rafmacalaba/data-use-mentions-extended huggingface dataset:
The United Kingdom adopted a flexible e-invoice system in accordance with the EU Directive on e-invoicing. According to the UK’s VAT Notice on electronic invoicing, e-invoices can be issued where invoice authenticity and integrity is ensured through such means as an advanced electronic signature, an EDI, or business controls enabling a reliable audit trail between an invoice and the supply of goods or services.<sup>25</sup> Therefore, businesses can use such systems as “security of networks/communication links,” “access controls,” and “message transfer protocols” to the extent that the taxpayer can secure the authenticity and integrity of invoice data. In addition, a wide range of electronic message formats including a structured XML format, an unstructured PDF format, and traditional EDI standards are allowed as a valid e-invoice. In 2012, 55 percent of invoices in the UK were in PDF format, a relatively easy approach to e-invoicing (Institute of Financial Operations, 2012, p. 8). Taxpayers may also choose to outsource electronic invoice to a third party but they continue to assume the legal responsibilities and liabilities for the contents, storage, and production of the invoices. According to the Eurostat, 11 percent of enterprises with at least 10 employees in the UK sent or received e-invoices in 2010.<sup>26</sup>

# Non-EU Countries

# _Chile_

Under a strict invoice control system that Chile had maintained since 1954, invoices had to be stamped by the Chilean tax authority prior to use as they functioned as a proof of transaction and evidence for claiming input VAT credit to tax authority. Such strict rules made Chile pioneer e-invoicing in Latin America in 2003 that enabled the tax authority to seal invoices electronically and significantly accelerate invoice processing. The introduction of e-invoice in Chile removed the limitations of the traditional invoice administration and greatly simplified tax procedures (Piaggesi, Sund, & Castelnovo, 2011, p. 385). In 2005, the Chilean tax authority launched e- invoice portal, through which 200,000
All data used to construct our dataset are publicly available, often in transparency portals provided by the TCEs.<sup>9</sup> The structure, coverage, and quality of the raw data vary across states and often across municipalities in the same state.<sup>10</sup> For those reasons, the data require extensive upfront work to be harmonized, cross-checked, and cleaned for usage. The dataset we build is fully and publicly available on the Data Basis ( _Base dos Dados_ ) platform.<sup>11</sup> This is an ongoing project that currently covers 3,076 (out of 5,570) municipalities in 7 states (out of 27), and we expect to keep expanding the data to the extent possible.<sup>12</sup> We provide all code used to download, clean, and produce the final datasets on GitHub. Below we provide more explanation of the institutional context and key variables related to public procurement and budget execution.

# **2.1 Public procurement**

Public procurement is the process through which governments acquire goods and services. As a rule, governments are expected to run competitive tenders when buying goods and services. The specific method used, such as reverse auctions, invitations to tender or framework agreements, will depend on the nature of the object to be acquired and its estimated value. In exceptional circumstances (such as when there is only one feasible supplier or during an emergency) or when purchase values are small, officials can waive tenders and directly contract with suppliers (see Table A.2 for more details).

Our municipal public procurement dataset is organized into three tables: _tender_ , _tenderitem_ , and _tender-participant_ .

In the _tender_ table, one observation is a tendering procedure that some agency in a given municipality executes. Tenders are often comprised of several _items_ , so they should be thought of as a batch of items that are separately sold – one tender might contain, for example, ten
impacts on children’s school enrollment.

Lokshin and Yemtsov (2005) used community-level data from Georgia to assess the welfare impact of infrastructure rehabilitation projects (school rehabilitation, improvements in road infrastructure, and water system rehabilitation projects) in rural areas between 1998 and 2000. Using propensity score-matching and difference-in-difference methods, they measured the impact of water projects (including installing new or repairing existing communal water tanks, installing water treatment equipment, fitting new pumps, repairing or installing pipes, and rehabilitating wastewater management networks) on various outcomes including female wage employment and incidence of water-borne diseases. Their results indicate that water rehabilitation projects significantly reduce the incidence of water-borne diseases. The effect on female employment was however found not to be significant (which, they argue, could be explained by the low number of such projects in the sample).

4
pay higher wages, are older, and are larger than their private peers. Next, we perform a series of estimates controlling for firms’ characteristics to examine how BOS differ from private firms in terms of innovation, employment and employment growth. Using data from 2016 to 2020, we find that BOS are more innovative and larger than fully private companies, consistent with findings in China (Lo et al., 2022). In particular, participated companies - private companies with public investments - are more innovative and have higher employment relative to other types of BOS, thus suggesting the public sector invests essentially in some key sectors and innovative private companies. Furthermore, BOS grew more in terms of employment, although it is only statistically significant for participated firms.

