rafmacalaba/datause-encoder-data huggingface dataset:
(Voghouei et al. 2011). Social infrastructure, the services sector GSDP (SSER) also positively affects financial infrastructure as an increase in the services sector GSDP induces higher demand for financial products and simultaneously increases the supply of financial infrastructure.

The impact of debt on financial development is positive and significant, indicating that public debt plays a critical role in promoting financial sector development by providing safe and benchmarking assets (Hauner, 2009). The development of the debt market will broaden the financial sector in India, and that will help finance infrastructure at a reasonable cost. However, the capital expenditure is found to be statistically insignificant and hence, dropped from our final estimation.

**Table 7: Determinants of Financial Infrastructure**

|**_Variables_**|**_Model 1_**|**_Model 2_**|**_Model 3_**|**_Model 4_**|**_Model 5_**|**_Model 6_**|**_Model 7_**|**_Model 8_**|
|---|---|---|---|---|---|---|---|---|
|**_Constant_**|-1.32**<br>(-3.21)|-1.24**<br>(-3.39)|-1.78**<br>(-3.44)|-1.33**<br>(-3.27)|-0.58*<br>(-1.97)|-0.37**<br>(-4.27)|-0.94**<br>(-3.57)|-0.68**<br>(-4.48)|
|**_FINFRAt-1_**|0.94**<br>(74.34)|0.84**<br>(29.87)|0.92**<br>(67.22)|0.82**<br>(22.25)|0.86**<br>(30.25)|0.83**<br>(30.25)|0.91**<br>(51.65)|0.80**<br>(33.18)|
|**_GSDP_**|0.14**<br>(3.06)||0.10*<br>(2.33)||0.08*<br>(2.33)|0.07**<br>(4.21)|0.11*<br>(2.55)||
|**_PGSDP_**|<br>-|0.20**<br>(2.55)|<br>-|0.28**<br>(4.14)|<br>-|<br>-|<br>-|0.49*<br>(2.89)|
|**_INV_**|0.002**<br>(4.96)|<br>0.004**<br>(5.98)|0.002*<br>(2.29)|<br>0.003*<br>(2.38)|0.008**<br>(4.47)|0.002**<br>(3.87)|0.001**<br>(3.43)|<br>0.006*<br>(5.48)|
|**_SSER_**|<br>0.003**<br>(3.23)|<br>0.003**<br>(4.21)|<br>0.003*<br>(2.78)|<br>0.003**<br>(4.21)|<br>0.003**<br>(2.95)|<br>0.003**<br>(5.55)|<br>0.004**<br>(4.80)|<br>0.002**<br>(5.55)|
|**_UR_**|-0.0002<br>(-1.62)|-0.0001<br>(-0.15)|0.0003<br>(0.37)|0.002*<br>(-2.15)|-|-|-|-|
|**_Debt_**|0.001*<br>(2.26)|0.001*<br>(2.11)|0.001**<br>(2.24)|0.0001<br>(0.39)|0.0001<br>(0.62)|0.0001<br>(0.75)|0.01<br>(0.83)|0.0001*<br>(2.18)|
|**_PDEN_**|<br>0.0001**<br>(4.14)|<br>0.0005**<br>(3.95)|<br>0.0001**<br>(3.81)|<br>0.0002**<br>(3.65)|<br>0.0001**<br>(5.53)|<br>0.0003**<br>(3.44)|<br>-|<br>-|
|**_SCST_**|<br>-|<br>-|<br>-0.004*<br>(-2.29)|<br>-0.008**<br>(-3.98)|<br>-0.003*<br>(-2.77)|<br>-0.009**<br>(-4.08)|-0.001*<br>(-2.61)|-0.006<br>(-1.30)|
|**_SINFRA_**|||||0.10**<br>(3.07)||||
|**_PINFRA_**||||||0.08**<br>(2.16)|||
|**_DUM_**|||||||0.06*<br>(3.43)|0.07**<br>(4.02)|
|AR (1) (p-<br>value)|(0.00)<br>(0.87)|(0.00)<br>(0.14)|(0.05)<br>(0.32)|(0.05)<br>(0.26)|(0.00)<br>(0.32)|(0.05)<br>(0.31)|<br>(0.04)<br>(0.51)|<br>(0.00)<br>(0.34)|
|AR (2)(P-<br>value)<br>Sargan test<br>(P-value)<br>No.<br>Instruments<br>Hansen test<br>of<br>Exogeniety|(0.11)<br>22<br>0.12|(0.07)<br>22<br>0.06|(0.07)<br>17<br>0.09|(0.09)<br>21<br>0.12|(0.08)<br>22<br>0.06|(0.15)<br>16<br>0.09|(0.08)<br>17<br>0.33|(0.13)<br>16<br>0.21|

