rafmacalaba/datause-encoder-data huggingface dataset:
16 significance. Variables that remain are GDP per capita, secondary school enrolment ratio (or human capital investment), annual population growth and gross capital formation as ratio of GDP (which is considered as investment).

In their study, Davoodi and Zou used five-year and ten-year average data to smooth over short-term effects. Here, with a limited sample that covers only three years for each cross-section, no such average could be used. However, centred three-year moving averages<sup>*</sup> have been applied on dependent and control variables to minimize any shortterm effects. What is estimated here is not the relation between decentralization and growth on a short-term or year-to-year basis. It is the relation between decentralization and growth on an average medium-term basis.

In the Oates model, the dependent variable ( _Yit_ ) is the public sector size measured as total aggregate government current expenditure as a share of GDP. In the original model, two proxies for decentralization (θ _it_ ) were used: revenue share and expenditure share. Again, measures of decentralization of Ebel and Yilmaz and the new measures of this study will be added as θ _it_ . In this model, only countries fixed effects (α _i_ ) will be considered. Joint F-test on fixed effects reveals that time dummy coefficients are not significant, while country dummies are significant. The set of control variables ( _X it_ ) will be the same as in the original study, including urban population ratio, GDP per capita and total population. Because the dependent variable in this model is computed from the OECD data, which are available for only three-year period, it is impossible to use three-year moving averages to smoothen for short-term effects. It must be notice dough that no average data was used in the Oates study. It was a cross-section analysis over only one-year data.

Every model is estimated with each indicator of decentralization, once in a multiple regression including control variables, and once again in a simple regression.

> * A three-year moving average is a process by which data _X t_ is replaced by ( _X t_ −1 + _X t_ + _X t_ +1) / 3 .
3 valuable information to policy makers and help target the limited resources for redistribution toward those public services of maximum benefit to the poor. However, these studies do not, to date, e..fer benefit measures on the broad range of government services that more traditional benefit incidence studies offer.

The next section of the paper reviews the methodology of benefit incidence, followed by a section focusing particular attention on methodological issues in developing countries. The fourth section briefly examines recent empirical results on benefit incidence obtained for developed countries. The fifth section examines the empirical results for developing countries, and in the last section we present our conclusions, including recommendations for further research and guidance.to researchers charged with doing benefit incidence studies within a limited time frame.

# **IL** Methodology

There is some confusion in the empirical literature about terminology, necessitating some preliminary remarks. Musgrave (1959), McLure (1974), McLure and Thirsk (1975), Meerman (1979), DeWulf (1981), and Piggott and Whalley (1987), distinguish between expenditure incidence and benefit incidence. The former concept refers to the changes in relative factor and product prices and real incomes that result from government input purchases and the production cf public output. Expenditure incidence does not explicitly account for the benefits of public goods (McLure et al., 1975, p. 195). Benefit incidence examines the consumption of govermment services by income or other subgroup, and ideally would include the shifting of government benefits and the relative price and real income changes due to changes in the demand for private goods.<sup>3</sup> We adopt this terminology, recognizing that it differs from that used by some authors. Ideally, the total benefit incidence of existing government programs (the "post-fisc" equilibrium) would measure benefits relative to a counterfactual world without govenmmen ( he **t** "pre-fisc" equilibrium). No research has yet established a counterfactual world, without government. Most empirical studies of benefit incidence allocate public expenditures, and not consumer surplus benefits, to households based on tbeir utilization of the services. The consumer
# **Figure 2**

<!-- Start of picture text --> URUGUAY FINANCIAL ASSETS<br><!-- End of picture text --> <!-- Start of picture text --> 22 -<br>20-<br>14 -<br>0~~ 12-<br>10-<br>o 6<br>o 4-<br>-<br>0 _ Dmm m:mal:llC _8<br>Dec - 84 Dec-6 Oec -8 Oec - o<br>Cec- 5 Dec- 87 Dec- 89<br>DeCentef 1984 - Seotenter 1991<br>National currsncy<br>EForeign cuirrenc:y<br><!-- End of picture text -->

# **The Banking System in Uruguay**

The Uruguayan banking system consists of the Central Bank, two Government-owned banks-Bank of the Republic (BROC) and the Housing Bank (BHU)--and twenty-one commercial banks. Additionally, eighteen financiers and some credit unions also satisfy retail or consumer credit demands. Of the commerciai banks, twenty are foreign owned. Two conmmercial banks that had become insolvent in the mid-1980s were taken over by the Government. They are still in public hands, although their reprivatization is part of the financial sector reform program undertaken by the Uruguayan government.

