rafmacalaba/datause-encoder-data huggingface dataset:
of 2.4. The public system continued to expand slowly but with a growth rate below that of the population.

The period of abject relative decline of the public school system corresponds closely with the reign of the dictator François “Papa Doc” Duvalier, who came to power in 1957. After his son Jean-Claude “Baby Doc” Duvalier took over in 1971, the public system continued to stagnate, but the growth rate of non-public schools accelerated, in part due to a rule instituted by Baby Doc that religious missionaries were required to build an affiliated school with any new church.<sup>8</sup> The expansion of private schools increased further in the late 1980s, after the end of the repressive Duvalier regime in 1986. The years 1994-1999 were a peak period for school construction. This coincides with the first democratic transition, a period of relative political stability, and a national campaign to promote the importance of education. The period was also marked by large investments in social sectors from external aid funds.

As of the 2003 school census, 92 percent of Haitian schools were private, accounting for more than 80 percent of school enrollment, as shown in Table 1. Of the 15,223 schools in the country, 33 percent were in urban areas. Fifty-four percent of schools were “multigrade,” i.e. had more than one grade in the same classroom. Although this policy has emerged out of necessity due to the limited number of classrooms and teachers, it may contribute to poor student performance, due to the low time of attention that every teacher has to give to the students. The School Census also shows that in 2003 only 8 percent of private schools functioned with a license, a government credential which certifies that minimum facility and quality standards are met. The difference in licensing between urban and rural areas reinforces the geographical differences in schooling: 17 percent of the schools located in urban areas are licensed, compared to only 3 percent of rural schools. This may also be a reflection of the Ministry of Education’s weak presence outside of Haiti’s urban areas.

To understand the broad evolution of the Haitian education system over time, we examine the schooling attainment levels of Haitians from three birth cohorts: 1950-54, 1965-69, and 1980-84. Students in the first cohort were of primary school age in the late 1950s and early 1960s, a period marked by Papa Doc’s arrival. The second cohort reached primary age in the first years of rule of Baby Doc. The third cohort entered primary school in the years after Baby Doc was overthrown by a popular uprising in 1986. The period 1994 to 2000 was characterized by

> 8 Fass (1988) provides a history of the growth of schools in Haiti.

5
where _LGDi_<sup>_TTC_</sup> is the through-the-cycle value of LGDs taken from the QIS5 study, _PDi_<sup>S</sup> , _j_ are the values computed in (9), and the parameter _ρLGD_ , _PD_ controls the extent of the correlation between LGDs and PDs. Note that there exists considerable evidence in the literature to suggest that _ρLGD_ , _PD_ increases during crisis times, that is, under the Stress scenario (see, for instance, Altman _et al._ , 2002). We therefore suggest to calibrate the _ρLGD_ , _PD_ parameter in the 10% _−_ 20% range for the non-crisis TTC and PIT scenarios, and increase the _ρLGD_ , _PD_ parameter to the 30% _−_ 50% range during crisis times (under the Stress scenario). The latter range corresponds to the preliminary results found in the study by Moody’s (2010) for the global financial crisis period.

Notice from (10) above, that because the _PDi_<sup>S</sup> , _j_<sup>are bounded by [</sup><sup>_PD_</sup> _i_<sup>S,</sup><sup>_PD_</sup> _i_<sup>S+</sup><sup>_κ_], where</sup> _κ PD_<sup>S</sup><sup>_PD_S</sup><sup>_PD_S</sup> will be greater than 0, the term ( _i_ , _j_<sup>/</sup><sup>_PD_</sup> _i_<sup>S</sup><sup>_−_1) will be 0 if</sup> _i_ , _j_<sup>=</sup> _i_<sup>and it will be</sup> equal to _κ_ / _PDi_<sup>Sif</sup><sup>_PD_</sup> _i_<sup>S</sup> , _j_<sup>=</sup><sup>_PD_</sup> _i_<sup>S+</sup><sup>_κ_.This means that the relation in (10) gives bounds on</sup> the effective _LGDi_<sup>S</sup> , _j_<sup>of [</sup><sup>_LGD_</sup> _i_<sup>S,</sup><sup>_LGD_</sup> _i_<sup>S</sup><sup>_× ρ_</sup> _LGD_ , _PD_<sup>_× κ_/</sup><sup>_PD_</sup> _i_<sup>S]. Since</sup><sup>_κ_enters the upper bound</sup> as a product term, it is again the case that if _κ_ = 0, the LGDs for each bank will be set to the aggregate _LGD_<sup>S</sup> for that asset class.

