rafmacalaba/data-use-mentions-extended huggingface dataset:
interstate and societal violence ( _inttot_ and _civtot_ ), as well as a dummy variable, _dum_mepv_ , which equals 1 for any period that contains a major episode of political violence. Note that Systemicpeace.org data does not include data for 2019.<sup>17</sup>

> 17 In future updates of the dataset, we plan to include data from the Varieties of Democracy Project to capture institutional quality.

-12-
The data (Table 3) further suggest that manufacturing becomes a leading sector in towns in Zhejiang, whereas in other two provinces agriculture remains the leading sector. About 40 percent people employed in manufacturing sector in Zhejiang, whereas in Henan and Sichuan, there were only 12 percent and 14 percent employed in the manufacturing sector respectively. But, retail and hotel sector seem well developed in these two provinces. This could also have created more job opportunities. It is also interesting to note that the percentage of people employed in the local government institutions were higher in the less developed regions such as Henan and Sichuan than in the developed region of Zhejiang.<sup>3</sup> Table 3 Employment by industrial sector in towns in three provinces: 2000

|Province|1|2|3|4|5|6|7|8|9|
|---|---|---|---|---|---|---|---|---|---|
||||(|%)||||||
|Zhejiang|16.54|6.76|39.50|4.74|17.38|1.27|4.59|5.60|3.54|
|Henan|43.21|5.37|11.92|4.36|12.68|1.73|2.64|8.44|9.46|
|Sichuan|32.50|6.55|14.07|5.33|18.12|1.66|4.32|10.00|7.22|

Sources: calculated from Tabulation on the 2000 Population Census of the P. R. China, Table 4-1b, page 989-1042.

Note: 1, agriculture; 2, construction; 3, manufacturing; 4, transportation, and telecommunication; 5, retail
# Table 3: Round 1 characteristics - Government officials survey

||(1)<br>ULGSP LGA|(2)<br>Control LGA|(3)<br>Dif|(4)<br>p-value|(5)<br>N|
|---|---|---|---|---|---|
|Master plan up to date|0.46|0.27|0.19|0.03|120|
|Master plan approved in previous 2 years|0.33|0.12|0.21|0.00|120|
|LGA has formal plan for capacity building|0.94|0.62|0.33|0.02|39|
|Showed formal plan|0.76|0.46|0.30|0.09|30|
|Percentage of unplanned settlements|48.96|48.45|0.51|0.94|59|
|Seldom experience delay in preparing fnal budget|0.86|0.86|-0.01|0.92|155|
|Seldom experience delay in guidelines from central gov. for fnal budget|0.53|0.56|-0.03|0.71|156|
|Agrees that budget was executed in accordance with expected results|0.16|0.11|0.05|0.14|464|
|Agrees that disbursements from central government were timely|0.09|0.04|0.05|0.02|453|
|Position flled? Municipal/City/District Internal Auditor|0.94|0.79|0.16|0.01|120|
|Agrees that ofce of internal audit is independent|0.68|0.58|0.10|0.02|459|
|
(2009) for the Mombasa-Nairobi corridor in East Africa (1.88 times that in the U.S.) and for the Bamako-Accra corridor in West Africa (3.28 times that in the U.S.).

# **6 Bridging the Methodologies**

I finish the review with a comparison of methodologies laid out so far and a discussion of how they can be used in tandem. Table 1 provides a summary of data requirements, types of transport costs inferred and challenges for each.

As described above, estimation based methods recover trade costs at large, including frictions other than transportation costs. In their review of international trade costs, Head and Mayer (2013) make an accounting exercise using observable international shipping costs,<sup>9</sup> and a range of reasonable parameter values for the elasticity of trade to trade costs. Their results suggest that "dark trade costs," i.e., what cannot be accounted for and is therefore a residual, explains between 50-85% of the effect. Similar to the literature trying to explain per capita income differences across countries using observable capital and labor stocks, a large unexplained residual remains as the measure of our ignorance. In the context of domestic trade, this residual component is expected to be smaller since some of the border-related frictions are absent. Still, an expected gap is an important point to keep in mind for practitioners when they compare estimated trade costs with survey-based or imputed transport costs.

