rafmacalaba/data-use-mentions-extended huggingface dataset:
the smaller is ...rm size dispersion within the industry. These ...ndings are robust to alternative measures of ...rm size dispersion, the time period chosen, estimation procedures, and functional speci...cation. Both tangible and intangible sunk costs have a statistically signi...cant in‡uence on the size distribution of ...rms.

This paper provides indirect support for one of the most fundamental welfare properties of contestable markets: the absence of any sort of ine¢ ciency in production in industry equilibrium. Incumbents whose outputs di¤er substantially from the minimum scale of operation cannot withstand the pressure of potential entrants who, in the presence of low sunk costs, can e¤ectively exploit the opportunities offered by the presence of ine¢ ciency and waste in production through hit-and-run entry. Thus the forces of contestability, facilitated by low sunk costs, continuously work to weed out ine¢ cient ...rms through a process of "creative destruction". Our ...ndings provide speci...c guidance for the design of appropriate public policies towards investment and changes in regulatory regimes to enhance the contestability of markets. Accelerated depreciation policies, favorable tax treatment of leasing operations, and the removal of regulatory restrictions on the types of capital (e.g., new versus used) deployed by entrants are some obvious candidates.<sup>22</sup> Acknowledgements We are indebted to William Baumol, Christine Kessides, Dennis Mueller, Mike Toman, two anonymous referees, and the General Editor for their very helpful comments. Any remaining errors are our own.

# Appendix

Our sample consists of all 4-digit U.S. manufacturing industries for which a complete set of variables could be obtained. Since the estimation of our basic equation entails a logarithmic transformation, some industries were eliminated because of zero values of the RES variable.<sup>23</sup> Industries were also excluded because: they were badly de...ned;
# TABLE V

# HUMAN CAPITAL AND ECONOMIC DEVELOPMENT – COMPARING MEASURES

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|Human Capital - Learning|0.065***||||0.047**|0.049**|0.055**|0.050**|
||(0.019)||||(0.023)|(0.022)|(0.023)|(0.023)|
|Human Capital - Penn World Tables||0.033***|||0.019|||0.021|
|||(0.011)|||(0.012)|||(0.036)|
|Human Capital - Schooling|||0.016***|||0.009||0.012|
||||(0.006)|||(0.006)||(0.020)|
|Human Capital - HDI Education Index||||0.020**<br>(0.008)|||0.008<br>(0.009)|-0.022<br>(0.022)|
|Observations|107|107|107|107|107|107|107|107|
|R-squared|0.275|0.261|0.255|0.240|0.291|0.290|0.281|0.298|

_Notes:_ Dependent variable: annual growth rates averaged across 2000-2010. Human Capital -
disapproval. Interestingly, the disapproval for married women’s work was higher than the levels recorded in response to a similar question in the American General Social Survey nearly 45 years ago. Using content analysis of stereotyping in job advertisements in India for instance, Anand (2013) finds widespread use of gender specific terms for jobs such as that of a receptionist, a telecaller, data entry operator and a teacher. Terms range from the benign ‘Receptionist only – Female’ to comments regarding age and physical attributes: ‘beautiful and broad minded (F) office assistant and personal secretary’, ‘up to 25’ and so on. Conversely, sales and field jobs are earmarked as a ‘boys-only’ section, with keywords like ‘field boys’ and ‘sales boys’. Khandelwal (2002) similarly finds that male managers are stereotyped into working in production and sales whereas women work in ‘soft fields’ like Human Resources and Public Relations.

In a more recent analysis of 800,000 job recruitment advertisements sourced from an online job portal in India, Chowdhury et al (2018) find that it is common to mention the preferred gender in job advertisements. Further, these advertisements tend to favor men over women. Although advertisements for professional occupations exhibit less explicit gender bias, they too are not completely gender neutral. In all professional jobs, those advertisements that target men specify/offer a higher salary.

Gender stereotyping and pervasive bias in attitudes during recruitment is something of a self-fulfilling prophesy. Once women view the labor market as being discriminatory, or ‘feel’ that they would not be selected for a job, they may abandon the search. Discriminatory or non-transparent hiring practices send misleading signals to women about the kind of jobs they are suitable for, in turn dampening their aspirations. Women construct their identities through the lens of these gender stereotypes and willingly accept their disadvantaged place in the workforce (Ridgeway, 1997). In a review undertaken for the World Bank to unpack gender constraints and opportunities in India’
text --> 80%<br><!-- End of picture text --> <!-- Start of picture text --> 90%<br><!-- End of picture text --> <!-- Start of picture text --> 100%<br><!-- End of picture text --> Note: Baseline information refers to the ORBIS first baseline using the algorithm developed without complementing any databases, overlap firms mean firms identified in ORBIS and external sources, and External Supplementary sources refer to the firms that were identified only through external sources.

