rafmacalaba/data-use-mentions-extended huggingface dataset:
well as market participants-businesses (including SOEs, the Privatization Investment Funds (PIFs) and banks), consumers, workers, and the general public-both understand the basic concepts of competition and regulation, and are motivated to act in such a way as to capitalize on the role that competitive forces can play in fueling economic prosperity and growth. There are several areas where this challenge is particularly pronounced and where there is a priority for action-in particular mobilizing t-aining, pragmatic policy advice and public education about competition and regulation.

_Monopoly Register._ One of the primary instruments by which the AMC implements competition policy is through its Register of Monopoly Enterprises - a policy instrument commnon to Russia and many other CIS countries.<sup>4</sup> Uzbek enterprises that are deemed as "dominant"defined by statute as generally having a market share of at least 65 percent, and under certain conditions a market share of at leaLst 35 - percent are listed on AMC's Register and therefore must declare (register) their prices and profits for AMC approval. In addition, registered monopolists, once they agree with their input sellers and c.utput buyers on volumes, delivery times, and other conditions (as well as prices) must register these transaction terms with the AMC along with their expected profits. In certain cases-typically for infrastructure ("utility") monopolies-the AiC directly determines prices and profits.

As of October 1, 1999 there were 716 enterprises and 1,924 prodlucts listed in the **AMVIC's** Monopoly Register, **of** which 91 enterprises and 205 products were registered as monopolies at the national (Republic) level, with the remaining (and vast majority) of monopoly firms and products registered in the AMC's 14 regional offices. Table 1 indicates the sectoral distribution of the registered monopolies. In Uzbekistan there are approximately 176,800 firms with business licenses, the vast

> 4 A description of Russia's competition policy framework is contained in Broadman (2000).

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# **Understanding Informality: Comprehensive Business-Level Data and Descriptive Findings**<sup>1</sup>

**Adam Aberra Gemechu Aga** _The World Bank The World Bank_ **Filip Jolevski Nona Karalashvili** _The World Bank The World Bank_

**Keywords** : informality; development; business; workers; performance

**JEL Classifications:** D20, D22, E24, J46, L20, O10, O17

> 1 The authors are grateful for the comments provided by Norman Loayza, Jorge Rodriguez Meza, David Francis, and Joshua Wimpey, as well as the participants at the World Bank Global Indicators Group Seminar Series. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors They do not 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. The authors can be contacted at <u>aaberra@worldbank.org, gayanaaga@worldbank.org, fjolevski@worldbank.org; and nkaralashvili@worldbank.org.</u>
section III of this report, most international migrants are younger, and have terminal degrees in either vocational or secondary education. These groups are strongly over-represented in migrant flows in comparison to the general population. In contrast, tertiary educated people are underrepresented in current migrant flows.

The following sections of this paper proceed as follows. Section II includes an overview of the data used, section III provides an overview of aggregate migration patterns for Uzbekistan, demographic and related information on migrants, and details on the profile of sending households. Section IV investigates the drivers of migration decisions, focusing mostly on the panel survey data which allow analysis of the patterns of departing/current/returning migrants over time. Section V provides analysis of household well-being, including remittances and monetary measures, as well as subjective measures. Section VI concludes.

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have 0.27 sons more than non-participants and spend significantly more time collecting firewood. The magnitude of the difference in the number sons suggests the economic impact, if any, is small. However, the difference in time to collect firewood is large, making it important to control for the differences in time constraints. We discuss this variable in further detail in the next section. Overall, table 3 suggests that the program does not appear to be targeted in placement because there are no other significant differences between women in treated and untreated districts. These data illustrate that the women we sample in treated and untreated districts are largely similar in covariates.

Another source of endogeneity could arise from the potential placement of the program in villages where women have a relatively high level of bargaining power and thus are more likely to respond favorably to the treatment. We use administrative block-level<sup>10</sup> data from the Indian censuses of 1991 and 2001 on village-level female bargaining power. Matching the year that _Mahila Samakhya_ entered a block to the most recent census before that year, we compare the levels of bargaining power in blocks blocks which later received _Mahila Samakhya_ with those that did not. Results for t-tests of equality, presented in table 4, show that there are no significant differences in any of the block-level measures of female bargaining power: sex ratio for the entire population and for children up to the age of six, the scheduled caste or scheduled tribe sex ratio, and the literacy ratio are all statistically similar across treatment assignment. Similarly, the sex ratio of workers and non-workers also does not vary between treated and untreated blocks. Thus, these t-tests also fail to yield evidence that would cause us to believe that the program was systematically targeted at villages where women were either less empowered or already more empowered, and hence more likely to respond to the treatment.

