rafmacalaba/datause-encoder-data huggingface dataset:
15 Note that for all simulations, the 1991/92 HBS data is taken as corresponding to calendar year 1992, and likewise the 2000/01 data is taken as being from 2001. Consequently, the projections apply the annual growth rates starting in 1993, the year following the first survey. The simulations are carried forward one additional year past the second survey, to 2002. An alternative choice would be to assign the two surveys to calendar years 1991 and 2000, respectively, and apply the growth rates from 1992 onwards. Several versions of the analysis (not shown) were run with this assumption, and results were similar.

# **5.1 Simulation with Uniform National Growth Rates**

The simplest version of the analysis is to apply the national GDP per capita growth rates, as shown in Table 2, uniformly to all households. Headcount rates from this simulation are shown in Appendix Table A2 and plotted in Figure 4 below. Poverty levels for the two years corresponding to the surveys, 1992 and 2001, are shown in italics. Headcount rates from the 2000/01 HBS are also appended to the end of table for comparison purposes. The simulated poverty rates for 2001 match the survey data surprisingly well. The survey estimate of 0.357 is well within the confidence interval of the simulated value, 0.343. The simulated headcount rates for “other urban areas” and rural areas also match up well with the survey estimates. This simplest form of the simulation, however, does not reproduce the steeper decline in poverty in Dar es Salaam.

**Figure 4**

<!-- Start of picture text --> Simulated changes in poverty<br>using national growth rates<br>1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002<br>Year<br>Mainland Tanzania Dar es Salaam<br>Other urban areas Rural areas<br>.45<br>.4<br>.35<br>.3<br>.25<br>Fraction below poverty line<br>.2<br><!-- End of picture text --> The overall picture shows the inverse of the growth pattern in Tanzania in the decade: declining GDP per capita in the early 90s drove a steep rise in poverty, while the country’s improved growth trajectory in more recent years has achieved a steady decline in poverty. With additional versions of the simulation, we can assess the sensitivity of this general pattern to the underlying assumptions. Note that applying uniform growth rates to all households does not imply identical
**Table 5: Summary of systematic reviews with meta-analyses on the risk of malnutrition/disease associated with diet in children <5 years**

|Author (Year)|Study Type &<br>Location|Participants|Diet Assessed|Nutrition, health<br>outcomes assessed|Key Findings|
|---|---|---|---|---|---|
|Undernutrition outcom|es|||||
|Azmeraw et al.<br>(2023)|SRM of 10 studies<br>in Ethiopia|Children 6-23 mon<br>(n=14,733)|Dietary diversity|Anemia|Low diet diversity associated with risk<br>of anemia (OR 2.73, 95% CI 2.06,<br>3.39)|
|Belachew and<br>Tewabe (2020)|SRM of 16 cross-<br>sectional studies,<br>Ethiopia|Children <5 y<br>(n=11,924)|Dietary diversity(n=5<br>studies)|Anemia(Hb<11 g/dL)|Low diet diversity (<4 food groups per<br>day) associated with anemia (OR<br>1.71;1.10,2.68)|
|Abdulahi et al.<br>(2017)|SRM of 18 cross-<br>sectional studies,<br>Ethiopia|Children 0-5 y<br>(n=39,585)|Dietary diversity|Stunting, underweight,<br>wasting|Diet diversity was significant<br>protective factor for stunting (n=2<br>studies) OR=0.78 (95% CI 0.20,1.35)|
|Overweight and obesi|tyoutcomes|||||
|Horta et al. (2023)|SRM of 159 studies|Most studies carried<br>out on individuals 1-9y|Breastfeeding|Overweight or obesity|Breastfeeding protective for OWOB:<br>pooledOR 0.73 (0.71,0.76)|
|M. Nguyen et al.<br>(2023) †|SRM of 48 articles<br>(40 cohorts)|Children, median age<br>10 y, range 6 mo to 17<br>y (n=91,713)|SSB intake|BMI|Each serving/day increase in SSB<br>intake was associated with a0.07<br>kg/m<sup>2</sup> (95% CI 0.04, 0.10) higher BMI<br>in children|
|Abbasalizad<br>Farhangi et al.<br>(2022) †|SRM of 33 studies<br>(23 cross-<br>sectional, 1 case-<br>control, 4 cohort, 6<br>longitudinal),<br>included Argentina<br>(3), Mexico, China<br>(7), the Islamic<br>Republic of Iran,<br>Lebanon|Children 2-18 y<br>(n=121,282)|SSB intake|BMI(n=19),<br>body fat percentage(n=5),<br>waist circumference<br>(n=15)|High SSB intake associated with<br>0.75 kg/m<sup>2</sup>increase in BMI in children<br>and adolescents (WMD 0.75; 95% CI<br>0.35, 1.15), higher WC (WMD<br>2.35 cm; 1.34, 3.37) and BFP (WMD<br>2.81; 2.21–3.41).|
|Babio et al. (2022) †|Cross-sectional<br>and prospective<br>cohort studies<br>(most in HICs but<br>included China,<br>Mexico & Lebanon)|Children 2-21 y<br>(n=28,740 for total<br>dairy and obesity)|Dairy product<br>consumption|Overweight, obesity|_Cross-sectional studies:_Total dairy<br>consumption inversely associated<br>with risk of obesity (OR 0.66, 95% CI<br>0.48, 0.91) but not overweight (OR<br>1.04, 95% CI 0.73, 1.49); no evidence<br>for association with milk or yogurt<br>_Prospective studies_: total milk<br>consumption associated with<br>overweight (OR 1.13; 95% CI 1.01,<br>1.26)|

