«June 2015 Abstract Since 2011, Saudi Arabia has dramatically extended its labor market policies to address youth unemployment and low Saudi ...»
Chay, K. Y. , ‘The impact of federal civil rights policy on black economic progress: Evidence from the equal employment opportunity act of 1972’, Industrial and Labor Relations Review 51(4), pp. 608–632.
Chin, A. & Prakash, N. , ‘The redistributive e↵ects of political reservation for minorities:
Evidence from India’, Journal of Development Economics 96(2), 265–277.
Dahlberg, M., M¨rk, E., Rattsø, J. & ˚gren, H. , ‘Using a discontinuous grant rule to identify o A the e↵ect of grants on local taxes and spending’, Journal of Public Economics 92(12), 2320–2335.
Dunne, T., Roberts, M. J. & Samuelson, L. , ‘The growth and failure of U.S. manufacturing plants’, The Quarterly Journal of Economics 104(4), 671–98.
El-Katiri, L., Fattouh, B. & Segal, P. , ‘Anatomy of an oil-based welfare state: Rent distribution in kuwait’, Research Paper, Kuwait Programme on Development, Governance and Globalisation in the Gulf States.
Fan, J. & Gijbels, I. , Local Polynomial Modelling and Its Applications, Chapman and Hall, London.
Fang, H. & Norman, P. , ‘Government-mandated discriminatory policies: Theory and evidence’, International Economic Review 47(2), 361–389.
Forstenlechner, I., Madi, M. T., Selim, H. M. & Rutledge, E. , ‘Emiratisation: determining the factors that inuence the recruitment decisions of employers in the UAE’, The International Journal of Human Resource Management 23(2), 406–421.
Forstenlechner, I. & Rutledge, E. , ‘Growing levels of national unemployment in the Arab Gulf: Time to update the ‘social contract”, Middle East Policy 17(2), 38–51.
Fryer, R. G. & Loury, G. C. , ‘Valuing diversity’, Journal of Political Economy 121(4), 747– 774.
Gri n, P. , ‘The impact of a rmative action on labor demand: A test of some implications of the LeChatelier principle’, Review of Economics and Statistics 72(2), 251–60.
Guryan, J. , Does money matter? Regression-discontinuity estimates from education ﬁnance reform in Massachusetts, NBER Working Papers 8269, National Bureau of Economic Research, Inc.
Hertog, S. , Arab Gulf states: an assessment of nationalisation policies, GLMM Research Paper 1, Gulf Labour Markets and Migration Programme, Badia Fiesolana, Italy.
Holzer, H. & Neumark, D. , ‘Assessing a rmative action’, Journal of Economic Literature 38(3), 483–568.
Howard, L. L. & Prakash, N. , ‘Do employment quotas explain the occupational choices of disadvantaged minorities in India?’, International Review of Applied Economics 26(4), 489–513.
Jones, M. R. , The EITC and labor supply: evidence from a regression kink design, Working paper.
Kasolowsky, R. , ‘UAE mulls new labor law to attract Emiratis to private sector’, Reuters.
February 16, 2013.
Kurtulus, F. A. , The impact of a rmative action on the employment of minorities and women over three decades: 1973-2003, Working paper.
Lee, D. S. & Lemieux, T. , ‘Regression discontinuity designs in economics’, Journal of Economic Literature 48(2), 281–355.
Looney, R. , ‘Saudization and sound economic reforms: Are the two compatible?’, Strategic Insights 3(2), 1–9.
McCrary, J. , ‘Manipulation of the running variable in the regression discontinuity design:
A density test’, Journal of Econometrics 142(2), 698–714.
Miller, C. , The persistent e↵ect of temporary a rmative action, Working paper.
Nielsen, H. S., Sorensen, T. & Taber, C. , ‘Estimating the e↵ect of student aid on college enrollment: Evidence from a government grant policy reform’, American Economic Journal:
Economic Policy 2(2), 185–215.
Prakash, N. , Improving the labor market outcomes of minorities: The role of employment quota, IZA Discussion Papers 4386, Institute for the Study of Labor (IZA).
Ramady, M. , ‘Gulf unemployment and government policies: prospects for the Saudi labour quota or Nitaqat system’, International Journal Economics and Business Research X(Y).
