rafmacalaba/data-use-mentions-extended huggingface dataset:
attacks returned even while negotiations were ongoing, encouraged by the fact that the peace process had been initiated.<sup>104</sup> This gradual approach helped to build trust in the return process, both at the community level (that the return of families would not destabilize their community) and with IDPs with perceived ISIL affiliation (that they were safe from revenge attacks). Community members such as civil society and women played a vital role as the peace process advanced, as they shared information amongst their networks about the existence of the LPA and how it was being implemented.<sup>105</sup> This helped to generate momentum and encourage additional returns; as a political representative in Zummar noted:

> 99 According to IOM’s Integrated Location Assessment 4, the rate of physical violence, threats, mistrust and returnees ‘feeling unwelcome’ decreased within 12 months, but still remained.

> 100 Context indicators such as blocked return, social cohesion and movement restriction remained similar, according to IOM’s Return Index 12.

> 101 Context indicators in Yathrib showed marked improvement, with threats between tribal groups, blocked IDP return, and returnees ‘feeling unwelcome’ reported before the LPA was signed and absent 3 months post-signature, and no concerns over revenge attacks or tribal tension reported, according to IOM’s Integrated Location Assessment 4.

> 102 Context indicators in Tal Afar such as blocked return, social cohesion and movement restriction improved according to IOM’s Return Index 11.

> 103 For governorate level mappings of actors involved in the return process, as well as specific challenges see: RWG Return Process Mapping series available at: http://iraqrecovery.org/RWG. For example, Anbar governorate mapping available at: http://iraqrecovery.org/Files/2051/2191.pdf shows the multiplicity of competing security actors, governmental actors and tribal leaders involved in the process of return.

> 104 Interview with thematic expert, Erbil, 20 May 2021.

> 105
know why the school was closed or mentioned that the school was closed because no teacher had arrived or they had all left

> 8This is also why the 2010 wave did not include urban areas. Since school-level identifiers from the 2003 survey were not preserved (for confidentiality reasons), the panel needed to be constructed at the town/village level. However, since the fraction of urban schools covered in 2003 (relative to the total number of schools in the sampled towns) was very small, it was not possible to construct a credible panel-data estimate of school quality in towns. In rural areas, this was not a concern because we typically covered all the public schools in a village (in 84.2 percent of the cases) and had a mean coverage rate of 82.7 percent of public schools in the sampled villages.

9While the exact timing of the school year is not identical across states, the typical school year runs from mid-June to mid-April. The three visits therefore spanned two academic years, with the first visit being made during January - March 2010, the second visit being made during June - August, and the third visit during August - October 2010.

> 10This was important given the widespread possession of cell phones among teachers, which would allow them to call up absent colleagues as soon as they saw external visitors in the school who were measuring teacher absence.

> 11Not all interviews could be completed. Most non-responses were at the teacher as opposed to the school level (since absent teachers could not be interviewed, whereas school data could be obtained from either the head teacher or any other senior teacher). These non-responses are unlikely to affect the analysis in this paper because the panel-data analysis will focus on aggregated data at the village level as opposed to the individual data at the teacher level.

6
channels would include electoral mechanisms in the form of free and fair elections, which are held at regular intervals in line with legal provisions, and with no _de jure_ or _de facto_ impediments to participation. Other non-electoral, or social accountability mechanisms, could include, _inter alia_ : ICT-enabled platforms<sup>107</sup> for collecting citizen feedback, satisfaction surveys, complaint and redress mechanisms, petitions, protests, and other participatory institutions for citizens.

Given the need for both information to be publicly available as well as for mechanisms to be in place for citizens to express their voice and hold service providers to account, the research will investigate a number of enabling “conditions,” which have been postulated by the earlier work of Peixoto (2013), as noted above. These including the following:

- **Publicity Condition:** A vital element necessary for supporting citizen voice is the “publicity condition,”<sup>108</sup> which provides for an enabling environment whereby “disclosed information actually reaches and resonates with its intended audiences”.<sup>109</sup> Conceptualized as such, the publicity condition would presuppose the existence of a necessary degree of political freedoms and civil rights so that the disclosed data can reach citizens—if not directly, then through third-party intermediators such as CSOs, social movements, academics, and the media. At minimum, this condition would imply, _inter alia_ : constitutional protections for freedom of expression, speech, press (and internet); relevant freedom of information or access to information legislation; media freedom, impartiality, and protections against censorship; as well as the ability for civil society organizations, academia, unions, and other civic organizations to operate free from harassment, discrimination, or persecution.

