rafmacalaba/datause-encoder-data huggingface dataset:
respondents in firm surveys can be asked more specific and objective questions, because they comprise a more homogeneous group. A survey of elites that includes public officials, academics, journalists, etc. must frame questions in such a way that they can be answered meaningfully by all of them, which necessitates broader questions. All of the 83 questions in the UNECA survey, and all 30 in the WGA survey, are subjective, with a standard set of five qualitative response categories.

The World Bank’s Country Policy and Institutional Assessment (CPIA) is a hybrid of centralized and decentralized expert-based ratings. The ratings originate with the country teams and regional offices, but then are reviewed for cross-regional comparability by central units. Most ratings proposed by the regions are not changed in this review, however, and the final ratings are correlated at about .98 with those proposed by the regions.

A second way in which expert assessments differ from each other is in the extent of documentation they provide regarding definitions and methods. For example, NIT provides more details than ICRG on its assessment criteria and its methodology (including sources of information), and provides extensive country narratives containing qualitative assessments of corruption problems to accompany the quantitative ratings. The CPIA is transparent in some respects but opaque in others. Its detailed assessment criteria are posted on a public web site, and there are reasonably detailed narratives justifying the ratings. Neither the ratings nor the justifications are publicly released however.<sup>6</sup> Sources that are more transparent and accountability, as reflected by the availability of detailed assessment criteria and justifications for ratings of each country,

> 6 Ratings, but not justifications, for the IDA-eligible countries will be publicly released for the first time in summer 2006.

10
Our incentive-compatible CDM modelling approach differs in several respects from the commonly used IET representation.<sup>8</sup> First, the overall cost savings are lower than under IET because the scope for curbing emissions through output reduction in emission-intensive sectors of the CDM host country is limited due to the introduction of output subsidies. Second, the CDM-participating firms (sectors) in the CDM host country do not suffer from an increase in production cost. Third, the CDM transfers do not enter the budget of the representative agent in the CDM host country (as they are used for compensating the CDM-participating sectors via output subsides). Fourth, in contrast to the IET representation, there is no trade-induced price equalization of emission prices in the CER-demanding country (the CDM donor) and the prices for CDM offsets in the CDM host country.

# **4. Model application**

We highlight the relevance of our CDM representation by means of a large-scale CGE application based on empirical data. For this purpose, we adopt a generic multi-region, multi-sector CGE model of global trade and energy use (see, e.g., Böhringer and Rutherford, 2002) calibrated to data of the Global Trade Analysis Project (GTAP). We compare the economic impacts of the CDM when represented either in our novel incentive-compatible approach or in the conventional IET manner. We first provide a non-technical summary of the basic model structure,<sup>9</sup> followed by information on the underlying GTAP database. We then lay out the policy scenarios and simulation results including sensitivity analysis for key parameters.

## **4.1. Model structure**

Goods are produced with intermediate inputs and primary factors (labor, capital, and natural resources). Primary energy goods (crude oil, natural gas, and coal) exhibit decreasing returns to scale with respect to natural resource inputs which are sector-specific. Capital and labor are intersectorally mobile, but immobile across regions.

The production of energy and other goods is described by nested constant-elasticity-of-substitution (CES) cost functions which characterize substitution possibilities between inputs (see Figure 1). For all goods except fossil fuels, the CES cost functions are arranged in multiple levels. The top-level nest combines an aggregate of capital, labor, and energy inputs (KLE) with a composite of material inputs (M); the second-level nest combines an aggregate of energy inputs (E) with a value-added composite

> 7 The CDM budget constraint is associated in complementarity with the shadow emission tax τ.

> 8 The unit-cost function of the IET-type CDM representation is equivalent to Eq. (2) with the output subsidy rate set to zero (μ= 0), and with the emissions price (τ) determined as the shadow price of the emissions cap of the multi-regional IET which includes the CDM-hosting countries (sectors).

> 9 A more detailed technical description is provided in Böhringer and Rutherford (2011).

