rafmacalaba/data-use-mentions-extended huggingface dataset:
the ease of entry afforded the informals that has the greatest implications for policy makers and will likely drive informal sector growth in the next decade.

## A Response to Criisis - Supplying **Labor** to **the Informal Sector**

40. The contraction of the Mongolian economy during the early and mid 1 990s caused the release of - large numbers of workers from formal sector employers a survey of privatized Mongolian enterprises conducted by Georges Korsun and Peter Murrell, together with the author, found that between 1990 and 1995 employment fell by 50% for the average privatized enterprise, slightly more for the privatized sector as a whole.<sup>48</sup> Those released from formal employment, combined with the large proportion of schoolleavers inherent in a young population, produced a steady flow of workers, many of whom had to chose between informal employment or abject poverty4<sup>9</sup> At the same time, declining real wages in the formal sector have led many formal sector employees to supplement their income by moonlighting in the informal sector.

41. The informal sector surveys conducted by the author support "response-to-crisis" as a factor contributing to the growth of the informal sector. Over half of the taxicabs surveyed said the reason they give the _duureg_ for being unemployed is that they have lost formal employment due to lay-offs or bankruptcy, or that they can not find a job to match their skills. (Taxicab drivers are generally welleducated and highly skilled.) Anecdotally, the researchers who surveyed street boot repairmen found that they were largely skilled leather workers laid-off from Ulaanbaatar's boot manufacturing and leather processing enterprises.
is employed by Eurostat to identify minimum wage earners in the Structure of Earnings Survey. To account for individuals earning less than the minimum wage, we also incorporate a lower threshold, symmetrically set at 95%.

- For part-time workers, the minimum wage value adjusts proportionally based on the number of working hours they engage in.

We may overestimate the number of minimum wage earners because some taxpayers in the first range are entitled only to the basic minimum wage. Unfortunately, our data source does not provide information on the education level.

# Results

**Despite the challenges posed by the pandemic crisis, Romania's labor market exhibited a relatively resilient performance during the period spanning from 2020 to 2021** . Despite the economic activity distortion caused by the COVID-19 crisis, the impact on the labor market was moderate, thanks to support measures adopted by authorities. Labor market adjustments were predominantly made through reduced working hours rather than personnel layoffs. Absences from the workplace were generally temporary amid the moderation of economic activity. In Romania, both direct (technical unemployment) and indirect (liquidity support measures, SME investments, tax deferrals) facilities from authorities limited adverse effects on the labor market, preventing a sharp increase in the unemployment rate. Technical unemployment support allowed job retention, providing employees with financial assistance comparable to that of other EU member states in terms of duration and amount. Notably, the unemployment rate steadily rose from 4.9% in 2019 to 6.1% in 2020, but a positive trajectory was evident in 2021, with unemployment receding to 5.6%. Consequently, with support measures, the workforce experienced a complete recovery in the last quarter of 2021 compared to the pre-crisis situation.

**Signs of stability were also observable in the wage distribution.** The mean gross wage demonstrated an upward trend, progressing from 4,458 RON in January 2020 to a noteworthy 5,295 RON by the end of December 2020 in nominal terms. Regarding the minimum wage policy, given the high
sup><sup>_σ_</sup> _c_<sup>_Lεs_ ̄)and</sup><sup>_cH_</sup> _s_ ̄<sup>=exp(</sup><sup>_μH_</sup> _c_<sup>+</sup><sup>_σ_</sup> _c_<sup>_Hεs_ ̄),respectively.Asaresultofthisprocedure,</sup> the ordering of potential entrants based on marginal costs is the same for low- and highquality provision. In other words, potential entrants who are more efficient in the provision of high-quality services are also more efficient for low-quality services, a feature that simplifies the equilibrium computation below.