Randeree, K. , ‘Strategy, policy, and practice in the nationalization of human capital:
‘Project Emiratization”, Research and Practice in Human Resource Management 17(1), 71–91.
Randeree, K. , Workforce nationalization in the Gulf Cooperation Council states, Occasional paper no. 9, Center for International and Regional Studies, Georgetown University School of Foreign Service in Qatar.
Sadi, M. A. , ‘The implementation process of nationalization of workforce in Saudi Arabian private sector: A review of “Nitaqat scheme”’, American Journal of Business and Management 2(1), 37–45.
Simonsen, M., Skipper, L. & Skipper, N. , Price sensitivity of demand for prescription drugs:
Exploiting a regression kink design, Working Papers 10-1, University of Aarhus, Aarhus School of Business, Department of Economics.
Sowell, T. , A rmative Action Around the World: An Empirical Study, Yale University Press.
Tran, T. , The impact of a rmative action and equity regulations on Malaysia’s manufacturing ﬁrms, Technical report, IZA Discussion Paper.
World Bank Group, Ozden, C., Parsons, C., Schi↵, M. & Walmsley, T. L. , ‘Global bilateral ¸ migration database’.
Figures Figure I: Weekly Totals of Saudi and Expatriate Private-Sector Employees (#$" 7.6 4*?69" )*+,-."/0"12345.645-"7/.8-.9":+6;;6/9=" 7.4 )*+,-."/0"4*?6"7/.8-.9":+6;;6/9=" (" 7.2 12345.645-9" !#'" !#&" 6.8 6.6 !#%" 6.4 !#$" 6.2 !" 6
Notes: This ﬁgure shows the weekly totals of Saudis and expatriate workers in the Nitaqat data. Vertical lines indicate important dates in program enforcement.
Figure II: Movements Between Color Bands (July 2011 to October 2012) 100%
Notes: This ﬁgure shows the proportion of ﬁrms in each starting category (x-axis) that transitioned into di↵erent color bands. For example, most ﬁrms in the yellow starting color band moved to the green category, and less than ten percent moved into the red category by October of the following year.
Notes: These ﬁgures show how Saudization compliance requirements are normalized into a policy rule with a single kink at zero. Panel (a) plots the required increase in Saudization percentage against starting Saudization rate for medium-sized construction ﬁrms, which had a 6 percent Saudization target. Yellow dots correspond to ﬁrms in the Yellow and Red bands, and green dots to ﬁrms in the Green and Platinum bands.
The red line marks the compliance cuto↵ at 6 percent. Panel (b) plots this relationship for all ﬁrms, with kink locations corresponding with cell-speciﬁc compliance quotas. Panel (c) plots required increase against distance from the cuto↵, normalizing all kinks to zero.
Figure IV: Normalized Compliance Requirement: Required Change vs. Initial Distance from Cuto↵
Notes: This ﬁgure shows the compliance rule in terms of the required increase in the number of Saudi employees holding expatriate employees ﬁxed (panel (a)) and the decrease in the number of expatriate employees needed holding the number of Saudi employees ﬁxed (panel (b)). In contrast to Figure IIIc, the units on the axes are number of employees rather than Saudi percentage.
Notes: Firms with zero Saudization percentage at baseline are excluded from this ﬁgure. Bin size on is
0.5 percentage point. This ﬁgure corresponds to a McCrary test for a break in the baseline Saudization percentage for Green and Yellow ﬁrms at the compliance cuto↵. The corresponding McCrary test statistic is 0.94.
Notes: Parametric tests for a kink in these baseline employment ﬁgures fail to reject the null of no change in the slope at all conventional signiﬁcant levels. There is no evidence of a kink in either the linear ﬁt or in the local quadratic polynomial ﬁt.
Notes: These ﬁgures show the linear RKD results for the full sample, with endline employment set to zero for exiting ﬁrms. Circles plot the average outcome variable for ﬁrms in one-unit bins based on initial distance from the cuto↵. Fit lines are based regression lines for ﬁrms within ten units of the cuto↵. Black lines for Saudi and expatriate employees show full-compliance benchmarks.
