rafmacalaba/datause-encoder-data huggingface dataset:
# **3 - Data and Methodology**

# **_3.1 - Data_**

The empirical analysis in this paper makes use of micro-level data from the Pakistan Integrated Household Survey 1991, (PIHS 1991). The data set consists of 35,774 individuals of all ages, of which 4480 are aged 10-14 with 2348 boys and 2132 girls.<sup>7</sup> The PIHS 1991 was conducted throughout the year 1991, with approximately equal number of households from each region of the country interviewed each month. Thus, the data has a unique quality which can help in exploiting the regression discontinuity design and is ideal for the use of the identification strategy. Another reason for the selection of the year 1991 for such an analysis is that it was a year that was relatively free of much lobbying and international pressure against child labor in the country. This helps identify the true impact of the law, which is the main aim of the paper.

Identifying the households interviewed by months enabled the division of the data set into two groups; the households interviewed during January to April and those interviewed during May to December, giving the pre-intervention and the post-intervention periods respectively. Since the EoCA 1991 was introduced in April and implemented the same month, the two sub-groups of the data may provide suitable comparison groups for the study of postintervention child labor situation in Pakistan. For our study different age and/or occupation groups are used from this pool of data as robustness checks for our findings.

Table 1 gives employment rates for children age 10-14 years in the months January-April and May-December in 1991. There appears to be a statistically significant decrease in the

> 7 A few individuals (12 individuals) reported age more than 100, but we exclude these observations from our analysis.

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The Basel Committee (2010) recommends that colleges “should facilitate effective crisis management by assisting in planning the crisis management meeting, encourage the banking group to produce appropriate information for crisis management and serving as a conduit for information sharing (p.13)”.

A closer look at stages of banking supervision will help to better understand the complexity of the interlinkages between supervisory colleges and Cross Border Crisis Management Groups (CMGs). Claessens Herring and Schoenmaker (2010) describe the three typical stages of banking supervision: prevention, remedial and resolution. The first or preventative stage consists of licensing procedures, ongoing supervision, such as inspections and off-site analysis, and taking disciplinary actions when required. In this stage, policy is developed and supervision is performed to address emerging risks. In the remedial stage, supervisors take actions in response to the problems that have emerged. This can include, improving risk management processes, removing managers and/or placing restrictions on activities or dividends. In the resolution stage, supervisory authorities deal with serious weaknesses and act in concert with central banks, the Ministry of Finance, resolution authorities and bankruptcy courts, if applicable. The instruments range from private sector solutions such as a takeover of a weak bank by another bank, restructuring and bankruptcy) to public sector solutions such as government provision of capital, lender of last resort facilities, nationalization).

**Table 2: Stages of Supervision and the Role of Supervisory Colleges**

|||**_Stage of_**<br>|**_supervision_**<br>||
|---|---|---|---|---|
|||**_Prevention_**|**_Remedial_**|**_Resolution_**|
|**Supervision**<br>**institutions**|**of**|Licensing<br>Ongoing supervision|Risk<br>management<br>changes<br>Management changes<br>Other restrictions|Private sector resolution<br>Bankruptcy/restructuring<br>Public sector resolution|
|||||(Supervisory college)|
|**Leading actors**||**_Supervis_**|**_ory Colleges_**|Central bank<br>Ministry of Finance<br>Resolution authority<br>Courts<br>**_Crisis management_**<br>**_groups _**|

_Source:_ author based on Claessens, Herring and Schoenmaker (2010) p. 34 In reality, these three stages are more of a continuum and each prudential supervisor in a college will of course have its own definition and interpretation. Generally speaking, banking supervisors through supervisory colleges would play the leading role in the first and the second stage, but have a complementary and more supportive role in crisis management situations.

Claessens Herring and Schoenmaker (2010) correctly state that the tools in each stage are interrelated and should be considered collectively. So, the incentives to intervene early using the remedial measures will be driven by the perception of financial resources at risk from failing to take proper action (p.35). A similar view is expressed by the IMF (2010) when stating that “the existence of an effective resolution 21
# **Box 2: An Example of a Performance Oriented Grant: Education grant to set minimum standards while encouraging competition and innovation** _Allocation basis among local governments_ : School age population.

