rafmacalaba/datause-encoder-data huggingface dataset:
Compared to the baseline year of 2001, residents were more fearful of crime by 0.17 sd. These fears are not necessarily unfounded, as we find some weak evidence of changes in levels of violence in their parishes. Compared to 2001, a 1-SD increase in refugee presence in 2011 is associated with a 1.26 percentage point increase in likelihood of a violent event, and in 2016, a 1.11 percentage point increase. These findings are in line with our predictions for Uganda. As in Global North contexts, we recognize that out-group members can elicit fears and insecurity. It is unclear from the ACLED dataset, however, whether these violent events involve refugees. It is also possible that ACLED underreports violent incidences that are not reported by the media. Recent scholarship on the relationship between refugees and violent conflict finds that hosting generally has null effects on conflict (Zhou and Shaver, 2021); when conflicts do occur, refugees tend to be the victims (Savun and Gineste, 2019). Nevertheless, by 2020, like with Afrobarometer respondents reporting feeling more safe, these fears of crime reverse with a negative effect of -0.13 sd.

As we theorize, the positive externalities for local communities (in the form of improved service delivery), generated by Uganda’s integrative approach to hosting refugees, generally balance out these fears, which do not generate a backlash against refugees and inclusive migration policies. Improving basic services is of the utmost importance to host communities in developing contexts regardless of who is providing them (Sacks, 2012).

All the results reported here use our main specification of the Nearest + 20km exposure measure (which takes into account not only the nearest settlements, but also all settlements within 20km) and the subset of parishes that are within 150km of a settlement. In SI Section S4, we present the regression tables for all of the results shown in Figures 5 and 6, along with their robustness specifications. These tables display the effects across all three measures of exposure (Nearest, Nearest + 20km, Nearest + 50km) and across the various radius cutoffs for parishes (within 100km, 150km, 200km, and all parishes). These results demonstrate that our main results are robust across specifications. In additional robustness checks, we also conduct formal sensitivity analyses and address concerns about multiple hypothesis testing by adjusting for the false discovery rate and showing Benjamini-Hochberg-adjusted p-values in SI Sections S5 and S6.

An alternative explanation is that our results are driven by a change in the composition of host citizens. It is possible that the positive effects we observe are due to the internal migration of Ugandans: those who move to refugee settlement areas may be positively disposed toward refugees, while those who leave are more likely to be anti-migrants. While there is no data to test 23
The paper is organized as follows: The next section describes the program. Sections 3 and 4 discuss data used in our analysis and our estimation method, respectively. Section 5 discloses the average treatment effects. The empirical results are summarized in Section 6. Section 7 concludes.

# **2. Program Background**

The Third Elementary Education Project (TEEP) was implemented from 2000 to 2006 by the Philippine Department of Education in all public primary and elementary schools<sup>4</sup> in the 23 provinces<sup>5</sup> identified as the most socially depressed in the Social Reform Agenda.<sup>6</sup> The total project cost was US$221.16 million ($91.07 million from JBIC and $82.84 million from World Bank, $47.25 million from the Philippine government).<sup>7</sup> The unique feature of TEEP is a combination of investments in school facility and education materials and school governance reform. Not only were school facilities and textbook supply improved, but the decisionmaking process was also decentralized to the school and community levels. TEEP introduced a package of investments to schools in the selected 23 provinces. Specifically,

> 4 Primary schools cover grades 1 to 4, while elementary schools cover grades 1 to 6.

> 5 The program covered both primary (grades 1–4) and elementary (grades 1–6) schools. This paper analyzes the impacts on only elementary schools. However, converting primary schools to elementary schools by extending enrollment up to grade 6 was also an important part of the TEEP program. Students who complete primary schools are likely to attend elementary schools in grades 5 and 6, which changes the student body of those schools between grades 1–4 and grades 5 and 6.

> 6 The Ramos administration, along with their medium term development plan, called _Philippines 2000_ , identified reforms as the key to bridging social gaps and alleviating poverty. The objective of enhancing development through social reforms led to the formulation of the blueprint for social development in the Philippines, the Social Reform Agenda (SRA), marked as the first instance of social reforms in the history of the Philippines (Ramos 1995). As a result of the initial success of the SRA, the Congress of the Philippines in 1998 passed Republic Act 8425, widely known as the Social Reform and Poverty Alleviation Act (Republic of the Philippines, Congress, 1998). The law institutionalized the poverty alleviation program and a host of grassroots development strategies.

