rafmacalaba/datause-encoder-data huggingface dataset:
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# ANNEX 5. Review of Pricing and Cost Recoverv in SARs:

# HIGHWAYS SECTOR

# **A.** THE POLICY

# A.1 Interoretation of Efficiency Pricing

1. Efficiency pricing of road services requirex that user charges are set **at a** level that would reflect **the** opportunity costs of providing the service.<sup>1</sup> These costs consist of the variable maintenance costs and congestion costs (those that arise when an additional vehicle increases the costs of travel for all other vehicles). A congestion levy is appropriate to apply only on those roads (and, strictly speaking, during those hours) when congestion exists; it would be inefficient to charge a price higher than the variable maintenance costs in the absence of congestion as this would result in roads being underutilized.

# A.2 Constrainta to Implementing Efficiency Prices

2. Maintenance costs vary according to types of road (e.g., paved versus earth or gravel roads) and vehicle weights; thus ideally road user charges should adequately reflect the differences in maintenance costs due to these factors. "Ideal" prices are, however, difficult and costly to administer as they would require information on the damage caused by different types of vehicles to paved and unpaved roads. In addition, studies have shown that the use of tolls or other means to directly relate road use to charges is rarely cost-effective. Thus, in practice indirect assessments such as fuel taxes are often used even though these do not clearly reflect different costs imposed by users. This issue is often handled through differing tax rates on diesel and gasoline. Charging for traffic congestion is generally done via differential annual license duties, purchase taxes and/or import duties on vehicles. These levies are differentiated according to categories of vehicles which are used almost exclusively in the urban areas; for example, higher license fees are charged to vehicle owners living in the cities than to those in rural areas. In a study conducted by Churchill in Central America, it was concluded that the fuel tax would be the appropriate means of approximating the variable maintenance costs in rural areas and license duties would be the primary means of reflecting the congestion costs in urban areas.

# A.3 Adjustments to Efficiency Prices

3. Efficiency pricing as defined above can gnsure an optimum consumption of road services by users, but may fall short of attaining fiscal objectives. Most governments in LDCs have inadequate fiscal resources for development; consequently, it is often desirable to set prices above efficiency levels. Achieving a balanced road budget is a modest 1/ This section draws largely from Road User Char a in Central America by A. Churchill, and The Economics of ad Usr Qarg2s by A Walters
the precise ranking is difficult to obtain given rounding.

To the extent that these two states represent India, the combination of a wide achievement distribution and immense population explains why perceptions of India can vary so dramatically. In Table 4, we use population age-cohort estimates and enrollment rates to estimate the _number_ of 14-year olds in each country who pass the international benchmarks set by TIMSS. The results are striking. If one percent of Indian children reach the advanced international benchmark— the average suggested by Rajasthan and Orissa—the total cohort size ranks 5th out of all the countries tested. Only Japan, the United States, South Korea, and Taiwan have more students passing the top benchmark. For every ten children who pass the advanced benchmark in the United states, there are four children who pass the benchmark in India. Indeed, the 101 thousand Indian children who pass the advanced benchmark exceeds the total number of children who pass in bottom 32 countries combined. If India were added to the TIMSS sample, one out of every fourteen children who pass the advanced benchmark would be Indian.

The view from the top—that Indian’s form a substantial fraction of top performers worldwide— contrasts sharply with the view from the bottom. The sheer magnitude of India’s youth population and poor average performance means that over 17 million Indian 14-year olds are either not enrolled or fail the low international benchmark. This number is 22 times the number in the United States, 217 times the number in South Korea, and 726 times the number Japan. Indeed, there are more Indian’s either not enrolled or who fail the low benchmark than in all the other TIMSS countries combined.

# **4.3 Variance Decomposition**

The striking disparity between top- and bottom-achievers hints that children receive different educational inputs, both based on the state in which they live and the characteristics of their families and schools. While it is impossible to draw definitive causal conclusions using simple correlations or variance decompositions, the patterns that emerge from even a basic analysis are broadly consistent with a view of an education system rife with inequality but rich in potential. In a hopeful sign, the form inequality takes suggests that public policy plays a role. The impact of household attributes—educational inputs that the government has little power to control— appears mitigated by the institutional structure of states and schools.

