rafmacalaba/datause-encoder-data huggingface dataset:
- 17 -

Average speed is defined by the distance divided by the number of days required for that shipment ( _SPEED_ ). It is further divided by 24 hours.<sup>7</sup> In our sample data, firms are highly heterogeneous.<sup>8</sup> Firms vary considerably in terms of age, market orientation and ownership structure. Surveyed firms were established on average 14 years ago ( _AGE_ ). The survey also asked firms’ targeted markets: Global, national or local. The last two market orientations are represented by two dummy variables: _NATN_ and _LOCL_ , while the global orientation is used as a baseline. The average share of foreign ownership is 12 percent ( _FORN_ ): Some firms are domestic, and others are fully owned by foreign investors (i.e., the share is 100 percent). More formally, rail users tend to be more foreign owned: Based on the firm-level data, the average foreign share is 20.2 percent among rail users (c.f., 6.1 percent among road users) ( **Table 7** ). This is consistent with the fact that rail users are more focused on the global market: The share of firms responding that their main markets are local (within their localities) is 85 percent among road users, while 32 percent of the rail users indicated their local orientation. Rail users are more focused on global and/or national markets.<sup>9</sup> In our sample, rail users are also found relatively larger and more transport-intensive, meaning the share of transport spending in the total operating cost is high.

> 7 The speed variable defined in this way is obviously underestimated because the normal operating time of rail or truck transportation is less than 24 hours per day.

8 From an empirical point of view, the current sample frame may not be ideal because it is significantly unbalanced. It is not easy to identify clear rail transport users. Still, there is economic potential to (re)develop rail transportation in large countries, such as Tanzania. Thus, the current study was designed as a potential baseline for further surveys. As the government is investing in rail (and lake) transport infrastructure, the follow-up surveys are expected to show more visible impacts of improved rail transport.

9 While local market orientation is referred to mean that firms’ main product lines are targeted at their local areas, national market orientation indicates that firms are active in several locations in the country. Global market oriented firms involve significant amounts of international transactions.
Lanka (and in this study) in that they do not benefit from capital injections. However, female owners of larger businesses, who report full decision-making power, are able to generate profits in response to treatment. In sum, the ability of women to capitalize on business training or increased access to capital seems to depend not only on the social context, more broadly but also on their level of agency.

We also find positive returns to offering larger loans for the lender insofar as the offer of larger loans led to increased lending without a rise in default. The benefits from relaxing borrower constraints were more modest for clients, however. Perhaps because in the context we study, the prevailing loan limits were adequate for most clients. In contrast, while clients do benefit from the offer of business training, the lender realizes negative returns. This may explain why only a third of the reporting institutions in the MIX Market data claim to offer enterprise skill development training.

Despite these encouraging results, we note that ninety percent of businesses in our sample have no hired employees and most business owners have low levels of literacy. They are therefore “subsistence” entrepreneurs, that is, individuals that engage in selfemployed activities to survive and perhaps provide employment to family members (Schoar, 2010; Woodruff, 2006). However, even if the impact of these businesses on the aggregate economy is small, they do account for a large share of the population and as a result, business training could serve both as an effective poverty alleviation strategy, as well as a screening device for the provision of microcredit.

30
to differentiated access to life opportunities which follows an ordinal logic, with non-manual workers at the top of the stratification and agricultural workers at the base.<sup>46</sup>

**Table 5. Distribution, total income and average schooling and ISEI, by occupational stratum. Individuals between 30-64 years of age, ENIGH 2016.**

|Stratum|Total (%)|Males (%)|Females (%)|Total<br>income<br>(monthly)|Schooling<br>(average)|ISEI<br>(average)|
|---|---|---|---|---|---|---|
|NM|23.57|51.05|48.95|6,146.03|14.4|61.76|
|Commerce|11.56|45.05|54.95|4,194.14|9.93|37.16|
|HM|22.63|72.90|27.10|3,478.67|9.15|29.75|
|LMM|10.31|82.29|17.71|3,038.06|7.28|21.17|
|LMS|19.40|32.00|68.00|2,332.47|8.03|25.8|
|Agriculture|12.53|72.94|27.06|1,818.51|5.38|13.8|

Source: Own elaboration from ENIGH 2016.

In general, the data show a descending pattern of the total income, schooling and ISEI, with one exception. The LMM stratum clearly has higher income than the LMS, but their average schooling and ISEI are lower. This may be due to the fact that, as shown in table 5, these strata show differentiated composition of sexes, with the LMM stratum predominantly made up of males and the LMS of females. Despite having more average schooling, the more feminized stratum registers lower income, which is an example of gender inequalities in the labor market. Furthermore, in relation to the ISEI, the difference in order may be due to some occupations in Mexico not providing an income at a comparable level to that in other countries captured in the index (Solís, 2010).

