rafmacalaba/datause-encoder-data huggingface dataset:
|mal and Formal Sectors - Manufacturing Sample<br>Intermediate Consumption<br>Energy Consumption<br>Formal<br>Informal<br>Formal<br>Informal<br>(3)<br>(4)<br>(5)<br>(6)<br>-0.0148<br>-0.0157***<br>-0.0162<br>-0.0214***<br>(0.00929)<br>(0.00577)<br>(0.0103)<br>(0.00685)<br>0.931<br>0.948<br>0.937<br>0.940<br>34,390<br>46,566<br>34,342<br>46,487<br>0.00228<br>-0.00562<br>0.00611<br>-0.00417<br>(0.00943)<br>(0.00809)<br>(0.00802)<br>(0.00879)<br>0.931<br>0.948<br>0.937<br>0.940<br>34,390<br>46,566<br>34,342<br>46,487<br>-0.0471<br>-0.0389***<br>-0.0514<br>-0.0532***<br>(0.0293)<br>(0.0140)<br>(0.0327)<br>(0.0167)<br>34,390<br>46,566<br>34,342<br>46,487<br>**are of IDPs (% Working Age Pop.)**<br>0.314***<br>0.403***<br>0.314***<br>0.403***<br>(0.0225)<br>(0.0245)<br>(0.0225)<br>(0.0245)<br>195.4<br>270.8<br>194.61<br>270.14<br>34,390<br>46,566<br>34,342<br>46,487<br>Yes<br>Yes<br>Yes<br>Yes<br>Yes<br>Yes<br>Yes<br>Yes<br>Yes<br>Yes<br>Yes<br>Yes<br>e interactions of year dummies and i) armed attacks by illegal armed groups<br>ures in 1995, v) central government transfers to health, education, and other<br>ollection offces in 1995, viii) 2000 GDP share in agriculture, services, and<br>ed standard errors by frm are reported in parentheses. _∗∗∗_signifcant at the|
|---|
|**Table (VIII)**<br>Impacts of IDP infows on Firms in the Infor<br>**Dependent Variables (in logs)**<br>Production<br>**Type of sector**<br>Formal<br>Informal<br>(1)<br>(2)<br>**Panel A. Reduced Form**<br>-0.0125<br>-0.0109*<br>Predicted Infows<br>(0.00808)<br>(0.00570)<br>R-squared<br>0.946<br>0.954<br>Observations<br>34,395<br>46,572<br>**Panel B. OLS**<br>Share of IDPs (%Pop. in Working Age)<br>0.00187<br>-0.00190<br>(0.00794)<br>(0.00822)<br>R-squared<br>0.946<br>0.954<br>Observations<br>34,395<br>46,572<br>**Panel C. 2SLS**<br>Share of IDPs (%Pop in Working Age)<br>-0.0397<br>-0.0271*<br>(0.0256)<br>(0.0138)<br>Observations<br>34,395<br>46,572<br>**Panel D. First Stage**<br>**Dep. Variable: Sh**<br>Predicted Infows<br>0.314***<br>0.403***<br>(0.0225)<br>(0.0245)<br>First Stage F-statistic<br>195.38<br>270.84<br>Observations<br>34,395<br>46,572<br>**Controls for all Panels**<br>Year FE<br>Yes<br>Yes<br>Firm FE<br>Yes<br>Yes<br>Additional Controls<br>Yes<br>Yes<br>_Notes:_ Each coeffcient corresponds to a separate regression. Additional controls includ<br>in 1995, ii) fatal victims of attacks in 1995, iii) homicide rates 1995, iv) public expendit<br>expenditures in 1995, vi) number of fnancial institutions in 1995, vii) number of tax c<br>industry, ix) municipal tax income in 1995, and x) night light density in 1995. Cluster<br>1%, _∗∗_signifcant at the 5%, _∗_signifcant at the 10%.|

39
criterion was not collected. We find that, during the monga period, less than one-third of the sampled households actually received benefits from one or more safety-net programs. This finding perhaps has little to do with targeting efficiency, and is related more to constrained resources: There are simply not enough safety-net resources to provide for all who deserve it. Thus, a key question is what determines household access to any safety-net program. In this section, we examine various factors that might determine whether a household receives safety-net benefits.