7
<!-- Start of picture text --> 12 6<br>(ee 5 os<br>10 poss \ a Ae Te<br>5 “ 7 ‘\\ an° ltaie ataeTN se(eeiisFee oN<br>2 “ ceaoN i i ae ~ ne<br>s o - .TM Ss Poa ae Sn an<br>3 8) a eer N 2 - _—— ~ ~ .<br>Cy 7 ao feos 8 Lao ~~ _ oN Ni<br>oO° a _ Le4 >.Ne >c 4 NN~~ vsNs<br>a — ee Oo wee 2 VON ©<br>©> 6 “7tr_—— —_—— eeee tes wg s x \ YY.AS,<br>=of aeee oscee ne}o \\ WSNy<br>=® AU “oaA we wee be]a \\ \\<br>4707 wen B33 v\<br>44 ae is a<br>ee —— CostaRica —-——~—- Panama a —— CostaRica ———~—- Panama \<br>ae ----------- Guatemala —-—-- El Salvador s--s------- Guatemala —-—-- El Salvador ‘<br>2 —-—-— Honduras —— — ~ Nicaragua 242 TT Honduras — — — - Nicaragua<br>60-64 55-59 50-54 45-49 sama)ge35-39 30-34 25-29 20-24 19-15 60-64 55-59 50-54 45-49 Samy)ge35-39 30-34 25-29 20-24 19-15<br><!-- End of picture text -->
To understand what is the direct mechanism driving this decline in educational achievement following the genocide, we examine the role of orphan status and its ability to explain the results. Since approximately 10 percent of the Rwandan population died in 1994 and those deaths were concentrated among adults (de Walque and Verwimp, 2007), it is natural to think that orphanhood might be one of the main driving forces. In the 2000 DHS, 22.3 percent of the children aged 0 to 14 had lost at least one parent (ORC Macro, 2001). Figure 3 explores this hypothesis by displaying the years of education for orphans and non-orphans in 1992 and 2000 for children age 6 to 14 inclusive.<sup>12</sup> The figure illustrates that years of schooling is consistently higher in 1992 than in 2000, both for orphans and non-orphans. Strikingly, orphans in 1992 are better off, in terms of educational achievement, than both orphans in 2000 and non-orphans in 2000. Given the results in Figure 3, it is unlikely that the decline in educational attainment for the young cohort exposed to the genocide is mainly due to orphanhood.

# _4.2 Robustness checks: Triple Difference and Instrumental Variables_

As discussed in Section 3, the analysis so far is a comparison within a given province of younger children who were of school age compared to older children (who had finished school) and then a further comparison of a cross section of these children before and after the 1994 genocide. Given the genocide was such a large magnitude shock to Rwandan society, it is logical to think that most of the differences between 1992 and 2000 are due to this event. However, there could have been other changes occurring during this time interval and these changes could be correlated with changes in schooling and we might be incorrectly attributing the observed decline in schooling achievements to the impact of the genocide. To examine this possibility, in

> 12 The Demographic and Health Survey only reports orphan status for children under age 15, which limits the children for which we can explore this hypothesis.

14
SIERRA LEONE‘S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 1. Sierra Leone’s economy is projected to rebound**

<!-- Start of picture text --> 8<br>7<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>2007 2008 2008 2009 2009 2010 2011 2012<br>(Actual) (Prog.) (Est.) (Budget) (Proj.) (Proj.) (Proj.) (Proj.)<br>Aggregate Per-capita<br>Real GDP growth, %<br><!-- End of picture text --> _Sources:_ International Monetary Fund and World Bank staff estimates and projections; World Bank 2010. _Notes:_ The GDP estimates are provisional and remain subject to review.

Despite improvements in infrastructure, Sierra Leone added only 0.51 percentage points to the per capita growth rate from 2003 to 2007—much less than most other countries in the region or many other fragile countries. But like other African countries, the boost came predominately from the ICT revolution, while power-sector deficiencies and poor roads held back per capita growth by 0.08 and 0.05 percentage points respectively (figure 2a). Looking ahead, simulations suggest that if Sierra Leone‘s infrastructure could be improved to the level of the African leader—Mauritius—annual per capita growth rates would be 3.34 percentage points higher than they are at present. This impact would come from improvements not only in ICT, but also from increase in power-generating capacity and better road infrastructure (figure 2b).

5
numerous empirical papers which examine the trade-migration nexus. Gould distinguishes an _information_ channel through which migrants reduce the transaction costs of trade, from a _preference_ channel via which migrants foster trade flows through demanding domestically produced goods. Collectively, these two channels may be termed _direct immigrant links (direct links_ henceforth), since they pertain to the effects of migrants whose country of birth relates to either the importing or the exporting nation. In other words migrants which directly affect trade flows either to or from their country of origin.