While the order of strata may be considered ordinal, as observed, the differences in income are not equidistant. That is, the movement between the different strata may mean changes of different magnitude in the average access to income and other life opportunities. Furthermore, it must be considered that a movement to an adjacent stratum (or nearby) represents a change of lesser magnitude than one that is of greater distance.

# D.2 _Methods for the analysis of absolute mobility_

Absolute mobility analysis was based on calculations derived from tables of intergenerational occupational mobility, which are contingency tables in which each row corresponds to a different occupational origin (the stratum of the providers) and each column to an occupational destination

> 46 The order remains when using labor income, except for the stratum of commerce, which has an average labor income that would place it in the same level as the HM stratum, due to fact that its total income has a higher composition of non-labor income than the other strata. We consider it is correct to use the total income because belonging to an occupational stratum is related not only to labor income, but also to access to other sources of income and life opportunities in general.

26
- 3 -

of various training modes is constrained. However, the large sample of projects studied and the use of multiple criteria of effectiveness have made it possible to gain some insight into the relative effectiveness of different institucional training modes in varying economic contexts.

A clear and signifi^ant shift over the past twenty-three years of Bank lending for -ocatio.ially-specific education and training (VET) away from vocational secondary schools towards various forms of non-formal training is found. There is some evidence to suggest, however, that all modes of training have been difficult to establish in low-income countries and, conversely, that all modes can be established in middle income countries. In these latter circumstances, successful investment strategies for the development of training systems share key poli:y and operational characteristics. Finally, the "new educational vision," at least as represented in investments in diversified secondary curricula, has had a decidedly mixed history.

# DEFINITIONS

The field of vocational education and training is beset by definitional problems. In his review of the literature on the cost-effectiveness of training, Dougherty (1988, forthcoming) found that " ... much of controversy in the literature appears to be attributable to antagonists unwittingly focussing on two different points on what is in effect a continuous spectrum and then arguing at cross purposes." To avoid, or at least minimize that problem in the present paper, it is necessary to discuss briefly the definitions that have been used in the analysis of World Bank experience. These
# **I. Introduction**

Recent decades have seen an increased emphasis on evidence-based decision making in development policy. As part of the trend, the past 20 years have witnessed a sharp rise in the implementation of rigorous impact evaluations of development programs.<sup>1</sup> Impact evaluations are a key tool for providing policy makers with evidence on what does and does not work to reduce poverty, expand investments in human capital, improve opportunities for women, and achieve other social objectives.

There is also an increasing awareness that analyzing impact alone is not enough to determine whether a particular program is worth investing in. The cost-effectiveness of the program or, in other words, how much it will cost to achieve a given impact, is also crucial. How this compares across programs should clearly affect evidence-based policy making. Consider, for example, a low-cost remedial tutoring program and a high-cost extension of the school day that both deliver the same improvement in test scores. Impact (or “effectiveness”) alone would fail as a guide to policy, whereas cost-effectiveness would point to the lower cost program as the better investment. Cost-effectiveness analysis is proposed as an aid to compare the impacts and costs of various programs implemented in different countries and years when the programs have a common objective, making them comparable.

Recent years have seen significant advances in tools to conduct cost-effectiveness analysis in development contexts, often applied to interventions in education. There is a growing literature documenting methods of cost-effectiveness analysis (see Levin & McEwan 2001, Levin et al. 2012, and Glennerster and Takavarasha 2013, for examples). At the same time, recent reviews have discussed the issues surrounding the assumptions on which such analyses rely, and have made recommendations on which of these assumptions may be reasonable for policy makers to employ, bringing the development community closer to consensus on a more standardized methodology for cost-effectiveness analyses (Dhaliwal et al. 2013; McEwan 2012). There have also been advances in implementing a standardized approach to cost-effectiveness analysis. Evans and Ghosh (2008) draw on 40 randomized and non-randomized evaluations of education programs to compare their cost-effectiveness in achieving increases in enrollment, attendance, and test scores. They compare the average program cost (in 1997 USD) for an additional year of school participation, and for a 0.1 standard deviation improvement in test scores, a common measure intended to allow the comparison of gains in test scores in different contexts irrespective of whether the tests are the same. Dhaliwal et al. (2013) use randomized evaluations of 11 education programs from six countries to compare the cost-effectiveness for student attendance and enrollment, in

> 1 Randomized experiments are one form of rigorous impact evaluation: A recent review found that the vast majority of available randomized experiments in primary schools have been completed since 2000 (McEwan 2014).