27
16 our setting this second group includes those that had already served when the exemption was passed so that their behavior could not be A tentative estimate of the quantity P (Di1 > Di0) can be obtained from the available data as follows. Let s(a) be the proportion of conscripts at age a, so that s(a) = 0 if a ≤ 18, and C(a) = 1−<sup>�a</sup> j=18<sup>s(j),</sup> the corresponding proportion who has not served by age a. The function C(a) can be approximated by the cross-sectional relationship between age and the proportion in service in non-exempt towns at the census date. The function, reported in the top panel of figure (6), shows that about 30 percent of eligible males serve when 19 years old, an additional 20 percent at 20 years old, and so on. Importantly, about 30 percent of eligible males has not served by age 35 and presumably will not serve thereafter. Therefore, the proportion of always-takers (P (Di1 = Di0 = 1), i.e. those that always skip service) is about 0.3<sup>18</sup> .

Consequently, the proportion of males of a given age who did not serve because of the exemption can be estimated as follows. Let s ̃(a) be the proportion of youths of age a from exempt towns who report being in service at census date. Then the proportion of those who did not serve because of the exemption can be proxied by C<sup> ̃</sup> (a) = 1 −<sup>�a</sup> j=18<sup>−1s(j) −s ̃(a)undertheassumptionthatallthose</sup> who have not yet served when exempted will not do so in the future. That is, we assume that until age a − 1 (or, alternatively, 1980) youths from exempt towns served in the army as youths from non exempt towns and then, because of the exemption, all were freed except those who were already in service in 1981. The lower panel of figure (6) reports for each cohort the estimated proportion of men from exempt towns who did not serve in the army. All youths exempt before formal eligibility were freed from service, while only about a half of the cohorts born between 1959 and 1961, exempt after

> 18This proportion is remarkably consistent with what can be estimated from the Indagine Longitudinale sulle Famiglie Italiane (ILFI; http://www.soc.unitn.it/ilfi/eng.index.html). The survey was started in 1998 with a full set of retrospective information on a representative sample of about 5,000 Italian households. Individuals were also asked whether they were ever drafted for compulsory military service (see Pisati and Schizzerotto (2004) for details). The nationwide proportion of adult males reporting never to have served in compulsory military service is between 0.25 and 0.3 and fairly stable across cohorts (data available upon request).
14 {c, j} (Dc,j) and combine it with 1991 census data on the corresponding population at risk obtaining Dc,j/Nc,j, the measure of interest. The data also include detailed information on causes of death, according to the 9th release of the International Classification of Diseases<sup>14</sup> . The evidence shows that the probability of dying over the decade 1991-2001 was lower among exempt 1963-65 cohorts by 0.34 percentage points (p-value: 0.034). At the same time, the difference among the two older cohorts is basically zero, and is estimated with a similar degree of precision as that between the younger cohorts. The difference among younger cohorts, as shown in the last two rows, is entirely due to a lower incidence of natural causes<sup>15</sup> . The drop in mortality rates is quite substantial: it amounts to about one fourth of the death rate from all causes estimated for non-exempt control cohorts and to about one half of deaths due to natural causes only. The difference implies that in the entire region targeted by the exemption about 600 males in their mid 20s who would have otherwise died earlier reached their mid 30s. The effect on life expectancy at age 25 is also substantial. Under the extreme assumption that the mortality rate reduction induced by the exemption is limited to ages 26 to 36, life expectancy at age 25 increased by about one quarter of a year. To put this in context, between 1980 and 1990 life expectancy at age 25 increased by about one year.

