rafmacalaba/datause-encoder-data huggingface dataset:
31 organizational vehicle through which workes take on the responsibilities to monitor and often diret quality control and production processes.

The training needs generated by now production and control systems go beyond traditonal requirements. Not only must the worKforce have quantitative analytic skills, it must be skilled in the use of computer and other electronic technologies. Furthermore, team systems require communication and group skills to facilitate the operation and coordination of team tasks. Factory studies show increasing percentages of skilled workers, many of them newly cross-trained (in additional skills), accompanied by declining percentagas of the traditional semi-skilled (see, for example, Milkman and Pullman 1991). Even the latter require new training in organizational skills (for teamwork, participation, job rotation) and/or more substantive skills development for the monitoring of expensive microelectronicrun machinery (Kem and Schumann 1984).

Training and retraining programs have therefore taken on added importance throughout the Industrialized world. This is true both because of the rapid pace of technological change itself, which means that employees need frequent retraining, and because of the nature of new work organization and technologies. The problem for firms and govemments is how to build up the necessary pool of skilled workers, how to build up the abilities and flexibility of the less skilled, and how to develop reliable structures and incentives for continual training and retraining.

Union involvement in the promotion and operaton of training programs can be a valuable asset in successful upskilling programs. At the firm level, such involvement can encourage cooperative labor-management relations and form part and parcel of the building of a *productivity coalition" (Streeck 1984b) that includes management, union and workforce. Local unions and/or works councils are often well placed to help run training programs in a way that appears fair and wins the trust of the worktorce.

The German Training **System** The German case also illustrates the constructive role that unions can play in the running of a successful national system of vocational education - as part of a productiviy coalition at the macro
# **4 Estimating Spillovers in Tax Compliance**

## **4.1 Background**

There is a large literature on nudges and tax compliance (Antinyan and Asatryan, 2024), but there is relatively scant evidence on the social interaction effects behind these interventions. We designed and implemented an intervention based on the framework presented in the previous sections to illustrate its potential to capture social interaction effects in tax compliance.

The intervention took place in a large municipality of Argentina where dwellings are billed and required to pay a municipal property tax on a monthly basis (the _Tasa por Servicios Generales_ ). The treatment consisted of a one-page personalized letter with information on the current billing period, past due debt, and how to pay online or in person.<sup>8</sup> The randomized treatment assignment was conducted in two stages—first at the street block level (clusters), and then at the taxpayer account/dwelling level (units). In the first stage, we randomly divided blocks into four categories with different intensity of treatment, as depicted in Figures A.2 and A.3: (1) pure control blocks where no accounts were treated, (2) blocks with 20% of the accounts treated, (3) blocks with 50% of the accounts treated, and (4) blocks with 80% of the accounts treated. These different treatment intensities were designed to assess whether spillovers depend on the saturation of our information campaign at the block level (namely, low, medium, and high saturation levels).<sup>9</sup> In the second stage, we randomly selected accounts within the latter three groups of blocks according to their treatment saturation to receive the letter. The experiment was run on residential dwellings present in the municipality in 2019. The timeline of the intervention is displayed in Figure A.4. The letters were delivered between September 28th and October 7th, 2020, corresponding to payments due on October 9th, 2020, as well as past due debt (if any).

## **4.2 Administrative Data**

We use a combination of administrative databases provided by the revenue agency of the municipality where the experiment took place. The main database is constructed from the monthly bills issued to account holders between January 2018 and December 2020. The unit of observation is an account ( _cuenta_ ), which coincides with a dwelling unit. The data contain the following billing details and demographic characteristics of the account holder ( _titular_ ): account number (unique ID), address, block number, name of locality (neighborhood), year and month of the bill (12 bills per year), monthly fee (in pesos), paid fee

> 8Figure A.1 in the appendix provides an anonymized example of the intervention letter. Our simple design emphasized actionrelevant information, in accordance with De Neve et al. (2021) who show that simplified tax letters are an effective way to increase tax compliance.

> 9The choice _p_ 1 = 20%, _p_ 2 = 50% and _p_ 3 = 80% attempts to balance parsimony with the flexibility to detect nonlinearities in direct and spillover effects without having to estimate too many parameters. See Section 3.4 for further discussion.