> 7 See World Bank (2007, annex 1).

5
<!-- Start of picture text --> ‘total nr. of EU countries adopting RIA (left axis) — — total nr. of RIAsin EU (weighted and upscaled, right axis)<br>25 6,000<br>.<br>7<br>20 eee<br>a =—----<br>15 -7 - o 4,000<br>-<br>10 o o a 2,000<br>5<br>1D<br>2006 2007 2008 2009 2010 2011 2012*<br><!-- End of picture text --> <!-- Start of picture text --> 015<br>®S<br>B 014<br>S<br>3<br>3<br>=Fl 013<br>3=<br>z<br>go<br>2<br>a<br>one Absence of Impact Assessment<br>Presence of Impact Assessment<br>0 20 40 60 80<br>Analysis time (in months)<br><!-- End of picture text -->
and AOWs, the economic model was used first to predict the demand for physicians. Systematic ratios were then applied to predicted physician densities to estimate the number of nurses/midwives and AOWs.

The economic model specifies physician density (dependent variable) as a function of GDP, OOP and size of the population over 65 years. Given data availability constraints, we include country fixed effects to account for time‐invariant unobservable heterogeneity across countries (i.e. differences in baseline characteristics) that cannot otherwise be controlled. To further account for potential endogeneity, all independent variables were lagged to ensure the direction of causality. Lags for up to five years for each predictor were included to allow time for such factors to work through the economy and affect the labor market. A stepwise approach was used to select the specific combination of year lags that maximized the predictive power of each variable. Lagged variables that achieved a minimum one percent level of significance after repeated iteration were kept within the model, resulting in the following optimal model:

- (Eq 1) ln( _physicians per 1000 populationit_ ) = β0 + β1*ln( _GDP per capitait‐1_ ) + β2*ln( _GDP per capitait‐4_ ) + β3*ln( _GDP per capitait‐5_ ) +β4*ln( _OOPPCit‐2_ ) + _β_ 5*ln( _Pop65it‐3_ ) + _μi_ + _ξit_

where _μc_ represents a vector of country fixed effects, _ξct_ is the disturbance term, and β coefficients are unknown parameters to be estimated from the model. Quadratic terms for income and health spending indicators to additionally account for nonlinearities were investigated but ultimately excluded due to multicollinearity.

Equation 1 was fit through a generalized linear model (GLM) using a maximum likelihood estimator. GLM was chosen over OLS as a more flexible estimator; sensitivity tests with OLS produced similar results. Estimated coefficients from the regression model were then applied to the future values of each predictor variable to compute the future predicted physician density.

Alternative model specifications were explored, which included different ways in which input parameters could be calculated (e.g. percentage of the population aged 65+, out‐of‐pocket health spending as a percentage of total health expenditures). To select the appropriate model, the data were split into an initializing data set (data years 1995‐2004) and an attesting data set (data years 2005‐2013) with which to assess the precision of predicted values resulting from different specifications. The model in Equation 1 yielded predictions with the lowest mean errors.

We conducted two additional sensitivity analyses of the projections of physician demand resulting from the optimal demand model chosen to alternative input parameters. First, we assess the stability of the predictions to alternative estimated future values of GDP per capita. We use alternative estimated real GDP per capita (US$2010) from the Economic Research Service (ERS) International Macroeconomic Data Set published by the United States ‐ Department of Agriculture (USDA), available at <u>http://www.ers.usda.gov/data</u> 6
<!-- Start of picture text --> 1438 - 14,000<br>GS 15,004 - 30,000<br>HE 30.001 25.001 -25.000-e000025.000 -e000025.000<br>; HE 60.001 90.000<br>a. ices HM 20.001. 44<br>| yo [ aa<br><!-- End of picture text -->

<!-- Start of picture text --> 1438 - 14,000<br>GS 15,004 - 30,000<br>HE 30.001 25.001 -25.000-e000025.000<br>| > ; HE 60.001 90.000<br>[ = i PL a. ices HM 20.001. 44<br>| yo [ aa<br>a a | a<br><!-- End of picture text -->
different groups of customers, use different technologies, and/or have different effects on competition (see DeYoung, Hunter, and Udell 2004 for a survey).