16
Table 1: Sample Characteristics by Respondent Gender

||(1)|(2)|t-test|
|---|---|---|---|
||Male|Female|Difference|
|Variable|Mea|n/SE|(1)-(2)|
|Marital Status: Having a long-term partner or a spouse|0.59|0.57|0.02***|
||[0.00]|[0.00]||
|Relationship with head of household||||
|Head of Household|0.44|0.25|0.19***|
||[0.00]|[0.00]||
|Spouse or partner|0.16|0.37|-0.22***|
||[0.00]|[0.00]||
|Child or Grandchild|0.26|0.24|0.02***|
||[0.00]|[0.00]||
|Other|0.15|0.13|0.01***|
||[0.00]|[0.00]||
|Number of people under same roof (excluding respondent)||||
|0, I live alone|0.09|0.07|0.02***|
||[0.00]|[0.00]||
|1 person|0.14|0.17|-0.03***|
||[0.00]|[0.00]||
|2-5 people|0.61|0.62|-0.01***|
||[0.00]|[0.00]||
|6-10 people|0.13|0.12|0.01***|
||[0.00]|[0.00]||
|11 or more|0.03|0.02|0.01***|
||[0.00]|[0.00]||
|Education||||
|Secondary or less|0.42|0.39|0.02***|
||[0.00]|[0.00]||
|More than secondary|0.58|0.61|-0.02***|
||[0.00]|[0.00]||
|Age||||
|24 or younger|0.26|0.28|-0.01***|
||[0.00]|[0.00]||
|25-64 years old|0.74|0.72|0.01***|
||[0.00]|[0.00]||
|Urbanicity||||
|City|0.60|0.61|-0.01***|
||[0.00]|[0.00]||
|Village, rural area, or other|0.40|0.39|0.01***|
||[0.00]|[0.00]||
|Own land|0.23|0.16|0.07***|
||[0.00]|[0.00]||
|Observations<br>***, **, and * indicate significance at the 1, 5, and 10 percent criti<br>The value displayed for t-tests are the differences in the means acr|73535<br>cal level.<br>oss the gro|79020<br>ups.||

27
Even though some observers have argued that administrative land reallocation may promote equity and potentially improve land‐labor matching in the absence of land market, any potential benefits associated with land reallocations may come with an additional efficiency loss. Our results suggest that strengthening property rights over agricultural land may be essential for removing biases in the movement of labor out of agriculture during the process of structural change and urbanization. As migration for work generally contributed to higher earnings and consumption of China’s rural residents (de Brauw and Giles, 2008), one direction for future work on the effects of insecure property rights would be to examine the effects of insecure property rights on measures of income and well‐being. As rural areas continue to depopulate with increases in the movement of labor to urban areas, one would expect that rural institutions, including those governing land, to change in response to migration‐ induced social and demographic changes. More research is needed to examine potential relationships between migration and the evolution of property rights. Even as the Rural Land Contracting Law provided stronger claims to contracted land after 2003, land tenure insecurity is manifest in increased seizure of land without proper compensation, as opposed to reallocations of an earlier era. Reducing labor migration may not be an effective strategy for rural residents to prevent land seizures and they may have to undergo costly adjustment to labor allocation to cope with land loss. More research is needed to examine how rural residents cope with this new source of insecurity and the institutional arrangements that may reduce the incidences of such land‐taking.

# **6 References**

Acemoglu, Daron, Johnson, Simon, and Robinson, James. 2001. “The Colonial Origins of Comparative Development: An Empirical Investigation.” _American Economic Review_ 91(5): 1369‐1401.

_Land Tenure Insecurity and Migration, Page 30_
ticle XXIV, General Agreement on Trade in Services (GATS) Article V, or the Enabling Clause. Paragraphs 4 to 10 of GATT Article XXIV contain provisions covering the formation of customs unions and free trade areas in merchandise trade, while GATS Article V covers agreements in services, and the Enabling Clause (The 1979 Decision on Differential and More Favorable Treatment, Reciprocity and Fuller Participation of Developing Countries) deals with trade in goods between developing countries. The provisions of each of the above disciplines generally require that countries entering a PTA do not raise trade barriers with the rest of the world, but are extremely vague on the specifics. For example, despite specifying that preferential liberalization should eliminate barriers on “substantially all trade,” neither Article XXIV itself nor any subsequent legal document quantifies this requirement. Similarly, member countries are required to notify the Secretariat of any PTAs they enter, and agreement provisions can be reviewed by the WTO. However, any such examination is voluntary, and the outcome of the report (of which few have been completed) has no bearing on the WTO attitude towards or legality of the agreement. Therefore, there appears to be no enforcement mechanism that guarantees accurate reporting of PTAs by WTO members and the administrative framework to ensure PTA compliance with WTO principles is non-existent.<sup>20</sup> In order to create a single dataset for both the WTO notified and unnotified agreements, we undertook an extensive data-gathering exercise to supplement the official WTO database, relying on unpublished WTO data as well as other available information.<sup>21</sup> The main source has been unofficial communication from the WTO, who compiled a large database of agreements not formally notified to them (both PTAs that have been concluded and those in various stages of negotiations) by collecting information from various newspaper articles. These data were supplemented by information from the websites of the Office of the US Trade Representative and the EU Trade Commission. Still more PTAs were added through various print and web media searches. The scope of data collected is similar to the format used by the WTO’s PTA database: for each agreement, we specify the name, country members, date of signing, and date of entry into force, classify

