rafmacalaba/datause-encoder-data huggingface dataset:
**<u>Table 6: Incidence of informal land transactions in rural areas</u>**

||**Total**|**Southern**|**Western**|**Northern**|**Eastern**|
|---|---|---|---|---|---|
|Share of newly acquired land since last visit (i.e., 2012)<sup>a</sup>|0.12|0.11|0.11|0.12|0.14|
|**All types of transactions**<sup>**b**</sup>||||||
|Registered during LTR|0.512|0.577|0.369|0.597|0.469|
|Subsequent registration|0.020|0.006|0.035|0.039|0.000|
|Not officially registered|0.468|0.417|0.596|0.365|0.531|
|Of which: register only at the village|0.423|0.659|0.145|0.363|0.547|
|<br>RwF willing to pay for reg.|4442|2937|3794|4208|7188|
|<br>Number of parcels|1,147|324|255|310|258|
|**Market transactions**||||||
|Registered during LTR|0.352|0.354|0.218|0.418|0.395|
|<br>Subsequent registration|0.026|0.007|0.056|0.050|0.000|
|<br>Not officially registered|0.622|0.639|0.726|0.532|0.605|
|<br>Of which: register only at the village|0.500|0.783|0.189|0.347|0.634|
|Number of parcels|576|144|124|141|167|
|**Inheritance transactions**||||||
|Registered during LTR|0.673|0.756|0.511|0.746|0.604|
|Subsequent registration|0.014|0.006|0.015|0.030|0.000|
|<br>Not officially registered|0.313|0.239|0.473|0.225|0.396|
|Of which: register only at the village|0.268|0.395|0.081|0.395|0.306|
|Number of parcels|571|180|131|169|91|
|**Reason for non-registration**||||||
|<br>Lack of information|0.21|0.34|0.09|0.18|0.31|
|Lack of interest|0.13|0.10|0.10|0.24|0.09|
|Fees to high|0.13|0.16|0.06|0.13|0.19|
|Will register later|0.12|0.10|0.03|0.22|0.18|
|Seller didn’t have certificate|0.02|0.03|0.04|0.00|0.02|
|DLO is too far|0.01|0.01|0.01|0.01|0.01|
|Conflict on the parcel|0.01|0.01|0.01|0.01|0.01|
|Other reason|0.38|0.25|0.67|0.22|0.21|
|No. of ownedparcels|12,798|3,574|3,501|3,234|2,489|

_Source:_ Own computation from 2015 round of Rwanda Land Tenure Regularization Survey a Includes newly acquired parcels located outside the cell boundary or with missing detailed information on subsequent registration. b Restricted only to parcels acquired within the cell of sampled villages.

21
_Figure 6.3: Total emission reduction in millions of tonnes from base case_ <!-- Start of picture text --> Reduction in total emission (from all sources) from tax on fossil fuel<br>compared to base case (millions of tonnes of CO2)<br>2018 2022 2026 2030<br>(5.0 USD/ton) (13.3 USD/ton) (21.7 USD/ton) (30.0 USD/ton)<br>0<br>-0.5<br>-1<br>-1.5<br>-2<br>-2.5<br>-3<br>-3.5<br>-4<br>-4.5<br>DTAX STAX SAVINGS CORPOR TRANS<br>Millions of tonnes of carbon<br><!-- End of picture text --> 16
25 Table 1 Unit Costs of Education-Type Interventions