Such comparisons, however, are valuable in that they provide benchmarks across studies. Similar to the practice by Atkin and Donaldson (2015) described above, Porteous (2019) leverages information generated by different methodologies. After estimating trade cost for agricultural commodities in Africa, he compares the values for the corresponding corridors with the trucking costs from Teravaninthorn and Raballand (2009). His trade cost estimates are 50 to 100% higher than survey-based freight costs, which, per the discussion above, is an expected outcome since price-differentials capture more
119***|-94.086|0.004|28.196|-0.119***|-130.179|
||(0.034)|(92.347)|(0.013)|(77.689)|(0.032)|(84.062)|
|Treatment_×_Endline|-0.008|-101.556|0.014|33.650|-0.007|-135.206|
||(0.057)|(216.646)|(0.022)|(118.138)|(0.052)|(164.083)|
|Mean in control|0.430|640.652|0.048|132.113|0.420|508.539|
|Adjusted R-squared|0.117|0.027|0.023|0.000|0.112|0.018|
|Observations|13464|13464|13464|13464|13464|13464|

**Source:** Author’s analysis based on original survey data. **Notes:** The table reports ITT estimates based on specification (2) estimated with OLS. The sample includes observations from ultra-poor households surveyed at the midline and endline surveys. All specifications control for the baseline level of the outcome, survey wave and subdistrict (strata) fixed effects. Standard errors are clustered at the BRAC branch office level (unit of randomization). All monetary values are measured in Bangladeshi Takas, deflated to 2007 prices using the annual CPI index published by the Bank of Bangladesh. In 2007, 1USD=69BDT. *** (**) (*) indicates significance at the 1% (5%) (10%) level. The dependent variable in Panel A, column 1 is a dummy variable (DV) equal to 1 if the respondent’s household
at risk for depression: a prediction score performance in cohorts based in 3 different continents. _Journal of the American Academy of Child & Adolescent Psychiatry_ , 60(2).

- Rosenberg, M. (1965). _Society and the Adolescent Self-Image_ . Princeton University Press.

- Rossell ́o, J., Bernal, G., and Rivera-Medina, C. (2012). Individual and group CBT and IPT for Puerto Rican adolescents with depressive symptoms. _Journal of Latinx Psychology_ , 14(3):36–51.

- Salomon, J. A., Haagsma, J. A., Davis, A., de Noordhout, C. M., Polinder, S., Havelaar, A. H., Cassini, A., Devleesschauwer, B., Kretzschmar, M., Speybroeck, N., et al. (2015). Disability weights for the Global Burden of Disease 2013 study. _The Lancet Global Health_ , 3(11):e712–e723.

- Salomon, J. A., Vos, T., Hogan, D. R., Gagnon, M., Naghavi, M., Mokdad, A., Begum, N., Shah, R., Karyana, M., Kosen, S., et al. (2012). Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010. _The Lancet_ , 380(9859):2129–2143.

- Saxena, S., Thornicroft, G., Knapp, M., and Whiteford, H. (2007). Resources for mental health: scarcity, inequity, and inefficiency. _The lancet_ , 370(9590):878–889.

