rafmacalaba/datause-encoder-data huggingface dataset:
Figure 3. Contextual and process analysis <!-- Start of picture text --> C‐1. Economic context in C‐2. Policy environment<br>which the project operates and political context in which the project operates C‐3. Institutional and operational context Physical environmentC‐4.<br>P‐1 P‐5 P‐6<br>[FormulationRationale]DesignAnd InputsP‐2 Implementation[Activities]Process P‐3 OutputsP‐4 Unintended]Outcomes[IntendedAnd Unintended][IntendedImpactsAnd SustainabilityP‐7<br>C‐5. Socio‐economic and cultural characteristics of the affected populations<br>Years<br><!-- End of picture text --> <!-- Start of picture text --> 3<br><!-- End of picture text --> Figure 3 presents a stylized model that provides a framework for assessing both the quality of project implementation and the level of conformity to the original implementation plan and contextual factors that affect both overall implementation and factors explaining variations of performance in different project settings. Steps P-1 through P-7 describe the typical stages of the project implementation process, while Boxes C-1 through C-5 identify five sets of contextual factors such as the local, regional and national economy; the policy and political environment; the institutional and operational environment; the physical environment (droughts, floods, soil erosion etc); and the socio-economic and cultural characteristics of the affected populations that can affect implementation and impacts in different locations.

While some contextual factors can be measured quantitatively (for example, percentage changes in indicators such as unemployment), others will usually be measured qualitatively (for example, assessing whether the local political context is supportive of, neutral or opposed to the project<sup>12</sup> ; the capacity and performance of local agencies involved in the project). The decision whether to use quantitative and/or qualitative indicators will also depend on data availability, so that in one country opinion polls or citizen report cards may provide detailed statistical data on attitudes to the performance of public service agencies, while in another country the rating may be based on the opinion of the local consultant or the pooled views of several key informants. For large projects with a longer time horizon and more resources, it may be possible to commission local researchers to conduct an in-depth diagnostic study covering all of these factors, but more commonly the ratings will be based on rapid data collection. Often mixed method data transformation techniques will be used so that qualitative ratings are aggregated into dummy variables that can be incorporated into regression analyses. Where time and resources permit this can be an iterative process (Figure 4) in which researchers return to the field to conduct in-depth analysis to explain how the different contextual factors influence implementation and outcomes.

> 12 On attempts to assess such political contextual variables, see Barron, Diprose and Woolcock (forthcoming).

14
**Table 8. SMEs or medium-and-large firms**

|Dependent Var.||Female en|trepreneur||
|---|---|---|---|---|
||SM|Es|Medium and|large firms|
||(number of em<br>|ployees three<br>|(number of em<br>|ployees three<br>|
||years ago:|0 or fewer)|years ago:|above 50 )|
||(1)|(2)|(3)|(4)|
|F_c|0.624***||0.264**||
||(0.108)||(0.105)||
|F_cj|-0.051|-0.018|-0.122|-0.099|
||(0.085)|(0.072)|(0.080)|(0.062)|
|OwnLargest|-0.004|-0.002|-0.049***|-0.054***|
||(0.009)|(0.008)|(0.010)|(0.011)|
|Small3|0.032***|0.033***|||
||(0.004)|(0.004)|||
|Large3|||-0.004|-0.004|
||||(0.005)|(0.005)|
|Age6_10|0.001|-0.002|0.004|0.003|
||(0.007)|(0.007)|(0.012)|(0.012)|
|Age10plus|-0.011*|-0.009|0.000|0.003|
||(0.006)|(0.006)|(0.012)|(0.013)|
|Corruption|-0.012|0.011|-0.009|0.036**|
||(0.014)|(0.013)|(0.014)|(0.018)|
|Overdraft facility|-0.015|0.011|-0.000|0.007|
||(0.016)|(0.016)|(0.012)|(0.017)|
|Trade Credit|-0.047*|-0.011|-0.005|0.018|
||(0.024)|(0.018)|(0.021)|(0.021)|
|Inf. Competition|0.007|0.006|0.008|0.005|
||(0.013)|(0.010)|(0.014)|(0.015)|
|Outage|-0.024*|0.015|-0.012|-0.004|
||(0.014)|(0.010)|(0.012)|(0.014)|
|Web|0.019|0.006|0.019|0.021|
||(0.015)|(0.014)|(0.015)|(0.016)|
|Capacity Agglo.|-0.070**|-0.047*|0.011|0.018|
||(0.030)|(0.026)|(0.024)|(0.028)|
|Lngdppc|-0.014<br>||-0.015*<br>||
||(0.010)||(0.008)||
|Education|0.043***||0.008||
||(0.014)||(0.012)||
|Urbanization|0.000||-0.000||
||(0.000)||(0.000)||
|**Country FE**|**No**|**Yes**|**No**|**Yes**|
|Industry, Year FE|Yes|Yes|Yes|Yes|
|Observations|33,637|35,398|11,959|12,304|
|AdjustedR<sup>2</sup>|0.063|0.097|0.027|0.047|

