rafmacalaba/datause-encoder-data huggingface dataset:
The gap between connection and reliability of water system is also particularly pronounced in secondary cities in Albania, Armenia, Georgia, Tajikistan and Turkmenistan (Figure 4.13).

**Figure 4.13. Water connection versus reliability in ECA countries (other urban)**

<!-- Start of picture text --> Connection Reliability<br>100<br>80<br>60<br>%<br>40<br>20<br>0<br>Balkans/EE Caucasus Central Asia<br><!-- End of picture text -->

*Bosnia  mixed settlement

Source: see Table 2.1

# **4.2.2. Households pay little for infrastructure and energy services and housing**

**Changes in household expenditures for housing and utilities.** Despite widespread efforts to reform the housing sector by privatizing housing and reforming utility provision since the early 1990s, households in transition countries (especially in the FSU) devote smaller shares of expenditures to housing and related utility services than do those in OECD countries (Table 4.3).  At the beginning of transition, housing and utilities accounted for less than 3 percent of household expenditures in the FSU.  A decade later, housingrelated expenditures remained below 10 percent for most FSU countries.  Low tariffs, widespread exemptions and weak collection rates explain the low rate of spending on housing and utilities.  Only in Armenia, Kazakhstan and Ukraine did expenditures reach 10 percent or a bit above.

Changes in expenditure patterns for housing have been particularly dramatic in the Baltics, where housing and utilities accounted for less than 3 percent of expenditures at the beginning of transition as was true in the rest of the FSU. However expenditures by households for housing and utilities have increased sharply and now account for about 15 percent. This is primarily due to increased expenditures for energy. In Eastern Europe, expenditures were a bit higher at the beginning of transition, but have also increased and now average about 15-20 percent for households with much of the increase reflecting increased costs for energy. Eastern Europe is approaching OECD shares where households spend from 20-30 percent on housing and utilities.

**Non-payment is widespread.** Non-payment for infrastructure and energy services is widespread in the region, in particular for water, central heating and natural gas (Figure 4.14).  However, overall more than 20 percent of households do not even pay for electricity, where payment enforcement is relatively simple. Even in apartment buildings, individual households can be disconnected at little cost and electricity is commonly metered, unlike the other utilities.

In general, households with access to a given service in the capital are more likely to pay than those in secondary cities who, in turn are more likely to pay than those in rural areas. The reason behind low payment rates are multiple. This can be due to a large number of waivers for privileged groups, which may not necessarily be the most vulnerable. It can also reflect the legacy of the past, when services were 32
-4 -

**II. The Data**

The basic information used for the analysis of representation was provided by the WTO/GATT Directories issued in 1982 and in August of 1987 and 1997. These Directories have a listing of all staff working in each member country Mission dealing with WTO/GATT matters as well as the location of the Mission. The listings contain only professional staff - secretarial and support staff (drivers etc.) are excluded; and are usually headed by an Ambassador, permanent representative of the country to the WTO/GATT. As noted above, the representation may be from a Mission in Geneva, from a Mission elsewhere in Europe or in a few cases from a Ministry in the capital of the country itself. They are all listed in the WTO/GATT Directories -- whose format has changed little over the years; they have just become thicker.

The period covered is of interest because it looks at the WTO/GATT representation at three different points in time, each associated with a distinct period in the organization's activity: 1982 is before the beginning of the Uruguay Round, 1987 is a year after the Uruguay Round was launched, and 1997 is the present -- ten years later, when the WTO has been established and the implementation of the Round is in full swing.

The Directories also contain a listing of the officers of the Organization and all subsidiary bodies, committees, working groups etc. as well as their country affiliation which is used in the discussion of participation in WTO activities. Chairmen have traditionally played a relatively active role in the GATT and the WTO -- their role has not been purely cosmetic. An organization like the WTO -- and previously the GATT -- which works with consensus despite the fact that the countries represented are very different in their economic size, presents complex challenges in designing decision making structures that result in an equitable representation of the interests of all participants. Chairmanships play a role in this effort to maintain a reasonable balance of interests. Thus, the share of chairmanships
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32
– structural transformation employment transitions from agriculture to manufacturing – and services with economic development is primarily driven by men. Women follow a different pattern: at low levels of development, they exit agriculture and primarily transition out of the labor force. At higher levels of development, women re-enter the labor force, primarily in the service sector. Unlike men, women’s representation in manufacturing remains low across all development levels. We further document gender differences in occupational choices _within_ sectors, showing that men increasingly work in professional and industrial jobs in richer countries, while women’s employment (relative to men) expands faster in clerical jobs but slower in professional and industrial jobs.