- **Political Agency Condition:** A second critical element is the presence of a “political agency condition,”<sup>110</sup> which provides the legal and institutional “mechanisms through which citizens can

> 106
and public-sector versus private-sector employment (ILO 2018).

Our experiment took place in Jendouba, one of the poorest governorates in Tunisia.<sup>3</sup> The Jendouba governorate is administratively divided into 95 Imadas (localities), 15 of which are classified as urban, and 80 of which are classified as rural. Our RCT targeted 2,000 women in the 80 rural Imadas. These women were recruited from the treatment and control groups of another randomized experiment, which evaluated the impact of a public-works program (The World Bank 2017).<sup>4</sup> Data from the 2014 census and from our baseline survey provide information about life in rural Jendouba (our data are described in Section 4.1). In 2014, only 37% of the adult population of rural Jendouba was economically active. Illiteracy rates were around 40%, and 48% of household heads had no education. In 2016, the value of daily consumption per capita at baseline was about TND 9 (less than USD 4). For most households, the main source of income is coming from casual work, agriculture, and animal farming. The labor market in rural Jendouba is highly segregated by gender. Female workers are typically working in agriculture, either as casual laborers (harvesting, weeding, sowing) or at home (Zuccotti et al. 2018). The United Nations General Assembly (2013) describes that _“In Jendouba, agriculture is the main source of income and depends primarily on female labour, particularly older women, who are ready to accept the sector’s low wages. These older rural women are predominantly casual agricultural labourers, who are collected every morning from the streets, transported, standing in the back of trucks, to the farms, and compelled to work long hours for meagre pay.”_ Women are also in charge of small-scale agriculture and livestock farming at home (Massin et al. 2016). About 18% of households reported owning land at baseline and
- Blasques, F., Gorgi, P., Koopman, S. J., and Wintenberger, O. (2018). Feasible invertibility conditions and maximum likelihood estimation for observation-driven models. _Electronic Journal of Statistics_ , 12(1):1019–1052.

- Boudjellaba, H., Dufour, J.-M., and Roy, R. (1992). Testing Causality Between Two Vectors in Multivariate Autoregressive Moving Average Models. _Journal of the American Statistical Association_ , 87(420):1082.

- Brockwell, P. J. and Davis, R. A. (2002). _Time series : theory and methods_ .

- Covey, T. and Bessler, D. A. (1992). Testing for Granger’s Full Causality. _The Review of Economics and Statistics_ , 74(1):146.

- Deschenes, O., Greenstone, M., and Shapiro, J. S. (2012). Defensive Investments and the Demand for Air Quality: Evidence from the NOx Budget Program. _NBER Working Paper No. 18267_ .

- Dufour, J.-M., Pelletier, D., and Renault, E.<sup> ́</sup> (2006). Short run and long run causality in time series: inference. _Journal of Econometrics_ , 132(2):337–362.

- Dufour, J.-M. and Renault, E. (1998). Short Run and Long Run Causality in Time Series: Theory. _Econometrica_ , 66(5):1099.

- Dufour, J.-M. and Taamouti, A. (2010). Short and long run causality measures: Theory and inference. _Journal of Econometrics_ , 154(1):42–58.

- Eichler, M. and Didelez, V. (2010). On Granger causality and the effect of interventions in time series. _Lifetime Data Analysis_ , 16(1):3–32.

