rafmacalaba/data-use-mentions-extended huggingface dataset:
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agreements through extension to non-union members and unaffiliated employers. In some countries, the difference between these two measures can be substantial. France is an example. Union density and bargaining coverage are relatively straightforward indicators since they can be expressed in numerical terms. However, particularly in developing countries, these data are often only partial and difficult to obtain.

The third dimension looks at the structure of collective bargaining. This is difficult to summarize in a single or small number of measures. Typically, two aspects are considered. One is the extent to which bargaining is centralized—for example, at the national, sectoral (intermediate), or establishment level. The other is concerned with the degree of coordination, i.e., the extent to which negotiations are guided by “peak” organizations (e.g., industry or national unions or employers’ associations); by tripartite social pacts; by pattern bargaining; or are determined in some way by government-imposed terms. Collective bargaining structures are usually measured by indices to capture the range from low to high centralization and coordination. Most often, these two aspects are measured separately though some researchers combine them in a single “corporatism” indicator. There is considerable debate about how well indices capture collective bargaining arrangements, since subjective judgements are required and since the arrangements can vary in different situations within a single country.

Empirical work on the effects of unions and collective bargaining usually takes one of two forms (Aidt and Tzannatos 2002). “Micro” analysis estimates various effects (on wages, employment, productivity, etc.) of union membership and collective bargaining on union workers or firms relative to non-union ones, or between workers/firms under different collective bargaining arrangements. This literature is usually based on data from household or establishment surveys in a single country. “Macro” analysis is concerned with many of the same variables but at level of national economies, using cross-country comparisons based on aggregate data.

The research on the impacts of unions and collective bargaining
or informal items) will pass-through their unrecovered VAT in the form of higher final prices to be paid by consumers. Source: CEQ Handbook, Chapter 7 (Jellema & Inchauste, 2018).

> 48 To estimate the informal purchase share by decile in the West Bank and Gaza, the estimations of “self-consumption” (nonmarket informal consumption available in the PECS 2016/17) was deducted from “total informal consumption” (average from 10 similar countries in Bachas et al. 2020).

> 49 In an ideal VAT system (without exemptions and informality), there would not be VAT indirect effects or cascading effects since all producers and sellers along the distribution chain are able to receive a VAT credit for the VAT they paid on their inputs. However, in the presence of exemptions and informality, the VAT input credit mechanism is broken. In the Cost-Push Model used in the current study it is assumed that sellers of exempt and informal goods cannot claim their VAT input credit, hence they passthrough their unrecovered input VAT through higher final prices paid by consumers.

> 50 IMF (2022). West Bank and Gaza: Selected Issues.

30
Policy Research Working Paper 9988

# **Abstract**

This paper examines if and how deeper economic integration with high-income nations impacts industrial performance. It exploits Poland’s accession to the European Union in 2004 as a source of variation in the degree of market integration with Germany. Using data on Polish manufacturing firms over 1995–2013, the paper finds that EU accession was followed by significant within-firm growth in output and productivity, notably in industries in which Germany was more specialized at the moment of accession. Increased flows of German investment to these sectors played an important role in shaping these effects.

This paper is a product of the Development Research Group, Development Economics. 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://www.worldbank.org/prwp. The authors may be contacted at pbastos@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
Importantly, we can rule out some potential mechanisms. On the supply side, we can exclude any mechanism that operates through the credit registry, as our findings are based on loan approvals rather than loan issuances, and loan approvals are not recorded in the Peruvian credit registry. On the demand side, we can rule out complementarities in borrowing whereby an initial loan from our partner bank increases demand for credit from other lenders; few of the borrowers in our sample who received loans from competing lenders first borrowed from our partner bank.

Though we cannot pin down a single explanation, we argue that the precise mechanism by which this free riding occurs does not influence our broad conclusions; so long as a loan approval by our partner bank _causes_ (directly or indirectly) other lenders to approve the same borrowers, the private returns of identifying credit worthy borrowers and expanding the financial supply will diverge from the corresponding social returns.

Our paper relates to several literatures. First, we complement the literature examining how variation in the credit supply decisions of one lender influences the credit supply of competitors (Agarwal et al. 2018, Karlan and Zinman 2018, Azevedo et al. 2019, Burke et al. 2019). Through variation in loan terms or access to credit, each of these papers finds evidence that an initial loan from one lender causes other lenders to provide access to credit as well. Our paper is distinct in this literature in that we identify information spillovers that occur even before the initial loan is issued, and are therefore more deleterious to private incentives to expand the credit supply. Also of note, much of this focuses on consumer lending (Burke et al. 2019), or microfinance (Agarwal et al. 2018, Karlan and Zinman, Azevedo et al. 2019), while our focus is on SME lending.

