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———. 2020. “Aspirations and Economic Behaviors.” _Annual Review of Economics_ 12: 715–746.

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# Labor Market Policies and Unemployment in Morocco: A Quantitative Analysis

Pierre-Richard Agenor and Karim El Aynaoui* The World Bank, Washington DC 20433 JEL Classification Numbers: C68, D58, 011

> *We are grateful to participants at presentations in the Ministry of Finance in Morocco, Cairo University, and the University of Casablanca for helpful<sup>commentsonan</sup> earlier version, and to Abdelkhalek Touhami for constructing the social accounting<sup>matrix</sup> that underlies the model. Dominique van der Mensbrugghe, Henning Jensen, and Nihal Bayraktar provided excellent technical advice and assistance.
the model does not account for the coexistence, in a long-run equilibrium, of both types of activities, possibly with imitation requiring only workers with basic skills and basic capital, and true innovation requiring both advanced skills and advanced public capital.<sup>34</sup> While the resulting model may well prove intractable analytically, its properties can be studied numerically. An interesting question in that context is under what conditions would both types of activities coexist, and only one type would prevail. We suspect that some of the channels identified in the present paper will matter (especially the composition of public capital), but this remains to be examined more carefully.

Notwithstanding these extensions, it is our belief that as it stands this paper sheds some useful new light on the ongoing debate on middle-income growth traps and on policies to avoid them. Put in a broader perspective, our view is that for a low-income country the provision of basic infrastructure is essential to initiate the transfer of labor from agriculture to manufacturing, and facilitate the adoption, adaptation, and diffusion of pre-existing technologies imported from more advanced countries. There is also a learning-by-doing effect in the process, which promotes human capital accumulation and productivity in general. Indeed, knowledge may grow in part because of imitation of foreign products, even though this may occur with decreasing returns. However, beyond this initial stage, to sustain productivity growth and avoid a growth slowdown, it is critical to invest in the type of infrastructure that will generate strong marginal benefits in terms of knowledge diffusion and knowledge networks.

> 34Studies that focus on the transition from imitation to innovation include Walz (1996), Currie et al. (1999), Perez-Sebastian (2007), Mondal and Gupta (2009), and Iacopetta (2010). However, none of them discussed the role of public capital in that context.

27
years, there have been several attempts to improve the TOT regime, including changes in rates and thresholds, which we exploit for identifying variation. We also implement a randomized experiment with over 10,000 TOT payers that tests an alternative design of an STR that aims to better balance the objectives of revenue collection, simplicity, and equity. This analysis is complemented by two surveys, one of registered small businesses and the other of TOT payers,<sup>2</sup> which helps to unpack the mechanisms behind the behavior of taxpayers.

Three key design features of STRs that influence the trade-offs that policy makers face are the level of minimum exemption thresholds, whether businesses are required to pay a set fee or a percentage of their turnover, and the size of tax obligations. When minimum exemption thresholds are set very high, this theoretically simplifies the regime for the smallest businesses as they are no longer required to pay tax, and revenue authorities do not need to register and maintain large databases of very small businesses; however, this reduces the total tax revenue that could be collected. Requiring all small businesses to pay a set fee (i.e., a lump-sum payment) makes tax obligations simpler and generates revenue, but this is quite regressive as the effective tax rate is inversely related to the size of business income. Requiring small businesses to pay a percent of their firm-specific turnover is a more equitable way of collecting revenue than requiring them to pay a set fee; however, this introduces greater complexity as small businesses often do not have extensive transaction records. Underlying all these trade-offs is the size of the tax obligations that small businesses must pay. When there is a desire to maintain equity across tax types, there is a need to consider how STRs relate to corporate or personal income tax regimes, particularly to ensure that as businesses grow, they are not discouraged from graduating to the corporate income tax (CIT) regime.

