Overall, from 2006 to 2013, employment increased in all regions expect TR22, TR83, and TR90 (Figure 25). Istanbul had the most impressive growth, over 811,000 new jobs were created from 2006 to 2013; there was also a lot of internal migration to this region as well. In terms of growth, the south-eastern regions had consistently high levels of growth. TRC performed exceptionally well, with almost 50 percent growth in the number of jobs from 2006 to 2013.

Turkey’s ability to create jobs even during a crisis period is a large accomplishment. From 2009 to 2013, 4.2 million jobs were created in Turkey, while the number of jobs in the EU declined by 2 million (World Bank, 2014). The reasons for this labor market success story is tentative but can be related to growth in services such as construction and structural change that is occurring throughout the country. Wages are higher in the West. Over time, workers are becoming better educated and structural shifts contribute to increasing wages. New jobs are characterized by being of better quality, having higher wages, and employing more highly educated people.

Table 6 illustrates regression results using employment as a determining factor. The coefficients can be interpreted as elasticities. At all levels of aggregation, it is clear that growth in the services sector has large effects on poverty reduction. Moreover, the poverty reduction impact of employment from services exists across all regions. Nationally on average, the elasticity of poverty to services employment is significant at -0.136 and when controlling for NUTS1 regions, the absolute value of the elasticity is even higher at -0.142. In columns (3) and (4) with East and West interactions, employment growth in agriculture is also important in the East, but this significance is lost when using the three region grouping (columns 5 and 6).

Table 6. Employment growth in the services sector has a strong relation to poverty reduction (2006-2013)

|No Regional<br>Interactions|||With East/West<br>Regional Interactions|||With 3 Regional<br>Interaction Terms|||
|---|---|---|---|---|---|---|---|---|
||(1)|(2)||(3)|(4)||(5)|(6)|
|�∆ln �����<br>��<br>�∆ln �����<br>��|-0.00776<br>(0.00973)<br>0.00308<br>(0.0172)|-0.00957<br>(0.0104)<br>-0.00337<br>(0.0202)|�∆ln �����<br>��*West<br>�∆ln �����<br>��*East|0.00185<br>(0.00903)<br>-0.0794**<br>(0.0357)|0.000494<br>(0.00946)<br>-0.112**<br>(0.0447)|�∆ln �����<br>��*R1<br>�∆ln �����<br>��*R2|-0.0188<br>(0.0169)<br>0.0150<br>(0.0260)|-0.0217<br>(0.0190)<br>0.0157<br>(0.0281)|
|�∆ln �����<br>��|-0.136***<br>(0.0405)|-0.142***<br>(0.0394)|�∆ln �����<br>��*West<br>�∆ln �����<br>��*East|-0.0290<br>(0.0217)<br>0.0439**<br>(0.0193)|-0.0174<br>(0.0237)<br>0.0142<br>(0.0247)|�∆ln �����<br>��*R3<br>�∆ln �����<br>��*R1|-0.00506<br>(0.00823)<br>0.0147<br>(0.0209)|-0.00870<br>(0.00930)<br>0.000940<br>(0.0256)|
||||�∆ln �����<br>��*West|-0.130***<br>(0.0272)|-0.127***<br>(0.0300)|�∆ln �����<br>��*R2|-0.0428<br>(0.0280)|-0.0307<br>(0.0313)|
||||�∆ln �����<br>��*East|-0.242**<br>(0.108)|-0.304***<br>(0.0908)|�∆ln �����<br>��*R3<br>�∆ln �����<br>��*R1<br>�∆ln �����<br>��*R2<br>�∆ln �����<br>��*R3|-0.000727<br>(0.0252)<br>-0.174***<br>(0.0601)<br>-0.108**<br>(0.0437)<br>-0.0824***<br>(0.0264)|0.00874<br>(0.0316)<br>-0.179***<br>(0.0577)<br>-0.0937*<br>(0.0459)<br>-0.0947***<br>(0.0326)|
|Constant|0.00108<br>(0.00200)|-0.00212***<br>(0.000477)|Constant|0.00164<br>(0.00197)|-0.00159***<br>(0.000538)|Constant|0.000441<br>(0.00181)|-0.00258***<br>(0.000687)|
|NUTS1 controls||X|NUTS1 controls||X|NUTS1 controls||X|
|N|182|182|N|182|182|N|182|182|
|R-squared|0.157|0.213|R-squared|0.216|0.281|R-squared|0.180|0.234|

_Notes_ : Table 24 show regression results limited to the period 2007-2011 to match periods with GVA. R1=Rest of the country, R2=Anatolian Tigers, R3=developed west. Period is 2006-2013. _Source_ : TUIK, LFS, SILC 2007-2011, author’s calculations 23