Turning to the dynamic performance effects associated with domestic M&As, the empirical evidence on U.S. bank M&As using data from the 1980s generally finds little or no cost efficiency improvement after consolidation on average, although some M&As yielded substantial gains and others yielded substantial losses (e.g., Berger and Humphrey 1992). The studies using U.S. data from the early 1990s are mixed, with some finding cost efficiency gains, and others finding little cost efficiency improvement (e.g., Rhoades 1998). Studies of European M&As also give mixed cost efficiency findings (e.g., Vander Vennet 1996).

Profit efficiency studies of U.S. bank M&As from the 1980s and early 1990s find that M&As improved profit efficiency, and that this improvement can be linked to portfolio shifts that generated higher revenues due to improved risk-expected return frontiers (e.g., Akhavein, Berger, and Humphrey 1997, Hughes, Lang, Mester, and Moon 1999). U.S. banks involved in M&As may also have improved the quality of their outputs in the 1990s in ways that increased costs, but still improved profit productivity by increasing revenues more than costs (Berger and Mester 2003). Other studies also find that large U.S. banks shift their portfolios away from SME lending after M&As, although other local banks tend to react by increasing their SME credit supplies (e.g., Berger, Saunders, Scalise, and Udell 1998).

# **2.2. Foreign ownership and acquisitions**

Studies of the effects of foreign governance typically include static efficiency differences between foreign-owned and domestically-owned private institutions. Foreign-owned banks are usually part of large banking organizations, and so generally face the same scale economies and diseconomies as large, domestically-owned institutions. They may also have advantages in serving multinational customers by setting up offices in countries where their home-country customers have foreign affiliates (e.g., Goldberg and Saunders 1981). Foreign-owned banks may also have better access to capital markets, superior ability to diversify risks, and the ability to offer some services to multinational clients not easily provided by domestically-owned banks. In developing nations, foreign-owned institutions from developed nations may also have access to superior technologies, particularly information technologies for collecting and assessing “hard” quantitative information. However, foreign-owned banks may also have some disadvantages due to problems in managing from a distance, coping with multiple economic/regulatory environments, and accessing “soft” qualitative information about local 4
**Figure 2. Product Market Regulation among OECD countries, a comparison between 1998 and 2003**

<!-- Start of picture text --> 4<br>3.5<br>3<br>2.5<br>2<br>1.5<br>1<br>0.5<br>0<br>1998 2003<br>United KingdomAustraliaIcelandDenmarkU.S.New ZealandIrelandCanadaSwedenLuxembourgJapanFinlandAustriaNetherlandsBelgiumSlovak Rep.GermanyNorwayKoreaPortugalSpainCzech Rep.FranceSwitzerlandGreeceHungaryItalyMexicoTurkeyPolandEU15<br><!-- End of picture text --> Source: Conway et al. (2005). Note: the 1998 data were re-based to be made more comparable to the 2003 data, given the change in methodology. This explains the slight differences in the data for 1998 between figure 2 and figure 3.a.

28. This positive effect is very much noticeable in Romania. In 2002 it ranked towards the bottom of the league of the 28 countries for which the overall PMR indicator was available. In 2006, out of 33 countries, Romania can confidently be ranked as one of the “middle of the road” countries, a remarkable progress by any measure (Figure 3.a and 3.b).

