rafmacalaba/data-use-mentions-extended huggingface dataset:
ZIMBABWE‘S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE from 34 percent in 1999 to 37 percent in 2005, conceals a major contraction in the use of stand posts, from 10 to 5 percent over the same period. In fact, 0.8 percent of the population per year lost access to standposts and around 0.3 percent of the population each year has been gaining access to wells and boreholes, a lower-quality form of water supply (figure 8a).

**Figure 8. While access to improved water supply has kept pace with population growth, sanitation levels lag (annualized growth)**

<!-- Start of picture text --> Population gaining access per year, 1999–05<br>a. Water b. Sanitation<br>2<br>2<br>1.4<br>1.4<br>1<br>1<br>0.2<br>0.2<br>0<br>0<br>National Urban Rural<br>National Urban Rural<br>-0.5<br>-0.5<br>-1<br>-1<br>-2<br>-2<br>Piped Water Standposts Flush Toilets Improved Latrines<br>Wells/Boreholes Surface Water Traditional Latrines Open Defecation<br>Annualized Growth Annualized Growth<br>Population gaining access per year (%)<br>Population gaining access per year (%)<br><!-- End of picture text --> _Source:_ WHO 2010, from the 1999 and 2005 Demographic and Health Surveys.

Access to improved water is highly inequitable, with the poorest quintiles of the population not connected to piped water. Access to improved water in urban areas—where most of the better-off population lives—is 99 percent versus 67 percent in poorer rural areas (figure 9a), according to the 2005 Demographic and Health Survey (DHS). The main
# **Annex B: Dropout predictors**

Using the full universe of students who had entered the COMIPEMS in the academic year 20082009, and who were supposed to complete high school in Spring 2012, we regress the dummy for taking part in the 2012 ENLACE 12<sup>th</sup> grade - a proxy for on-time EMS completion – on the lower secondary GPA score and the score in the COMIPEMS admission exam, both measured in the school year 2008-2009.<sup>12</sup> While the intervention aims at tackling both academic and socioemotional issues that can lead to the decision of dropping out of high school or EMS, at the time of the pilot’s design, we had no information on proxies for the socioemotional skills of 9<sup>th</sup> grade students in Mexico. Once we condition on school fixed effects, GPA and the COMIPEMS admission exams could explain 19% of the total variation in the probability of completing, on-time, upper secondary.

With the OLS estimates of the coefficients on GPA and the COMIPEMS exam in hand, for all the first-year EMS students in each of the 20 schools in the evaluation sample, we construct a predicted probability of not finishing EMS.

|**Dropoutpre**|**dictors**<br>|
|---|---|
|COMIPEMS scores|-0.003***<br>(0.018)|
|Secondary average|-0.174***<br>(0.018)|
|Male|0.004<br>(0.002)|
|Observations|186,293|
|Mean Dep. Control|0.518|
|Group||
|SD Dep. Control Group|0.500|
|R-square|0.185|

> 12 For a discussion on the reliability of ENLACE 12th grade as a proxy for EMS completion see de Janvry, Dustan and Sadoulet (2017) and
This is the first study to use firm-level data to investigate how well water infrastructure can cope with extreme weather variability. It is also the first study of the effect of water infrastructure quality on firm performance that is truly global in nature. Thus far, the handful of studies on water infrastructure quality and firm performance have tended to focus on a specific region such as SubSaharan Africa (Moyo, 2011; Escribano et al., 2010, Davis et.al, 2001) or Eastern Europe and Central Asia (Iimi, 2011; Bogetic and Olusi, 2013). Furthermore, most of these studies are based on a small number of countries (Moyo, 2011) or construct their own data for a specific country (Davis et.al, 2001). Finally, all previous studies based on World Bank Enterprise Surveys use data from early rounds that were not nationally representative (Iimi, 2011; Moyo, 2011; Escribano et al., 2010; Bogetic and Olusi, 2013).

