rafmacalaba/datause-encoder-data huggingface dataset:
**Table 6: long term impacts of the 4P program on assets**

||Hous<br>|ingconditions in<br>|dices<br>||Asset indices<br>||
|---|---|---|---|---|---|---|
||KKL|PCA|ICW|KKL|PCA|ICW|
||||Wo<br>|men<br>|||
|ITT|-0.062|-0.339|-0.290|0.001|-0.275|0.159|
||(0.21)|(0.13)|(0.46)|(0.98)|(0.31)|(0.81)|
|Observations|437|348|348|437|437|437|
|Adj. R2|0.11|0.08|0.05|0.09|0.12|0.02|
|Control mean|-0.035|0.059|0.951|-0.039|-0.315|-0.653|
||||M|en|||
|ITT|-0.052|-0.182|-0.332|-0.016|-0.361|-0.434|
||(0.30)|(0.44)|(0.43)|(0.57)|(0.15)|(0.51)|
|Observations|435|337|337|435|435|435|
|Adj. R2|0.11|0.15|0.06|0.03|0.12|0.02|
|Control mean|-0.055|-0.138|0.529|-0.066|-0.614|-1.011|

Regression results from equation 1; with demeaned covariates and interaction of full set of covariates with treatment variable. KKL denotes average of z-scores as in Katz, Kling and Liebman (2007); PCA is the first component of PCA; and ICW applies inverse covariate weighting. P-values in parentheses: * p<0.1 ** p<0.05 *** <u>p<0.01</u> 29
relationship between regulatory quality and financial inclusion outcomes. The remainder of the paper is organized as follows. The next section describes the regulatory index constructed, with explanations on the rationale of selection, scoring methodology and general trends. Section III presents the econometric models used and the results of the estimations. Section IV contains some concluding remarks.

# **II. Data description**

To construct our regulatory measures, we employ data from the World Bank’s Enabling the Business of Agriculture (EBA) project. EBA finance data are collected through standard questionnaires, which are completed by three main types of respondents: financial sector supervisory authorities, financial lawyers, and legal officers of financial institutions. All data are supported by official regulations and cover 62 economies.<sup>2</sup> The EBA data set features finance indicators benchmarking regulations in areas that are key to promote access to financial services by unserved or underserved customers (table 1). Six indicators are developed from three different aspects that affect financial inclusion: 1) local providers of financial services, including MFIs and financial cooperatives; 2) delivery channels of financial services, with focus on the booming branchless banking activities; and 3) movable collateral facilitating access to credit.

**Table 1.** EBA Finance indicators

- <mark>NON-BANK LENDING INSTITUTIONS</mark> _1) Operation and prudential regulation of MFIs_  Prudential rules (capital adequacy ratio, minimum capital, loan loss provisioning)

- Loan size limits  Consumer protection (effective interest rate disclosure, deposit insurance)

- _2) Operation and governance of financial cooperatives_  Prudential rules (minimum capital, solvency/liquidity ratio)

- Consumer protection (effective interest rate disclosure, deposit insurance)

- Ability to merge

- <mark>BRANCHLESS BANKING</mark> _3) Agent Banking_  Minimum standards to operate as an agent and services offered by agents

- Exclusivity of agent contracts

- Financial institution liability for agent actions

- _4) E-money_  Allowing e-money activities (issued by either financial or non-financial institutions)

- License requirements (interoperability, internal controls, consumer protection mechanisms) for non-financial institution e-money issuers

- Safeguards for customer funds

- <mark>MOVABLE COLLATERAL</mark> _<u>5) Warehouse receipts</u>_

> 2 See Annex I for the list of countries included in the EBA sample. The 62 countries are chosen to represent all country groups based on income level, geographical position and role of the agriculture sector as defined by World Bank (2007). For full information on EBA data and underlying methodology, see World Bank (2017).