In the aggregate model, we set the common pair of daily fixed costs for low- and highquality provision to _F_<sup>_L_</sup> = 128 _._ 90 and _F_<sup>_H_</sup> = 322 _._ 25, respectively, based on industry cost reports (see Mitchell and Stoney (2012) and footnote 23 for more details). In the location61
size of the area within the corresponding polygon boundary. In some specifications, we also consider the units’ _administrative type_ as defined by the 2011 Census.

Data from outer space are selected building on the remote sensing literature, as well as on recent developments in the economics literature that use satellite imagery (Burchfield and others 2006; Donaldson and Storeygard 2016; Henderson, Storeygard, and Weil 2012; Jean and others 2016). Our indicators are derived from the best open‐source satellite imagery available for 2001 and 2011, which are the years when population was counted. The indicators are computed by overlaying the boundaries of towns and villages on the processed built‐up or nighttime light imagery.

In line with the literature, we choose _built‐up share_ and _lit‐up share_ at the town or village level as the two key indicators from outer space. Built‐up share is computed as the ratio between the built‐up area in a specific polygon boundary and the total area of the polygon. Lit‐up share is the share of the surface of the polygon whose nighttime light intensity exceeds some critical threshold. In some specifications, _built‐up area_ and _lit‐up area_ without dividing by the surface of the polygonare used as alternative indicators from outer space.

The assessment of land cover has improved rapidly over the last decade thanks to more precise spatial, spectral and radiometric resolutions of satellite imageries, and to much greater computational power to process the data. Three open‐source products on built‐up cover stand out as providing the best quality at the global scale:

- _MODIS_ relies on images taken by sensors aboard satellites from the Earth Observing System program.  

- These images known as the Land Cover Type Yearly Grid are provided by the Land Processes Distributed Active Archive Center managed by the U.S. National Aeronautics and Space

14
in Teso appear to be systematically better students than those who participated in the program. These patterns all complicate causal inference in Teso district.

> 10 This comparison in Table 2 relies on the assumption that the household characteristics (i.e., parent education, fertility, and asset ownership) were not directly affected by the scholarship program by mid-2002, which seems reasonable. There is no analogous baseline household survey data.

> 11 Jacob and Levitt (2002) develop an empirical methodology for detecting cheating teachers in Chicago primary schools, which relies on identifying classes where test scores rose sharply in a single year (the year of the cheating) and not in other years, and where many students had suspiciously similar answer patterns. Although we cannot examine the second issue, since we only have total test scores for the district exams, the finding of persistent test score gains in the year following the competition argues against cheating as an explanation for our main results.

15
# Progress and Challenges of Upper Secondary Education in China

Dandan Chen Ning Fu Yilin Pan<sup>1</sup>

**JEL codes:** I21, I28

**Keywords:** Upper secondary education, vocational education, tracking, China

1 This report has been co-authored by Dandan Chen, Ning Fu, and Yilin Pan. Authors are listed alphabetically. We would like to thank Prof. Yiming Zhu and Dr. Minyu Wu of East China Normal University for their substantial input, including field data collected from Yunnan Province and interviews conducted in Shanghai. We would also like to thank Yunnan Provincial Department of Education and Tengchong County Education Bureau for their support for data collection. The findings, interpretations, and conclusions presented 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 that they represent.
</mark> _<mark>106</mark>_ <mark>, 102190.</mark> **<mark>[</mark> 4]** <mark>Parnell, S., & Ruwani, W. (2011). Sub-Saharan African urbanisation and global environmental change.</mark> _<mark>Global Environmental Change</mark>_ <mark>, 21, S12-S20.</mark> **<mark>[</mark> 1]** <mark>Peri, G., & Sasahara, A. (2019).</mark> _<mark>The impact of global warming on rural-urban migrations: evidence from global big data</mark>_ <mark>(No. w25728). National Bureau of Economic Research.</mark> **[1]** <mark>Piguet, E., Pécoud, A., & De Guchteneire, P. (2011). Migration and climate change: An overview.</mark> _<mark>Refugee Survey Quarterly</mark>_ <mark>,</mark> _<mark>30</mark>_ <mark>(3), 1-23.</mark> **<mark>[</mark> 1]** <mark>Prifti, E., Daidone, S., & Davis, B. (2019). Causal pathways of the productive impacts of cash transfers: Experimental evidence from Lesotho.</mark> _<mark>World Development</mark>_ <mark>,</mark> _<mark>115</mark>_ <mark>, 258-268.</mark> **[4]** 48
open to trade everywhere. Only a few large countries, in particular Cameroon, Chad and Tanzania, have firms that are systematically more than average globally engaged.<sup>4</sup> The main message from the analysis based on the input-output tables is similar: foreign sourcing is rising more quickly than exporting. One summary measure that underscores this evolution is the decline in the domestic value added to gross exports ratio for the manufacturing sector in exactly half of the countries in the sample. The same measure increases for most countries when calculated economy-wide, but this gives a biased impression as it is inflated by the rising importance of the service industry. Apart from the low overall GVC engagement, the input-output results also show the remarkably low regional integration of production. At the same time, neighboring or more distant sub-Saharan countries were systematically the regions that showed the most variation in importance across countries. It implies that some strong local value chains exists – in particular the economies around South Africa are more strongly integrated in that production network.

