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28
# Table A2. 15. Tariffs trade barriers

||**Tarif**|**fs trade b**|**Codi**<br>**arriers**|**ng of answers**|||**Bulgaria**|**Romania**|**Croatia**|**Albania**|**OECD**|**EU15**|**Poland**|**Slovak Republic**|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**Average production-weighted tariff**|<=3%|<=6%|<=9%|<=12%<br><=15%|<=18%|>18%|8.6|15.8|4.9|5.7|5.5|7.4|13.4|5.1|
|**Country scores (0-6)**|0|1|2|3<br>4|5|6|2.0|5.0|1.0|1.0|1.4|1.0|4.0|1.0|

# Table A2. 11. Regulatory barriers to trade and investment

## **Regulatory barriers**

||**_Question_**<br>**_weights_**<br>**_(c k )_**|**_Yes_**<br>**Coding of a**|**_No_**<br>**nswers**|**Bulgaria**|**Romania**|**Croatia**|**Albania**|**OECD**|**EU15**|**Slovak**<br>**Republic**|**Poland**|
|---|---|---|---|---|---|---|---|---|---|---|---|
|The country has engaged in Mutual Recognition||||||||||||
|Agreements (MRAs) in at least a sector with any other<br>country|2/5|0|6|yes|yes|**yes**|yes|na|na|yes|yes|
|There are specific provisions which require or<br>encourage regulators to consider recognizing the||||||||||||
|equivalence of regulatory measures or the result of<br>conformity assessment performed in other countries,<br>wherever possible and appropriate|4/15|0|6|yes|yes|**no**|yes|na|na|no|no|
|There are specific provisions which require or||||||||||||
|encourage regulators to use internationally harmonized<br>standards and certification procedures wherever<br>possible and appropriate|2/9|0|6|yes|yes|**no**|yes|na|na|yes|yes|
|There are any specific provisions which require or<br>encourage regulatory administrative procedures to<br>avoid unnecessary trade restrictiveness|1/9|0|6|yes|yes|**yes**|yes|na|na|yes|yes|
|**Country scores(0-6)**||kckanswerjk||0.00|0.00|**2.93**|0.00|0.22|0.18|1.60|0.00|

54
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35
-22-

US$1 million for works and below US$500,000 for goods. The procurement of works up to a ceiling of US$50,000 would be done by the urban local governments of the project towns, Dar es Salaam and Dodoma with the assistance of the PSUs (which will also be responsible for other project related functions; see para. 3.5).

3.13 Table 3.1 summarizes the estimated costs and procurement methods of the works, goods and services to be financed under the project. Both International Competitive Bidding (ICB) and National Competitive Bidding (NCB) would be used for the procurement of civil works, while ICB, NCB, National Shopping would be used for goods. Agreement was reached with the Government during negotiations that adequate organizational capacity for procurement, satisfactory to IDA, will be established in the PMU and the PSUs for the duration of the project. Adequate procurement arrangements would consist of a full-time Procurement Specialist as head of the procurement unit, responsible for all procurement in PMU, and a sufficient number of full-time procurement officers to undertake the substantial procurement work load. The detailed organizational arrangement for procurement, the flow of documentation for decision

**Table 3.1: Summary of Procurement Arrangements** (US$ Million Equivalent)

|**t:Descriptiong:**<br>i;;L;:;g|:g;**ICB**|**NCB**|**Other**|**Non-Bank**<br>**EFinanced**|**Total**|
|---|---|---|---|---|---|
|Civil Works|29.6|34.8||14.4|78.8|
||(23.1)|(33.1)|||(56.2)|
|Goods|8.40|6.80|1.4|2.5|19.1|
||(8.40)|(6.80)|(1.4)||(16.6)|
|Consulting Services|||13.6|4.9|18.5|
||||(13.6)||(13.6)|
|Training|||1.5|0.3|1.8|
||||_(1.5)_||(1.5)|
|Studies|||6.9||6.9|
||||(6.9)||(6.9)|
|O&M Costs 1|||8.6||8.6|
||||(3.8)||(3.8)|
|Incremental Operating|||5.7||5.7|
|<br>Costs2|||(4.5)||(4.5)|
|Refunding of PPF|||1.9<br>(1.9)||1.9<br>(1.9)|
|TOTAL::|**38**|41.6|39.6|22.1|**141.3**|
|**.. . ... .**<br>**.t**.tt;**.**<br>ttt t(31..)||(39.9):|:(33.6)||(1050)|

# **_Note: Figures in parentheses are the anounts to befinanced by IDA.._**

- 1/ Expenditures incurred for operation and maintenance of the assets to be created or rehabilitated under the project (see para. 4.20 and Chart 1) through civil works and goods contracts procured through NCB.