Because receipt of safety-net benefits can be represented as a binomial variable, a probit model is used to estimate it, which is expressed as follows: where  and  are the normal density distribution and the cumulative normal distribution functions, respectively; _X_ is a vector of household and community characteristics; and _β_ is the vector of parameters to be determined. Both household- and village-level characteristics are likely to affect the receipt of safety-net benefits during the monga season. Among household-level factors, we consider various types of household assets, dependency ratio, and the age and education of household head. The village-level variables include access to microcredit programs and the unemployment rate.<sup>4</sup> Moreover, we use several other location and agroclimate factors that can affect households’ vulnerability to monga and whether they are recipients of the safety-net resources disseminated: (i) average yearly rainfall at the upazila (sub-district) level, (ii) proportion of high land in the upzila,<sup>5</sup> and (iii) whether the village is located in a char area.<sup>6</sup> Finally, we control for

> 4 The rate of village-level unemployment has been defined by the proportion of households in the village whose heads are unemployed.

> 5 According to the Bangladesh Agricultural Research Countil (BARC), a high land area is one where the flood-water level remains below a height of 3 feet.

> 6 A char is a land area formed by river sediments that is then inhabited by homeless, destitute people.

15
|P069909|2001|2002|6/10/2002|3 Closed|Sao Tome and Principe|
|---|---|---|---|---|---|
|P069909|2001|2003|4/29/2003|5 Closed|Sao Tome and Principe|
|P069909|2001|2004|6/30/2004|7 Closed|Sao Tome and Principe|
|P069913|2002|2002|4/12/2002|2 Closed|Argentina|
|P069913|2002|2003|6/14/2003|5 Closed|Argentina|
|P069913|2002|2004|6/18/2004|7 Closed|Argentina|
|P069913|2002|2005|5/4/2005|9 Closed|Argentina|
|P069913|2002|2005|6/16/2005|10 Closed|Argentina|
|P069913|2002|2005|6/30/2005|11 Closed|Argentina|
|P069913|2002|2006|12/21/2005|12 Closed|Argentina|
|P069916|2002|2002|6/26/2002|1 Closed|Philippines|
|P069916|2002|2003|6/20/2003|3 Closed|Philippines|
|P069916|2002|2004|5/5/2004|5 Closed|Philippines|
|P069916|2002|2005|6/8/2005|7 Closed|Philippines|
|P069916|2002|2006|12/12/2005|8 Closed|Philippines|
|P069916|2002|2007|10/30/2006|9 Closed|Philippines|
|P069916|2002|2008|12/27/2007|10 Closed|Philippines|
|P069917|2002|2002||0 Closed|Armenia|
|P069917|2002|2003|1/28/2003|2 Closed|Armenia|
|P069917|2002|2004|6/2/2004|5 Closed|Armenia|
|P069917|2002|2005|6/1/2005|7 Closed|Armenia|
|P069917|2002|2006|7/28/2005|8 Closed|Armenia|
|P069917|2002|2006|12/8/2005|9 Closed|Armenia|
|P069917|2002|2007|7/31/2006|10 Closed|Armenia|
|P069917|2002|2007|11/21/2006|11 Closed|Armenia|
|P069917|2002|2007|5/21/2007|12 Closed|Armenia|
|P069917|2002|2008|7/25/2007|13 Closed|Armenia|
|P069917|2002|2008|3/7/2008|14 Closed|Armenia|
|P069917|2002|2008|5/23/2008|15 Closed|Armenia|
|P069917|2002|2009|12/24/2008|16 Closed|Armenia|
|P069917|2002|2009|4/8/2009|17 Closed|Armenia|
|P069922|2001|2001|5/2/2001|2 Closed|Grenada|
|P069922|2001|2002|5/3/2002|4 Closed|Grenada|
|P069922|2001|2003|5/30/2003|7 Closed|Grenada|
|P069922|2001|2004|5/3/2004|9 Closed|Grenada|
|P069922|2001|2005|4/29/2005|11 Closed|Grenada|
|P069922|2001|2006|11/11/2005|12 Closed|Grenada|
|P069922|2001|2006|1/3/2006|13 Closed|Grenada|
|P069922|2001|2006|4/27/2006|14 Closed|Grenada|
|P069923|2002|2002||0 Closed|St. Vincent and the Gr|
|P069923|2002|2003|5/30/2003|5 Closed|St. Vincent and the Gr|
|P069923|2002|2004|5/3/2004|7 Closed|St. Vincent and the Gr|
|P069923|2002|2005|4/29/2005|11 Closed|St. Vincent and the Gr|
|P069923|2002|2006|10/15/2005|12 Closed|St. Vincent and the Gr|
|P069923|2002|2006|1/3/2006|13 Closed|St. Vincent and the Gr|
|P069923|2002|2006|4/26/2006|14 Closed|St. Vincent and the Gr|
|P069930|2000|2000|6/30/2000|1 Closed|Djibouti|
Policy Research Working Paper 7617