_Distribution to providers_ : Equal per pupil to both government and private schools. _Conditions_ : Universal access to primary and secondary education regardless of parents’ income; improvements in achievement scores; no condition on the use of grant funds. _Penalties for non-compliance with standards_ : public censure, reduction of grant funds. _Incentives for cost efficiency_ : retention of savings. Source: Shah (1998) Conditional non-matching transfers to ensure national minimum standard are rarely used in DTEs. Central government transfers to provincial and local governments in Indonesia (the former roads and education grants), central per capita transfers for education in Colombia and South Africa, and the capitation grant to Malaysian states come close to the concept of such a transfer.

# v _. To influence local priorities in areas of high national but low local priority_

In a federation, there is always some degree of conflict among priorities established by various levels of government. One way to induce lower level governments to follow priorities established by the higher level government is for the higher level government to use its powers of the purse, the so-called spending power. Matching transfers are often used to influence lower level priorities. Both the national and intermediate level governments could legitimately pursue such policies.

Open-ended matching transfers with matching rate (percent of expenditures financed from own sources by the recipient) to vary inversely with fiscal capacity would be consistent with this use. The use of ad hoc grants or open-ended matching transfers for local tax effort would be inadvisable. The former is unlikely to have behavioral responses consistent with grantor’s objectives and the open-ended nature of the latter may create budgetary difficulties for the grantor. India, Malaysia, and Pakistan use conditional closed ended matching programs. Pakistan in late 1990s got into serious difficulty by offering open-ended matching transfers for provincial tax effort. Central government had to abandon this program in midstream as it could not meet its obligations under the program.

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**Figure 3: Woman’s Time Use Results in Minutes at Midline**

<!-- Start of picture text --> Midline: Time use woman<br>personal<br>chores<br>care<br>work<br>social<br>other<br>-100 0 100 200<br><!-- End of picture text --> Note: Figure 3 depicts the coefficient plots with point estimates and the 95% confidence interval from Table 5.

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**Figure 2: Difference in Capabilities, South Africa (LHS) and Other SACU Countries (RHS) versus ASEAN**

**South Africa v. ASEAN (Avg)**

**Other SACU Countries (Avg)  v. ASEAN (Avg)**

<!-- Start of picture text --> Proximity to Markets ‐0.53<br>Natural Capital ‐0.33<br>Human Capital ‐0.16<br>Physical Capital ‐0.29<br>Institutional Capital 0.25<br>Logistics/Connectivity ‐1.02<br>Wage Competitiveness 0.08<br>Market Access ‐0.49<br>Access to Inputs 1.60<br>‐3.00‐2.00‐1.000.00 1.00 2.00<br><!-- End of picture text --> <!-- Start of picture text --> Proximity to Markets ‐0.78<br>Natural Capital 0.23<br>Human Capital 0.26<br>Physical Capital ‐0.20<br>Institutional Capital 0.33<br>Logistics/Connectivity 0.65<br>Wage Competitiveness ‐0.83<br>Market Access 0.67<br>Access to Inputs 1.25<br>‐3.00‐2.00‐1.00 0.00 1.00 2.00<br><!-- End of picture text --> Source: Authors’ calculations from data sources listed in Table 1

# B. How do SACU’s capabilities compare to requirements of GVC sectors?

Overlaying the global requirements of each GVC sector described previously and the capabilities present in SACU economies, Figure 3 depicts the alignment between SACU’s current endowments and the requirements in the largest sectors of GVC trade. The units of the axes are standard deviations from the average endowment. For simplicity, here we average SACU’s endowment across all five SACU countries, although we disaggregate countries in later analysis. The figure helps visualize where SACU’s capabilities fall short of what is required to produce in a sector. The gaps with respect to machinery/electronics and transport are especially apparent in long‐term policy‐dependent capabilities like human capital, physical capital, institutional capital but also logistics/connectivity (short‐term policy variable) and proximity to markets (fixed characteristic). The total gap across all capabilities seems substantially higher in machinery/electronics and transportation as compared to clothing and textiles.