- 2/ Expenditures incurred for fuel, maintenance and insurance of vehicles, office supplies and minor office equipment, utilities and travel and field allowances for project staff approved by IDA. Only the portion of operating costs that would be financed by IDA is shown as a project cost.
the civil society leaders interviewed in our surveys are representative of community leaders within these villages, but they are only rarely the leaders who were actually trained alongside the village head. In our analysis, we focus on the effect of the intervention on all the independent civil society leaders included in our sample, thereby capturing the extent of changes to this group of leaders in treated villages.<sup>23</sup> The effect of the intervention on civil society leaders as a group is both of theoretical interest in understanding the total horizontal pressures on village heads, and it is an identifiable effect, in the sense that it is possible to measure without knowing which civil society leader would have been selected for training had villages not assigned to the civil society leader treatment arm instead been assigned to it. However, outcomes measured at this level may not be sensitive enough to detect changes that affected only the trained civil society leader.<sup>24</sup> The first mechanism through which civil society leaders could encourage reform is by competing with the village head to offer services to villagers, thereby allowing villagers to select among them as service providers and motivating both sets of leaders to offer better terms in order to keep clients. If competition is the mechanism driving village-level reforms, we would expect to see an increase in civil society leaders independently offering services in the same domains as the village head as a result of the training. In table 11, we present data that suggests this did not generally occur. This top row shows other civil society leaders were slightly less likely to be involved in distributing food aid in villages where a civil society leader was trained. The second row shows that, across all treatment arms, household respondents rarely said they would take land or livestock disputes to community leaders other than the village head for resolution, and the training of a civil society leader had little additional effect. The bottom row shows that household respondents were slightly less likely to contact civil society leaders other than the village head for assistance in villages where a civil society leader was trained. Thus, civil society leaders do not appear to have improved local governance by competing with the village head to provide services.

The remaining two mechanisms – capacity upgrading and monitoring – are distinguished by the fact that the first involves only changing capacity to implement reforms the village head already favors and the second also involves changing their incentives to implement reform. Both of these mechanisms share two observable implications: the trained civil society leaders should have more information about village-level

> 23In our survey of civil society leaders, we also sampled dare members. Because they were not eligible to be the “civil society leader” included in the training, we exclude them from analyses in this section. 24We estimate there were about 5 eligible civil society leaders per village.

30
# **1.  Introduction**

Financial inclusion refers to the ownership and use of financial products to enable personal financial wellbeing. Research shows that having and using a financial account creates significant economic benefits for individuals, households, and small businesses by enabling people to safely manage their finances, increase savings, access credit, and receive money from friends or family (Moore, et al., 2019). These benefits help account owners weather financial ups and downs and capture economic opportunities more effectively than their unbanked peers. As a result, organizations such as the World Bank, the United Nations, and the G20, as well as government financial ministries around the world, have made financial inclusion a cornerstone of their development policies.

However, significant barriers limit access to appropriate and affordable financial services for unbanked adults. Women, people with low incomes or low education, and adults who are out of the workforce are all more likely than men and higher-income, more educated adults to be unbanked and confront barriers to access and usage. If left unmediated, the lack of access to financial services creates a damaging cycle, whereby the people who are already the most vulnerable to poverty lack access to the financial tools and resources that could help them avoid it. Yet recent innovations, as well as new government-led interventions, have shown that overcoming access barriers is possible when accounts are affordable, practical, and convenient. This paper provides an overview of how global financial inclusion reduces poverty and improves outcomes, and how both technology and government-led programs are helping to increase access. The paper starts by highlighting available evidence about the benefits of account access and usage and an overview of the state of financial inclusion worldwide, followed by a discussion of the policies, products, and incentives that will be needed to safely expand financial access for positive development impact. Throughout, we highlight the impact of the pandemic and digital technology on recent advances in financial inclusion.

# **_2._ Account ownership and development outcomes**

Around 76 percent of adults worldwide had a financial account as of 2021, according to the Global Findex database (2021). This represents a 50 percent increase from the worldwide 2
program transfer acts as an income shock, rather than changing applicants’ school choices through other channels.