Source: Authors’ elaboration based on ORBIS and Global BOS database.

On average, supplementary databases increased the number of firms identified with state participation by 47%, although with variation across regions. ORBIS is a limited source to provide a full landscape of the state footprint in the markets. Using supplementary databases (See Annex 3) beyond ORBIS as well as implementing a protocol to validate the information with government counterparts was key to overcome these limitations. For example, in the SSA region more than 60% of the firms with state participation were identified through complementary and official sources (Figure 3). In Moldova, Montenegro, and Serbia, 16
(World Value Surveys, 1981-2009). Moreover, identification of firm responses is facilitated by the unexpected and ―quasi-experimental‖ nature of the crisis and its severity, the high flexibility of Indonesian labor markets at the inception of the crisis, and the richness of the Indonesian manufacturing census dataset that not only provides detailed information on employer characteristics, but also gender disaggregated employment information by broad occupational categories (e.g white- and blue-collar workers).

The paper is organized as follows. The next section reviews the related literature and provides background information on the Indonesian crisis. The data are discussed in Section 3, which also provides a static overview of sorting patterns by gender and a bird‘s eye view of employment and wage adjustment during the crisis. Section 4 assesses sorting effects by examining whether firms that employed proportionately more women were more likely to exit and by analyzing how, among continuing firms, employment growth was correlated with the initial gender composition of the workforce. Next, Section 5 examines the evidence for differential treatment by assessing whether women were proportionately more likely to be fired than men in firms that adjusted the size of their workforce. It not only assesses whether men and women were treated differently at the firm-level, but also whether the crisis led to a change in such discriminatory practices/differential treatment of men and women within firms.<sup>4</sup> We therefore test how employment adjustment and wage setting during the crisis differed from non-crisis periods. Section 6 examines the evolution of the gender wage differences to assess whether women suffered more severe wage cuts than men, and the extent to which there is gender-specificity in employment-wage tradeoffs. Conclusions are presented in Section 7.

The appendix validates our firm-level analysis with an analysis of the evolution of wages and employment using data on manufacturing employees from SAKERNAS, a nationally representative labor force survey in Indonesia. We cannot tell from this labor force survey the characteristics of the employer, but the labor force data enable us to control for individual characteristics and the comparison with
# **3. Sampling Methodologies**

For each of the methods (satellite mapping, segmentation, grid squares, Qibla method, and random walk) and assignment mechanisms (random assignment, spatial clustering, and extreme spatial clustering), 10,000 simulated samples were drawn and relevant probability weights calculated. Each sample consisted of ten structures per PSU. For the cases in which the household sample was selected in two stages, two segments of five households were chosen within each PSU for segmentation, and two grid boxes of up to five households were randomly chosen in the grid square selection. This section provides further detail on the selection methods and describes the weight calculations necessary to achieve unbiased results.

# _3.1 Satellite mapping_

A full mapping of the PSU entails using satellite maps to identify the outline of each structure (see appendix). In this case, we used maps publically available on Google Earth and maps of the EA boundaries provided by the Somali Directorate of Statistics. From these maps, the structures inside each PSU can be assigned numbers (either by hand or digitally) and selected easily in the office with simple random sampling. The coordinates of the selected households can be loaded onto GPS devices to assist interviewers’ locating efforts.

