rafmacalaba/data-use-mentions-extended huggingface dataset:
a whole, with employment in urban areas outpacing both population growth in the cities and the rate of employment growth in the state as a whole. Table II.2 illustrates. Median household expenditure in Ahmedabad as measured by the National Sample Survey, has grown at over 5 percent a year in real terms in the 5 years between 2004/2005 and 2009/2010<sup>6</sup> . Thus, the problems of affordable housing in the AMC are resulting not from a distressed economy and growing poverty. The issue in this city lies elsewhere.

> 3 Report Of The Technical Group On Population Projections Constituted By The national Commission On Population May 2006.Office Of The Registrar General & Census Commissioner, India 2a, Mansingh Road, New Delhi

> 4 RBI website Handbook of Statistics of the Indian Economy. consulted 08/11/11 http://rbidocs.rbi.org.in/rdocs/Publications/PDFs/009T_HBS120911.pdf

> 5 Data from Census 2001 and 1991 Marginal Workers and Main Workers Categories. Such employment data is not available for the AMC itself and only for the Urban Agglomeration (UA).

> 6 Nominal data is converted using the GDP deflator for Gujarat published by the Reserve Bank of India. As is commonly the case with rapid income growth, the mean expenditure is growing more rapidly than the median. The ratio between mean and median in the 2009/10 survey has risen only slightly to 1.22 from 1.20 in the 2004/05 data.
Policy Research Working Paper 7558

# **Abstract**

The present study combines data from Mexico’s employment surveys (Encuesta Nacional de Empleo and Encuesta Nacional de Ocupación y Empleo) with the country’s official statistics on murder rates to create a state-level panel data set covering the period 1995 to 2013. Including most of the common controls identified by the literature, the results show that the rate of male youth ages 19 to 24 not studying and out of work (the so-called ninis), is not correlated with homicide rates during the period 1995 to 2006. However, there is evidence that a positive correlation between male ninis and murder rates arises between 2007 and 2013, a period during which murder rates in Mexico increased threefold. The association between ninis and homicide rates is stronger in states located along the border with the United States, a region particularly affected by organized crime and the international financial crisis of 2008–09.

This paper is a product of the Education 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 rdehoyos@ 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
**Figure 8. Medium-Term and Long-Term Correlates of Mobility, Ordered Logit Model with Random Effects, Marginal Effects, RLMS 1994-2015**

<!-- Start of picture text --> Panel A: 1994-2004 Panel B: 2004-2015 Panel C: 1994-2015<br>10<br>5<br>0<br>-5<br>Note: Orange/green lines are related to 95% confidence intervals. Data on formal sector are available since 1998 and data on public sector are available since 2004.<br>The estimation sample is restricted to individuals who are 18 years old and older. The dependent variable is income mobility between year t-1 and year t . The<br>terciles are defined using the cross-sectional sample for each year. Incomes are deflated with December to December regional CPIs and weighted with population<br>weights, where the first survey round in each period is used as the base year. All control variables are measured in the reference year t-1 except for the occupation<br>transition variables, which are the changes between year t-1 and year t .<br>To full-time employmentNo transitionUpward skills mobilityNo transition To formal sectorNo transitionTo full-time employmentNo transitionUpward skills mobilityNo transition To public sectorNo transitionTo formal sectorNo transitionTo full-time employmentNo transitionUpward skills mobilityNo transition<br>Mobility(%)<br><!-- End of picture text --> 49
# **IV. Final remarks**

Weak economic growth and deterioration of social outcomes since the plunge in oil prices combined with a high influx of Venezuelans demanded a rapid response from Ecuador’s government. The survey (i.e., EPEC) was designed and implemented to produce comparable findings of the lives and livelihoods of host communities and Venezuelan migrants and refugees for policy design. Even though Ecuador has a reliable and updated sampling frame, the lack of information on how many Venezuelan migrants are settled in Ecuador and where they reside in the territory posed challenges for the design and implementation of the survey. This difficulty shows in many developing and developed countries that are affected by a rapid influx of people. The exclusion of these types of populations from national sampling frames provides a biased picture of the situation the country is experiencing (World Bank, 2018). Moreover, as the number of migrants and refugees continues to increase, it becomes more relevant to develop strategies to include them in frequent representative socio-economic surveys.

