rafmacalaba/datause-encoder-data huggingface dataset:
**9**

scope was initially limited to villages near watersheds and other natural resources.<sup>11</sup> The establishment of a Millennium Challenge Corporation (MCC) compact between the United States and Benin in 2006 considerably increased the resources available for these interventions and changed the scale of experimentation. Under the compact, approximately US$34 million was put towards land formalization activities, including the establishment of PFR Rural Land Use Plans, policy reform activities, and land information systems. With MCC’s technical and financial support, the PFR intervention in Benin enables producers to formalize rural land rights obtained under customary arrangements.

The PFR exemplifies the aforementioned paradigm shift in land formalization programs, as it embeds the recognition of land rights within existing, customary practices. The program consists of two key steps: first, each community identifies and demarcates all land parcels, mapping out customary rights through a full topographic land survey, and laying cornerstones to explicitly mark parcel boundaries; second, land ownership is formally documented in the form of certificates. The capstone step of the program is the delivery of a legally valid land certificate ( _Certificat Foncier Rural_ ) to individual landholders, resulting in a formal recognition of existing customary land rights (with the option of upgrading to a fully-fledged title at a later stage).<sup>12</sup> At the time of our field work, this second phase of the program had not taken place. We exploit this timing to examine the early effects of the land formalization program’s demarcation activities.

# **2.3 Land demarcation intervention**

The demarcation process clarifies claims and facilitates land-related conflict resolution, and culminates with a written documentation of existing land rights as well as the physical marking of parcel boundaries with cornerstones. As such, land demarcation is the opportunity for the community to resolve disputes and overlapping claims on the land, and sets the stage for the second key step of the formalization process—land certification.

Land demarcation is marked by a series of sub-interventions at the village level, where the parcel (i.e., the landholding) is the primary unit of treatment. The demarcation process is led, with support from the PFR program, by local land management commissions ( _Sections villa-_

> 11The original program was implemented in Benin by the _Projet de Gestion des Ressources Naturelles_ , funded by the World Bank, Agence Française de Développement (AFD), and German Technical Cooperation (GTZ), and the _Projet de Gestion des Terroirs et des Ressources Naturelles_ , funded by AFD and GTZ.

> 12The distinction between land use certificates and titles will soon be abolished with the recent creation of a single property right, the land property certificate ( _Certificat de Propriété Foncière_ ).
pollution as a problem.

To measure managerial quality, we follow de Mel et al. (2008) and McKenzie and Woodruff (2017), who build on the work of Bloom and Van Reenen (2007) to adapt standard management surveys to the context of small firms in developing countries. In particular, we create a standardized index of manager quality by aggregating a wide range of questions about marketing practices, stock management of inputs, recording of transactions, financial performance review, business planning and forecasting. The index should be interpreted as a summary measure of overall management quality. We validate the index in Bassi et al. (2021), where we show that it is a strong predictor of revenues per worker. The exact construction of the index is detailed in Appendix A.1. In addition to managerial quality, we also collected detailed information on other owner and worker characteristics (e.g. education, age, experience etc.) including measures of workers’ time use at the

**Descriptives.** Table 1 reports descriptive statistics for the 1,027 firms in our survey sample. The average firm has about five employees. Average monthly revenues and profits are $1,481 and $244, respectively. To put these numbers into perspective, per capita GDP in Uganda was $60 per month in 2018. Thus, the average firm is profitable, and operates beyond subsistence level. Besides, these are established and regular activities: the average firm has been in business for 10 years. The average owner works 9 hours per day for the firm, so this is the primary job for the majority of them. The average employee has 3.5 years of tenure, works 9.9 hours per day for the firm, and makes about $71 per month. Taken together, the evidence shows that our sample is composed of established and profitable firms that employ workers who hold stable, regular, and well-paying jobs by Ugandan standards.

