rafmacalaba/data-use-mentions-extended huggingface dataset:
**MONGOLIA'S INFORMAL** SECTOR -

**Notes**

**61**

66.The sample included 15 kiosks, representing the "high end" of the informal spectrum, and 15 street infonnals, representing the "low end." Results were nearly identical for kiosks as for the street informals. This survey was conducted by the author for the purposes of this study.

The results in this section are consistent with Centre for Social Development, 1996, whose field work suggested: "an informal credit and loan system operates readily within the informal sector, mostly between friends and relatives. ... It is interesting to note that none of the informants mentioned borrowing money from a 'money lender,' they always said family, friends and acquaintances, although the latter could be the equivalent. Pawnbrokers, called 'lombards,' do exist but these were never mentioned as a source of initial investment, they are primarily used for livelihood purposes." p.48.

# 67.Seventy percent of those loans were taken out in 1997.

68.Owing to the nature of the activities, many informals can avoid paying their tax. But the tax collectors are vigilant in Mongolia, and a large number of informals seem to comply with the rules. The percentages of a sample of activities reporting that they were registered are as follows: 100% of kiosks, 74% of full-time taxicabs, 63% of boot repairmen, 31% of vendors of used auto parts, and 0% of the petty retailers of chewing gum, cigarettes, and soft drinks. (All based on the informal sector surveys conducted by the author.) 69.The relative stability of incomes also influences the incentives to engage in informal activities. Informal sector incomes are usually assumed (and empirically shown) to be less stable than those of formal sector employees. But some informal occupations may be more immune to the income erosion caused by inflation than is wage income. Specifically, informals engaged in distribution can
Figure C20: Decomposition of Theil coefficients and GDP, sorted by Theil index <!-- Start of picture text --> (A) DOU (B) DB<br>1 1<br>.8 .8<br>.6 .6<br>.4<br>.4<br>.2<br>.2<br>0<br>0<br>WDI three letter country codes<br>Between Within National<br>Source: International Urban Poverty Database.<br>Note: Countries are sorted in ascending order of log of GDP per capita, measured in PPP (constant 2017<br>international $). WorldPop 250m is used for the DOU and DB methods. See Figure C21 for the same chart with<br>countries reordered by the highest to the lowest Theil indexes.<br>Figure C21: Decomposition of consumption difference between urban and rural areas<br>(A) DOU (B) DB<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>.2 .2<br>0 0<br>National Between Within<br>NERMWITCDETHGNBBFAUGAGINTZALSOSENBGDGHACIVMRTAGOVNMCOLGAB<br>NERMWITCDETHGNBBFAUGAGINTZALSOSENBGDGHACIVMRTAGOVNMCOLGAB<br>MWIAGOCOLLSOUGAGHABFATZANERGABSENVNMETHCIVTCDBGDGNBMRTGIN MWIAGOCOLLSOUGAGHABFATZANERGABSENVNMETHCIVTCDBGDGNBMRTGIN<br>Theil index<br>Theil index<br>Theil coefficient Theil coefficient<br><!-- End of picture text --> Source: International Urban Poverty Database.

Note: Each boxplot shows the distribution of percentage contribution of (1) endowments and (2) returns to the mean differences in the log per capita consumption expenditures between urban and rural areas in 18 countries based on the Oaxaca-Blinder decomposition. The share of interactions is not shown for the sake of presentation. WorldPop 250m is used for the DOU and DB methods.

83
The results, reported in column (1) of Appendix Table A.7, provide no evidence that the relatives of incumbent mayors were more likely to win closely contested elections. Restricting the sample to elections decided by 3 percentage points or fewer does not change this basic conclusion. In columns (3) and (4), closely fought elections involving a relative are added to the main sample. Their inclusion reduces the magnitude of the discontinuity from 0.016 (reported in column (1) of Table 1) to 0.008 and the estimate becomes statistically insignificant. However, the estimate based on a bandwidth of 3 percentage points, reported in column (4), is very similar in both magnitude and significance to the estimate reported in column (3) of Appendix Table A.1. The analysis then relates the narrow victory of relatives to the number of post-election casualties using a sample of narrow incumbent victories which also includes relatives. The results in columns (1) and (2) of Appendix Table A.8 are similar to the results reported in Table 3 and Appendix A.2. This analysis suggests that narrow victories of incumbent relatives are not associated with post-election violence.