20
**Table A.3. Estimates of Firm Death Rate in Existing Literature**

||||**Sample**||**Death**|**Annualized**|**Attrition**||
|---|---|---|---|---|---|---|---|---|
|**Study**|**Country**|**Type of firm**|**size**|**Period**|**rate**|**Rate**|**rate**|**Note**|
|Cabal (1995)|Dominican<br>Republic|micro and small enterprises|n.r.|n.r.|n.r.|22%-29%|n.r.|e.|
|Daniels (1995)|Zimbabwe|micro and small enterprises|n.r.|n.r.|n.r.|11.5%|42%|e.|
|Davies and Kerr (2015)|Ghana|All Manufacturing|1000|10<br>years|21%|2.1%|22%||
|||0-9 worker manuf.|386|10<br>years|24.7%|2.5%|28.5%||
|Fajnzylber et al. (2006)|Mexico|self-employed individuals (own-account<br>workers or employers)|n.r.|2<br>years|n.r.|30.1%|n.r.||
|Fisscha (1994)|Jamaica|micro and small enterprises|n.r.|n.r.|n.r.|4.1%|n.r.|f.|
|Frazer (2005)|Ghana|selected manufacturing|200|2<br>years|6.3%|3.2%|n.r.|a.|
|Haddad et al. (1996)|Morocco|Manufacturing firms|n.r.|1 year|4.6%-<br>7.1%|4.6%-7.1%|n.r.||
|Kilby (1994)|Nigeria|micro and small enterprises|n.r.|n.r.|n.r.|1.3%|n.r.|f.|
|Klapper and Richmond|Cote d'Ivoire|Formal firms|5941|20|n.r.|17%|n.r.|b.|
|(2011)||||years|||||
|Krafft (2016)|Egypt|Household non-farm|828|8|51.4%|6.4%|n.r.||
|||||years|||||
|||Household non-farm|1584|6<br>years|60.9%|10.2%|n.r.||
|McCaig and Pavcnik|Vietnam|Household enterprises|n.r.|2|30-35%|15-17%|n.r.||
|(2016)||||years|||||
|Mead and Liedholm<br>(1998)|Botswana|micro and small enterprises|n.r.|n.r.|n.r.|6.0%|n.r.||
||Kenya|micro and small enterprises|n.r.|n.r.|n.r.|15.9%|n.r.||
||Malawi|micro and small enterprises|n.r.|n.r.|n.r.|15.0%|n.r.||
||Swaziland|micro and small enterprises|n.r.|n.r.|n.r.|10.5%|n.r.||
||Zimbabwe|micro and small enterprises|n.r.|n.r.|n.r.|7.0%|n.r.||

68
respectively. Of the 1,477 individuals who continued past primary school, 233 (16 percent) entered the VTE stream, 129 immudiately after primary school (into a secondary technical school or First-Cycle ESEP) and 104 after secondary school (into an IETS or Second-Cycle ESEP). Of those whose highest schooling level was secondary, 12 percent did VTE; of those who went on to tertiary education, 25 percent took VTE.