The remainder of this paper is organized as follows. In Section 2 we discuss the information contained in the WBES, the fraction of each country’s exports that the surveys represent, and the results on firm-level and country-level indicators of GVC engagement that we calculate from this data. In Section 3 we discuss how we constructed similar indicators of GVC engagement at the industry-level using the multi-region input-output table of Eora. We illustrate a number of patterns for the sub-Saharan African region, averaging over individual countries, focusing explicitly on the inputs sourced from various regions and the nature of the export linkages between different regions. In the conclusions, in Section 4, we highlight a few patterns that stand out using both data sources.

# **2. Firm-level information on input sourcing and sales destinations**

## **2.1 World Bank Enterprise Survey**

Through the Enterprise Surveys portal, the World Bank makes a series of firm-level datasets available to researchers.<sup>5</
through other non tax favored assets. In this alternative analytical framework, Besley and Meghir shown that, even in the case where the total e¤ect of an increase in the real interest rate is positive, the creation of tax favored assets will have an ambiguous e¤ect on saving.

Another important issue that has to be taken into account when dealing with voluntary pension programs is the presence of a ...scal cost. Voluntary pension programs are typically implemented by allowing tax exemptions to pension fund holders. In other cases they only allow tax deferrals. The bottom line is that, for a given amount of private saving, preferential tax treatment imply lower tax revenues and thus, lower government saving.

# 3 Existing Evidence

The empirical studies estimating the e¤ect of pensions on saving can be divided in two groups. The ...rst group analyses the case of pay as you go schemes while the second group focuses on funded schemes. Each of the groups can be subdivided in three categories depending on the type of data employed to conduct the estimations: time series, cross section or cross country.

We will next brie‡y comment on a couple of well known papers in each of the categories distinguished above. This is just to illustrate that the comparison of di¤erent studies is not straightforward since they usually measure di¤erent things. Exhaustive reviews of the literature can be found in Congressional Budget O¢ ce (1998) and in Kohl and O’Brien (1998).

14
# **4. Results**

Table 2 presents the results for an OLS regression of average GDP per capita growth on the aggregate, normalized Doing Business index and a number of control variables for the year 2009. The table reports results for five-year and 10-year average growth respectively. Data availability restricts the sample size to 175 countries at its maximum to 166 when controlling for FDI and exports.

**<u>Table 2:</u>** <u>GDP per capita growth – the Doing Business ranking (1)</u>

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|Dep. Variable<br>|Average<br>|GDPper ca<br>|pitagrowth<br>|<br>|||||
|# Years|5|10|5|10|5|10|5|10|
|DBI|2.685<br>(2.010)|5.195***<br>(1.769)|3.635**<br>(1.752)|5.513***<br>(1.728)|3.593**<br>(1.764)|5.502***<br>(1.736)|3.406*<br>(1.796)|4.573**<br>(1.980)|
|initial log<br>GDP/cap|-0.350<br>(0.272)|-0.658***<br>(0.225)
- There is strong potential to scale programs by building on pre-existing government programs, e.g., building on national social safety net programs to create “cash-plus” programs, using school infrastructure or adapting existing curriculum to implement new programs, etc.

