rafmacalaba/datause-encoder-data huggingface dataset:
Table 5B: Robustness checks (Coefficient on IBRD country)

||()<br>Number o|Q<br>fprojects|6<br>Number of|4)<br>HD projects|6)<br>Share ofH|6<br>D projects|
|---|---|---|---|---|---|---|
|Base specification|-0.680**|-0.852**|-0.342"«|-0.360"*|-0.071**|-0.068**|
|(allcountries,1988-2016)|(0.347)|(0.398)|(0.089)|(0.097)|(0.032)|(0.034)|
|<br>Longertime frame|-0.533***|-0.494*|-0.167***|-0.208***|-0.034**|-0.043**|
|(all countries, 1961-2016)|(0.148)|(0.215)|(0.050)|(0.065)|(0.017)|(0.019)|
|Excludereverse graduates|-0.711*|-0.853*|-0.338***|-0.338**|-0.046|-0.043|
|(1988-2016,5excluded)|(0.408)|(0.474)|(0.102)|(0.113)|(0.032)|(0.036)|
|<br>Exclude small andlarge countries|-0.563|-0.690*|-0.305**|-0.307*"*|-0.069*|-0.068*|
|(1988-2016, 11 excluded)|(0.392)|(0.409)|(0.075)|(0.083)|(0.036)|(0.036)|
|Additional control variables|-0.412|-0.667|-0.327%* =|= -0.357***|-0.089**|-0.100**|
|(all countries, 1988-2016)|(0.413)|(0.470)|(0.110)|(0.117)|(0.042)|(0.039)|
|Controls|no|yes|no|yes|no|yes|
|Country fixed effects|yes|yes|yes|yes|yes|yes|
|Fiscalyearfixedeffects|ves|yes|yes|ves|ves|ves|

Notes: Each observation is a country year, thus the coefficients can be interpreted as the average differences between IDA/Blend and IBRD country. Control variables in the even numbered columns are (a) log of GNI per capita, (b) log of population, and (c) Net aid flow. The rows with additional countrol variables include (a) Polity Index (-10 to 10), (6) Number of years left in current term of the executive, (3) If executive has finite terms in office, and (4) Indicators for left and nght leaning executive. Standard errors are clustered at the country level. * Significant at 10%, ** Significant at 5%, Significant at 1%.
The conventional definition of the RCA measure was first proposed by Balassa (1965). Export RCA of country j’s sector _k_ is defined as the share of exports ( _X_ ) of sector _k_ in j’s total exports relative to the world average share of the same sector _k_ in world exports as follows: where G is the total number of countries in the world. The RCA measure has been used extensively in the literature to measure the competitiveness of a country in a particular sector. When the RCA exceeds one, the country is deemed to have a revealed comparative advantage in that sector; when it is below one, the country is deemed to have a revealed comparative disadvantage in that sector.

Koopman, Wang, and Wei (2014) and Wang, Wei, and Zhu (2013) point out that the traditional RCA ignores both domestic production sharing and international production sharing. First, it ignores the fact that a country-sector’s value added may be exported indirectly via the country’s exports in other sectors. Second, it ignores the fact that a country-sector’s gross exports partly reflect foreign content. A conceptually correct measure of comparative advantage needs to exclude foreign-originated value added and pure double counted terms in gross exports, and to include indirect exports of a sector’s value added through other sectors of the exporting country. When a country uses imported intermediate goods intensively to produce for its exports, Koopman, Wang and Wei (2014) show that RCA based on gross exports can be misleading. The problem of double counting of certain value added components in the official trade statistics suggests that the traditional computation of RCA could be noisy. The gross export decomposition method suggested by Koopman, Wang and Wei (2014) provides a way to remove the distortion of double counting by focusing on domestic value-added in exports. Following Wang, Wei, and Zhu (2013), we calculate RCA based on _domestic valued added (DVA) in gross exports_ , rather than gross exports, for country i in sector k as follows ( _i_ = 1, 2, ..., G; _k_ = 1, 2, ..., N).