In addition to gender employment gaps, we also analyze the evolution of gender wage gaps for a select set of countries which provide high-quality micro-data on hourly earnings. We find that wage gaps have narrowed over time across all occupation-sector pairs. However, women in the 2010s still earned, on average, only 70 cents for every dollar earned by men. Furthermore, we observe a weak correlation between gender wage – gaps and countries’ development levels in contrast to gender employment gaps that tend to decrease in richer countries. Additionally, gender employment and wage gaps do not necessarily correlate across occupation-sector pairs.

We then propose a model of occupational and sectoral choice that can speak to these empirical findings and that builds on Hsieh et al. (2019). The documented changes in gendered employment and wage patterns – both across countries and within countries over time – can be partly driven by previously studied economic channels, such as income effects in consumption, sector- or factor-specific technological change, or shifts in the supply of, or returns to human capital.<sup>2</sup> Specifically, technological change and income effects can increase labor demand in the “female-gendered” service sector, disproportionately benefiting women (Ngai and Petrongolo, 2017; Fan et al., 2023). Additionally, the narrowing of gender education gaps has expanded the supply of women’s human capital (Evans et al., 2021; Feng et al., 2023). On the other hand, the documented changes in gendered labor market outcomes can also be driven by a decline in barriers that women face in certain occupations and sectors, which would increase women’s _labor supply_ in them.<sup>3</sup> Our model enables us to disentangle the effects of economic mechanisms from those

> 2See for example Ngai and Pissarides (2007); Boppart (2014); Herrendorf et al. (2013, 2014); Comin et al. (2021); Porzio et al. (2022); Huneeus and Rogerson (2024).

> 3See Jayachandran (2021) for a review of social norms around women’s labor force participation and Hyland et al. (2020) for a review of legislative changes over time and across countries that improve women’s rights for fair remuneration and for accessing job opportunities.

3
|**Table 5a: Effect of formalizing on fir**|**m outcomes**<br>||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
||Monthly<br>Profits|Truncated<br>Profits(99th)|Truncated<br>Profits(95th)|Log<br>Profits|Monthly<br>Sales|Truncated<br>Sales(99th)|Log<br>Sales|Number of<br>Paid Workers|Recruited a<br>New worker|Log<br>Capital Stock|
|_Full effect (Upper bound)_|||||||||||
|Registered with the D.S.|13,706*|10,834|5,923|0.357*|122,295|99,073|0.460|0.525|0.102|0.396|
||(8,241)|(6,847)|(4,774)|(0.202)|(85,196)|(72,440)|(0.319)|(0.426)|(0.0902)|(0.258)|
|_Effect after controlling for log capital_|_stock (lower bo_|_und)_|||||||||
|Registered with the D.S.|8,996|7,054|2,544|0.168|61,868|44,438|0.174|0.431|0.106|n.a.|
||(8,074)|(6,474)|(4,462)|(0.187)|(85,602)|(71,944)|(0.298)|(0.437)|(0.0925)||
|Number of Observations|2,181|2,181|2,181|2,123|2,139|2,139|2,088|1,017|1,017|1009|
|Mean for controlgroupin sample<br>Notes:<br>Registration with the D.S. instrumen<br>Information only treatment group e<br>All regressions include controls for r<br>Robust standard errors in parenthes|30537<br>ted with offer<br>xcluded from th<br>andomization s<br>es, clustered at|28662<br>of the 10,000 Rs,<br>ese regressions.<br>trata and for the<br>the firm level, *|25048<br>20,000 Rs, or 40,<br> <br>baseline value<br>, **, and *** ind|9.87<br>000 Rs registr<br>of the depen<br>icate signific|237185<br>ation treatme<br>dent variable.<br>ance at the 10,|211399<br>nts.<br>5 and 1 percent s|11.42<br>ignificance l|2.35<br>evels respectively|0.36<br>.|12.278|
<!-- Start of picture text --> Chad Oil Production<br>(millions barrels per year)<br>2003 - 2009<br>70<br>60<br>50<br>40 Production (millions barrels per<br>30 year)<br>20<br>10<br>0<br>2003 2004 2005 2006 2007 2008 2009<br>Years<br>years)<br>Barrels (million per<br><!-- End of picture text --> Source: Chadian Authorities and IMF projections.

Inflation increased to an annual average of 8 percent in 2005 owing to a drought in 2004, and, despite a better harvest, remained high in 2006 because of increasing meat prices. The real effective exchange rate appreciated, mainly reflecting the appreciation of the Euro against the U.S. dollar. After stagnating in 2003-04, broad money grew by 32 percent in 2005 owing to a rise in credit to the cotton sector, but monetary expansion slowed down to about 28 percent by late 2006. There is no credible sign of Dutch disease in Chad subsequent to the onset of oil production in addition Chad is a member of CFA franc zone, which had been pegged<sup>6</sup> to the French franc and, since the beginning of 1999, has been pegged<sup>7</sup> to the Euro.

