rafmacalaba/datause-encoder-data huggingface dataset:
|Table S.11: Imp|acts on c|hildren’s edu|cational|achievement|- Banglade|sh genera|l studies: h|eterogene|ity (OLS)|
|---|---|---|---|---|---|---|---|---|---|
|Dependent variable:|||Ban|gladesh gener|al studies:|GPA z-sco|res|||
|_X_:|Age|Education|Male|Household<br>size|No. of<br>male<br>members|Head<br>age|Head<br>education|Head<br>male|Land<br>size|
||(1a)|(1b)|(1c)|(1d)|(1e)|(1f)|(1g)|(1h)|(1i)|
|**December in 2013**||||||||||
|All products|-0.337|0.082|-0.021|0.236|0.131|0.272|0.085|0.089|0.055|
||(0.519)|(0.220)|(0.072)|(0.258)|(0.153)|(0.405)|(0.078)|(0.195)|(0.072)|
|One product|0.531|0.438|0.048|0.259|-0.017|-0.145|0.117|-0.038|0.118|
||(0.686)|(0.338)|(0.099)|(0.330)|(0.163)|(0.341)|(0.084)|(0.229)|(0.099)|
|All products _× X_|0.033|-0.004|0.202|-0.034|-0.027|-0.005|-0.015|-0.025|0.001|
||(0.041)|(0.042)|(0.134)|(0.050)|(0.059)|(0.010)|(0.030)|(0.209)|(0.002)|
|One product _× X_|-0.033|-0.069|0.167|-0.028|0.060|0.006|0.005|0.173|0.000|
||(0.055)|(0.069)|(0.146)|(0.062)|(0.061)|(0.008)|(0.038)|(0.237)|(0.003)|
|R-squared<br>No. of obs.|0.271<br>850|0.271<br>850|0.272<br>850|0.270<br>850|0.271<br>850|0.271<br>850|0.270<br>850|0.270<br>850|0.270<br>850|
||(2a)|(2b)|(2c)|(2d)|(2e)|(2f)|(2g)|(2h)|(2i)|
|**December in 2014**||||||||||
|All products|-0.864|-0.324|-0.020|-0.287|0.033|0.125|-0.155|-0.355|-0.144|
||(0.647)|(0.306)|(0.103)|(0.309)|(0.190)|(0.338)|(0.104)|(0.283)|(0.096)|
|One product|0.179|0.365|-0.020|0.457|0.183|0.480|-0.008|0.046|-0.017|
||(0.730)|(0.329)|(0.115)|(0.330)|(0.176)|(0.480)|(0.099)|(0.381)|(0.100)|
|All products _× X_|0.060|0.042|-0.251|0.032|-0.065|-0.006|0.023|0.250|0.002|
||(0.051)|(0.060)|(0.162)|(0.053)|(0.065)|(0.008)|(0.030)|(0.270)|(0.003)|
|One product _× X_|-0.016|-0.084|0.001|-0.100|-0.087|-0.012|-0.013|-0.073|-0.000|
||(0.057)|(0.067)|(0.206)|(0.065)|(0.076)|(0.011)|(0.029)|(0.395)|(0.003)|
|R-squared|0.129|0.131|0.130|0.130|0.129|0.128|0.128|0.128|0.128|
|No. of obs.|846|846|846|846|846|846|846|846|846|
|Baseline control|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|School FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Village FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|

Notes: (1) Figures ( ) are standard errors. *** denotes significance at 1%, ** at 5%, and * at 10%. (2) Standard errors are robust to heteroskedasticity and clustered residuals within each school-grade. (3) The baseline controls include age (years); education (years); gender (dummy); household size; no. of males; head age (years); head education (years); head gender (dummy); and land size (natural number).

56
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# **Restructuring of Large Firms in Slovakia**

# **I. Introduction**

The restructuring of large enterprises has received much attention in the transition of centrallyplanned economies to market economies. The need to transform these enterprises into viable firms is widely acknowledged. The extent of such restructuring and the determinants that underlie a successful transformation are less studied. Various schemes for dealing with large enterprises have been tried. The effect of such programs is hard to measure since the restructuring of enterprises (or the lack thereof) has taken place in the context of significant changes in the overall economic environment. Notwithstanding the difficulty in such measurement, a proper evaluation is crucial for designing further reform policies.