2
10 However, source countries’ FDI is not originating from a single resident location in practice. To reflect this fact in our model, we incorporate costs to treaty-shopping. Specifically, we assume that the MNE incurs costs C� if the share of funds provided from location i deviates from this location’s actual funding potential ~~α~~ � ~~.~~ In the empirical application, we use GDP weights to proxy for funding potential. Following the literature on international profit shifting (see e.g. Huizinga and Laeven,2008), we assume treaty shopping costs take the simple quadratic functional form: where the parameter γ determines the overall costs of treaty shopping.<sup>23</sup> A deviation between real funding potential and reported financing is costly as it requires the establishment of new organizational structures, which may need to have sufficient substance for an entity to qualify for treaty benefits.<sup>24</sup> As γ→0, treaty shopping costs tend to infinity, in which case the actual funding share in each location is no longer a choice variable.

Equation (2) suggests that _marginal_ tax avoidance costs are linear in the avoided tax base. In the context of our model, this implies that variation in a country’s bilateral tax treatment of income flows provides an identification device for treaty-shopping. In contrast, van’t Ried and Lejour (2018) employ a network analysis and assume that _total_ tax avoidance costs are linear in the avoided tax base. As a result, the minimal bilateral tax burden determines income flows in their framework, rather than the entire distribution of a country’s bilateral tax rates. Note that all investments should be rerouted through a single conduit country if total treaty-shopping costs are linear in the avoided tax base. This assumption is easier to reconcile with empirical data when using bilateral FDI data, such as van’t Ried and Lejour (2018), than when using aggregate FDI data as we do.<sup>25</sup> The MNE seeks to maximize its global return after-tax and after treaty-shopping by choosing the investment magnitude and the place of financing subject to the constraint that the investment is fully financed ∑α� � �1. Formally, the MNE’s maximization problem reads: 23 For simplicity, we assume in the theoretical model that these costs are constant across all resident locations. In the empirical section, however, we allow them to vary between investment hubs and other locations.

24 Arguably costs of treaty shopping have escalated due to the recent emphasis in the OECD/G20 BEPS initiative on introducing anti-abuse provisions that require sufficient substance for an entity to qualify for treaty benefits.

> 25 In other words, it is easier to argue that all investments from country P to country S are rerouted through conduit country C, than to argue that all investments in country S are structured through country C.
|Railway power / 100 million kWh|3.77|
|---|---|
|Waterway diesel/Mt|11.29|
|Waterway fuel oil/Mt|21.42|
|Aviation kerosene / Mt|25.6|

Source: Wang (2011).

The building sector is divided into urban residential, rural residential, general public construction and large-scale public construction according to the type of building. The enduse energy demands are space heating, cooling, lighting, cooking, hot water and other equipment. The base year data are provided in Table B5.

**Table B5** Baseyear data for the building sector (unit: Mtce)

|**Base year calibration**<br>**(Mtce)**|**general**<br>**public**<br>**construction **|**large-scale**<br>**public**<br>**construction **|**urban**<br>**residential**|**rural**<br>**residential**|
|---|---|---|---|---|
|**Heating**|5141|855|10971|5412|
|**Refrigeration**|1490|480|516|130|
|**Lighting**|1055|313|544|523|
|**Others**|1073|149|787|361|
|**Cooking and hot**<br>**water**|1363|250|4267|2296|
|**Total**|10121|2048|17086|8721|

The main sources of energy demand data are energy balance tables available from China’s energy statistical yearbook. For energy consumption in the industrial sub-sectors and technologies we used several sources such as _China Statistical Yearbook 2006-2011_<sup>[24]-[29]</sup> , _Industrial Statistical Yearbook_ 2010-2013<sup>[30]-[33]</sup> , _China Steel Statistics 2011_<sup>[34]</sup> , _China Chemical Industry Yearbook_<sup>[35][36]</sup> , _China Nonferrous Metals Industry Yearbook_<sup>[37][38]</sup> , _China Energy Statistical Yearbook 2006-2013_<sup>[39]-[42]</sup> . We also use technical parameter documents on production lines of major industrial sectors, as well as calculation and collation from related literature. The data of the transport sector are from: _Research into China's Medium and Long-Term Development Strategy on Traffic and Transportation_<sup>[43]</sup> , _Automotive Energy Outlook 2012_<sup>[44]</sup> , _China Transport Yearbook_<sup>[45]-[47]</sup> , _China Bulletin on Motor Vehicles Pollution Prevention_ , _China Energy Statistical Yearbook 2010-2013_ , as well as data research and calculation based on major literature. For the building sector, the data sources include _The Annual Development and Research Report on Building Energy Efficiency in_ 44
Despite this liberalization and subsequent expansion of the financial sector, significant barriers remained that hindered the extension of credit and collection of deposits. In a recent World Bank report, Kumar (2008) collected survey responses from central bank regulators and commercial banks in 54 countries around the world. The responses document the various barriers to financial access by poor households and SMEs. While India has some of the lowest fees of the 54 countries surveyed, access is still hindered there by some of the longest wait times and highest document requirements for deposit accounts.

