rafmacalaba/datause-encoder-data huggingface dataset:
counseling help students from poor rural areas go to high school? Evidence from China. _Journal of Comparative Economics_ , _41_ , 1012-1025. doi:10.1016/j.jce.2013.06.004 Lucas, A. M., & Mbiti, I. M. (2012). Access, sorting, and achievement: The short-run effects of free primary education in Kenya. _American Economic Journal: Applied Economics_ , _4_ (4), 226–225. doi:10.1257/app.4.4.226

- Mo, D., Zhang, L., Lui, R., Qu, Q., Huang, W., Wang, J., et al. (2013). _Integrating computerassisted learning into a regular curriculum: Evidence from a randomized experiment in rural schools in Shaanxi_ (REAP Working Paper No. 248). Stanford, CA: Stanford University, Rural Education Action Project.

Nitsaisook, M., & Anderson, L.W. (1989). An experimental investigation of the effectiveness of inservice teacher education in Thailand. _Teaching & Teacher Education_ , _5_ (4), 287-302. doi:10.1016/0742-051X(89)90027-9

- Piper, B., & Korda, M. (2011). _EGRA Plus: Liberia_ (Program evaluation report). Durham, NC: RTI International. Retrieved from http://files.eric.ed.gov/fulltext/ED516080.pdf. Accessed December 16<sup>th</sup> , 2016.

- Pournara, C., Hodgen, J., Adler, J., & Pillay, V. (2015). Can improving teachers' knowledge of mathematics lead to gains in learners' attainment in Mathematics?. _South African Journal of Education_ , _35_ (3), 1-10. doi:10.15700/saje.v35n3a1083

- Spratt, J., S. King, & Bulat, J. (2013). Independent Evaluation of the Effectiveness of Institut pour

- l’Education Populaire’s “Read-Learn-Lead” (RLL) Program in Mali. Menlo Park, CA: The William and Flora Hewlett Foundation. Retrieved from

http://www.educationinnovations.org/sites/default/files/Mali RLL evaluation Endline 41
19 experience with it in the PHN projects of the major donors. The third paper (SWP 662, 1984), also commissioned by the forumer Project Policy Department, looked at the potential for adapting the Bank's training and visit system of agricultural extension to the PHN sector.

# Current Work

Five ralevant studies were under way in mid-1987 in the Population and Human Resources Policy and Research Division. Three of these dealt with the issue of financial incentives. One (Chomitz and Birdsall) was a broad review of the experience to date with both client and provider incentives, and of related conceptual, economic and ethical issues; one (Allison) looked at the potential for using incentives to increase client and provider involvement in IEC activities; and the third (Stevens) was a review of experience in the Ammanpettai program, India, with the payment of incentives to unsterilized, married women for remaining non-pregnant. Of the remaining two studies, one (Chernichovsky and de Leeuw) was a study of the cost-effectiveness of the Indonesian family planning programme, including the relative cost-effectiveness of different service delivery models. The other (Lewis and Kenney) planned to review the role, achievements, and potential of the private sector in family planning.

## Conclusions

A study-by-srudy analysis would be required to assess the value of the above work to the Bank. But the following broad conclusions can be drawn from the overall scope of the subject matter. First, though the range of the studies is impressive, two areas--targeting and qualitative learning--which this paper argues have been given insufficient emphasis in project lending have also received little emphasis in the Bank's policy and research work. Second, that nearly all the studies are desk reviews, reflecting the fact that the Bank has not been engaged in operational research in the field, with the recent exception of the cost-effectiveness study of the Indonesian family planning program. Third, that most of the studies focus on rather broad strategic issues (for example, the pros and cons of community-based distribution of contraceptives) rather than detailed organization and management issues (for example, the kinds of incentives, supervision and training which make outreach workers effective at community-based distribution). The last two conclusions are related, in that the PHN literature, on which most of the studies are based, is deficient in analysis of process issues during implementation.

Specific suggestions for the focus of future studies in the subject area of this paper are made in Section 4 below (Conclusions and Recommendations).

# D. Institutional Issues in the Bank

The focus of Bank work in the PHN sectors is the product not only of the intellectual state of the art in the sectors and of Bank assistance policy, but also of the Bank's institutional context. This partially determines whether and how know-how and policies are disseminated and
firecj = the number of permanent employees that firm j in country c would have let go in fiscal year t in absence of rigid labor regulations.

] emplcj = emplcj + hirecj − firecj.

createcj = max(0, hirecj − firecj).