Notes: *, **, *** represent statistical significance at the 10, 5, and 1 percent levels. Heteroskedasticitycorrected standard errors clustered at the country-industry level in columns. OLS are used here. Based on non-FDI firms, i.e. we delete FDI firms with 10% or more foreign ownership.

30
39 approach to reform has definite merits,<sup>especially if reserves have been built</sup> up to tide the country over the period<sup>of economic disruption that is likely</sup> to follow. However, it too runs high<sup>risks, because of the potential for</sup> chaos.

Especially in this situation, technocratic solutions are not sufficient. In addition to tryi.ng to define optimal, or even feasible,<sup>transition</sup> strategies, economists must have an<sup>eye for the major inconsistencies,</sup> risks and dead-ends likely to result from<sup>strategies driven by political processes,</sup> and must seek ways to defuse such<sup>problems, if possible before they become</sup> aerious enough to undermine reform.<sup>At the same time, politicians have to</sup> recognize that the present crises<sup>have been created by the neglect of economic</sup> factors, and that political considerations alone cannot drive the reform process.
31 devaluation in SSA economies results in output contraction and high inflation. A few empirical studies seem to confirm this. For example, a study conducted by Demeke (1992) on a sample of 30 SSA countries for the period 1980-88 concluded that the effects of currency depreciation on output and export was at best insignificant and that it triggered a high rate of inflation. The effects on the current account balance were positive but due largely to import compression. Two methodologies were used in this study: the before-after approach and the econometric techniques. However, using data from the period 1965-89, Balassa (1989) analyzed SSA economic performance in general and agriculture exports in particular. He found that a 1 percent change in the real exchange rate is associated with a 0.8 to 1 percent change in the ratio of exports to output in SSA countries. Balassa also found that the response of the export-output ratio to the real exchange rate changes for SSA countries is higher than for other parts of the world. His evidence on export shares argues against the prevailing pessimistic export position.L9/ Using a CGE model for two African countries, Madagascar and Niger, Dorosh (1994) and Dorosh, Essama Nssah, and Samba-Mamadou (1994) found positive association between real exchange rate depreciation and changes in real exports. A RER depreciation of 10 percent was associated with an increase in real exports of 5.9 percent in the case of Madagascar and 3.4 percent in the case of Niger.

In SSA economies, the tradeable sector is constituted essebtially by the agriculture sector. For this reason, supply response by tradeables will be measured by the supply response of the agricultural sector. Two caveats should be borne in mind. First, imports of manufactured goods are important, especially the essential products that cannot be domestically produced. Second, tradeables, on the export side, are made up of not only agricultural products, but also non-primary commodities (including mineral products and oil). It is believed that the results are essentially the same for mineral producing countries as for agricultural producing countries except that the underlying elasticities involved are lower.