31
<u>Table 3. PPML Regression: Trade Creation</u>

||Depth PP<br>|ML<br>||||||
|---|---|---|---|---|---|---|---|
|VARIABLES|(1)<br>Trade|(2)<br>Trade|(3)<br>Trade|(4)<br>Trade|(5)<br>Trade|(6)<br>Trade|(7)<br>Trade|
|Depth LE|0.118**||||0.195***|0.366***|0.356***|
||(0.053)||||(0.065)|(0.125)|(0.122)|
|Depth All||0.099**||||||
|||(0.042)||||||
|Depth Core LE|||0.059*<br>(0.034)|||||
|Depth Core All||||0.053*||||
|||||(0.030)||||
|old PTAs|||||0.143***|0.185***|0.171***|
||||||(0.050)|(0.057)|(0.055)|
|PTA||||||-0.074|-0.079*|
|||||||(0.049)|(0.048)|
|ln(1+TTRI)|||||||-0.206<br>(0.562)|
|N|110,739|110,739|110,739|110,739|110,739|110,739|94,057|
|Exp.-Year|yes|Yes|yes|yes|yes|yes|yes|
|Imp.-Year|yes|Yes|yes|yes|yes|yes|yes|
|Exp.-Imp.|yes|Yes|yes|yes|yes|yes|yes|
|Period|2002-14|2002-14|2002-14|2002-14|2002-14|2002-14|2002-14|

Note: LE stands for legally enforceable. Robust standard errors, clustered at the country-pair level, are in parentheses.

*** p<0.01, ** p<0.05, * p<0.1

We find that controlling for _old PTAs_ (columns 5 to 7), agreements that are no longer in force and on the content of which we have no information, increases the magnitude and statistical significance of the impact of depth on trade. Specifically, in this specification trade between country pairs that sign an agreement with the highest depth increases by 44 percent. Intuitively, the inclusion of the _old PTA_ variable increases the magnitude and precision of the _depth_ estimates because it allows us to distinguish between country-pairs in the control group that had a PTA at some point in time and those that never had a PTA and for which _depth_ is equal to zero.<sup>25</sup> _core LE_ become insignificant in a specification where we include controls for _old PTA_ , _PTA_ , and bilateral tariffs together, for which there is limited variation within country-pairs. Finally, results are robust to an alternative definition of depth based on the principal component analysis “PCA,” as in Orefice and Rocha (2014). Moreover, we find that results are also robust to the exclusion of crises years (i.e., 2008 and 2009) with coefficients around 10 percent higher than those in specifications using the full sample.

> 25 The old PTA dummy captures the pre-accession agreements for countries that joined the EU after 2002 and a small number of other PTAs no longer in force: the trade agreement between Mexico and the three Northern Triangle countries – El Salvador, Guatemala and Honduras – that was active between 2001 and 2012, the trade agreement between Mexico and Nicaragua (1998-2012), and Closer Economic Partnership Arrangement (CEPA)

20
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these jobs. Since manual workers also comprise the largest single category of workers in formal enterprises (Table 3), the closure of this avenue may contribute significantly to women’s low participation in urban employment. The gender gap narrows with higher skill levels, but administrative, technical and managerial workers form such a small proportion of the total workforce in formal enterprises that this does not have a major impact on women’s employment.

**Table** **<u>3: Distribution of workers by skill-level and sex in formal enterprises</u>**

||Average number of male workers|Average number of female workers|
|---|---|---|
|Manual|6.9|1.0|
|Service|4.4|1.3|
|Administrative|2.8|0.8|
|Technical|2.7|0.3|
|Managerial|1.4|0.2|

Source, UES, 2004.

