rafmacalaba/datause-encoder-data huggingface dataset:
letter issued by the Ministry of Youths and Sports approving the study. The issue was resolved, and respondents were informed through text messages that they needed a valid travel document to take up migration to Dakar. According to the follow up survey, the main reasons for not migrating to Dakar included being unable to redeem the vouchers for cash (28 percent), too many responsibilities in the village (13 percent), not enough information about the offer (10 percent), unable to afford the costs of staying (10 percent), not interested in working in Dakar (7 percent), working (5 percent), not trusting the offer (4 percent), and studying (4 percent).

These logistical issues suggest that facilitating large regional international migration flows may require offering potential migrants more assistance than was needed to facilitate internal migration in Bryan et al. (2014). A more intensive intervention could also provide financial and logistical assistance for finding housing, and potentially connect migrants to employers before moving to ensure that they have jobs ready to start upon moving. Such assistance could be potentially more important when facilitating migration to places where there is not a strong existing network that migrants could otherwise use to help find jobs, housing, and other support.

The final treatment was the tuition-free vocational training program. Out of the 892 respondents assigned to this treatment, 680 (about 76 percent) of them said they were interested in participating in the training program. In collaboration with The Gambia Technical Training Institute (GTTI), training was scheduled for September 2019, and would last for six months. The training finally started on 25 November 2019. The reason for the delay of the training program was due to respondents’ preference. They requested that the training start at the end of the rainy season as the majority of them were engaged in farming activities, and were unable to leave their farms to engage in the training program. 105 participants (12 percent) enrolled in training. In feedback from monthly surveys of beneficiaries participating in the training program, they complained about financial pressures in sustaining themselves while studying, and so we added a monthly stipend of 1,000 GMD conditional on regular attendance. The COVID-19 pandemic resulted in the closure of all educational programs in the country as of 18<sup>th</sup> March 2020. This resulted in a nine-month suspension of the GTTI training program partway through the program. The training program was then resumed in January through July 2021. Only half the participants returned, with 49 respondents participating throughout training and 31 of them being certified by the program. Youth in this treatment group indicated several reasons for not taking up the training offer. The main reason was due to too many responsibilities in their home villages (33 percent), while the other 20
# Appendix B: Item-level sensitive response shares analysis

## **Personal exposure to conflict events**

|**Question**|**Share of r**<br>**choosing**<br>**that indi**<br>**severe ou**<br>_PPCS_|**espondents**<br>**responses**<br>**cate more**<br>**tcomes (%)**<br>_Facebook_|**Difference**<br>**(Percentage**<br>**point)**|<br>**N**<br>**(combined)**|
|---|---|---|---|---|
|Have you been injured due to Israeli airstrikes or|1.01|9.29|8.28|2929|
|clashes with Israeli security forces in May 2021?|(0.20)|(1.52)|(1.53)||
|Has a household member of yours died due to|0.23|6.22|5.98|2933|
|Israeli airstrikes or because of clashes with Israeli<br>security forces in May 2021?|(0.09)|(1.26)|(1.26)||
|Was any other household member injured in|1.37|11.26|9.90|2927|
|Israeli airstrikes or clashes with Israeli security|(0.27)|(1.66)|(1.68)||
|forces in May 2021?|||||
|Did an extended family member or close friend die|10.53|32.08|21.54|2934|
|due to Israeli airstrikes or clashes with Israeli<br>security forces in May 2021?|(1.16)|(2.43)|(2.69)||
|Was an extended family member or close friend|10.22|38.04|27.82|2931|
|injured in Israeli airstrikes or clashes with Israeli|(0.90)|(2.53)|(2.69)||
|security forces in May 2021?|||||
|Was your workplace demolished or damaged due|2.26|35.91|33.64|2900|
|to Israeli airstrikes in May 2021?|(0.32)|(2.62)|(2.64)||
|Was your home destroyed or damaged due to|26.65|36.39|9.74|2923|
|Israeli airstrikes in May 2021?|(1.93)|(2.54)|(3.19)||
|_Average _|7.47|24.17|16.70|2925|