|Country|Cost/Beneficiary|Comments|Source|
|---|---|---|---|
||Nutrition Educ|ation||
|Morocco|$1- $3|monthly class:<br>additional to<br>MCH program|Hornick(1985)|
|Indonesia|$2|mass media<br>component of<br>MCH program|Hornick (1985)|
|Honduras|$2.50|mass media<br>effort on ORT|Hornick (1985)|
|Philippines<br>(Manoff)|$3.33|mass media<br>efforts to<br>add oil to<br>weaning food|Hornick (1985)|
|Burkina Faso|$0.22|volunteers<br>taught mothers<br>to prepare<br>weaning foods|Heimendinger,<br>et al. (1981)|
|Dominican Republic|$23.17|combined with<br>growth monitoring<br>community workers<br>receive only<br>token wages|USAID (1988)<br>:|
||Breastfeeding Pro|motion||
|Hypothetical<br>NOTE: costs are in cur|$1-$5<br>rent dollars.|no program data<br><br> <br><br>|Phillips,<br>Mills and<br>Feachem<br>(1987)|
UNCTAD. (2009). Information Economy Report 2009: Trends and Outlook in Turbulent Times. New York and Geneva: United Nations. <u>http://www.unctad.org/en/docs/ier2009_en.pdf.</u> Vashistha, Avinash and Ed Nair. (2010). Location Assessment: Perception and Reality for Global Businesses: Tholons Inc. & Global Services. Webminar. January 15.

Villafania, Alexander (2009). Call Center Revenues Reach $5B in ‘09. Retrieved January 11, - 2010, from http://newsinfo.inquirer.net/breakingnews/infotech/view/20090720 <u>216409/Call-center-revenues-reach-5B-in-09</u> Wadhwa, Vivek, Ben Rissing, Gary Gereffi, John Trumpbour, and Pete Engardio. (2008). The Globalization of Innovation: Pharmaceuticals: Can India and China Cure the Global Pharmaceutical Market: Kauffman Foundation. This research was comissioned by the Kauffman Foundation.

<u>http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1143472#PaperDownload.</u> Young, Allie, Dane S. Anderson, Kenneth F. Brant, Robert H. Brown, Linda R. Cohen, Susan Cournoyer, Claudio Da Rold, Matthew Goldman, Helen Huntley, Venecia K Liu, Richard T. Matlus, William Maurer, Ben Pring, Cathy Tornbohm, Gianluca Tramacere, Jim Longwood, Ian Marriott, Dean Blackmore, TJ Singh, Cassio Dreyfuss, and Rishi Sood. (2008). Gartner on Outsourcing, 2008-2009: Gartner. <u>http://www.gartner.com/DisplayDocument?doc_cd=164206.</u> 31
Table 15. Turkey Regional NUTS2 Income Based Poverty Rates from LFS ($2.5 PPP)

|**Label**|**2006**|**2007**|**2008**|**2009**|**2010**|**2011**|**2012**|**2013**|
|---|---|---|---|---|---|---|---|---|
|TR10|0.84|1.24|1.76|1.66|1.65|1.85|2.11|2.61|
|TR21|2.50|2.10|2.41|1.93|2.30|2.15|2.39|2.85|
|TR22|2.70|2.60|2.97|2.63|2.77|2.46|2.82|3.41|
|TR31|1.94|2.06|1.54|1.61|1.44|1.44|1.77|2.12|
|TR32|2.67|2.99|2.73|2.78|2.22|2.31|2.44|3.14|
|TR33|2.38|2.74|2.72|2.71|2.00|1.95|2.36|3.12|
|TR41|1.23|1.29|1.63|1.68|1.85|1.58|1.73|2.09|
|TR42|1.63|1.85|2.56|2.68|2.52|2.22|2.55|2.86|
|TR51|1.71|1.71|1.91|1.72|1.90|1.62|1.95|2.36|
|TR52|2.58|2.83|2.63|2.51|2.49|2.29|2.84|3.43|
|TR61|6.14|5.19|5.12|3.48|3.22|3.91|4.25|4.84|
|TR62|5.36|4.93|5.51|4.01|3.60|4.34|5.21|6.10|
|TR63|6.21|5.60|6.99|5.42|5.05|6.16|6.76|7.63|
|TR71|3.72|4.80|5.79|5.62|4.47|4.41|5.33|6.08|
|TR72|3.89|5.36|6.05|5.02|4.45|4.54|5.40|6.17|
|TR81|2.95|4.46|5.10|3.39|2.52|2.58|3.18|3.82|
|TR82|2.69|4.52|5.35|4.29|3.52|2.91|3.31|4.00|
|TR83|3.93|5.43|6.00|4.90|3.77|3.02|3.64|4.64|
|TR90|2.89|3.27|4.10|4.26|4.14|3.87|4.15|4.75|
|TRA1|7.17|9.80|12.36|8.83|9.31|11.82|12.97|15.13|
|TRA2|11.24|17.40|21.45|17.48|16.06|18.50|19.20|22.83|
|TRB1|8.51|8.73|12.70|11.44|12.70|12.39|14.42|17.19|
|TRB2|19.11|19.84|26.96|24.82|26.60|23.98|25.35|28.22|
|TRC1|20.60|22.92|25.80|21.03|19.55|19.80|22.20|23.02|
|TRC2|24.68|26.17|30.62|27.27|25.39|23.76|26.79|31.19|
|TRC3|23.09|25.82|30.82|25.31|22.53|20.62|24.81|26.87|