# **4.4 Road Network Data**

We supplement the pollution measures and firm survey with data on the network of Ugandan roads published by the World Food Program following the United Nations Spatial Data Infrastructure (UNSDI) for Transport standards.<sup>23</sup> The WFP shape-file distinguishes between 5 distinct road types in Uganda: _track/trail_ , _tertiary roads_ , _secondary roads_ , _primary roads_ , and _highways_ , by converting Open Street Map (OSM)’s highway tag.<sup>24</sup> The geo-referenced nature of the dataset allows us to match roads with both the pollution and the firm survey data. We create an ordinal measure of road size. To do so, we rank road types by size such that _track/trail_ are assigned the number 1, and _highways_ are assigned the number 5. We use these values when

> 23Source: `https://geonode.wfp.org/layers/ogcserver.gis.wfp.org:geonode:uga_trs_roads_osm/ metadata_detail.`

> 24The WFP classification is a mapping of the 18 OSM’s highway tag into 7 categories (the five categories mentioned above, as well as Residential and Path/Footway, which are absent from the Uganda road shape-file). Details of the mapping can be found on the WFP website.

15
Rose, A., Wei, D., 2013. Estimating the economic consequences of a port shutdown: the special role of resilience. Econ. Syst. Res. 25, 212–232.

- Santos, J.R., Haimes, Y.Y., 2004. Modeling the Demand Reduction Input‐Output (I‐O) Inoperability Due to Terrorism of Interconnected Infrastructures*. Risk Anal. 24, 1437–1451.

- Scussolini, P., Aerts, J., Jongman, B., Bouwer, L., Winsemius, H.C., de Moel, H., Ward, P.J., 2015. FLOPROS: An evolving global database of flood protection standards.

Siegel, P., de la Fuente, A., 2010. Mainstreaming natural disaster risk management into social protection policies (and vice versa) in Latin America and the Caribbean. Well‐ Soc. Policy 6, 131–159.

- Skoufias, E., 2003. Economic Crises and Natural Disasters: Coping Strategies and Policy Implications. World Dev., Economic Crises, Natural Disasters, and Poverty 31, 1087–1102.

- Surminski, S., Bouwer, L.M., Linnerooth‐Bayer, J., 2016. How insurance can support climate resilience. Nat. Clim. Change 6, 333–334.

UN‐ISDR, 2015. Global Assessment Report on Disaster Risk Reduction.

- USGS, 2015. USGS. 2015. “PAGER (Prompt Assessment of Global Earthquakes for Response).” http://earthquake.usgs.gov/research/pager/.

Winsemius, Hessel C., Brenden Jongman, Ted I. E. Veldkamp, Stephane Hallegatte, Mook Bangalore, and Philip J. Ward. 2015. “Disaster Risk, Climate Change, and Poverty : Assessing the Global Exposure of Poor People to Floods and Droughts.” World Bank Policy Research Working Paper 7480 (November): 1–35.

World Bank, 2013. Risk and Opportunity: Managing Risk for Development (World Development Report).

44
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|---|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Honduras Rural Competitiveness Project<br>Augusto Garcia|
|Support for the Second Phase of the Expansion of the Program of CoTheresa Jones|
|Support for the Second Phase of the Expansion of the Program of CoTheresa Jones|
|Support for the Second Phase of the Expansion of the Program of CoTheresa Jones|
|Support for the Second Phase of the Expansion of the Program of CoTheresa Jones|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
|Agriculture and Rural Development Project<br>Daniel P. Gerber|
# **Appendix B Variable Definitions**

