rafmacalaba/datause-encoder-data huggingface dataset:
targeted at girls (and children from ethnic minorities) making the transition from primary school to lower secondary school. Filmer and Schady (2008) evaluate the program and conclude that, despite the small amount of the transfer, which (like the CSP) accounted for only 2-3 percent of the total consumption of the median recipient household, the JFPR increased enrollment rates by almost 30 percentage points. Program effects were particularly large among girls in the poorest households.

In the time period we study, the CSP operated in 100 of the approximately 800 middle schools in Cambodia. These schools were selected on the basis of administrative data which indicated that poverty rates in the areas served by these schools were high and, by implication, secondary school enrollment rates low. In addition, there was a requirement that none of the selected schools participate in other scholarship programs, including the JFPR.

The selection of CSP recipients within eligible schools was done in three stages. First, using administrative data from the 100 CSP schools, program officials identified all of the primary “feeder” schools for every CSP school. (A primary school was designated a feeder school if it had sent graduating students to a given CSP school in recent years.) Second, within feeder schools _all_ 6<sup>th</sup> graders were asked to complete a CSP “application” form— regardless of whether these students or their parents had previously expressed an interest in attending secondary school. The application form consisted of 26 questions about characteristics that were highly correlated with the probability of school dropout, as indicated by analysis of a recent nationwide household survey; the questions were also reasonably easy for students of this age to answer, and for peers and teachers to validate. In practice, the form elicited information on household size and composition, parental education, the characteristics of the home (the material of roof and floors), availability of a toilet, running water, and electricity, and ownership of a number of household durables. Forms were filled out in school, on a single day. Students and parents were not told beforehand of the content of the forms, nor were they ever told the scoring formula—both decisions designed to minimize the possibility of strategic responses; for example, by a student seeking to maximize her chances of receiving the award. Once completed, forms were collected by head-teachers, and sent to the capital, 12
# Why Are Adult Women Missing?

Son Preference and Maternal Survival in India<sup>_∗_</sup>

## Annamaria Milazzo<sup>_†_</sup>

JEL classification: J16, J13, I10, D63 Keywords: missing women, maternal mortality and morbidity, son preference, fertility, birth spacing, India

> _∗_ I am grateful to Eliana La Ferrara for continued guidance and support, and to Alberto Alesina, Siwan Anderson, Sonia Bhalotra, Maristella Botticini, Abel Brodeur, Jishnu Das, Jed Friedman, Robert Garlick, Selim Gulesci, Eeshani Kandpal, Elaine Liu, Owen Ozier, Debraj Ray, Dominique van de Walle, and Adam Wagstaff for very helpful comments. I thank seminar participants at Bocconi University, 2012 NEUDC conference, and 2013 CEA Conference at HEC Montr ́eal for comments and suggestions. All errors are my own. The findings, interpretations, and conclusions expressed in this paper do not necessarily represent the views of the World Bank, its Executive Directors, or the countries they represent.

> _†_ The World Bank. Email: `amilazzo14@gmail.com; amilazzo@worldbank.org`

1
(4) 0 _=Qv + Pv_ with (5a) _PV_ = _IN )_ **1** **_17 T_** _I T_ (5b) _QV= IN -PV_ For any integer m, let _Im_ be an m x 1 vector of ones. The idempotent matrix Q, transforms the original variables into deviations from individual means and Pv transforms original variables into a vector of individual means.

# **4. Dataset and results**

# 4.1 Dataset

In order to perform this analysis, a primary dataset was recently collected with detailed information on several hundreds industrial plants in Zhenjiang, covering the period 1993 to 1997. In 1997, the total number of plants included in our sample is 640. Of these, 26% are state owned enterprises, the majority being collectively-owned enterprises. Most of the plants in the dataset are medium and small enterprises, with only 4% of the enterprises being large. These large plants however, accounts for approximately one third of the total value of output of the enterprises in the dataset. A further breakdown indicates that the timber processing, the food processing and the petroleum processing industries represent the largest number of sectors in our dataset with 17.2%,15.6% and 10.2% of the plants.

Table la and lb describe the water (2a) and air (2b) pollution discharges of the firms in 1997. In brackets is the number of firms on which the entry has been computed. Note that a large proportion of the firms in the dataset have paid water levies, and therefore were not complying with the standards. The proportion of firms violating the air pollution concentration standards appear to be significantly lower.