5
**12**

## **Infonnational barriers**

Insufficient economic data, data limitations, and poor information about the cultural, social, and political norms of the existing population often hinder development of an effective planning strategy. Additionally, short sighted development goals, insufficient budget for planning, and poor appreciation of the importance of good planning are further impediments to effective management of river basin resources.

## **Physical barriers**

The physical nature of a river basin can confound efforts to manage the basin's resources. Because basins are irregular and receive water flows from multiple sources, difficulties are often encountered when attempting to divide a basin into discrete, manageable subunits. Further, the stochastic nature of the water supply makes prediction and control of the water problematic.

_Inlerbasin transfer._ Temporal and spatial variability are usual barriers to integrated river basin development. The possibility of interbasin transfer has implications for the planning of aL regional development projects while providing flexibility and stability in water supply. Sometimes the geography is such that it does not allow large scale interbasin transfer of water, and sometimes the geopoGtics is such that it does not accept the results from the integrated approach.

# **Institutional barriers**

Although economic models can indicate opportunities for improvement in river basin planning, development, and management, existing institutions and conflicting policies may pose insurmountable barriers to more effective management. Grigg and Flemming (1980) discussed the United States! policy on water quality management. As stated in the Federal Water Pollution Control Act of 1972, the water quality management objectives are to maintain United States waters, give the States an expanded role in implementing water quality programs, and to assure that programs are equitable across all states, geographic regions, and industries. This third objective by definition rules out many economic approaches to water quality management such as marginal pollution taxes and transferable discharge permits; that give low cost polluters a comparative advantage over other polluters.

# **Application Bariers**

As was correctly indicated by Tanji (1981), many models are formulated and applied to specific problems, and are not amendable to more generalized problem situations. If a model is to be applied from one problem situation (or location) to another, the model generally needs modification, calibration and validation. These modifications are associated with additional cost (e.g., in terms of time) to the potential user. This cost may become a barrier to effective use of the model even if it is the best that fits the problem needs.
Policy Research Working Paper 6032

# **Abstract**

Albania’s radical farmland distribution is credited with averting an economic crisis and social unrest during the transition. But many believe it led to a holding structure too fragmented to be efficient, and that public efforts to consolidate plots are needed to lay the foundation for greater rural productivity. This paper uses farm-level data from the 2005 Albania Living Standards Measurement Survey to explore this quantitatively. The analysis finds no support for the argument that fragmentation reduces productivity. However, producers fail to utilize about 10 percent of the country’s productive land, and, in the majority of cases, this land has been idle for at least five years. Farmers quote inefficiently-small plots as the reason for this in few cases, casting doubt on the scope for land consolidation to solve this issue. Instead, the data are consistent with the notion of land market imperfections, which can be traced to gaps in the legal and policy framework, as well as inefficiencies in registry operations, leading to land abandonment on a large scale. To maintain the productive potential of Albania’s rural economy and, if and when needed, the ability to conduct consolidation in a cost-effective and sustainable manner, it will be critical to complement the emphasis on consolidation with an effort to address those gaps and inefficiencies on a priority basis.

This paper is a product of the Agriculture and Rural Development 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 kdeininger@worldbank.org, gcarletto@worldbank.org; sara.savastano@uniroma2.it.

_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
# **8. References**

Adamo, S. (2008) _Addressing Environmentally Induced Population Displacements: a Delicate Task_ . Background paper for Cyberseminar on Environmentally Induced Population Displacements, Population-Environment Research Network, August 2008.

Adger, W.N. (2006) Vulnerability. _Global Environmental Change_ 16: 268-281.

Adger, W.N., Agrawala, S., Mirza, M., Conde, C., O’Brien, K., Pulhin, J., Pulwarty, R., Smit, B. and Takahashi, K. (2007) Assessment of adaptation practices, options, constraints and capacity. In M. Parry, O. Canziani, J. Palutikof, P. van der Linden and C. Hanson (eds.), _Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change_ . Cambridge University Press, Cambridge and New York: 717-743.

Adger, W.N. and Barnett, J. (2005) Compensation for Climate Change Must Meet Needs. _Nature_ (Correspondence) 436(7049): 328.