We conduct a comprehensive review of STRs across Sub-Saharan Africa, which shows that governments have implemented these regimes in a wide variety of ways, resulting in stark differences in how trade-offs between revenue collection, simplicity,

> 2Small businesses that are registered with the government may or may not be registered with the revenue authority as a TOT payer.

2
ZIMBABWE‘S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE wastewater services from the ZINWA to local governments, and the capital city water services to Harare Water, is an important step to restore coverage and service quality to pre-ZINWA levels.

**Figure 10. Distribution losses and labor productivity among southern African utilities**

<!-- Start of picture text --> Latest available year<br>a. Distributional losses (percentage of production) b. Labor productivity (connections per employee)<br>50 1000<br>45 900<br>40 800<br>35 700<br>30 600<br>25 500<br>20 400<br>15 300<br>10 200<br>5 100<br>0 0<br>Percentage of production Connections per employee<br>Mozambique, Av. Zimbabwe, ZINWA Zambia, Av. Swaziland, SWSC Malawi, Av. Madagascar, JIRAMA Lesotho , WASA South Africa , Av. Namibia, Av. Botswana, WUC SSA Madagascar, JIRAMA South Africa , Av. Namibia , Av. Zambia, Av. Lesotho , WASA Zimbabwe, ZINWA Mozambique, Av. Swaziland, SWSC Malawi, Av. SSA<br><!-- End of picture text --> _Source:_ AICD water and sanitation utilities database (www.infrastructureafrica.org/aicd/tools/data). _Note:_ Per water connection. Zimbabwe data is for 2008; SSA = Sub-Saharan Africa.

Another problem is that water tariffs do not cover costs. At an estimated $0.23 and $0.82 per m<sup>3</sup> for residential and nonresidential tariffs, respectively, the ZINWA‘s tariffs are below the tariffs reported in other water-scarce countries in Africa and other developing regions in the world (see table 7).

About 60 percent of total water and sanitation sector spending needs comes from urban areas. This is due to the relatively rapid population growth in urban as opposed to rural areas (1.4 percentage points per annum versus 0.2 percentage points) and due to the prevalence of more costly higher-end water and sanitation solutions in urban areas (such as piped water and flush toilets). Water accounts for 87 percent of total needs, while sanitation accounts for the rest. Around 70 percent of sanitation needs are in the rural areas (table 8).

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explained by the adoption of high-yielding varieties and the intensive use of fertilizer. In SubSaharan Africa, the average rate of agricultural growth was 3 percent over the same period but growth per capita of the agricultural population (a broad measure of agricultural income) was 0.9 percent, less than half the growth rate in other regions. Moreover, whereas agricultural growth during the Green Revolution in Asia was driven by intensification, agriculture in Sub-Saharan Africa has been growing mostly as a response to land expansion and yields have been stagnant. Since the potential for land expansion will soon be exhausted, further agricultural growth will have to come from increased yields.<sup>7</sup> What needs to be done in order to achieve higher yields and, hence, agricultural growth in Sub-Saharan Africa?<sup>8</sup> The consensus about the need for a Green Revolution for Africa is universal but the characteristics of the African continent call for a different approach to the transformation of agriculture. In comparison with Asia, Africa is heterogeneous in terms of agro-ecological conditions, farming systems and types of crops planted. The FAO considers that there are 14 main farming systems in Sub-Saharan Africa. They depend rather weakly on rice or wheat, which have been the drivers of the Asian Green Revolution. Moreover, most agriculture is rainfed (de Janvry and Sadoulet 2009a) whereas the Green Revolution in Asia was partly driven by intensive irrigation. In fact, only 4 percent of crop area in Africa is irrigated, versus 34 percent in Asia. Another factor that makes the Sub-Saharan African context different is the underdevelopment of infrastructure, which hinders market access and leads to high transportation costs. As a consequence of the heterogeneity across Sub-Saharan Africa, several geographically separate revolutions will have to take place, in contrast to the Asian Green Revolution, which was based on wheat and rice (Staatz and Dembele 2007).

