rafmacalaba/datause-encoder-data huggingface dataset:
Personnel Bureaus and tho Pl-nning Commission. Students **are** eventually assigned to jobs by the unit that owns the school.

For the SVS, an entrance examination for general and key general secondary schools, and for SVS, is prepared and administered by the provincial education bureau on a city-wide basis. Students select both the type of school and the specialty desired before taking the examination and are assigned to schools by the municipal education bureau.

Data from Anshan City in Liaoning province illustrate the pressure of applicants upon available places. As shown in Table 5, the overall ratio of secondary applicants to enrollments in 1985 was 2.5:1. For key general secondary schools, the ratio was 3.6:l; for SVS, it was 6.9:1; for STS, it was 2.6:1; and for SWS, it was 5.9:l.

**Table** 5: Applications, Intake, and Examination Cut-Off Scores, Ansebn City Secondary Education*

<!-- Start of picture text --> Year Total Key Gen. Gen. E".o. SVS STS S9S<br>sec. sec.<br>-<br>Applications 16,797 4,287 - 3,451 1,768 7,311<br>1985 Intake 8,638 1,200 3,000 500 690 1,248<br>Exaa Cut-Off 516.5 320 441.5 - na- -n-<br>-<br>Applicatiors 18,847 5,181 - 3,514 2,019 9,153<br>1988 Intake 7,538 1,000 3,200 810 905 1,821<br>bE Cut-Off 543 370 473.5 -a- -na-<br>Ratlo of 1985 2.5:1 3.6:1 1.4:1 6.9:1 2.6:1 5.9:1<br>App'licants<br>to Intake 1986 2.5:1 5.2:1 1.6:1 5.8:1 2.2:1 5:1<br>Ratio (Totals) 1985 1.72 : 1<br>Geeral Sewndary (4,200) (2,3U)<br>to Vocational 1986 1.25 : 1<br>Enrollments (4,200) (3,336)<br><!-- End of picture text -->

*Source: Edceatlon Resurdc Center, M"han Teachtrs College

- 29 -
25 _The main sectors in which urban women are employed are trade, the administration, and services, although differences emerge across employment statuses._ Indeed, urban self-employed women are mainly engaged in trade (76.2 percent, see Table F). As for urban female wage earners, their main sectors of employment are the administration (36.7 percent), and services (31.2 percent). Over half of all female day laborers work in trade and a quarter of them in services. As mentioned above, urban men are more likely to be wage earners than urban women. They are also engaged in a slightly wider range of sectors (Table E). For instance, although male wage earners – like female ones – are mainly employed by the administration (29.2 percent) or engaged in trade (13 percent), they also work, even if to a lesser extent, in transport, mining, construction, and fishing activities (respectively 9.6 percent, 6.4 percent, 5.1 percent, and 4.8 percent). As for urban self-employed men, they are mainly engaged in trade and services (42.2 percent and 12.8 percent).

# **_3.3 Youth_**

_The labor market participation of youth – i.e. all individuals aged 15 to 24 – is roughly half that of people aged 30 or more_ (Table 15). It stands at 25.9 percent for individuals aged 15 to 19 and at 41.6 percent for those aged 20 to 24. Employment-to-population is also low: only 21.6 percent of the youth are employed (this ratio further falls to 16.2 percent for the 15-to-19 population) whereas 56.3 percent of all adults over 30 are employed. Moreover, the unemployment rate of the 15-to-24 age group is five times that of the 30 to 64-year-old population. Finally, gender gaps are substantial: males’ labor force participation and employment ratios are double that of females’ for instance.

**Table 15. Main Labor Market Indicators for Youth (in %)**

||_All youth_<br>||_Age G_|_roup_||_Ge_|_nder_|
|---|---|---|---|---|---|---|---|
||_(15 to 24)_|_15-19_|_20-24_|_25-29_|_30-64_|_Male_|_Female_|
|Labor force participation<sup>~~*~~</sup>|32.7|25.9|41.6|49.9|60.2|45|21.6|
|Employment-to-population<br>ratio<br>|21.6|16.2|28.7|38.7|56.3|31.3|12.9|
|Unemployment rate<sup>*</sup>|33.8|37.4|30.9|22.5|6.4|30.3|40.4|