# **4.1**

We first document important differences across high school tracks in terms of the costs associated to school attendance. First, the average yearly tuition fees of a vocational option in the COMIPEMS system amount to 3,986 MX$ (13 percent of the average household income in our sample), as opposed to 2,644 MX$ for a technical option costs and 3,521 MX$ for an academic option (see Panel a in Table 5). The average difference in tuition costs between vocational and technical options is therefore substantial as it accounts for roughly 5 percent of the average household income.

Second, vocational options tend to be situated further away from applicants’ places of residence when compared to technical and academic options (see Panel a in Table 5 and Fig. 1). For instance, the closest technical school is located on average 2 Km away from applicants schools of origin, whereas the closest vocational school is located 3.2 Km away. Taken together, these two pieces of evidence suggest that, especially relatively to the technical track, the vocational track may entail a higher financial burden for the poor households in our sample - in terms of both tuition and transportation costs.

We next provide evidence on the labor market returns associated to each high school track. We start by computing the average hourly earnings in 2008 for employed individuals aged 16-35 who reside in urban areas of the State of Mexico and the Federal District. Among individuals with completed secondary and no tertiary education, average hourly earnings are 14 percentage points higher for those who attended the vocational track vis-a-vis the academic and technical tracks. Perhaps not surprisingly, the opposite holds for individuals with tertiary education: hourly earnings are 8-10 percentage points lower for those who attended the vocational track (see the fourth and fifth row of Panel a in Table 5).<sup>20</sup> The higher labor market returns of the vocational track among individuals with secondary

> 20A similar pattern emerges using the nationwide urban sample of the ENOE in the context of Mincer-type regressions, which also control for (potential) experience. The corresponding OLS estimates indicate that the vocational track is associated with a positive return of 0.057 (std. err.=0.021) for individuals with secondary education and a negative return of 0.125 (std. err.=0.034) for those with tertiary education.

17
|Registered when started||0.040||0.047||0.003||0.039|
|---|---|---|---|---|---|---|---|---|
|Y:1 N:0||(0.209)||(0.209)||(0.206)||(0.208)|
|Legal form fixed<br>||Yes||Yes||Yes||Yes|
|effects|||||||||
|Visited by tax officials||-0.014||-0.031||-0.048||-0.040|
|Y:1 N:0||(0.105)||(0.106)||(0.109)||(0.106)|
|Employment growth||-0.216||-0.257||-0.241||-0.251|
|rate (per annum, log||(0.304)||(0.298)||(0.304)||(0.298)|
|difference)|||||||||
|Bought assets last year||0.131||0.116||0.115||0.117|
|Y:1 N:0||(0.124)||(0.121)||(0.123)||(0.121)|
|GDP per capita growth||0.030||-0.007||0.004||-0.021|
|rate (%, annual)||(0.030)||(0.030)||(0.031)||(0.032)|
|Primary enrollment||-0.179**||-0.193**||-0.173**||-0.175**|
|gender parity index||(0.070)||(0.081)||(0.076)||(0.080)|
|% of women in 35-64||0.335*||0.627***||0.436**||0.526**|
|years age group||(0.188)||(0.209)||(0.214)||(0.229)|
|Total population (logs)||-1.763||-0.511||-1.244||-1.283|
|||(1.298)||(1.349)||(1.448)||(1.486)|
|Country fixed effects|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Year fixed effects|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Industry fixed effects|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Number of|15,132|15,132|15,460|15,460|15,219|15,219|15,460|15,460|
|observations|||||||||
||||**Panel B: Ma**|**rginal effect**|||||
||**Total cred**<br>**sec**|**it to private**<br>**tor**|**Bank cre**<br>**depos**|**dit to bank**<br>**it ratio**|**ATMs p**<br>**ad**|**er 100,000**<br>**ults**|**Bank br**<br>**100,00**|**anches per**<br>**0 adults**|
|Financial development|0.255***|0.254***|0.067***|0.046*|0.051***|0.062***|0.069***|0.054**|
|measure as above|(0.045)|(0.067)|(0.022)|(0.024)|(0.011)|(0.018)|(0.020)|(0.024)|
|Controls(as above)|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|

All coefficient values are log odds ratios obtained from logit estimation. Huber-White robust standard errors clustered on country in brackets. *** (1%), ** (5%), * (10%).