In order to understand past developments in agriculture and predict future ones, the mechanisms behind agricultural development and growth must be identified. Schultz (1964) formulated the idea that peasants are rational decision-makers maximizing the returns from the resources at their command and responding to incentives. Many of them remain poor not because they are ―backward‖ but because their government provides them with few technical and

> 7 The source of agricultural growth also matters for its impact on poverty reduction. Agricultural growth in East Asia has been achieved with technologies increasing labor productivity and has led to large reductions in poverty. By contrast, in Africa, where labor productivity gains in agriculture have been small and most growth has come from land expansion, poverty reduction has also been low (de Janvry and Sadoulet 2009b).

> 8 This discussion owes much to Binswanger-Mkhize and McCalla (2010).  Numbers are from the 2008 World Development Report.

14
# Table 8: First-stage results using 1994 industrial conditions from female-owned businesses

|||Incumbe|<br>nt industrial con|ditions in 2000 a|nd 2005||
|---|---|---|---|---|---|---|
||o tota|o|o tota|o|aor|nut-outut|
||<br>incumbent<br>employment|female-owned<br>incumbent<br>businesses|<br>incumbent<br>employment|female-owned<br>incumbent<br>businesses|market<br>strength,<br>female-owned<br>businesses|market<br>strength,<br>female-owned<br>businesses|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Log total incumbent employment in|**0.177+++**|0.093+++|**0.174+++**|0.091+++|0.022++|0.029+++|
|district-industry in 1994|**(0.016)**|(0.020)|**(0.016)**|(0.020)|(0.010)|(0.010)|
|Log female-owned incumbent businesses|0.094+++|**0.286+++**|0.071+++|**0.259+++**|0.027+++|-0.000|
|in district-industry in 1994|(0.014)|**(0.024)**|(0.016)|**(0.027)**|(0.011)|(0.010)|
|Index of labor market strength, female-|||0.058++|0.102+++|**0.177+++**|0.031+++|
|owned incumbent businesses in 1994|||(0.024)|(0.039)|**(0.022)**|(0.011)|
|Index of input-output strength, female-|||0.037|-0.014|0.029|**0.198+++**|
|owned incumbent businesses in 1994|||(0.046)|(0.063)|(0.026)|**(0.067)**|
|Observations|4,336|4,336|4,336|4,336|4,336|4,336|
|F Statistic|105|104|55|54|31|17|
|Partial R-squared|0.074|0.076|0.076|0.078|0.078|0.068|
|Shea Partial R-squared|0.023|0.024|0.021|0.022|0.034|0.041|

Notes: See Table 6. Estimations report first-stage results from instrumenting district-industry incumbent conditions with incumbent conditions in 1994. Conditional estimations include district-year and industry-year fixed effects.
35

# 11. Ibid.

12. These fees provide a basic indication to what can be the higher--and at times prohibitively so--cost of doing business officially. Nevertheless, enterprises still "chose" to pay high unofficial fees rather than to stay in the official economy.

# 13. Some of these "protection" fees also need to be paid by firms operating officially.

# 14. See Kaufmann, et al., "The Evolution of Ukraine's Administrative Controls," forthcoming.

15. The unwillingness (or delay) to come back to the official economy can be conceptualized in terms akin to a hysteresis effect, in which there is an option value of waiting, while uncertainty is (partly) being resolved (e.g., further information about costs and benefits in each "state" is being gathered, etc.). See Avinash K. Dixit and Robert S. Pindyk, **Investment Under Uncertainty** (Princeton, NJ: Princeton University Press, 1994).

16. Kaufmann, et al., "The Evolution of Ukraine's Administrative Controls," forthcoming.

17. Johnson, Kaufmann, and Ustenko, "Winners, Losers and Survival Strategies." 18. Dobozi and Pohl, "Real Output Decline in Transition Economies." 19. This discussion of the potentially biasing factors draws substantially from Dobozi and Pohl, ibid.