- The use of digital technology is critical to overcome capacity constraints and improve program management, e.g., the use of digital payment systems, mobile phone-based monitoring systems, biometric smart cards, creation of digital platforms to access programs, online training programs, use of government databases to create registries.

- Strong partnerships with communities and NGOs are integral: engagement of community groups and local governments is crucial (especially for program delivery), while technical assistance from NGOs can be very beneficial.

- Understanding the basic cost structure of programs (e.g. spending on aid/services received by beneficiaries vs. delivery costs vs. staff costs, etc.) is a vital starting point for analyzing scalability (of course, extrapolating cost structure of small-scale programs to large-scale programs is difficult due to economies of scale and differences in implementation strategy, but this should at least provide guidance on whether programs are likely to involve a lot of overhead costs). The <u>Partnership for Economic Inclusion Costing Dashboard</u> is an excellent tool for providing information of cost structure for various economic inclusion programs.

- Program flexibility is integral - the ability to adapt and alter programs based on context and new research is crucial for the successful implementation of programs in new settings.

- Finally, as noted in Cull and McKenzie (2020), it is important to pay attention to the quality and capability of the bureaucracy when considering whether an intervention could be successfully scaled in a given context (the World Bank’s Bureaucracy Lab is useful for these purposes).

Based on this guidance, we believe the interventions in Table 1 that can be more easily scaled are (a) those that can build/expand on existing government programs, infrastructure, or networks,
(0.000)|(0.000)|(0.000)|
|Female|0.003|0.005**|-0.002***|0.003|0.005**|-0.002***|
||(0.003)|(0.002)|(0.001)|(0.003)|(0.002)|(0.001)|
|arcsinh(income)||||-0.001**|-0.001|-0.000***|
|||||(0.000)|(0.000)|(0.000)|
|Wage worker mean|0.119|0.109|0.010|0.119|0.109|0.010|
|Sample size|87,741|87,713|75,601|87,493|87,465|75,353|

_Notes:_ The sample is the set of individuals aged 18-65 surveyed in the CFPS 2010 and 2016, ELMPS 1998, 2006 and 2012, IHDS 2005 and 2011/12, IFLS 2000, 2007/08 and 2014/15, MxFLS 2002, 2005/06 and 2009/12, LSMS-ISA 2010/11, 2012/13 and 2015/16, KHDS 1991/94, 2004 and 2010, and PSID 2001, 2007 and 2017. We drop respondents who are not self-employed or paid workers in the baseline wave of each survey. Refer to online appendix section B for more details on variable construction in the different surveys. Each column reports marginal effects from a probit regression of an indicator for migration on an indicator for self-employment at baseline. Each regression controls for country-wave fixed effects. Columns (4)-(6) additionally control for the inverse hyperbolic sine (arcsinh) of the respondent’s income in the baseline wave.
the labor market shows that gender biases affect both the demand and supply of female labor. The case of women in science, technology, engineering and mathematics (STEM) is salient, as women are hugely underrepresented even in countries where larger proportions of them acquire STEM skills. A recent study in the US shows that women are considered intellectually inferior for jobs in science and technology and are therefore less likely to be referred than men for work that requires ‘brilliance’, ‘superior reasoning skills’ and ‘natural intelligence’ (Bian, Leslie and Cimpian, 2018).