> 20The lack of a PTA enforcement mechanism suggests that the WTO does not view the pursuit of PTAs as a threat to the multilateral outcome. There is a large literature that supports the “building block” view of PTAs, including Schott (2004), Lawrence (1991), and Winham (1986) (cited in World Bank, 2004). On the other hand, studies such as Saggi (2004), Saggi and Yildiz (2004), and Lim ̃ao (2003) caution that the pursuit of PTAs may reduce the motivation to lower multilateral tariffs and slow the progress towards global free trade.

> 21The results of this exercise were presented briefly in World Bank (2004).

12
0

# TABLE 3: KOREA: FINANCIAL ASSETS AND LIABILITIES BY SECTOR end-1984

|Trillions<br>of won|Total|Househ|old|Busin|ess|Govern|ment|Financi|al|Rest of|World|
|---|---|---|---|---|---|---|---|---|---|---|---|
|||Assets|Liabs|Assets|Liabs|Assets|Liabs|Assets|Liabs|Assets|<br>Liabs|
|Gold|0.0|||||||0.0|||0.0|
|Currency and transferable<br>deposits|<br>10.2|3.2||2.8||1.5||2.6|10.2|||
|Other deposits|32.9|20.8||8.1||1.4||2.5|32.9|||
|Life<br>insurance and pension furds|7.3|7.3|||||||,.3|||
|Short-term securities|8.7|1.8||1.8|4.2|0.0||5.0|4.5|||
|Long-term securities|16.9|4.9||1.3|7.9|0.4|0.3|10.3|8.7|||
|<br>Stocks|12.5|7.3||2.8|10.3|0.4||2.0|2.1|||
|Loans by financial<br>institutions|70.6||18.0||39.4||3.6|70.6|9.5|||
|Govermuent loans|6.3||0.5||3.3|6.3|||2.5|||
|Equities<br>other than stocks|10.6|3.4||1.8|8.7|4.7||0.7|1.9|||
|Trade credit|18.2||3.4|18.2|14.8|||||||
|Foreign exchange holdings|6.3|||||||6.3|||6.3|
|<br>Foreign claims and debts|41.8|||2.4|11.4||7.2|1.3|19.5|38.1|3.7|
|Miscellaneous|22.4|3.7||11.3|14.4|1.6|1.2|5.9|6.9|||
|Net financial<br>position||30.6||-63.8||3.9||1.3||28.0||
|Total|264.5|52.5|21.9|50.7|114.4|16.2|12.3|107.1|105.8|38.1|10.0|
|Percentage of GNP CGNP= 69.4):||||||||||||
|Gold|0.0|||||||0.0|||0.0|
|Currency and transferable<br>deposits|14.6|4.7||4.1||2.1||3.8|14.6|||
|<br> <br>Other deposits|47.4|30.0||11.7||2.0||3.6|47.4|||
|Life<br>insurance and pensionfunds|10.5|10.5|||||||10.5|||
|<br>Short-term<br>securities|12.5|2.6||2.7|6.1|0.0||7.2|6.4|||
|Long-term securities|24.4|7.1||1.9|11.4|0.6|0.5|14.8|12.6|||
|Stocks|18.0|10.5||4.1|14.9|0.5||2.9|3.1|||
|Loans by financial<br>institutions|101.8||26.0||56.8||5.2|101.8|13.7|||
|<br>Govern ent loans|9.0||0.7||4.8|9.0|||3.6|||
|Equities<br>other than stocks|15.3|5.0||2.6|12.5|6.8||0.9|2.8|||
|<br>Trade credit|26.2||4.9|26.2|21.3|||||||
|Foreign exchange holdings|9.1|||||||9.1|||9.1|
|<br>Foreign claims and debts|60.2|||3.5|16.5||10.3|1.8|28.1|54.9|<br>5.3|
|<br>Niscellaneous|32.4|5.3||16.3|20.8|2.3|1.7|8.5|9.9|||
|Net financial<br>posn||44.1||-91.9||5.6||1.8||40.4||
|<br>Total|381.4|75.7|31.6|73.1|165.0|23.3|17.7|154.4|152.6|54.9|14.4|