Although SSA countries differ greatly in their geographical and physical conditions, weather patterns, and cultural heritage, the similarity of their economic structures is striking. In most SSA countries, agriculture dominates the economy and for many, accounts for 30 to 60

**_191_ BDlaa's results rely on regrcssions hlving low coefrciunts of detecnination (the highcr is equal to 0.092), and, thexefom, must be interpreted with caution.**
The slowdown in population growth rate has been preceded by a sharp decline in fertility rates (Figure 11). The number of births of an average Nepali woman declined from over 6 in the 1970s and over 5 in the 1990s to around 2 in 2014. Demographers have variously attributed this fertility transition in Nepal to the spread of mass education, increasing female labor force participation, and mechanization of agriculture (Bhandari and Ghimire 2013; Axinn and Barber 2001). Another potential driver is the increase in urbanization. The share of urban population has been increasing steadily, from 3 percent in the 1960s, to 9 percent by 1990, and to 18 percent by 2014 (World Bank 2016b). Nepal’s urban population growth has been the fastest in the region, although the country remains the least urbanized in South Asia today (Muzzini and Aparicio 2013). More recently, the social and economic changes, brought by the increase in the migration of overwhelmingly male population together with an increase in educational attainment of girls, have led to delayed marriage and reduction in total fertility (Shakya and Gubhaju 2016).

**Figure 11: Population and Population Growth in Nepal**

<!-- Start of picture text --> 30 7<br>6<br>25<br>5<br>20<br>4<br>15<br>3<br>10<br>2<br>5<br>1<br>0 0<br>Rural Population Urban Population<br>Population Growth (annual %) Fertility rate (Birth per women)<br>Total Population (millions)<br>Population Growth (%)/Fertility Rate (birth per woman)<br>1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014<br><!-- End of picture text --> Source: World Development Indicators (World Bank 2016b) The dramatic fertility transition in the last two decades and the reduction in average household sizes accompanied by the declining dependency ratio had a significant effect on the observed 19
12 <!-- Start of picture text --> Figure 8 4 : Thai Cassava Export Composition (Volume of Final Products)<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>Starch Pellets Chips<br>1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008<br>Millions<br>Metric Tonnes<br><!-- End of picture text --> _Source:_ TTTA (2004 and 2009)

**Figure 9: Shares in Thai Cassava Starch Export to China**

<!-- Start of picture text --> 80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>2001 2002 2003 2004 2005 2006<br>Native starch Modified starch<br><!-- End of picture text --> _Source: TTSA (2008)_

> 4 There are major differences in the data on production and trade provided by the TTTA and COMTRADE. To facilitate a comparative analysis of Thai export trade we have used COMTRADE as a data source on exports. But since COMTRADE data does not distinguish between pellets and chips, TTTA is used a the source of the product composition of dried cassava trade.
# **2. Introduction**

## **The G20 reform agenda**

In the wake of the global financial crisis, the G20 embarked on an ambitious financial regulatory reform agenda to address the fault lines that caused the crisis and build a safer, more resilient global financial system that better serves the real economy while preserving its open and integrated structure.

This reform agenda has been coordinated through the Financial Stability Board (FSB) and involved significant work by the three main international regulatory standard-setters in banking, insurance and securities.<sup>1</sup> Most of this work has focused on four core areas:<sup>2</sup>

1. **Making financial institutions more resilient** by lowering the probability and cost of failure through higher capital levels, limitations on leverage, more liquidity, improved risk governance and culture, and risk-adjusted remuneration incentives;

2. **Ending “too-big-to-fail”** through enhanced resilience, more intensive supervision and more effective resolution of systemically important financial institutions (SIFIs); 3. **Addressing “shadow banking” risks** , by regulating non-bank credit intermediation, limiting the interconnectedness between banks and other parts of the financial system, and analyzing potential risks to financial stability posed by asset management activities and financial technology developments; and 4. **Making derivatives markets safer** , through reporting of all over-the-counter (OTC) derivatives transactions to trade repositories; central clearing and, where appropriate, trading on exchanges or electronic trading platforms of standardised OTC derivatives; and higher capital and margin requirements for non-centrally cleared derivatives.

The global benefits of the reform agenda are expected to significantly outweigh the economic costs. However, the costs and benefits of the G20 reforms may differ across countries, particularly for EMDEs. Therefore, as the design and implementation (in particular in FSBmember countries) of the reforms nears completion, it becomes increasingly important to

> 1 The Basel Committee on Banking Supervision, the International Association of Insurance Supervisors and the International Organization of Securities Commissions.

> 2 Also see the FSB’s annual reports to the G20 (e.g., FSB (August 2016)).

5
is consistent with how the **GVC** _backward_ (i.e. **VS** ) measures the portion that is related to backward GVC connections.