The above new RCA measure is the share of a country-sector’s forward linkage-based measure of domestic value added in exports in the country’s total domestic value added in exports relative to that sector’s total forward linkage-based domestic value added in exports from all countries as a share of global value added in exports. The domestic value added (DVA) in gross 11
3 sections on desired goals for the country. The 1974 Yugoslav constitution, for example, has over 400 articles on over 160 pages.8 The federalist structure of Yugoslavia gave the Republics extensive powers over the legal frameworks within their jurisdictions, especially under the federal constitution of 1974. In addition to the federal constitution, each republic had its own constitution. Slovenia's most recent socialist constitution dates from 19Y4, with amendments in 1981, 1989, 1990, and 1991.9 Federal law was supposed to set the basic legal foundation in any particular area, with specifics regulated by republican law; for example, federal law set the foundations of the tax system, with specific rates and regulations set by the republics. In case of conflict the federal law had priority, but the Republics began to question this priority as tensions developed in the late 19808.

# Movee toward Independence

0 The 1990 and 1991 amendments to the Slovene constitutionlwere designed to further reforms toward a market economy and set the stage for the ultimate independence of Slovenia. For example, amendment 91 in March 1990 deleted the word "Socialist" from the Republic's title. Amendment 96 in September 1990 reversed the priority of laws in cases of conflict, stating that articles of the Federal constitution would not apply if not in accord with the Slovene constitution, and that new federal laws, regulations, and acts of federal authorities would be valid in Slovenia only after a?proval by the Slovene Parliament. Old Yugoslav laws were implicitly still valid unless specifically rejected by Parliament. More than 200 Yugoslav laws implicitly remained in force.

8 The U.S. Constitution, in comparison, has 7 articles with 20 sections on 16 pages.

9 Ustava Socialistibne Republike Slovenije [Constitution of the Socialist Republic of Slovenia], Uradni list Socialistifne republike Slovenije (Official Gazette of the Socialist Republic of Slovenia] (hereinafter "Official Gazette SRS"), No 6 (1974). Ustavni amandmaji k ustavi SRS (Constitutional Amendments to the Constitution of the Socialist Republic of Slovenia], Official Gazette SRS, No 22 (1981) Amendments I-VII; No 32 (1989) Amendments VIII-LXXXIX; No 8 (1990) Amendments XCI-XCV; Official Gazette RS, No 35 (1990) Amendments XCVI-XCVIII, No 7 (1991) page 282, Amendment XCIX; No 1 (1991), Amendment C. (Upon declaring independence, Slovenia began renumbering the issues of its official gazette from the beginning.) 10 Supre note 9.
-46-

with poverty, particularly high infant mortality rates<sup>76</sup> . Having extra children "..can be interpreted as the insurance response parents<sup>make in the</sup> face of high infant mortality. As the risk of infant mortality declines, these excess births should become unnecessary" (Birdsall and Griffin,<sup>1988, p.</sup> 36). Thus, it appears that fertility declines follow reductions in infant mortality<sup>77</sup> . Higher infant mortality, in addition, increases the number of pregnancies for extremely-poor females since: (a) more children are<sup>wanted</sup> and, (b) more replacement births are required to attain the<sup>desired family</sup> size. This increases the dependency ratio, as female members retire from active participation in work during childbirth and lactating periods.<sup>Higher</sup> fertility, however, may also be due to lack of education and access to birth control methods. Hence, unwanted pregnancies are higher. Unwanted pregnancies that lead to abortions are an additional burden on the health<sup>and</sup> nutritional status of females<sup>78</sup> ; those that lead to children, on the other hand, further increase the dependency ratio.

76See Mina Valdez (1988) for a study of infant mortality in Mexico. In particular, see his table 5, p. 280, where average infant mortality rates<sup>for</sup> the period 1965-79 for eight 'social classes' are computed as follows: bourgeoisie, 36.5; new petty bourgeoisie, 30.2; traditional petty bourgeoisie, 54.1; non-wage free laborers, 57.3; typical proletariat, 59.2; un-typical proletariat, 53.5; peasants, 81.2; agricultural proletariat, 96.7. While<sup>it</sup> is difficult to interpret some of these social classes, these numbers<sup>do</sup> roughly indicate a strong association between lower income and high infant mortality. Also, the World Bank (1989b, p. 42) estimates infant mortality rates in Mexico per live births of 20/1000 in the metropolitan areas<sup>vs.</sup> 80/1000 in backward rural areas. Finally, a 1982 nutrition survey<sup>in rural</sup> areas of Oaxaca found that women average nine deliveries during their childbearing years, with only five children surviving to<sup>adulthood (Torche,</sup> 1990, p. 13).