Rauch (2001), an advocate of the „network‟ view of trade, stresses the role of business contacts and social networks that promote „trusting‟ contractual arrangements and overcome informational asymmetries and informal trade barriers. These arguments are akin to Gould‟s transaction cost mechanism or information channel. Rauch and Trindade (2002) examine the extent to which concentrations of ethnic Chinese<sup>4</sup> – and not the absolute levels - foster trade. The key additional insight proffered by Rauch and Trindade therefore is that _third-party_ migrants, the ethnicity of which pertains neither to the importing or exporting nation, may also promote bilateral trade flows. This is what Felbermayr, Jung and Toubal (2009) refer to as indirect effects.

The majority of papers in the trade-migration literature, implement gravity models and build upon Gould‟s insight to test these links in a variety of (predominantly OECD-centric) geographical settings, most commonly focusing upon a single country and her trading partners.<sup>5</sup> Head and Ries (1998) investigate immigrant-links in Canada, Dunlevy and Hutchinson (1999, 2001) examine historical data for the United States, Girma and Yu (2002) study the impact of migration on trade in the UK, Bryant et al (2004) for New Zealand, Blanes-Cristobel (2003) in Spain, White (2007b) for Denmark and Hatzigeorgiou (2010) in Sweden. At the _country_ level, only three papers examine direct-links amongst groups of countries. Hatzigeorgiou (2009) examines a cross-section of 75 countries in 2000, while Felbermayr and Toubal (2008) implement a cross-section for the OECD in the same year. Felbermayr and Jung (2009) is the only paper to the knowledge of the author which implements a panel of countries (for 1990 and 2000).

Greater availability of disaggregated data has spurred ever more sophisticated empirical studies. Some focus upon the trade-migration nexus within a country, for example Combes et al (2005) for France. Yet another strand of the literature examines _states_ or _provinces_ trading with overseas country partners. Examples include Wagner et al (2002) for Canada, Co et al (2004), Bardhan and Guhathakurta (2005), Herander and Saavedra (2005), Dunlevy (2006) and Bandyopadhyay et al (2008) for the US and Peri and Requena (2010) for Spain.

> 4 These concentrations are modelled as the cross-products of the share of ethnic Chinese in each trading partner. 5 Migration data are notoriously weak and this focus can be explained by the paucity of the available migration data.

4
Krueger, A.B., J. Angrist. 2001. Instrumental variables and the search for identification: From supply and demand to natural experiments? _Journal of Economic Perspectives_ 15: 69-85.

La Porta, R., F. Lopez-de-Silanes, A. Shleifer, and R. Vishny. 1997. Legal Determinants of External Finance. _Journal of Finance_ 52: 1131-1150.

———. 1998. Law and Finance. _Journal of Political Economy_ 106: 1113-1115.

La Porta, R., F. Lopez-de-Silanes and G. Zamarrita. 2003. Related Lending. _Quarterly Journal of Economics_ , 18, No. 1: 231-68.

Love, I., and N. Mylenko. 2003. _Credit reporting and financing constraints_ . World Bank Policy Research Paper, No. 3142.

McMillan, J., and C. Woodruff. 1999. Interenterprise relationships and informal credit in Vietnam. _Quarterly Journal of Economics_ ; 114, No. 4:1285-1320.

Pal, Sarmistha. 2002. Household sectoral choice and effective demand for rural credit in India. _Applied Economics_ , 14: 1743-1755.

Petersen, M., and R. Rajan. 1997. Trade credit: Theories and Evidence. _The Review of Financial Studies_ , 10, no. 3: 661-691.

Stiglitz, Joseph, and A. Weiss. 1981. Credit rationing in markets with imperfect information. _The American Economic Review_ , 71, no. 3: 393-409.

Tirole, Jean. 2006. _The Theory of Corporate Finance_ . Princeton, N.J.: Princeton University Press.

16
household displacement and the destruction of household dwellings during the violent events. We are also able to measure conflict intensity across time – including peaks of violence at various stages of the conflict – at the district level from event data on violence intensity during the conflict in Timor Leste. We focus on primary school effects because only a small percentage of the Timorese population attended secondary school.