# **4 Conclusion**

There is a widespread belief among academics and practitioners that elections perceived as fraudulent can increase support for non-democratic actors and serve as a catalyst for civil conflict (World Bank, 2012; Donno, 2013; Norris, 2014; Hall et al., 2015). Over the past few decades, international donors and the World Bank have intensified their efforts to ensure that elections in fragile democracies are conducted fairly (Daxecker, 2012) and have spent substantial amounts on election monitoring and other related programs (Kelley, 2008).

This study examines the association between narrow incumbent victories and civil conflict using data from the 2007 mayoral elections held in the Philippines. With a forensic ap49 municipalities in which one of the candidates is a relative of the incumbent mayor. Limiting the sample to a bandwidth
: the role of siblings.</mark> _<mark>Demography</mark>_ <mark>,</mark> _<mark>40</mark>_ <mark>(3), 395-418.</mark> <mark>Popoola, O. A., & Adeoti, A. (2016). Child Welfare Deprivation in Rural Nigeria: A Counting Approach.</mark> _<mark>Child Development Research</mark>_ <mark>,</mark> _<mark>2016</mark>_ <mark>.</mark> <mark>Raleigh, C., Linke, A., Hegre, H., & Karlsen, J. (2010). Introducing ACLED: an armed conflict location and event dataset: special data feature.</mark> _<mark>Journal of peace research</mark>_ <mark>,</mark> _<mark>47</mark>_ <mark>(5), 651-660.</mark> Rotondi, V. and Rocca, M. (2019). Bombs and babies: Terrorism increases fertility in Nigeria. Retrieved 15<sup>th</sup> June 2019: http://paa2019.populationassociation.org/uploads/192867 <mark>UNICEF. (2011). A multidimensional approach to measuring child poverty.</mark> _<mark>Social and Economic Working Briefs</mark>_ <mark>.</mark> <mark>UNICEF (2017). I</mark> mpact Evaluation of Unicef Nigeria Girls' Education Project Phase 3 (GEP3) Cash Transfer Programme (CTP) in Niger and Sokoto States. Unicef Nigeria Country Office: Abuja, Nigeria <mark>UNICEF (n.d.). Education. Programme: Girls' education - Gender equality in education benefits every child. UNICEF: Retrieved April 27
Sales volumes of different fuels present various patterns of growth ( **Figure 2** ), reflecting influences of economic conditions, domestic policies, international markets, and technological invention/adoption. Diesel oil consumption has been increasing more steadily across time, with temporary dips during recessions. Gasoline consumption has been growing with medium-term fluctuations, partially reflecting world commodity cycles/oil crisis. Hydrous ethanol grew rapidly in the 1980s, lost momentum in the 1990s, before trending up again amid short-term fluctuations, likely resulting from policy incentives and the flex-fuel technology introduced in 2003 that enables ethanol to substitute gasoline. The growth of natural gas has been stagnant since 2007/2008 and was surpassed by biodiesel in 2013, the latter of which continues to grow thanks partially to policy support. Overall, the total volume of these fuels grew until the mid-2010s when it started fluctuating, closely mirroring the country’s real GDP.

<!-- Start of picture text --> Figure 2. Varied Paths of Consumption across Time<br>a. Accumulated/Stacked Values (10 3 toe) b. Time Series of Each Fuel (10 3 toe)<br>90000 40000<br>80000 35000<br>70000 30000<br>60000 25000<br>50000 20000<br>40000 15000<br>30000 10000<br>20000 5000<br>10000 0<br>0<br>Diesel Oil Biodiesel<br>Diesel Oil Biodiesel Gasoline Gasoline Anhydrous Ethanol<br>Anhydrous Ethanol Hydrous Ethanol Natural Gas Hydrous Ethanol Natural Gas<br>Data Source: Brazilian Energy Balance (BEN), EPE.<br>1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2014 2018<br>1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 2015 2018 2021<br><!-- End of picture text --> Fuel prices, another factor that affects fuel consumption and its resultant emissions, present both spatial and temporal variations, which
|**Variable Name**|**Description**|**Source**|
|---|---|---|
|Bank capital / assets|Bank capital to assets ratio %|World Development<br>Indicator (World Bank)|
|Bank Concentration|Assets of three largest banks as a share of assets of all commercial<br>banks.|Financial Structure<br>Database (World Bank)|
|Bank Deposit / GDP|Demand, time and saving deposits in deposit money banks as a share of<br>GDP, calculated using the following deflation method: {(0.5)*[Ft/P_et +<br>Ft-1/P_et-1]}/[GDPt/P_at] where F is demand and time and saving<br>deposits, P_e is end-of period CPI, and P_a is average annual CPI|Financial Structure<br>Database (World Bank)|
|Bank liquid reserves / assets|Bank liquid reserves to bank assets ratio %|World Development<br>Indicator (World Bank)|
|Banking supervision|Measure of prudential regulations and supervision of the banking sector|Abiad, Detragiache and<br>Tressel 2009 (IMF)|
|Chinn-Ito Index of Financial<br>Openness|A measure of the degree of financial openness of a country where higher<br>value indicates greater de jure financial openness.|Chinn & Ito (September<br>2008)|
|Crisis Dummy|Dummy set to one if a country is experiencing a banking crisis|Laeven Banking Crisis<br>Database|
|Financial Reform Index|Measure of financial reform. Normalized from 0 to 1. (1 stands for fully<br>liberalized)|Abiad, Detragiache and<br>Tressel 2009 (IMF)|
|GDP per capita growth|GDP per capita growth annual %|World Development<br>Indicator (World Bank)|
|International capital liberalization|Measure of restrictions
), 567–588. https://doi.org/10.1080/19439342.2011.621025