Source: EPCV 2004. Figures are displayed in percentage. * Standard ILO definition _Youth’s labor force participation and employment-to-population indicators are highest among the poor._ Young people aged 15 to 19 and 20 to 24 living in poor households display labor force participation rates approximately 10 percentage points higher than the non poor (Table G). Moreover, 18.3 percent of the poor aged 15 to 19 and 31.7 percent of those aged 20 to 24 are employed as opposed to respectively 14 percent and 26.6 percent for the non poor. The young poor also experience higher unemployment rates than the non poor, especially those aged 15 to 24 whose unemployment rate is nearly 10 percentage points above that of non poor people of the same age. However, the gap
Policy Research Working Paper 9030

# **Abstract**

Parents play a crucial role in the promotion of early childhood development, and understanding parental perceptions of early childhood development may help enhance parental investments early in life. To explore this question, caregivers were asked to rank their child’s intelligence in comparison with other children in the community, and the rankings were compared with children’s scores on an assessment of developmental abilities across multiple domains. Using cross-sectional data on children ages 16–42 months in rural Madagascar, this paper documents the discordance between caregivers’ perceived early childhood development with an interviewer-based measure of early childhood development. The paper examines the determinants of caregivers’ under- and over-estimation of child development using multinomial logistic regressions. The study finds that caregiver perceptions of early childhood development in Madagascar do not align consistently with an interviewer-based measure. Approximately 8 percent of the caregivers under-estimated and almost 50 percent over-estimated their children’s abilities. Better child nutritional status, caregivers with a greater belief in their influence on child intelligence, and higher socioeconomic status were associated with lower odds of under- or over-estimation of early childhood development. Further research is needed to understand the common cues that caregivers use to identify child development milestones, to inform the design of parenting interventions.

This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at egalasso@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
patterns and correlates of services trade costs. Measures of services trade costs remain scant, which makes it difficult to assess and quantify their determinants. In addition, since trade costs in services are largely associated with regulatory barriers, further analysis of the role of regulatory heterogeneity across sectors and regions seems warranted. Trade costs accumulate with multiple border crossings through the global value chain. Investigating what policy measures can be most effective in reducing trade costs when countries are involved in complex value chains is also key. Finally, further research could aim to better understand the distributional and climate-related effects of reducing trade costs.

transactions profitable (World Bank 2021c).
_“Have there been times in the past 12 months when you did not have enough money to buy the food that you or your family needed?”_ A simple yes or no answer is recorded. For simplification, we refer to this as the “food insecurity” indicator rather than a more cumbersome term such as “unaffordability of food.”<sup>8</sup> What are some of the strengths and weaknesses of this question? The strengths include a focus on access rather than availability, a recall period (12 months) capable of capturing seasonality and other short-run food price movements, and large cross-country and multiyear coverage. This last strength is a significant advantage in the absence of more regular economic or nutritional surveys, but there are also limitations with subjective data. Unlike simulation approaches, for example, subjective data do not provide much information about the mechanisms or magnitudes of welfare impacts. However, there are some indications that the simple yes/no indicator used here may not lead to much loss of information in practice. The GWP has data for Africa in which a similar question is asked that allows for five different answers based on the frequency of deprivation. Those data show a similar trend to the dichotomous indicator (see fig. S.1 in the supplemental online appendix, available at http://wber.oxfordjournals.org/).

A more significant problem is that the definition of food needs is not universal. For a well-off or well-educated family accustomed to a high-quality diet, “food” may mean a food bundle of

> 8 We note that there are other welfare indicators measured by Gallup, including a question pertaining to hunger rather than food affordability as well as a general life satisfaction question (scaled from one to ten). In earlier versions of this paper, we considered the hunger variable, but the sample size for that indicator was much smaller, and trends in that variable could not be significantly explained by economic growth or food inflation. The life satisfaction question was not explored because it is not obvious that changes in this indicator over 2006–08 would be substantially related to food inflation. Even so, that indicator generally suggests sizeable improvements in well-being in developing countries, with only a handful of exceptions (Pakistan, Sierra Leone, Egypt, and Afghanistan). Hence, we concentrate on the more relevant food insecurity question.