As we discussed above, foreign currency deposits in Uruguay represent an important element of the monetary scene. Foreign currency deposits grew to about US$7 billion at the end of 1990 from about US$1 billion participation in total currency composition of the banking system in 1980. About four-fifths of the assets and liabilities of the banking system became dollarized. The legalization of unlimited foreign currency holdings and banking credit operations contributed to the currency replacement and dolarization of the economy during the 80s. Another important factor in the increase in foreign inflows was the **decline** in world interest rates, which made risk-adjusted financial yields more attractive to foreignr depositors. This phenomenon was not limited to Uruguay. To a more or less extent, many Laiin American countries attracted depositors in this way.

Rates on deposits and loans were positive in real te.sns for loans but negative for deposits during the 1980s. Nominal interest rates on peso loans have fallen from around 180 percent in June of 1989 to 120 percent in March of 1992. Still they are about 30 percent above inflation. Nominal interest rates 26
_Figure 13. Effect of fiscal policy in 2012/13 and 2016/17_ _a. Gini coefficient b. Poverty Headcount rate (national poverty line)_ <!-- Start of picture text --> 0.434 23.70<br>0.420<br>0.414 0.419 0.411 0.402 21.39 21.44 21.42<br>0.401 0.400 0.398 19.80 19.80 19.70 19.9<br>0.381<br>2012/13 2016/17 2012/13 2016/17<br>c. Marginal contribution to redistribution d. Marginal contribution to poverty reduction<br>1.51<br>0.1 0.2 0.3<br>1.27<br>1.04<br>0.95 0.0<br>-0.4<br>0.76<br>0.59<br>0.10 0.23<br>0.07 0.05 0.09<br>-3.0<br>2012/13 2016/17 2012/13 2016/17<br>Gini coefficient<br>Percent of the population<br>Gini points<br>Percentage points<br>Health Educ<br>Ind. subs. Ind. taxes<br>Ind. taxes Ind. subs.<br>Direct trans. Direct taxes Direct trans. Direct taxes<br><!-- End of picture text --> _Source: Authors’ calculation based on UNHS 2016/17 and using the national poverty line._ _Note for c): A positive redistributive effect means inequality declines, while a negative redistributive effect means inequality increases (in Gini points). For d): A positive poverty reducing effects means poverty is declining while a negative poverty reducing effect means poverty is increasing (in percentage points)._ 35
replace the dependent variable in our SDM in equation (3) by estimates of the Gini index of consumption inequality from the same NSS data.

Table 5 provides the results. Whether we use illuminated area or total light, or variable or fixed masks, we find no sign of significant effects on inequality. The effects of urban growth on rural poverty appear to be transmitted entirely via growth in mean rural consumption. This result does not differ between secondary towns or cities.

# **VI. Conclusions**

The scope for escaping rural poverty through urban economic growth has been a longstanding development issue, going back to the classic model of Lewis (1954). We have revisited this issue, focusing specifically on the question of whether cities or towns are better generators of rural-poverty reducing growth in India, using data on 59 regions observed four times from 1993/94 to 2011/12. The rural headcount poverty rate fell by half in this period and the poverty gap index fell by two-thirds. The pace of poverty reduction was spatially uneven. Using night lights as the indicator of urban economic activity, we find that the geographic expansion of urban areas is associated with lower rural poverty measures; these effects are consistently found using different specifications, while there is little apparent effect on the rural sector from the brightness of lights coming from urban areas. It is urban growth on the extensive rather than the intensive margin that matters for rural poverty reduction.

When the effects of big-city growth on rural poverty are compared to those of secondary towns, some consistent associations emerge, indicating that the growth of towns matters far more than cities to reducing rural poverty in India. This effect is close to inequality-neutral, in that it was not associated with higher, or lower, inequality within rural areas. In expectation, the poverty effect is transmitted through mean consumption.

We remind readers that here we have only studied this question for India, at its stage of economic development. The pattern we have uncovered may not hold at all stages of development. Indeed, our theoretical model suggests that cities may eventually take over from towns as the drivers of rural poverty reduction. For now, however, India should look to its towns, not its cities, to help reduce rural poverty, on top of promoting agricultural and rural development.