Notes: Responses indicating more severe outcomes are operationalized in this module as responses of “Yes”. Contingent questions (following up on the answers to the last two questions) have been excluded. Estimates are unweighted, and clustered standard errors are reported in parentheses.

|**A**<br>**Statement**|**ggression**<br>**Share of r**<br>**choosing**<br>**that indi**<br>**severe ou**<br>_PPCS_|**espondents**<br>**responses**<br>**cate more**<br>**tcomes (%)**<br>_Facebook_|**Difference**<br>**(Percentage**<br>**point)**|**N**<br>**(combined)**|
|---|---|---|---|---|
|Given enough provocation, I may hit another|16.64|16.68|0.04|6859|
|person.|(0.84)|(1.19)|(1.46)||
|I often find myself disagreeing with people.|24.63|40.12|15.50|6853|
||(1.06)|(1.57)|(1.89)||
||28.83|59.28|30.45|6851|

21
- 35 -

In total employment unless agricultural output grows by at least 3.25 percent per annum.

64. Note that growth In nonfarm employment contributes relatively more to the Increase In total employment when agricultural growth Is low and/or has a low employment elasticity. It will be particularly Important In helping to absorb projected increases In the rural labor force If agriculture grows at less than 2.4 percent, especially If future growth Is focused on rainfed a agriculture.

65. For hlgh rates of agricultural growth, Table 15 suggests that total employment would quickly outstrip the growth In the total rural plus rural towri labor force. The surplus labor demand would clearly have to be resolved through higher wage rates or urban-rural Irrlgatlon, neither of which Is adequately captured In our model.
method is required prior to the auction. Consistently, our estimation results show that good governance is a key to help mitigate the renegotiation risk.

<u>Table 13. Alternative First-Stage Regressions</u>

||Linear|Linear|Probit|
|---|---|---|---|
|Unemployment|0.0199 <sup>*</sup>|0.0373 <sup>**</sup>|0.1194 <sup>*</sup>|
||(0.0107)|(0.0178)|(0.0623)|
|Poverty headcount ratio|0.0517<br>(0.0390)|||
|Gini coefficient|-0.0464|||
||(0.0319)|||
|Govt effectiveness|1.3080 <sup>*</sup><br>(0.6822)|||
|Regulatory quality|-1.6701<br>(1.2286)|||
|Control of corruption|0.5724 <sup>*</sup><br>(0.3159)|||
|Argentina||-0.4486 <sup>***</sup>|-1.2678 <sup>***</sup>|
|||(0.1709)|(0.4999)|
|Bolivia||-0.6310 <sup>***</sup><br>(0.1264)||
|Brazil||-0.7479 <sup>***</sup><br>(0.1407)||
|Colombia||-1.0623 <sup>***</sup><br>(0.2564)||
|Mexico||-0.5517 <sup>***</sup><br>(0.1302)||
|Peru||-0.4940 <sup>*</sup>|-1.3621 <sup>*</sup>|
|||(0.2569)|(0.7687)|
|Uruguay||-0.7953 <sup>***</sup><br>(0.1522)||
|Constant|3.2345|0.4369 <sup>***</sup>|-0.3060|
||(2.2658)|(0.1531)|(0.4606)|
|Obs.|123|123|54|
|_F_statistics|8.25|...||
|R-squared|0.3790|0.4079||
|Wald test statistics|||7.32|
|Pseudo R-squared|||0.1152|

Note: The dependent variable is the binary variable for the multidimensional auction selection. The robust standard errors are shown in parentheses. *, ** and *** indicate the 10%, 5% and 1% significance levels, respectively.

# **7. CONCLUSIONS**

Multidimensional auctions are a natural and practical solution when auctioneers pursue more than one objective in their PPP-related transactions. Both in theory and practice, however, it seems difficult to achieve auction efficiency with multiple award criteria.