22. (b) <u>Scale of Operation of Urban Enterprises: Information obtained on turnover of</u> urban enterprises confirms their small size, with the large majority being very small ventures and only a minority medium or large. Table 4 shows that over 15 percent of formal and almost half of informal enterprises have an annual turnover of under USD 1000. Overall, over 93 percent of informal and over 60 percent of formal enterprises have an annual turnover of under USD 10,000.

**<u>Table 4: Annual Turnover of Urban Enterprises</u>**

|**Annual Turnover USD**|**Numbe**|**r of Firms**|**Percen**|**t Firms**|**Cumulative F**|**requency (%)**|
|---|---|---|---|---|---|---|
||**Formal**|**Informal**|**Formal**|**Informal**|**Formal**|**Informal**|
|0-1,000|74|254|15.4|46.6|15.4|46.6|
|1,001-5,000|144|213|29.9|39.1|45.2|85.7|
|5,001-10,000|73|45|15.2|8.3|60.4|93.9|
|10,001-20,000|59|23|12.2|4.2|72.6|98.2|
|20,001-50,000|53|5|11.0|0.9|83.6|99.1|
|50,001-150,000|47|3|9.8|0.6|93.4|99.6|
|150,000-500,000|15||3.1||96.5||
|500,000-1,000,000|8||1.7||98.1||
|150,001-1,000,000||1||0.2||99.8|
|1,000,000|9|1|1.9|0.2||100|
|**Total**|**482**|**545**|**100**|**100**|**100**||

Source: UES, 2004.

23. (c) <u>Sectoral Composition of Urban Enterprises</u> **<u>:</u>** In keeping with trends in other low-income countries, urban enterprises in Timor-Leste are predominantly in trading and to a lesser extent in the construction and services sector. Informal enterprises are almost entirely small trading ventures – perhaps operating from the home and street stalls as vendors and hawkers, as well as petty repair shops (see also section on location of enterprise).

24. _(i) Formal Sector:_ Over two-fifths of formal enterprises operate in wholesale and retail trade and in maintenance and repair. Another one-fifth operates in the construction sector. This is in keeping with the understanding that construction is a growing sector in TL.<sup>4</sup> Services such as health, education and other social services make up another 18 percent of formal enterprises. Hotels and restaurants are 12 percent of these enterprises, while mining is only 5 percent and manufacturing even lower, at less than 3 percent (consistent with TLSS). Therefore, to reiterate: trading, of diverse kinds and perhaps heterogeneous - is at the core of formal

> 4 Wichmann, 2003.

12
-12a-

FIGURE 3 <!-- Start of picture text --> sources of Aevov (in pwentc p or GP)<br>40<br>35<br>30<br>25<br>20<br>15 - TP RvmtUs (non coo/coto.)<br>10<br>7071 7273 74 7576 7778 7980 81 6283 048S 8687 66 69<br><!-- End of picture text -->
Figure 22. Access factors and subsidy design factors affecting targeting performance <!-- Start of picture text -->
1.60<br>Congo<br>1.40<br>1.20<br>Gabon<br>1.00 Togo  Nigeria<br>Guinea  Mozambique<br>Cape Verde Côte d'ivoire<br>0.80 Ghana<br>CAR Cameroon<br>Sao Tome<br>Burkina<br>Senegal<br>0.60<br>Chad<br>Rwanda Burundi<br>0.40 Uganda<br>0.20<br>0.00<br>0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90<br>Access Factors<br>Source:  Banerjee and others 2008.<br>Note : Access factors capture the rates of connection among the poor to the network divided<br>by the rates of connection to the population as a whole. Subsidy design factors are the ratio of<br>the average benefit from the subsidy among all poor households connected to the network<br>divided by the average benefit among all households connected to the network. A value<br>greater than 1 implies that the factor distribution is progressive (pro-poor), because the share<br>of benefits allocated to the poor is larger than their share in the total population. A value less<br>than 1 implies that the distribution is regressive (pro-rich).<br>Tariff Structure and Subsidy Design<br><!-- End of picture text -->

In general the findings are that the subsidy design factor exceeds the access factor. As was to be expected, given the pattern of connections to power, the access factor is always less than one meaning highly regressive. The tariff factor, on the other hand, ranges from 0.4 (indicating a highly regressive tariff structure) and 1.6 (indicating a moderately progressive tariff structure). The most progressive tariff structures are found in DRC, Gabon and Togo. However, for the bulk of countries analyzed are marginally below unity, suggesting that the tariff structures are at best distributionally neutral. However, this is not much of an achievement given that the intention behind the predominantly IBT tariff structures is to favor the poor. This finding is explained by the fact that the traditional IBTs that prevail in Africa tend to be poorly targeted because tariff structures subsidize consumption in the first blocks even for customers whose aggregate consumption is high. On top of that, the consumption threshold for the lower blocks tends to be too high to single out the poor, the price difference between blocks is not very large, and fixed charges are too high.<sup>8</sup>

> 8 Also discussed in Wodon (2007) and Banerjee and others (2008).