The financial health of the banking system appears broadly satisfactory, although vulnerable because of its overexposure to government deposits. Despite the relative soundness of Chad financial system, it remains among the least developed in the region. Commercial bank services are only available in the five largest cities<sup>8</sup> . The microfinance<sup>9</sup> sector has been gaining importance in recent years. The emergence of microfinance contributed to the improvement in the population’s access to financial service. The development of commercial bank network or financial system is critical for the implementation of the poverty reduction strategy since it can contribute to ease transactions and to smooth the budget execution and therefore increases the service delivery for the poorest people in Chad.

Public expenditure increased reflecting the onset of oil revenue, which reached 8 percent of GDP in 2005. Non-oil revenue also bolstered by improved revenue

> 6 The real exchange rate appreciation in response to an improvement in terms of trade is not affected by the existing exchange rate regime. The essential element of the economy’s adjustment relates to the relative price change.

> 7 We are not going to discuss the potential advantages or inconvenient of a fixed exchange rate regime. 8 IMF Country Report No. 06/06/321 – Central African and Monetary Community: Financial System Stability Assessment, including Report on the Observance of Standards and Codes on the following topics: Monetary and Financial Policy Transparency, and Banking Supervision.

> 9 The microfinance sector still small though.

7
# **TABLE A2. Average wage. ICT intensity**

||F<br>|E<br>|FE‐2<br>|SLS<br>|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|ICT|‐0.49|‐0.087|12.5|12.9|
||(1.50)|(1.41)|(17.2)|(16.8)|
|ICT|‐0.43|‐0.14|11.0|12.7|
||(1.47)|(1.40)|(17.0)|(16.8)|
|Skills|0.31***|0.16**|0.32***|0.15**|
||(0.074)|(0.065)|(0.074)|(0.066)|
|ICT|‐3.11|‐2.54|‐1.57|‐0.44|
||(1.92)|(1.75)|(15.2)|(15.1)|
|ICT * High Productivity|6.58**|5.88**|31.6***|32.0***|
||(2.59)|(2.45)|(11.7)|(11.7)|
|Skills|0.31***|0.16**|0.31***|0.15**|
||(0.074)|(0.065)|(0.075)|(0.068)|
|ICT|‐2.07|‐1.76|1.46|1.70|
||(1.59)|(1.48)|(16.3)|(16.2)|
|ICT * Skills|7.30***|7.19***|28.1***|26.2**|
||(2.70)|(2.57)|(10.7)|(10.6)|
|Skills|0.31***|0.16**|0.31***|0.15**|
||(0.074)|(0.065)|(0.074)|(0.067)|
|Observations|3,259|3,248|3,259|3,248|

Analogous to Tables 5 and 6. Regressor: average firm investment in ICT over firm sales during sample period.

42
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22
# **Figure A.2 Employment and Labor Force Participation in China: Evidence from the China Urban Labor Survey**

<!-- Start of picture text --> A. Employed Share<br>Urban Male Urban Female<br>25 30 35 40 45 50 55 60 25 30 35 40 45 50 55 60<br>Age Age<br>2001 2005 2010 D10 2001 2005 2010 D10<br>Migrant Male Migrant Female<br>25 30 35 40 45 50 55 60 25 30 35 40 45 50 55 60<br>Age Age<br>2001 2005 2010 D10 2001 2005 2010 D10<br>(D10: sample distribution in 2010)<br>B. Labor Force Participation Rate<br>Urban Male Urban Female<br>25 30 35 40 45 50 55 60 25 30 35 40 45 50 55 60<br>Age Age<br>2001 2005 2010 D10 2001 2005 2010 D10<br>Migrant Male Migrant Female<br>25 30 35 40 45 50 55 60 25 30 35 40 45 50 55 60<br>Age Age<br>2001 2005 2010 D10 2001 2005 2010 D10<br>1 .1 1 .1<br>.8 .08 .8 .08<br>.6 .06 .6 .06<br>.4 .04 .4 Fraction .04<br>.2 .02 .2 .02<br>0 0 0 0<br>1 .1 1 .1<br>.8 .08 .8 .08<br>.6 .06 .6 ion .06<br>.4 .04 .4 Fract .04<br>.2 .02 .2 .02<br>0 0 0 0<br>1 .1 1 .1<br>.8 .08 .8 .08<br>.6 .06 .6 .06<br>.4 .04 .4 Fraction .04<br>.2 .02 .2 .02<br>0 0 0 0<br>1 .1 1 .1<br>.8 .08 .8 .08<br>.6 .06 .6 ion .06<br>.4 .04 .4 Fract .04<br>.2 .02 .2 .02<br>0 0 0 0<br><!-- End of picture text --> <!-- Start of picture text --> (D10: sample distribution in 2010)<br><!-- End of picture text --> _Source_ : China Urban Labor Survey (CULS) from 2001, 2005 and 2010. The CULS team worked with local offices of the National Bureau of Statistics to collect representative samples of local and migrant households. In the 2010 survey round, this included 700 local resident households and 600 migrant households per city surveyed. In the first wave, there were 600 local households and 500 migrants sampled per city. Descriptive statistics are presented for the five cities where the survey was implemented in 2001, 2005 and 2010: Fuzhou, Shanghai, Shenyang, Wuhan and Xian. The CULS was developed and administered by the Institute for Population and Labor Economics at the Chinese Academy of Social Sciences (CASS-IPLE) with consultation from faculty at University of Oxford and researchers from the World Bank.