This paper extends the literature on the microeconomics of transition by re-examining the stylized facts about firm restructuring in the light of new empirical evidence. The study is based on twenty-one case studies of Slovak firms and uses detailed financial information for the 1991-96 period and interviews with top management. A large part of our sample represents firms that were initially classified as "non-viable loss-makers." We show that the majority of large Slovak firms have successfully restructured in the absence of foreign investors and government-led restructuring programs. The study also throws some new queries on the effectiveness of different privatization methods in enhancing corporate governance and improving access to skills and capital.

We find that privatization to insiders through management-employee buy-outs did not hamper firm restructuring as the new owners (old managers) invested heavily in new technology, laid off substantial part of their workforce, sought foreign partnerships, and were prepared to sell controlling stakes to outsiders in return for fresh financial resources. The evidence also suggests that the mass privatization program did not result in weak corporate governance since it was followed by a rapid consolidation of ownership. Our findings support the view that the main objective of privatization programs should be the speedy transformation of ownership, not the selection of perfect owners.

2
**Table 4. Vulnerability Lines using Pseudo-Lopez Calva Method (2008-2016)**

|**Year**|**Vulnerability line ($**<br>**real COP, Bogota**<br>**2008)**<sup>**a**</sup><br>**Vulnerability line**<br>**($PPP 2011)**<sup>**b**</sup>|**Increase with**<br>**comparison to**<br>**poverty line (%)**<sup>**c**</sup>|
|---|---|---|
||**_Model 1_**<br>||
|**2008-2010**|519671<br>15.48|166|
|**2010-2012**|513082<br>15.28|162|
|**2012-2014**|524594<br>15.63|168|
|**2014-2016**|597737<br>17.81|205|
||**_Model 2_**||
|**2008-2010**|401966<br>11.97|105|
|**2010-2012**|412978<br>12.30|111|
|**2012-2014**|386059<br>11.50|97|
|**2014-2016**|457724<br>13.64|134|
||**_Model 3_**||
|**2008-2010**|384313<br>11.45|96|
|**2010-2012**|393411<br>11.72|101|
|**2012-2014**|404297<br>12.04|107|
|**2014-2016**|446504<br>13.30|128|
||**_Model 4_**||
|**2008-2010**|385275<br>11.48|97|
|**2010-2012**|398487<br>11.87|104|
|**2012-2014**|409832<br>12.21|109|
|**2014-2016**<br>**a**The vulnera|442236<br>13.17<br>bility line corresponds to the monetary-value per pe|126<br>rson, below such value|

> **a** The vulnerability line corresponds to the monetary-value per person, below such value and above the poverty line, for which the probability of falling into poverty in the second period is 10%. c Since vulnerability line is above the poverty line, this column reflects the relative increases of the vulnerability line from the poverty line (of $195703 at real COP, Bogota 2008). **Source:** Own estimations based on GEIH from 2008 to 2016.

23
iv

# **Timeliness of Transport**

8. Cultivation takes place over space and the optimal rule for evacuating the crop, other things being equal, is to collect first from the nearest location and last from the furthest. This minimizes the cost, whether that is reckoned in interest or in crop losses: the optimal procedures minimize (other things being equal) the aggregate waste through deterioration. In the Cote d'Ivoire, however, the delay in collecting the ready crop is negatively correlated with the distance of zones from the port. Failing other good reasons, the cause may be institutional inefficiency and distorted incentives for the transport operators. If good reasons (such as differential timing of rains) do not exist, the procedure is irrational. It may induce "backhauling": the nearer farms carrying their crop further inland to depots served earlier than those closer to port. It may also induce over-investment in transport equipment, by the nearer farms, which may thus minimize their loss from being left until last in the timing of evacuation; total transport cost is then raised, through under-utilization of the stock of vehicles or inappropriate sizes, and aggregate producer surplus is encroached on. Such investments would, of course, mitigate the loss through irrational evacuation procedures.