Finally, other studies have measured a country’s forward GVC participation by identifying the export components that are later re-exported by the direct importer, as we propose here (see, among others, Rahman and Zhao, 2013; Cappariello and Felettigh, 2014; Ahmed et al., 2017; Altomonte et al. 2018). However, these contributions rely on the decomposition of gross exports of Koopman et al. (2014) or, alternatively, on that of Wang et al. (2013). The problem, discussed in more detail in Section 5.2, is that these methodologies do not properly allocate countries’ exports between the share that is directly absorbed by importers and the one that is re-exported abroad. The resulting measures of GVC participation are also imprecise.

# **3.2 Bilateral sink-based breakdown**

While the source-based approach discussed above is most suited to examining the production linkages, the sink-based approach is most appropriate when the focus is on final demand and how it is related to the total value-added produced in a country. That’s because in the sink-based decomposition a given item is accounted for as ‘value-added’ the last time it leaves national borders, and, in the case of multiple crossing, it is considered ‘double counted’ in prior shipments. Reconsidering, for instance, the illustrative example of Figure 3, the whole value-added generated in phases 1 and 2 is accounted for as such in the last shipment from country _s_ (i.e. in shipment 2), whereas the value of shipment 1 is entirely attributed to the double-counted term. Then, in order to single out the ‘value-added’ components in a sink-based framework, it is necessary to isolate the portion of ultimate shipments _/s_ within a certain bilateral trade flow. These ‘ultimate exports’ ( **E**<sup>(</sup> _sr−→_ **Y** _∗_ )) are made up of final goods ( **Y** _sr_ ) and of intermediate goods that do not re-enter country _s_ ’s _/s −→_ **Y** _∗_ ) exports, before reaching the ultimate destination ( **A** _sr_ **X** _j_<sup>(</sup> ). Since the latter are commensurate with final goods as concerns the exporting country _s_ , the overall value-added can be computed by pre-multiplying the vector of ‘ultimate exports’ by the **VB** matrix. In other words, once the part of ‘ultimate exports’ is singled out, the value-added in exports can be computed in the same way as how the **VBY** matrix is used to measure the total value-added in final demand (see Appendix A). In particular, the global Leontief inverse matrix **B** takes into account all the upstream production stages, as required by the sink-based approach. Conceptually, assuming 21
# 5 Numerical Calibration

To calibrate the model for Brazil, several data sources are used. The World Development Indicators (WDI) database of the World Bank, data from the 2009 National Household Sample Survey (PNAD), produced by IBGE, and data available in published papers, as needed.

On the household side, the annual discount rate is set at 003, as in Glomm and Rioja (2004). This implies that the discount factor is equal to 097 on a yearly basis. Interpreting a period as 25 years in this framework yields an intergenerational discount rate of 097<sup>25</sup> = 0467.

To calibrate women’s bargaining power, as defined in equation (38), requires setting six parameters: , κ ̄ , <sup></sup> , 3, 4, and , and knowing the equilibrium value <sup></sup> . As discussed below, coefficients 3 and 4 are set equal to 07 and 01, respectively, and <sup></sup> = 0185. The parameter  is set to a “neutral” value of  = 1 and  is set at 05, to capture the fact that endogenous “macro” factors play only a limited role in determining women’s bargaining power. It is also assumed that there is some initial bias in mothers’ rearing time allocation toward boys and therefore set <sup></sup> = 06. The initial bargaining power of women κ is calibrated as in Agénor (2012a), by using the relative literacy rate of adult females (ages 15 and above), divided by the sum of literacy rates of adult males and females–which can be viewed as a measure of the relative human capital of women. As noted earlier, this corresponds to the main determinant of bargaining power.<sup>22</sup> Using WDI data for 2009, this gives κ = 902(902 + 898) = 0501. By this measure, therefore, there is not much evidence of gender bias in the family in Brazil, although some other measures (based, in particular, on control of household assets) would suggest otherwise. Expression (38) can therefore be solved ̄ ̄ backward for the parameter κ, thereby giving κ = 0395.

Survival probabilities <sup></sup> and <sup></sup> are calibrated as follows. In 2010 life expectancy at birth in Brazil was 697 for men and 767 years for women, with an average of 731 years.<sup>23</sup> This gives an annual death rate of 1697 = 0014 for men and 1767 = 0013

> 22See the references provided earlier.