> 10Blocks are small groups of villages and are the administrative unit directly above the village council. Within each district, the placement decision of _Mahila Samakhya_ is made
by the residence approach as our main results. But for robustness we also use the nationality-based and

> 3 Refinitiv’s SDC Platinum is one of the most widely used databases on transaction-level research (Henderson et al., 2006; Kim and Weisbach, 2008; Bruno and Shin, 2017). Dealogic, an alternative database, yields similar estimates of issuance activity.

> 4 In the case of China, domestic issuances are those performed by firms residing in Mainland China and issuing in Mainland China’s bond markets (Shanghai, Shenzhen, and over-the-counter markets). Therefore, we consider issuances in Hong Kong SAR by firms residing in Mainland China as international issuances.

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been participating in the labor force. Therefore, under the Trabajar and Plan Jefes y Jefas programs, about half of the employment gain came from unemployed workers, and the other half arose from inactive workforce participants.

Latvia’s public works program is an interesting case study. First, Latvia launched and implemented a public works program in response to a global financial crisis. Second, Latvia provides lessons on how public works programs can respond to a significant deterioration in labor market conditions. Third, relatively few public works program evaluations exist for upper-middle income countries (Latvia is an upper-middle income country) compared to low-income and lower-middle income countries.

This paper evaluates Latvia’s WWS program as a crisis response safety net instrument. Subject to data constraints and other restrictions, this paper complements other studies by evaluating the targeting performance of the WWS program and the effectiveness of the WWS program as a crisis mitigation instrument. The paper relies primarily on a unique household survey administered to 3,000 households during December 2010 - March 2011.

The findings of the paper are as follows. First, WWS targeted the poor households very well. Second, WWS was successful at increasing short-term household incomes by 37 percent relative to similar households not benefiting from the program, and helped those households to cope with the crisis. Third, the foregone income was low, and some of the foregone income is accounted for by loss of other safety net payments suggesting that the WWS did not replace other labor opportunities. The WWS program increased household income by LVL 67 while the actual WWS payment was LVL 100 per month. Thus, the Latvian WWS program experience highlights the usefulness of public works programs as short-term safety net instruments during times of crisis, even in upper-middle income countries.

The remainder of this paper is organized as follows: Section 1.1 presents an overview of the WWS program; Section 2 describes the data used in this paper; Section 3 outlines the methodology used to evaluate the WWS program’s targeting performance and impacts; Section 4 presents results
We have summarized the results of the many econometric specifications to explain the potential determinants of city governance in the synthesis in Table 6 (the full set of regressions are available upon request)<sup>18</sup> .

# **7 Concluding: Future Research and Emerging Policy Implications**

## **7.1 Brief synthesis**

In this paper we attempted to contribute to the field of urban governance and globalization through an empirically-based exploration of some key determinants of the performance of cities. This empirical inquiry was made possible through the construction of a worldwide database for cities that contains variables and indicators of globalization (at the country and city level), of city governance, and of city performance (access and quality of infrastructure service delivery). This city database integrates existing data with new data gathered specifically for this research project. We find that good governance and globalization matter for city-level performance in terms of access and quality of delivery of infrastructure services, and also that globalization and good city governance are related. There appear to be dynamic pressures from globalization and accountability that result in better performance at the city level. Furthermore, we find that there are complex interactions between technology, governance and city performance, as well as evidence of a non-linear (u-shaped) relationship between city size and performance, challenging the view that very large cities necessarily exhibit lower performance and pointing to potential agglomeration economies. Our framework also suggests a way of bridging two seemingly competing strands of the literature, namely viewing the city as a _place_ or as an _outcome_ . We find evidence that port cities seem to be in general more dependent on good governance for the city performance variables that matter for globalization (access to cell phone, internet access) and that capital cities tend more to serve local sewerage access better (water sewerage, electricity).

A preliminary analysis of city level data from EOS 2004 corroborates the main findings in our paper (summarized in Annexes A and B). These results were corroborated when replacing 2003 data
20 By themselves, these selection criteria are ideal for our purposes. However, donors needed local partners to establish the stations and idiosyncratic conditions within communes affected which communes yielded such partners. Ahokpossi (2009) argues that potential radio entrants in Benin took the commune as the relevant market and took commune-specific characteristics into account in deciding whether they would locate. Commune-specific characteristics, related to economic conditions and political struggles within a commune, therefore ultimately affected where radios were established For example, in a detailed case study of one of these community radios, Radio Tanguieta located in Tanguieta commune in Atacora department, Gratz (1999) reports on the political contestation over the locally-elected committee to oversee the radio and manage its funds. Control of the community radio rested in the hands of local politicians and Gratz indicates concerns about embezzlement and over-spending on salaries of numerous presenters representing different ethnic groups. Community radio projects are subject, then, to the same political risks of local elite capture and clientelist and ethnic politics as community-based projects in other sectors.