9
analysis of how politics and economics interact<sup>in shaping economic development. It explores why and</sup> how accountability, openness and predictability matter,<sup>and how the different ways in which governments</sup> use their power and authority create enabling or disabling<sup>economic environments.</sup> The issue of governance rose to the forefront of<sup>development agendas at the close of the 1980s,</sup> following nearly a decade of concern with macroeconomic<sup>policy reform. In Africa, calls by citizens</sup> and leaders for greater openness and accountability<sup>were joined by international donors. The World</sup> Bank's 1989 Long-Term Perspective Study (LTPS)<sup>_-- Sub-Saharan Africa: From Crisis to Sustainable_</sup> Growth--highlighted a deep concern with governance as<sup>a development issue: "Underlying the litany</sup> of Africa's development problems is a crisis of governance"<sup>(p. 60). Addressing political issues as</sup> openly as it did, the LTPS created a stir ifi the de-velopment<sup>community. The LTPS linked governance</sup> to issues of leadership authority and legitimary. It addressed<sup>the absence of balance of power, the lack</sup> of official accountability, the control of information, and<sup>a failure to respect the rule of law. The LTPS</sup> spoke in favor of "independence for the judiciary, scrupulous<sup>respect for the law and human rights at</sup> every level of government, transparent accountability<sup>of public monies, ancA independent public auditors</sup> responsible to a representative legislature, not to an<sup>executive" (p. 192).</sup> Although the calls for change have been loudest in Africa,<sup>other regions have undergone dramatic</sup> shifts in governance. In Latin America, the rapid transitions<sup>from authoritarian to democratic regimes</sup> over the past decade offered a different reason for attention<sup>to governance. Newly elected legislatures</sup> moved to transform old legal regimes, to reinforce new<sup>structures making government accountable to</sup> citizens, and to strengthen their own capacity to analyze, evaluate,<sup>and initiate policies.</sup> Governance issues surfaced in Asia over the past decade<sup>as well, most prominently in China,</sup> where a decade that opened with a dramatic transition to<sup>economic liberalization closed with the forceful</sup> suppression of calls for political change -- in Tiananmen<sup>Square. In the Soviet Union,</sup><sup>_glasnost_</sup> (openness) in the Soviet Union focused new attention on<sup>openness as a critical element in governance.</sup> In both the Soviet Union and Eastern Europe, political<sup>openness encouraged citizen's demands for</sup> accountability, and the move toward a market economy<sup>underscored the need to establish legal guidelines</sup> 2
In order to prepare the data set for computations, monetary variables were deflated by applying sector level wholesale price indices and energy price indices. Table 1 below presents some annual key figures from the data set. The figures are consistent with those officially announced by Turkstat.

**Table 1: Key Figures of the Turkish Manufacturing Industry over Time (All Firms)**

|**Period**|**Number of**<br>**Establishments**<br>**(1,000x)**|**Employment**<br>**(million)**|**Energy**<br>**Consumption**<br>**(2005 billion TL)**|**Value of**<br>**Production**<br>**(2005 billion TL)**|
|---|---|---|---|---|
|2005|302|2.58|11.4|322|
|2006|310|2.68|12.9|359|
|2007|317|2.78|14.0|372|
|2008|322|2.78|13.4|392|
|2009|325|2.50|11.6|350|
|2010|300|2.79|12.8|415|
|2011|333|3.08|14.0|488|
|2012|310|3.32|14.6|495|
|Average|315|2.25|13.1|399|

Since we can properly track only firms that employ 20+ employees every year within the period (due to the fact that firms with fewer than 20 employees are not subject to the census sample), we have to limit the firm level decomposition to firms existing in the data set every year over the period. The number of these firms (all period 20+ firms) is 9,379. Although they represent a very small share of all firms by count (3%), their average shares over the 20052012 period in total manufacturing employment, energy consumption and production are 45.6%, 72.5% and 66.5%, respectively. (Corresponding figures of 20+ firms and those of 9,379 all period 20+ firms are provided in the Appendix.) Next, we provide sector level statistics in the following three figures. First, Figure 1 provides an Index that compares total energy consumption of sectors in 2005 and 2012 and also shows how energy consumption of each sector changed over the 2005-2012 period. In the figure, the total energy consumption of all sectors is set to 100. The total of all sectors in 2012 is computed as 127.8, indicating a 27.8% increase in the total energy consumption of the manufacturing industry over the 2005-2012 period. (This can be verified in Table 1 as well.) As for sectors, classified by NACE (rev.1.1) 2-digit sectors, other non-metallic mineral products (cement, glasses, ceramics etc.) manufacturing, textile manufacturing and basic metals manufacturing were leading sectors in terms of energy consumption with a total share of 56% 7
6 This paper is also related to the literature on the so-called “resource curse”.<sup>8</sup> In particular, empirical evidence suggests that the curse in terms of the effect of natural resources on growth is less severe and can even turn into a boon if the quality of institutions is beyond a certain threshold (e.g., Mehlum, Moene and Torvik, 2006; Boschini, Pettersson and Roine, 2007). While this literature has long focused on the direction of causality running from natural resource endowments and institutions to growth and conflicts, our empirical results suggest that causality running from policies and market orientation to natural resource endowments is equally important. Our focus is on “upstream” rather than “downstream”. As such we are concerned with “external” policies and institutions that are geared toward foreign investors who conduct exploration activities. Our results do not contradict the fact that subsequent to a discovery, countries with poor “internal” institutions (e.g. weak state capacity) may experience poor economic performance and/or social outcomes or even civil strife.