19
manufacturing GVCs, including those in textiles and apparel, metal products, transport equipment, and electrical goods. Results from the analyses of the World Bank Enterprise Surveys show that domestic actors in these linkages are typically relatively large manufacturers of 100 or more employees that have been in operation in their respective industries five years or longer. As participants in GVCs, these manufacturers are more likely to have foreign equity holders or hold foreign technology licenses than other enterprises.

The current geographic configuration of these linkages evolved over the last 25 years, during which linkages of China and India to the United States, Western Europe, and the rest of the developing world developed. The paper shows that Africa accounts only for a tiny fraction of the volume of trade in manufactures of any one of China, Western Europe, or the United States, with linkage rates to Africa along manufacturing GVCs consequently being extremely low. Yet Africa’s manufacturing GVC linkage rate with the three larger economies is comparable to the corresponding linkage rates to economies of other developing regions including the external comparators namely, Bangladesh, Cambodia, Indonesia, and Vietnam.

At the same time, linkage rates across manufacturing GVCs do vary significantly between countries within Africa and have changed substantially over the past decade. A major factor in cross-country variation in linkage rates within the region is natural resource endowment, with countries that are rich in non-oil natural resources having greater linkages to manufacturing GVCs. Linkages to manufacturing GVCs have also increased over the period in non-oil resource rich countries but have declined quite steeply for non-resource rich countries as a group. This development needs to be seen against the premise that governments’ efforts across Africa for promoting job growth through industrialization would succeed only in as far as they facilitate entry of domestic firms into manufacturing GVCs at links deemed to maximize expected gains in jobs and productivity.

The level and dynamics of linkage rates to manufacturing GVCs also vary between countries within the resource rich group and between the non-resource rich. This is partly due to differences in the levels of natural resource endowment across countries. It is also because linkage rates depend on other factors such as differences in the per capita incomes, size and 22
NGOs on the scope of the project and its effective management. The specific design of the community-based activities and their operationalization required an evidence-base on the communities’ socio-economic and cultural characteristics, life style, health seeking pattern and knowledge regarding febrile and other common illnesses. Baseline qualitative research provided such evidence [10]. Community level meetings and participatory social mapping exercises conducted in every study village led to the further fine-tuning of intervention strategies. These meetings also provided an opportunity for the implementing NGO and the community to build rapport. As part of the national malaria control program’s strategy, LLINs were distributed and the ASHA were provided with RDT and ACT for management of fever and malaria cases in all three arms. Every study village – both in treatments and control – contained an active ASHA worker previously trained in malaria case management.

**_Community mobilization:_** Community mobilization efforts focused on modifying population health seeking behavior towards effective malaria control and management. Specifically, mobilization efforts aimed at 1) increasing the consistent use of long lasting insecticide treated bed nets that were provided to the community free of cost by the NVBDCP, and 2) timely care seeking for febrile illnesses from the ASHA in the village. Activities included the dissemination of appropriate behavior change messages through locally acceptable communication channels. The formative research conducted during the planning phase helped incorporate local norms and customs into the design of the community mobilization strategies and messages [10]. Mobilization activities were most intensive during the transmission season with follow up activities afterwards. Various target groups such as local self-government, social organizations, women, men, youth, school and religious groups were chosen for community mobilization. The