_Notes_ : LFS imputed data using OLS, regionally deflated. Poverty estimates have standard errors. _Source_ : LFS, SILC 2006-2013; authors’ calculations.

Table 16. Literature on patterns of growth and poverty reduction

|Country|Aggregation|Primary Drivers of Poverty<br>Reduction|
|---|---|---|
|Brazil, 1985-2004<br>(Ferreira,Leite, andRavallion,2010)|Region, Industry, Year|Social Spending<br>Services Sector|
|Indonesia, 1984-2002<br>(Suryahadi, Suryadarma, and Sumarto,<br>2009)|Sector, urban-rural, year|services growth and rural<br>agricultural growth in rural areas|
|Global cross-country<br>(Loayza andRaddatz,2010)||Unskilled labor intensive sectors|
|China, 1984-2004<br>(Montalvo andRavallion,2010)|Province, year|Growth in the agricultural sector|

45
15,000 residents, and an urban sample, that included larger localities (more than 15,000 residents).<sup>6</sup>

# **Table 1 Mexico-Social Network Effects Among Indigenous Males and Females 12-17 years of age**

|||**Males 12-17yrs old**<br>||
|---|---|---|---|
||**Rural areas**|**Semi-Urban areas**|**Urban areas**|
|**Attending School**|-.023|**0.336**|**0.326**|
|t-value|(-0.28)|**(2.03)****|**(1.84)****|
|Adjusted R-squared|0.2988|0.2768|0.3225|
|Number of observations|51,111|11,845|3,081|
|**Working**|0.018|**0.392**|**0.451**|
|t-value|(0.20)|**(2.12)****|**(1.71)***|
|Adjusted R-squared|0.2310|0.2185|0.3402|
|Number of observations|51,334|11,906|3,089|
|||**Females 12-17yrs old**||
||**Rural areas**|**Semi-Urban areas**|**Urban areas**|
|**Attending School**|-0.089|0.002|0.148|
|t-value|(1.04)|(0.02)|(0.89)|
|Adjusted R-squared|0.3496|0.3104|0.3500|
|Number of observations|49,519|11,669|3,793|
|**Working**|**0.140**|.088|-0.234|
|t-value|**(1.96)****|(0.65)|(-1.16)|
|Adjusted R-squared|0.1373|0.1555|0.3636|
|Numberofobservations|49,766|11,740|3,808|

Source: Authors’ estimates of the social network effect based on the 2000 Population and Housing Census (10% sample).

Notes:

- t-values based on robust standard errors corrected unknown forms of heteroskedasticity

- * p-value <0.10

- ** p-value<0.05

- *** p-value<0.01

The results summarized in Table 1, suggests that strongly positive and significant effects are at work in the decision to attend school and work among male teenagers in semi-urban and urban areas but not for girls. In fact, network effects among teenage males in these areas are equally strong with respect to school attendance as they are for work. In the rural areas, social

> 6  The full set of parameter estimates for all the control variables included in regression equation (3) is not reported here but is available directly from the authors upon request.