15
Figure 2. Reliance of Moshavim on Supply Cooperatives <!-- Start of picture text --> 1o0x<br>Current mochaw debt to supply cooperatUte<br>R Total current moshav debt<br>60% iaountain momhavim<br>R<br>40X<br>20X Valley mosh.wis*<br>0 -. .- ..<br>1976 1977 1978 1079 1980 1981 1982<br><!-- End of picture text --> The financial dependency of the Mountain Region moshavim on their supply nooperative did not increase the regionals' control over its members. On the contrary, it reduced control: because the moshavim in this region have only limited access to alternative-sources of credit, the supply cooperative is committed to their continuous funding and the managers of the regional organization could hardly afford the dire financial, social, and political consequences of members' bankruptcies. This is born out by the following observation.

A reasonable rough measure of the financial exposure of a member moshav is the ratio of the ou'standing debt to its monthly sales through the regional office ("credit months"). Kadishay (1985) found that, during the period 1977-1981, only 3 out of 20 moshavim observed by him in the Valley Region exceeded 12 credit months and that too only for short durations. In the Mountain Region, with stronger interreliance, 13 out of 24 observed moshavim exceeded 12 credit months and for relatively long durations.

Thus, while the "strength" of the supply cooperative's power over the individual moshav association is considerable, the "cost" of its application is also very high. The financial power of the supply cooperative over its members, the moshav associations, is thereby 16
Moreover, while prices have been liberalized and the subsequent stabilization efforts have been impressive, the structurl change sought in the production system has been slow. The speed of adjustment is hampered by institutional and legal difficulties, such as the privatization of large enterprises, the introduction of property rights, new accounting system etc. A slower privatization and structural adjustment in turn implies that a large segment of supply is unable to respond efficiently to liberalized prices. Thus, the expanded tax bases promised by a more productive market economy have largely not been realized (see Sachs [19911 and Zou [1993]).

Figure 2 reports the contraction of the general tax bases, as measured by the gross domestic product (GDP). Compared to the peak in 1989, real GDP in 1992 has shrunk on average by about a quarter: 37.5 percent in Bulgaria; 22.6 percent in the former Czechoslovakia; 14.1 percent in Hungary; 18. 1 percent in Poland; and 32.3 percent in Romania. To be sure, the extent of decline of output may be overstated because of measurement problems. It could be claimed that the pre-reform output was largely <!-- Start of picture text --> 120<br>00 5 - Fm C l __ - - -----<br>0.. -8- Hungary\<br>70 - - -v--- RomBulgania<br>go go 8 + -a- Pola---nd Fanner Czechoslovakia ___ -- _ .<br>n ~~-[3 - Hungary'<br>o ~~~-o - Poland v<br>70 _ Romania --- ---- __ ,<br>60 .,,,<br>1986 1987 1988 1989 1990 1991 1992<br>Year<br><!-- End of picture text --> Figure 2: GDP in **Easten** Europe (in constant 1986 prices)

**_Go: Revenue Uncenainry_**

_5_
Figure A.11: The Impact of Reductions in Commission Fees and Tax Withholding Rates On The Share of Firms with a POS Around January 2012 <!-- Start of picture text --> A. All Firms B. Retail Firms<br><!-- End of picture text --> <!-- Start of picture text --> I. Balanced Sample<br>2009m1 2010m1 2011m1 2012m1 2013m1 2009m1 2010m1 2011m1 2012m1 2013m1<br>Year-Month Year-Month<br>I. Unbalanced Sample<br>2009m1 2010m1 2011m1 2012m1 2013m1 2009m1 2010m1 2011m1 2012m1 2013m1<br>Year-Month Year-Month<br>26 58<br>25 56<br>24 54<br>Share of Firms with a POS 23 Share of Firms with a POS 52<br>22 50<br>21 52<br>20.5 50<br>20<br>48<br>Share of Firms with a POS Share of Firms with a POS<br>19.5 46<br><!-- End of picture text --> Notes: This figure plots the share of firms that had a POS around January 2012, when withholding rates applied by credit/debit card companies were reduced (see Figure A.7) and commissions charged by credit/debit card companies were lowered (see Section 3.3). In the unbalanced sample, we omit the months of December and January each year to avoid outliers, which arise from the fact that many firms file in only these months. This figure is discussed in Section 6.