The term empl<sup>]</sup> cj is the number of full-time permanent employees that firm j in country c would have employed in absence of rigid labor regulations. The job creation figure for the firm, createcj, only takes on non-negative values. In the case that the firm would not have increased the number of permanent full-time employees in the absence of rigid labor regulations, this job creation figure is zero. In the event that the firm would have increased the total number of permanent full-time employees in absence of rigid labor regulations, we say that the increase in the number of employees is the number of jobs that would have been created. The term destroycj measures the number of jobs that would have been destroyed in absence of rigid labor regulations. It is analogous to createcj, but deals with decreases in the number of permanent full-time employees that would have occurred in absence of rigid labor regulations.

In order to gain some intuition about what these statistics measure, consider the following example. Suppose that, in absence of rigid labor regulations, firm A would have hired one employee and fired zero employees. Suppose further that firm B would have hired 100 employees and fired 99 employees. For both firms A and B, it would be recorded that they would have created one job if labor regulations did not exist. Obviously their values for the number of workers that would have been hired and fired are dramatically different. We therefore see from this example that the number of jobs that would be created by making labor regulations more flexible and the number of people who would be hired might be substantially different things. An analogous example would show that the number of jobs destroyed and the number of people fired might be quite different as well.

Now that the relevant statistics have been defined at the firm level, I turn to how I aggregate up to the level of the country. If I had access to a census of firms, aggregation would be a simple matter of summing across all firms. Since different firms had different ex-ante probabilities of entering the sample, some firms "represent" more firms than do others. Now define wcj to be the inverse of the ex-ante probability that 7
sectors and subsectors.

Fifth, since donors delegate aid to ML in the model because of better aid selectivity, we should observe that IDA’s aid allocations are more policy and poverty selective than aid allocations by bilateral donors. Support by the U.S. and other donors for the multilateral development banks enabled them to “depoliticize foreign assistance and avoid strains” in their relations with developing countries” (Gwin, 1997, p. 213). In 1964 eligibility for IDA resources was limited to lowincome members, and this restriction has remained in force since, with few exceptions. “Economic performance,” sometimes defined in terms of “absorptive capacity” for aid, or in terms of macroeconomic, structural and human development policies, has also influenced IDA’s country allocations since its early years. Beginning in 1977, these policy-based criteria for each country were assigned numerical ratings, eventually evolving into today’s Country Policy and Institutional Assessments (CPIA). Over time, the ratings process became more formal and rigorous, and the methods for determining allocations made more transparent. The allocation formula is by design both policy and poverty selective, but the donor representatives to IDA have occasionally adjusted the relative weights given to policy and to poverty considerations, as well as the weights assigned to different aspects of policy (World Bank, 1989, 2001). The emphasis on policy was increased during the 1980s, coinciding with the rise of structural-adjustment lending, and again in the late 1990s as a consensus emerged on the importance of public sector management and governance.

Although the IDA allocation formula in recent decades has been both poverty and policy selective, the Bank’s staff, management and Executive Directors retain sufficient discretion in designing and approving grants and loans that the formula by itself does not ensure selectivity in actual disbursements (Hout, 2007, p. 47). Moreover, it does not by itself allow a comparison with bilateral aid. We therefore test the hypothesis that IDA aid is selective, in absolute terms and in comparison with bilateral aid, using a recipient-year panel dataset for the 1977-2012 period.

Equation (4) specifies the aid allocation rule of donors maximizing aid impact across recipients. The allocation rule depends on relative levels of policy and poverty across recipients. Our measures of policy and poverty are the same as those used by the World Bank in its country allocations of IDA funds. Poverty is measured by (low) GNI per capita in current USD, using the Atlas method to smooth the effects of exchange rates. Policy is measured using the World Bank’s Country Policy and Institutional Assessments (CPIA), updated annually by Bank staff with expertise in the relevant countries and sectors. The CPIA content and methodology has changed somewhat over time. To maximize comparability over time, we use the overall CPIA rating (averaging over all of its component indicators on macro and structural policies, policies for improving human development and 25
After the first year of implementation, some control schools had PEC and some treatment schools did not receive PEC. These cross-overs challenge the exogeneity of the assignment when the internal validity of the experiment was compromised. In this case, causal inferences cannot be claimed for the second and third years of the evaluation. For the first year, the results are valid.