With auction data on road and railway concessions in Latin America, the paper aimed to estimate the impact of adopting the multidimensional format by a two-stage least squares technique with a binary selection in the first-stage regression. One of the 24
REFERENCE S Bentkover, J.D., V.T. Covello, and J. Mumpower.<sup>1985. Benefits Assessment: the State of the Art.</sup> D. Reidel Publishing Co., Dordrecht, Netherlands.

Bojo, J.,K-G Maler, and L. Unemo. 1990. Environment<sup>and Development: an Economic Approach.</sup> Klower Academic Publishers, Netherlands.

Brajer, V., J.V. Hall, and R. Rowe. 1991.<sup>The Value of Clean Air: an Integrated Approach.</sup> Contemporaiy Policy Issues, Vol.9, 81-91.

Chestnut, L.G.,and R.D. Rowe. 1988. Ambient Particulate<sup>Matter and Ozone Benefit Analysis for</sup> Denver. RCG/Hagler, Bailly,Inc.,Prepared for the<sup>U.S.Environmental Protection Agency, Boulder.</sup> Crosson, P.R. and A.T. Stout. 1983. Productivity<sup>Effects of Cropland Erosion in the United States.</sup> Resources for the Future, Washington D.C.

De la Burde, B. and M.S. Choate Jr. 1975. Early<sup>Asymptomatic Lead Exposure and Development</sup> at School Age. Journal of Pediatrics, Vol.87, 638-642.

Diaz, F.G. January 1987. Debt Accumulation<sup>and Distorted Growth Through Subsidized Public</sup> Sector Prices. UK Economic and Social Research Council<sup>and The World Bank.</sup> Environmental Protection Agency. February<sup>1985. Costs and Benefits of Reducing Lead in</sup> Gasoline: Final Regulatory Impact Analysis. Washington,<sup>D.C.</sup> Enviromnental Protection Agency. June 1986. Air Quality<sup>Criteria for Lead. Environmental Criteria</sup> and Assessment Office, Cincinnati, OH, Vols.I-IV, EPA<sup>600/8-83/028dF.</sup> Evans, J., T. Tosteson, and P.L. Kinney. 1984. Cross-Sectional<sup>Mortality Studies and Air Pollution</sup> Risk Assessment. Environment International,<sup>Vol. 10, 55-83.</sup> Ferris, B.G.Jr. May 1978. Health Effects of Exposure<sup>to Low Levels of Regulated Air Pollutants:</sup> A Critical Review. J.Air Pollution Control Assoc.,<sup>Vol.28, 482497.</sup> Harrington, W., A.J. Krupnick, and W.O. Spofford,<sup>Jr. 1991.Economics and Episodic Disease: the</sup> Benefits of Preventing Giardiasis Outbreak. Resources<sup>for the Future. Washington, D.C.</sup> Hirschhorn, N. and W.B. Greenough III. May<sup>1991. Progress in Oral Rehydration Therapy.</sup> Scientific American, Vol.264, No.5, 50-56.

