**<u>Table 11: Impact of using a computer at work on wage growth, conditional on being employed</u>**

|||**Male**<br>|**sample**<br>|||**Female**<br>|**sample**<br>||
|---|---|---|---|---|---|---|---|---|
|VARIABLES|(1)<br>Wage<br>growth|(2)<br>Wage<br>growth|(3)<br>Wage<br>growth|(4)<br>Wage<br>growth|(5)<br>Wage<br>growth|(6)<br>Wage<br>growth|(7)<br>Wage<br>growth|(8)<br>Wage<br>growth|
|Use computer at work|0.145**|0.064|0.067|0.059|0.118|0.065|0.059|0.058|
||[0.066]|[0.069]|[0.069]|[0.069]|[0.102]|[0.102]|[0.103]|[0.104]|
|Use computer with Internet at work|0.173|0.094|0.098|0.077|-0.021|-0.012|0.005|0.004|
||[0.131]|[0.131]|[0.131]|[0.130]|[0.139]|[0.137]|[0.137]|[0.138]|
|Married|0.028|-0.057|-0.064|-0.060|0.060|-0.016|-0.048|-0.042|
||[0.056]|[0.066]|[0.067]|[0.067]|[0.107]|[0.105]|[0.108]|[0.110]|
|Age||0.006**|0.007**|0.007**||0.019***|0.021***|0.021***|
|||[0.003]|[0.003]|[0.003]||[0.005]|[0.005]|[0.005]|
|Primary or preparatory education||-0.008|-0.003|-0.005||0.131|0.116|0.121|
|||[0.084]|[0.084]|[0.085]||[0.466]|[0.463]|[0.461]|
|Secondary education||0.009|0.015|0.030||0.261|0.262|0.296*|
|||[0.071]|[0.072]|[0.072]||[0.171]|[0.174]|[0.175]|
|Above secondary education||0.244***|0.254***|0.267***||0.539***|0.567***|0.585***|
|||[0.082]|[0.084]|[0.084]||[0.176]|[0.179]|[0.180]|
|Rural|||0.050|-0.138|||0.196**|0.400*|
||||[0.050]|[0.326]|||[0.091]|[0.224]|
|Observations|2,609|2,608|2,608|2,608|626|624|624|624|
|R-squared|0.005|0.014|0.014|0.022|0.003|0.039|0.047|0.053|
|Region dummies|NO|NO|NO|YES|NO|NO|NO|YES|
|Dependent variable mean|0.869|0.870|0.870|0.870|0.941|0.940|0.940|0.940|
|Robust standard errors in brackets. *** p<0|.01, ** p<0.0|5, * p<0.1|||||||

_Notes._ Each cell represents a coefficient estimate using OLS regression. The analysis is restricted to employed individuals in 2012 that were also interviewed in 2018, aged 15 to 64 years old in 2012. Employed individuals are defined according to the market definition of labor force participation. The dependent variable is the logarithm of the difference in inflation adjusted hourly wages between the years 2018 and 2012. The main independent variables of interest are a dummy variable indicator equals to one if the individual reports using computer at work and a dummy variable indicator equals to one if the individual reports using a computer connected to the Internet at work. The control variables refer to the year 2012 and they include: a dummy variable for having Internet access at home, age, a dummy variable for being male, a dummy variable for being married, three dummies for the individual’s educational attainment (primary or preparatory education, secondary education either general or vocational and above secondary education either post-secondary institute or university and above, and the reference category is no educational degree either illiterate individuals or literate individuals without any diploma), a dummy variable for rural areas as well as dummies for the various geographical regions included in the last column (Greater Cairo, Alexandria, and Suez cities, Urban Lower Egypt, Urban Upper Egypt, Rural Lower Egypt, and Rural Upper Egypt). The dependent variable mean is reported in the last row.

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