10
**Figure 10** also shows that: (i) the share of commercial debt in total public and publicly guaranteed (PPG) debt remained stable from 2007 to 2016, and (ii) the share of PPG bonds increased from 9 percent in 2007 to 19 percent in 2016. The amount owed to bondholders (6.6 percent of GNI in 2017) is now comparable to that owed to either multilateral organizations or bilateral creditors (6.5 and 5.9 percent of GNI in 2017, respectively).

As argued above, the share of the public external debt being held by non-Paris Club governments and private creditors (bondholders and private commercial banks) has been gradually rising in the post-debt-relief period. **Figure 11** shows that the composition of bilateral debt has changed significantly: countries have shifted from Paris Club debt toward non-Paris Club creditors. Within one decade after HIPC and MDRI, the share of non-Paris Club creditors in total PPG debt doubled, from 15 percent in 2007 to 30 percent in 2016, while the share of Paris Club bilateral debt decreased from 25 to 7 percent. At the end of 2016, non-Paris Club debt accounted for 80 percent of total bilateral debt. This trend is even more pronounced in commodity exporting countries, where the share of non-Paris Club creditors increased to nearly 90 percent of total bilateral debt at the end of 2016.

**Figure 11. Composition of PPG Public Debt over time** **_(%)_**

<!-- Start of picture text --> 100<br>8 7 8 7 6 6 6 7 7 7 6<br>9 9 9 10 15 16<br>20 19 20 20 19<br>80<br>60 42 44 44 45<br>45 44 38<br>42 42 41 40<br>40<br>7<br>27 25 23 23 15 14 11 10 8 8<br>20<br>30<br>19 21 21 22 25 26<br>14 15 15 15<br>0<br>2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br>Non-Paris Club Bilateral Paris Club Bilateral Multilateral Bonds Commercial<br><!-- End of picture text --> _Source: World Bank International Debt Statistics and staff calculations. Published in: World Bank (2018) Africa’s Pulse, Volume 17. Washington, DC: The World Bank, October_ The change in the composition of public debt in Sub-Saharan Africa summarized above implies that the region is gradually moving away from traditional concessional sources of financing. Over the past 15 years we have observed a gradual and protracted change in the composition of debt portfolios in Sub-Saharan Africa away from traditional concessional sources of financing ( **Figure 12** ). The share of multilateral and concessional debt (from multilateral and bilateral sources) in the region’s public external debt has steadily declined over time. The average share of concessional 12
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26
WPS3822

# **Telecommunications Performance, Reforms, and Governance**<sup>*****</sup>

## **ANTONIO ESTACHE**

The World Bank ECARES, Universite Libre de Bruxelles _E-mail:_ _<u>aestache@worldbank.org</u>_ **ANA GOICOECHEA** The World Bank _E-mail:_ _<u>agoicoechea@worldbank.org</u>_ **MARCO MANACORDA** Department of Economics, QMUL CEP, London School of Economics _E-mail:_ _<u>M.Manacorda@lse.ac.uk</u>_

## **Abstract**

This paper assesses the effects of private capital and independent regulatory agencies on telecommunications performance by using cross-country panel data from 1990 to 2003. In general, we find that having independent regulatory agencies positively affects affordability and labor productivity, but negatively affects quality; while having private capital positively affects access, quality and labor productivity, but negatively affects affordability. However, reform policies affect developing and developed countries differently in some cases. We also find that governance plays an important role as it affects performance and interacts with reform policies.

## World Bank Policy Research Working Paper 3822, January 2006

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

* We are grateful to Jose-Luis Guasch, Paul Noumba Um, Stephane Saussier, Tomas Serebrisky, Lourdes Trujillo, Tommaso Valletti, David Veredas and Christine Wei for useful discussions and suggestions.
external rather than internal financing. Thus, we expect that as the transition moves along-China’s GDP per capita in PPP rose from around US$2,900 (in 2011 US$) in 1993 to about US$11,000 in 2012<sup>9</sup> -- Chinese firms will rely less on political connections and more on formal institutions such as courts and banks.