This approach is the closest of the proposed study methods to the gold standard of a well‐implemented full household listing. The main differences are that in a field listing, enumerators can exclude ineligible structures, such as uninhabited and commercial buildings, and include information not available from satellite maps, such as the identification of individual units within multi‐household structures. In addition, whereas listing is always done just before the data collection, the satellite maps may be out of date, leading to under‐coverage of newly constructed units and/or selection of units that no longer exist. As noted in the previous section, the maps used for this paper were about one year old at the time of the initial analysis. The historical imagery from Google Earth indicates these maps are
users need to make use of the sampling weights, EA identifiers, and strata identifiers. As mentioned above, these three variables are present in all four datasets of the HP. Statistical software typically provide packages that enable use of these variables to estimate nationally representative indicators, such as Stata’s</mark> _<mark>svy</mark>_ <mark>set of commands which allow the running of statistical models with complex survey data. Users must use the sample weights (</mark> _<mark>pw</mark>_ <mark>) as probability weights to obtain valid point estimates, EA identifiers (</mark> _<mark>ea_id_obs</mark>_ <mark>) and strata identifiers (</mark> _<mark>strataid</mark>_ <mark>) to obtain valid standard errors.</mark> <mark>As noted above, variables that identify panel units end with the</mark> _<mark>_obs</mark>_ <mark>suffix. Users are advised to use these variables when performing panel analysis. Panel identifiers exist for EAs (</mark> _<mark>ea_id_obs</mark>_ <mark>), parcels (</mark> _<mark>parcel_id_</mark>_ <mark>obs), households (</mark> _<mark>hh_id_obs</mark>_ <mark>)</mark> _<mark>,</mark>_ <mark>individuals (</mark> _<mark>indiv_id_obs</mark>_ <mark>), plot managers (</mark> _<mark>plot_manager_id_obs</mark>_ <mark>), and respondents (</mark> _<mark>respondent_id_obs</mark>_ <mark>). Moreover, while EA and stratum variables remain fixed, households may move during
reduces communication costs between regions rather than trade costs. _(2) Mainly used for business purposes:_ Survey data indicates that nearly half of HSR travel is for business purposes, with leisure and commuting making up the remaining major segments (Lawrence et al., 2019; Lin, 2017).7 _(3) Designed for middle-distance journeys:_ As pointed out by Lawrence et al. (2019), HSR dominates travel between 150 km and 800 km and competes with air travel for distances up to 1,200 km.8 _(4) Frequent, convenient, punctual, safe and high-quality service:_ Compared to airlines, HSR is less impacted by weather, features simpler security checks, and involves shorter waiting times. Unlike airports, HSR stations are centrally located, offering more convenient access. Passengers can also use phones and the internet during travel, reducing the opportunity cost of time—an advantage particularly valuable for business travelers.9 _(5) Stable and relatively low price:_ HSR fares in China are relatively low compared to other countries, making it an attractive option for passengers across various income levels.

In short, the expansion of HSR has had a profound impact on business travel, reshaping the flow of information and business opportunities across regions in China. This development has facilitated better matching between production and consumption, as well as between different production hubs.10

**Network Effects of the HSR** Beyond these important attributes, the most defining feature of HSR is its _network effects_ . While direct HSR connections between cities are crucial, the value of indirect connections –whether through transfers across multiple HSR lines or integration with other transport modes –plays an even bigger role. For instance, the Zhengzhou-Xi’an line was initially an isolated route, serving only passengers between these two cities. However, after connecting to the BeijingGuangzhou HSR line in 2013, its passenger volume surged by 43 percent, and passenger-kilometers increased by 72 percent. By 2016, almost half of the
|---|---|---|---|
|Source of inefficiency|ICT|Power|Transport|WSS|Total|
|Underrecovery of costs|n.a.|110|—|38|148|
|Overstaffing|—|9|n.a.|0|9|
|Distribution losses|n.a.|33|n.a.|4|37|
|Undercollection|n.a.|5|—|1|6|
|Low budget execution|0|0|0|0|0|
|Total|0|157|0|43|200|

Source: Derived from Foster and Briceño-Garmendia 2009. Note: Estimations based on operating performance data up to 2007. — = not available; n.a. = not applicable Underpricing of power and water services costs Mali about US$148 million each year. In the power sector, it is estimated that the average total cost of producing electricity has been $0.33 per kilowatt-hour historically (as of 2007), but the average effective residential tariff is only about $0.20. This is sufficient to cover operating and maintenance costs (barely), but not investments. Overall, the power utility covers 50 percent of costs, leaving the capital investment unfunded. The financial burden associated with 44
[0.49]||
|N_(all households)_|1415|134||1312|237||799|750||417|1132||166|1383||
||1,|549||1|,549||1|,549|||1,549|||1,549||
|N_(households with children)_|568|68||675|130||576|569||374|1030||164|1349||
||6|36|||805||1|,145|||1,404|||1,513||

_Note: significance level p< 0.01 - ***, 0.05 - **, 0.1 - *; the value displayed in the "Differences (T-C)" column are the differences in the means across the groups; +dependency ratio defined as the ratio of dependents (children under 18 and adults 60+) to working age adults (aged 18-59 years old);_<sup>_++_</sup> _sample limited to household with children;_<sup>_+++_</sup> _F-test of joint-orthogonality excludes the proportion of children attending school because it is undefined for households without children; all expenditure and debt values are deflated across regions and months into average 2017 Turkish Lira and are windsorized at the 99th percentile;_<sup>_++++_</sup> _The food consumption score (FCS), reduced coping strategies index (rCSI), and livelihoods coping strategies index (LCSI) are calculated as per the WFP's methodology described in section 3, for the FCS a higher score indicates better food consumption outcomes, for the rCSI and LCSI a lower score indicates a better coping strategies outcome (i.e. fewer coping strategies employed)._ 45
. This strong cultural norm might lead them to devote additional resources such as cash transfers, in priority to more and better food, potentially explaining these findings.