Table 2 shows the number of schools that received between 0 and 5 years of PEC by school year. In the baseline, 50 schools experience PEC at least one year (including treatment and control). After a year of the intervention, only 31 schools did not experience PEC or 53 percent of the control group never had any experience of PEC. The accumulative experience of PEC increased with the intervention among the treatment. The second year of the experiment, the years of PEC increased again. The final year of the intervention, 10 schools had five years of PEC experience, 11 schools had four years of PEC, 23 schools had three years, 24 schools had 2 years, 14 school had only one year of the program and finally 16 control schools never got PEC.

|Table2:Intensity of P<br>|ECImpl|ementatio|n|
|---|---|---|---|
|Intensity<br>2005|2006|2007|2008|
|0 PEC<br>48|31|16|16|
|1 PEC year<br>26|30|17|14|
|2 PEC years<br>24|25|32|24|
|3 PEC years<br>0|12|21|23|
|4 PEC years<br>0|0|12|11|
|5PEC years<br>0|0|0|10|
|Total<br>98|98|98|98|

Source: ENLACE and Evaluation roster The fact that the evaluation was contaminated by the factors mentioned above makes the evaluation invalid after the first year. We use the number of years in PEC the last year of the evaluation and schools are identified since the baseline.

<u>Table 3: PEC Schools by Years in PEC</u>

|Intensity|Baseline|2008|2012|
|---|---|---|---|
|0 PEC|48|16|2|
|1 PEC year|26|14|22|
|2 PEC years|24|24|13|
|3 PEC years|0|23|22|
|4 PEC years|0|11|17|
|5 PEC years|0|10|22|
|Total|98|98|98|

Source: ENLACE and Evaluation roster Table 4 illustrates the intensity of treatment analysis. Schools with zero years with PEC had an increase of 24 points (0.24 standard deviation). Schools with only one year in the program had an increase of 6 points; whereas, schools with three years of PEC increased by 9 points. Those schools that have 3 and 4 years in PEC had an increase of 13 and 21 points.

16
Figure E.2. Task Immersion Measurement in the Treatment <!-- Start of picture text --> None 5.8<br>8.9<br>A little 36.2<br>26.7<br>Quite a bit 46.9<br>50.8<br>Completely 11.1<br>13.7<br>0 10 20 30 40 50 60<br>Game Video<br><!-- End of picture text --> _Notes:_ The figure illustrates the question used to evaluate the level of immersion experienced by respondents during both treatments. The question posed was: “To what extent did you perceive the experience of the Venezuelan migrant is an extension of yourself?” Respondents provided their responses by selecting from a 4-point scale ranging from “none” to “completely.” Figure E.3. Respondents’ Emotions after Treatment <!-- Start of picture text --> (A) Compassion (B) Distress (C) Happiness<br>GAME VIDEO GAME VIDEO GAME VIDEO<br>10 10 10<br>9 9 9<br>8 8 8<br>7 7 7<br>6 6 6<br>5 5 5<br>Mean of Compassion 4 Mean of Distress 4 Mean of Happiness 4<br>3 3 3<br>2 2 2<br>1 1 1<br>0 0 0<br><!-- End of picture text --> _Notes:_ The figure illustrates how the treatment affects participants’ emotions. The emotional reactions stem from a question aimed at measuring the respondents’ emotions after receiving the treatment. The question asks: Please indicate how much you experienced the following emotional states when you watched the video or engaged in the virtual activity: a. Compassion; b. Distress; and/or c. Happiness. Respondents answer by selecting one choice for each option a, b, and c, from a Likert scale ranging from one to ten, where one signifies “Not at all” and ten indicates “A lot.” 52
|**Information Source**|**Table A10: Most trusted inform**<br>BurkinaFaso|**ation sources**<br>Malawi|Nigeria|
|---|---|---|---|
|Medical professional|45.2|34.3|28.7|
||(41.0 to 49.4)|(30.1 to 38.6)|(25.7 to 31.7)|
|Scientists and epidemiologists|0.1|0.0|0.3|
||(0.0 to 0.3)||(0.1 to 0.6)|
|Celebrities and influencers|0.0|0.9|2.3|
||(0.0 to 0.1)|(0.3 to 1.6)|(1.3 to 3.3)|
|NGO outreach programs|0.4|1.4|1.0|
||(0.1 to 0.7)|(0.3 to 2.6)|(0.4 to 1.6)|
|Other outreach programs|0.3|2.3|1.0|
||(0.0 to 0.7)|(0.9 to 3.6)|(0.5 to 1.6)|
|Local government|5.7|0.5|10.1|
||(4.0 to 7.4)|(0.0 to 1.3)|(8.2 to 12.1)|
|Federal government|0.3|0.0|8.8|
||(0.0 to 0.7)||(7.2 to 10.4)|
|State government|6.2|0.0|6.4|
||(4.4 to 8.0)||(5.0 to 7.8)|
|Family and neighbors|5.6|4.1|12.8|
||(3.9 to 7.2)|(2.2 to 6.0)|(10.7 to 14.8)|
|Religious organizations|0.9|2.3|3.7|
||(0.1 to 1.7)|(0.6 to 4.0)|(2.7 to 4.7)|
|Traditional healer|0.4|0.0|0.0|
||(0.0 to 0.9)|||
|Traditional ruler|1.8|2.0|1.5|
||(0.7 to 2.9)|(0.9 to 3.1)|(0.7 to 2.4)|
|Media|26.5|34.4|10.9|
||(22.9 to 30.0)|(30.3 to 38.4)|(9.1 to 12.7)|
|Other info source|0.4|0.4|2.1|
||(0.0 to 0.7)|(0.0 to 0.9)|(1.1 to 3.2)|
|None|1.7|4.1|5.1|
||(1.0 to 2.4)|(2.5 to 5.6)|(3.8 to 6.4)|
|Trust all equally|4.6|13.3|5.2|
||(3.2 to 5.9)|(10.6 to 16.0)|(3.8 to 6.5)|
|_N_<br>Note: Most trusted inform|1,744<br>ation sources. All values in percent.|1,443<br>95% confidence inte|2,488<br>rvals in parentheses.|