77There is, of course, a lag between the drop in infant mortality and the behavioral response of parents to limit family size and increase investments per child; this lag is sometimes referred to as the 'demographic transition', and explains why in most LDC's death rates fell long<sup>before birth rates.</sup> Policy can influence this lag be reducing child mortality<sup>and increasing</sup> income security (cf. Birdsall and Griffin, 1988, p.<sup>37).</sup> 78Preliminary results from the 1988 National Nutrition Survey show that one-third of all pregnant women have an inter-birth<sup>interval of less than 24</sup> months, and that women with short birth intervals have significantly<sup>worse</sup> hemoglobin levels (World Bank, 1990a, p. 3).
# **Table 6: IV analysis**

||**Panel A: 1st stage regressio**<br>|**ns**<br>|
|---|---|---|
||Rule of law|Human capital|
|Distance|36.57<sup>**</sup>|1.53<sup>***</sup>|
||(17.48)|(0.58)|
|Log (settler|<br>-7.75<sup>***</sup>|-0.24<sup>***</sup>|
|mortality)|(2.04)|(0.07)|
|European lan|guage<br>7.11|0.59<sup>***</sup>|
|(%)|(5.37)|(0.18)|
|Constant|74.18<sup>***</sup>|3.26<sup>***</sup>|
||(12.20)|(0.40)|
|R-squared|0.52|0.62|
|N|59|59|
|**Panel B: Te**|**sts of overidentifying restric**<br>|**tions**<br>|
||Sargan|Basmann|
|chi2(1)|0.37|0.34|
|p-value|(0.55)|(0.56)|
||**Panel C: 2nd stage regressi**|**on**|
||Intangible capital||
|Rule of law|2,326||
||(3,190)||
|H|77,921||
||(78,161)||
|Constant|-266,511<sup>***</sup>||
||(64,854)||
|R-squared|0.58||
|N|59||

28
UN’s forecast of demographic trends for Angola, which suggests that population growth will fall from about 3 percent in 2020 to 2 percent by 2050. The workingage population is predicted to rise from 52 percent of total population in 2020 to 58 percent in 2050. Moreover, based on recent trends, the labor force participation rate is assumed to remain constant at around 80 percent of the working-age population until 2050 (WB-WDI).

**Table 3: Baseline calibration to Angola (Default model)** <u>Selected Parameters, Initial Conditions & Trajectories of Exogenous Variables</u>

||**VALUE**|**SOURCE**|**TIME SERIES**|
|---|---|---|---|
|_A. Parameters_<br>||||
|Depreciation rate (δ) <br>|4.4%|PWT 10|2000-2019 average|
|Labor share total (β<sup>PWP</sup>)|0.34|PWT 10|2015-2019 average|
|Labor share, non-oil (β)|0.56|Calculation|2015-2019 average oil share|
|Oil rents (γ)<br> <br><br>|0.33|GTAP|Median oil-exporters 2004-14|
|_Government:_<br><br>||||
|Tax rate in oil sector (τR)<br><br>|0.7|IMF-WCE|2001-2013 average|
|LR public investment (e)<br>|6→2% of GDI|IMF-FAD|2015-2017 average|
|MPI (θ)<br>|0.2<br>|IMF-FAD|BBR: 2000-2017 average;<br>SSR (θ = 0);HR (θ = 1)|
|Sectoral investment elasticity (μ)|1|Assumption||
|_B. Initial conditions_<br>||||
|Real GDP per capita<br>|US$2,890*|WB-WDI|2020|
|Exports of oil(I= 1)|50.8% of GDP|UN-CT|2007-2015 average|
|<br>_Capital to GDP ratio:_|2|PWT/MFMod|2011|
|<br>Non-oil sector|1|Endogenous|Equalize initial MRPKs|
|Oil sector|1|Endogenous|Equalize initial MRPKs|
|Reserves of oil|9.5 Bi/barrels|BP-Energy|2017|
|Participation rate,_% of working_|_-age population_|||
|Male / Female|80.2 / 76.4|WB-WDI|2017|
|Base year for oil prices|2010||User choice|
|Initial year of simulation|2020||User choice|
|_C. Trajectory of exogenous var_<br>|_iables, 2023-2050_<br>|<br>||
|Price of oil|US$50/barrels|World Bank|Estimated mean 1960-2019|
|Private investment|20% of GDI|IMF-FAD|2000-2017 average|
|TFP growth, non-oil sector|1%|PWT 10|Median of LMCs, 2000-19|
|TFP growth, oil sector|0%|PWT 10|Median oil exporters, 2000-19|
|Human capital growth|0.7%|PWT 10|2000-2019 average|
|Oil Discoveries||||
|Baseline & Discovery Shock|400m bbl/year|BP-Energy|25<sup>th</sup>percentile 1990-2017|
|Price shock|Endogenous**|Assumption||
|_Demographics:_||||
|Population growth|3.4→2.3%|ILO|Forecast for 2023–2050|
|Working-age population|51→59% pop.|ILO|Forecast for 2023–2050|
|Population, male|49.1% of pop.|ILO|Forecast for 2023–2050|
|Participation rate(M&F)|≈0 growth|WB-WDI|2000-2019 average|