Second, our paper relates to the literature on the consequences of information sharing through credit registries on bank competition and credit supply (eg. Jappelli and Pagano 2002, Djankov et al. 2007, Hertzberg
as land based financing instruments – such as property taxes, exaction and development impact fees, and land sales or leases. Land-based instruments provide cities with an opportunity to enhance urban efficiency by intensifying the use of land and managing densities while sharing the cost of infrastructure provision with private landowners and developers.

# **2. Land Valuation Methods**

The success of tools used for urban expansion and land based financing is based on robust systems for determining land values. Developed countries rely on a number of forms of available data and supporting institutions to assess land values. Among these are market data

> 7 The 2009 World Development Report (World Bank 2008) provides a definition of the stages of urbanization as follows: Early 0-25% urban, Intermediate 25-75% urban; Advanced 75% urban and more.

> 8 Consider China, where government acquisition of rural land for urban expansion has generated much public discontent and protests.  In the United States, urban revitalization projects are blocked by lawsuits undertaken by dissatisfied property owners who are unwilling to sell their landholdings to make way for new development.  The conventional way of dealing with property owners’ resistance is either to buy them out or to force them out using the government’s compulsory purchase power (Hong, 2011).

3
Panel C: Guinea

# Panel D: Mali

<!-- Start of picture text --> Guinea Mali<br>Error term Random Effect Error term Random Effect<br>2 4 .4<br>.2<br>1 .1 .2<br>2<br>0 0 0<br>0<br>-1 -.1 -.2<br>-.2<br>-2 -2 -.4<br>-2 -1 0 1 2 -.2 -.1 0 .1 .2 -2 -1 0 1 2 -.3 -.2 -.1 0 .1 .2<br>Inverse normal Inverse normal Inverse normal Inverse normal<br>Quantiles of Pearson residuals Quantiles of Random Effects Quantiles of Pearson residuals Quantiles of Random Effects<br><!-- End of picture text --> Panel E: Niger <!-- Start of picture text --> Niger<br>Error term Random Effect<br>3<br>.2<br>2 .1<br>1 0<br>0 -.1<br>-1 -.2<br>-2 -.3<br>-2 -1 0 1 2 -.2 -.1 0 .1 .2<br>Inverse normal Inverse normal<br>Quantiles of Pearson residuals Quantiles of Random Effects<br><!-- End of picture text -->

# **4. Evaluation exercise: Comparison of geospatial and census-based estimates of headcount poverty in Burkina Faso**

Before presenting estimates of headcount poverty rates for the four focus countries that lack recent census data, we conduct a sensitivity analysis with data from Burkina Faso. The availability of a recent census in Burkina Faso creates an opportunity to assess the estimates produced with geospatial covariates and the unit context model against officially adopted EBP census-based estimates as described below
regulation will have—and specifically the share of the labor market it will affect—different levels of enforcement might lead to different economic outcomes. In most low-income countries enforcement tightening cannot take place due to the lack of administrative and monitoring capacity governments face. Likewise, the logic that more enforcement would lead to a decline in aggregate employment also plays an important role when deciding the optimal level of enforcement (when that is an option). With tighter enforcement, less productive firms would be the most affected by the minimum wage and this would lead to important negative employment effects. Based on this rationale, Badaoui and Walsh (2022) use information across 22 developing countries with minimum wage regulations<sup>10</sup> to argue that an enforcement regime based on worker complaints can be used to target enforcement toward high-productivity firms and thus avoid the employment cost. The authors show that, while an increase in random enforcement may have large negative employment effects, if a substantial percentage of informal firms could not be viable at the minimum wage, a workers’ complaints-based enforcement would more likely rise compliance and wages in higher-productivity firms but have less impact on lower-productivity ones where workers have little incentive to complain. Contrary to the logic that more enforcement leads to bad employment outcomes Meghir et al. (2015) argue in the context of Brazil that enforcement-tightening does not increase unemployment, but it does increase wages and total welfare by enabling a better allocation of workers to higher-productivity jobs. Recent reviews of the economic impact of minimum wage regulations include Dube (2019),<sup>11</sup> , Manning (2021a) and Neumark (2019); and focusing exclusively on LMICs: Broecke et al. (2017), Belman and Wolfson (2016) and Bhorat et al. (2017).