20. Dobozi and Pohl, ibid., maintain the unitary elasticity assumption throughout their calculations. A number of criticisms have been leveled against the unitary elasticity assumption in their calculations; see Vincent Koen's and Lev Freinkman's letters to the editor in **Transition** Newsletter. We relax this assumption and provide a more differentiated classification in the second and third scenarios presented.

21. See Dale Gray, "Reforming the Energy Sector in Transition Economies: Selected Experience and Lessons," World Bank, Discussion Paper No. 296, 1995; and Caroline L. Freund and Christine Wallich, "Raising Household Energy Prices in Poland: Who Gains? Who Loses?" World Bank, Working Paper No. 1495, 1995.

22. As of late 1995, Russian national accounts were undergoing a significant revision in order to incorporate unofficial activities. This does not affect the official figures we utilized, which were received up to mid-1995.

23. Valeriy M. Rutgaizer, Gregory Grossman, Vladimir G. Treml, et al., "Studies on the Soviet Second Economy," various reports, 1986-91. Also, see various estimates in Janine Braithwaite, "From Second Economy to Informal Sector: The Russian Labor Market in Transition," mimeo, World Bank, 1994.
# Table 4: Program Impact on New Enrollment

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|---|---|---|---|---|---|---|---|---|---|
|||6-15 years old|||6-12 years old||1<br>|3-15 years ol<br>|d<br>|
||All|Boys|Girls|All|Boys|Girls|All|Boys|Girls|
|Meals*Follow-up|0.017|-0.015|0.049|0.012|-0.034|0.064|0.025|0.059|-0.005|
||[0.019]|[0.028]|[0.025]**|[0.023]|[0.034]|[0.031]**|[0.025]|[0.042]|[0.028]|
|Rations*Follow-up|0.062|n.a.|0.056|0.065|n.a.|0.065|0.049|n.a.|0.029|
||[0.021]***|n.a.|[0.025]**|[0.026]**|n.a.|[0.031]**|[0.023]**|n.a.|[0.023]|
|Follow-up|-0.153<br>[0.014]***|-0.16<br>[0.021]***|-0.147<br>[0.019]***|-0.178<br>[0.017]***|-0.178<br>[0.025]***|-0.179<br>[0.023]***|-0.066<br><sup>[0.020]***</sup>|-0.092<br><sup>[0.035]***</sup>|-0.042<br>[0.021]**|
|Girl|-0.041|||-0.045|||-0.037|||
||[0.009]***|||[0.011]***|||[0.013]***|||
|Constant|0.177|0.173|0.137|0.191|0.186|0.145|0.069|0.045|0.057|
||[0.014]***|[0.022]***|[0.016]***|[0.016]***|[0.025]***|[0.017]***|<sup>[0.014]***</sup>|[0.028]|[0.018]***|
|Observations|6587|2537|4050|5097|1967|3130|1490|570|920|
|R-squared|0.12|0.14|0.11|0.11|0.15|0.09|0.1|0.13|0.14|

## Robust standard errors in brackets

* Significant at 10%; ** significant at 5%, *** significant at 1% Dependent variable is whether the child started school in survey year. Regressions also control for child age, orphanhood, parents education, ethnicity, religion, household assets and village fixed effects (not reported).

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<!-- Start of picture text --> 0.49<br>0.48 — -Data<br>—, 0.47<br><<br>wv” 0.46 ------ -----HKe<br>3<br>L 0.45<br>5<br>O 0.44<br>0.43<br>0.42) 5 10 15 20<br>Flat Tax Rate (%)<br><!-- End of picture text --> <!-- Start of picture text --> 0.65<br>0.64 — -Data<br>068<br>no<br>_= 0.62<br>0.61<br><= nie ele eee<br>5 0.6<br>Oo 0.59<br>0.58<br>0.57() 5 10 15 20<br>Flat Tax Rate (%)<br><!-- End of picture text -->
- 37 -

- (e) Forest services need to revise their fees and taxes often. The Zambian fees quoted in Table 3.1 were published about eight years after they were first proposed, and therefore were out of date as soon as they came into effect. In Sudan, stumpage rates and other forest fees have not been revised since the 1930s. As forest service fees generally have to be approved by the government in developing countries, the issue of fee revision can become politically sensitive, and the process is usually slow. But in most cases, if realistic stumpage fees were set and the charges properly collected, the money obtained would more than pay for an improved forest service, and investments in wood production.