**Table B.1 Definition and sources of project-level variables**

|_Variable_|_Definition_|_Source_|
|---|---|---|
|Early termination|1 if project is canceled, 0 otherwise. A project is<br>canceled if the private party exits by selling or<br>turning over its shares back to the government or<br>byceasingoperations.|PPI database and authors’<br>collection|
|Contract period|Percentage of contract period elapsed until early<br>termination (as defined above), otherwise until<br>end of 2020|PPI database and authors’<br>collection|
|Type|_Greenfield_if the special purpose vehicle (SPV)<br>builds and operates a new facility,_brownfield_if<br>the SPV takes over an existing asset and either<br>rehabilitates or expands it,_management and_<br>_lease_if the SPV takes over the management of the<br>public asset while ownership and investment<br>decisions remain with thegovernment|PPI database|
|Sector|Electricity, natural gas, telecom, airports,<br>railroads, toll roads, seaports, treatment plants,<br>water utility|PPI database|
|Direct government support|1 if capital, revenue or in-kind subsidies exist, 0<br>otherwise|PPI database|
|Indirect government support|1 if payment, debt, revenue, or other kind of<br>guarantee exists,0 otherwise|PPI database|
|Multilateral support:|1 if a multilateral bank provides financial support,<br>0 otherwise|PPI database|
|Subnational government<br>contract|1 if local or provincial/state government grants<br>the contract,0 otherwise|PPI database and authors’<br>collection|
|Physical Investment|Total investment in physical assets, in 2020 billion<br>US dollars|PPI database and authors’<br>collection|

**Table B.2 Definition of macroeconomic variables**

|_Variable_|_Definition_|
|---|---|
|Annual GDP per capita growth rate|Annual GDP per capita growth rate for previous year, detrended and<br>demeaned using the filter suggested by Hamilton (2018). Calculated using<br>the GDP per capita growth series from_World Development Indicators_<br>(WDI).|
|Annual depreciation|Depreciation rate of local currency against US dollar the previous year,<br>detrended and demeaned using the filter suggested by Hamilton (2018).<br>Calculated using the “DEC alternative conversion factor (LCU per US$)”<br>series from the WDI.|
|Banking crisis occurred|1 if a systematic banking crisis occurred in the country the previous year, 0<br>otherwise(from Laeven and Valencia 2018)|
|Debt crisis occurred|1 if a debt crisis occurred in the country the previous year, 0 otherwise<br>(from Laeven and Valencia 2018)|
|Exchange rate crisis occurred|1 if an exchange rate crisis occurred in the country the previous year, 0<br>otherwise(from Laeven and Valencia 2018)|

37
# **Mining and Economic Development: Did China’s WTO Accession Affect African Local Economic Development?**<sup>**‡**</sup>

Tony Addison<sup>2</sup> , Amadou Boly<sup>3</sup> , and Anthony Mveyange<sup>4</sup>

**<mark>Key Words:</mark>** <mark>mining; commodity boom; local development; Africa; China; WTO</mark> **_<mark>JEL Codes:</mark>_** _<mark>O130, O55, Q32, Q330, R32</mark>_

> ‡ **<mark>Acknowledgements:</mark>** <mark>The authors wish to thank the participants of the Environmental and Resource Economics Seminar at the University of California Berkeley for their constructive comments. We also wish to thank the participants of the 2015 East Africa Evidence Summit held in Nairobi, Kenya. Anthony Mveyange acknowledges the funding received from the United Nations University-World Institute for Development Economic Research (UNUWIDER) to support this study. This paper has been supported by UNU-WIDER’s ‘Macro-economic management (M-</mark> <u><mark>EM)’ project. The usual caveats apply.</mark></u>

> 2 Chief economist and deputy director, the United Nations University World Institute for Economic Development Research (UNU-WIDER), email: <u>addison@wider.unu.edu.</u>

> 3 Principal research economist, the African Development Bank (AfDB), email: <u><mark>a.boly@afdb.org</mark></u>

> 4 Economist, the World Bank Development Research Group (DECRG) and corresponding author, email: <u>amveyange@worldbank.org.</u>
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Benhabib, J., and M. M. Spiegel. 2000. “The Role of Financial Development in Growth 29
importance of the services sector and the declining importance of the agriculture sector reflects the process of structural transformation resulting from economic development (Lewis 1954, McMillan, Rodrik and Sepúlveda 2017).

**Following the ICLS-17 definition of formal employment, less than one third of workers in Indonesia are formally employed, with higher levels of formal employment in more developed provinces.**<sup>**5**</sup> In short, a worker is formally employed if they are covered by labor legislation (Wihardja and Cunningham 2021).<sup>6</sup> The ICLS-17 definition of formal employment is used throughout this paper. Figure 8 shows that there is a high positive correlation between Gross Regional Domestic Product (GRP) per capita and formal employment of 0.68. Moreover, Figure 9 shows that between 2016 and 2023, the share of formal employment in Indonesia has remained somewhat stagnant, with less than 25 percent of workers being formally employed throughout the period. Formal employment is highest among workers aged 25 to 34 at 33.5 percent, as shown in Figure 10. Formal employment is lowest among workers aged 65 and older at 3.1 percent.