The findings of these studies have not led to a definitive conclusion on whether and how much water infrastructure reliability impacts firm performance. On the one hand, deficiencies in water supply are found to be the largest impediment to firm productivity in the Russian Federation using Enterprise Surveys conducted between 2003 and 2008 (Bogetic and Olusi, 2013). The Enterprise Surveys conducted in 2005 also found that water shortages add to firms’ costs in the Eastern Europe and Central Asia region (Iimi, 2011). Similarly, Moyo (2011) using Enterprise Survey data for five economies - South Africa, Zambia, Uganda, Mauritius and Tanzania, between 2002 and 2005, finds poor water infrastructure quality has a negative effect on firm productivity. More recently Islam (forthcoming) has illustrated the extreme impact that water shortages can have on informal firms, which are an important source of employment in the developing world. On the other hand, Davis et al. (2001) find a small effect of water infrastructure improvement on expenditures of small enterprises. Escribano
payments are triggered by recorded weather data rather than expensive claims-handling of crop damage in multiple small farms); (ii) no moral hazard (as payouts are independent of farmers‘ practices); (iii) no adverse selection or over-representation of high-risk insured in the pool (as there is a balance of information about the weather on part of insurer and insured). A pilot scheme during the 2005-06 season that bundled bank loans with the insurance (so that farmers could pay for both the premium and high-yield seeds) demonstrated that the scheme could operate without ongoing subsidies (after the mechanism was set in place and start-up expenses were covered by the government). The scheme decreased crop losses by offering incentives to change cultivation practices to become more resistant to drought. And it decreased vulnerability by increasing productivity in good seasons: with a doubling of their cash crop in good seasons, famers were able to save, both raising and smoothing their income over time.

The experience highlights the importance of absorptive capacity at the individual level. A survey revealed that only 55% of farmers reported understanding the scheme before joining it, highlighting the need to substantially improve communication and education. The survey also revealed a lack of trust among farmers in the weather station measurements, highlighting the importance of institutional trust as a challenge in scaling up operations. Source: Kunreuther and Michel-Kerman (2011) and Suarez and Linnerooth-Bayer (2010).

Finally, three issues are particularly relevant for developing countries. First, as global green technologies improve, the **falling costs of adoption** relative to existing non-green technologies facilitate their adoption by firms. They also lower the costs of adopting the relevant environmental regulation by governments. In their study of the adoption of regulations limiting emissions of nitrogen oxides (NOX) and sulfur dioxide (SO2) at coal-fired plants across 39 developed and developing countries, Lovely and Popp (2011) show that countries adopting these regulations at later dates do so at lower levels of per capita income than adopters who enacted similar regulations earlier.
database only, as the main results are valid when considering trading times across countries from the regional database.

A difficulty in this exercise is that the sensitivity of trade flows to shipment time strongly depends on the characteristics of the product considered. In other words, the “value of time” is not equal across industries. Among many sector‐specific characteristics governing the impact of time on trade, one can cite the rate of depreciation, storability, seasonality, demand uncertainty or substitutability with domestic products. All those traits influence the elasticity of shipment time to trade flows and it is important to take into account this heterogeneity across sectors.

In the rest of the section, we first discuss the methodology used to transform shipment times into trade costs, then we present the results for the global and regional databases.

# **a. From shipment times to trade costs**

To transform the shipment times from our network analysis into trade costs, we use the seminal work of Hummels and Schaur (2013). This paper provides estimates for the ad‐valorem value of a shipment day for many sectors, at both four‐digit and two‐digit levels of disaggregation in the Harmonized System (HS). Recognizing the fact that air cargo is many times more expensive than maritime transport but arrives in destination markets much faster, Hummels and Schaur (2013) use U.S. imports data and detailed information on the premium paid for air shipping and in time lags for ocean transit to identify consumers’ valuation of time. To our knowledge, these results constitute the most comprehensive and detailed estimates of value of time at the sectoral level, providing rich heterogeneity and overcoming several endogeneity issues faced by previous work.