-
The General Statistics Office of Vietnam recently published the 2009 Population and Housing Census and the 2010 Vietnam Household Living Standard Survey. These datasets permit a new updating of the Vietnam poverty and inequality maps. This paper presents new estimates of expenditure poverty at the province and district level of Vietnam. The estimates are based on the 15-percent sample of the 2009 Population and Housing Census in combination with the 2010 Vietnam Household Living Standard Survey. In addition, we estimate poverty at the provincial and district level for different groups including rural and urban, Kinh/Hoa and ethnic minority people. We also report small area estimates of inequality and examine in which provinces and districts the richest 15% of Vietnam are to be found. Finally, we compare the 1999 and 2009 poverty maps and analyze how evidence on local level changes can inform social policy making in Vietnam.

We simulate the impact of spatial targeting of a hypothetical budget, directed in turn to localities defined in terms of increasing spatial disaggregation to assess the gains from geographic targeting. The departure point of this analysis is a paper by Ravallion (1993) showing how spatial disaggregation to the regional level in Indonesia improves targeting, albeit to only a modest extent. In contrast, Elbers, Fujii, Lanjouw, Özler, and Yin (2007) apply an approach identical to the one employed here and find that in the case of Ecuador, Madagascar and Cambodia, when the geographic disaggregation is to a considerably finer level the gains from spatial targeting become very pronounced.

Vietnam has previously employed geographic targeting based on a fairly arbitrary list of poor communes, and is currently using a bottom-up approach to define who is poor and eligible for social assistance. Doubts about the effectiveness and transparency of both methods have been raised (Litvack, 1999; Baulch and Minot, 2002; van de Walle, 2002, Nguyen et al., 2010). Although poverty reduction in Vietnam has been impressive over the last decade, geographic targeting based on more clearly objective criteria may be needed to maintain further progress. Our
market shares be achieved within a reasonable period in mandatory lines such as MTPL and medical (and thereafter sustained), and that a minimum aggregate premium retention level of say 30% to 40% be maintained (to remove the disguised brokers). Finally, the insurance sector could be required to publish efficiency benchmarks, such as premium per employee, combined ratio and net expense ratio.

# **<mark>Box 3:  Competition – why insurance is different from banking</mark>**

<mark>There is a large amount of empirical evidence that scale economies apply to the insurance sector up to a relatively large size of operation. For non life insurance this is partly an overhead spreading issue but the credibility of claims data also increases (roughly to the square root of the number of claims) with size. Thus large non life insurers can price more accurately. Smaller insurers often follow the leaders‟ pricing structures and attempt to compete on some other basis. Unfortunately there is little credible data in new insurance markets and insurers will typically not know the real cost of their product for some years. Thus under the pressure of too many competitors it is relatively easy for insurers to under-price and undermine the financial position of the whole sector (consumers tend to be efficient at finding the cheapest insurance price). This will be exacerbated if investment returns are high and some insurers believe that they can cover underwriting losses. Under-pricing combined with under-reserving leads to prolonged disputes and settlement delays and adversely affects the development of the sector.</mark> <mark>For life insurers scale is important because of the enormous investment that is required in building and retaining marketing and distribution capacity (typically up to 70% of total costs). Thus a start up life insurer can expect to be making accounting losses for some time, even if its intrinsic value (i.e. NPV) is increasing. However the underlying processes tend to be more stable than for non life insurance and the actuarial profession usually</
The goal is to measure constraints for each sector in the country of study and compare these measurements with benchmarks of performance in countries across the world where investments have been successfully made in this same sector. This is expected to provide a revealed measure of whether a constraint is absolutely binding or not for investors in a sector. For example, if a given indicator (e.g. electricity supply) is essential for a sector (e.g. manufacturing), only countries with good electricity supply will witness successful private investment in manufacturing. For other sectors that depend less on electricity supply, such as agriculture, countries with poor electricity supply may still attract successful private sector investment. This benchmarking of constraints thus enables singling out the set of constraints for each sector where the country’s performance is below the minimum level required for successful investment. If constraints are frequently below investment level across different sectors, then this would also reveal constraints that may be binding for the entire economy.