Our results show mixed evidence for the impact of violent conflict on educational outcomes. Mirroring some of the findings of Bellows and Miguel (2006) and others, we find evidence for a rapid recovery of the education sector in Timor Leste, and of educational outcomes, particularly for girls. However, in line with emerging results in the micro-level literature, we find that the 1999 wave of violence in Timor Leste – as well as peaks of violence in the 1970s and 1980s – resulted in negative effects on primary school attendance and attainment. This effect is particularly strong for boys. We attribute the first result to a process of educational catch-up among girls in Timor Leste that started before the conflict and continued despite the conflict. The second result is likely to be due to large rates of grade repetition and of delay entry that were exacerbated by the need to remove boys from school due to the negative economic effects of the conflict on households more exposed to the violence.

The paper is structured as follows. In section 2, we present a literature review on the impact of violent conflict on development outcomes in general and education in particular. Section 3 provides a descriptive background of the conflict in Timor Leste and the country‘s education sector. In section 4, we describe the datasets, discuss our identification strategy and present some descriptive results. Section 5 discusses our empirical results, as well as a range of robustness checks. Section 6 concludes the paper.

# **2. Literature review**

An emerging body of literature has provided valuable empirical evidence on the effects of violent conflict on income and consumption levels, and more generally on the welfare of populations living in areas of violence (Ibáñez and Moya 2009, Justino and Verwimp 2006, Verwimp and Bundervoet 2008). A significant number of studies have also examined the health impact of violent conflict, finding that violence results in negative health effects in terms of lower height-for-age and lower nutritional outcomes among children that will generate long-term consequences on future outcomes.<sup>2</sup>

> 2 See Alderman et al. (2006) for Zimbabwe, Bundervoet et al. (2009) for Burundi, Akresh and Verwimp (2006), Akresh, Verwimp and Bundervoet (2007) and Akresh and de Walque (2008) for Rwanda and Guerrero-Serdán (2009) for Iraq.

4
# **Table 11: Official Population Estimates by region and year, in 100,000s**

||`00|`01|`02|`03|`04|`05|`06|`07|`08|`09|`10|`11|`12|`13|`14|`15|`16|`17|`18|`19|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|National|244.9|248.1|251.2|254.3|257.1|260.2|263.1|266.6|270.7|275.3|280.0|291.2|295.6|299.9|304.9|310.2|315.8|321.2|326.6|332.6|
|Karakal.|15.0|15.3|15.4|15.5|15.6|15.7|15.7|15.8|16.0|16.2|16.3|16.8|16.9|17.1|17.4|17.6|17.9|18.2|18.4|18.7|
|Andijan|21.9|22.2|22.5|22.8|23.1|23.4|23.8|24.1|24.5|25.0|25.5|26.7|27.1|27.6|28.1|28.6|29.1|29.6|30.1|30.7|
|Bukhara|14.2|14.4|14.6|14.7|14.9|15.1|15.3|15.5|15.7|15.9|16.1|16.8|17.1|17.3|17.6|17.9|18.2|18.4|18.7|18.9|
|Jizzakh|9.7|9.9|10.1|10.2|10.3|10.4|10.5|10.6|10.8|11.0|11.2|11.7|11.9|12.1|12.3|12.5|12.8|13.0|13.3|13.5|
|Kashk.|21.7|22.1|22.5|22.9|23.4|23.8|24.2|24.6|25.1|25.6|26.2|27.2|27.8|28.3|29.0|29.6|30.3|30.9|31.5|32.1|
|Navoi|7.8|7.9|8.0|8.0|8.0|8.1|8.1|8.2|8.3|8.4|8.5|8.7|8.8|8.9|9.0|9.1|9.3|9.4|9.6|9.8|
|Namangan|19.2|19.5|19.8|20.1|20.4|20.7|21.0|21.3|21.7|22.2|22.6|23.8|24.2|24.6|25.0|25.5|26.0|26.5|27.0|27.5|
|Samarkand|26.7|27.1|27.5|27.9|28.3|28.7|29.1|29.6|30.0|30.6|31.2|32.7|33.3|33.8|34.5|35.1|35.8|36.5|37.2|38.0|
|Surkh.|17.4|17.7|18.0|18.3|18.6|18.9|19.3|19.6|19.9|20.3|20.8|21.8|22.2|22.6|23.1|23.6|24.1|24.6|25.1|25.7|
|Syrdarya|6.4|6.5|6.6|6.6|6.7|6.7|6.8|6.8|6.9|7.0|7.1|7.3|7.4|7.5|7.6|7.8|7.9|8.0|8.2|8.3|
|Tashkent|23.5|23.7|23.9|24.1|24.3|24.5|24.7|24.9|25.2|25.5|25.9|26.4|26.7|27.0|27.3|27.6|27.9|28.3|28.6|29.0|
|Fergana|26.6|27.0|27.3|27.7|28.0|28.4|28.8|29.2|29.7|30.2|30.7|32.3|32.8|33.3|33.9|34.4|35.1|35.6|36.2|36.8|
|Khorezm|13.2|13.5|13.7|13.9|14.1|14.3|14.5|14.8|15.0|15.3|15.6|16.0|16.3|16.5|16.8|17.2|17.5|17.8|18.1|18.4|
|Tashkent city|21.4|21.4|21.4|21.4|21.4|21.4|21.4|21.6|21.8|22.1|22.3|23.0|23.1|23.4|23.5|23.7|23.9|24.2|24.6|25.1|