An obvious limitation of these estimates is that they are based on information from the United States, which might create at least two types of potential biases when using the values for a worldwide analysis. First, there may be a selection issue since the United States does not have positive imports in every sector, which
CAMEROON’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE Cameroon’s air market is more competitive than that of other countries in the region. The HerfindahlHirschmann Index (HHI), a commonly accepted measure of market concentration,<sup>7</sup> shows that Cameroon has the lowest concentration of services among its neighbors, with the measurement taken before the collapse of Cameroon Airlines. The collapse of Cameroon Airlines was followed by a significant increase in capacity by Royal Air Maroc and Ethiopian airlines, indicative of a more liberalized environment.

Cameroon is one of the few African countries that has managed to attract private sector participation in its air transport infrastructure. Between 1993 and 2008, 7 of Cameroon’s 14 airports were included in a 15-year joint-management contract involving shared risk between the public and private sector. The contract was co-managed by Aéroports de Paris (34 percent) and the government of Cameroon (24 percent), and other carriers (42 percent).

## **Challenges**

In spite of the general traffic turnaround, the domestic market has yet to recover. The domestic market was the most impacted by the collapse of the air market: the number of domestic seats dropped from 640,620 in 2001 to 105,742 in 2007, a decline of 80 percent. In 2008 Cameroon's domestic capacity nearly collapsed with the demise of Cameroon Airlines. In 2009 the number of domestic seats further declined by 66 percent from 2007 levels, dropping to 36,480 seats (figure 11a). Similarly, the number of domestic city pairs dropped from 17 in 2001 to 10 in 2007 and 1 in 2009 (figure 11b).

Safety oversight needs strengthening. In September 2005 Cameroon Airlines was blocked from entering France until significant improvements in operations could be demonstrated. The ban was eventually lifted. But the 2005 safety audit of the International Civil Aviation Organization showed significant room for improvement. As part of a regional West and Central African project, Cameroon is now working on improving its safety oversight.

# Water resources
either survey. From the household survey, trust in the local council did fall, as did the share of respondents reporting that most neighborhoods are accessible by road and that had satisfactory responses from officials regarding complaints. Among government officials, no results suggest worsening response about state capacity, and several indicators related to planning systems, taxation, capacity building and culture of performance registered improvements.

Turning to the right-hand panel, the observation is that for almost all indicators, changes in project areas were not different from those observed in comparison areas (i.e., estimates of the β coefficient are often very small in magnitude and statistically indistinguishable from zero). Among households’ responses about state capacity, for example, no indicators related to urban planning, fiduciary systems, accountability or taxation changed differentially in project areas between the first and second survey rounds. The only indicator that recorded a differential change in the treated areas was the share of neighborhoods accessible by road, which decreased in in comparison areas while increasing in project LGAs.

Among government officials, the same pattern repeats: for the vast majority of indicators we observe no differential trend in project vs. comparison LGAs. For the few indicators that did change differentially, we observe better performance of comparison LGAs: for several indicators related to taxation, like seeing opportunity to increase tax revenue and respondents paying taxes on their own property, performance improved more in comparison than project areas.

We also present results for the aggregate indices created, in Table 9 and Table 10. In both tables, panel A presents results for a simple difference-in-differences specification, without including any comparisons, while Panel B includes individual-level comparisons. For both panels, Table 9 shows that, except for the Accountability and Oversight index, respondents in comparison LGAs were more positive in the second survey than in the first one - as documented by the positive coefficients of the indicator variable for the 2018 survey round. The improvement in project LGAs, however, was no different than that observed in comparison LGAs: the coefficients on
Table 5 explores this correlation in more detail. It uses the detailed 10-digit import data and examines whether growing imports from China in a product or industry are associated with expanded exports to the United States, controlling for the significant variables from Table 4. For all goods (Table 5A), exports to the US are not significantly correlated with growing imports from China. For strategic industries (Table 5B), there is evidence that increased imports from China are correlated with increased exports to the United States. When we control for intra-industry trade, growth in 2-digit and 6-digit imports matter for strategic industries. The former is consistent with value chain trade, while the latter could reflect transshipment or limited additional value added before goods being shipped to the United States. The coefficient of 0.04 on 6-digit imports implies that a 10 percentage points increase in imports from China is associated with 0.4 percentage points higher exports to the United States. The effect of growth in imports from China at the 2-digit level is about twice as important, as reflected by the higher coefficient (albeit lower significance). In terms of economic importance, using standardized coefficients, intraindustry trade is roughly six times more important than what could be transshipment (as measured by growth in 6-digit imports). For other goods (Table 5C), growth in imports from China is not important.