# Operational Implications

9. For operational purposes, the significance of the study is to clarify the relation that exists between different marketing board pricing systems and the method of implementing the schemes on the one hand, and, on the other, the implicit incentives for transport use, producer surplus and returns to transport investments. These relations, illustrated numerically from Cote d'Ivoire data, dictate questions tiat ought to be asked in evaluating agricultural transport projects and, equally, in reviews of agricultural pricing or agricultural tax schemes. Specifically, a pure tax on agricultural output and thus also full-cost pricing of agricultural transport are suboptimal; so is panterritorial pricing and the implied 100 percent subsidy on transport of crops. Further, demand estimates for purposes of transport investment appraisals should not be made independently of an investigation of the agricultural pricing system, particularly when the system is itself in process of change. Lastiy, the location ot marketing board depots and the logistics of crop evacuation also contain incentives for different ways of using transport and may therefore generate a substantial waste of transport resources.
<!-- Start of picture text --> a ee :<br>.<br>te<br>A, ys<br>Abeta..=" CHAD<br>— =I %<br>an is 1” as<br>NIGERIA ¥¢<br>a‘<br>a<br>ele 2<br>a»<br>‘* ?<br>T* ¥ = 5 i Is<br>MY my yi,<br>if | ty A (] . 4<br>ae SSP Aceon f CENTRAL AFRICAN REPUBLIC<br>a= ? a te<br>Fea,6 _ #; ; eea F f ?<br>Sao”. ees OF<br>a = id ral . ol<br>LEO et & — f Est<br><> § ~ 4<br>SY d ene” ~ \ CONGO<br>plains a Man \/ CONGO<br>SAO TOME AMD PRINCIPE EQQATORIAL GUINEA GABON<br>7<br><!-- End of picture text -->

<!-- Start of picture text --> Current Irrigation (% Area)<br><1% @iw-5% @>5u<br>il Dams<br><!-- End of picture text -->
Winters (2001) show that male and female networks for Mexican immigrants function similarly in that they both affect female migration behavior and apparently operate as substitutes. A recent study from Thailand further demonstrates the gender specificity of migration social capital in terms of its impact on male and female migration decisions (Curran, Garip et al. 2005). Notwithstanding the above-mentioned study from Thailand, the preponderance of empirical evidence on cumulative causation is built on Mexican migration case. This geographic focus constrains the development of a more generalized understanding of the linkage between cumulative causation and migration.

A further constraint to forming a deeper understanding of the connection between gender and social networks – and unrelated to the empirical focus on Mexico – is that the validity of empirical studies remains hampered by the fact that migration capital is often already accumulated well in advance of data collection efforts. The complexity arises when migration streams go back in time and migration capital is interwoven with other forms of human and social capital. The interaction between these processes undermines our ability to correctly identify the role of migration networks on migration patterns (Palloni, Massey et al. 2001; Munshi 2003). While innovative empirical strategies have been used to capture variation across regions in their access to migration resources from the distant past – such as McKenzie and Rapoport’s (2007) use of railroad data from Mexico – migration becomes highly endogenous over time. Such endogeneity concerns resulting from reverse causality may be particularly acute when examining the relation between gender, social capital and migration. Ideally, from the standpoint of causality, gender in the process of cumulative causation could be examined from a start-date with no migration and its evolution could be analyzed. Albania, which Russell King knowingly terms a real-world empirical laboratory to study migration and development (2005), offers just such an opportune setting. In Albania, there is both a clear starting point with respect to the lack of migration capital existing prior to the start of migration as well as a rapid accumulation of migration capital following the onset of migration. Thus, the Albanian context offers an ideal setting to test our fifth hypothesis: that migration capital is gendered and that men and women rely more on both family and community networks of their own sex. Given the rapid expansion of migration capital combined with extensive social turmoil, our sixth hypothesis is that the value of migration capital declines over time.

7
-9-

# Voluntary ComDliance

2.16 Taxpayers may also be induced to voluntarily supply information directly to the assessor, particularly where it involves changes in ownership. Because property ownership in Brazil is subject to dispute, purchasers will often register their property with the assessor in an attempt to strengthen their claim.*1 Registration on the property tax rolls does not legally constitute a recognition by government of a taxpayer's claim, but in the absence of contrary evidence, it is often accepted as such by the courts. In order to avoid liability for property they no longer own, sellers of property may also notify the assessor of a change in ownership.

2.17 Experience with voluntary compliance is mixed. In Recife, the assessor reports a high degree of compliance among property owners with particularly dubious claims. In towns where absentee ownership of vacant urban land is widespread, assessors report great difficulty in determining ownership, and little cooperation on the part of property owners.

2.18 Cross-referencing and voluntary compliance do not eliminate the need for site visits and additional investigation. !'roposed subdivisions or new construction--although approved by the public works department--may never take place, and therefore have to be verified. Subdivision plans and building permit applications may not provide sufficient information to permit an in-office valuation. Voluntary compliance is only effective in bringing changes in ownership to the assessor's attention. As a result, cross-referencing--even where it works--serves only a limited function: that of bringing changes in the tax base to the assessor's attention.