The contribution of this study relies on the innovative methodological approach of using Big Data for sampling design. The methodology brings a proper solution for approximating the total number of migrants -including regular and irregular migrants- and their location in a country. The strategy implemented in this survey can be useful in designing similar exercises in countries with limited information (i.e., lack of a recent Census or a migratory registry) and scarce resources to rapidly gather socio-economic data of migrants and host communities for policy design.<sup>15</sup> Even though access to Big Data is beneficial for sampling design, researchers and policy makers could face a limitation in the lack of knowledge and technical capacity from telecommunication companies to implement the method. Also, Big Data are particularly precise when both market share and coverage -i.e., urban areas- are high. Thus, information on geographic regions (e.g., rural areas) where coverage is low, or market shares are
|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Year FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Size, Age, SOE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|R2|0.813|0.813|0.812|0.812|0.537|0.538|0.535|0.535|
|Adjustd R2|0.810|0.810|0.810|0.810|0.530|0.531|0.528|0.528|
|Obs total|22,137|22,137|20,831|20,831|26,618|26,618|24,991|24,991|

_Source_ : Firm census panel data from 2010-2018 matched with public procurement transaction data. _Note_ : 25
it is worth noting that destination countries with implemented projects are larger and have more abundant land for cultivation and land under forests (respectively 6.5 and 13.1 million hectares). On the contrary, origin countries have no such land left, as is most clearly visible for ―exclusive‖ ones, (with 0 and 0.1 million hectares respectively for land for cultivation and land under forest). There is some difference in agro-ecological potential between the country categories: as one would expect if such investments were to follow comparative advantage, potential output values from cultivation of uncultivated land are higher in destination than origin countries, and highest in those with implemented projects. Also, with origin countries obtaining more than half of the attainable yield already compared to about one-third in destinations, there appears to be potential for catch-up growth using existing technology. Interestingly, this potential is even greater in destination countries with implemented projects than in other destination countries. Data on governance suggest that, overall, regulatory quality, protection of investors‘ rights, and land governance are significantly weaker in destination countries. Interestingly, there is no significant difference in governance between destinations with and without implemented projects.

# **4. Econometric results**

Analyzing the determinants of large agricultural investment in unilateral and bilateral models suggests that (i) agro-ecological suitability is indeed a critical factor for both demand and actual implementation; (ii) the difference between potential and actual production (i.e. the ―yield gap‖) affects land demand but not project implementation; and (iii) while conventional governance variables are at most weakly significant, a measure of land governance that incorporates the security of local land rights is highly significant, strongly suggesting that demand for land is significantly higher in settings where such rights are only weakly protected.

# **4.1 Unilateral relationships**

Regressions for the count of projects involving large-scale land acquisition at the country of destination (unilateral case) are reported in Table 5 (where the top panel refers to
# 2.4.3. Indirect Subsidies

- <u>Water: Ugandan households receive indirect subsidies in the form of water infrastructure investment</u> contributions. Tariffs in urban areas are set to cover operating and maintenance costs, so consumption of water in urban areas is only subsidized indirectly by lowering the investment cost component that would otherwise have to be recovered through higher tariffs.  In the case of rural areas, the water supply is directly subsidized from the national budget, which funds part of the operating costs of water delivery. These data come from the Annual Budget Performance Report 2016/17 (MoF 2017) and the Uganda Water and Environment Sector Performance Report 2017 (MoWE 2017).

- <u>Agricultural Inputs: While the Government of Uganda (GoU) provides a variety of agricultural services</u> to rural households across the country, the core of its agricultural program is the provision of farming inputs (mainly seeds) to farmers. This is primarily implemented by the Operation Wealth Creation initiative, a Presidential program created in 2013 to distribute subsidized inputs by the military forces. This function was formerly performed by the National Agricultural Advisory Services (NAADS) program that operated under the Ministry of Agriculture. Extension services are also provided at the local level (district) under the guidance of the Ministry’s Directorate for Extension, recently created in 2016, but the scope of the program is rather limited (World Bank, 2018b). The data included in this analysis come from the Ministry of Finance, Planning and Economic Development’s Annual Budget Performance Report, MoF (2017).

_Table 3. Uganda Government Expenditures, 2016/7_

||**UGX**<br>**(billions)**|**% of**<br>**GDP**|**Included in**<br>**Analysis**<br>**(Yes/No)**|
|---|-
# **b. Tobacco price elasticities**

Price elasticities of demand by decile follow the methodology from previous country studies published by the World Bank. In each country, several models have been tested on household microdata on tobacco expenditures; in general, a fixed effects model with controls has been preferred. (See annex A for details.) Table 2 and figure 2 show the estimated average price elasticity of cigarette products for each decile and country. Consistent with previous empirical results, elasticities are higher in the lowerincome deciles of the eight countries. Demand responses remain inelastic in all countries, that is, with absolute values of elasticities below 1. Responsiveness diminishes with income level. Only the lowest income group in Bosnia and Herzegovina has an elastic response to changes in the price of cigarettes.