23
Most transactions are arranged through known intermediaries. A theme that dominated the research is the role of ‘political agents’ - usually relatives or personal secretaries of the elected representatives and departmental administrative staff, referred to more widely as clerks. These agents facilitate access to political leaders and higher level officials for favorable treatment in the four HR functions under study here. For example, these intermediaries contact MOs regarding undisclosed post vacancies in desirable locations or are contacted by physicians regarding the same. They also serve as conduits for channeling payments received by MOs. In the words of respondents from State A and B respectively: “ _To expedite the transfer request, one is expected to give money to the clerks at various levels.”_ _“The agents approach the MOs or even other government officials offering service to get transfers done. It is also not uncommon in some cases where the MO is desperate to get the transfers, usually know whom to contact and how to approach the local public representative holding [a key] position.”_ A high percentage of perception survey respondents (74 and 75 percent in States A and B respectively) consider that these agents “play the role of conduits for MOs to get a desired place of postings.” Similar results emerged from the UCT survey where, for example, 89 percent of State A respondents considered that “department staff exercise undue authority over MOs and indulge in unofficial financial dealings.” Physicians seeking a transfer usually have to pay on both ends of the transaction: the intermediaries as well as the final designator or decision maker who arranges the requested action (e.g., posting, transfers, etc.).

# (g) Perceptions by Physician Characteristic

To check whether perceptions reported in the survey varied by specific traits of the respondents, we regressed probability of agreement with statements related to the four human resource functions on certain physician characteristics.<sup>19</sup> Annex Table 1 presents selected results by one characteristic: years of tenure.

18
5 Table 1: Tax Structure (1993) and Government Revenues in Bulgaria

|Type of Tax|Rates|Base|Reve|nue (% o|f CDP)|
|---|---|---|---|---|---|
||||1991|1992|1993|
|Profits Tax|40% standard rate for<br>non-financial enterprises.<br>50% rate for banks and<br>insurance companies<br>30% for private<br>companies with profits<br>below1million leva|Profits of all SEs,<br>MEs', and private<br>enterprises|17.3|8.3|5.2|
|Social Security<br>contributions|pension: 40%<br>unemployment: 7%|Gross wage|7.8|_9.1_|8.4|
|Income Tax|Marginal rates from<br>20% to 52%|Individual income|3.8|_5.4_|4.8|
|Turnover TaxIVAT|Standard rate: 22%<br>(lower rates: 2%, 10%)|Retail turnover of all<br>enterprises; lower<br>rates apply to food<br>and select sectors<br>(construction)|3.8|3.5|3.8|
||VAT (1994) Single rate:<br>18%|Value added of<br>goods and services||||
|Excises and customs|Ad valorem excise rates<br>vary from_35%_(diesel<br>fuel) to 70% (alcohol,<br>jewelry)|Turnover of select<br>goods|4.8|4.6|6.2|
|Non-tax revenue|Various fees, charges on<br>|select public services|4.8|7.5|6.2|
||services||Total<br>42.3|Total<br>38.3|Total<br>34.6|