6
|**Table 12: Inst**|**rumental- vari**<br>SDQ Em<br>Prob|**able regres**<br>otional<br>lem|**sion results o**<br>SDQ C<br>Prob|**f project im**<br>onduct<br>lems|**pact on chil**<br>SDQ Hyp|**d developme**<br>eractivity|**nt (Depende**<br>SDQ Peer|**nt variable i**<br>Problems|**s standardize**<br>SDQ Pr<br>Beh|**d SDQ scor**<br>o-social<br>avior|**e)**<br>SDQ Tota|l Problems|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Unadjusted|Adjusted|Unadjusted|Adjusted|Unadjusted|Adjusted|Unadjusted|Adjusted|Unadjusted|Adjusted|Unadjusted|Adjusted|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|Village is Batch 1|||||||||||||
|(1=Yes)|-0.0788|-0.0684|-0.115|-0.107|0.0180|0.0122|-0.0604|-0.0864|0.0306|0.0223|-0.0982|-0.101|
||(0.0571)|(0.0603)|(0.0610)|(0.0642)|(0.0621)|(0.0652)|(0.0524)|(0.0563)|(0.0591)|(0.0572)|(0.0599)|(0.0624)|
|Constant|0.553***|0.861*|0.497***|1.403***|0.612***|1.393***|0.140*|0.630|-0.343***|-0.112|0.688***|1.603***|
||(0.103)|(0.346)|(0.100)|(0.383)|(0.125)|(0.357)|(0.0643)|(0.369)|(0.0552)|(0.354)|(0.0941)|(0.365)|
|N|1919|1717|1919|1717|1919|1717|1918|1716|1918|1717|1918|1716|
|AdjustedR-squared|0.084|0.127|0.076|0.089|0.088|0.094|0.054|0.058|0.118|0.138|0.121|0.143|
|**Controls Included**|||||||||||||
|Child Characteristics|N|Y|N|Y|N|Y|N|Y|N|Y|N|Y|
|Household|||||||||||||
|Characteristics|N|Y|N|Y|N|Y|N|Y|N|Y|N|Y|
|Height and Weight|N|Y|N|Y|N|Y|N|Y|N|Y|N|Y|
|Parenting practices at<br>baseline|N|Y|N|Y|N|Y|N|Y|N|Y|N|Y|
|District dummies|Y|Y|Y|Y|Y|Y|Y|Y|Y|Y|Y|Y|
|First stage F-Statistic||97.630||97.630||97.630||97.480||97.630||97.480|
|First stageR-squared||0.775||0.775||0.775||0.775||0.775||0.775|

_Note:_ Robust standard errors clustered at the village level in parentheses. Child characteristics include: child’s age and gender. Household characteristics include household size, household wealth and mother’s education. Height and weight include stunting and wasting status at baseline. Parenting practices are self-reported by caregiver at baseline. District dummies are controlled for in both adjusted and unadjusted models.

*** p<0.01, ** p<0.05, * p<0.1

46
IV regression results for equation (3) with and without additional controls are stated in Table 7.

**-** **<u>Table 7: IV Growth regression results (1990 2000)</u>**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||<br>|**Second stage**<br>|**regressions**<br> <br>||
||_English_|_& French_|_English,_<br>_Soc_|_French &_<br>_ialist_|
|_Law_|.188<sup>***</sup>|.186<sup>***</sup>|.209<sup>***</sup>|.201<sup>***</sup>|
||(.004)|(.007)|(.000)|(.005)|
|_S_1990|-.378<sup>**</sup>|-.355<sup>***</sup>|-.476<sup>***</sup>|-.515<sup>***</sup>|
||(.029)|(.003)|(.001)|(.000)|
|**All controls**||Yes||Yes|
|Sample<br>|89|89|94|94|
|_R_<sup>2</sup>|.01|.25|.01|.24|
|Hansen test|.057|.062|.181|.399|
|**p-value**|**.812**|**.803**|**.913**|**.819**|
|Shea partial|.157|.147|.195|.147|
|corr. for_Law_|||||

**<u>First stage regressions: Dependent variable is</u>** **_<u>Law</u>_**

|_ELF_|-1.05<sup>***</sup>|-.696<sup>**</sup>|-1.11<sup>***</sup>|-.684<sup>**</sup>|
|---|---|---|---|---|
||(.001)|(.021)|(.000)|(.023)|
|_French_|-.410<sup>**</sup>|-.358<sup>**</sup>|-.420<sup>**</sup>|-.364<sup>**</sup>|
||(.017)|(.020)|(.014)|(.017)|
|_Socialist_|||.187|-.413|
||||(.609)|(.211)|
|_R_<sup>2</sup>|.42|.72|.42|.71|

p values in brackets. **All controls** include: _Continent, Latitude_ and the decadal change (2000 value minus 1990 value) in _GDP, Pop_ , _Power, Roads_ .

25
constitutes only about 11 percent of the total civil service workforce<sup>5</sup> [Table 2]. Comparable numbers for professional and technical staff in Gambia (in 2007) were 26 percent and even in Sudan (in 2004) 14.3 percent.<sup>67</sup> This is commonly referred to as the problem of the ̳missing middle‘.