# **5. Exposures at Default**

We follow the general approach in the literature (see, for example, Bluhm, Overbeck and Wagner, 2003) and calculate the exposures at default (EADs) for the purpose of credit risk modelling as a weighted sum of _on-balance_ sheet and _off-balance_ sheet credit risk exposures. Off-balance sheet exposures include future drawdowns such as loan commitments, pre36
Van Hespen, R., Hu, Z., Peng, Y., Borsje, B.W., Kleinhans, M., Ysebaert, T., Bouma, T.J. (2021). Analysis of coastal storm damage resistance in successional mangrove species. Limnology and Oceanography 66.

Van Rooijen, A. A., McCall, R. T., van Thiel de Vries, J. S. M., van Dongeren, A. R., Reniers, A. J. H. M., Roelvink, J. A. (2016), Modeling the effect of wave-vegetation interaction on wave setup, J. Geophys. Res. Oceans, 121, 4341–4359, doi:10.1002/ 2015JC011392.

Van Wesenbeeck, B.K., Wolters, G., Antolínez, J.A., Kalloe, S.A., Hofland, B., de Boer, W.P, Çete, C., Bouma, T.J. (2021). Wave attenuation through forests under extreme conditions. Scientific Reports.

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# **1 Introduction**

Intimate partner violence (IPV) is a global public health epidemic; nearly one in three women will experience physical or sexual IPV in her lifetime (World Health Organization, 2021). In Tanzania, 32% of ever-partnered 15-19 year olds report ever experiencing IPV and 25% report experiencing IPV in the last 12 months (World Health Organization, 2021). IPV is also associated with other risky sexual behavior, such as low rates of modern contraceptive use and multiple partnerships (Melesse et al., 2020; Nkata, Teixeira and Barros, 2019; DHS, 2016). In addition to the direct negative effects of violence on women’s physical, mental, sexual, and reproductive health, social norms that perpetuate IPV and the resulting lack of bargaining power with sexual partners affect female ability to make safe choices around sexual and reproductive health (SRH).

We implement a randomized controlled trial (RCT) with female and male adolescents in Tanzania to change these power dynamics around adolescent relationships with the goal of improving SRH outcomes related to violence and risky sexual behaviors.<sup>1</sup> Our interventions build on an ongoing adolescent empowerment program (Empowerment and Livelihoods for Adolescents (ELA) clubs) delivered to females through a network of 149 clubs in three regions of Tanzania. For females, we randomize invitations to participate in a goal setting activity aimed at motivating the adoption of safe behaviors to improve their SRH outcomes. Males from a random subset of communities are invited to participate in an intervention using an innovative sport-based pedagogy that employs soccer-specific activities, metaphors, and language to educate and inspire them. The curriculum focuses on reshaping males’ attitudes and behaviors around masculinity, gender-based violence, and sexual relationships. We collect baseline data on all female ELA participants aged 10-24 and their boyfriends and resurvey them two years later.

Intent-to-treat (ITT) estimates show that female experience of IPV decreases by 0.229 of a standard deviation as a result of the males soccer ( _Boys_ ) intervention and by 0.298 of a standard deviation as a result of the female goal setting ( _Goal_ ) intervention. Impacts are

> 1This research received ethical clearance in country through the Tanzania National Institute for Medical Research (NIMR) (protocol NIMR/HQ/R.8a/Vol. IX/2247) and from the University of California Los Angeles Institutional Review Board (protocol # 16-000125).

3
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26
future economic and political stability. Recent episodes of civil violence – including the civil strife in 2006 – have been linked to high levels of unemployment and lack of skills among young males (Muggah et al. 2010, Scambary 2006). This may well have resulted from lost education opportunities among boys during the 25 years of conflict, although we would need data beyond 2007 to test this hypothesis in more detail.

# **5.3. Robustness checks**

We have performed several robustness checks in order to address some important issues that may affect our estimates above. The main issues we address are the possible exposure of the sample surveyed in 2007 to the civil violence that erupted in Timor Leste in 2006, and impending selection biases in the 2001 and 2007 results due to non-random migration patterns.

# **_5.3.1. Civil war exposure in 2006_**

One important concern with the results discussed in the previous section is whether some estimates may be capturing the civil violence that took place in Dili during the implementation of the TLSS 2007 (see section 4). In 2006, Timor Leste experienced large internal civil strife as a result of fighting between different factions in the independence forces. The violence in 2006 resulted in 37 killings, 2,000 severely damaged houses, 3,000 completely destroyed houses, and 150,000 displaced people (against 400,000 in 1999) (Muggah et al. 2010, Scambary 2006). Most displaced people were located around Dili (65 IDP camps were put in place), and were still displaced in 2007. These events took place at the time of the implementation of the TLSS 2007 in March 2006. In order to minimize exposure to the violence, and due to the security situation, the TLSS 2007 was interrupted and resumed in January 2007. All households interviewed previously were reinterviewed. It is, however, still possible that some biases may remain. In particular, it is possible that some of the results we obtain are not due to exposure to the 1999 violence but to exposure to the civil upheaval in 2006.