45
first chapter, “The principle of the hiding hand,” “a bit thin, particularly with respect to relevant guidance for those who must decide whether to undertake, continue, or complete a proposed project.”<sup>67</sup> This was not unexpected, since Asher himself had previously called Hirschman’s theses “disconcerting [...] to those in quest of clearer criteria to govern eligibility for foreign aid” (Asher 1962, p. 217). In “The principle of the hiding hand,” Hirschman stated that the underestimation of problems is a powerful mechanism that allows projects to be taken up that would never otherwise be initiated. According to Hirschman, the problems that arise when a project is under implementation usually trigger a creative effort that leads to their solution. Differently from Toynbee’s theory of challenge and response, Hirschman’s principle posited that “people undertake some new task not because of a challenge, but because of the assumed _absence_ of a challenge.”<sup>68</sup> Toynbee’s thesis, according to Hirschman, was an ex-post rationalization, “ _per fare bella figura_ .”<sup>69</sup> Though rhetorically forceful and “Hirschmanesque” (Walter Salant’s term), this principle left many unconvinced. Even the members of the Brookings Advisory Committee who were more favorable to Hirschman’s approach, such as Walter Salant or Edward Mason, considered the principle one-sided.<sup>70</sup> Salant, for example, noted that this principle, far from being a general principle as Hirschman seemed to imply, was only one of the many possible associations between the estimation of problems and the estimation of one’s ability to solve them: of course problems might be underestimated, but they might also be either correctly estimated or overestimated, and the same would be true for the ability to solve them. Nine outcomes were actually possible, from the successful Hiding Hand to sheer disaster (when an underestimated problem is coupled with an overestimated ability to solve it).<sup>71</sup> Years later, Hirschman admitted that his opening chapter “was close to a provocation. Nothing could be less ‘operationally useful’ than to be told that underestimating the costs or

> 67 Robert E. Asher to Mr. Albert O. Hirschman, May 27, 1966, Barcode 30036183 - Projects and Studies - Projects Evaluation - Professor Albert O. Hirschman - Volume 2, Series No. 4225: Operations policy files - Projects and studies - General Files - General 1946-1968, World Bank Group Archives (henceforth World Bank Hirschman Folders Vol. 2); the same criticism was made by Kenneth Bohr to Albert Hirschman, July 14, 1966, Albert O. Hirschman Papers, Box 56, Folder 15.

> 68 Albert Hirschman to Katia and Lisa, April 4, 1965, Albert O. Hirschman Papers, Box 57, Folder 8, emphasis in the original.

> 69 Original Italian, Albert Hirschman to Katia and Lisa, April 4, 1965, Albert O. Hirschman Papers, Box 57, Folder 8.

> 70 “Advisory Committee for _Development Projects Observed_ by Albert O. Hirschman,” September 21, 1966, Albert O. Hirschman Papers, Box 57, Folder 1.

24
the South in a given year is calculated by multiplying the total value of its international reserve assets in that year by the share that advanced countries allocate to South currencies in that same year.

One consideration in constructing this country-to-region data set for international reserves relates to the classification of countries, as the IMF uses advanced and emerging regions in the COFER database that do not exactly match our definitions of North and South. Advanced economies include several high-income economies that we consider in our analysis to be part of the South (such as Australia; the Czech Republic; Hong Kong SAR, China; and Singapore). This would tend to underestimate investments in the South because countries investing in advanced economies could, in fact, be investing in currencies associated with the South in our classification.

Another consideration relates to the currency classification in COFER. In addition to the wellknown currencies, the data include “unallocated reserves” and “other currencies.”<sup>34</sup> We assume that “unallocated reserves” are allocated across currencies in the same proportion as the “allocated reserves.” We also assume that international reserves held in “other currencies” are held entirely in South currencies. This last assumption is based on the results of the “Survey on the Holdings of Currencies in Official Foreign Currency Assets” conducted by the IMF in 2015. This survey collected year-end data for 2013 and 2014 for 130 countries and provided a more detailed breakdown of the currency allocation of international reserves than COFER. The shares of the world’s international reserves that were unambiguously allocated to South currencies were 3.3 and 3.6 percent in 2013 and 2014, respectively. These estimates provide a lower bound on the allocation of international reserves in South currencies, since the currency breakdown in the survey did not include all South currencies. We match these survey allocations more precisely when allocating “other currencies” entirely to the South (yielding allocations to South currencies of 4.7 and 4.4 percent in 2013 and 2014, respectively)

> 34 The COFER data identify the following currencies from North countries: Canadian dollar (from 2012), euro, Japanese yen, pound sterling, Swiss franc, and U.S. dollar. From South countries, the data only distinguish Australian dollars (from 2012 onward) and Chinese renminbi (from 2016 onward).