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**Table 4.2 Days above Ozone Daily 1-hour Maximum Standards and Contingency Stages**

|_Ozone(ppm)_|_Bas_|_eline_|_10% _|_Red_|_20%_|_Red_|_Atsta_|_ndard_|
|---|---|---|---|---|---|---|---|---|
|>0.355|0|0%|0|0%|0|0%|0|0%|
|>0.281|8|3%|2|1 %|0|0%|0|0%|
|>0.233|60|18%|25|8%|5|1 %|0|0%|
|>0.110AQS|319|87%|306|84%|285|79%|0|0%|

The highest frequency distribution for the PM1O daily maximum concentration in the ZMVM shows that air quality at that specific place would trigger one _contingencia_ (see table 4.3 and figure 4.4). The highest values are measured at the stations Nezahualcoyotl or Xalostoc.

**Table 4.3 Days above the PM,0 Daily Maximum Standards and Contingency Stages**

|_PM10 (pg/m3)_<br>_Baseline_<br>_10%Red_<br>_20%Red_<br>_Atstandard_|
|---|
|>420<br>0<br>0%<br>0<br>0%<br>0<br>0%<br>0<br>0%|
|>300_Neza<br>1<br>1 %<br>1<br>0%<br>0<br>0%<br>0<br>0%|
|>270_Xal<br>2<br>1 %<br>1<br>0%<br>0<br>0%<br>0<br>0%|
|>15OAQS<br>87<br>16%<br>59<br>12%<br>34<br>7%<br>0<br>0%|
|Figure4.4Cumulative FrequencyDistributionofXalostocStationPM,0 AirQuality<br>Scenarios,1995-99<br>Station Xalostoc<br>300- -<br>. .<br>-|
|_<br>F<br>~~~~~~~~~~~~~~~~~~~+<br>Baseline<br>4F<br>°10%Red<br> <br>|
|250<br>a**I**0%Red<br>e t<br>- ~~~~~~~~~~~~~~~~~at<br>AQS<br>**ab**200-|
|<br>I.00<br>_50_<br>0<br>0<br>50<br>100<br>150<br>200<br>250<br>300<br>350<br>400<br>Days|

Figure 4.4 Cumulative Frequency Distribution of Xalostoc Station PM,0 Air Quality Scenarios, 1995-99 _17_
THE CENTRAL AFRICAN REPUBLIC’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE (0.19 percent of GDP). Another $4 million (or 0.3 percent of GDP) per year could be saved by raising bill-collection efficiency from 64 to 100 percent.

Operational inefficiencies are also present in the water supply sector and cost the CAR about $2 million a year, equivalent to 0.12 percent of GDP, with distributional losses responsible for about 85 percent of the hidden costs and collection inefficiencies for about 15 percent. The CAR could avoid this cost by reducing nonrevenue water from 51 percent to the 20 percent benchmark of a well-functioning utility.

If the CAR tackles the operational inefficiencies in the power and sanitation sector it could expand the budget envelope by 0.62 percent of GDP, which is equivalent to almost 70 percent of the contribution of infrastructure to the CAR’s economies during the earlier 2000s. The burden of operational utility inefficiencies in the CAR is lower than for the benchmark countries (figure 23).

**Figure 23. Uncollected bills and unaccounted losses in power and water utilities, 2009**

<!-- Start of picture text --> Percentage of GDP<br>a. Power sector<br>2.0<br>1.8<br>1.6<br>1.4<br>1.2<br>1.0<br>0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>CAR LIC-Fragile<br>Collection inefficiencies Unaccounted losses<br>Percenatage of GDP<br><!-- End of picture text --> b. Water supply and sanitation sector <!-- Start of picture text --> 0.40<br>0.35<br>0.30<br>0.25<br>0.20<br>0.15<br>0.10<br>0.05<br>0.00<br>CAR LIC-Fragile<br>Collection inefficiencies Unaccounted losses<br>Percenatage of GDP<br><!-- End of picture text --> _Source:_ Derived from Briceño-Garmendia, Smits, and Foster (2009). _Note:_ LIC = low-income country; GDP = gross domestic product.

# **Improving cost recovery from user charges**

Underpricing of power costs the CAR about $4 million each year, or around 0.3 percent of the country’s GDP. If compared with the rest of Africa, where underpricing of power is commonplace, the CAR’s power utility ENERCA is doing better than other fragile, low-income countries. It is estimated that the average total cost of producing electricity has been $0.20 per kWh in the CAR, while the average effective tariff stood at $0.15, as of 2009 (figure 24).