Since the unobserved characteristics of communes that affect these projects could plausibly affect education outcomes, we do not exploit inter-commune differences in community radio access to identify radio effects on education outcomes. Instead, all estimates control for commune fixed effects and identify the influence of community radio on education outcomes based solely on intracommune variation in radio access.

Even within a commune, however, villages with access to more within-commune community radio broadcasters may have unobserved economic and cultural characteristics that promote better education outcomes. We constructed our sample of villages to be able to address such concerns. The 210 villages in the study were selected from maps showing the location of villages, radio towers, and major road networks. We restricted the sample frame to villages that were
Figure 13: Formal and informal employment distribution by age cohort in manufacturing: Rwanda (2013) <!-- Start of picture text --> Entrant 1−5 years<br>6−10 years 10+ years<br>Employment in formal establishments Employment in informal establishments<br>1 − 4 5 − 9 10 − 19 20 − 99 100+ 1 − 4 5 − 9 10 − 19 20 − 99 100+<br>1 − 4 5 − 9 10 − 19 20 − 99 100+ 1 − 4 5 − 9 10 − 19 20 − 99 100+<br>Share of employment (%)<br>80<br>60<br>40<br>20<br>0<br>80<br>60<br>40<br>20<br>0<br><!-- End of picture text --> _Source:_ Establishment censuses obtained from the statistical agencies of the selected countries; see section 3. _Note:_ The reference is the total employment for each age cohort and formality status. The figure is constructed based on data for establishments in the manufacturing sector. Establishments with missing employment or age data and state-owned are excluded.

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when accounting for measurement errors, our main messages persist across the different specifications. Thus, risk-induced vulnerability remains the main driver behind vulnerability, and idiosyncratic vulnerability plays a more significant role than covariate vulnerability. Additionally, there is substantial variation in vulnerability across departments. While some of our main messages fall when increasing the measurement error to 50 percent, the occurrence of a measurement error of this scale is highly unlikely.

# 6.3. Relying on 50 Autorepresentative Municipalities

**We take advantage of the fact that 50 of the included municipalities are autorrepresentative and reestimate vulnerability to poverty using this restricted sample.** This robustness test is useful for estimating covariate vulnerability, especially as the estimation might suffer from the lack of representativeness in the rest of the municipalities. Our findings on the relative importance of idiosyncratic and covariate shocks hold (see Annex 4). The ratio of idiosyncratic to covariate vulnerability is very similar to our baseline results (2.5 versus 2.9). Still, covariate vulnerability is slightly lower when only considering the 50 auto-representative municipalities (0.052 versus 0.095). Overall, the vulnerability rate is lower under this model specification than under the full model specification. This is mainly because the 50 auto representative municipalities are not representative of the overall country in many aspects, and the underlying estimation should not be taken as a reference.

# 6.4. Decreasing the Probability Threshold

**To test the validity of our main messages, we decrease the probability threshold, which defines if a person is vulnerable or not, to 25 percent.** This means that a person is vulnerable if their probability of falling into poverty is higher than 25 percent in the next two years, or a yearly probability of 14.5 percent. Similarly to our robustness check on measurement errors, we apply this robustness check to the 2019 crosssection of the underlying household data.

**Under this threshold, the vulnerability rate in El Salvador is much higher and our main messages reinforce themselves.*
Food and Non-food Expenditures and CPI and Food Price Developments, 1998-2002**

<!-- Start of picture text --> Food as % of consumption<br>70 16 CPI and Food Price developments 1998-2001 135<br>14<br>60 130<br>1998 2002 12<br>50 10 125<br>40 8 120<br>6<br>115<br>30 4<br>2 110<br>20<br>0 105<br>10 -2<br>100<br>0 -4 Annual CPI e.o.p. Annual Food e.o.p<br>1 2 3 4 5 6 7 8 9 10 -6 CPI-Index (RHS) Food-Index(RHS) 95<br>Consumption deciles July: 1998 1999 2000 2001 2002<br><!-- End of picture text --> The same situation applies to developments in the real effective exchange rate and the composition of tradables versus non-tradables in each decile’s expenditure pattern (see Figure 13). The appreciation of the zloty during the latter part of the period induced all expenditure groups to spend less on tradables and more on non-tradables, indicating once again that the income effect dominates the substitution effect.

- 13  For further discussion of this issue, see Chapter 3 of Poland Living Standard Assessment, World Bank (2004).