Table 3.1: ZAMBIA 1988 - FEES AND PRICES FOR FOREST PRODUCTS (Revised March 25, 1988) Part I

||Pe<br>--|r tree<br>----Un|<br>Per Cubic Meter<br>its/Kwacha<br>a/------|
|---|---|---|---|
||A Timber|||
|001|Afzelia<br>quanzensis|35.00|<br>80.00|
|002|Alvizia<br>species|25.00|<br>60.00|
|003|Balklaea<br>pluriJuga|37.00|<br>90.00|
|011|Pterocarpus<br>angolensis|40.00|<br>100.00|
|012|Other species|12.00|<br>20.00|
||B Poles b/||Kwacha|
|021|PG es not exceeding<br>14 cm butt diameter|s|0.20 each|
|022|Poles between<br>15 and 19 cm butt diamete|rs|0.50 each|
|025|Bamboo||1.50 per 20 canes|
||C Fuel from Indigenous<br>Trees||Kwacha|
|0.31|Stacked In cubic meter or Just stacked||3.00 per m3 stacked|
|0.32|In cords 1mxlmx 3 m||8.00 per stacked<br>cord|
|0.33|In headloads||2.50per5headloads|
|0.34|Charcoal<br>c/||0.50per standard<br>bag|
||D Hut Materiel||various<br>products<br>and prices|
||E Miscellaneous||various<br>products<br>and prices|

Part 11 Fees and Services various services and fees Part _ilI_ Honey and Beeswax various grades and charges a/ Official exchange rate (May 88) K7.86 * USSI (Feb. 89) K10.00 * USSI. Parallel market r.te (May 88) K30-K40 * USSi (Feb. 89) K80-100 a USSi.

b/ Length of poles nt specified c/ The standard bag may vary between 35 kg and 40 kg. Also there Is a removal fee of KOo50 per bag.

Source: Zambia Gazette dated March 25, 1988.
# **5. Conclusions**

In conclusion, there is strong evidence of a direct impact of concession schools in reducing dropout rates. There is also some evidence of an indirect impact of the concession schools on the dropout rates in nearby regular public schools. Furthermore, there is evidence of a positive impact on test scores of students in concession schools when compared with students in other public schools.

Moreover, as discussed previously, there is some evidence of downward bias in the estimations. Indeed, OLS estimators are lower than the matching estimators. This finding strengthens one important idea of the paper: given that propensity and matching estimators correct only partially the sources of bias, presumably the effects of concessions are larger than the ones presented here.

The results for dropout rates are especially important in light of the current situation in the country. The enrollment rate in secondary education in the cities is reaching levels of 85 percent but the dropout rates are higher in the transition from primary to secondary education. Concession schools seem to be a promising intervention for reducing desertion from schools at this critical juncture. However, as public investment in each concession school is around $2.5 million, it is important to perform a cost-benefit analysis.

The test score results are also promising, especially considering that they are just the initial impacts. The concession schools program started in 1999, four years before the test score data were collected. Individuals who took the exam were in grade 11, and therefore, they most likely transferred into the concession schools in grade 8. Presumably, the impact on individuals who start in a concession school from grade 1 onward will be higher.

Instruments for improving the quality of education are limited. In fact, the educational sector in Colombia, and most likely in several other countries, is subject to inflexible policies adopted in the past under different conditions. Concession schools are an option that may be able to generate consensus as a positive measure. However, the potential scale of any such program may be limited. The program relies on private, high quality schools to manage public schools.

27