Following this initial assessment, we explore the link between BOS and the labor market by testing for a wage premium associated with BOS. BOS, especially public enterprises, have different wage-setting mechanisms, commonly resulting in a wage premium, which, in 2
(-41.77)|
|_N_|<br>2222|<br>1694|
|_adj R_<sup>_2_</sup>|0.2266|0.2359|
|F-value|73.32|66.35|
|Note: t statistics in parentheses<br>Source: RLMS|||

The IV estimation results, using the parental SES and regional dummies, are shown in the upper panel of Table 3. The instrumental variable approach yields the rate of returns to education in Russia of around 14.3 percent for females and 8 percent for males. Females' IV parameters appeared to be tangibly larger compared to the respective OLS estimate of 7.6 percent, while for males the IV and OLS (6 percent) estimates are much closer in magnitude. The female estimates are in line with what other researchers using instruments find in Russia (see, for example, Arabsheibani and Staneva 2012).

15
The remainder of paper is as follows. Section 2 describes the data under consideration and provides descriptive statistics. Section 3 presents the empirical strategy to identify the impact of the intensity of robot use in HICs on greenfield FDI flows from HICs to LMICs. Section 4 concludes.

# **2. Data and Descriptive Statistics**

The relationship between new automation technologies and GVCs is analyzed by combining data on the use of industrial robots from the International Federation of Robotics with data on greenfield FDI flows from the fDi Markets Database.

# a) <u>Foreign direct investment</u>

The data on foreign direct investment are taken from the fDi Markets Database, which is compiled by the Financial Times Group. fDi Intelligence has been tracking and verifying bilateral crossborder “greenfield” investment projects since 2003. The resulting fDi Markets Database provides annual information on the number and value of investment projects until 2015. Unlike other investments, which can be sticky and slow to change in response to other factors, these greenfield FDI data represent announcements and are therefore forward-looking. The database also enables the identification of tasks within industries, as it provides a business activity marker – for example, within apparel manufacturing, it distinguishes between manufacturing per se and design/retail services etc.

The literature distinguishes four types of FDI: (a) natural resource–seeking investment (focused on exploiting natural resources); (b) market-seeking investment (serving large domestic or regional markets); (c) strategic asset-seeking investment (driven by investor interest in acquiring strategic assets through mergers and acquisitions); and (d) efficiency-seeking investment. Of interest here is the last type of investment, which is typically export-oriented; leverages local factors of production to reduce costs; and involves the transfer of production and managerial know-how, access to distribution networks, and sources of finance. Greenfield FDI, by definition, excludes strategic asset-seeking FDI through mergers and acquisitions. Further, because these data go beyond country aggregates and consider differences at the industry level, it enables the
sample, as expected, the probability of treatment jumps discontinuously from zero to one at the cutoff. These patterns in the conditional probabilities of treatment motivate our selections of partially-fuzzy and sharp RD designs for the phase-3 and phase-4 SLQAT samples, respectively.

_Local smoothness in the density function of SLQAT pass rates_ Rejection of local smoothness in the density function of the assignment variable at the cutoff may suggest manipulation of the assignment variable _z_ (McCrary 2008). Manipulation is plausible in our case as the SLQAT pass rate cutoff for program participation was advance public knowledge, and schools and perhaps even program managers may have an interest in a particular treatment outcome. The pass rate that the school _actually_ received on the SLQAT may be subject to partial manipulation, which is typically benign.<sup>25</sup> However, PEF staff exercise full control over the calculation of SLQAT pass rates, as well as their reporting, thus, introducing the risk of complete manipulation.<sup>26</sup> Given that we use SLQAT pass rates calculated by us based on the individual student test score data as our measure of the assignment variable, and these calculations nearly always match the pass rates calculated by PEF, manipulation would have to occur at the individual student level. Manipulation at this level is less straightforward; nonetheless, we cannot rule out the possibility.

Figures 4 and 5 present frequency histograms of schools with bins equal to the integer values of SLQAT pass rates for the SLQAT and cutoff neighborhood samples, respectively, separately by phase. A simple visual inspection of the SLQAT pass rates for both the phase-3

> 25 The day the SLQAT is offered, the classes which are tested, and the specific SLQAT papers offered at the school are stochastic elements from the perspective of the school and outside its control.

> 26 PEF staff may face incentives to manipulate the pass rates of marginal passers downwards (to just below the cutoff) if, for example, the program budget limits the number of schools that the program can be offered
being almost twice as likely to be married as men (15% vs 8%), and about 2.5 times as likely to have a child (18% vs 7%). On the labor market front, while almost 85% had ever worked, only 40% had worked for pay in the month before the survey, and only 3% report working in a formal job. Across all of the variables reported in Table A1, the only statistically significant difference between the treatment and control groups is the share of respondents from Southern Province. This broad balance is confirmed in Panel D which reports a joint F-test of equality across the treatment and control groups for the variables in Panels A-C.