25
30 Table 4. Estimating the Determinants of International Migration

|||De<br>|pendent Variable =<br>|Migrants as Shareo<br>|f Country Populati<br>|on<br>||
|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|Distance (miles) from country to labor-<br>receiving region (US, OECD or Arab Gulf)|-1.171<br>(-6.88)**|-1.406<br>(-6.99)**|-1.535<br>(-6.00)**|-0.985<br>(-4.86)**|-1.045<br>(4.13)**|-0.952<br>(-4.86)**|-1.006<br>(-4.13)**|
|Economic variables||||||||
|ii ffii||1.008|0.050|2.313|1.518|2.447|2.058|
|Gn coecent||(1.39)|(0.05)|(3.37)**|(1.81)*|(3.68)**|(2.53)*|
|||16.963||14.498||13.133||
|Per capita GDP (constant 1995 dollars)||(4.51)**||(4.00)**||(3.68)**||
|Per capita GDP<sup>2</sup>||-1.183<br>(-4.60)**||-1.004<br>(-4.08)**||-0.892<br>(-3.70)**||
||||0.123||0.289||0.225|
|Poverty headcount ($1/person/day)|||(0.72)||(1.70)||(1.44)|
|<sup>2</sup>|||-0.035||-0.050||-0.063|
|Poverty headcount|||(-0.73)||(-1.12)||(-1.39)|
|||-0.111|<br>-0.186|-0.047|<br>-0.071|-0.073|<br>-0.076|
|Rate of consumer inflation||(-1.27)|(-1.80)*|(-0.59)|(-0.76)|(-0.95)|(-0.86)|
|f l i l f||-0.004|0.360|-0.119|0.166|-0.123|0.115|
|Rate o unempoyment n abor orce||(-0.002)|(1.60)|-(0.64)|(0.78)|(-0.66)|(0.55)|
|Demographic variables<br>||||0.777|0.880|0.783|0.852|
|Population density (people per sq km)||||(5.08)**|(5.20)**|(4.99)**|(4.96)**|
|Share of population over age 25 with||||<br>0.614|<br>0.829|<br>0.581|<br>0.754|
|secondary education||||(2.57)**|(3.20)**|(2.49)**|(3.00)**|
|Political, Financial variables||||||||
|Government stability||||||0.419<br>(1.36)|0.518<br>(1.54)|
|Country credit rating||||||<br>-0.595<br>(-1.81)*|<br>-0.631<br>(-1.97)*|
||7.224|-48.615|9.811|-47.836|1.212|<br>-42.804|<br>3.270|
|Constant|(5.16)**|(-3.67)**|(3.72)**|(-3.64)**|(0.41)|(-3.35)**|(0.98)|
|N|<br>121|<br>94|<br>88|<br>91|<br>85|<br>88|<br>82|
|Adj R<sup>2</sup>|0.470|0.580|0.489|0.671|0.625|0.685|0.649|
|F-Statistic|18.75|12.68|8.56|15.15|11.79|13.66|10.99|

Notes: Estimates obtained using ordinary least squares. All variables based on labor-exporting country and expressed in logs. T-ratios shown in parenthesis; coefficients for regional dummies not reposted. Number of observations reduced for certain equations because of missing values. See Annex Table A1 for countries and survey dates.

* Significant at the 0.10 level.

** Significant at the 0.05 level.
# **Table 13: Panel Regression on Life Satisfaction and Migration**

||**xt.O**|**LS: Life Satisfa**|**ction (1-5)**|**xt.O**|**LS: Low Satisfa**|**ction = 1**|
|---|---|---|---|---|---|---|
||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|
|Considering Migration|-0.160***|||0.054***|||
||(0.043)|||(0.017)|||
|Current Migrant||0.019|||0.000||
|||(0.032)|||(0.010)||
|Daily Contact with Migrant|||0.158***|||-0.033***|
||||(0.044)|||(0.012)|
|Several Times a Week Cont.|||0.078*|||-0.005|
||||(0.045)|||(0.014)|
|Weekly Contact|||0.102**|||-0.021|
||||(0.052)|||(0.014)|
|Twice Month Contact|||-0.004|||-0.008|
||||(0.078)|||(0.027)|
|Constant|3.222***|3.215***|3.133***|0.035***|0.037***|0.053***|
||(0.012)|(0.013)|(0.064)|(0.004)|(0.005)|(0.021)|
|Number of observations|12,137|12,137|1,645|12,137|12,137|1,645|
|Calendar Month FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Household FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Adjusted R2|0.021|0.018||0.032|0.031||
|r2_w|0.021|0.019|0.010|0.033|0.031|0.048|
|r2_o|0.012|0.012|0.040|0.022|0.021|0.041|
|r2_b|0.000|0.001|0.043|0.004|0.005|0.029|
|sigma_u|0.454|0.453|0.403|0.152|0.152|0.140|
|sigma_e|0.559|0.560|0.609|0.214|0.214|0.213|
|rho|0.397|0.396|0.305|0.337|0.336|0.301|