# **Abstract**

The collection of survey data from war zones or other unstable security situations is vulnerable to error because conflict often limits the implementation options. Although there are elevated risks throughout the process, this paper focuses specifically on challenges to frame construction and sample selection. The paper uses simulations based on data from the Mogadishu High Frequency Survey Pilot to examine the implications of the choice of second-stage selection methodology on bias and variance. Among the other findings, the simulations show the bias introduced by a random walk design leads to the underestimation of the poverty headcount by more than 10 percent. The paper also discusses the experience of the authors in the time required and technical complexity of the associated back-office preparation work and weight calculations for each method. Finally, as the simulations assume perfect implementation of the design, the paper also discusses practicality, including the ease of implementation and options for remote verification, and outlines areas for future research and pilot testing.

This paper is a product of the Poverty and Equity Global Practice Group. 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://econ.worldbank.org. The authors may be contacted at khimelein@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
international migration over 1960–2000. Section V discusses some implications of the study.

# _I. PRELIMINARIES_

Migration data are complex. They almost always come from destination countries, because it is difficult for origin countries to collect demographic data on people who are not living in the country. Unlike trade and financial statistics, which are recorded by both transacting parties, the quality of migration statistics depends almost entirely on the rigor with which destination countries survey the migrants within their borders. In addition, destination countries‘ recording and dissemination methods can differ greatly. Understanding the analysis in this article requires an understanding of the subtle differences in various sources and definitions, together with an understanding of the inherent inconsistencies between them.<sup>3</sup>

# _Who Are Classified As Migrants?_

The United Nations (1998, p. [6]) defines a migrant as ―any person that changes his or her country of usual residence.‖ This broad definition implies a movement from one location to another, the most relevant concept for economic analysis. However, official records apply many different definitions of what constitutes an international migrant. Most common criteria are based on country of birth, country of citizenship, purpose of visit or visa type, place of last permanent residence, and duration of stay.

The two main definitions of migration—being born in or being a citizen of a foreign country—are used most consistently over time and across countries. Citizenship is important for determining an individual‘s legal rights for employment, voting, and access to public services. The place of birth definition is superior for determining physical movement. Destination countries typically publish migration statistics by either category, mainly according to national migration and citizenship laws. Historically, countries in the Americas and Oceania favor the country of birth definition whereas countries in Asia, Africa, and Europe traditionally adopt a mix of the two definitions.

Individuals may be classified as migrants or nonmigrants depending on the definition. Many destination countries grant citizenship to foreign-born people who are family members of citizens or who satisfy certain legal and residence requirements. These naturalized citizens continue to be recorded as migrants under the foreign-born definition but not under the foreign citizen definition. Many destination countries (for example, the United States) grant automatic citizenship to people born within their territory regardless of parents‘ citizenship. Yet others, such as Japan, require at least one parent to be a citizen for children to acquire citizenship, even if they were born within its borders. Because of these differences in citizenship and naturalization laws, the numbers of migrants will be substantially higher in the United States if the foreign-born criterion is 3 This section highlights many of the nuances in the data, but for fuller treatment of the subject, see Bilsborrow and others (1997).

5
benefits in Panel C of $96 billion when all projects built in complement, only slightly higher than the baseline.