# 4.2 Simple estimates of the long-run effects of avoiding military service

The results presented above represent the change in outcome associated with a randomly offered exemption from compulsory military service, the so-called intention-to-treat (ITT) effect. To infer the effects of not serving in the army on the outcomes of interest from the ITT it is necessary to quantify the proportion of the cohort that did not serve because of the exemption. In principle, if retrospective information on military status was available for the cohorts of interest, we should simply compare

> 14See http://www.cdc.gov/nchs/icd/icd9.html.

> 15 We code deaths on the basis of the main cause as reported in the death certificate according to the 9th revision of the International Classification of Diseases (ICD9). We define natural deaths as those due to internal causes (codes: 0001-7999).
Policy Research Working Paper 5809

# **Abstract**

This paper examines the key aspects of the practices of school-based management in Indonesia, and its effect on education quality. Using a conceptual framework of an accountability system of public service delivery, the paper explores the relations among Indonesian parents, school committees, schools, and government education supervisory bodies from three tenets: participation and voice; autonomy; and accountability.

Using the data from a nationally representative survey of about 400 public primary schools in Indonesia, the paper finds that the level of parental participation and voice in school management is extremely low in Indonesia. While the role of school committees is still limited to community relations, school facilities, and other administrative areas of school management, school principals, together with teachers, are much more empowered to assert professional control of the schools. The accountability system has remained weak in Indonesia’s school system, which is reflected by inadequate information flow to parents, as well as seemingly low parental awareness of the need to hold schools accountable. The accountability arrangement of the Indonesian school system currently puts more emphasis on top-down supervision and monitoring by government supervisory bodies.

The findings show that although the scope of schoolbased management in Indonesia is limited, it has begun to help schools make the right decisions on allocation of resources and hiring additional (non-civil servant) teachers, and to create an enabling environment of learning, including increasing teacher attendance rates. These aspects are found to have significantly positive effects on student learning outcomes.

This paper is a product of the Education Sector Unit, East Asia and Pacific Region. 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://econ.worldbank.org. The author may be contacted at dchen1@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
ECLAC (2010), “Latin America and the Caribbean in the World Economy 2009-2010”, Santiago, Chile.

ECLAC (2011), Latin America and the Caribbean in the World Economy 2010-2011, Santiago, Chile.

Evans, Peter (1995), Embedded Autonomy. States and Industrial Transformation, Princeton: Princeton University Press.

Fernandez Jilberto, Alex (2000) “América Latina: el debate sobre los nuevos grupos económicos y conglomerados industriales después de la reestructuración neoliberal” European Review of <u>Latin American and the Caribbean Studies, No. 69, October.</u> French-Davis, Ricardo (2005), <u>Reformas para América Latina después del fundamentalismo neoliberal”, Buenos Aires: Siglo XXI.</u> Giordano, Paolo and Robert Devlin (2012), “Regional Integration” In José Antonio Ocampo and Jaime Ros (eds.), The Oxford Handbook of Latin American Economics, Oxford: Oxford University Press Gobierno Federal de Brasil (2011) “Plano Brasil Maior 2011-2014. Innovar para competir. Competir para crecer”.

Gonzalez, Francisco (2012), <u>Creative Destruction? Economic Crisis and Democracy in Latin America, Baltimore: Johns Hopkins Press.</u> Griffins, Andrew and Raymond Zammuto (2005), “Institutional Governance Systems and Variations in National Comparative Advantage”, The Academy of Management Review, Vol.30, No.4 (October).

Grindle. Merilee (2010),”Constructing, Deconstructing, Reconstructing Career Civil Service Systems in Latin America”, CID Working Paper 204, Center for International Development, Harvard University, Cambridge, Mass. (October).

Guerchunoff, Pablo and Guillermo Cánovas (1994) “Las privatizaciones en Argentina: impacto micro y macroeconómicos” Serie de Reformas en Política Pública N0. 21, CEPAL, Santiago de Chile.

Hausmann, Ricardo (2008), “The Other Hand: High Bandwidth Development Policy”, Research Working Paper08-060, Kennedy School, Harvard University, Cambridge MA. (October).

40
the agent or teller to present the documentation and open the account was not different by location and lasted 26.6 minutes.