38
sub-option `userpath("` _string_ `")` ; _ii_ ) the name of the `.csv` file containing the table, via the sub-option <u>`tablename(`</u> _string_ `)` ; the name of the file containing the country list, via the sub-option `countrylistname(` _string_ `)` .

Notice that the table’s `csv` file must contain only one matrix of dimension ( _G × N_ ) _×_ ( _G × N_ + _G × U_ ), where _G_ is the number of countries, _N_ the number of sectors and _U_ the number of uses (i.e. consumption, investment, etc.). See the `icio` help file for more details.

# **3 Supply, demand and supply-demand linkages**

ICIO tables can be used in combination with long-established accounting relationships (Leontief, 1936) to measure the net value of production (GDP) of a country/sector, the value of final demand in a given country/sector and to pin down the links between the country-sector where the value-added originates and the market where it is absorbed in demand.

In Appendix B we show how to retrieve supply, demand and supply-demand linkages, i.e. GDP by country/sector of origin and/or destination, from ICIO tables while in Section 3.1 we describe how to compute these measures in `icio` , providing also some examples.

## **3.1 Implementation: Supply and demand with** `icio`

The `icio` command can be used to retrieve the GDP (i.e. value-added) produced by a given country or industry (origin of value-added) by specifying the option `origin()` , to measure the final demand in different countries and sectors (destination of the value-added) by specifying the option `destination()` , or a combination of the two (both `origin()` and `destination()` ).

### **3.1.1 Syntax**

### **1. Gross Domestic Product:**

`icio, origin(` _country_ _~~c~~ ode_ `[,` _sector_ _~~c~~ ode_ `]) [` _standard_ _~~o~~ ptions_ `]`

### **2. Final demand:**

`icio, destination(` _country_ _~~c~~ ode_ `[,` _sector_ _~~c~~ ode_ `]) [` _standard_ _~~o~~ ptions_ `]`

### **3. Value-added by origin and final destination:**

6
50 in Russia (91%) than in eastern Germany (84%) or in Poland (88%). Also job accession rates are larger in Russia (60%) than in the other two transition economies (54% and 46% respectively). Over the year nearly two thirds of the Russian unemployed leave the unemployment stock. Whilst for Poland this number is only 52%, eastern Germany has comparable large annual outflows from unemployment. However, in the latter case the outflows are nearly evenly divided between job accessions and labour force withdrawal (35% and 27%). The large majority of Russian outflows consists instead of job accessions (51%), with only 16% withdrawing from the labour force. Finally, the inflow rate into unemployment is marginally lower than in Poland (3.3% cf. to 4%) and a lot lower than in eastern Germany (9.3%) where after monetary and social union SOE's relentlessly shed labour. The interesting point coming out of these comparisons is that, unlike in Poland, unemployment in Russia is not a stagnant pool but has a rather dynamic nature. This is derived above all from large outflows out of unemployment while inflows are comparable to transition economies in Central Europe which in turn have relatively low inflow rates (Boeri, 1994). In Central Europe, persons, once flown into unemployment, have on average great difficulties leaving this state while Russian unemployed, on the LFS measure, do not share this experience during the reported period.<sup>40</sup> While the usual demographic patterns of gross transition probabilities can be observed in the Russian sample (e.g. larger labour force withdrawal rates for older workers) very strong patterns by demographic characteristics (gender, age and education) which allow the identification of problem groups cannot be made out for the reported period. Foley's disaggregation of employment into the set {state enterprise, private enterprise, work collective, otherwise owned, self-employment) shows why this is so: the labour market experience of various demographic groups is in fact sector-specific. While women, older persons and the less educated have essentially better prospects in state enterprises, men, younger persons and the more educated fare better in the private sector and self-employment. As state enterprises stop labour hoarding and commence employment reductions in earnest, it is likely that also in Russia a person with one or more of the characteristics of the first group mentioned will experience a deteriorating labour market experience. The thus far analysed data do show a very different behaviour of state owned firms with a strong element of labour hoarding which seems to help those groups which in other transition economies bear the brunt of the restructuring effort.