**Figure 8: GRP per capita and formal employment rate by province, 2023**

<!-- Start of picture text --> 200,000 50<br>40<br>150,000<br>30<br>100,000<br>20<br>50,000<br>10<br>0 0<br>GRP per capital (constant 2010 IDR) Formal employment rate (%) (RHS)<br>Formal employment rate (%)<br>GRP per capita (constant 2010 IDR) East Nusa Tenggara Maluku West Nusa Tenggara West Sulawesi Bengkulu Gorontalo Nangroe Aceh Darussalam West Kalimantan Lampung Central Java DI Yogjakarta West Sumatera West Java South Kalimantan Bali North Maluku North Sulawesi North Sumatera Southeast Sulawesi Bangka-Belitung South Sulawesi Central Kalimantan Banten South Sumatera East Java Jambi Papua Central Sulawesi West Papua Riau Kep Riau North Kalimantan East Kalimantan DKI Jakarta<br><!-- End of picture text --> Source: Author’s calculations using BPS and Sakernas data

> 5 In comparison, the national statistics office of Indonesia ( _Badan Pusat Statistik,_ BPS) defines formal employment based on a matrix of occupation and job status. See Wihardja and Cunningham (2021) for details on both the BPS and ICLS-17 definitions of formal employment.

> 6 Following ICLS-17, a formally employed worker is defined as: (1) a self-employed individual, or an employer assisted by temporary, unpaid, or permanent workers in a formal production unit, OR (2) an employee or casual worker who receives at least one social benefit and paid leave, OR (3) an employee or causal worker who receives neither social benefits nor paid leave but has a permanent contract. See Wihardja and Cunningham (2021) for details on both the BPS and ICLS-17 definitions of informal employment.

6
Policy Research Working Paper 6686

# **Abstract**

Bureaucratic reform is a priority of donor organizations, including the World Bank, but is notoriously difficult to implement. In many countries, politicians have little interest in the basic financial and personnel management systems that are essential to political oversight of bureaucratic performance. To explain this, this paper presents a new perspective on the political economy of bureaucracy. Politicians in some countries belong to parties that are organized to allow party members to act collectively to limit leader shirking. This is particularly the case with programmatic parties. Such politicians have stronger incentives to pursue public policies that require a well-functioning public administration. Novel evidence offers robust support for this argument. From a sample of 439 World Bank public sector reform loans in 109 countries, the paper finds that public sector reforms are more likely to succeed in countries with programmatic political parties.

This paper is a product of the Macroeconomics and Growth Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at pkeefer@worldbank.org.

_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 views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
**Figure 4.2 Reference Scenario for Population Exposure to Ozone and PM10 for the ZMVM, 1995-99**

Ozone, maximum and annual average daily 1-hour maximum <!-- Start of picture text --> Population exposed to the stated concentration<br>20,000,000 1 03-max<br>18,000,000 _ 901% B 03_AA<br>16,000,000<br>14,000,000<br>12,000,000<br>10,000,000 _ ___<br>8,000,000<br>6,000,000 - _ _<br>4,000,000 - _____<br>2,000,000<br>0.000 0.050 0.100 0.150 0.200 0.250 0.300 0.350<br>Ozone concentration (ppm)<br>daily and and annual average population exposure<br>Population exposed to the stated concentration<br>18000000 ----.......<br>16000000 -O-|PM10_max<br>-O -PM1O AA<br>14000000 - _ . AQS<br>12000000<br>10000000<br>8000000<br>6000000<br>4000000 _____- __<br>2000000 = _ _ , _ _<br>0<br>0 50 100 150 200 250 300 350<br>PM15 concentration (:g/m3)<br><!-- End of picture text -->

PM10, maximum daily and and annual average population exposure _15_