In order to control for this potential exposure to the violence in 2006, we explore a variable in the 2007 dataset that captures whether an individual has been absent from home in the past 12 months for security reasons.<sup>27</sup> Our calculations show that individuals who have been absent from home for security reasons in 2006 are all residing in Dili. Therefore, we believe that this dummy reliably captures quite well the level of exposure to the 2006 violence.

> 27 Those that declare being absent from home for security reason represents the 2.7 % of our sample.

30
|**Tabl**<br>**Data Provider**<br>**Description**<br>**Website**<br>**Data Source**<br>|**e A25: International Budget**<br>International Budget Project<br>Nongovernmental organization<br>civil society capacity to influenc<br>www.internationalbudget.org<br>Open Budget Index<br>|**Proj**<br>based<br>e gove|**ect O**<br>in Wa<br>rnmen|**pen B**<br>shingto<br>t budg|**udget**<br>n, Un<br>et proc|**Inde**<br>ited S<br>esses|**x (OB**<br>tates, d<br>.|**I)**<br>evoted|to de|veloping|
|---|---|---|---|---|---|---|---|---|---|---|
|**Type**|Expert assessment||||||||||
|**Respondents**|Local experts recruited by the<br>review|Inter|nationa|l Budg|et Pr|oject|subject|to an|onymo|us peer|
|**Frequency**<br>**Coverage**<br>**Public Access**<br>**Description**|Every two years<br>Global country sample<br>Yes<br>The Open Budget Index is base<br>various dimensions of the availa<br>documents. Note that the 2006<br>2008 index refers to conditions i|d on a<br>bility,<br>index<br>n 2008|questi<br>timeli<br>refer<br>.|onnair<br>ness an<br>s to dat|e with<br>d qua<br>a refl|122<br>lity o<br>ecting|multipl<br>f centr<br>condit|e choic<br>al gove<br>ions in|e ques<br>rnmen<br>2005|tions on<br>t budget<br>and the|
|**Voice and Accountability**|2008|2007|2006|2005|2004|2003|2002|2000|1998|1996|
|Open Budget Initiative|X|X|X|X|..|..|..|..|..|..|
|**Political Stability and Abse**<br>NA|**nce of Violence**<br>..|..|..|..|..|..|..|..|..|..|
|**Government Effectiveness**<br>NA|..|..|..|..|..|..|..|..|..|..|
|**Regulatory Quality**|||||||||||
|NA|..|..|..|..|..|..|..|..|..|..|
|**Rule of Law**|||||||||||
|NA|..|..|..|..|..|..|..|..|..|..|
|**Control of Corruption**|||||||||||
|NA|..|..|..|..|..|..|..|..|..|..|
|**Country Coverage**<br>|**85**<br>|**59**<br>|**59**<br>|**59**<br>|**..**|**..**|**..**|**..**|**..**|**..**|
|**Year of publication**|**2008**|**2006**|**2006**|**2006**|**..**|**..**|**..**|**..**|**..**|**..**|

64
may be a more immediate priority than land consolidation. This is particularly so as consolidation efforts -which may be desirable in specific situations or needed in the future- can be carried out cost-effectively and sustainably only if they complement existing markets rather than trying to substitute for them.

The paper is structured as follows. Section two places Albania in a regional context by describing the nature and challenges of its transition and by using LSMS data to illustrate salient characteristics of its rural economy. Section three introduces the key questions to be explored by discussing relevant methodologies and evidence from the literature. Section four provides evidence on levels of technical efficiency in the agricultural sector and underlying determinants, the extent, nature, and proximate causes of cropland not being used productively, and the extent to which markets for rental and sale help to transfer land to more productive producers. Section five concludes by drawing out relevant policy implications.

# **2. Data and context**

To place Albania in regional and global context, we review the circumstances that led to one of the most radical land redistributions in Eastern Europe‟s post-communist transformation and characterize the emerging farm structure and the challenges associated with it. Data from the 2005 LSMS then help to illustrate inter-regional differences in farm structure and productivity, income sources, operation of factor markets, and migration as well as plot fragmentation.

# **2.1 Albanian history of collectivization and reform**

At independence in 1912, Albania inherited a _latifundia_ system that had land ownership concentrated in few hands. The 1945 Agrarian Law eliminated private property and transferred land use rights to small farmers who were then organized in production cooperatives which often formed the basis for state farms. Private ownership of land, even for house plots, was eliminated with the nationalization of all land in 1976 (Cungu and Swinnen 1999). Agricultural policy thereafter focused on achieving food selfsufficiency. However, productivity declined, resulting in food shortages and a severe drop in welfare. In the late 1980s, reforms under the “new economic mechanism” aimed to address this via (i) distribution of house plots in private ownership; (ii) decentralization and liberalization of enterprise management; and (iii) opening of private marketing channels for most agricultural produce. A failure of these measures to prevent a sharp drop in food production made Albania dependent on food aid and resulted in stagnation, political instability, and social disorder that contributed to radical changes including the adoption of private property rights in 1991.