- Schwarzer, R. and Jerusalem, M. (1995). Generalized self-efficacy scale. In Johnston, M., Wright, S., and Weinman, J., editors, _Measures in Health Psychology: A
<!-- Start of picture text --> Figure 2. Key growth drivers in WAEMU and Figure 3. Key growth drivers in WAEMU and<br>SSA (2011-2016) SSA (2000-2010)<br><!-- End of picture text --> <!-- Start of picture text --> 3.5 3.0<br>2.5<br>2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>-0.5 WAEMU SSA WAEMU SSA<br>Structural Stabilization Residual (unexplained growth) Persistence<br>External Persistence External Stabilization<br>Residual (unexplained growth) Structural<br>Source: Authors’ estimates based on data described in Section 3. Source: Authors’ estimates based on data described in Section 3.<br>Figure 4. WAEMU and SSA: Structural drivers of Figure 5. WAEMU and SSA: Structural drivers<br>growth (2011-2016) of growth (2000-2010)<br>1.8 0.8<br>1.3 0.6<br>0.8 0.4<br>0.3 0.2<br>0.0<br>-0.2 WAEMU SSA<br>WAEMU SSA<br>-0.2<br>-0.7<br>Schooling Credit/GDP Trade/GDP<br>Gov Cons./GDP Infrastructure Schooling Credit/GDP Trade/GDP<br>Source: Authors’ estimates based on data described in Section 3. Source: Authors’ estimates based on data described in Section 3.<br>Figure 6. Key growth drivers in WAEMU Figure 7. Structural drivers of growth in<br>countries (2011-2016) WAEMU countries (2011-2016)<br>4.5 2.5<br>3.5 2.0<br
40 See next page for table notes.

Source: Authors ̳ calculations using Demographic and Health Surveys microdata. Notes: Robust standard errors are shown in parentheses. Sample size: 4668 observations.

(1) Sample is restricted to the relevant malaria zone.

(2) Observations from strata with single sampling unit were excluded.

(3) Figure based on a different sample – children born up to 12 months before the interview and alive.

(4) Figure based on a different sample – pregnant women in full DHS sample.

(5) Based on children alive only. Vaccination records are not available for deceased children. For definition of "all vaccinations" see Annex.
with a random effect to one that estimates state results directly without a random effect. The latter has the advantage of being much simpler to estimate, particularly when it comes to measures of uncertainty.

# **C. Municipal-level estimates for sampled municipalities.**

We now turn to municipality-level statistics, which the survey is not designed to estimate reliably. All reported estimates in this section pertain to in-sample municipalities only, so that the direct and SAE estimators are compared over the same municipalities. We begin by comparing measures of uncertainty for direct estimates and small area estimates. We present these results for all four labor market statistics in Table 4 . The estimated mean squared error is always substantially smaller for the small area estimates than the direct estimates. This difference is largest – in percentage terms – for male labor force participation, where the estimated mean squared error is around a third as large as the direct estimate, roughly equivalent to effectively tripling the size of the sample.

The second row reports coverage rates, which is the share of municipalities for which the true census value is within 1.96 standard errors of the point estimate. Despite the smaller estimated mean squared error for the small area estimates, the coverage rates are also higher, again across all four indicators. For female labor force participation in particular, there is a significant increase in coverage rates from 87 to 98 percent in the small area estimates. This suggests that uncertainty for the direct estimates is underestimated and uncertainty for the small area estimates may be slightly overestimated. Therefore, for reach of the four indicators, we multiply the MSE of the municipal direct estimates by a constant greater than one to replicate the coverage rate of the small area estimates. When coverage rates are equalized in this way, the estimated MSE falls by a factor of four to five for labor force participation.<sup>22</sup> <u>Table 4 - Measures of Uncertainty and Coverage for Municipal Estimates</u>