33
- 23 -

levelsl Underestimation in the rate of inflation over the period would need, in our view, to be implausibly high to alter the conclusion that poverty decreased.

A significant (though less dramatic) decline in poverty in both urban and rural areas is also indicated if one uses the share of total consumption devoted to non-food goods as the indicator of welfare, thus avoiding the problems of adjusting for inflation. The proportion of the population who devoted three-quarters or more of their total consumption to food fell from 32 percent to 28 percent over the period. Furthermore, our qualitative conclusions are robust to relaxing the assumption that the household level consumption data are even level comparable across dates; poverty is also found to have decreased (though again by a less dramatic margin than CPI adjusted consumptions indicate) if one bases the comparisons of mean consumptions solely on national accounts, only using the household level data tapes to compare relative consumptions at any one date.

Though the caloric intake data is less than ideal (with some underestimation being likely at both dates), there is strong evidence that the extent of undernutrition also fell significantly. This holds for both urban and rural sectors, over a very wide range of alternative measures of undernutrition and it holds for any (unknown) interpersonal distribution of nutritional requirements, provided that this did not also change over the period. The shift in the caloric intake distribution was far from negligible at its lower end; we find, for example, that 27 percent of the 1987 population did not attain a caloric intake which 37 percent bad failed to reach in 1984.

In summary, while legitimate doubts can be raised about the quantitative magnitudes involved, the qualitative conclusion is plain:
mainly serves to investigate to what extent results from an activity perspective will differ from results based on a product perspective.

**Figure 5: Economic growth and degree of path-defying specialization**

<!-- Start of picture text --> 4 IRL<br>MNG CHN<br>LTU<br>TUR LKA TWN MLT<br>KOR<br>POL<br>ROULVA<br>2 EST INDSVK VNM<br>IDNLUX<br>RUS BGR SWD E U THA USA<br>CZE KHM AUS<br>NOR HUNJPN GBRAUT BELDNKCANNLDBGDPHL<br>FRA<br>FIN SVN FJI<br>0 ESP<br>NPL KGZPRT MEXBRA<br>ITA<br>CYP<br>PAK<br>-2<br>GRC<br>.2 .3 .4 .5 .6<br>Average Path Defying Share<br>Orthogonal Component of Real GDP per Capita Growth<br><!-- End of picture text --> _Notes_ : Figure plots the orthogonal component of average real GDP per capita growth rate against the average share of path defying entries (as defined in equation 11) across the eight overlapping periods for each country. Regression control for initial (log) GDP per capita. Slope (standard error) of the linear fit is 3.73 (2.18). Size of circles represent country size measured as average real GDP in 2017 US$. _Sources_ : Authors’ calculations based on Penn World Table version 10.0, ADB MRIOTs and Occupations Database.

Additional data sources and regression results are given in Appendix B. The dependent variable is the average growth rate of GDP per capita in the period [t, t + 5]. The key variable of interest is the share of path-defying entries which appears to be strongly significant and positively related to growth. Interestingly, the positive impact remains even after controlling for factor endowments in terms of human capital levels and financial development. This suggests that the capabilities needed to undertake new path-defying activities go beyond the mere expansion of educational attainment levels and general development of financial markets in a country. It is also found that the impact of path defiance on growth is moderated by the initial level of GDP per capita: it appears to be 26
# Policy Research Working Paper Series