The remainder of the paper is organized as follows. Section II puts forward some predictions based on a simple two-region model of depletion and discoveries, and discusses our empirical strategy. Section III presents the data used in the empirical analysis. Section IV presents the main results and key robustness checks. Section V concludes.

# **II.   ANALYTICAL PREDICTIONS AND EMPIRICAL STRATEGY**

We specify a simple two-region, three-period model of endogenous reserves and natural resource discoveries with international resource companies (IRCs) arbitraging to decide on the optimal geographical allocation of their exploration and depletion activities. The North has free access for IRCs but the South is less open for IRCs. Lack of openness in the South is interpreted captured by a virtual tax. IRCs decide _where_ to explore reserves depending on local extraction costs which depend on market orientation and availability of subsoil resources. Global IRCs relocate exploration across the globe until costs of resource exploration across the globe are equalized. We can then get the following analytical predictions (see Appendix A): 8 See Frankel (2012), Venables (2016), Ross (2012), and van der Ploeg (2011) for recent surveys.
range between 0 and 34 percent after defecation and 3 and 37 percent after cleaning up a child.<sup>11</sup> This paper focuses on handwashing promotion intervention, which attempts to improve child health by changing this key hygiene-related behavior rather than by implementing large and costly infrastructure investments in water supply or sanitation. In particular, we analyze the Global Scaling Up Handwashing Project in Peru, a large-scale intervention that aims to generate and sustain handwashing with soap behavior at critical junctures among mothers, caregivers, and children up to 12 years old in rural households. By trying to change the underlying factors that determine handwashing behavior (such as knowledge, beliefs, and accessibility of soap and water) among the target population, which is expected to result in improved handwashing behavior, the program tries to disrupt the causal chain that links poor hygiene with parasitic and microbiological disease transmission and thus ill health in children. Thereby, the study focuses on the following relevant outcomes: exposure to the intervention, changes in determinants of handwashing behavior (knowledge, beliefs, and access to/placement of soap and water), handwashing behavior (self-reported and observed), environmental contamination, and child health. To measure these behaviors and outcomes, we combined different quantitative and qualitative data collection techniques, including detailed questionnaires, structured observations, microbiological analysis of samples of children’s stools, capillary blood, and drinking water collected in the field, and anthropometric measures performed by health experts.

The Global Scaling Up Handwashing Project in Peru intervention consisted of two main components:

- a province-level mass media campaign; and

- a more comprehensive district-level community treatment that included, in addition to the media campaign, training of community agents; capacity building of mothers, caregivers, and children; and the inclusion of handwashing promotion as part of primary school curricula.

> 11 World Bank 2005.

3
<!-- Start of picture text --> Chronic poverty Moving out of poverty<br>ms =<br>= =<br>“a “a<br>TM~<br>aa<br>=A 2 xle si sia] 5My - xb ste si]<br>s ai e ¥ be s “A s s-ay 3<br>Moving into poverty Non-poor in both rounds<br><0 >| I<br>= =<br>“a “a<br>oo. ee... .<br>=aSy xle si sia] 5= - xb ste sA]<br>s A: Sn _ abe s A s ssMf id<br>| Range between upper and lower bound<br>Probabilities are based on synthetic panel estimates for household heads aged between 25 and 55<br>in the first round of each interval. The vertical axes give the conditional probability.<br><!-- End of picture text -->