Table 4 HIQ EDUATINCR IE\ ATIhE BY IDCATICN _AID_ SECIR

||Ncme|Primaty|SySe<br>tecldcal|condary<br>general|Post-seec<br>aixmv.|Universit|y Total|
|---|---|---|---|---|---|---|---|
|MetropolitanIM||||||||
|VWgeaeployem|8<br>(1.1)|L39<br> (18.4)|38<br>(5.0)|392<br>(51.9)|36<br>(4.8)|143<br>(18.9)|**756**<br>(100.0)|
|Self -eqWlyed|5<br>(1.2)|138<br> (k2.3)|26<br>(6.0)|163<br>(38.2)|22<br>(5.2)|73<br>(17.1)|427<br>(100.0)|
|Al1lmorkwors|13<br>(1.1)|277<br> (23.4)|64<br>(5.4)|555<br>(46.9)|58<br>(4.9)|216<br>(18.3)|1,183<br>(100.0)|
|Other urban areas||||||||
|Wage epwlyeee|7<br>(1.3)|206<br> (39.1)|38<br>(7.2)|209<br>(39.7)|26<br>(4.9)|41<br>(7.8)|527<br>(100.0)|
|Self-oplyed|13<br>(2.6)|217<br> (43.3)|27<br>(5.4)|171<br>(34.2)|20<br>(4.0)|52<br>(10.4)|500<br>(100.0)|
|AllGAwoPsers|21<br>(2.0)|423<br>(41.2)|65<br>(6.3)|380<br>(37.0)|46<br>(4.5)|93<br>(9.1)|1,027<br>(100.0)|
|Allurban areas of Peru||||||||
|Wageemployees|15<br>(1.2)|345<br>(26.9)|76<br>(5.9)|601<br>(46.8)|62<br>(4.8)|184<br>(14.3)|1,283<br>(100.0)|
|Self-employed|18<br>(2.0)|355<br>(38.3)|53<br>(5.7)|334<br>(36.0)|42<br>(406)|125<br>(13.5)|927<br>(100.0)|
|Allurban wrkers|33<br>(1.5)|700<br>(31.7)|129<br>(5.8)|935<br>(42.3)|10&<br>(4.7)|309<br>(14.0)|2,210<br>(100.0)|

Note: Number of orkers (percentage of ,rcup in parentieses).

10
a unique mapping of the source countries where processing inputs are imported from and the destination countries of processed exports. This makes it possible to examine the role of both trade costs related to the import of inputs ( _upstream trade costs_ ) and trade costs related to the export of final goods ( _downstream trade costs_ ) on intra-GPN trade. Such mapping of GPNs cannot be conducted with regular trade data since imports are not necessarily used solely for export purposes, but can also be consumed domestically, as we explain in Section 2.

In Section 3, we identify three stylized facts that suggest that both upstream and downstream trade costs play an important role on China’s processing trade. First, China’s processing exports heavily rely on foreign inputs, with a relatively low share of the value made in China. According to a recent estimate by Koopman, Wang and Wei (2008), only 18% of China’s processing exports value is produced in China, while the remaining 82% consists of the value of imported processing inputs. Second, the average distance traveled by processing imports (import distance) is shorter than the average distance traveled by processing exports (export distance). In 2008, 75% of China’s processing imports originated from within the East Asian region, while 62% of the processing exports were destined to non-Asian OECD countries. Third, this spatial pattern is not consistent across processing locations. In a cross-section of 29 Chinese provinces, import distance is negatively correlated to export distance for most years between 1995 and 2008. In other words, locations in China that import their processing inputs from nearby tend to export their processed goods far away, and vice versa.<sup>3</sup> To explain the role of trade costs on intra-GPN trade, we in Section 4 develop a threecountry general-equilibrium trade model.<sup>4</sup> In the model, the world consists of three countries: _East_ (for advanced East Asian countries), _West_ (for Europe and North America), and _China_ . Multinational firms from the two advanced regions, _East_ and _West,_ sell goods in each other’s markets. Each firm can serve the other market in one of two

> 3 In this paper, “province” encompasses all of China’s first-tier administrative divisions: provinces, municipalities and autonomous regions. We have excluded Tibet and Ningxia from our analysis since they have no processing trade in at least one year of our data sample. Furthermore, we treat Hong Kong SAR, China; Macau SAR, China and Taiwan, China as foreign economies.

> 4 Our model builds on the recent export platform FDI literature by Yeaple (2003), Grossman, Helpman and Szeidl  (2006) and Ekholm, Forslid and Markusen (2007). It is a generalized version of the model developed by Ma, Van Assche and Hong (2009).

3
mechanism, we examine if the effects of robotization on imports are heterogeneous across intermediate and other goods. Although it is empirically challenging to precisely identify imports of intermediate goods (and distinguish them from imports of other goods), we use two product-level classifications that have been widely adopted in the literature to achieve this objective. First, the BACI data set makes it possible to distinguish between intermediate inputs from other goods using the Broad Economic Categories Classification of the UN (see Appendix B.1 for details). Second, we adopt the approach proposed by Schott (2004), who identifies as inputs only those goods for which the product codes explicitly contain the words “parts” or “components”. For both these classifications, the IV estimates in columns (2) and (4) in Table 7 reveal that robotization has a considerably stronger positive impact on imports of intermediate than on other goods.