38
<!-- Start of picture text --> Complete model: Median=0.044, 54.6% over 0<br>Partial model: Median=-0.057, 22.6% over 0<br>"=<br>o<br>ro)<br>2s<br>8<br>8<br>°<br>-2 -1 te) 1 2<br>Marginal effect WEB<br>——— Complete model ——— Partial model<br><!-- End of picture text --> <!-- Start of picture text --> Complete model: Median=0.015, 67.3% over 0<br>Partial model: Median=-0.001, 49.5% over 0<br>N<br>0<br>><br>a<br>82<br>°o<br>-5 to) 5<br>Marginal effect EMAIL<br>———Complete model ——— Partial model<br><!-- End of picture text --> <!-- Start of picture text --> Complete model: Median=0.036, 59.4% over 0<br>Partial model: Median=0.056, 100.0% over 0<br>9;<br>8<br>3<br>o<br>-1 -5 oO 5 1<br>Marginal effect EXP<br>——— Complete model ———— Partial model<br><!-- End of picture text --> <!-- Start of picture text --> Complete model: Median=0.001, 60.6% over 0<br>Partial model: Median=0.001, 82.9% over 0<br>8<br>8<br>g<br>a°<br>8<br>o<br>-.01 -.005 f) .005 01 .015<br>Marginal effect MANG<br>——— Complete model ———— Partial model<br><!-- End of picture text -->
<!-- Start of picture text --> ey al \ a TRIPURA (INDIA) 5) a: aan<br>peep 5 \ ee va a at i Coastal District Map<br>rE 6 kes ae ee < as pe A cael ean<br>BAeag | td |.<br>H SS sie/ = ns Sy? : ‘ capi<br>AATRIS) OLR (|<br>INDIA SO tat) Sj Gf \ BP tan | Sineten Ares<br>Le ip %,” « “« °<br>MYANMAR Location Map<br>\ ae 10—0 10 20 Kilometers A<br>BangladeshProjection Transverse Mercator (BTM)<br>\\ :<br>Lt wim<br><!-- End of picture text -->
the qualitative results also suggest that the good quality of student-teacher interactions in preschool may mediate the positive impact on cognitive and social-emotional skills in primary school.

Recent work has highlighted that the treatment impacts of early childhood interventions can differ for subgroups of the sample (Dinarte Diaz et al., 2023). We explore heterogeneous treatment impacts using machine learning tools and causal forests to estimate the Conditional Average Treatment Effect (CATE) (Athey and Wager, 2016, 2019a; Athey et al., 2019a), following Carlana et al. (2022). We observe substantial heterogeneity by child development skills at baseline. For preschool attendance and primary school enrollment, target children with lower scores at baseline benefited more from the program. However, the opposite is true for the skills index. In this case, the target children with higher scores at baseline benefited more, likely due to dynamic complementarities in the formation of skills (Heckman et al., 2010; Conti et al., 2016; Garcıa and Heckman, 2014).

Interestingly, the program impacted other secondary outcomes. First, it resulted in improved parental practices. We leverage data that we collected on parental stimulation and play activities and find that parents in treated communities provide a more stimulating environment for their children (a 0.17 SD effect), engage more in play at home with their children (0.08 SD), and are more involved with the child’s primary school. For example, parents and other household members in the treated communities were 32% more likely to meet with the child’s primary school principal in the past year relative to those in control communities. Complementing this finding, we observe a slight but significant decrease in the labor supply of mothers, possibly suggesting that the program promoted a redistribution of time use from work to investment in children. The vast majority of caregivers interviewed in the qualitative study report that they perceive improved children’s learning, which could serve as a potential mechanism to the increased quality of parental practices.

Second, the program had interesting spillovers to younger siblings of the target child.<sup>4</sup>

> 4We argue that these results are spillovers because these younger siblings were not the target group when the program was being implemented, i.e., these kids were younger than 3 years of age at that time.

4