# Ongoing Field Surveys

2.19 To supplement these indirect means of discovering changes in the tax base, assessors rely extensively on field work by their own staff. Staff of the assessors office--termed fiscais--regularly patrol designated zones of the _-/ Thls problem has deep historical roots. Present claims to property ownership descend, In princlple, from grants made by the Portuguese klng in the sixteenth century. As these grants were contingent upon the productive use of property, the colonLal authorities rarely objected when new settlers took over parcels of unused land for thelr own use, regardless of whether the land had already been granted to someone else. By the mid-elghteenth century, overlapping claims were widespread. Shortly after independence (1822), laws were enacted to enable squatters to legalize their clalms, but these opportunities were not widely exploLted. New disputes over land ownership have emerged in the wake of Brazil's urbanization. Low-Lncome households, unable to obtain urban land legally, often resort to Illegal occupation on public or private land._ _Brazil's prlvate deeds registrars--the cartorios- -record claims to property. Deeds, of course, are merely evidence that a particular transaction has taken place, and do not constltute proof of legal ownership. Property descriptions contained on deeds are also often unclear, and are not supported by monumentation on the ground, glving rise to disputes over boundaries._
|**Appen**|**dix B. Clas**<br>**U.N.**|**sification of countries by t**<br>**12-24**|**iming of peak**|**in populati**<br>**Avera**<br>**grow**|**on aged**<br>**ge annual**<br>**th**|
|---|---|---|---|---|---|
|**Classific**|**country**||**Year of**|**2005-**|**2025-**|
|**ation**|**code**|**Country**|**peak**|**2015**|**2035**|
|**1. Countrie**|**s with peak bef**|<br>**ore 2000**||||
|1|152|Albania|1989|-0.5%|0.1%|
|1|106|Armenia|1980|-3.0%|0.2%|
|1|183|Barbados|1976|-1.6%|-0.8%|
|1|127|Belarus|1977|-4.3%|-0.6%|
|1|154|Bosnia and Herzegovina|1978|-1.8%|-0.7%|
|1|128|Bulgaria|1970|-3.6%|-1.4%|
|1|71|China|1987|-1.0%|0.3%|
|1|155|Croatia|1950|-1.7%|-0.3%|
|1|186|Cuba|1986|-0.9%|-1.0%|
|1|129|Czech Republic|1967|-2.6%|-0.5%|
|1|140|Estonia|1988|-3.7%|0.2%|
|1|111|Georgia|1977|-2.6%|-1.0%|
|1|190|Guadeloupe|1989|1.1%|-1.6%|
|1|221|Guyana|1981|-1.3%|-3.4%|
|1|130|Hungary|1970|-1.6%|-0.8%|
|1|84|Kazakhstan|1977|-2.5%|-0.2%|
|1|74|Korea, Dem. Rep.|1988|0.5%|-0.2%|
|1|146|Latvia|1979|-4.0%|-0.2%|
|1|147|Lithuania|1983|-2.7%|0.1%|
|1|193|Martinique|1980|-0.6%|-1.5%|
|1|17|Mauritius|1984|0.1%|-0.5%|
|1|131|Poland|1973|-3.3%|-0.3%|
|1|133|Romania|1991|-3.4%|-1.1%|
|1|134|Russian Federation|1975|-4.4%|-0.5%|
|1|163|Serbia and Montenegro|1998|-1.8%|-0.5%|
|1|135|Slovakia|1997|-2.8%|-0.5%|
# _Question 24: Time for getting public telephone line connected._

<!-- Start of picture text --> Question 24 asked about<br>sufficiency of telecommunications It takes less than I month to get a public telephone line connected<br>and accessibility for businesses. 90<br>80<br>24. How long does it take to get a public<br>telephone line connected? 70 -<br>(1) less than 1 month .<br>(2) 1 to3 months C 50<br>(3) 3 to 6months<br>(4) 6months to 1 year 40<br>(5) more than 1 year D 30<br>(6) difficult to say |<br>20<br>More than 80 percent of<br>World LDC DC SSEA MNA CEE LAC SSA CIS<br><!-- End of picture text -->

More than 80 percent of respondents from developed countries answered that it takes less than a month to get a public telephone line connected. Only about 50 percent of business people in Asia have this same fortune. 25 percent of surveyed CEE and CIS entrepreneurs can obtain a telephone line in less than a month.