8
- 19 -

Figure 9: Institutional Investors' Portfolio <!-- Start of picture text --> UK-PortfolIos of Life Ineorens _ UK-Portfolio, of Pension Fund. UK-Portfolios of Open-end<br>Cop.n.,s (1990-1995) :198,.1995) Invelmmont Compenles<br>sT Loonse 1t% LT L.-<br>Oth., T ':.~~~~~~~~~~~~~TBl l SSTfln d<br>:~,ILC I LT S TS nd1<br>TLT Bond<br>Shoroc ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ h<br>N eth-iend-Portfo .of Life N.th-S e n- d-Porffollo of NPth.orends-P.rtfotoe. of<br>Inourne Cmp.nlo Ponsion Funds (1980-1995) tnveetm.ent Compenle<br>LToas (190-1999) .. -, LToa LTBil d. )1980-199B)<br>Ot ~ Shore 1a% 12% M<br>SThe "'" 16% nd% ST Loons la t rl l t<br>ST L. IIn LT Bonds 0d C.si<br>-nd Cssh 2 a SBi |ST 17% LT Bond<br>0% STSll ST Loose-<br>01% Rood ~~~~~~~~~ end ~ - LT~~~~~~~~~~~dB.d Coonn<br>LT .l Bnd B LT Loose TB.ndTod T Loon. end~~~~~~~L *dBnsLTo L-nd<br>ST Sill. LB ST Bondi ii LT Bonds<br>Olsonrr LoO irf oenon ler S sl l rl<br>Aotrst Ie-Lifo 0th , In.o....e T..l L- 2% Ao.t,.lI.-Portfo Oth. 9%~~O I1os of Auetreto-Ope..nd 01h0 I-onst-Os % te Oar<br>Co (pn8e- (19BB1995) on F.n ond d 9 B119955 C -on 198819955<br>end Bonde<br>LTBond. ST Bil LTd BondST111,1<br>Su dr -P-ce:. In 00rn5 C.nsp.ei.. of Lifs Sweden-PorOfolios of Pension S19d97PorffolofOpeBdSenvetseni Companeete<br>(1990-1995) F und s (11 9 0-1 995) (1990-1995)<br>Told L-o<br>ST B.H.% Told Loos and Cessh C 14% O.h m oj_ % r 4% 6% hs 1 1 ST ToW too nd 5, dC. 5%STA 7% 1% B%1 Olson 5 _ Shors l l T.W L-n3 nd a~~~~~~~~~~~~~~~S- .h . ed C.Mhn ISh %3Oh 1<br>.nd B.nds L ndB Sn.d B-d.<br>To'^i Bonds Loan- | t | w TolalLoanst LT 4ii % 1 1 i11111~~~~~~ Sh..<br>ST ~ Bil. SBil d CT.,s T o<br>54%78<br>LT Bonds LT Bends<br>N.m.ny.loortf.iios of Life Non-ny.P-tfoli.. of Penion N.rw.y.Portfoltee of Opec-sod<br>10 eneComlpeni. 0F nds (1980-1995) 5 Os-met Compeniss<br>980 995gs (1995 1999)<br>Oth. Sh.- Ot- 3% li% Oth.~~~~hons<br>4% 0% T en CaI 9%<br>( U ~~~~~~~~~~~~~~~ST Bel<br>Tola Loa,ns t<br>LTB.nd. and Cooh LT 00n00<br>1% 8<br>S ~~~~~~~~~~~ST SBil LT Bonds<br>and 01nd. and Bonde<br>Source: OECD, Instituotional Investors Yearbook, 1997.<br><!-- End of picture text -->
_Figure 6: Simulation of income shock among rural households._ <!-- Start of picture text --> 100<br>90<br>80<br>76<br>70<br>65<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>0 0.5 1 1.5 2 2.5 3 3.5 4<br>Daily core consumption expenditure per capita (US$)<br>Poverty change Core consumption (2017)<br>Income shock<br>% of population<br><!-- End of picture text -->

# Source: Authors’ calculations.

The simulation results emphasize that a sustainable poverty reduction strategy should involve making rural households more resilient to climatic income shocks. To guide such efforts, it is instructive to analyze the characteristics of the most affected rural households. To do this, we focus on which households self‐ reported having been affected by the 2016/17 drought, regressing it on household characteristics while controlling for location, income, and households’ exogenous level of drought exposure as measured with NDVI. First, households relying on agricultural income are 20 percent more likely to report being affected by the drought. In contrast, households relying on salaried labor are significantly less likely to report being affected by the drought (Figure 7). The fact that households relying on agricultural income are mainly in rural areas is likely part of the reason why no drought effect was found in urban areas. The particular vulnerability to drought shocks of agricultural households is also well‐documented in the literature (e.g. Hill and Mejia‐Mantilla, 2017). This set of findings suggests that agricultural households may benefit from insurance products, such as agricultural index insurance (see Berhane et al., 2012; Dercon et al., 2014). Further, measures facilitating the diversification of income sources, especially the shifting of household members towards wage jobs, could help cushion the effect of climatic shocks (Alem and Soderbom, 2012).