One hypothesis is that our single sector model ignores the fact that transportation investments may be especially beneficial to specific sectors. Using data on trade flows in North America, Caliendo and Parro (2015) find an aggregate elasticity of trade to trade costs θ= 4.55, close our baseline value, though they also find that θ can vary by sector. The value θ= 2 is a theoretical minimum (if the variance of the Type-II extreme value distribution underlying city productivity in the model is to be finite; see Donaldson and Hornbeck, 2016). Caliendo and Parro (2015) estimate elasticities in agriculture (θ= 8.11) and mining (θ= 15.72) implying these sectors offer a higher sensitivity of trade to trade cost than in aggregate. Alternative columns of Table 6 consider project benefits as if all trade was in these sectors. While project values are lower with θ= 2, they are almost double the result of the baseline specification when we set θ= 15.72. Nonetheless, the value of all projects in Panel C even under this specification is still just $170 billion, approximately half of costs. Allowing a very high sensitivity of trade to trade costs therefore may increase gains from individual projects but does not lead the present value of benefits from all projects to exceed their costs.

We turn to alternative specifications of income. First, we use alternative estimates of city GDP from the research service Oxford economics, as described in Section 3. These alternative values of city GDP lead to an estimate in Panel C of the present value of project benefits equal to $140.6 billion, 60 percent more than the baseline specification, but still less than half of project costs. Second, we use alternative estimates of city GDP that assume all of countries’ income is allocated to the nodes on the network. Here the present value of project benefits in Panel C is $272.2 billion, which is 309 percent of the baseline estimate, but still less than estimated projects costs. Even under the assumption therefore that within country trade costs are zero off of the international transportation network, and that the value of all land in the country will increase identically in response to 29
**FOR OFmFCIAL** USE ONLY

# AVERTING FINANCIAL CRISIS - KUWAIT

## By: Fawzi H. Al-Sultan

|Chronology<br>..............................................<br>l1|
|---|
|The Stock Market<br>................................................<br>4|
|Market Expansion<br>...............................................<br>4|
|The First Market Break<br>............................................<br>5|
|Futures Trading<br>.............................................. 8|
|Toward a Solution<br>.............................................. 10|
|Government Intervention<br>..........................................<br>11|
|The Chamber of Commerce Approach<br>.................................<br>14|
|A Comprehensive Solution?<br>...........................................<br>15|
|The Clearing Solution<br>............................................<br>15|
|Distressed Dealers<br>..............................................<br>17|
|The Banking Crisis ..............................................<br>18|
|Effects of Growth<br>..............................................<br>19|
|End of the Boom ..............................................<br>21|
|Difficult Credit Facilities Settlement Program<br>......................<br>23|
|The Causes of the Crisis<br>............................................<br>25|
|Structural Factors<br>...............................................<br>26|
|The Role of Regulatory Institutions<br>..............................<br>31|
|Restructuring<br>..............................................<br>35|
|Stock Market Reform<br>..............................................<br>37|
|Costs of the Solution<br>............................................<br>37|
|Issues for Evaluation<br>..............................................<br>38|
|References<br>...<br>......................................................<br>42|
|Stzistical Appendix ..................<br>44|

This document has a restricte **d** istribution and may be used by recipients only in the performance of their official duties. Its contents may not otherwise be disclosed without World Bank authorization.
improved outcomes, an important premise is that local governments would improve their performance on account of improved accountability, which in turn hinges on citizens being able to discern between good and bad government and then influence their local authorities.<sup>5</sup> This implies that in order to understand whether decentralization is likely to improve service delivery, it is important to understand what household and community level factors (other than quality of services) determine citizen satisfaction.

The above questions are addressed here by exploring the relationships between satisfaction, household and community characteristics, and the actual quality of service delivery as measured using objective indicators.

_Concerns with satisfaction surveys and the example of GDS-2_ Despite the growing prevalence of surveys administering satisfaction-related questions, there are serious concerns regarding the information content of the data, fueled by results from survey data that often appear puzzling. One example is Indonesia, where the nationally representative GDS-2 household survey reveals extremely high satisfaction with health and education services. More than 90 percent of households report being at least somewhat satisfied with the overall quality of health services (Figure 1), while 72 percent feel that health service delivery has improved in the last 2 years (Figure 2). For education services, more than 80 percent report being at least somewhat satisfied and 73 percent report improvement in the last 2 years.