**Table 2: The composition of civil service in Sierra Leone (2008-2011)**

|||**20**|**08**|**2**|**011**|
|---|---|---|---|---|---|
|**Category**|**Grades**|**Numbers**|**Percent**<br>**of total**|**Numbers**|**Percent of**<br>**total**|
|Low|1-5|13,255|92.2%|11,881|87.3%|
|Middle|6-10|995|6.9%|1,559|11.4%<sup>8</sup>|
|High|11+|134|0.9%|177|1.3%|
|**_Total_**||**_14,384_**|**_100%_**|**_13,617_**|**_100%_**|

<mark>Notes: (i) The figures for 2008 are from World Bank (2010): Sierra Leone Public Expenditure Review, Report Number 52817-SL, October 28, 2010; (ii) Figures for 2011 were provided to Bank staff by the MoFED in September-November 2011; (iii) Figures for both 2008 and 2011 include core civil service and health workers; (iv) grades 1-5 are the lower grades/―blue collar‖ workers; grades 6-10 are professional and technical staff with grade 7 as the graduate entry level; and grades 11 and up are the senior management cadre.</mark> _Source_ : World Bank (2012b) Several features characterize the current state of the civil service in Sierra Leone, including (i) extremely low levels of remuneration that are inadequate for attracting and retaining staff; (ii) patronage based appointments, promotions and remuneration levels; and (iii) the virtual absence of intrinsic or extrinsic incentives for performance. In addition, internal inequities which engender frustration and dissatisfaction are not conducive to establishing an _esprit de corps_ . While it is difficult to disentangle the impact of each of these, it is more than likely that together they act as ̳binding constraints‘, the lifting of which would be a necessary (if not sufficient) condition to improve overall civil service performance. We now review them in turn.

> 5 The comparable figure was 7% in 2008 (World Bank 2010). The ―civil service‖ in Sierra Leone includes health workers but not teachers who are included in the ―public service‖ count but not in the ―civil service‖.

> 6 Figures for Gambia are from the payroll for 2007; figures for Sudan are from Public Administration/Civil Service, Government of Sudan, Background Paper, Sudan: Joint Assessment Mission, World Bank, unpublished mimeo, 2004.

> 7 The Public Expenditure Review (World Bank 2010) suggests 45% as the desirable percentage.

> 8 The real problem of the low numbers in the middle/technical and senior grades is in the ―bureaucracy‖ and not with the front line staff associated with service delivery. For example, close to 60 percent of teachers hold positions between grades 6-10, i.e. are at the middle levels.

6
# **Introduction**

A potential obstacle to durable peace, and an empirical reality of many civil wars, is that conflicts often involve numerous rebel groups. Cases in point are, for instance, Bosnia and Herzegovina, Burundi, Colombia, the Democratic Republic of Congo, and Sudan. Some scholars hold that if a peace agreement includes all the warring parties, peace is more likely to prevail (e.g. Hampson, 1996; Rubin, 2002). For instance, Licklider (2001: 701) stresses the importance of inclusiveness and points out that third parties ‘... should exert every effort to bring all of the important players into the process as soon as possible.’ The argument implies that the presence of excluded parties can jeopardize peace, not only by heightening the risk of violence involving the outside actors, but also by influencing the commitment to peace among the signatories. However, while many seem to expect that all-inclusive peace agreements are more likely to see peace prevail, this claim has so far not been examined in a quantitative study. The present study addresses this lacuna in previous research by providing a first test of this proposition. Hence, the _purpose_ of this article is to explore whether all-inclusive peace agreements are more likely to provide durable peace than partial agreements that leave out one or more rebel groups.

I argue that all-inclusive peace deals are not the panacea for peace that many seem to believe. If we think of parties in civil wars as strategic actors that look ahead when they make decisions, we can expect that the signatories have considered the possibility that excluded parties may continue to engage in armed conflict. Thus, the risk of violent challenges from outside actors is likely to already be factored into the decision-making calculus when the signatories decide to reach a deal. This suggests that while the excluded actors may continue to fight, settlements leaving out one or more rebel groups should not necessarily make the signatories any more likely to engage in violence.

Implications from this theoretical argument are tested using unique data from the Uppsala Conflict Data Program (UCDP) on the conflict behavior of the government and each of the rebel groups in internal armed conflicts, 1989–2004. The statistical analysis is conducted employing a Cox proportional hazards model. The results are well in line with the theoretical argument. The findings show that whether an agreement leaves out one or more rebel groups does not affect whether the signatories stick to peace. At the same time, agreements that exclude some party are found to reduce the overall prospects for peace in the conflict, that is, when taking 2