Adger, W.N., Dessai, S., Goulden, M., Hulme, M., Lorenzoni, I., Nelson, D., Naess, L., Wolf, J. and Wreford, A. (2009) Are there limits to social adaptation to climate change? _Climatic Change_ : in press.

Adger, W.N., Huq, S., Brown, K., Conway, D., and Hulme, M. (2003) Adaptation to climate change in the developing world. _Progress in Development Studies_ 3(3): 179-195.

Afolayan, A, and Adelekan, I. (1998) The role of climatic variations on migration and human health in Africa. _The Environmentalist_ 18: 213-218.

Agrawal, A. (2008) _The Role of Local Institutions in Adaptation to Climate Change_ . Paper prepared for the Social Dimensions of Climate Change, Social Development Department, The World Bank, Washington DC.

Amin, S. (1995) Migrations in contemporary Africa: a retrospective view. In J.Baker and T.A. Aida (eds.), _The Migration Experience in Africa_ , Nordiska Afrikainstitutet, GOTAB, Sweden. Anderson, K. and Bows, A. (2008) Reframing the climate change challenge in light of post-2000 emissions trends. _Philosophical Transactions of the Royal Society_ 366: 3863-3882.

Anthoff, D., Nicholls, R., Tol, R. and Vafeidis, A. (2006) _Global and Regional Exposure to Large Rises in Sea-Level: a Sensitivity Analysis_ . Tyndall Centre Working Paper No. 90. Tyndall Centre for Climate Change Research, Norwich, London.

48
Or, for the periodistudied, 1962-85, market forces have played a sub-ordinated role in wage determination in manufacturing and mining. Considering the important role of government and public enterprises in manufacturing and mining, unionization with increasing militancy until 1980, the attempt<sup>to</sup> introduce incomes policy under the Eqevit government in 1978-79 followed by the public wage controls and labor market repression by the military government from 1980, and the introduction since 1969 of minimum wages, this also might cause no surprise.

Painfully aware of the low quality of Turkish labor market statistics, I feel nonetheless inclined to adopt the second interpretation. We would then for the period in question have a labor market with approximate market clearing for uneducated, unskilled labor in rural areas and high unemployment in urban areas and for educated labor generally, explained by government and union interference and interaction. Faced with the objection that real wages fell strongly in manufacturing and mining after 1978 and that unemployment does not seem to responded much, the answer is that such response, through structural change, should be expected to take considerable time and that, in fact, some labor market indicators, placement office data, do indicate a decline in excess supply of labor since 1982.

Notes to Section 4:

1. An estimated Phillips relation published by the OECD, Economic

- 70 -
<!-- Start of picture text --> Garud, R., Jain, S., & Kumaraswamy, A. (2002). Institutional entrepreneurship in the sponsorship of<br>. National Bureau of Economic<br>Gertler, M.S. (2010). Rules of the game: The place of institutions in regional economic<br>Gollin, D., Jedwab, R., & Vollrath, D. (2016). Urbanization with and without industrialization.<br>regions: Identifying routes to new path development using qualitative comparative analysis.<br>. World Bank Publications.<br>Gruber, J., Johnson, S., & Moretti, E. (2023). Place-Based Productivity and Costs in<br>Hewison, K. (2014). Considerations on inequality and politics in Thailand.<br>Hussen, M.S., & Cokgezen, M. (2022). Relationship between innovation, regional institutions and<br><!-- End of picture text -->
Theory suggests lower bank barriers in countries with more effective contractual and informational frameworks. Banks arise to overcome asymmetric information between lenders and borrowers (Diamond 1984, 1991, Ramakrishnan and Thakor 1984, Boyd and Prescott 1986), which leads to adverse selection and moral hazard problems, but the efficiency with which they are able to overcome these asymmetries, depends on the contractual and informational framework within which they operate. Specifically, more efficient systems of credit information sharing allows banks to better assess loan applicants, thus potentially reducing reliance on noninterest screening mechanisms such as minimum loan amounts and fees, while increasing the possibility to use less personal application channels such as phone or Internet and allowing for faster processing of loans. More efficient systems of contract enforcement help banks overcome problems of moral hazard and again allow them to rely less on non-interest barriers and to process loans faster. However, a more efficient contractual and information environment might also allow banks more easily to accept new deposit clients. An extensive empirical literature has shown the importance of effective contractual and informational frameworks for financial sector depth (Beck and Levine, 2005). There is empirical evidence that this relationship also holds for financial sector penetration and access to finance (Beck, Demirguc-Kunt and Martinez Peria, 2007; Beck, Demirguc-Kunt and Levine, 2005; Haselmann, Pistor and Vig, 2005; Visaria, 2006). Here we explore whether the contractual and informational frameworks have a similar importance for bank barriers. We utilize two indicators from the _Doing Business_ database (World Bank, 2006a) that measure the efficiency of credit information systems and the cost of contract enforcement relative to GDP per capita.

