
Observations99703191107449100352
Regional FE
Baseline controls

This table presents OLS estimates of the impact of the exposure to robots in automotive industries and others. The measurement of robot exposure is an instrumental variable. The outcome variables are the long difference in employment-to-population ratio. Regressions are weighted by population in the start-of-period. The list of covariates is documented in  Appendix A. The missing geographic and industry values in Germany are due to confidentiality-related data limitations. Statistical significance based on robust standard errors (reported in parentheses) is denoted by ***P< 0.01, **P< 0.05, and *P< 0.10.

Table 5.

The impact of robot exposure across industries

Long difference of total employment, OLS
(1)(2)(3)(4)(5)(6)(7)(8)
DenmarkFinlandGermanyItalyNorwaySpainSwedenUnited Kingdom
Panel A. Automotive industry
Exposure to robots−0.2431.038−0.082−0.476***0.7040.117−0.204−0.217
(0.667)(0.666)(0.065)(0.154)(1.244)(0.116)(0.190)(0.175)
R-squared0.1740.5860.1810.6490.2900.8640.3100.435
Panel B. All Industries excluding automotive
Exposure to robots1.308−2.791***−0.286−0.734−3.642***−0.916−0.442−1.028*
(1.285)(0.784)(0.178)(0.639)(0.941)(0.626)(0.612)(0.524)
R-squared0.1890.6310.1770.6260.4470.8670.3050.440
Panel C. Highly exposed manufacturing industries
Exposure to robots0.456−0.245−0.099−0.524***−1.904***0.090−0.296−0.361*
(0.751)(0.734)(0.066)(0.151)(0.708)(0.119)(0.189)(0.184)
R-squared0.1770.5710.1850.6550.3480.8630.3220.439
Observations99703191107449100352
Regional FE
Baseline controls
Long difference of total employment, OLS
(1)(2)(3)(4)(5)(6)(7)(8)
DenmarkFinlandGermanyItalyNorwaySpainSwedenUnited Kingdom
Panel A. Automotive industry
Exposure to robots−0.2431.038−0.082−0.476***0.7040.117−0.204−0.217
(0.667)(0.666)(0.065)(0.154)(1.244)(0.116)(0.190)(0.175)
R-squared0.1740.5860.1810.6490.2900.8640.3100.435
Panel B. All Industries excluding automotive
Exposure to robots1.308−2.791***−0.286−0.734−3.642***−0.916−0.442−1.028*
(1.285)(0.784)(0.178)(0.639)(0.941)(0.626)(0.612)(0.524)
R-squared0.1890.6310.1770.6260.4470.8670.3050.440
Panel C. Highly exposed manufacturing industries
Exposure to robots0.456−0.245−0.099−0.524***−1.904***0.090−0.296−0.361*
(0.751)(0.734)(0.066)(0.151)(0.708)(0.119)(0.189)(0.184)
R-squared0.1770.5710.1850.6550.3480.8630.3220.439
Observations99703191107449100352
Regional FE
Baseline controls

This table presents OLS estimates of the impact of the exposure to robots in automotive industries and others. The measurement of robot exposure is an instrumental variable. The outcome variables are the long difference in employment-to-population ratio. Regressions are weighted by population in the start-of-period. The list of covariates is documented in  Appendix A. The missing geographic and industry values in Germany are due to confidentiality-related data limitations. Statistical significance based on robust standard errors (reported in parentheses) is denoted by ***P< 0.01, **P< 0.05, and *P< 0.10.

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