The situation is the worst in Sub-Saharan Africa, where less than 10 percent respondents can be connected to public telephone network in less than a month.

42
causal impacts of the program on a specific child, because childbearing is endogenous to treatment. However, as the causal effects of cash transfers targeted to females of childbearing age (rather than to pregnant women or mothers) is an important policy question, we attempt to disentangle the selection-driven components of fertility and parentage from the direct treatment effects on the actual sample of children born. The technical details of the assumptions required and the sequence of adjustments – to move from the overall reduced-form difference between children born to mothers in the treatment and control groups towards a more standard causal effect on the children actually born – are outlined in Appendix C.

To investigate how differential exposure to CCTs and UCTs drives treatment effects, we consider the sample of children born during three epochs. The first epoch captures those _directly exposed_ to the program, meaning those born during the program.<sup>26</sup> This cohort is exposed for a maximum of two years, with some combination of in utero and child exposure depending on the exact birth date of the child. The second epoch covers those born within nine months of the end of the program, who were _exposed in utero_ for a maximum of nine months. Finally, the third epoch covers those born more than nine months after the end of the program, who were _not exposed_ to cash transfers either as children or in utero and could only benefit from the program due to improved outcomes of their mothers **.** We concentrate our analysis on height-for-age z- scores (HAZ), which is an objectively measured indicator of stunting that affects almost 50% of children under the age of five in Malawi, and is a strong predictor of productivity as an adult in low income settings (LaFave and Thomas 2016).<sup>27</sup>

> 26 The percentage of baseline schoolgirls who reported having been ever pregnant was less than 2% at baseline. Hence, children directly exposed to the program in this stratum are almost exclusively born during the intervention. However, approximately 45% of baseline dropouts had already started childbearing at baseline. Therefore, our analysis includes children under two at the start of the program, who were at least partially exposed to cash transfers. 27 Of the two anthropometric measures that we collected for children aged 0-59 months – height and weight – stunting (height-for-age z-score<-2) is the key indicator of malnutrition in Malawi: almost half of the children under the age of 5 were categorized as stunted in 2010, while wasting (weight-for-height z-score<-2) rates are low at 4%

29
|Table S.18: Children|’s education|al efciency|- GPA z-|scores: spe|cifcation (2)|(OLS)|
|---|---|---|---|---|---|---|
|Dependent variables:|Bengali|English|Math|General<br>science|Islam<br>studies|Bangladesh<br>general<br>studies|
||(a)|(b)|(c)|(d)|(e)|(f)|
|All products|0.028|0.018|-0.085|-0.058|-0.001|-0.085|
||(0.111)|(0.099)|(0.095)|(0.100)|(0.104)|(0.115)|
|One product|0.181|0.090|0.069|-0.052|0.121|0.025|
||(0.118)|(0.107)|(0.108)|(0.107)|(0.113)|(0.121)|
|Study at school|-0.001|-0.000|-0.002|0.000|-0.000|-0.001|
|(per-day minutes)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|
|Study at home|0.001|0.001|0.000|0.001|-0.000|-0.000|
|(day, per-day minutes)|(0.002)|(0.002)|(0.002)|(0.002)|(0.002)|(0.002)|
|Study at home|-0.002|-0.001|0.000|-0.002|-0.001|-0.002|
|(night, per-day minutes)|(0.002)|(0.002)|(0.002)|(0.002)|(0.002)|(0.002)|
|One if attend|0.213**|0.133|0.158|0.187**|0.214**|0.205*|
|(February)|(0.100)|(0.092)|(0.099)|(0.085)|(0.099)|(0.114)|
|One if attend|-0.254***|-0.211**|-0.149|-0.201**|-0.213***|-0.127|
|(April)|(0.092)|(0.104)|(0.093)|(0.088)|(0.078)|(0.125)|
|One if attend|0.043|0.001|0.047|0.085|-0.003|-0.029|
|(August)|(0.076)|(0.097)|(0.069)|(0.078)|(0.090)|(0.098)|
|R-squared|0.140|0.131|0.178|0.167|0.133|0.141|
|No. of obs.|618|618|618|618|618|618|
|Baseline control|No|No|No|No|No|No|
|School FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Village FE|Yes|Yes|Yes|Yes|Yes|Yes|

Notes: (1) Figures ( ) are standard errors. *** denotes significance at 1%, ** at 5%, and * at 10%. (2) Standard errors are robust to heteroskedasticity and clustered residuals within each school-grade.

63