> 23In principle, the adult survival probability in the model should be calculated on the basis of life expectancy at middle age. However, no such data are available.

20
-32 -

logistic models corrected for autocorrelation, a significant association was found between oxidants and daily incidence of eye irritation. Specifically, the results indicated: logit (eye irritation) = 0.0202 * ozone (pphm) The standard error of the estimated regression coefEfcient was 0.0018. Taking the derivative, analyzing, and substituting the mean incidence rate of eye discomfort of 3.75 percent, the following functions are obtained for adults, in terms of cases per year per annual change in average 1-hour maximum ozone (ppm): Upper change in eye irritations = 29.9 * change in 1-hour max ozone (ppm) Central change eye imtations = 26.6 * change in 1-hour max ozone (ppm) Lower change in eye irritations = _23A_ * change in 1-hour max ozone (ppm) Asthma Exacerbation. Whittemore and Korrt? studied the acute effect of oxidants (including ozone) on the increased probability of a daily asthma attack. The data were taken from 16 panels of adult asthmatics located in six Los Angeles communities. The median one-hour maximum oxidant level ranged from 0.03 to 0.15 ppm across the communities studied. with single day peaks of 0.40 ppm. The study used a statistically powerful approach to estimate both individual-level and group effects. Oxidants were found to be statistically related to exacerbation of asthma, after controlling for asthma status on the previous day, temperature. hunidity, and day of study. Using a logistic model. they obtained a regression coefficient of 1.66 and a standard error of 0.72. We use a baseline daily probability of asthnma attack of 0.13 as discussed above.

In a similar study using daily data on asthmatics in Houston. Stock et al-55 report an association between ozone and the likelihood of an asthma attack. The regression specification included several pollutants, pollen, humiditv, temperature and whether an effect occurred on the previous day. The results from the regression model that included particulate measurements was used to generate the upper bound.
54 2001), but it remains to be seen whether cost-effective strategies for changing batterer behavior can be found.

# **_Shelters_**

Many researchers and advocates have called on governments and donors to create shelters for women who experience GBV. Typically, these facilities offer emergency refuge as well as counseling, medical and legal assistance, job training, telephone hotlines, and other services. Most rigorous evaluation studies on the effectiveness and quality of shelters come from settings such as the United States, where over 1200 were in operation as of 1998 (Chalk and King, 1998). In high-income settings, survivors consistently rated shelter services highly, relative to mixed reviews of other institutions such as health services, police and courts. Many, however, question the feasibility and cost-effectiveness of shelters in middle and lowincome settings, where they remain rare (e.g. Larrain, 1999).<sup>44</sup> Documentation of the Acción Ya shelter in Estelí, Nicaragua indicates that for some women, the shelter provides a crucial opportunity to escape from immediate violence and to explore alternatives, particularly when the shelter is coordinated with other social and counselling services (Centro Acción Ya, 1999). Shelters, however, are very expensive to maintain and it is difficult to keep their location secret, particularly in small towns or rural areas. In Latin America, women's groups have tended to focus efforts on organizing informal strategies that help women and children find refuge among friends, family or volunteers.

# **_Support groups for survivors_**

Support groups are effective and low-cost techniques for helping survivors overcome their experiences of violence. There are several Latin American organizations—CEFEMINA in Costa Rica and the Flora Tristán Center in Peru are good examples—with extensive experience in organizing self-help or support groups for violence survivors _._ The PAHOsupported networks in Central America and the Andes have also developed a model for facilitating support groups in institutional settings such as health centers.

One of the main advantages of support groups is that they enable centers to respond to many more individuals than would be possible with individual psychological care. Additionally, the group facilitator does not have to be a mental health professional, although special training is necessary. Another advantage is that women are given the opportunity to help each other and to realize that they are not the only person suffering from violence. In some cases, support groups have led to collective action. These have all been identified in qualitative studies as key factors that enable women to leave violent relationships. Unfortunately, there are no quantitative evaluations of the impact of support groups on revictimization in Latin America or the Caribbean.

> 44 Activists, on the other hand, often question why victims should be forced to leave their homes and neighborhoods, rather than perpetrators.