This happy picture is quite inconsistent with the poor reputation of health and education services in Indonesia, which is also supported by more objective measures of quality

> 5 See, for instance, Ahmad et al. (2005) and Grindle (2007).

5
**Table 2: Corruption risk indicators thresholds used in North Macedonia’s composite risk score (CRI)**

|**Indicator name**|**Indicator definition**|
|---|---|
|Single bidder contract<br>(corr_singleb )|Low risk: more than one bid received<br>High risk: one bid received|
|Procedure type<br>(corr_proc)|Low risk: Negotiated with publication, Open, QualificationSystem<br>Medium Risk: Low estimated value procedure, Request For Proposal, Simplified Open<br>Procedure*.<br>High risk: Negotiated without publication, Other.|
|Length of advertisement<br>period<br>(corr_subm)|Number of days between publication of call for tenders and submission deadline<br>Low risk: from 15 to 365 days<br>High risk: from 1 to 14 days & missing values|
|Length of decision period<br>(corr_decp )|Number of calendar days between submission deadline and announcing of contract<br>award<br>Low risk: from 59 to 111 days<br>Medium risk: from 27 to 58 days & missing values<br>High risk: from 1 to 26 days & 112 to 730 days|
|Supplier’s dependence<br>(w_ycsh4)|Shows the supplier's contract share received from the same procurement authority in a<br>given year based on contract values.|
|Benford’s law<br>(corr_ben)|Flags contracts by buyers whose contract prices do not conform with the Benford’s<br>distribution<br>Low risk: Acceptable conformity, Close conformity<br>High risk: Marginally acceptable conformity, Nonconformity|
|Tax haven<br>(taxhav2)|Supplier registered in a country flagged as a tax haven based on the Financial Secrecy<br>Index by the Tax justice network|
|* Simplified open procedure<br>2019. THe amendment incr<br>heavy dependence on this n<br>We found that these newly i<br>to the previously used Open|s started to be used from 2019 after a law amendment that entered into force in February<br>eased the thresholds allowed for the use of this simplified procedure type which led to the<br>ew type compared to the previously used Open procedures (Palguta and Pertold 2017).<br>ntroduced Simplified procedures are correlated with higher single bidding risk compared<br>procedures and thus were included as risky procedure types.|

15
- Nunn, N., & Puga, D. (2012). Ruggedness: The blessing of bad geography in Africa. _The Review of Economics and Statistics_ , _94_ (1), 20–36.

- Nunn, N., & Wantchekon, L. (2011). The slave trade and the origins of mistrust in Africa. _American Economic Review_ , _101_ (7), 3221–3252. https: //doi.org/10.1257/aer.101.7.3221

- Nunnenkamp, P., Öhler, H., & Andrés, M. S. (2017). Need, merit, and politics in multilateral aid allocation: A district-level analysis of World Bank projects in India. _Review of Development Economics_ , _21_ (1), 126–156. https://doi.org/10.1111/rode.12259

- Okoye, D., & Pongou, R. (2017). _Sea changes: The transatlantic slave trade and missionary activity in Africa_ [Unpublished manuscript]. Retrieved December 6, 2017, from https://sites.google.com/site/dozieaokoye/ home/research

- Oster, E. (2019). Unobservable selection and coefficient stability: Theory and evidence. _Journal of Business & Economic Statistics_ , _37_ (2), 187–204.

- Robinson, C. H. (1915). _History of Christian missions_ . Edinburgh, Scotland, Clark.

- Roome, W. J. W. (1924). _Ethnographic survey of Africa: Showing the tribes and languages_ . London, England, Stanford.

- Strandow, D., Findley, M., Nielson, D., & Powell, J. (2011). _The UCDP and AidData codebook on georeferencing aid: Version 1.1_ (UCDP Paper No. 4). Uppsala University. http://docs.aiddata.org/ad4/files/ucdp_ aiddata_codebook_published.pdf

- Waldinger, M. (2017). The long-run effects of missionary orders in Mexico. _Journal of Development Economics_ , _127_ , 355–378. https://doi.org/ 10.1016/j.jdeveco.2016.12.010

- World Bank Group. (2013). _A stronger, connected, solutions World Bank Group: An overview of the World Bank Group strategy_ (tech. rep.). World Bank Group. Washington, DC.

45