At the time of the baseline survey and intervention, we also implemented a neighborhood survey to identify all bank and microfinance branches and banking and mobile money agents in the study areas. By design, a study area contained one Microcred branch and one Microcred agent. Combining all study areas, the neighborhood survey identified a total of 391 establishments, including 57 bank branches, 44 microfinance branches, 6 Microcred banking agents and 251 mobile money agents, so the density of financial providers was high. Branches are from all major banks, savings cooperatives and microfinance institutions, including CBAO, Banque Atlantique, PAMECAS, SGBS and our partner Microcred, among others. In contrast, only Microcred had banking agents at the time of the study, so all banking agents are from Microcred.

A Microcred banking agent can collect deposits into and make withdrawals from the Sukaliku savings account and other Microcred accounts. Both branches and banking agents also provide various mobile money and money transfer services simultaneously, including Wari, Joni Joni, Orange Money, Western Union, MoneyExpress and MoneyGram among others. Microcred branches and agents typically work with 2-3 mobile money providers, while the median mobile money agent in our sample works with 4 mobile money providers. Microcred branches are open from 8:30 am to 7 pm from Monday to Friday, 8:30 am to 5:30 pm on Saturdays and are closed on Sundays. Microcred agents are typically open for longer hours (until 9pm or 10pm) and they also operate on Sundays. Most agents are retail shops (typically electronics), although some work exclusively as banking and mobile money agents. Banking agents receive a commission per transaction from the bank. Online Appendix OA1 provides more details about the commission that agents receive per transaction.

The neighborhood survey also included a module that collected basic individual characteristics for a sample of Microcred agents and Microcred branch tellers. Online Appendix Table OA2 compares the characteristics of respondents, Microcred agents, other agents and branch tellers. Respondents and Microcred branch tellers are older than Microcred agents (38 and 32 years old, respectively versus 24.5 years old) and more likely to be married (66 and 69 percent versus 33 percent), but Microcred agents and bank tellers are far more educated than respondents (14 and 16 years of education, respectively versus 6.5 years) and perhaps as a result, they enjoy higher monthly household income. It thus appears that both Microcred agents and branch tellers belong to a different socio-economic group from that of 11
enroll the vast majority of students in Jordan.<sup>5</sup> One can clearly see that the growth in the supply of public basic schools started to take off for the cohort born in 1950 and continued at a rapid pace through the mid-1970s cohort. Initially more boys’ schools were being built, corresponding to the early school acquisition of Jordanian males (panel [A] of figure 2). The supply of girls’ and mixed schools was also rising for the cohorts born in 1950 onward, but by the 1965 cohort, there appears to have been a concerted effort to dramatically increase the supply of mixed schools. This corresponds roughly to the cohort of Jordanian women that have experienced the largest increase in schooling relative to previous cohorts. Indeed, an examination of the 2010 school census data reveals that the majority of students in mixed schools are girls at both the basic and secondary levels (70 percent and 86.5 percent respectively), which suggests that the rapid increase in schooling for females was primarily accounted for by the growth in mixed schools. On the other hand, the growth in the supply of boys’, girls’, and mixed secondary schools was steady across the observed birth cohorts (panel [B] of figure 2). The number of boys’ secondary schools being equal to the number of girls’ and mixed secondary schools combined, bearing in mind the fact that mixed secondary schools were _de facto_ girls’ schools.

Since the empirical analysis is contingent on the exogeneity of the growth in the supply of schools at the local level, controlling for governorate-level time-varying heterogeneity, an analysis of its association with the initial observable characteristics of the local populations is necessary. Because there are no reliable historical data on the characteristics of subdistricts in Jordan, the characteristics of those 60 and older from the 2004 population census (who have

> 5. Data from the JLMPS 2010 indicate that 94.1 percent of Jordanians between the ages of 25 and 35 who went to basic schools within Jordan were enrolled in public schools run by the Ministry of Education or some other Ministry of the Jordanian government or by the UN Relief and Works Agency for Palestinian Refugees in the Near East (UNRWA), which provides basic schooling to Palestinian refugees in Jordan. For purposes of the analysis, UNRWA schools are considered public schools. The proportion of secondary school students in 2010 enrolled in public schools is 94.7 percent.

9
- 19 -

which means that projects evaluated in a given year may have been approved nearly 10-15 years prior to the evaluation. Thus, in evaluation year CY87, for example, the approval dates for the set of projects range from CY73 to CY84. In the majority of cases, projects were closed in the year prior to evaluation, although some projects may have been evaluated several years after closing. Thus the data represent the evolution of ID results, and not necessarily the evolution of ID design. Additionally, the evaluations of overall project objectives and ID objectives have been done independently; thus, overall ratings are nos weighted by corresponding ID ratings.