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, as a minimum condition of admission, the successful completion of education<br>|
|gross)|at the secondary level<sup>14</sup>|
|1International Finance Corporation's micro, small, and medium-size enterpri<br>2World Bank national accounts data, and OECD National Accounts data file<br>3International Labour Organization,usingWorld Bankpopulation estimates|ses database (http://www.ifc.org/ifcext/sme.nsf/Content/Resources<br>).<br>s.<br>.|

17
Table 8: Marginal Impact in Percentage Point - Summary

|All sample<br>|ODT<br>|
|---|---|
|Tab. 6<br>Col. 4<br><br>|Tab. 7<br>Col. 6<br>|
|Foreign presence _per se_<br>2.62<br>Foreign exports value<br>0.04|1.39<br>0.04|
|Figures correspond to the increase in the a<br>ability that domestic frms start exporting<br>|verage prob-<br> in a prod-<br>|
|uct/country pair when foreign frms’ exports|are positive|
|for this product/country pair (frst row) and|when foreign|
|frms’ exports rise by 10% (second row).||

Ultimately, focusing on ordinary trade activities for both foreign and domestic firms, the presence _per se_ of foreign firms exporting product _k_ to country _j_ increases the average probability that domestic firms in the same province will start exporting this product to this country by 1.39 percentage points.<sup>17</sup> This effect is almost four times greater than the effect of a 10% increase in the GDP per capita of the destination country and three times greater than the impact of a 10% increase in the product-destination country total imports. A 10% increase in the value of foreign exports increases the average probability that domestic firms will start exporting by 0.04 percentage points.<sup>18</sup>

# **III Conclusion**

Using panel data from Chinese customs for the 1997-2007 period, domestic firms’ capacity to start exporting new varieties to new markets is shown to respond positively to the export activity of neighboring foreign firms. The results are very robust to the introduction of different sets of fixed effects and to instrumentation strategies that control for the endogeneity of foreign
spatial pattern of background As levels has remained largely unchanged (BBS and UNICEF, 2010). Similarly, our groundwater risk maps represent an average level of salinity though it varies seasonally (Zahid et al., 2013). Our groundwater risk maps are based on multi-hazard indicators of various levels. Therefore, any area outside the mapped risk categories may or may not be free from a single hydrological hazard such as elevated arsenic, salinity or depletion of water storage. For example, an area with high salinity (>1500 μS/cm) but low arsenic (<10 μg/L) is not mapped as groundwater risk as it does not fulfill the set criteria of multi-hazard indicators but considered to be affected by individual hazards.

Our groundwater risk maps update the current, rather loosely constrained, estimates of population exposure to elevated As and salinity concentrations in Bangladesh. Our groundwater risk mapping reveals that an estimated 33 (23% of total population) and 64 (44%) million people in Bangladesh are currently exposed to As concentrations greater than 50 and 10 μg/L (WHO standard), respectively in shallow (<150 mbgl) groundwater. Using the groundwater electrical conductivity (EC) map, we estimate that approximately 26 million (18%) people, predominantly in the coastal region of Bangladesh are exposed to considerably high salinity (EC >1500 μS/cm) in groundwater. Our estimate of population exposure to high salinity in groundwater is substantially greater than a previous estimate of 20 million (Khan et al., 2011) people in coastal Bangladesh. Furthermore, the analysis of population exposure to various levels of groundwater risks reveals that approximately 37 million (26%) to 47 million (33%) people are currently at risk of elevated arsenic, salinity and declined groundwater storage combined that covers 31% to 44% of the land area of Bangladesh. Given the proven public-health risk to elevated arsenic and salinity in drinking water and considerable threat to food security associated with depleted water storage, our national-scale multi-hazard
Equations (1) and (3) are jointly estimated using the generalized method of moments estimator derived in Kapoor, Kelejian, and Prucha (2007), and implemented in R statistical software (Millo and Piras 2012).