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</mark>

# **<mark>2. Data and poverty rates</mark>**

National and international poverty rates are estimated using nationally representative householdlevel surveys that collect detailed food and non-food consumption data. Table 2 shows the household surveys that are used by the eight countries in South Asia to estimate poverty rates.

**<u>Table 2. South Asian household-level surveys used to estimate poverty</u>**

|**Country**|**Survey**|**Year**|
|---|---|---|
|Afghanistan|Living Conditions Survey (ALCS)|2012|
|Bangladesh|Household Income and Expenditure Survey (HIES)<sup>6</sup>|2010|
|Bhutan|Living Standards Survey (LSS)<br>|2012|
|India|National Sample Survey 68<sup>th</sup>Round (NSS)|2011|
|Maldives|Household Income and Expenditure Survey (HIES)<sup>7</sup>|2009/2010|
|Nepal|Living Standards Survey (LSS)|2010|
|Pakistan|Pakistan Social and Living Standards Measurement (PSLM)|2011|
|Sri Lanka|Household Income and Expenditure Survey (HIES)|2012|

Source: South Asia Harmonized Micro Dataset (SARMD).

Living standards vary considerably among countries in South Asia. Table 3 lists the international extreme poverty rates of each South Asian country, along with their GNI per capita, and number of extreme poor. The international extreme poverty rate of each country has been determined by

> 6 Bangladesh conducted the latest round of the HIES in 2016/17.

> 7 Maldives conducted the latest round of the HIES in 2016, but the data are not yet available as of October 2018.

4
_Ingo Borchert and Mattia Di Ubaldo_ exceptions clauses, safeguard mechanisms, movement of natural persons, rules of origin for judicial and natural persons (ownership and nationality), type of dispute settlement.

# **3.2 Services Trade Data**

The most comprehensive dataset including bilateral and sectoral services trade flows is the newly published International Trade and Production Database for statistical estimation (ITPD-E). This dataset is described in detail in Borchert et al. (2021). The ITPDE contains consistent data on international and domestic trade for 243 countries, 170 industries, and 17 years. The data are constructed at the industry level and cover 17 services sectors. The time series commences in 2000 and extends to 2016.

The ITPD-E is constructed using reported administrative data and intentionally does not include information estimated by statistical techniques. The primary source of services trade data in the ITPD-E are the ‘WTO-UNCTAD-ITC Annual Trade in Services Database’ and the UN ‘Trade in Services Database’ (UN TSD). Whilst the nature of services trade raw data remains qualitatively unchanged, the data in ITPD-E are appreciably enhanced by blending two principal sources of statistics, a conservative use of mirroring techniques, and casting all services trade data in the latest EBOPS 2010 format. These features, as well as the unprecedented coverage of industries and countries with consistent international and domestic trade data, renders the ITPD-E well suited for the estimation of gravity models.

Over the recent past, there have been substantial efforts by multilateral agencies and national statistical offices to improve both the quality and coverage of services trade statistics, and these improvements are fully reflected in the ITPD-E. By contrast, services trade data prior to 2000 is widely understood to be of lesser quality, with only few reporting 17
the countries are categorized as less developed.

# **3.3 Roads**

We combine geo-referenced household survey data with spatial data on road expansions as used by Berg et al. (2018) and Jedwab and Storeygard (2021).<sup>3</sup> The development of road infrastructure is tracked over 40 years from 1971 to 2014. Data on both the layout and road type are included, relying on layouts from Nelson and Deichmann (2004) and completed with information extracted from Michelin maps. The road-layout information used by Nelson and Deichmann (2004) was primarily constructed using information from the U.S. Digital Chart of the World database, originally constructed by the U.S. Defense Mapping Agency. Road surface information was obtained using 64 Michelin road maps for the northeast, northwest, and central-south regions of mainland sub-Saharan Africa. Roads are divided into the following categories: earth/dirt, paved, improved, or highway. We combine the last three of these categories into one ”main road” category. Michelin also collects statistics on road development projects, and its maps are meant to specify the year during which a specific road was made operational. However, Michelin maps for some states and time periods do not exist. Overall, the road network in Africa has steadily expanded from 239,018 km in 1971 to 334,391 km in 2014. Figure 1 depicts the evolution of main roads from 1971 to 2012. We combine the road network information with the geo-referenced households from the DHS. Overall, the mean distance of households from the main roads is 66 km in the DHS and 14.6 km in LSMS surveys.

> 3The roads digitization effort of Jedwab and Storeygard (2021) benefited from funding under the DFID/World Bank’s Strategic Research Program on Transport Policies for Sustainable and Inclusive Growth.

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