Land privatization initially entailed giving rights to workers of former production cooperatives and state farms under the guidance of district and village land commissions. Reforms were implemented rapidly 4
3 only some are targeted with vote-buying – and fewer groups are targeted with vote-buying than would be targeted with post-electoral transfers in settings with greater political credibility.

These conclusions have implications for the welfare and distributional consequences of votebuying. The analysis supports the conjecture in Kitschelt (2000) that groups targeted with vote-buying would not, in fact, receive government transfers in the event that vote-buying were banned. They are, therefore, net losers if prohibitions on vote-buying are enforced. On the other hand, all others, including groups that are targeted neither for post- nor pre-electoral transfers, unambiguously gain from the elimination of vote-buying.

A different concern among policy makers and scholars is the association of corruption and rentseeking with vote-buying. Keefer and Vlaicu (2008) show that political credibility drives an association between rent-seeking and post-electoral transfers: less credible politicians confront fewer electoral constraints on rent-seeking and greater electoral imperatives to rely on targeted transfers. In the analysis here, we show that the same logic extends to a dynamic setting that allows for pre-electoral transfers (vote-buying).

The next section presents stylized facts regarding vote-buying and reviews previous research analyzing the phenomenon. We then present the model and close with a discussion of different types of evidence in the literature that supports the plausibility of the model’s predictions.

# **How does past research explain variations in political reliance on vote-buying?**

In countries where vote-buying is pervasive, pre-electoral transfers to voters are substantial. Across the 17 countries surveyed in the 2005-06 wave of the Afrobarometer survey, 19 percent of more than 20,000 respondents reported that they had been offered a gift in the last election. Brusco et al. (2004) surveyed nearly 2,000 respondents in three Argentine provinces three months after the October 2001 elections. Forty-four percent of respondents said that parties had distributed food, clothing and other items to homes in their neighborhoods; 7 percent of respondents acknowledged receiving
their neighbors. _5_ Such pressure is, admittedly, difficult to measure. Here we employ the percentage of countries within a region that adopted explicit insurance as a crude proxy for pressure."<sup>6</sup> One would expect a positive relationship between these "neighbor" effects and explicit deposit insurance.

The regression analysis that follows controls simultaneously for banking instability, and the other aspects of deposit insurance decisions described above to better isolate the effect of each component on financial depth. The results in Table 5 indicate that the probability of adopting explicit insurance increases by 25-30%17 for countries that experienced systemic banking crises within the preceding five years. _1_<sup>_8_</sup> However, in only one specification (model 3) does the crisis coefficient achieve significance at the . 10 level.

**N** eighbor effects in the U.S. have been studied by Case et al. (1989). They find that a state's level of per capita income is affected by the expenditure levels of its neighbors. In specifying neighborliness they note that. "various measures of distance between neighbors vield similar results, as long as the measures are powerful enough to select a small number of states as a given state's neighbors." (p. 19). The argue that "copycatting" is not confined to subfederal jurisdictions but also may be practiced by national governments.

- 16 In the models of deposit insurance choice that follow. the country in question (i.e., the one making the choice) is excluded from the regional pressure calculation.

- **17** All percentage change estimates were calculated at the means of the explanatory variables in Table 5.

- **_18_** The bank crisis dummy variable used here comes from Demirguc-Kunt and Detragiache (1997). They define "full-fledged" crises as those where at least one of the following four conditions held: (1) the ratio of non-performing assets to total assets in the banking system exceeded 10%; (2) the cost of the rescue operation was at least 2% of GDP; (3) the episode involved a large scale nationalization of banks; (4) extensive bank runs took place or emergency measures such as deposit freezes, prolonged bank holidays, or generalized deposit guarantees were enacted by the goverrnent. To identify crises that satisfy these criteria they relied on four recent studies: Caprio and Klingebiel (1996), Kaminsky and Rhinehart (1996), Lindgren _et al._ (1996), and Sheng (1995). Based on the crisis dates reported in Demirguc-Kunt and Detragiache (1997) and Caprio and Klingebiel (1996), 1 constructed a dummy variable equal to one if a crisis had occurred during any part of the five years leading up to the adoption of explicit deposit insurance. For countries that retained implicit schemes, the crisis dummy equaled one if a crisis occurred from 1989-1993. Because the papers used to construct the crisis dummy focus on 1980-1995, countries that adopted explicit deposit insurance prior to 1980 are dropped from the regression analysis in Table 5.

14