# **6 Counterfactual simulations**

In this section, we use our theory to perform counterfactual simulations on the general equilibrium effects of reductions in robot prices on trade patterns, wages and welfare in the North and the South. To approximate the setting we explored in the regressions, we calibrate a model with three countries and three sectors. We consider a representative high-income Northern country, a representative country in the South, and a group of other (lower-income) developed countries. The existence of a group of other developed countries allows us to examine the extent to which the quantified model is able to reproduce the relative trade effects we documented in the regressions.<sup>13</sup> Among the three sectors considered, two sectors are tradable and the other sector is nontradable. Production may be subject to robotization only in one of the tradable sectors. This sector consists of automotive, rubber and plastic, electronics, chemicals, metal and machinery industries. The non-robotized tradable sector consists of all other manufacturing industries, including food and textiles, agriculture, mining and utilities. The non-tradable sector consists of construction and services.

> 13If we were to aggregate all groups, the North would account for more than 50% of world GDP, and the bulk of world trade would occur within the North. This setting would underrepresent the importance of North-South trade, and trade as share of GDP would be very small. To avoid this aggregation bias, we construct instead representative countries in the North and the South. Considering a relatively large group of other developed countries is also important to allow for the possibility that competitiveness gains associated with robot adoption in the North translate into higher demand for its final-goods exports.

20
Sri Lanka) and the optimal mix of electricity generation capacity and electricity output from each type of capacity in each year for the 2015-2040 period is produced for each country (‘Baseline’ scenario<sup>12</sup> ). In the next step, the model is run as if the entire South Asia is fully interconnected and there occurs free flow of electricity across the borders as driven by economics of power system expansion (‘Regional Electricity Trade’ or ‘REG TRADE’ scenario). Finally, a carbon tax with a rate of US$10/tCO2 during the 2020-2025 period, US$25/tCO2 during the 2025-2030 period and US$ US$30/tCO2 during the 2030-2040 period, is introduced on top of the full transmission interconnections across the borders in South Asia (‘Regional Electricity Trade and Carbon Tax’ or ‘REG TRADE & CT’ scenario).

The detailed results of the REG TRADE scenario are available in Timilsina and Toman (2016) and the detailed results of the REG TRADE & CT scenario are available in Timilsina and Toman (2018). We focus here on highlighting how hydropower development and trade would occur under those cases. The hydropower specific results presented here are additional to those available in Timilsina and Toman (2016, 2018). We also want to emphasize that while the findings reported here are for regional power trade across South Asia, Timilsina and Toman (2016, 2018) also investigated sub-regional power trade, in particular for the eastern sub-region (Bangladesh, Bhutan, India, and Nepal, abbreviated hereafter as BBIN). The findings are very similar, as discussed further below. This is reassuring since power trade among BBIN is more plausible in practice over the near to medium term than trade across the whole region.

> 12 The baseline scenario includes existing and agreed but not yet started bilateral electricity trade specially between India and its northern and eastern neighboring countries (Bangladesh, Bhutan and Nepal). It also includes all power plants under construction or committed for construction through securing the necessary financing.

26
# Research Copponents<sup>of World Bank Education Projects,</sup> since 1982.