_note: .01 - ***; .05 - **; .1 - *; Panel regression; Standard errors clustered by household; Control for month of interview;_ 28
Europe and 62 percent in Australia. They are the principal vector for the spread of HIV in a number of countries. Cocaine is the biggest problem drug in the Americas, accounting for 58 percent and 40 percent of total drug treatment in South America and North America, respectively.

The paper begins by providing a description of how consumption, production and trafficking are distributed among countries. The following section offers some hypotheses about why both production and trafficking are so concentrated in so few countries. It then describes the ways in which governments have attempted to reduce both production and trafficking and summarizes what is known about the effectiveness of the different methods used. It concludes with comments about some major research questions.

# **1.  ILLICIT DRUG TRENDS AND DEVELOPING COUNTRIES**

This section provides background on the levels and trends in cocaine and heroin consumption; it shows which countries are most important and summarizes indicators of drug use in major developing countries.

# **CONSUMING COUNTRIES**

There are no reliable data on the worldwide consumption of illicit drugs. The United Nations Office on Drugs and Crime (UNODC) reports the prevalence of illicit drug use through surveys of countries’ governments in its annual _Global Illicit Drug Trends_ . But with exception of the United States and (more recently) a few other industrialized nations,<sup>3</sup> countries have not developed the necessary capability to collect such information (and some have little desire to do so). Thus the UNODC survey responses suffer from lack of data, varying estimation methodologies across different countries, and biases that governments bring to the reporting of the level of consumption.<sup>4</sup> According to the UNODC (2003, pp. 101-102), cannabis is the most widely abused drug worldwide (around 160 million people) followed by amphetamine-type stimulants (35 million people). Approximately 15 million people abuse cocaine, and a similar number abuse opiates;

> 2001).  The _World Drug Report_ contains estimates of “wholesale revenues” but it is unclear what share should be assignedto developing nations.

> 3 Among those that regularly now both conduct general population surveys and attempt to estimate the number of “problematic” drug users, a term coined by the European Monitoring Center on Drugs and Drug Abuse, are: Australia, the Netherlands, Switzerland and the United Kingdom.  There are good quality data from school surveys of 15-16 year olds in most European nations; The European School Project on Alcohol and Other Drugs: (ESPAD) can be found at www.espad.org

> 4 On occasion there are gross inconsistencies that undermine confidence; for example, a nation might report more opiate addicts than opiate consumers or wholesale purity that is lower than retail purity.

2
# **5.3. The interplay of decentralization and local governance**

In Table 7, we report the coefficient estimates on the interplay between decentralization and corruption, and their confoundedness in explaining how natural resources endowment affects citizens’ perception of the state’s delivery of public goods and services. More precisely, we analyze how the negative marginal effect of the incidence of bribe payment (Table 5) and the positive marginal effect of Decentralization (Table 6) comes into play in the relationship between natural resources endowment and citizens’ perception of government performance as well as their outlook on the future.

For residents living near active mines, the results indicate that the positive marginal effect of decentralization is reduced by the incidence of corruption on the perception of government performance on improving living standards, improving water & sanitation, job creation, health and education, and public services as a whole. The incidence of bribe payment statistically and significantly reduces the positive marginal effects of decentralization.

Figure 3 and Figure 4 illustrate the local effects of active mining and the interplay of decentralization and the incidence of bribe payment. We illustrate these effects and the interplay for the individual assessment of government performance in improving living standards and public services delivery. We do so by following the methods prone by Dawson and Richter (2006). We first compute the slope of the dependent variable (improving living standards or public services delivery) on the independent variable (active 50 km) when the moderators (decentralization and bribe) are held constant at different combinations of high and low values. In addition, we test the differences among all pairs of slopes by using the ‘ _pwcompare(effects)_ ’ option of the ‘ _margins_ ’ command in Stata 16 (StataCorp., 2019).