Our results suggest that banks in countries with more efficient systems of credit information sharing are more likely to accept deposits at multiple locations, require lower minimum balances and fewer documents to open accounts, allow for loan applications to be 23
**Table 1: Summary Statistics for Male and Female Migrants and Non‐Migrants, based on characteristics at first year of observation within each interval, Albania LSMS 2005**

|||**Wo**|**men**|||**M**|**en**||
|---|---|---|---|---|---|---|---|---|
||**1990-**|**1992 **|**2001**|**-2003**|**1990-**|**1992 **|**2001**|**-2003**|
||Migr|ants|Mig|rants|Migr|ants|Mig|rants|
||No|Yes|No|Yes|No|Yes|No|Yes|
|**Age**|22.546|25.338|25.609|23.639|22.425|23.093|25.296|23.414|
|**Wealth Index**|0.232|1.033|0.080|0.256|0.153|0.786|0.079|‐0.082|
|**No HS**|0.475|0.277|0.536|0.438|0.486|0.405|0.470|0.625|
|**At least some HS**|0.399|0.492|0.348|0.413|0.414|0.498|0.418|0.330|
|**At least some Univ.**|0.125|0.231|0.116|0.149|0.099|0.097|0.112|0.045|
|**Tirana**|0.149|0.200|0.134|0.163|0.138|0.190|0.153|0.075|
|**Coastal Urban**|0.135|0.354|0.111|0.135|0.122|0.234|0.104|0.089|
|**Coastal Rural**|0.207|0.154|0.184|0.313|0.192|0.234|0.155|0.189|
|**Central Urban**|0.125|0.169|0.106|0.096|0.121|0.138|0.102|0.059|
|**Central Rural**|0.143|0.031|0.157|0.135|0.154|0.126|0.161|0.175|
|**Mountain Urban**|0.077|0.031|0.095|0.091|0.074|0.022|0.102|0.116|
|**Mountain Rural**|0.165|0.062|0.213|0.067|0.200|0.056|0.224|0.298|
|**Male Family Network**|0.026|0.215|0.507|0.606|0.020|0.167|0.536|0.505|
|**Female Family Network**|0.005|0.077|0.214|0.404|0.007|0.033|0.165|0.193|
|**Community Male Network**|0.004|0.027|0.240|0.300|0.003|0.023|0.224|0.257|
|**Community Female Network**|0.000|0.004|0.072|0.102|0.000|0.002|0.073|0.068|
|**Illness Shock**|0.018|0.000|0.190|0.139|0.017|0.022|0.173|0.182|
|**Property Loss Shock**|0.001|0.000|0.039|0.067|0.001|0.004|0.043|0.050|
|**Job Loss Shock**|0.025|0.031|0.192|0.188|0.032|0.048|0.212|0.182|
|**Pyramid Failure Shock**|0.044|0.031|0.545|0.476|0.053|0.074|0.564|0.500|
|**Counts**|2078|65|3247|208|1870|269|1883|440|

23
apparent disagreement among corruption indicators – in levels or changes or time – is that they do not all purport to measure exactly the same concept. These differences are easily seen in the definitions in Appendix A. Most notably, perhaps, the CPIA attempts to measure not only corruption in the public sector, but also “transparency and accountability.”

