rafmacalaba/datause-encoder-data huggingface dataset:
# **Table 7: Indirect Questions about Informal Payments and other Sensitive Acts referring to “establishments in this line of business”**

||N|N<br>Reticent|Coefficient<br>Reticence<br>Dummy|t‐statistic|Uncond.<br>Mean|
|---|---|---|---|---|---|
|To what extent do you**agree or disagree**<br>with the following statements?<br>**It is common forestablishments in this**<br>**line of business**<br> **to have to pay informal**<br>**payments/gifts to get things done with**<br>**regard to customs, taxes, licenses,**<br>**regulations, etc.**<br>(scale 1‐4; 1= strongly disagree<br>to 4= strongly agree)<br>**Establishments in this line of business**<br>**know in advance about how much this**<br>**informal payment/gift is to get things**<br>**done.**<br>(scale 1‐4; 1=strongly disagree<br>to 4=strongly agree)|4640<br>4638|610<br>610|-0.052<br>0.007|(-1.20)<br>(0.16)|2.228<br>2.113|
|**What percentage of total annual sales**<br>**would you estimate atypical**<br>**establishment in your sector of activity**<br>**reports for tax purposes?**<br>(0=more than median;<br>1= less than median)<br>**What percentage of total workforce**<br>**would you estimate thetypical**<br>**establishment in your line of business**<br>**declares for tax purposes?**<br>(0=more than median;<br>1= less than median)|4641<br>4641|610<br>610|_0.053**_<br>_0.124***_|_(2.39)_<br>_(5.55)_|0.440<br>0.476|

t statistics in parentheses

* p<0.10, ** p<0.05. *** p<0.01

23
# **Sources**

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Bhatnagar, S. 2006. ―India‘s Software Industry.‖ In V. Chandra (ed), _Technology, Adaptations, and Exports: How some developing countries got it right_ , 49–81. Washington DC: World Bank.

Binswanger, H. P., and V. W. Ruttan. 1978. _Induced Innovation: Technology, Institutions, and Development._ Baltimore: Johns Hopkins University Press.

Calderón, C. 2007. ―Trade, Specialization and Cycle Synchronization: Explaining Output Comovement between Latin America, China and India.‖ Mimeo. Washington DC: World Bank.

Calderón, C, W. Easterly, and L. Servén. 2002a. ―How did Latin America‘s infrastructure fare in the era of macroeconomic crises?‖ _Central Bank of Chile Working Paper_ 185, Santiago: Central Bank of Chile.

———. 2002b. ―Infrastructure compression and public sector solvency in Latin America.‖ _Central Bank of Chile Working Paper_ 187, Santiago: Central Bank of Chile.

Calderón, C. and K. Schmidt-Hebbel. 2003. ―Learning the hard way: Ten lessons for Latin America‘s turmoil.‖ Mimeo, Santiago: Central Bank of Chile.

Calderón, C. and L. Servén. 2010. ―Infrastructure in Latin America.‖ In J. Ocampo and J. Ros (eds), _The Oxford Handbook of Latin American Economics,_ New York: Oxford University Press.

Chang, H. J. 2003. _Kicking Away the Ladder: Development Strategy in Historical Perspective_ , London: Anthem Press.

Chandra, V., J.Y. Lin, and Y. Wang, 2012. ―Leading Dragons Phenomenon: New Opportunities for Catch-Up in Low-Income Countries.‖ _World Bank Policy Research Working Paper_ 6000, Washington DC: World Bank.

Chenery, H. B. 1958. ―The Role of Industrialization in Development Programmes.‖ In A. N. Agarwala and S. P. Singh (eds), _The Economics of Underdevelopment_ , 450–471, Bombay: Oxford University Press.

———. 1961. ―Comparative Advantage and Development Policy.‖ _American Economic Review_ , 51(1): 18–51.

Dailami, M. and R. Hauswald. 2003. ―The emerging project bond market: Covenant provisions and credit spreads.‖ _World Bank Policy Research Working Paper_ 3095, Washington DC: World Bank.

55
<!-- Start of picture text --> A B<br>Cc<br>2 ~ —ialy+—-<br>re]£ D<br>3<br>2 E<br>r —ii-<br>F<br>G<br>Hl<br>| a<br>—_]}—_<br>J<br>Poverty line<br>Mean and Variance of welfare<br><!-- End of picture text -->
**<u>Table 6. IV estimated impact on enrollment and child development outcomes</u>**<sup>**a**</sup>