10
- **Duflo, Esther and Rohini Pande** , “Dams,” _Quarterly Journal of Economics_ , 2007, _122_ (2), 601–646.

- **Elbers, Chris, Jean Lanjouw, and Peter Lanjouw** , “Micro-level Estimation of Poverty and Inequality,” _Econometrica_ , 2003, _71_ (1), 355–364.

- **Faber, Benjamin** , “Trade Integration, Market Size, And Industrialization: Evidence From China’s National Trunk Highway System,” _Review of Economic Studies_ , 2014, _81_ (3).

- **Fafchamps, Marcel and Forhad Shilpi** , “Cities and Specialisation: Evidence from South Asia,” _The Economic Journal_ , 2005, _115_ (503), 477–504.

- **Fan, Shenggen and Peter Hazell** , “Returns to Public Investments in the Less-Favored Areas of India and China,” _American Journal of Agricultural Economics_ , 2001, _83_ (5), 1217–1222.

- **Fernando, A. Nilesh** , “Shackled to the Soil: The Long-Term Effects of Inherited Land on Labor Mobility and Consumption,” 2016. Working paper.

- **Foster, Andrew D. and Mark R. Rosenzweig** , “Are Indian Farms Too Small? Mechanization, Agency Costs, and Farm Efficiency,” 2011. Working paper.

- **Gelman, Andrew and Guido Imbens** , “Why High-order Polynomials Should Not Be Used in Regression Discontinuity Designs,” _Journal of Business & Economic Statistics (accepted)_ , 2017. NBER Working Paper No. 20405.

- **Ghani, Ejaz, Arti Grover Goswami, and William R. Kerr** , “Highway to Success: The Impact of the Golden Quadrilateral Project for the Location and Performance of Indian Manufacturing,” _Economic Journal_ , 2015.

- **Gibson, John and Scott Rozelle** , “Poverty and Access to Roads in Papua New Guinea,” _Economic Development and Cultural Change_ , 2003, _52_ (1), 159–185.

- **and Susan Olivia** , “The Effect of Infrastructure Access and Quality on Non-farm

- Enterprises in Rural Indonesia,” _World Development_ , 2010, _38_ (5), 717–726.

- **Goldin, Claudia** , “The U-shaped Female Labour Force Function in Economic Development and Economic History,” in T. Paul Schultz, ed., _Investment in Women’s Human Capital_ , Chicago and London: University of Chicago Press, 1995.

- **Gollin, Douglas and Richard Rogerson** , “Productivity, Transport Costs and Subsistence Agriculture,” _Journal of Development Economics_ , 2014, _107_ , 38–48.

- **, David Lagakos, and Michael E. Waugh** , “The Agricultural Productivity Gap,” _Quarterly Journal of Economics_ , 2014, _129_ (2), 939–993.

28
**Figure 2: Variance Decomposition of Siblings Years of Schooling: Rural Sample**

<!-- Start of picture text -->
1.0<br>0.9<br>0.8<br>0.7<br>0.6<br>0.5<br>0.4<br>0.3<br>0.2<br>0.1<br>0.0<br>1993 2006 1993 2006 1993 2006<br>All children Male Female<br>Idiosyncractic Neighb'hood Corr Intergen Corr (Sqrd) Other Family Factors<br><!-- End of picture text -->

**Figure 3: Variance Decomposition of Sibling's Years of Schooling: Urban Sample**

<!-- Start of picture text -->
1.0<br>0.9<br>0.8<br>0.7<br>0.6<br>0.5<br>0.4<br>0.3<br>0.2<br>0.1<br>0.0<br>1993 2006 1993 2006 1993 2006<br>All children Male Female<br>Idiosyncractic Neighb'hood Corr Intergen Corr (Sqrd) Other Family Factors<br><!-- End of picture text -->

47
sector. Although no private firms offer service as extensive as those of KOTRA and KTA, private general trading companies are strong competitors and their services are often more up-todate and specific to the needs of the individual exporter. In the case of technical support, there is much less competition from the private sector. Although large principal contractors often provide technical assistance to SME subcontractors on an ad hoc basis, this practice is less common between secondary contractors and their subcontractees. Also, technical collective technical support agencies charge such low fees for their services that private suppliers have trouble competing with them.