SEs denotes state enterprises, MEs denotes municipal enterprises. Municipal entexprises and state enterprises with more than 50% municipal participation in ownership were liable for an additional 10% tax On profits payable to their municipalities. Source: Bogetid and Hillman (1994), World Bank (1994a), and _Tax Notes Internauional_ (1993).
35

# **Conclusions**

This paper represents the first attempt to analyze the Mauritanian labor market using data from the latest national household survey. On the basis of the analysis conducted in this paper, the following salient conclusions emerge. First of all, the Mauritanian labor market is characterized by lower participation rates, lower employment-to-population rates and relatively higher unemployment rates than the corresponding values in neighboring countries. Over half of the working-age population lives in a poor household. The non poor fare better on the labor market than the poor. Even though the labor force participation of the poor is higher than that of the non poor, the poor display a higher unemployment rate and lower employment rate than the non poor. The data also suggest a negative correlation between wage employment and poverty, that is, wage employment increases with wealth. Substantial differences emerge between gender labor market indicators. Women systematically earn less than men, independently of their sector and type of employment, and controlling for other factors (e.g. education). The youth experience considerable difficulties in entering the labor market. The employment-to-population ratio for the 15 to 24-year-old group is roughly half the overall employment rate for Mauritania.

If Mauritania is to attain the ambitious poverty-related goals set out in the PRSPs, policy makers need to focus more squarely on labor market policies. The analysis conducted shows that the Mauritanian labor market is not vibrant. As evidenced by the PRSP-2, the country has taken a passive approach to employment generation and promotion to date, regarding it as a mere bi-product of policies aimed at fostering growth. Moreover, there is the need to ensure that labor market data are collected and analyzed on a regular basis, through a sound mix of quantitative and qualitative techniques, which is currently not the case. As mentioned, gender disparities remain important for similar levels of education. Therefore, policy makers need to pay attention to the binding constraints outside the education sector, which deserve further investigation, including cultural factors that may prevent women to enter the labor market. Concerning the poor labor market indicators for young adults, ensuring – within a reasonable timeframe – that the current generation has access to jobs should undoubtedly be a key priority for the authorities. Better informed labor market policies should be a prominent feature of future poverty reduction strategies.
techniques. The IMF’s China Country Report (2011)<sup>5</sup> analyzed the spillover effects of domestic policies in China. Based on the work by Chen, Gray, N ’ Diaye, Oura, and Tamirisa (2010),<sup>6</sup> the report assessed how the worsening credit quality of the Chinese corporates and banks negatively affects the rest of the world by using the GVAR. Ahuja and Nabar (2012), Ahuja and Myrvoda (2012) are another examples. They have investigated the impact of two different sources of China’s slowdown: one is the real estate investment slowdown, and the other is a slowdown in investment spending (as a component of GDP). One last example is a paper by Duval et al. (2014). They have examined the relationship between trade integration and business cycle synchronization, and reported how China’s growth shocks are associated with the real GDP growth of other countries.

These papers are different from ours in several respects. First, the sample period is shorter than ours. Chen at al. (2010) uses monthly data for the period January 1996 to December 2008, Duval et al. (2014) uses 1995Q1-2012Q4, and Ahuja and Nabar (2012), and Ahuja and Myrvoda (2012) use January 2000 to September 2011. Our dataset ranges from 1979Q1 to 2014Q3, thus covering the period when the size of Chinese economy and its regional and global influence expanded over more than three decades. The second difference concerns the measurement of country linkages. Duval et al. (2014), for instance has reported the importance of using value-added trade data for measuring trade integration. On the other hand, Chen et al. (2010) used financial weights and trade weights to construct foreign variables. However, due to limited data, they used fixed weights for both financial and trade linkages. Reflecting the lack of historical time series data, as reported by previous researchers, and following the tradition of GVAR literature by Pesaran and others, we have decided to use the gross trade flow data. Thirdly, except for Chen et al. (2010), the models are different: Ahuja and Nabar (2012), and Ahuja and Myrvoda (2012) used FAVAR, and Duval et al. (2014) used a reduced-form panel regression model. We used the GVAR specification because it imposes an intuitive structure on cross-country interlinkages (Chudik and Pesaran, 2014),

> 5URL is http://www.imf.org/external/pubs/ft/scr/2011/cr11193.pdf

> 6URL is https://www.imf.org/external/pubs/ft/wp/2010/wp10124.pdf

4