−50 −40 −30 −20 −10 0 10 20 30 40
Notes: These ﬁgures show the linear RKD results for the matched sample, with endline employment set to zero for exiting ﬁrms. Circles plot the average outcome variable for ﬁrms in one-unit bins based on initial distance from the cuto↵. Fit lines are based regression lines for ﬁrms within ten units of the cuto↵. Black lines for Saudization percentage and for Saudi and expatriate employees show full-compliance benchmarks.
Figure IX: Composition of New Entrants Relative to Quota: July 2011 and October 2012
Notes: This ﬁgure shows the distribution of ﬁrms relative to distance from the cuto↵ (in terms of Saudi employee percentage) at entry for ﬁrms that entered the market in July 2011 (solid line) and ﬁrms that entered in October 2012. There were 5,276 new entrants in July 2011 and 8,634 new entrants in October
2012. Kolmogorov-Smirnov test p-value: 0.001 Figure X: Strategic Firm-Level Hiring Patterns: Employment of Saudis and Expatriates over the Nitaqat Period
Notes: Panel (a) shows the kernel density of the distribution of ﬁrms by size in July 2011 and in October
2012. Panel (b) shows the same density ﬁgure for only ﬁrms that appear in the baseline data, with Green and Platinum ﬁrms on the left and Red and Yellow ﬁrms on the right. Panel (c) shows the percentage of ﬁrms that exited the sample between July 2011 and October 2012 by initial number of employees. Yellow circles shows the exit rates for Yellow/Red ﬁrms and green circles show the rates for Green/Platinum ﬁrms.
Notes: This table shows the total number of workers employed at firms in each color band Notes: This table shows the total number The sample includes employees atcolorfirms that were inand in July 2011 and October 2012. of workers employed at ﬁrms in each all band in July 2011 October 2012. The sample period. employees at all ﬁrms that were in the sample in either period.
the sample in either includes
Notes: This table provides sample statistics on the number of firms in each of 37 industries and 4 size categories at baseline (July 9, 2011). Of the firms in the baseline sample, 1,027,017 were too small to be included in the Nitaqat program (fewer than ten employees). The fifteen industry classifications that were added in later versions of Nitaqat were road transport of goods within cities; road transport of goods between cities; laboratories; governmental and private schools (boys; mixed gender); security escorts;
private employment offices; kindergarten; bakeries; ready-mixed concrete; information technology;
governmental construction contractors; governmental hygiene contractors; petrol stations; and stone, granite and brick.
Notes: This table provides sample statistics on the composition of the workforce by industry at baseline (July 9, 2011). Column 1 counts the number of firms in each industry category, and column 2 the number of employees at firms in those industries. Column 3 sorts industries by their share of the total private-sector workforce.
Columns 4 and 5 report the number of Saudi workers in each industry and the share of workers in that industry in the total Saudi private sector workforce. Column 6 calculates the share of workers in each industry that are Saudi nationals, i.e. the overall industry Saudization rate. The last line reports the same statistics for the firms that were too small to be included in the Nitaqat program (less than ten employees).
Notes: This table provides sample statistics on the composition of the workforce by size group at baseline (July 9, 2011). Column 1 counts the number of firms in each size category, and column 2 the number of employees at firms in those categories. Column 3 lists the category share of the total private-sector workforce. Columns 4 and 5 report the number of Saudi workers in each size group and the share of workers in that group in the total Saudi private sector workforce. Column 6 calculates the share of workers in each size category that are Saudi nationals, i.e. the overall category Saudization rate.
Notes: This table gives the full set of results for the RKD estimates on the full set of ﬁrms in the data in July 2011.
For Saudi employees the running variable is distance from the cuto↵ in terms of number of Saudis. For expatriate employees the running variable is distance from the cuto↵ in terms of number of expatriate workers. For ﬁrm size the running variable is Saudization percentage point distance from the cuto↵. The number of employees in all categories ! 48 is set to zero for ﬁrms that exit the market between July 2011 and October 2012. Bandwidth is based on the units of the running variable. The largest and smallest 1% outliers in outcome variables are dropped for the Saudi and expatriate regressions and the largest 1% increases from the ﬁrm size regressions.