# **VII Poicy Recommendations**

This detailed survey of 122 SMEs in Korea and related analysis, leads to certain conclusions about SME support policies: 1) SMEs, more than larger firms, face genuine externality problems in gining technical knowledge, marketing information and advice, and financing. Considering the favorable effect of past government policy favoring large firms, and the growing advantage of SMEs in terms of flexibility, technical efficiency, and the ability to fill market niches, it would seem that government support for SMEs is also likely to yield ample benefits. In apparent recognition of this, the government introduced several additional measures for SME support in 1992 and 1993. These included an upward adjustment of the IOU discount ceiling and the allocation of an additional 500 billion won (US$625 million) for SME fnance in 1992 alone.

2) The institutional governanoe stucres of SME support agencies in Korea appear to be a factor in the relative success of SME support services. Compared to other developing countries, the multiplicity of use of SME support systems in Korea, and the relatively high values attached to them, are commendable.

3) Finally, despite overall high usage levels, there are many SMEs that have not used any type of collective support in a certain area, or if they have, were not satisfied. Our survey suggests several specific measures that might be taken to improve SME support in Korea.

* SME support providers should take steps to strengthen the "voice" of SMEs in their organization **s** o that SMEs can better exert pressure to improve compatibility between SME needs and support.

42
Figure 4.4: Interest Rate Ceiling as Obstacle to SME Lending If there are maximum regulatory lending rates, do they prevent you from expanding SME lending?

<!-- Start of picture text --> 100%<br>80% 75%<br>60%<br>40%<br>25%<br>20%<br>0%<br>Yes No<br><!-- End of picture text --> _Source: Authors’ analysis of bank questionnaires (simple averages across all banks)._ Although not as binding due to recent policy measures, the ceiling appears to hinder access to credit for riskier SMEs. Both the method of calculation and periodicity of the ceiling were recently changed<sup>34</sup> , effectively raising the maximum interest rate that can be charged for commercial (including SME) loans. However, as can be seen in Figures 4.5 and 4.6 below, there is a relatively large number of SME borrowers whose interest rates lie just below the ceiling. This is an indication, albeit one that has to be validated in more detail, that access to credit by the official banking system might be restricted for some firms – presumably smaller and younger ones – forcing them to use alternative sources of financing, including the “ _mercado extrabancario_ ”<sup>35</sup> . The problem is particularly acute for those firms transitioning from micro enterprise to SME status based on the legal definition, because the effective interest rate ceiling for the former is much higher than for the latter. Not only is the legal ceiling for microcredit (currently 33.9 percent) higher than for SME loans (currently 28.5 percent), but an additional 4.5-7.5 percent commission (depending on loan size) can also be charged by credit institutions in the case of microcredit. The extent of the problem depends on each credit institution’s target market, with those focusing on smaller firms (primarily domestic banks) being the ones that are most exposed (Figure 4.4).

> 34 The ceiling had traditionally been calculated on a monthly basis as 1.5 times the average current interest rate across all types of loans (except mortgages, whose ceiling is estimated separately). Decrees 4090/2006 and 519/2007 introduced sector-based interest rate ceilings (a common ceiling for commercial and consumer credit was adopted), changed their re-setting frequency from monthly to quarterly, and excluded loans at preferential rates (“ _créditos de tesorería_ ”) from their calculation.

> 35 An alternative hypothesis would be that credit institutions have sufficient market power to maintain interest rates for certain SME borrowers to the highest possible level, so the interest rate ceiling helps to control predatory pricing. This hypothesis can only be validated empirically via borrower/loan-level analysis, but available evidence – for example, on SME market concentration and on the use of multiple banks by most SMEs – seems to cast doubt on its validity.

23
15

**Figure 9.  Latin American Cumulative Amount Raised by Privatizations (1988-2003)**

# (In billion USD)

<!-- Start of picture text --> 200<br>180<br>160<br>140<br>120<br>100<br>80<br>60<br>40<br>20<br>0<br>1988 1990 1992 1994 1996 1998 2000 2002<br><!-- End of picture text --> _Source: De la Torre and Schmukler (2007)._

**Figure 10.  Latin American Advance of Reforms (1989-1999)**

<!-- Start of picture text --> 80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>Total Trade Finance Tax Privatization Labor<br>‐10%<br>Until 1989 Until 1994 Until 1999<br><!-- End of picture text --> _Note: The advance of the reforms is measured as the margin for reform existing in 1985 that has been utilized by 1989, 1995 and 1999. Source: Lora (2001)._