*Real US Dollars of 2010. **Discoveries are set to keep reserves constant in per worker terms.

26
# **References**

- Acevedo, P., G. Cruces, P. Gertler, and S. Martinez (2017): “Living Up to Expectations: How Job Training Made Women Better Off and Men Worse Off,” _NBER Working Paper No. 23264_ .

- Adoho, F., S. Chakravarty, K. Jr, D. T., M. Lundberg, and A. Tasneem (2014): “The Impact of an Adolescent Girls Employment Program: The EPAG Project in Liberia,” _World Bank Policy Research Working Paper, no. 6832_ .

- Alzu ́a, M. L. and P. Brassiolo (2006): “The impact of training policies in Argentina: an evaluation of Proyecto Joven,” _Inter-American Development Bank Working Paper_ .

- Attanasio, O., A. Guar ́ın, C. Medina, and C. Meghir (2017): “Vocational Training for Disadvantaged Youth in Colombia: A Long-Term Follow-Up,” _American Economic Journal: Applied Economics_ , 9, 131–143.

- Attanasio, O., A. Kugler, and C. Meghir (2011): “Subsidizing Vocational Training for Disadvantaged Youth in Developing Countries: Evidence from a Randomized Trial,” _American Economic Journal: Applied Economics_ , 3, 188–220.

- Betcherman, G., K. Olivas, and A. Dar (2004): “Impacts of Active Labor Market Programs: New Evidence from Evaluations with Particular Attention to Developing and Transition Countries,” _Social Protection Discussion Paper, World Bank, Washington, DC._

- Blattman, C. and L. Ralston (2015): “Generating employment in poor and fragile states: Evidence from labor market and entrepreneurship programs,” Columbia University, Mimeo.

- Caliendo, M., S. K ̈unn, and R. Schmidl (2011): “Fighting Youth Unemployment: The Effects of Active Labor Market Policies. IZA DP No. 6222,” _Institute for the Study of Labor_ .

27
Siegel, Jeremy. 1992. "The Real Rate of Interest from 1800-1990." _Journal of Monetary Economics 29:_ 227-252.

Smeeding, Timothy (Luxembourg Income Study), Director. 1991. "Cross National Patterns of Retirement and Poverty among Men and Women in the 1980s: Full Stop or GradualWithdrawal?..". Luxembourg Income Study (October).

- "Why the US Antipoverty System Doesn't Work Well." 1992. _Challenge_ (January-February): 30-5.

Social Insurance Agency. Japanese Govermnent 1990. Outline of social insurance in Japan, 1990. Japan.

Social Security Administration. 1991. _Social Security Programs Throughout the World._ Washington D.C.: US Department of Health and Human Services.

South Africa, Government of. 1992. _Mouton Report._ Johannesburg.

Stahlberg, Ann-Charlotte. 1989. "Redistribution Effects of Social Policy in a Lifetime Analytical Framework." In Gustaffson and Klevmarken (1989). The Political Economy of Social Security. North Holland: Elsevier Science: 51-60.

State Institute of Statistics Prime Ministry Republic of Turkey. 1990. Statistical Yearbook of Turkey, 1990 Turkey: TIY.

Statisticni Letopis, Republike Slovenije, 1992 Letnik XXXI, Ljubljana 1993 (transl. Milan Vodopivec).

Sunden, Annika and Olivia Mitchell. Administrative Cost Analysis of the U.S. Social Security Administration; Unpublished.

Superintendencia de AFPs (Banco Central de Chile). 1993. _Informe Anual._ Santiago, Chile: Banco Central de Chile.

_Sweden: Social Insurance Statistics._ Stockholm, 1989.

Szalchman, Raquel and Andras Uthoff. 1992. "Sistema de Pensiones en America Latina: Diagnostico y Alternativas de Reforma." Comision Economica para America Latina, Santiago, Chile.