The analysis is based on country-specific performance indicators (163 in total sourced from the World Bank TCdata360)<sup>14</sup> as sub-indicators of 12 categories representing: Demand, Factors (labor, capital), Key Inputs (infrastructures), and Institutions (macroeconomy, governance). The binding nature of the constraints measured by these indicators is then assessed by benchmarking them with a metric of third countries and sector specific score of success. In its current form, this metric is the existence of actual FDI in a sector and country<sup>15</sup> as recorded by the Financial Times' _fDi Markets_ database.

The CBT is designed to guide analysis through a large amount of information and provide an initial indication of where the biggest issues may be. However, the approach comes with limitations. First, it does not provide the user with the information on whether the variables included are associated in a statistically significant way with the success outcome of interest (i.e., attracted FDI or a revealed
data on GDP growth, CPI inflation, the lending rate, LCU/EUR exchange rate change, and non-performing loans as a proportion of total loans (NPLs). We work with fourth differences of the variables, i.e., four-quarter or year-on-year GDP growth, CPI inflation etc., measured in percentages.

**Table 3:** TTC, Baseline PIT and Stress Scenarios.

|Macroeconomic Scenarios|TTC||Fut|ure (_t_+1)||
|---|---|---|---|---|---|
|||PIT|Stress VAR|Stress Int.|Pr(Stress Int.)|
|NPL ratio (%)|10.1%|10.1%|12.0%|22.9%|_NA_|
|GDP growth (% change)|3.2%|0.5%|_−_6.9%|_−_6.3%|86.7%|
|Infation (% change)|2.8%|2.4%|11.7%|26.5%|99.8%|
|Real interest rate (%)|9.4%|9.3%|10.0%|19.0%|100.0%|
|Exchange rate (LCU/EUR) (% change)|0.0%|0.0%|0.0%|_−_31.5%|99.7%|

**Notes:** A negative value ( _−_ ) in the (nominal) exchange rate denotes a depreciation of the Local currency unit (LCU) relative to the EUR.

The TTC values are the long-run equilibrium values of the four macroeconomic variables of interest. We compute these equilibrium values as simple arithmetic averages us- _−_ ing quarterly data over the period from 1996:
ences remains debated (Haaland and Roth 2020, Williamson 2020). Recent behavioral studies also suggest that perspective-taking interventions may influence native attitudes toward migrants. Simonovits et al. (2018) show that online interventions can reduce ethnic prejudice, while Adida et al. (2018), Williamson et al. (2021), and Chatruc and Rozo (2024) find that empathy-based interventions can increase support for migrants, albeit with short-term effects. Our study contributes to this literature by evaluating how information provision interventions affect native voting behavior, social capital, and attitudes toward migrants in the context of a large-scale regularization program.

# **II CONTEXT: THE PEP PROGRAM**

By mid-2022, more than 5.6 million Venezuelans had fled the humanitarian crisis in their country. Approximately 2.5 million of them had settled in Colombia, currently the primary recipient of Venezuelan migrants (UNHCR 2023). This number represents a shock equivalent to about five percent of Colombia’s total population.<sup>10</sup> Despite the size of the migration flows, the Colombian government granted these migrants free mobility and opportunities to regularize their status. One of the largest initiatives was the PEP program in 2018.

_The RAMV census:_ between April and June of 2018, the Colombian government undertook a countrywide survey to count the number of irregular (undocumented) migrants living in its territory. It was called the RAMV, _Registro Administrativo de Migrantes Venezolanos_ . Colombian authorities administered the survey at 1,109 different stations in 441 of the 1,122 municipalities. The registration points were located in border municipalities, in municipalities with a large population of Venezuelan migrants, and in municipalities where local authorities requested them. In order to register, migrants had to go to the registration point with proof of Venezuelan citizenship through official identification documentation. Registration was voluntary and was only advertised as a statistic exercise.

10Compared to the Colombian population, Venezuelan migrants are younger, more educated, and have lower employment rates (see Table A.1
Davidson R., Adam Wagstaff, and Abdo S. Yazbeck. 2005. _Reaching the Poor with Health, Nutrition and Population Services_ . The World Bank, Washington DC.

- Halvorsen, Robert and Raymond Palmquist. 1980. “The Interpretation of Dummy Variables in Semilogarithmic Equations.” _The American Economic Review_ . 70(3): 474-475.