# **5. What Aspects of Corruption are the Broad Indicators Measuring?**

The prevalence and conceptual variety of corruption measures in the 2005 BEEPS and WEF surveys can be exploited to identify which aspects of corruption are best captured by broader, perception-based measures - including the BEEPS question on corruption as an obstacle to doing business. Table 8 reports correlations of NIT, ICRG, CPIA, EIU, the BEEPS “obstacle” question, and the TI and WBI composite indexes with a comprehensive set of corruption measures included in the BEEPS and WEF.<sup>37</sup> The assessment criteria for NIT, ICRG and CPIA reflect roughly equal mixtures of administrative corruption and state capture, while the extremely brief criteria for EIU (“how pervasive is corruption by public officials?”) is consistent with both types. The correlations with BEEPS variables reported in Table 8 suggest, however, that all of these sources – particularly the CPIA – are measuring primarily administrative corruption. Among the various BEEPS measures, bribes in business licenses and permits and in tax collection are most strongly correlated with the broadly-defined corruption measures from other sources. None of the four broad indicators is strongly correlated with bribes

> 37 These correlations are limited to ECA countries.  The larger sample of WEF countries could be used to compute correlations with most of these indicators (all but BEEPS “obstacle” and NIT).

37
that the performance of head teachers—as school leaders—is an important determinant of school performance (see, for example, Waters, Marzano, and McNulty 2003; Robinson, Claire, Lloyd, and Rowe 2008; Mulford 2003).<sup>3</sup> Bonuses to head teachers may also be a more efficient way to raise school performance than providing bonuses to all teachers. To test whether leveraging head teachers is either sufficient or augments program impacts, the receipt and size of the bonus for a given level of school performance are randomly assigned across schools according to whether or not the teacher is the school’s head teacher.

In the first treatment variant, head teachers are eligible for “level-1” bonuses, while other teachers are not eligible for any bonuses. In the second treatment variant, all teachers (whether head teacher or not) are eligible for level-1 bonuses. In the third and last treatment variant, head teachers are eligible for higher “level-2” bonuses, while other teachers are eligible for level-1 bonuses. Level-2 bonuses are fixed to be twice as large as level-1 bonuses for a given level of school performance. The treatment variants and untreated status are randomly assigned across the evaluation sample of 600 public primary schools with essentially the lowest school-level mean 2010 PEC exam scores, located in three districts (out of Punjab’s 36 districts) with the lowest district-level mean 2010 PEC exam scores.

Using the PEC exam and ASC survey data, we evaluate program impacts on school enrollment, exam participation rates, and student exam scores in the first three years of program implementation. Evidence of significant mean impacts across the three indicators is mixed. Significant positive mean impacts are concentrated in the third year. The program increases school enrollment by, on average, 4.1 percent in the third year. Treatment variants have similarly-sized third-year mean impacts, but only the impact for the treatment variant that offers bonuses solely to head teachers is significant. The program increases exam participation rates by, on average, 3.4 percentage points (ppts) in the third year. Given a baseline mean exam participation rate of 97 percent, the mean impact maximizes the rate. Treatment variants have similarly-sized third-year mean impacts, and all of them are significant. We do not find that any of the treatment variants, and hence the program, increases student exam scores in any year.

> 3 Factors that may drive a positive relationship between head teachers and school performance include “instructional leadership” (the ability to create an environment conducive for student learning), “transformational leadership” (the ability to motivate and empower teachers), and “managerial skills” (the ability to manage the school as a typical bureaucracy) (Boyd at al 2011, Ingersoll 2011, Grissom and Loeb 2011). High-performing school systems are often found to nurture, retain, and promote leaders in their teaching workforces as a core strategy for student learning (see, for example, Darling-Hammond and Rothman 2011 and World Bank 2011).

4