Also at round 2, conditional cash transfers appear to outperform UCTs in improving anthropometric outcomes. They have a statistically stronger impact than UCTs on weight-for-age z-scores and they are improving arm circumference-for-age and height-for-age z-scores, while UCTs have no significant impacts on those measures.

> 19 The average yields in kg/ha over the 1998-2008 were 838 for peanuts, 795 for millet and 955 for sorghum. In 2009, they were 722, 774 and 920 respectively, while in 2010 they were 830, 843 and 1004, respectively. Food and Agriculture Organization of the United Nations. 2014, FAOSTAT database, available at <u>http://faostat3.fao.org/home/E (accessed on 10/30/2014).</u>

> 20 For the focus groups, we selected one village from each of the four treatment groups. In each village, we conducted a focus group discussion with 10 men from different recipient households and a separate focus group discussion with 10 women from different recipient households.

17
a4ln(W1it)*ln(W2it) + a5ln(W1it)*ln(W3it) + d1Trend + d2Trend<sup>2</sup> + d3Trend*ln(Qit)+d4Trend*ln(W1it ) + d5Trend*ln(W2it ) + where i denotes banks and t denotes years. C is total operating plus financial costs, Q is total assets, W1 is the ratio of interest expenses to total deposits and money market funding (proxy for input price of deposits), W2 is the ratio of personnel expenses to total assets (proxy for input price of labor) and W3 is the ratio of other operating and administrative expenses to total assets (proxy for input price of equipment/fixed capital). We also include a trend to capture the influence of technical change leading to shifts in the cost function over time. As in most papers, the estimation is done under the restrictions of symmetry and degree one homogeneity in the price of inputs. However, our results do not change if we drop these constraints.

The Lerner Index for Jordan indicates rising market power among banks in the system over most of the period 1994-2006 (see Figure 3). According to data from Bankscope, the Lerner index has risen steadily from 0.14 to 0.41 (or 41%) between 1994 and 2006. This decline in competition is consistent with what we find using the H-statistic. Relative to measures reported for other countries such as Mexico and the European Union (EU) (see Maudos and Solis, 2007 for Mexico and Fernandez de Guevara et al., 2005 and 2007 for the EU), the current numbers for Jordan seem to indicate greater evidence of market power, and hence a lower degree of competition.<sup>8</sup>

# **6. Conclusions**

The banking sector in Jordan is concentrated. However, the link between concentration and competition is not always clear. Hence, an analysis of competition in the banking sector requires a
# **1. Introduction**

Accurate measurement of food consumption is key to the assessment and monitoring of multiple welfare dimensions, including food security, nutrition, health, and poverty. These household welfare measures are, in turn, central to the design of many development projects and policies aimed at improving well-being. It is therefore critically important for effective policy design and targeting to ensure that food consumption is collected with minimal measurement error.

With economies developing, and consumption patterns rapidly changing across the developing world, some traditional survey modules are becoming less informative over time. One recent trend is the growth in the popularity of meals prepared, packaged, and consumed outside the home (in commercial establishments and locations such as schools, work, restaurants or on the street) in contrast to the more traditional meals prepared and consumed within the home. As a result, food consumed outside the house is taking up an ever-growing share of households’ food budget. For example, the percentage of households reporting consuming meals outside the home increased from 20 to 46 percent between 1981 and 1998 in the Arab Republic of Egypt, from 23 to 39 percent between 1994 and 2010 in India, and from 42.3 to72.4 percent in Colombia (Smith, 2015; Smith et al., 2014; DANE). In China, household per-capita expenditure in FAFH rose at an average annual rate 9.5 percent from 2002 to 2011, and the share of FAFH in total food expenditure rose from 18.2 to 21.5 percent (You, 2014).

However, food consumption survey modules that were designed with more traditional eating patterns in mind may be failing to appropriately measure this growing segment of food consumption, with important consequences for welfare measurement. In India, Smith (2015) find that the increase in undernourishment at the time of falling poverty rates can be partly explained by lack of measurement of calorie consumption from FAFH. Borlizzi and Cafiero (2017) show that failure to account for children’s school meal
Policy Research Working Paper 10899

# **Abstract**

This paper studies the impact of working with same-race coworkers on individuals’ retention at firms. Using administrative employer-employee data from Brazil, the paper exploits unexpected deaths of workers from different racial groups as exogenous shocks to peer group composition. The findings show that a decrease in the non-white share of coworkers reduces the retention of non-white workers but does not affect the retention of white workers. The effects are driven by non-whites quitting and moving to new jobs with more peers of the same race than in their old jobs. The findings highlight how peer dynamics can contribute to racial segregation across workplaces.

This paper is a product of the Social Protection and Jobs Global Practice. 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 kfietz@worldbank.org and aiko.fiete.schmeisser@uni-potsdam.de.

_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