Recent national surveys demonstrate that our sample is significantly more educated and less likely to have started families than the broader population of Rwandan youth. Specifically, only about 8% of Rwandan women aged 24-30 have attended some tertiary education—one of the eligibility criteria for our program—while 62% are married and 77% have given birth, rates almost 4 times higher than our sample (Rwandan National Institute of Statistics, 2021). Tertiary educated women are generally significantly better off than their less-educated peers, with living

> 19Appendix Tables A6-A7 present balance tables of pre-program measures of soft skills for the treatment and control groups.

8
## **3.3 Exit Rates**

Although firms can adjust their material costs and their payroll, some firms remains unprofitable following the lockdown, or more unprofitable than prior to the crisis. This applies to firms with high fixed costs and those receiving a large revenue shock, especially if their baseline profitability is also low. The profit loss would trigger an increase in firm exit rates. Exits are primarily thought of as firms closing their operations and filing for bankruptcy but could also refer to firms’ leaving the formal sector and thus disappearing from the corporate tax data.

We estimate the potential increase in exit rates by exploiting the panel structure of our data. We calculate the average exit rate among loss-making and profit-making firms prior to 2020, as well as the overall average (benchmark) exit rate, for each of the three impact sectors. At baseline, profit-making firms display a 1015% chance of exiting in a given year and loss-making firms a 20-30% exit rate. These patterns are stable across countries, as shown in Figure 2b, and across sectors and over time. We then apply the exit rates for loss-making and profit-making firms respectively, after shifting the profitability distribution for 2020 through the revenue shock and the material and labor cost adjustments, and hence obtain the overall share of firms exiting. Figure 2c shows that exit rates increase by 112% (147%) on average compared to the baseline for the three-month (five-month) lockdown. The increase in exit rates varies across countries, as the share of profitable firms also varies substantially and because the increases are calculated over a small (albeit stable) baseline exit rate. The increase in exit rates varies from 47% to 283% for the three-month

# **4 Implications for Government Policy and Public Finances**

We now study the implications of our simulations for government policy and public finances. First, we estimate to what extent wage subsidies—a widely discussed policy tool, common in many European countries (Giupponi and Landais, 2020)—
**Figure 11: Exporter Entry Rates by Broad Sector Panel A. Entry - Averages in 2005-2007 Panel B. Entry - Averages in 2008-2009**

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participation. In essence, good measures of GVC participation are needed to discern the importance of a given country’s involvement for the domestic economy, and whether it primarily manifests itself as input supply to downstream nations and industries, as utilization of foreign inputs, or as a combination of both. Assessing the extent to which the production and exchange of goods and services is interconnected globally is, however, a complex task. The most accurate and thorough approach requires data at the individual company level from numerous countries, especially when aiming for a global perspective. Obtaining such extensive and specific data poses a major hurdle, since very few countries generate the required data (Bems & Kikkawa, 2021). Owing to the shortage of such data, researchers have dedicated significant effort over the past twenty-five years to methodically combine transaction data from customs with national aggregate production data. They have developed accounting measures at the country-sector level based on global databases of inter-country input-output (ICIO) relationships. This approach ensures a scientific rigor in their analysis, despite well-known limitations due to assumptions in terms of homogeneity, proportionality and aggregation that such data require, as discussed by de Gortari (2019), Antr`as (2021) and Bems and Kikkawa (2021) among others. The resulting country-sector level measures have allowed to quantify the extent to which production processes have become global in the past decades, and how countries and sectors participate in GVCs, together with other features of participation, such as direct and indirect supply and demand inter-linkages. The study by Antr`as (2020) calls this body of work “the broad view of GVC participation” while Antr`as and Chor (2022) define it as the “macro-approach” to GVC
|
||(0.055)|(0.058)|(0.147)|(0.082)|(0.062)|(0.082)|
|Treatment student * % of friends treated|0.136*|0.038|0.258*|0.248**|0.056|0.179*|
||(0.081)|(0.080)|(0.155)|(0.106)|(0.079)|(0.100)|
|Spillover student * % of friends treated|−0.280*|0.170|0.185|−0.154|−0.034|−0.050|
||(0.159)|(0.177)|(0.380)|(0.213)|(0.196)|(0.217)|
|Number of friends|0.034*|0.074***|0.151***|0.080***|0.036*|0.104***|
||(0.018)|(0.017)|(0.043)|(0.019)|(0.019)|(0.020)|
|Control for baseline value of dep. var.|Yes|Yes|Yes|Yes|Yes|Yes|
|_P_-value treatment * (% of friends)<br>=spillover * (% of friends)|0.0387|0.492|0.859|0.0788|0.669|0.334|
|Observations|3,853|3,845|3,828|3,866|3,853|3,888|

_Source_ : Authors’ analysis from student surveys.