||(1)<br>
Figure 14: Contribution of Regulation-Based Entry Barriers and Idiosyncratic Distortions to TFP Gains <!-- Start of picture text --> TFP Gain Relative Full Reform TFP Gain Misallocation Only TFP Gain Entry Barrier Only<br>Kenya<br>SalvadorPortugal KenyaSalvadorPortugal<br>EthiopiaGhana<br>BulgariaIndiaRomaniaPeruColombiaMalaysiaChile Belgium EthiopiaGhanaBulgariaIndiaRomaniaPeruColombiaMalaysiaChile Belgium<br>Hungary Hungary<br>LatviaSpain F Italyranceinland LatviaSpain F Italyranceinland EthiopiaKenyaGhanaSalvadorBulgariaIndiaMalRomaniaPeruPortugalColombiaHungLatviaChileSpBelgium aF Itysi r inl a anceylyin a nd<br>5 6 7 8 9 11 5 6 7 8 9 11 5 6 7 8 9 11<br>log GDPpc log GDPpc log GDPpc<br>1.6 1.6 1.6<br>1.5 1.5 1.5<br>1.4 1.4 1.4<br>1.3 1.3 1.3<br>1.2 1.2 1.2<br>Relative to Initial SS Relative to Initial SS Relative to Initial SS<br>1.1 1.1 1.1<br>1.0 1.0 1.0<br>0.9 0.9 0.9<br><!-- End of picture text --> Note: The figure decomposes the total gains in TFP resulting from the withdrawal of both entry barriers and idiosyncratic distortions into those stemming from removing a single distortion while holding the other one fixed. Entry barriers are taken from the World Bank’s Doing Business Indicator (DBI). The left-most panel reproduces the overall gains. The middle panel computes the gains from removing idiosyncratic distortions, setting _γi_ = 0 while keeping the corresponding entry barriers _τi_<sup>_E_.Theright-most</sup> panel sets the entry barrier to zero, _τi_<sup>_E_</sup> = 0 , keeping the productivity elasticity of distortions _γi_ fixed.

firm size to discipline the inference of distortions. Exploiting the countervailing forces exerted by each type of distortion on the average firm size,
Table 4: Impact of PROBEMS on EMS Graduation by Levels of Household Assets

|Outcome variable|ENLACE (Y/N)<br>Household index (0, 1 & 2)<br>Household|index (3 & 4)|
|---|---|---|
||(1)<br>(2)<br>(3)|(4)|
|Treatment|0.006<br>0.005<br>0.015|0.010|
||(0.020)<br>(0.020)<br>(0.013)|(0.013)|
|Controls|Yes|Yes|
|N|2,201<br>2,176<br>5,120|5,044|
|Mean Dep. Control group|0.67<br>0.68<br>0.69|0.69|
|SD Dep. Control group|0.47<br>0.47<br>0.46|0.46|
|***|_p <_0_._01, ** _p <_0_._05, * _p <_0_._1||

The full set of controls include age, dummies for sex and area (urban-rural) and test scores on Enlace 9, one for spanish and other one for mathematics. ENLACE (Y/N) takes the value of 1 if the student took the 12th grade exam in 2012 and 0 otherwise. The houseld index takes a value from 0 to 4 depending if the student’s household has cement roof, cement floor, piped water and piped water toilet.

survey ENIGH, which measures incomes and expenditures, to identify, self-declared, scholarship holders and divide them between recipients of “Oportunidades” and “other government program”. Using ENIGH 2010<sup>12</sup> we identify households with students enrolled
overtime become major markets for Vietnam’s exports of manufactured goods such as textiles, garments, and footwear (see Figure 2). The degree of concentration of trading partners, as measured by the Herfindahl Index, declined from 0.18 in 1992 to 0.11 in 2002 (IMF, 2003).<sup>3</sup>

**Figure 1.  Vietnam’s Export Structure by Sector**

<!-- Start of picture text --> 1992<br>2002<br>Rice Rice<br>12% 4% Crude oil<br>Crude oil 20%<br>Others 31% Others<br>23%<br>14%<br>Manufactures<br>6% Manufactures<br>Other primary Other primary 32%<br>commodities commodities<br>37% 21%<br><!-- End of picture text --> <!-- Start of picture text --> Source: ITC<br><!-- End of picture text -->