# **4.2.1 Minimum Wage: Impact on Living Standards**

**The impact of the minimum wage on wages and labor earnings:** Starting with the evidence gathered for developed countries
|U.N. 1988 revision (prelim.)|
|Chamnel Islards|Mar86|136 F|UNPVSR<br>4/87|Based on UNPVSR<br>7/86|Based on UNPVSR<br>7/86|
|Chile|Apr 82|11330 F|UNPVSR<br>7/86 (official<br>est.)|U.N. 1988 revision (prelim.)|U.N. 1988 revision (prelim.)|
|China (excl.<br>Taiwan)|Jul 82|1031883 F|Bank projection<br>from official<br>1984 est. using official<br>grouth rate of 1.08X|Bank est.|Bank est.|
|Colarbia|Oct 85|27867 J|Official<br>est.|Bank est.|Bank est.|
|Camoros|Sep 80|335 F|Bank projection from census,<br>excluding Mayotte Island<br>(population 50.74 thousand)|Bank sector report|Bank sxctor report|
|Congo, People's<br>Rep. of the|Jan 85|1854 F|Bank projection from census|Bank est.|Bank est.|
|Cook Islands|Dec 81|18 F|USBOC<br>1985|||
|Costa Rica|Jun 84|2417 J|UNPVSR<br>1/87 (official<br>est.)|U.N. 1988 revision (prelim.)|1980-85, Celade printout<br>2/87; 1985-90, Bank<br>projection|
|C6te dlvoire|Apr 75|6710 F|U.N. 1988 revision (prelim.)|1980-85, U.N. 1988 revision<br>(prelim.);<br>1985-90, Bank<br>projection|U.N. 1988 revision (prelim.)|
|CLba|Sep 81|9724 F|
# **Table 11. Use of sequences one year later**

||Sequence<br>(1)|Coaches<br>group<br>(2)|
|---|---|---|
|A. Teachers that continue teaching 7<sup>th</sup>grade Science<br>at the same school one year after the training.|27%|33%|
|B. 7th grade Science Teachers in the same school<br>that continue using the sequence after the training|100%|89%|

_Source:_ Author's analysis based on experimental data generated for this study.

_Note:_ Responses to one year follow up. Numbers show the percentages of teachers that still taught seventh grade science, and still use the teaching sequence one year after the intervention.

8
|13.5|38.4|23.7|
|Lower Secondary Teacher in Priv. School|34.1|n.d.|14.8|n.d.|57.6|n.d.|
|Upper Secondary Teacher in Pub. School|36.5|27.7|15.4|15.1|42.5|63.5|
|Upper Secondary Teacher in Priv. School|34.7|n.d.|15.4|n.d.|66.4|n.d.|
|University Teacher in Pub. School|38.0|n.d.|17.5|n.d.|34.5|n.d.|
|University Teacher in Priv. School|38.9|n.d.|16.1|n.d.|31.0|n.d.|
|**The mixed-skilled group**|**34.1**|**32.9**|**8.9**|**5.7**|**32.8**|**37.2**|
|The agricultural group|41.0|35.9|4.2|3.7|19.6|23.2|
|The low-skilled group|35.6|34.1|6.2|4.4|49.4|58.0|

n.d.: No data in the survey Source: Own calculations based on ENIGH96 survey

**Table 3. Age by Occupation in Urban areas**

|**T f Oti**||**1988**|||**1994 **|||**1999**||
|---|---|---|---|
. <u>http://documents.worldbank.org/curated/en/643471520429223428/Volume-1-Overview</u> <mark>World Bank (2020). BraSim Microsimulation tool: technical document. Poverty and Equity Global Practice, World Bank. Available at:</mark> <u><mark>https://documents1.worldbank.org/curated/en/796601595496808862/pdf/BraSim-MicrosimulationTool-Technical-Document.pdf</mark></u> <mark>World Bank (2021a).</mark> _<mark>Global economic prospects, January 2021</mark>_ <mark>. World Bank, Washington, DC. Available at:</mark> <u><mark>https://openknowledge.worldbank.org/bitstream/handle/10986/34710/9781464816123.pdf</mark></u> <mark>World Bank (2021b).</mark> _<mark>The impact of COVID-19 on the welfare of households with children: an overview based on high frequency phone surveys</mark>_ <mark>. World Bank and UNICEF joint publication. Available at: -</mark> <u><mark>https://www.unicef.org/media/117301/file/The%20Impact%20of%20COVID 19%20on%20the%20welfare%20of%20households%20with%20children.pdf</mark></u> 44
Policy Research Working Paper 6095

# **Abstract**

This paper applies an econometric analysis to estimate the average and distribution benefits of rural electrification using rich household survey data from India. The results support that rural electrification helps to reduce time allocated to fuelwood collection by household members and increases time allocated to studying by boys and girls. Rural electrification also increases the labor supply of men and women, schooling of boys and girls, and household per capita income and expenditure.

Electrification also helps reduce poverty. But the larger share of benefits accrues to wealthier rural households, with poorer ones having more limited use of electricity. The analysis also shows that restricted supply of electricity, due to frequent power outages, negatively affects both household electricity connection and its consumption, thereby reducing the expected benefits of rural electrification.