Source: Bank of Korea, Financial Statements nalysis, 1985
<!-- Start of picture text --> US Imports of apparel<br>from African LDCs t% yf ie<br>aw<br><!-- End of picture text --> <!-- Start of picture text --> EU Imports of apparel from ><br>African LDC: —————3<br>te<br>2<br>—<br>cure eee ee = em - a mt ka<br>e-- a Sar wd eae<br><!-- End of picture text -->
authors such as Beaudry et al. (2006) Bloom et al. (2015) and Bloom et al. (2012b). As these authors argue, these kinds of measures have the advantage of being recorded consistently in all firms and they do not depend on price indexes. Furthermore, as Bloom et al. (2012b) argue, they are highly correlated with other measures such as IT capital stock per worker. In this sense, we analyze computers-per-worker, the share of labor with Internet, and the share of labor with computer which should behave similarly to computers-per-worker and allows us to test the robustness of our main measure.

As our performance indicator considering the information available in ENTIC, we use sales-perworker, which, although it is an imperfect measure of productivity, has been widely used in previous studies.<sup>3</sup> For example Haltiwanger et al. (1999) and more recently Bloom et al. (2012a) use this indicator as their productivity measure. Table 1 shows descriptive statistics for firms in our sample in terms of performance, ICT use and other characteristics.

Finally, in order to analyze whether firms face competition, following Iacovone et al. (2013) we use the natural shock generated by the increasing competition from China in the Mexican market. In this sense, we measure competition as the change in the share of China in total Mexican imports for each HS1996 subheading between 2000 and 2008.<sup>4</sup> Table 1: Descriptive Statistics

|||20|08|||201|2||
|---|---|---|---|---|---|---|---|---|
|Variable|Mean|sd|p10|p90|Mean|sd|p10|p90|
|Computers-per-worker|0.24|0.22|0.06|0.50|0.28|0.23|0.07|0.57|
|Share of labor with Internet|0.20|0.19|0.03|0.40|0.20|0.19|0.03|0.40|
|Share of labor with computer|0.21|0.19|0.05|0.43|0.24|0.22|0.06|0.50|
|Sales-per-worker (thousand pesos)|997.36|1,638.24|123.01|2,192.49|1,005.39|1,407.87|131.20|2,494.11|
|Share of white-collar workers|0.22|0.17|0.05|0.42|0.25|0.23|0.06|0.59|
|Investment fxed assets/worker|46.10|111.03|0.00|130.11|41.34|91.19|0.05|113.05|
|(thousand pesos)|||||||||

*The sample includes 715 firms.

_Source:_ Authors’ calculations with data from ENTIC 2009 and 2013, INEGI

> 3We are unable to construct TFP measures because the survey does not include information on physical non-ICT related capital stocks

> 4Considering that according to data from Mexico’s Ministry of Economy, the U.S. market accounts for 80% of Mexican exports, we also analyzed the share of China in U.S. imports. Results are similar. This analysis is shown in Iacovone et al. (2015).

4
# **Figures**

**Figure 1: Predicted HIV prevalence using SAE methodology vs. observed prevalence in the 2004 DHS, national and regional (women age 15-49)**

<!-- Start of picture text --> 25<br>Predicted prevalence using SAE methodology, 2000 DHS<br>Observed prevalence, 2004 DHS 19.8<br>20<br>18.0<br>15<br>13.2 13.3<br>10.4<br>9.8<br>10<br>8.2<br>6.6<br>5<br>0<br>Malaw i North Central South<br>HIV prevalence (women age 15-49), %<br><!-- End of picture text --> 29
**Table S1.S: Results for specifications with dummy variables for web, email and perceived consequences of disputes**