The results of the pairwise comparisons are reported in Table 8 and Table 9. For both outcome variables, we found that, regardless of the level of decentralization (high or low), a high incidence of bribe payment leads to the worse impact of natural resources on individual perception of government performance. On the other hand, when corruption is low, a higher level of decentralization is preferable. By extension, when decentralization is low, a lower incidence of bribe payment is preferable. The pairwise comparison of these slopes is confirmed by the graphical analyses.

Poverty alleviation is the prime focus of the policy agenda in most African countries. Natural resources and the extractive industries have the potential of providing significant revenues for the government to implement pro-welfare policies, especially within resource-rich communities. Figure 5 further illustrates the interplay of local institutions and local taxing rights for both active and inactive mining areas. The probability of a positive appraisal of government performance in resource-rich communities more generally is the highest when the level of local taxing rights is 23
course this also implies that excess external imbalances have to be managed as their fruits are less supportive of growth.

<!-- Start of picture text --> Figure 1. Absolute Convergence and Excess Growth in Europe Prior to the Crisis<br>Convergence among European Countries Actual vs. Predicted Growth<br>(1997-2008) (2005-2008)<br>GEO<br>ARM<br>10 10 BLR<br>BIH<br>8 8<br>ARM BIH<br>MNE<br>SVKLTULVA BGRROM<br>6 LVAPOLEST SVK BLRSVN IRL 6 SVNCZE ESTPOLHRV UKRSRB ALB<br>4 4<br>GRCESPFIN LUX FINGRC<br>AUTESP<br>2 MDA TURMNEMKDSRB UKR PRT FRAITADEU 2 FRA PRT<br>ITA<br>0 0<br>7 8 9 10 11 1 2 3 4 5 6<br>Initial Level of Income, in logs Predicted Growth, %<br><!-- End of picture text --> Source: Authors’ calculations based on the World Bank and IMF data (2011). Note: Labels refer to countries placed outside the confidence bands. The dots are countries in between the bands.

# **2. Unprecedented Flows of Capital in Emerging Europe**

From a pure financing perspective, the foreign capital inflow (i.e., the current account deficit) serves to augment the economy’s scarce resources and to close the saving-investment mismatch. The reliance on external finance can be an outcome of domestic imbalances (e.g., low and stagnant saving rates) and of the behavior of non-residents (e.g., foreigners perceive a country’s productive or financial assets as attractive). This implies that the net amount of foreign capital in the recipient economy is simultaneously determined along with the saving and investment decisions of domestic economic agents.<sup>3</sup> Yet, before we undertake an empirical exploration of simultaneity, some stylized facts serve to motivate our work.

A descriptive analysis of the main trends during the transition period of the early and mid-1990s reveals that the net capital inflows were driven by the drop in the saving rates. In fact, the pre-transition saving rates were high by international standards, mainly because of the high involuntary savings in a central planning setting and limited consumer choice (Conway, 1995).<sup>4</sup> Average saving rates of 30 percent of GDP were common during the 1980s (Schrooten and

> 3 While the interpretation of the current account deficit as a saving-investment imbalance seems straightforward, it is important to note that savings, investment and current account balance are simultaneously determined by the general equilibrium of income and prices as well as the economy’s long-run solvency constraint. Not only foreign capital may crowd out domestic saving or augment the country’s physical capital stock, but also it may respond to changes in the saving and investment behaviour of residents. Hence, it is driven by both the domestic imbalances and behavior of foreign residents and influenced by both the market participants and government policy response (e.g., current account targeting strategy).

4 Throughout the report we also cover Turkey as one of the EU neighborhood countries, but of course its determinants of savings and investment are not linked to the same features of transition countries except in terms of closeness to the EU that is central to the conclusions of this paper.

4