_Note_ : Dependent variable is an index of
improve export performance. Studies like Hoekman and Nicita (2008) and Anderson and Marcouiller (2002) show that bilateral tariff rates significantly reduce export performance. In this study, I use two indices to measure the restrictiveness of tariff policies. Both indices are constructed by Kee et al. (2009).<sup>4</sup> The first index is trade tariff restrictiveness index (TTRI) which shows the restrictiveness of domestic trade policies on imports. The second index is market access trade tariff restrictiveness index (MATTRI) which shows the ease of foreign market access of the country. Unlike simple or weighted average tariff rates, these indices are well grounded in trade theory and provide sound aggregate measures of trade restrictiveness.

Despite of the substantial decreases in tariff rates since 1960s’ in many countries, the gap in trade performance across countries has not closed. Clarke (2005) and Morrissey (2005) note that the adoption of significant trade liberalization policies in the majority of African countries have resulted in a reduction of import tariff rates from 33% in early 1980s to 15% in 2002. However Gupta and Yang (2006) shows that the share of manufactured goods in total exports remains at about 30% during the same time span. Focusing on the low export performance of African countries, Iwanow and Kirkpatrick (2009) show that liberalizing trade is not sufficient to achieve high export performance.

> 2 See Berg and Krueger (2003) and Hallaert (2006) for literature surveys on the link between trade and growth.

> 3 Throughout the text, I use business environment and investment climate interchangeably.

> 4 The methodology developed in Kee et al. (2009) is built on the work of Anderson and Neary (1994,1996) on trade restrictiveness. A detailed discussion on the construction of the indices is provided in Kee et al. (2009).

2
- in the new version of the questionnaire (i.e., “Given that the household has at least one component belonged to the original sample selected from a population, does the individual belong to the same population or are they new (newborn or immigrant)?”).

- - 7, using other stored variables and making some accurate assumptions. This variable should be directly asked in the We artificially created the individual multiplicity factor, vvnew version of the questionnaire (i.e., “Does the individual of the original sample change parish from 2009 to 2013 (years of the original samples?)”).

- - 7 8. - 9 10, using Based on the values of vv , we computed the household multiplicity factor vv other stored variables and making some accurate assumptions.

- - We artificially rebuilt the response indicator variable in each wave, vv4, for each individual selected in the original  and vv sample (not for the incorporated individuals), even if the individual did not respond We stored the inclusion probability, vv(i.e., in the current panel data, the weight is missing).

- We computed the GWSM weight that does not rely on the concept of the parent household, which can be a complex operation in practice.

- We computed the final weights using the standard calibration estimator and applied these for the cross-sectional and longitudinal estimates, creating a unique vector of sampling weights that simplifies the coherence of the individual and household estimates.

# 7. CONCLUSIONS

Given the complexity of the topics covered, we now retrace our main steps to provide a unified picture of the various results. In this paper, we explored the problem of enhancing the quality of cross-sectional and longitudinal estimates from surveys that are obtained by combining samples chosen at previous times with given rules to track panel members as they move away from the location of their initial survey interview.

We have seen that the issue is complicated and that action needs to be taken on several fronts, which refer to
on these indicators, we generate five mutually exclusive and exhaustive binary outcome variables: (1) DI & no employment; (2) DI & employment; (3) employment & no DI; (4) public work & no DI; (5) no DI & no employment & no public work.

In addition, we look at four quarterly indicators of health care use: GP visits, outpatient specialist care visits, hospital days, and total spending (social security plus out-of-pocket spending) on prescription drugs. Indicators of health care use are included in our data from 2009.

We extend the analysis with job quality indicators derived from the administrative panel database. We generate a binary indicator of earnings above the minimum wage, after adjusting the monthly wage to hours worked. We define a binary indicator of full-time job, which equals one if the weekly hours of work are at least 40. We generate a binary indicator of working in a skilled job, which includes all occupations except for elementary occupations, with elementary occupations corresponding to International Standard Classification of Occupations (ISCO) code 9. Finally, using the entire sample in the administrative database, we calculate the year-specific median of the total factor productivity (TFP) of firms, weighted by firm size.<sup>8</sup> Based on this indicator, we define a binary indicator of above-median employer TFP.

# **4 Empirical Framework**

## **4.1 Control and Treatment Groups**

In our empirical analysis, we estimate the impact of the 2012 reform on DI recipients subject to the compulsory health reassessment—partially disabled individuals with health impairment below 80%, who were under age 57 at the end of 2011. A limitation of our data is that we do not have information on the reassessment procedure itself; we observe exits from the DI system, but not the reason for leaving the system. Consequently, it is not possible to isolate those who lost their benefit as a results of the revision from those