- Obermeyer Ziad, Julie Knoll Rajaratnam, Chang H. Park, Emmanuela Gakidou, Margaret C. Hogan, Alan D. Lopez, and Christopher J.L. Murray. 2010. “Measuring Adult Mortality Using Sibling Survival: A New Analytical Method and New Results for 44 Countries, 1974-2006.” PLoS Medicine, 7(4): e1000260.

- Preston, Samuel H. 1975. “The Changing Relation Between Mortality and Level of Economic Development.” Population Studies. July, 29:2, pp. 231-48.

- Preston, Samuel H. 1980. “Causes and Consequences of Mortality Declines in Less Developed Countries during the 20th Century” in Population and Economic Change in Developing Countries. R. A. Easterlin, ed. Chicago: University of Chicago Press.

- Timaeus Ian and, Jasseh Momodou. 2004. “Adult Mortality in Sub-Saharan Africa: Evidence from Demographic and Health Surveys.” _Demography_ , 41(4): 757-772.

- Trussel, James and German Rodriguez. 1990. “A Note on the Sisterhood Estimator of Maternal Mortality.” _Studies in Family Planning_ . 21(6):344-46.

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Gaps between private and public rental are reduced when considering energy costs. In Russia, for example, heating cost-to-income ratios for public tenants (at 4.6 percent) are significantly higher than for private tenants (3.8 percent). The effect is similarly pronounced in Romania. It must be left unresolved at this stage, whether private rental tenants simply spend less on heating, or whether their units are more energy efficient. Statistical errors typical for small sample size are a possibility, too. Additionally, rental contracts may include utilities within rental amounts. Armenia and Serbia - the two countries with the highest poverty evidence among the studied countries - show the highest absolute rent-to-income ratios for private rental units.

Relative to income levels, private rental housing tenure throughout the region is considerably less affordable than “privatized” ownership, which gives a clue of the size of the windfall - at least in current cash payment terms - that sitting tenants were given through the privatization. However, private rental is still relatively affordable compared with urban rent-to-income or housing cost-to-income burdens in Western Europe, where effort ratios of 15–20 percent (net of energy and heating) are typically found. Public rental housing is generally very inexpensive relative to income—with the exception of Armenia, for the reason discussed above - and most affordable in Romania and Russia.

# **_Affordability and Profitability of Renting_**

The findings on affordability seem to be at variance with popular notions of the high profitability of informal renting (Box 1). The perception of highly profitable private rental entrepreneurship in the region is biased toward cases of metropolitan cities with extreme demand conditions. Such perception problems are exacerbated by the stories of tenants in new municipal apartments who can quickly privatize, turn around, and sublet their units at market rents.

Considering the survey data that reflect broader urban area definitions and landlord categories, and contrasting current rent levels with investment return requirements, the picture of high profitability softens considerably. Lithuania may be more characteristic for the rental profitability trend in
Step 2. It is necessary to specify the period in the program. To do so, the first line of the program must be modified:

# WORKFILE a:\LITCYCLES M 1993:1 1999:12

With this command the EViews workfile _Litcycles_ is created on drive a:\ (this drive path can be modified), from January 1993 to December 1999. As the file is updated the last date in the command must be changed.

Step 3. Another item to be specified is the location of the file that contains the original data set (in this case LITUDATA.XLS). In the command below the default location is drive a:\

# READ(E,a2) a:\LITUDATA.XLS 10

The number 10 at the end of the command denotes the number of series in the LITUDATA database. This number is modified only in case one variable is added (deleted).

Step 4. Once the basic date adjustments have been completed, the program can be run by hitting the "Run" button in the choice menu at the top of the screen. The software will open a "Run Program" window where the operator must specify the maximum number of errors to be tolerated before halting (see Figure 1.3). This option can be arbitrarily set at 500, since Eviews treats missing values as an error and warning messages appear as the program runs.<sup>13</sup>

> 13 - The only error message that should appear is of the type "FP Exception  possible illegal operation on NA - Missing data generated in...". Any other type of error message indicates real problems with the program.

9