**40** Note that Commander and Yemtsov come to a similar assessment, using **aggregate data,** for **a** period well into **1994.**
# **DSF versus user fee removal**

**<mark>DSF schemes generally cover some part or all of service and access costs. From a consumer perspective, therefore, they can operate in a similar manner to the removal of user fees for specific services (e.g. family planning or delivery care). The main differences are that most schemes are targeted to certain income groups or areas, and some are managed by a third party structures. These third party structures may also leverage quality improvements, although again this can potentially be paralleled in an integrated structure, assuming payments to facilities are sufficient to allow some</mark> investment in quality enhancements.**

**<mark>Whether the higher costs of establishing and managing these structures is offset by greater targeting precision or more efficient purchasing will depend in the first case largely on demand conditions and the degree of public sector management capacity. If utilization of a service is low in absolute terms across all quintiles, then the costs of targeting are unlikely to be justified. Even if wealthier women are considerably more likely to deliver in a facility than poorer ones, if the overall skilled delivery rates are low, then targeting of payments may not be appropriate. There is also an important demonstration effect to consider – when wealthier women shift to facility deliveries, this will usually</mark> be emulated over time by other socio-economic groups.**

**<mark>On the supply side, administrative capacity is needed for good implementation of any of these policies. Effective financial management is highlighted as a challenge in most study reports, but</mark> particularly those utilizing regular government systems.**

# **DSF versus insurance**

**The cost-effectiveness and preconditions for DSF should also be compared with insurance approaches, which can have very similar goals – increasing service uptake and reducing financial barriers – although they commonly have wider financial protection aims as well. Some countries such as Argentina have adopted an insurance approach instead of CCTs: the Plan Nacer, for example, offers coverage for a package of basic interventions to all uninsured pregnant women and children under six. Its estimated cost is $10 per capita per month (World Bank, RBF 2010).**

# **The value-added of conditionality**

**<mark>While the Latin American CCTs such as PROGRESA have had positive impact on nutrition, health and development outcomes, the debate about the value-added of the conditionality continues, with unconditional cash transfers in other regions achieving significant gains for nutritional status of</mark>**

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|S/N|**Table A3 continued**<br>Data dimension|<br>Data category|Representative indicators|Categorical disaggregation|Coverage element 1 scoring guidelines*|
|---|---|---|---|---|---|
|5|Social Statistics|Health Outcomes|(5.1) Immunization rate.<br>(5.2) Diseases prevalence or<br>incidence.<br>(5.3) Stunting, wasting, or obesity<br>|(5.1) Age; sex.<br>(5.2) Age; sex; disease type.<br>(5.3) Age; sex.|To receive full point: Must have (5.1), (5.2) and (5.3)<br>by sex, and (5.2) by disease type.<br>To receive half point:Must have at least one indicator<br>with one disaggregation.|
||||rate.|||
|6||Reproductive Health|(6.1) Maternal mortality ratio or<br>rate.<br>(6.2) Infant mortality rate or<br>neonatal mortality rate;<br>(6.3) Under-5 mortality rate;|(6.1) None;<br>(6.2, 6.3) Sex;<br>(6.4-6.6) None.|To receive full point: Must have five indicators with one<br>disaggregation each.<br>To receive half point:Must have two indicators with one<br>disaggregation each.. One must be a mortality rate.|
||||(6.4) Fertility rate;|||
||||(6.5) Contraceptive prevalence rate;|||
||||(6.6)Adolescent birth rate.|||
|7||Gender Statistics|(7.1) Proportion or number of<br>women who are victims of physical,<br>sexual, or psychological violence;<br>(7.2) Proportion of women in<br>government, management or senior<br>positions;|(7.1) Age; disability status;<br>relationship to perpetrator;<br>(7.2) None;<br>(7.3) None.|To receive full point: Must have all indicators with one<br>disaggregation.<br>To receive half point:Must have at least one indicator<br>with one disaggregation.|
||||(7.3)Data on child marriages.<br>||**Table A3 continued**|

36