In the water sector, average tariffs charged by SODECA, the CAR’s water utility serving Bangui and seven urban centers, stand at $0.57/m<sup>3</sup> versus an estimated $1.1/m<sup>3</sup> average cost-recovery tariff. The consequent macroeconomic burden of undercharging for water services—at 0.12 percent of GDP—is somewhat lower than that for power (0.18 percent of GDP) and is comparatively lower than in other fragile states. Furthermore, underpricing is the major inefficiency driving up SODECA’s hidden costs.

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20 do enrollment rates. But the income related increase in enrollsmnt rates among girls is significantly larger than it is among boys (Schultz, 1987) A catching up for girls is evident in both cross country comparisons at different **stages** of development and within countries **as** income increases. Equal educational treatment of boys and girls appears to be a "normal good" within **the** family, and as income per capita **increases** and reproductive goals are freely chosen, **a** variety of indicators of consumption and investmnt become more equally distributed between sale and female family members. Public policies sometimes **are** limited in their ability to influence the family's distribution of consumption because the family can, if it wants, compensate for them. A free school lunch program in Brazil or India, for example, leads to decreases in the family's supply of food to those children who benefit from the school feeding program. Part of the family's food that would have been supplied to the children in the program is apparently reallocated within the family to advance the family's own objectives. Nutritional intervention programs have had to take this into account (Chernichovsky and Zangwill, 1988).

There axe more efficient ways to target resources transferred by public programs to specific uses in the family. The **state** could train individuals to accomplish their goal rather than contribute to the general pool of family resources or give the family incone in-kind (i;a. food or health care) or transfer selected items for specific individuals to consume, such as school lunches. If public programs train women for vocational opportunities where they earn cash incomes directly, rather than through integrated (i.e. unpaid) family activities, the gain in women's productivity may shift consumption patterns toward women's priorities. Recent **analyses** of Brazilian data confirm
Table 5: Differences in Means for Demographic Characteristics by Sex Composition

||Mo|thers _(N=74_|_80)_|Fa|thers _(N=54_|_96)_|
|---|---|---|---|---|---|---|
||Same-sex|Two boys|Two girls|Same-sex|Two boys|Two girls|
|Variables|(1)|(2)|(3)|(4)|(5)|(6)|
|Age|0.1252|-0.1683|0.3394|0.0045|-0.3907|0.4085|
||(0.1316)|(0.1510)|(0.1523)**|(0.1546)|(0.1769)**|(0.1795)**|
|Age at frst birth|-0.0160|-0.0414|0.0206|-0.1199|-0.2101|0.0546|
||(0.0807)|(0.0926)|(0.0934)|(0.1102)|(0.1362)|(0.1281)|
|Years of education|-0.0186|0.0020|-0.0270|0.0086|-0.0392|0.0520|
||(0.0728)|(0.0835)|(0.0843)|(0.0920)|(0.1054)|(0.1069)|
|Rural|-0.0014|0.0011|-0.0030|0.0122|0.0241|-0.0083|
||(0.0115)|(0.0132)|(0.0133)|(0.0131)|(0.0150)|(0.0153)|
|Muslim|-0.0121|-0.0109|-0.0051|-0.0082|-0.0109|0.0001|
||(0.0089)|(0.0102)|(0.0103)|(0.0105)|(0.0121)|(0.0123)|
|Catholic|0.0051|0.0057|0.0009|0.0065|0.0078|0.0007|
||(0.0063)|(0.0072)|(0.0073)|(0.0072)|(0.0083)|(0.0084)|
|Orthodox|0.0020|0.0085|-0.0059|0.0003|0.0087|0.0094|
||(0.0058)|(0.0066)|(0.0067)|(0.0067)|(0.0076)|(0.0078)|