What underlies discriminatory attitudes against women in the labor market? At the heart are often social norms that dictate the ‘place’ of women versus that of men. The former is widely perceived as having primary responsibility of the home and children with low ‘attachment to the labor market’. Even within the labor market, women are concentrated in traditionally ‘female’ occupations, those that are usually extensions of their role at home (e.g. teaching, cooking or nursing). Employers may prefer to hire women in quintessentially ‘female’ jobs – such as in office jobs or those that require more ‘feminine skills’ (i.e.: jobs that require social conversation like customer support or call center jobs). Jobs involving authority, technical knowledge and physical strength, on the other hand, are considered more appropriate for men, resulting in occupational sex segregation. Data on large US law firms in the mid-1990s indicate that when selection criteria include a greater number of stereotypically masculine characteristics, women constitute a smaller proportion of new hires (Gorman, 2005).

The distinction between the demand and supply of female labor is often obfuscated and this is reflected in the fact that the norms of each side often intersect. Take for instance 4
ues of �: To better understand the type of nonlinearity involved Figure 1 plots the time pro...le of the transition function, F (zt), over the range of zt.

# 3 Structural identi...cation and data

This paper uses a unique quarterly dataset from Malaysia to identify government consumption and government spending shocks. The data runs from 1981:1 till 2010:4. The identi...cation scheme is based on a generalised version of reduced form models in, amongst many others, Fatás and Mihov (2001), Blanchard and Perotti (2002), Perotti (2005), Cimadomo, Hauptmeier and Kirchner (2010), Corsetti, Meier and Müller (2010), Auerbach and Gorodnichenko (2010, 2011) and Bachmann and Sims (2011). The identi...cation approach is based on a recursive identi...cation scheme that aims to identify ...scal policy shocks on their timings within the system.

As in Blanchard and Perotti (2002) the basic model is computed using quarterly data and is composed of Xt = [Gt; Tt; Yt]: The variable Gt represents government spending shocks. Just as output multipliers for government purchases may differ according to the regime in which they occur, they can also di¤er for di¤erent components of government spending.<sup>11</sup> Leeper, Walker and Yang (2009), for example, have shown how the short-run multiplier for government investment shocks are smaller than those for government consumption innovations, but are more e¤ective in the longer-term.<sup>12</sup> Two types of government spending shocks are identi...ed: consumption and investment.<sup>13</sup> The government consumption de...nitions follow Perotti (2005a). Thus, government consumption spending is de...ned as gov-

> 11See Perotti (2005a, 2007).

12See Romp and de Haan
are more easily exposed to street crimes and more likely to be attacked by criminals (Langenderfer and Shimp, 2001; Holtfreter et al., 2008; Pratt et al., 2010), we use the following model to examine the determinants of approach propensity. A 0 − (3) Here is a dummy variable indicating whether the household ii ii ii cc ii _i_ was approached AAFFccFFvvh = δδ + δδββFFββFFv vvc ss + φφXX + θθ + ηη by fraudsters last year. ii refers to the same set of control variables as defined in equation FFA FFccFFvvh (1). County fixed effects (ii ) are included. The OLS estimation results using the urban XX sample are reported in Table 6. cc θθ Households are clearly not randomly approached by fraudsters. Households with higher income, worse health conditions, and better education are more likely to be approached by fraudsters. Compared to household heads that are younger and older, those with middle-aged household heads are more likely to be approached. This is perhaps because middle-aged-headed households have a higher level of income, which makes them “better” targets. And middle-aged household heads have more family responsibilities, and thus may engage more in social interactions with potential leaking of private information (i.e., adding strangers as WeChat contacts or follow WeChat public accounts for children’s extra-curriculum activities or elder parents’ old-age support).

To address the potential selection bias in household approaching, and the possibility that common factors determining both household approaching and fraud victimization, we employ the Heckman selection model (Heckman, 1979). This model first employs the probit model to predict the participation odds, and then introduces an adjustment term to the outcome model to eliminate potential omitted variable bias. To properly implement the Heckman model, the selection model should exploit exogenous variations that influence the participation decision (i.e., being approached) but that are independent of the outcome (i.e., fraud victimization).

We employ the E-commerce coverage at the community level as the