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- Bivins, A. W., Sumner, T., Kumpel, E., Howard, G., Cumming, O., Ross, I., ... Brown, J. (2017). Estimating Infection Risks and the Global Burden of Diarrheal Disease Attributable to Intermittent Water Supply Using QMRA. _Environmental Science and Technology_ , _51_ (13), 7542–7551. https://doi.org/10.1021/acs.est.7b01014

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2019 and Dominican Republic 2018. In these cases, the estimated growth of income along the whole distribution is very close to the actual growth for the _new model without rescaling_ , as shown in Figure 8. In contrast, the less flexible variations are more distant from the actual distribution and even out of the confidence interval, as in the case of Bolivia 2019. The latter is an interesting case since, as shown before, Bolivia is one of the countries with the poorest fit in poverty estimation. The explanation for this discrepancy relies on the measure of analysis. Poverty measures the number of people whose income falls below a determined poverty line. In this sense, this measure depends on the selected threshold and the income growth for the population most likely to have income below that threshold. In the case of Bolivia, the GICs presented in Figure 8 show a good level of adjustment overall but insufficient income growth below the 31 percentile, where the poverty lines probably fall. This example highlights the importance of considering the models concerning the target measure and the measured object of analysis (e.g., poverty, inequality, income distribution).

_Divergence of distribution tails_ In other cases, the fitting is not so good along the whole distribution. Argentina 2019 and Panama 2019 are examples of these cases (Figure 9). Notably, these countries show that the three assessed model variations might have difficulties estimating income variation in the distribution's tails. A possible explanation might be due to the limited employment sector classification. The micro-simulation model relies on a 6-sectors classification (formal agriculture, informal agriculture, formal industry, informal industry, formal services, and informal services), and movements of labor earnings according to aggregate output or average earnings are not enough to capture intra-sectoral variations. That said, 23
shock if the prior period‘s rainfall was at least one standard deviation more than the average 1951-1985 rainfall. Thus, there are in total four measures describing the prior year‘s (or wet season‘s or pre- _canícula_ period‘s) weather. Table 2 shows the 1951 to 1985 average weather conditions by regions for Mexico. One standard deviation rainfall shock translates to an average of about 30% difference in annual or wet season rainfall and a 50% difference for the pre- _canícula_ period. The GDD shocks are, on average, about 8% deviations from the mean. The climate in each of the regions is distinct and even within a region there is much variability. In general, however, the North is drier than the rest of the country and the Center is colder than the rest of the country.

> 18 To balance the need to calculate the historic means with as many years of information as possible but excluding recent years which may have been affected by changing climate, we construct the historic means and standard deviations of the weather variables using data from 1951 to 1985.

15
usable and accessible sample frame based on enumeration areas demands a workable and up-to-date national sampling frame in the country. Thus, given the unsuitability of the existing sample frames, this paper develops a national sampling frame based on pre-defined enumeration areas (pre-EAs) in Armenia that conceptually prevails over the existing sampling frames evaluated in this section.