_Notes:_ Differences in means (mean of the relevant group minus mean of the rest of the population) and their standard errors (in parentheses). * Indicates statistical significance at 10%. ** Indicates statistical significance at 5%. *** Indicates statistical significance at 1%. The sample of mothers consists of 7480 Albanian women aged 20 to 49 years old with two or more children aged 18 or younger. The sample for fathers consists of 5496 husbands of the married women with two or more children aged 18 or younger. The data used are the 2002 LSMS, the 2005 LSMS, the 2008-09 DHS and the 2012 LSMS 38
ficance of low inflation and competitive exchange rate for export performance is robust across various specifications. There is no significant impact of external debt accumulation on export performance related to AGOA. The role of labor market workings as measured by labor freedom - a quantitative index based on the World Bank’s Doing Business study - in the form of ease of regulations concerning minimum wage, rigidity of hours, difficulty of hiring and associated costs is significant. Countries with stricter labor market regulations impose costs in terms of providing opportunities for expanding export capacity.

We show that many countries in SSA have taken advantage of opportunities provided by AGOA, but the results vary both across countries and over time within a country. Countries with better ICT infrastructure, a relatively better functioning and effective judiciary, stable exchange rates and better macroeconomic environment seem to have registered significant export gains due to AGOA. It is evident that in order to raise exports and improve trade and hence promote growth and transformation of SSA economies, we need to improve a set of institutions in property rights protection and legal structures. Though improvements in other areas of institutions such as reduction of corruption are also important, in terms of trade and exports, emphasis on the rule of law and judiciary quality seems to have greater returns. SSA countries also need to adopt a set of sound macroeconomic policies to keep inflation low and exchange rates stable and competitive. Building on the quality and quantity of physical infrastructure, both ICT and others also present opportunities for expanding exports for international trade.

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Lesotho is by far the only country that exports almost 100% of its apparel to the U.S. under AGOA terms.<sup>33</sup> But, as figure 14 above illustrates, exports from Mauritius – when measured in dollar value per square meter equivalent – are nearly 43% higher. Specifically, value per square meter equivalent for Lesotho is approximately $3.79, while for Mauritius, it is $5.41, and for Madagascar, $4.08.

One advantage Lesotho currently has over many African countries is that it is one of the least developed countries in Africa with the highest labor standards. The reason for that is the close relationship Lesotho has developed with big international buyers (such as GAP and Levi’s) who require all their suppliers to comply with social and environmental standards in their codes of conduct. The Government of Lesotho is collaborating with the ILO on labor law reform and should take advantage of this collaboration by marketing Lesotho to the rest of the world as an international centre for socially responsible labor.<sup>34</sup> The question is, however, if that alone will suffice for the industry as a whole to survive.

# **_C. Producer-Driven Supply Chains: Automotive Parts in South Africa_**

Just like many formerly inward-oriented economies, South Africa’s industry started to face a radically new competitive environment as its trade barriers began to fall starting in the late 1980s.<sup>35</sup> The initial result of this reform in trade policy was a sharp increase in the trade deficit in the automobile and components sector of South Africa. In 1995, the South African government’s Motor Industry Development Program (MIDP) heralded a much-lauded shift in vision and aims. Its main objective was to improve the international competitiveness of firms in the industry, enhance growth through exports, and stabilize employment levels. In order to achieve these aims, a series of export-oriented incentives were introduced, coupled with a reduction in import tariffs between 1995 and 2002.<sup>36</sup> Since the implementation of the MIDP, South Africa has seen rapid growth in the auto sector, based on a speedy rise in the exports of completely-built-up units (CBUs), especially after 1998. In addition to exports of CBUs, there was also a marked increase in the exports of direct car components.

With respect to CBU exports, three German assemblers sourced large numbers of cars from South Africa to their global markets. _BMW_ decided to specialize on the 3-series car in order to obtain scale economies, and displaced local production of the 5- and 7-series with imports. Its exports of CBUs increased steadily from

> 33 Source: Africa Coalition for Trade, Inc.

> 34 Ibid.

> 35 Source: Barnes, J. and R. Kaplinsky, “Globalization and trade policy reform: whither the automobile components sector in South Africa?”, _Competition and Change_ 4, 3 (2000), pp. 211243

> 36 For the specifics on those export incentives, see Barnes, Kaplinsky and Morris, _Industrial Policy in Developing Economies: Developing Dynamic Comparative Advantage in the South African Automobile Sector_ , May 2003

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