# Results and Robustness Checks

This section describes the results of hypotheses testing based on the estimation of regression equations (1) and (3). Table 1 reports the generalized method of moments (GMM) estimates of these equations, with the explanatory variable cumulative values calculated over the 3-month window before elections to the election date _._ The first-stage coefficient estimates of the marginal effect of the instrumental variable, I are positive and statistically significant. This is consistent with our expectation that potholes are ββ more likely to appear in the municipalities with a larger number of daily temperature switches and more precipitation during the heating season. The Wald test confirms that the constructed instrumental variable cannot be excluded from the first stage without loss of statistical significance, rejecting the null hypothesis of weak instruments. The estimated spatial lag coefficient of the pothole complaints, , indicates negative spatial dependence. Turning to the second stage estimates, we see that the estimated marginal effect of digital public XX ρρ engagement measured by pothole complaints, , is positive and statistically significant in equations with total votes for incumbent and the margin of victory as dependent variables. Moreover, in both ββ equations, the magnitude of the estimated coefficient increases as the election date gets closer. These results indicate a sizeable positive effect of digital public engagement on the electoral support for the incumbent. Conditional on the municipal- and election year- fixed effects, each pothole complaint is associated with additional 29 to 44 votes for the incumbent and 18 to 27 votes increase in the margin of victory. The last column of Table 1 shows that an increase in digital public engagement also leads to a slightly lower turnout. However, this effect is not statistically significant. The estimated spatial lag coefficient of electoral competitiveness indicators, , indicates positive spillovers from neighboring municipalities. This coefficient, however
instance, Jumia.com, which is an online platform combining an e-commerce marketplace, classified websites, and applications, is widely used across the continent. In Nigeria, Property Pro (formerly Jumia) is the number one property transaction website, covering about 65 percent of the Nigerian online real estate market (Nairametrics 2018).

Additionally, EMDEs’ websites, particularly those that do not have a regional spread like Jumia.com in Africa, have limited formal standards regarding data entry. Many websites in emerging economies do not have consistent data on an array of property characteristics and provide somewhat limited information on the listed properties. Often, they only include some pictures of the property, the listed price, and a phone number through which the seller can be reached. Formal developers, who have started to also list newly built properties on online platforms (in addition to their own online or offline platforms), provide slightly more structured information on the transacted property. Yet, they are bound by the format of the online platform, which often only requires submission of property price and size. Few developers provide exhaustive property descriptions in free text format, which, if extracted, needs to be processed for data analysis through text mining. Hence, property data obtained through web scraping in emerging economies, in our experience, will not be as exhaustive in terms of obtaining different property features as found in publications on developed markets (cf. Section 2.2).

Furthermore, across websites in EMDEs, there is no standardized way to record the size of the property. Sometimes, the website does not provide the option to insert size information at all. In addition, userprovided information on size might not necessarily comply with the unit required by the platform (e.g., users insert square feet even though the platform requires square meters). The matter is even more complicated in economies where local measurement units for properties are used alongside more “standardized” measurements. South Asian websites (Nepal; Pakistan) allow for the
and debt repayment. But size, complexity, and organizational remoteness create some fundamental control problems which in the context of the moshav association were practically negligible but attain significant proportions in higher order cooperatives.

# 2. Roles of Regional Cooperatives

At the time of their establishment, the goal of the regional supply cooperatives was to pool together the purchasing power of several moshav associations in order to strengthen their bargaining position in the markets and to ensure reliable provision of farm inputs and household goods. Relying on mutual liabilities of their members, the supply cooperatives soon became major instruments for raising credit--initially it was chiefly factor suppliers' credit, then the government began channeling directed short term loans through the regionals, and as the apparent stability of the regionals was established, commercial banks were also willing and eager to offer credit. Financial intermediation thus expanded over the years.

Serving as a focal point for regional activity with an improved access to credit, the supply cooperatives assumed a leading role in setting up and operating the regional enterprises and other cooperative ventures. In addition, the supply cooperative became a center for political, particularly lobbying, activity and, as a result, regional public service became the route to political involvement at the national level. The economic and the political roles of the supply cooperatives reinforce each other; economics provides a firm basis for political operation, and political lobbying promotes the economic interests of the moshavim and their regional activity.

# 3. Financial Structure

Like the moshav balance sheet, that of the supply cooperative also 'reflects its role as a financial intermediary. In Table 3, 60.9 percent of **thE3** assets of the regional organization is members' debt and an additional 18.3 percent is debt incurred by regional service and production e-aterprises. The sources of short term credit are commercial bankE, suppliers, and gray market lenders (Section D).

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