**Hypothesis 4** . As the Chinese economy grows, firms rely more on courts, contracts, and external financing and less on families, retained earnings, and political connections. Moreover, firms improve their corporate governance and adopt more formal governance mechanisms (i.e., the board of directors and board of shareholders).

# **3. Data description**

Our key firm-level data consist of 10 waves of a nationwide survey of privately-owned firms (NSPF) in China, conducted in 1991, 1993, 1995, 1997, 2000, 2002, 2004, 2006, 2008, and 2012 jointly by the All China Industry and Commerce Federation, the Center for Private Economy Studies at the Chinese Academy of Social Sciences, and the CCP United Front Work Department. Our study ends in year 2012, which is the last year the NSPF data are publicly available. The sampling method used in NSPF was multistage-stratified random sampling to achieve a balanced representation of private firms across regions and industries. First, the total number of private firms to be surveyed was determined. Second, six cities or counties were selected from each province, including the capital city, one prefecture-level city, one countylevel city, and three counties. Next, the number of private firms to be surveyed in each province was determined as the product of the share of local private firms in the national total and the total sample size. The numbers of firms in each city, county, and sector were likewise determined. The survey thus covers firms in 19 sectors ranging from agriculture to service industries in 31 provinces, municipalities, autonomous regions in China. And consequently, NSPF is the most comprehensive survey on private firms and their BEs in China.

The survey was then conducted through interviews with firm owners. The survey covers owner attributes (i.e., family background, human capital, political connections, and occupational experiences) and firm attributes (i.e., size, age, and basic financial background). More importantly, the survey has information on firms’ external environments such as court

> 9 Data sources: Penn World Table version 9.0.

14
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20
point for reforms. Is this the case? And, if so, what explains the divergence across EU accession candidates in the depth of GATS commitments?

# **3. GATS Commitments and Actual Policies**

As mentioned in the Introduction, there are two rationales in the literature for the existence of trade agreements. The market access explanation is that agreements are a way of internalizing the spillovers that are created by other countries’ policies. This rationale emphasizes the terms of trade consequences of policies. The domestic political economy explanation puts the stress on the fact that trade agreements can be a vehicle for overcoming domestic resistance to desirable reforms (independent of any terms of trade rationale) and locking in such reforms (enhancing the credibility of reform). Given the small size of most transition economies the second explanation is more likely to apply. However, in assessing possible explanations for the observed pattern of GATS commitments, account needs to be taken of explanatory factors such as geographic proximity to a large market (the European Union), the size of the economy, and engagement in the EU accession process. Countries may have a greater incentive to use the GATS as a signaling and commitment device if they are small, geographically distant from large markets, and lack any prospect of joining the EU. In assessing the determinants of GATS commitments it is necessary to have an understanding of the actual policies applied by countries and the evolution in these policies.

What follows begins with an aggregate analysis of the extent to which GATS commitments by the four country groups match actual policies. The analysis is not a one-to-one comparison of commitments and practice in sub sector x or y. Our objective is simply to focus on the question whether GATS commitments help ‘lock in’ a broader reform agenda and are a good signal for actual policies or policy direction. Figure 1 reports data on the “quality” of actual service sector policies and reforms in the four country groups. The policy indices used were constructed by the EBRD and range from 1 to 4.3, with higher numbers implying a stronger commitment to reform (better policies). The Annex to this paper summarizes the criteria that qualify countries for the top score. Essentially the index measures the success of policy on the basis of privatization of state-owned monopolies, liberalization, and progress in implementing a supporting legal, institutional and regulatory framework. Thus, the indices used do not allow a direct comparison with GATS commitments, as the set of policies is different. The data span the 11