**Figure 2.  Vietnam’s Export Structure by Country/Region**

<!-- Start of picture text --> 1992 2002<br>Singapore China EU U.S. China<br>12% 3% 7% 14% 7%<br>Singapore EU<br>6%<br>24%<br>Japan<br>25%<br>Others Others Japan<br>53% 35% 14%<br><!-- End of picture text --> Source: IMF Direction of Trade Statistics Because of the linkages between trade and the environment (through scale, composition and technique effects), this rather dramatic shift in Vietnam’s trade patterns could have important implications for the environment and use of natural resources. Though the precise environmental impacts of the various bilateral, regional, or multilateral trade 3 The Herfindahl Index is
and infant and neonatal deaths. This is consistent with the results of categorical exposure version which showed harmful effects for infants and neonates exposed to freshwater and severely saline water as well as the protecting effects of mild salinity exposure. Calcium and magnesium peak around 1 mS/cm EC, but their concentrations do not change afterward with increasing level of EC, which explains why there was lower neonatal or infant mortality among the mild-salinity water drinkers (Naser et al., 2019b). In contrast, the relationship between groundwater sodium and EC followed an almost linear upward trend, suggesting severe-saline water drinkers have very high sodium intake. The concentration of these macro-minerals in drinking water is determined by the chemical properties of rocks and sediments through which groundwater percolates and interacts (Hudson, 2018).

The number of infant and neonatal deaths based on the RCS model with fully adjusted covariates (model 3) was predicted with covariates at BDHS cluster means. The first derivative of outcome with respect to drinking water salinity indicated by EC level predicts the probability of infant or neonatal death induced by salinity at each cluster for BDHS 2011 and 2014. To estimate population totals based on BDHS data, the standard weights were de-normalized. The number of live births and predicted infant/neonatal deaths were calculated as summation of de-normalized cluster values at subdivision levels.

Table 6 lists the number of live births, infant, neonatal deaths and their predicted values induced by high salinity exposure in coastal subdivisions in BDHS 2011. During the three years prior to the BDHS 11
sources. The dataset has been developed from satellite-derived Aerosol Optical Depth reflectance values calibrated to ground-based PM2 _._ 5 observations using a Geographically Weighted Regression.

Remote sensing methods aim to observe particulate matter but are prone to capturing fine dust released from barren lands that have similar reflectance properties in the high frequency spectral wavelengths. This poses a difficulty in our analysis, countries in desert regions have high country wide average pollution levels, while large countries, or those with substantial forest cover where ambient pollution is low, have lower average concentration to what the larger population is exposed to on a regular basis. We used gridded population data that are produced using a combination of light at night data and census data, to identify patches of urban areas.<sup>10</sup> We averaged gridded pollution data that falls within urban boundaries to the country-level, defining urban areas as places where population density was higher than 300 people per square kilometer. The results in fig. 1 show that

> 10The population grids are from http://sedac.ciesin.columbia.edu/data/collection/gpw-v4, we use the 2000 grids.

13
**6.23%**|**5.22%**|**4.39%**|**3.20%**|**3.10%**|

Perhaps due to a relative lack in competition and to a slow equity market, the fees for issuing equity are much higher, as illustrated in Table 7. For the largest deals, the banking fees alone amount to 3% of face value, and go as high as 4.5% for small issues. When issuing equity, firms are required to hire an external auditor, and pay different types of regulatory fees. In addition, they must maintain an internal registry for 16
relatively small. Aggregated at industry or sector level, the distribution reveals the importance of mineral exports in value, even if they represent only 4% of transactions compared with 52% for textiles.