Based on Figure 1, it seems that whatever the effects of the liberalization, they fell proportionally equally on all districts and did not affect the relative distribution of financial depth. A Spearman Rank test, used to estimate the correlation in a district’s rank in the financial depth distribution in 1991 with its rank in 2001, measures the correlation at over 0.8 indicating very little mixing over the 1990s.

This implies that whatever forces shaped the initial distribution of banking sector penetration did not go away after the liberalization.

# **<mark>2.2    Education and Literacy in India</mark>**

Similar to physical capital, human capital is non-rival and excludable. In addition, however, it is also nonappropriable, which means that it cannot be used as collateral and its accumulation may be difficult to fund by borrowing, even in relatively advanced credit markets. There are also well documented spillovers from human capital (as there are in many new growth theory models) that push the social marginal product above the personal marginal product. For these reasons, most governments around the world, including India’s, have chosen to subsidize education provision as a public good.

The National Policy on Education (NPE) 1986 and revised Plan of Action (PoA) 1992 envisioned that free and compulsory education should be provided for all children up to 14 years of age before the beginning of 21st 10
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# Appendix Table 3

# Share of social programmes at the local level

# MOSCOW MS.OBLAST OTHER TOTAL

|Enterpr.which have|||||
|---|---|---|---|---|
|HOUSING: None|14|3|0|17|
|Small|6|7|3|16|
|Compartoloc.|2|3|0|5|
|High|0|3|0|3|
|KINDERGARNone|14|7|1|22|
|Small|3|3|1|7|
|Compartoloc.|4|3|1|8|
|High|1|3|0|4|
|HEALTH<br>None|13|8|3|24|
|Small|8|5|0|13|
|Compartoloc.|1|3|0|4|
|High|0|0|0|0|
# VL ANALYSIS OF ERRORS

63. It should be stressed that the estimation of GDP for any country in an intemational comparative framework involves two distinct stages. In the first stage, GDP data in national acurencies are compiled in an intemationaily standardied framework (SNA). In counties where the compilers of national accounts have adopted the SNA framework, GDP data are comparable in terms of the economic activities covered by the data, but not conparable in terms of the unit (national aurencies) in which these data are epressed. In counties where the compilers of national accounts have been followmg other frameworks (MPS), GDP data are incomparable both in terms of the coverage of econonic activities and in terms of the unts in which these data are valued. In the second stage, GDP data **in** national crency are converted into a common curency, e.g. US dolars or intenmational dollars, depended on the converter used. Thus in order to obtain meamnil inteational comparison of real GDP, both stages are necessary for counties which do not work witin the SNA framework. For counties which have adopted the SNA fimework, studies belongmg to the second stage are stil necessary. Obviously, the long-term efforts in ICP frmework have been focused on the second stage rather than the first stage of makng GDP data intemationally comparable.

64. The history of itrnational compazisons sows th the early compeison were mnade between the industial countries (Gilbert and Kravis, 1954; Gibrt and Assodates, 1958). When the int onal comparisons were made under ICP, which inchlded developing economies, mny issues were raised with regad to concepts, methodology and econonuc justifications involved in these comparisons. These were discussed densvely in the magnum opus of Krais et aL (1982, see also Kravis et al., 1975, 1978). It is easy to see that cross-system comparisons between different ldnds of economies are more difficul **t** han compaisons betw mar economies (Maer, 1985). For this 28
|||**Pool with**<br>**subsequent**||
|---|---|---|---|
||**Pool**|**formality**|**2012-2018**|
|1990-1999|1.211|1.208|1.641|
||(0.273)|(0.272)|(0.802)|
|2000-2009|1.130|1.126|1.177|
||(0.309)|(0.314)|(0.568)|
|2010-2018|2.327*|2.382*|2.428|
||(0.991)|(1.050)|(1.459)|
|**People outside the HH employed (no omit.)**||||
|Yes|1.799**|1.738*|0.947|
||(0.404)|(0.394)|(0.367)|
|**Location (shop omit.)**||||
|Own home|1.287|1.189|1.786|
||(0.420)|(0.398)|(0.901)|
|Office/flat/building/rooms|1.106|1.332|3.412|
||(0.524)|(0.632)|(3.262)|
|Workshop/factory|1.340|1.388|1.351|
||(0.480)|(0.516)|(0.768)|
|Mobile worker|1.399|1.608|0.871|
||(0.504)|(0.614)|(0.586)|
|Kiosk/hut|0.195|0.219|0.389|
||(0.181)|(0.209)|(0.757)|
|Transport based|1.271|1.683|0.152*|
||(0.630)|(0.907)|(0.129)|
|Street/field/farm|1.069|1.220|1.202|
||(0.381)|(0.449)|(0.702)|
|**Sex (male omit.)**||||
|Female|0.693|0.625|0.685|

70