# **_5. Conclusion_**

This paper uses detailed trade data from 2017 to 2022 to study how US trade policy is impacting global supply chains. Despite the tariffs imposed by the US administration in 2018-19, the aggregate data show that overall US openness to the world, as measured by its aggregate imports, has not declined. Even so, we find that US tariffs on imports from China have induced significant direct decoupling, with China’s share of US imports falling by more than 5 percentage points relative to its level in 2017.

This decoupling has not led to a major diversification across import sources. Rather specific countries have benefitted—especially large developing countries
28 but, interestingly, this appears to be driven by the strength of the correlation in the hyperinflationary sub-period.<sup>37</sup> The correlation is both weaker and less significant during 1993-2004.

Table 7 also presents the correlation coefficients between inequality and poverty on the one hand, and an index of real wages in manufacturing in the state of São Paulo on the other. This index is powerfully negatively correlated with the FGT(2) poverty measure in the first period, and with inequality in the second. Like inflation, it is significantly correlated with both poverty and inequality in the entire period. It suggests that the impact of economic growth on poverty is channelled through wage growth in the labor market.<sup>38</sup>

# **Table 7: Simple and Partial Correlation Coefficients between Distributional and Macroeconomic Variables**

||**Theil**|**Index**<br>1981-|**FG**<br>1993|**T(2)**|
|---|---|---|---|---|
||ρ|p-value|ρ|p-value|
|Log inflation|**_0.747_**|**_0.008_**|**_0.623_**|**_0.041_**|
|Real Wage|-0.485|_0.131_|**_-0.919_**|**_0.000_**|
|||1993-|2004||
|Log inflation|0.570|0.085|**_0.903_**|**_0.000_**|
|Real Wage|**-0.783**|**_0.008_**|-0.584|0.077|
||1981-200|4, Simple Co|rrelation Co|efficients|
|Log inflation|**
way democracy works in El Salvador?” Again the main results do not depend on dichotomization decisions.

Table 1 shows some basic summary statistics for the aforementioned dependent variables as well as for some set of individual-level characteristics. Panel A focuses on LAPOP data while Panel B on Latinobar ́ometro data. My samples of analysis come from pooling different waves available for the time period 2004-2018. Note that the total number of observations for each variable vary because some of the questions were not asked every wave and, in some cases, when asked some respondents choose to not answer. Roughly half of the respondents are men (48%) and the average age is 39 in both samples. In the LAPOP sample, 38% are individuals living in rural areas while 18% of the individuals in the Latinobar ́ometro sample lives in small urban areas. Average years of schooling is above 8 years while, depending on the sample, between 7% and 9% of the individuals are unemployed (i.e,individuals who are not working and look for a job).

The LAPOP sample reveals substantial heterogeneity in the level of trust depending on which institutions one looks at. According to the respondents, the Catholic Church is the most trusted institution (60% of Salvadoran strongly trust in the Church) followed by mass media and municipal government (both with 56%). On the other hand, the national legislature (with 39%) and the president (with 45%) are the less trusted over the time period of analysis. Finally, only 38% of Salvadorans think that the judicial system would punish the guilty if they were a victim of a robbery or assault.