_Tanzanian Economic Survey._ 1991. November 1992. The Planning commission, Dar es Salaam.

TASPEN. 1990. Company Profile.

Turner, J. and D. Beller. 1989. _Trends in Pensions_ (annual). Washington, D.C.: U.S. Department of Labor.

Turner, John, and Lorna Dailey. 1991. _Pension Policy: An International Perspective._ Washington, D.C.: US Department of Labor.

138
29 Table 8 contains Edwards' 39 episodes classified according to this criterion. As can be seen, among the 29 stepwise devaluers, there are 13 clearcut successful cases, 9 clearcut failures and 7 limited-success cases. For the 10 crawlers there are three successful episodes, five unsuccessful ones and two cases of limited success. The 13 successful stepwise devaluers (Panel A.1 of Table 7) were able to sustain substantial real depreciations in the medium term. The average for the effectiveness Lndex after 3 years is 0.66 indicating that on average 2/3 of these nominal devaluations had been transmitted into a real devaluation. For these 13 countries as a group, 3 years after the crisis the RER stood on average 66% higher than its value immediately before the devaluations. For the 9 stepwise cases with limited success (Panel A.2 in Table 7) the average value of the effectiveness index is still an impressive 0.49. On the whole, then, this evidence strongly shows that for a large number of cases nominal devaluations have been helpful in generating real exchange rate realignments.

For the 9 unsuccessful stepwise episodes, on the other hand, the index of devaluation effectiveness had an average of -0.21 three years after the crisis, indicating that at that time the _RER_ was more then 20% ba1l its value immediately prior to the crisis. For these cases devaluations not only failed to generate a real exchange realignment, but even worse, three years after the event the magnitude of the external disequilibrium had greatly increased. In fact, for tbese countries in the three years following the devaluation the net foreign assets ratio declined on average by more than 10%.

Discriminant analy_is was used to test whether it was possible to statistically discriminate among successful and unsuccessful groups based on _the_ behavior of macroeconomic variables only. The two gro4ups of countries
**Figure 1: Predicted Poverty Rates by Interview Mode Using Different Levels of Poverty lines**

<!-- Start of picture text --> 50000 100000 150000 200000 250000 300000<br>Poverty line<br>CATI in urban CATI in rural<br>F2F in urban F2F in rural<br>.8<br>.6<br>.4<br>.2<br>0<br><!-- End of picture text --> Source: The authors’ estimation using data from the pilot. Note: Vertical lines are the two poverty lines that are used in table 8.

# **5.3 Resource Considerations**

The cost of implementing the survey experiment was relatively inexpensive. A total of $28,400 was used for the survey implementation, including recruitment and training of field enumerators and telephone operators, sample selection, piloting the questionnaire, programming of the data entry software for CATI, etc. An additional $30k was allocated for technical assistance to supervise the experiment, including consultant fees for a survey expert and trip costs.

In terms of time required to complete the interviews, the average length of the interviews ranged from 5 to 12 minutes. The median times for the interviews by area and interview mode are shown in Table 9. For the F2F survey and CATI baseline, interviewers manually recorded the start and end times of the interviews. By contrast, the times for the telephone interview were recorded automatically by the CATI computer program. As each interview would require an introduction to explain the purpose of the survey and to identify the appropriate respondent, much of the CATI baseline and F2F survey interview time would be for these activities and not just for asking questions and recording responses. It should be noted that the sum of the median times for the CATI pre-interview and interview stages is similar to time for the F2F interviews.

It is also worth noting that a total time needed for the survey implementation was short. The preparation of this survey started in March 2013 and was completed by late June 2013. The 20
Policy Research Working Paper 10315

# **Abstract**

Do income shocks locally affect internal conflicts? To address this question, this paper employs a meta-regression analysis of 2,464 infranational estimates from 64 recent empirical studies on conflicts and income-related shocks in developing countries. After accounting for publication selection bias, the analysis finds that, on average, wealth-increasing shocks in the agriculture sector are negatively associated with the local risk of conflict. Nonetheless, the analysis finds no average effect of wealth-decreasing shocks in the agriculture sector or wealth-increasing shocks in the extractive sector on the local risk of conflict. The paper also shows that studies that fail to uncover empirical effects that conform to researchers’ expectations on the theoretical mechanisms are less likely to be published. Differences in the geographical area of study, the choice of control variables, and the way shocks are measured substantially explain the heterogeneity among estimates in the literature.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at pmandon@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team