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|VARIABLES|Web|email|reput_D1|reputD_2|reputD_3|reputD_4|reputD_5|pcf_repD|
|Supbuy|0.0201|0.422|-0.461**|-0.220|0.307|0.282|0.357|0.403|
||(0.330)|(0.362)|(0.186)|(0.331)|(0.261)|(0.343)|(0.365)|(0.654)|
|samesup|-0.116*|-0.133**|-0.0748|-0.0456|-0.0410|-0.0600|-0.0665|-0.100|
||(0.0618)|(0.0639)|(0.0882)|(0.0822)|(0.0811)|(0.0743)|(0.0839)|(0.140)|
|samecus|0.135***|0.119***|0.0352|0.00193|-0.0673|-0.0878|0.0786**|0.0995|
||(0.0374)|(0.0300)|(0.0360)|(0.0450)|(0.0696)|(0.0651)|(0.0379)|(0.101)|
|same_sec|-0.0232|-0.0628***|-0.0122|-0.0151|0.00143|-0.00288|0.0198**|0.0151|
||(0.0151)|(0.0192)|(0.0139)|(0.0154)|(0.0118)|(0.0113)|(0.00982)|(0.0231)|
|Ldist|-0.00970***|-0.0153***|-0.00603***|-0.00417**|-0.000201|-0.00280|-0.00233|0.00565|
||(0.00332)|(0.00236)|(0.00171)|(0.00191)|(0.00302)|(0.00220)|(0.00387)|(0.00673)|
|ad_fmage|<br>-0.00224***|<br>-0.000539|<br>-0.000665|<br>0.000387|<br>0.000438|<br>-0.000245|<br>0.00110|<br>-0.000492|
||(0.000511)|(0.000915)|(0.000547)|(0.000692)|(0.000803)|(0.000622)|(0.00115)|(0.00121)|
|ad_meduc|-0.00629|0.0166|-0.00185|0.00253|0.00206|0.000247|0.00507|-0.00423|
||(0.00611)|(0.0108)|(0.00285)|(0.00439)|(0.00528)|(0.00489)|(0.00615)|(0.00882)|
|ad_mexper|0.000328|-0.00140**|0.000439|0.000105|-0.000964|-0.000796|-0.000885|-0.000556|
||(0.00129)|(0.000569)|(0.000601)|(0.000560)|(0.000597)|(0.000688)|(0.00107)|(0.00186)|
|ad_mfemale|0.239***|0.130***|0.0277|0.00221|-0.00538|0.0114|0.0190|0.0656|
||(0.0527)|(0.0431)|(0.0244)|(0.0204)|(0.0228)|(0.0258)|(0.0293)|(0.0552)|
|ad_lemp|0.0819***|0.0809***|0.0121|-0.00904|-0.00439|-0.0177***|-0.0186**|-0.0166|
||(0.0218)|(0.0227)|(0.0101)|(0.00658)|(0.00852)|(0.00583)|(0.00930)|(0.0154)|
|Constant|<br>0.213***|<br>0.321***|<br>0.468***|<br>0.484***|<br>0.450***|<br>0.492***|<br>0.396***|<br>1.105***|
||(0.0363)|(0.0353)|(0.0214)|(0.0201)|(0.0258)|(0.0201)|(0.0383)|(0.0531)|

Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 28
typically thin in rural SSA. We take these observations seriously and test the extent to which stronger feedback mechanisms can be leveraged to combat dropouts in the context of a feebased extension service in Rwanda.

# 2.2 Country context

Increasing agricultural productivity is central to the Government of Rwanda’s Economic Development and Poverty Reduction Strategy. The agricultural sector is the sector with the greatest potential to reduce poverty in Rwanda. Approximately 85% of the population lives in rural areas and rural poverty is persistent. The rural poverty rate is 48.7%, compared to 22.1% in urban areas.<sup>4</sup> Rwanda is one of the most densely populated countries in Africa, and land is scarce. In our sample, male clients live in households that farm 0.46 ha on average, female clients 0.36ha. Despite large efforts to convert non-cultivated areas into arable land, the scope to increase cultivated area is limited.

In a context where land is scarce, increasing agricultural productivity is essential for sustainable poverty reduction and economic growth. The public agricultural extension system in Rwanda has limited outreach, providing information to less than one-third of rural households (MINECOFIN, 2013). Poor quality of service delivery and informational content are also important constraints. Instead of increasing its investment in public extension services, the government chose to transition from service provider to “facilitator of the private sector”, as capacity grows and private sector investment increases.<sup>5</sup> (Ministry of Agriculture and Animal Resources – MINAGRI, 2013).

> 4 These figures were published by the Ministry of Finance & Economic Planning (MINECOFIN) in 2013. 5 Strategic Plan for the Transformation of Agriculture in Rwanda Phase III

6
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