The Latinobar ́ometro sample shows that 52% of respondents thinks that income distribution in El Salvador is “unfair” or “very unfair”. Few Salvadorans are optimistic about current economic conditions (only 16% answered that the economic conditions of the country were better than a year before). A large share of respondents (i.e
characterizes exporter dynamics and the other conducts a series of export growth decompositions. Section 5 concludes.

# **2. Data and Summary Statistics**

We use data covering the universe of export transactions by all Turkish-based firms between 2002 and 2011 collected by the Turkish Customs Authority and transferred to the national statistical institute _Turkstat_ for revision and cleaning before being used for policy or research purposes.<sup>6</sup> The variables included in the dataset are the identification code of the exporting firm, the year of the transaction, the exported product code at the HS 12-digit level, the destination market, the value of the transaction (in USD), and the quantity of the transaction (in kilograms).<sup>7</sup> Given that the exporting firm identification codes can be followed over time, our dataset is a panel of firms at the firm-product-destination-year disaggregation level.<sup>8</sup> The export transactions cover agricultural, mining, and manufacturing products but we will exclude from our analysis exports in HS Chapter 27 (hydrocarbons such as oil, petroleum, natural gas, coal).

The cleaning procedures that we applied to the dataset are as follows. First, although the data is collected at the HS 12-digit level and we will conduct some analysis at this level, we also aggregate it up to the HS 6-digit level which is a classification that is comparable to those used in other countries and will thus facilitate benchmarking of the stylized facts for Turkey. To our knowledge, our study uses the most disaggregated HS classification for products among recent empirical studies relying on exporter-level customs data.<sup>9</sup> Second, Turkey uses the special trade regime which means that customs record the sales from inland to their own free zones/customs warehouses as exports.<sup>10</sup> We drop from our dataset the observations for sales to free zones since

> 6 Note that the data is available to researchers but can be accessed only in _Turkstat_
as the share of female participants in the treatment and control group, asset ownership, as well as the distance to the reforestation site. Differences are relatively small in absolute terms, but in our regression analysis we try to mitigate any possible selection effects by including them as control variables. In addition, an F-test of the joint significance across baseline covariates fails to reject the null hypothesis of no significant difference between treatment and control groups. This gives us confidence that any observed difference is likely the result of chance and therefore should not affect our treatment estimation.

An endline survey was administered in November/December 2018, 5 to 6 months after the monetary transfers were disbursed to the PES participants, based on the tree survival rate on the respective reforestation plot. This follow-up survey was similarly structured as the baseline survey with the exception of a more exhaustive food security module. During this phase, we were able to track down 574 out of the 630 households interviewed at baseline, which corresponds to an attrition rate of 9%, which is fairly balanced across treatment and control households.<sup>7</sup> Potential biases are thus likely to be small. Nevertheless, we test for balance in between treatment and control groups on baseline characteristics using the endline sample (see Table 2), and confirm that most characteristics remain balanced between treatment and control.

> 7The difference in attrition rates between treatment and control groups was just 4.4 percentage points (p=0.053); See Table 2.

14
075,452|1,075,452|1,075,452|1,070,496|
|Year FE|YES|YES|YES|YES|YES|
|Flexible distance controls|NO|NO|NO|YES|YES|
|U.S. trade policy controls|NO|NO|NO|NO|YES|
|Pseudo R2|0.494|0.512|0.518|0.521|0.524|

Note: Robust standard errors in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1. Estimates over the sample of HS6 products with values of the upstreamness index _≤_ 1 _._ 3. The LHS variable in all models is _M_<sup>_k_in year</sup><sup>_t_.All models are</sup> _j,t_<sup>, the value of product</sup><sup>_k_imports to PR from origin</sup><sup>_j_</sup> estimated using the PPML estimator on PR’s import data pooled across years, HS6 digit products and places of origin, with year fixed effects included in the estimation. IHST denotes the Inverse Hyperbolic Sine Transformation. Pharmaceutical products are excluded from the estimation.

25