This paper is a product of the Agriculture and Rural Development Team, Development Research 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 author may be contacted at skhandker@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
# **4.2 Results**

# **4.2.1** **_Do post-TTB export values reach pre-TTB levels?_**

Table 3 presents one set of results, in which we define _Exportshijk_ as _ln(1+real exports_ **_hijk_** _)_ .<sup>12</sup> Specification (1) uses the full sample of 746 antidumping cases and ten years of data. Specification (2) uses the subsample of 126 antidumping cases targeting China’s exporters, while specifications (3) and (4) use the subsamples of 352 cases targeting high-income exporters and 268 cases targeting other emerging exporters (non-China), respectively. For each of the four specifications, the first column presents information on the average level of exports associated with a given year for antidumping imposed by high-income trading partners _i_ , and the second column addresses antidumping imposed by emerging economy trading partners _i_ . The superscripts denote whether average exports that year were statistically different from zero. The third column provides additional information from a _t-test_ regarding whether the averages within a year across the two categories of policy-imposing countries are statistically different _from one another_ .

Consider Table 3 specification (1) which covers the full sample of data. Overall, average annual exports are always statistically greater than zero, even during the years that the antidumping import restriction is in effect. Furthermore, average annual exports to high-income markets are always higher than exports to emerging markets. More importantly, the time trends across the two categories of policy-imposing countries are the same and they align with expectations. First, average exports increase considerably between _t-2_ and _t-1_ and then fall beginning when the TTB is imposed in year _t_ , declining again in _t+1_ and _t+2_ while the TTB is in effect. While expected, this result is important as it confirms that the HS-06 import data is sufficiently disaggregated for this context so as to capture the trade-impacts of the antidumping policy which itself is sometimes applied at an even more
7 thousand Georgians in 2017, under the analyzed policy scenarios. These results are a lower-bound estimate, as they consider out-of-pocket medical expenses only, and leave out other possibilities to reduce poverty through enhanced fiscal revenues and reduced public outlays on tobacco-related diseases.

However, the theoretical framework and decomposition of the ECBA also warn about possible short-term negative consequences on some poor and vulnerable smokers, who may be overburdened by a disproportionate price increase on their budgets, while they manage to reduce smoking. For example, some households who live out of poverty—but close to the poverty line—could still be vulnerable to income fluctuations and to fiscal impoverishment if taxes on tobacco are raised but smokers do not adjust their consumption behavior. Policy should accompany tax increases with complementing interventions to facilitate behavioral adjustments—to induce and assist smokers to quit tobacco—and to cushion temporary income shocks. As smokers quit and price elasticities increase in the medium- to long-term, the health and economic benefits of tobacco taxes expressed in the ECBA can be expected to offset those transitional income losses.

<mark>There are possible improvements to this empirical application of the ECBA in Georgia. First, it is often argued that the calculation of price-elasticities of demand from household survey data—which generally, as in the case of Georgia, omit price information—fails to account for quality shredding and substitution effects. This would be a source of concern to the extent that smokers in Georgia switch consumption to lower-price tobacco when faced by a price increase. The estimations of own-price elasticities of filtered cigarettes adapting the Deaton methodology (Deaton 1990; 2018) show a negative correlation of household incomes and their sensitivity to price changes in tobacco. Despite some potential quality shredding, consumers reduce overall cigarette consumption when faced with higher prices. Moreover, lower-income groups of the population are systematically more responsive to price changes in cigarettes. Smokers from poorer households in Georgia are more likely to adjust consumption, and to benefit most from the medium- and long-term benefits of reduced smoking. On the other
>Offering evidence from Egypt, this paper builds on the aforementioned literature on the impact of Internet job search by the unemployed on their employment prospects. Even though the cited literature spans several studies related to these questions, these studies focused for the most part on the United States. In the context of the MENA region, where digitalization and Internet use among the youth have spread rapidly in recent years, no studies have examined these questions. This paper therefore investigates these questions in the context of Egypt, using representative panel data on the Egyptian labor market, more specifically</mark> the two most recent survey rounds of the Egypt Labor Market Panel Survey (ELMPS), conducted in the years 2012 and 2018.

Using data from these two survey rounds and tracking individuals’ job trajectories, I first examine the impact of Internet job search in 2012 by the unemployed on their employment prospects within 5 years following their unemployment spell, conditioning on individual characteristics in the preperiod. I also examine the impact of Internet job search on wage growth for employed job seekers. Taking advantage of the panel dimension of the data, I also rely on a first difference model to examine the impact of the change in Internet job search on the change in the probability of labor force participation and employment for working age individuals between 2012 and 2018. Moreover, I estimate a fixed-effects model to examine the impact of Internet job search on the

> 2 See Kuhn (2003) for general representation of Internet job search and Internet recruiting and the possible effects on the labor markets and policy implications.

> 3 Also see Faberman and Kudlyak (2016) for a review of the studies on the labor market and online job search and <mark>Autor (2001) on a discussion of the various mechanisms through which Internet affects worker-firm communications.</mark>

3