# _Robustness check: Limiting the sample to countries with a STEP survey_

To assess if the imputation of task scores to countries beyond those covered by a STEP survey affects the results, we conduct a robustness check where we estimate the main equation using the original sample of countries with a STEP survey. Given that the number of observations is significantly smaller, we estimate more parsimonious specifications by replacing year dummy variables with decade dummy variables. In addition, we exclude GDP per capita (both in levels and changes) as control variables in the full model.

As seen in Table 10, the estimated coefficients associated with internet use and exports have in general the same signs as those of Table 5, although the latter are no longer statistically significant. Increased internet use is associated with increases (decreases) in the non-routine (routine) task intensity of jobs. Several other coefficients become statistically significant in this sample, but the number of observations is too small to draw conclusions.

**Table 10. Robustness check: Restricting the sample to countries with a STEP survey.**

||(1)|(2)|(3)<br>(4)|(5)<br>(6)|(7)<br>(8)|(9)|(10)|
|---|---|---|---|---|---|---|---|
||Non‐routin|e analytical|Non‐routine interpersonal|Routine cognitive|Routine Manual|Non‐rou|tine manual|
||STEP‐|sample|STEP‐sample|STEP‐sample|STEP‐sample|STEP|‐sample|
|GDP (log), change|‐0.0187||0.00405|‐0.0151|0.0391|0.0117||
||(0.0314)||(0.0195)|(0.0227)|(0.0289)|(0.0259)||
|GDP (lagged, log)|‐0.00422||‐0.00236|0.000933|‐0.00103|‐0.00349||
||(0.00977)||(0.00605)|(0.00705)|(0.00897)|(0.00806)||
|Industry VA (% of GDP), change||‐0.595***|‐0.255|0.292*|‐0.268||‐0.113|
|||(0.223)|(0.161)|(0.155)|(0.193)||(0.225)|
|Services VA (% of GDP), change||0.340***|0.164*|‐0.281***|‐0.294***||0.00581|
|||(0.119)|(0.0861)|(0.0831)|(0.104)||(0.121)|
|Skilled (% of working age population), change||‐0.0155|0.0344|‐0.000606|0.00224||0.0667|
|||(0.0631)|(0.0455)|(0.0439)|(0.0547)||(0.0638)|
|Females (% of employment), change||‐1.590***|‐0.573|0.478|0.0763||‐0.545|
|||(0.579)|(0.417)|(0.403)|(0.502)||(0.585)|
|Working age population (% of population), change||‐2.429***|‐1.012**|1.544***|1.414***||‐0.212|
|||(0.549)|(0.396)|(0.382)|(0.476)||(0.555)|
|Older than 65 years (% of population), change||‐0.885|‐0.0244|0.926|5.334***||1.409|
|||(1.880)|(1.355)|(1.308)|(1.632)||(1.901)|
|Internet users (% of population), change||0.296***|0.160**|‐0.195***|‐0.0833||0.0788|
|||(0.0949)|(0.0684)|(0.0660)|(0.0823)||(0.0959)|
|Imports (% of GDP), change||0.161*|0.122**|0.00631|0.209***||0.158*|
|||(0.0803)|(0.0579)|(0.0559)|(0.0697)||(0.0812)|
|Exports (% of GDP), change||‐0.110|‐0.0737|0.0191|‐0.139||‐0.165|
|||(0.0990)|(0.0714)|(0.0689)|(0.0859)||(0.100)|
|Observations|73|68|73<br>68|73<br>68|73<br>68|73|68|
|R‐squared|0.012|0.474|0.017<br>0.281|0.074<br>0.476|0.055<br>0.537|0.039|0.155|

Note: Sample includes countries covered by the STEP survey only. Dummy variables for each decade are included as covariates.

# **6. How do labor markets cope with the changing demand for skills?**

Changes in the demand for skills coming from trade and technology shocks can have disruptive effects in the labor market, especially when workers cannot easily move across occupations. There is a large body of literature showing that, even in developed countries with flexible labor markets, 28