_Source: Uzbekistan State Statistic Committee. Note that the reported figures are based on administrative data, in the absence of a national population census_ 57
"[Watta satta] means that you will give a daughter and receive the same in return. It also implies that if our daughter will be in pain, we will treat your daughter the same way." (woman from Badeen, Sindh)<sup>1</sup>

# 1 Introduction

Marriage is perhaps the epitome of an incomplete contract. Its terms can never be fully specified ex-ante or enforced ex-post. A vast body of literature has thus highlighted the role of post-marital bargaining in determining intrahousehold allocations (seminal papers include McElroy and Horney, 1981; Manser and Brown, 1980; and Lundberg and Pollack 1993). In traditional societies, where women’s formal legal rights are often weak, divorce is strongly stigmatized, and there is a high premium on female virginity, bargaining power can shift radically in favor of the man once the woman commits herself to marriage. This fact should have implications for the form of the marriage ‘contract’; in particular, its ex-ante provisions should reflect the interests of the wife and her family in deterring or mitigating ex-post malfeasance on the part of the husband.

In this paper, we argue that exchange marriage in rural Pakistan can play just such a role. Bride exchange, known locally as watta satta (literally, ‘give-take’), usually involves the simultaneous marriage of a brother-sister pair from two households. Remarkably, watta satta accounts for about a third of all marriages in rural Pakistan.<sup>2</sup> Watta satta is more than just an exchange of daughters, however; it also establishes the shadow of mutual threat across the marriages. As the watta-bride quoted above expresses so succinctly, a husband who ‘mistreats’ his wife in this arrangement can expect his brother-in-law to retaliate in-kind against his sister.

We shall show that such reciprocal threats operating across marriages can be credible and may, consequently, prevent inefficient marital outcomes. Husbands generally have coercive power over their wives, through various forms of physical and emotional intimidation. In virilocal societies, this power is heightened by the wife’s residence in

> 1 All of the quotations in this paper are from field interviews conducted as part of a qualitative survey undertaken in selected villages covered by the 2004-05 Pakistan Rural Household Survey.

> 2 Similar marriage patterns prevail in south India, whereas in north India sibling exchange marriage is generally disapproved of (Mencher and Goldberg, 1967; Karve, 1993; Trautmann, 1993). Nevertheless, exchange marriage appears to have been common among Hindus in the Punjab, at least formerly (Rose, 1908). Outside south Asia, exchange marriage has been documented in parts of China (Zhang, 2000). Early anthropological accounts of exchange marriage in west Africa also mention the ‘retaliatory’ motive emphasized in this paper, but here it is typically in reaction to a wife’s ‘malfeasance’ (such as leaving her husband) that her brother’s marriage is dissolved.(Bohannan, 1949; Meek, 1936).

1
# **Figure 1: From Public Spending**<sup>**to Better Health**</sup>

<!-- Start of picture text --> ,- -<br>/\<br>Public spending<br>onJ __<br>health services Organzatio<br>> _ | ' ~~~~~~~~~~~~~OrganizationI<br>,EHS Efficacy of and incentives I<br>PubZ7 4- -public sector in the public<br>I ~~sector<br>Level of publicly<br>provided<br>effective health services/.------<br>'Extent to which Demand for<br>public provision treatment.<br>8 *HS7~ 4 displaces 4 Existing and<br>private potential<br>provision I private supply.<br>Consumption of<br>effective<br>health services<br>a 7 Clinical {iMedical and<br>8 Consg < -" i effectivness of 4 biological<br>the services processes<br>g ~~Health<br>V status J<br>< ~~~(HS)<br><!-- End of picture text -->

_35_