**Table 1 – Distribution of export value by destination region and by sector over the period (in**

||**millio**<br>|**ns USD)**|||
|---|---|---|---|---|
|Asia-Pacific|EU||R.O.W.|Thailand|
|$201|$267||$87|$1,230|
|11%|15%||5%|69%|
|Minerals|Textiles<br>A|gricultur|e<br>Wood|Misc.|
|$927|$579|$151|$85|$60|
|51%|32%|8%|5%|3%|

_Source: Own calculations based on Lao PDR customs data_ In addition to this skewed landscape faced by potential exporting firms, it appears that the economic performance of Lao exporters does not compare well to nonexporters. Moreover, they face a heavier regulatory burden, even after controlling for firm characteristics such as size, ownership and sector. About 20% of manufacturing firms in Laos export some part of their output, but data from a 2009 World Bank enterprise survey indicate that annual value added per worker is much lower for exporters. Similarly, larger firms, which are more likely to have the scale necessary to serve export markets, generate less value addition than smaller firms. This suggests that the domestic market, buoyed by large FDI inflows and investment in construction, offers greater returns than the more competitive export markets, where high production and trade costs undermine Lao competitiveness (World Bank 2011).

To put the characteristics of Lao exports into perspective, the World Bank’s Export Dynamics Database provides
# **Table** 7 **(continued)**

|Grupo Mava (B)|3'12/91<br>3,/15/91<br>9/20/91*<br>11/27/91*|Company relocation requested bv Citizens.<br>Governrent action: warning.<br>Citizens complaint.<br> (11/25/94): Citizens and ecologists complaint.|
|---|---|---|
|Tolteca|10/14/90|NGO's black list of air polluter.|
||2/13i92|Temporary and partial shutdown.|
|Met-Mex<br>Penoles (A)|3/22/91<br>6/4/91<br>819/91*<br>3/2/94<br>3/4/94<br>8/27/94|Citizens complaints.<br>Company pollution bad record pointed bv a Senator.<br>Government action: company temporarily shutdown.<br>Accident: citizens complaint.<br>Pollution control equipment investigation.<br>Relocation of 300 families living in the vicinity of the co.|
|Met-Mex<br>Penoles (B)|3/22/91<br>6/4/91*<br>3/4/94|Citizens complaints.<br>Company pollution bad record pointed by a Senator.<br>Pollution control equipment investigation.|
|Cementos de<br>Chiguagua<br>(GC3)|5/25/92|Government action: warning about environmental<br>performance.|
|Kimberly Clark|5/21/92 *|Government action: fine for water pollution.|
|Grupo Bimbo|3/19/92 *<br>2/14/93|Black list of air polluter.<br>
locally weighted regressions. These are local linear regressions that weigh the data using kernel methods. We follow Fan (1992) and Pagan and Ullah (1999). We estimate a different nonparametric regression using data for 1996 and 1998.<sup>7</sup> The inspection of figure 6.1 provides details of the evolution of cotton as a cash crop in rural Zambia.

Both in 1996 and 1998, the cotton income shares increase at the very bottom of the income distribution and then decline with income. The maximum share is roughly over 10 percent. At the upper tail, the average share is quite small, of around 2 percent. As regards cotton dynamics, the average share is higher in 1998 at the bottom of the distribution (mostly poor households) and at its upper tail. In the middle of the income distribution, the cotton income share is higher in 1996 than in 1998.

It is instructive to look at the evolution of cotton shares across the different cottonproducing provinces. Figures 2 to 4 plot the non-parametric averages for the Central, the Eastern, and the Southern provinces, respectively. In the Central province, for instance, cotton income shares in 1998 track the shares in 1996 at the bottom of the distribution, but become smaller at the middle. The Central province resembles the pattern at the national level, with higher average shares in 1998 at to bottom and at the top of the distribution, and lower shares at the middle. In contrast, cotton shares in the Southern province are higher across the entire income distribution in 1998 than in 1996.

The results in the previous figures indicate a regionally differentiated effect of the reforms on the pattern on income sources in rural Zambia. In particular, the increase in cotton shares in the Southern province is remarkable. Since this is the region that is perhaps closest to the capital, the result indicates that access to markets and infrastructure are key variables in adoption and in the deepening on cotton production.

> 7  Unfortunately, the 1991 Priority Survey