First of all, OED data show that ID achievement in the set of 1,699 projects completed and reviewed over the period CY78-CY88 has declined significantly. Since 1982 the share of projects with negligible achievement has steadily increased from 15 percent to 25 percent (See Figure **l).26** The share of projects with substantial ID achievement has declined from 42 percent to 35 percent during the same period. The share of projects with partial ID achievement also has declined from 48 percent to 44 percent during this period. These are disturbing trends and deserve to be analyzed carefully. T-ne recent ARIS finding that institutional problems are becoming increasingly severe in the proiects currently under implementation adds to the significance of these trends. The factors underlying the deteriorating ID performance are examined in Section IV.

Second, in terms of regions, the neglig!hle ID achievement category in Asia has marginally worsened, and the substantial achievement category has declined significantly. In Africa, cn the other hand, the negligible achievement category, which had worsened significantly until 1985, has since stabilized. EMENA shows a decline in the substantial achievement category and a relatively stable trend in the negligible category. LAC shows a considerable worsening in both the substantial and negligible achievement categories (see Figures 2-5).

Third, with respect to sectors, the negligible ID achievement category in education has hotably worsened since 1982.27 Transport/urban and public utilities also show a similar (worsening) trend though the latter seems to be stabilizing. The negligible achievement category in agriculture is relatively stable, but in industry/DFC, there has been some improvemer,t. Note that transport/urban and agriculture have the highest levels in the negligible achievement category (see Figures 6-10). PHR completed projects were too few in number to be included in this assessment.

> 26 Changes in the OED criteria for eva''uation and learning over time might explain a part of this phenomenon. On the other hand, the ARIS reports reinforce the OED results in general.

> 27 The focus here is only on the negligible ID category and not on the overall ID performance of the sectors. For example, the partial ID achievement category has improved somewhat in education since 1983.
Moving to the central question, namely, the difference between the cost of transporting one quintal of each good one kilometre on a _kutcha_ track and an all-weather village road, respectively, the corresponding pairs of estimates and the associated standard errors are reported in Table 5. The difference between these pairs of estimates ranges from about Rs.7-8 for horse gram and millets (as for paddy) to about Rs.18-20 for cotton and green gram. All estimates of the coefficient on d0 are positive and statistically significant; the hypothesis that the coefficients on d0 and d1 are the same is rejected for all these crops. These results suggest that a household that markets a one-tonne ‘representative’ basket of paddy and these crops and whose village benefits from the conversion of a 5-km. _kutcha_ track to a PMGSY road would enjoy a reduction of about Rs.500 in transport costs on this score alone. A corresponding improvement in effective net prices might also induce substitution among crops; but the data needed to establish such an effect, which involve before and after comparisons, were not canvassed in the household survey for want of time and resources. The effect on cropping patterns was, however, taken up in the focus group interviews.

Table 5: Transport costs for 1 quintal of selected commercial crops, _kharif_ 2009

|Crop|_n_|uncensored|d0 (km.)|d1 (km.)|pseudo _R_<sup>2</sup>|
|---|---|---|---|---|---|
|cotton|53|22|22.26<br>(3.49)|3.87<br>(2.29)|0.3748|
|horse gram|75|70|14.52<br>(5.61)|7.53<br>(3.36)|0.0705|
|green gram|48|41|33.00<br>(7.31)|13.00<br>(3.62)|0.1190|
|_kandul_|42|41|16.37<br>(7.67)|2.15<br>(3.01)|0.0822|
|millets|54|49|28.17<br>(13.98)|19.31<br>(6.54)|0.1192|

d0: trip segment on a track or _kutcha_ road; d1 analogously defined for segments of village all-weather road and district road, respectively. Standard errors in parentheses.

# **3.2 The focus group interviews**

As emphasized above, an all-weather road affects villagers’ welfare not only by reducing transport costs, but also by enlarging their set of marketing opportunities, for example, by encouraging more competition among marketing agents and making arrangements to market jointly more attractive. The qualitative findings from the focus group interviews 15