39
**Table 3:  Weights Used to Aggregate Individual Data Sources in 2007 WGI**

|**VA**<br>**Commercial Business Information**|**PV**<br>**Providers**|**GE**|**RQ**|**RL**|**CC**|**Average**|
|---|---|---|---|---|---|---|
|**bri**<br>..|0.058|0.092|..|0.067|0.006|0.056|
|**dri**<br>..|0.116|0.030|0.024|0.025|0.019|0.043|
|**eiu**<br>0.071|0.126|0.084|0.063|0.104|0.050|0.083|
|**ijt**<br>..|0.094|..|..|..|..|0.094|
|**mig**<br>..<br>|0.074<br>|0.040<br>|0.038<br>|0.052<br>|0.126<br>|0.066<br>|
|**prs**<br>0.047|0.057|0.061|0.062|0.021|0.021|0.045|
|**qlm**<br>..|..|..|..|0.074|0.076|0.075|
|**wmo**<br>0.033|0.162|0.112|0.123|0.092|0.047|0.095|
|**Surveys of Firms or Households**|||||||
|**afr**<br>0.022|..|0.055|..|0.013|0.013|0.026|
|**bps**<br>..|..|0.001|0.000|0.001|0.021|0.006|
|**gcb**<br>..|..|..|..|..|0.006|0.006|
|**gcs**<br>0.007|0.029|0.065|0.042|0.060|0.045|0.041|
|**gwp**<br>0.002|..|0.006|..|0.003|0.006|0.004|
|**lbo**<br>0.001|..|0.001|..|0.004|0.000|0.001|
|**prc**<br>..|..|..|..|..|0.064|0.064|
|**vab**<br>0.018|..|..|..|0.025|0.008|0.017|
|**wcy**<br>0.005|0.033|0.048|0.056|0.062|0.072|0.046|
|**Non-Governmental Organization D**|**ata Provider**|**s**|||||
|**bti**<br>0.120|..|0.047|0.084|0.013|0.042|0.061|
|**ccr**<br>0.177|..|..|..|0.006|0.002|0.061|
|**egv**<br>..|..|0.008|..|..|..|0.008|
|**frh**<br>0.178|..|..|..|0.110|0.176|0.155|
|**gii**<br>0.074<br>|..|..|..|0.015|0.002|0.030|
|**her**<br>..|..|..|0.045|0.054|..|0.050|
|**msi**<br>0.048|..|..|..|..|..|0.048|
|**obi**<br>0.029|..|..|..|..|..|0.029|
|**rsf**<br>0.032|..|..|..|..|..|0.032|
|**Public Sector Data Providers**|||||||
|**adb**<br>..|..|0.079|0.170|0.045|0.045|0.085|
|**aeo**<br>0.001|0.032|..|..|..|..|0.017|
|**asd**<br>..|..|0.131|0.038|0.004|0.007|0.045|
|**ebr**<br>..|..|..|0.086|..|..|0.086|
|**hum**<br>0.035|0.067|..|..|0.013|..|0.038|
|**ifd**<br>0.005|..|0.026|0.030|0.013|0.015|0.018|
|**ipd**<br>0.080|0.116|0.050|0.033|0.064|0.082|0.071|
|**pia**<br>..|..|0.049|0.086|0.045|0.041|0.055|
|**tpr**<br>..|..|..|..|0.004|..|0.004|
|**Commercial Business Information**|**Providers**||||||
|Share of Sources<br>0.15|0.58|0.32|0.31|0.27|0.28|0.32|
|Share of Weights<br>0.15|0.71|0.43|0.32|0.44|0.35|0.40|
|<br>**Surveys of Firms or Households**|||||||
|Share of Sources<br>0.30|0.17|0.32|0.19|0.27|0.36|0.27|
|Share of Weights<br>0.06|0.06|0.18|0.10|0.17|0.24|0.13|
|**Non-Governmental Organization D**|**ata Provider**|**s**|||||
|Share of Sources<br>0.35<br> <br>|0.00<br>|0.11<br>|0.13<br>|0.19<br>|0.16<br>|0.16<br>|
|Share of Weights<br>0.67|0.00|0.06|0.13|0.20|0.22|0.21|
|<br>**Public Sector Data Providers**|||||||
|Share of Sources<br>0.20|0.25|0.26|0.38|0.27|0.20|0.26|
|Share of Weights<br>0.12|0.22|0.34|0.45|0.19|0.19|0.25|

31