**Table 3: Sampling frames of major surveys in Armenia**

|Surveys|PSUs in the sampling frames|
|---|---|
|Demographic and Health Survey (DHS)|Enumeration areas in the Armenia Population and Housing Census|
|Integrated Living Conditions Survey (ILCS)|Population census enumeration areas|
|UNICEF Multiple Indicator Cluster Survey<br>(MICS,first ever in Armenia)|Currently in search of a suitable sampling frame|

_Notes_ : The PSUs stand for primary sampling units.

# **3 Data and Methods**

## **3.1 Input Datasets**

This section describes the datasets obtained from different sources to establish the national sampling frame and support collecting field data in Armenia.

## **3.1.1 Gridded Population**

The gridded population for Armenia is obtained from WorldPop (Bondarenko et al., 2020) and is based on the 2020 population census or projection-based estimates for 2020. The population data contain an estimated total number of people per grid cell (panel (a) **Figure 2** ). The data at a resolution of 3 arcs (about 100 meters at the equator) can be downloaded in Geotiff format with the projection of Geographic Coordinate System, WGS84. The estimated number of people is in units of one pixel. The values marked with “NoData” denote regions mapped as unpopulated according to the results of the Built-Settlement Growth Model (BSGM) developed by Nieves et al. (2020). The WorldPop gridded population dataset was produced by disaggregating the projected subnational population totals into grid cells using machine learning techniques and a variety of geospatial layers derived from
couples on ownership and rights to dwelling and non-dwelling land — around 70 and 75 percent of land parcels in Tanzania and Malawi, respectively, 90 percent in Ethiopia, and 94 percent in Cambodia (Appendix Table A1).<sup>8</sup> On valuation specifically, the UN guidelines recommend that in estimating wealth, each asset should be valued individually at its current market price (the _potential sales value_ or _realization value_ , namely how much the respondent would expect to receive if they sold the asset today). This recommendation had been based on the experience under the World Bank Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA), the Gender Asset Gap Project, and the surveys that were supported by the EDGE project, which found that the potential sales value provides a more consistent measure of asset prices as compared to the construction value or rental value of the asset, as well as other approaches to sales valuation such as the “quick sale” price and “reservation” price.<sup>9</sup> The LSMS+ assets modules followed the UN guidelines and asked respondents that of each asset they owned, _“if you were to sell <THIS ASSET> today at current market prices, how much would you receive for it (in local currency)?”_<sup>_10_</sup> The approach was item-by-item and was asked of respondents for a point estimate valuation for each asset they owned (each land parcel, for example), as opposed to an aggregate estimate for all assets within a specific asset class. For financial accounts, respondents were asked about the current value of each account.

> 8 A parcel is defined as a continuous piece of land which can have more than one plot.

9 The “quick sale” price is what the owner could expect to receive if he/she sold right away, i.e. not necessarily at current market prices, and which could lead to an undervaluation of the asset. The “reservation”
# **III. Business reforms**

It is important to have a healthy private sector for an economy to thrive. And in order to allow private businesses to flourish, governments put in place laws and regulations that support entrepreneurship, allowing businesses to operate smoothly and expand. Therefore, regulators continuously strive to improve local business climate. Reforms aimed at fostering private sector development and growth often entail features such as cutting the red tape, aligning domestic laws with international best practices and introducing modern ways of doing business (i.e. use of electronic platforms). Reforms implemented in the areas measured by _Doing Business_ have proved to have favorable impacts on local economies. Some of the core benefits of _Doing Business’_ regulatory changes include increase in entrepreneurial activity and employment rates as well as upsurge in competition and innovation.<sup>4</sup> A substantial body of research shows the significance of reforms aimed at enabling favorable regulatory environment for entrepreneurship and hence firm creation. Klapper et al. (2006) highlight that costly regulations impede the establishment of new firms, especially small ones and particularly in the industries that are normally characterized by high entry propensity. Furthermore, cumbersome regulations mostly favor large firms, hindering growth of incumbent smaller businesses. Similarly, Klapper and Love (2010) explore how ease of registering a business and relevant regulatory reforms affect registrations of new firms. The authors demonstrate that costs, number of days and procedures required to start a business are the key factors impacting new firm registration.

Research also shows that improvements in business regulation can drive additional job creation, which is prompted by increased firm registration. Bruhn (2011) analyzed reforms that simplified business entry regulation in Mexico. The author finds that these reforms encouraged wage earners to open their own businesses, increasing the number of registered firms by 5%, while at the same time increasing wage employment by 2.2%. In the same vein, Branstetter et al. (2010), using Portuguese micro level data, investigated economic
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