|||Author||Contact<br>_IQLf_<br>r|
|---|---|---|---|---|
|WPS800|The Legal Framework for Private<br>Sector Development in a Transitiona<br>Economy : The Case of Poland|Cheryl W. Gray<br>l Rebecca J. Hanson<br>Michael A. Heller<br>Peter lanachokov<br>Youssef Djehane|November 1991|CECSE<br>37188|
|WPS801|Unraveling the Mysteries of China's<br>Foreign Trade Regime: A View from<br>Jiangsu Province|Arvind Panagariya|November 1991|D. Ballantyne<br>37947|
|WPS802|Strengthening the Bank's Populaf,on<br>Work in the Nineties|Steven W. Sinding|November 1991|0. Nadora<br>31091|
|WPS803|Financial Regulation: Changing the<br>Rules of the Game|Millard Long<br>Dimitri Vittas|November 1991|W. Pitayatonakarn<br>37666|
|WPS804|Global Trends in Raw Materials<br>Consumption|Boum-Jong Choe|November 1991|S. Lipscomb<br>33718|
|WPS805|Privatization in the Soviet Uinion:<br>The Beginnings of a Transition|Sergei Shatalov|November 1991|CECSE<br>37188|
|WPS806|Measuring Commercial Bank<br>Efficiency: Use and Misuse of Bank<br>Operating Ratios|Dimitri Vittas|November 1991|W. Pitayatonakarn<br>37666|
|WPS807|Moderate Inflation|lludiger Dornbusch<br>Stanley Fischer|November 1991|S. Moussa<br>33490|
|WPS808|The New Trade Protection: Price<br>Effects of Antidumping and<br>Countervailing Measures in the Unite<br>States|Ann Harrison<br>d|November 1991|D. Ballantyne<br>37947|
|WPS809|Openness and Growth: A Time<br>Series, Cross-Country Analysis for<br>Developing Countries|Ann Harrison|November 1991|WDR Office<br>31393|
|WPS810|Poverty and Income Distribution<br>during Adjustment: Issues and<br>Evidence from the OECD Project|Francois Bourguignon<br>Jaime de Melo<br>Christian Morrisson|November 1991|D. Ballantyne<br>37947|
|WPS81 1|Comparative Resource Allocations<br>to Human Resource Development|Peter T. Knight<br>Sulaiman S. Wasty|December 1991|D. Afzal<br>36335|
|WPS812|Alternative Forms of External<br>Finance: A Survey|Stijn Claessens|December 1991|S. King-Watson<br>31047|
|WPS813|Price Stabilization for Raw Jute<br>in Bangladesh|Takamasa Akiyama<br>Panos Varangis|December 1991|D. Gustafson<br>33714|
- 22 -

Box 7 (CQnt.) Risk Review Parametes A balance must be struck between the risks of breakdown and the costs of minimizing those risks. Maintenance, replacement or catastrophe back-up agreements with hardware vendors may assist in reducing the risk of hardware failure to a minimum. Software deficiencies are of particular concern and thorough testing procedures are necessary. In addition, where software development or enhancements use assumptions which prove inadequate, the system sponsor or system provider should have procedures in place to make adjustments and corrections on a timely basis. It is imperative that all software programs are properly documented, that the documentation is available to the relevant authorities and system personnel and that the system sponsor or the system provider is staffed with persons with the skills necessary to handle software and other failures.

Adequate procedures are required to ensure that the impact on the system of any human error is minimal. As communication occurs by electronic messages and is highly impersonal, trading on screenbased systems isolates users from the system sponsor and its personnel. The system sponsor should ensure that there is adequate opportunity for dialogue between itself and system users so that each may benefit from knowledge about the system in operation.

Finally, catastrophe procedures which are designed to be used during or after a failure and before the full recovery of all of the components of the primary system is achieved should be adequate and clearly eescribed. Procedures for treatmnent of orders which are in the system before the failure should be clearly established. And there should be express agreement Ls to the allocation of liability for losses resulting from system failures.

Principle 6. Procedures should be established to ensure the competence, integrity, and authority of system users, to ensure that system users are adequately supervised, and that access to the systern is **not arbitrarily or discriminatorily denied.** Access. Computerized trading systems have the potentiel to increase tile degree of direct access to a market well beyond that which is normally available on floor trading systems. For example, computerized trading systems are not subject to the same physical limits in relation to the number of traders on the floor which exist in traditional stock exchanges. Also, unlike floor trading systems, computerized systems permit system users in diverse locations to execute transactions without going through intermediaries on the exchange premises. For these reasons, adequate and well supervised standards for use of and access to the system should be approved by the regulatory authority. Such standards should be wricten in such a way that access to the system is not denied in an arbitrary or discriminatory way.
<!-- Start of picture text --> rh te<br>: & oS 3<br>a<br>fe<br>= -<br>;<br>\ nec Q<br>FArs<br><!-- End of picture text --> <!-- Start of picture text --> \<br>fe Prevalence<br>: . ‘, am - 0m<br>ie ~ es- ase<br>A Multatiew (eaass . a7<br>==, { ) ox, \ mer -070<br>\ od Vavenia 2 ‘<br>Nieabe e a<br>e Sm |<br>S cale:ource:PercentNationalof Surveyindividualson Self-reportedaffected by mentalHealth illness in Sri Lanka(0-100) 2014<br><!-- End of picture text -->