|Area ||Country<sup>and Loan/Credit</sup><br>A<br>Num_ber<br>I|pproved<br>I|Research Components<br> <br>I|Current Status<sup>of Studies, including</sup><br>Completed<br>Documents/Data|
|---|---|---|---|---|
|||<br>b<br>|of printing<br>and paper affect<br>longetivity<br>of<br> <br>ook use (3.09,<sup>13)</sup><br> <br>|program." (1986)<sup>(doc. U 339.117)</sup><br>"Feasibility<br>study on the<sup>future organizational</sup><br>structure of<sup>the ITP within the "OEC." (1984)</sup><br>(doe. # 330.296)<br> <br>lid|
|ASIA<br>ASIA<br>ASIA|Indonesia LN<sup>2290-IND</sup><br>Indonesia LN<sup>2341-IND</sup><br>Indonesia LN 2472-IND|1983<br> <br> <br> <br> <br> <br> <br> <br>1983<br>1985|Polytechnic II.<sup>(i) Extend the existing study</sup><br>of financiat<sup>and administrative</sup><br>schemes to<br>retain university<sup>teaching staff, to cover</sup><br>polytechnic<sup>teaching staff (para. 2.13 p.15);</sup><br>(ii) conduct studies<sup>to determine management</sup><br>skills requirements<br>and establish<sup>information</sup><br>system within<sup>polytechnic</sup><br>system (2.21 20);<br>(iii) feasibility<br>studies and identification<br>for other projects;<br>(iv) study shortage<sup>of technical teachers</sup><br>Third Agricultural<sup>Training. Management</sup><br>strengthening<br>through:<br>(i) evaluation<sup>of training programs and tracer</sup><br>study of graduates;<br>(ii) surveys<sup>of qualifications</sup><br>and technical<br>skills of agricultural<br>manpower;<br>(iii) development<sup>of curricula for agriculturat</sup><br>training programs;<br>(iv) development<sup>of training programs and needs</sup><br>(para.28 p.9)<sup>[costs: Annex 8 p.31</sup><br>Secondary Education<sup>and management Training.</sup><br>Studies include:<sup>(i) comprehensive</sup><br>training<br>needs assessment;<br>(ii) management<sup>study of NEC;</sup>|No info-mstion<br>suppe.<br>No informtion<sup>supplied.</sup><br> <br>(i) P.Hasfarm.<sup>"Training needs assessment</sup><br>Study"<br>Oregon State<sup>University (doc. I 338.433)</sup><br>(iv) Instructor<br>training and<sup>extension studies</sup><br>for PKG English<sup>language instructors</sup><br>(doc. I 434.202)|

41
The analysis covers both utilization of services and the distribution of total medical expenditures in the state budget. A central problem in estimating health expenditures is its contingency on the utilization of the health services, which, as a result, affects the distribution of the health expenditures. To address this problem, this paper adopts the multi-part model developed by Manning et al. (Manning, Newhouse et al. 1987) and Duan and Chau (Duan and Chau 1987) and utilized as part of the Rand Health Insurance Experiment (Newhouse and the Insurance Experiment Group 1996) and other papers (Ruiz, Amaya et al. 2007). The multi-part model separates the process into two stages, with the first being the decision to use medical services and the second being the level of expenditures for people who have used the services.

This paper follows the same strategy and uses the three part model to estimate the probability of utilizing services, the number of services used and the incurred medical expenditures. The three part model consists of a LOGIT model, an OLS and a LOG-Linear model. The formal utilization model specification is as follows: The LOGIT model estimates the probability of an individual seeking surgeries/in-patient services, especially to analyze whether the poorest and the most vulnerable individuals have utilized the benefits.

Prob (USE=1) = α1+ β1X+ ε1 , where USE is a binary variable with having received at least one surgery/in-patient care equal to 1; β1 is a vector of coefficients and X represents a set of independent variables.

Part two is a regression model analyzing the difference in number of utilizations by welfare quintiles among the eligible individuals who have used the services at least once.

N(service | USE=1) = α2+ β2X+ ε2 ,

Part three is the log-linear model that estimates the total expenditures for the surgeries and inpatient services.

LOG(EXP| USE=1) = α3+ β3X+ ε3

The vectors of the coefficient estimates for the respective models are represented by β1, β2, β3. The respective error terms are symbolized by ε1, ε2, and ε3. It is assumed that E (ε) = 0.

The data has been restricted to individuals between 18 and 80 years old. We restrict the sample to 18–80 years of age in order to control for education and employment status, information which is often missing for individuals below 18 years of old. Analysis for individuals between 3 and 17 years old reveals similar results, which are available upon request. In addition to age restriction, records with length of stay greater than 60 days or total expenditures greater than 10,000 GEL have been removed. In the end, the data contains 738,342 individuals, of whom 16,434 (2.23%) have used the services.

14