||IVMode|l:Baseline|IVMod|el:Midline|IVMod|el:Endline|
|---|---|---|---|---|---|---|
||Actua|l Batch 1|Actual|Batch 1|Actua|l Batch 1|
||Coeff|Robust SE|Coeff|Robust SE|Coeff|Robust SE|
|**Enrollment in ECED Programs**|||||||
|Was child enrolled in project playgroups in survey year (1=Yes)|0.154***|(0.034)|0.206***|(0.050)|0.245***|(0.058)|
|Was child enrolled in non-project playgroups in survey year (1=Yes)|0.008|(0.022)|0.006|(0.032)|-0.002|(0.035)|
|Was child enrolled in Islamic Kindergarten in survey year (1=Yes)|-0.010|(0.011)|-0.032|(0.023)|-0.052|(0.038)|
|Was child enrolled in Kindergarten in survey year (1=Yes)|-0.008|(0.016)|-0.075|(0.047)|-0.097|(0.065)|
|Was child enrolled in any ECED programs in survey year (1=Yes)|0.142***|(0.040)|0.045|(0.046)|0.003|(0.034)|
|Was child enrolled in Primary school in survey year (1=Yes)|NA|NA|0.015|(0.010)|0.004|(0.005)|
|Cumulated number of months of project playgroup|1.516***|(0.335)|3.029***|(0.661)|4.087***|(0.932)|
|Cumulated number of months of non-project playgroup|0.072|(0.220)|0.106|(0.383)|-0.160|(0.463)|
|Cumulated number of months of Islamic Kindergarten|-0.100|(0.108)|-0.423|(0.315)|-0.758|(0.567)|
|Cumulated number of months of Kindergarten|-0.094|(0.154)|-0.868|(0.555)|-1.770|(1.092)|
|Cumulated number of months of any ECED programs|1.394***|(0.392)|1.844**|(0.766)|1.399|(1.030)|
|Cumulatednumberof months of Primary school|NA|NA|0.154|(0.104)|0.256|(0.541)|
|**Standardized Child Development Outcomes**|||||||
|EDI: Physical Health & Well-Being|0.113|(0.095)|0.072|(0.080)|0.001|(0.098)|
|EDI: Social Competence|0.054|(0.099)|-0.089|(0.073)|-0.099|(0.079)|
|EDI: Emotional Maturity|0.018|(0.095)|0.019|(0.072)|-0.010|(0.083)|
|EDI: Language & Cognitive Development|0.067|(0.048)|0.050|(0.071)|-0.031|(0.030)|
|EDI: Communication & General Knowledge|-0.022|(0.057)|-0.103**|(0.044)|0.012|(0.100)|
|SDQ: Emotional Symptoms|-0.166*|(0.094)|-0.048|(0.077)|-0.036|(0.091)|
|SDQ: Conduct Problems|-0.121|(0.085)|-0.004|(0.074)|-0.094|(0.082)|
|SDQ: Hyperactivity & Inattention|0.012|(0.091)|-0.034|(0.074)|0.007|(0.089)|
|SDQ: Peer Problems|0.009|(0.101)|0.067|(0.089)|-0.016|(0.082)|
|SDQ: Pro-social Behavior|0.057|(0.093)|0.040|(0.086)|-0.077|(0.086)|
|SDQ:Total Difficulties|-0.122|(0.102)|-0.011|(0.076)|-0.059|(0.095)|

Notes: *** p<0.01, ** p<0.05, * p<0.1;<sup>a</sup> IVs are two dummy variables indicating original batches 2 or 3 with original batch 1 as a reference group. Each row is the result of a separate regression. Models are estimated separately for baseline, midline and endline. Controls include: child’s age, gender, household size, household wealth and mother’s education level. Robust standard errors are clustered at the village level. Sample size for each year varies from 1,311 to 1,317.

33
30 best approach for influencing the investment policies of DC pension funds and achieving efficient outcomes in the long-run. The application of VaRs for pension funds remains controversial, as there are well-known arguments against the adoption of a short run risk measure for institutional investors that should operate with a long time horizon.<sup>16</sup> Whereas the Mexican approach is innovative and attractive in many aspects, including the objective of containing downside risk, assessing its effectiveness will require a longer period and comparisons with the outcomes generated by other approaches to risk-based supervision of DC plans, such as the Australian.

**Table 11: Average Composition of the Aggressive Pension Portfolio in Mexico (Siefores 2)**

||2000|2001|2002|2003|2004|2005|2006|
|---|---|---|---|---|---|---|---|
|Government Bonds|92.6|89.8|85.5|84.5|85.5|86.1|76.5|
|Corporate Bonds|5.4|7.8|12.3|11.0|9.6|7.8|6.6|
|Financial Institutions Bonds|2.0|2.4|2.1|4.5|4.9|4.0|4.9|
|Domestic Equity||||||0.5|2.0|
|Foreign Assets||||||1.6|10.0|
|Fixed Income||||||0.6|4.2|
|Equity||||||1.0|5.8|
|Total|100.0|100.0|100.0|100.0|100.0|100.0|100.0|

_Source_ : Consar

**Figure 5: Shifts in the Efficient Frontier and Actual Risk-Return Combinations**

<!-- Start of picture text --> 27.5%<br>22.5% 1 0<br>3<br>12 11<br>9<br>6 8<br>17.5% 1 5 4<br>2<br>1<br>7 7 2 9 8 12 10 3<br>12.5% 6 11<br>4 5<br>7.5%<br>0.00% 0.05% 0.10% 0.15% 0.20% 0.25% 0.30% 0.35% 0.40%<br>VaR<br>2006 2006 without Equity Nov-05 Dec-06<br>Annualized rate of returns<br><!-- End of picture text -->
is less surprising; this series provides short-term forecasts for global and regional economic growth, and so have a rather short life; the forecasts are often picked up by the mass media, which will not be reflected in Google Scholar. Only one of the six editions of the _Global Monitoring Report_ has been cited (with the 2005 report receiving three); again, this might not be surprising given the report’s objective of surveying recent progress in attaining development goals. The seven editions of the _Doing Business_ series have hardly ever been cited in the documents covered by Google Scholar, though this series has clearly had a lot of impact on policy makers and civil society, and is more visible in Google News.

It is also notable that there are more scholarly background papers to a number of these flagship reports that get cited more in scholarly writings than the flagships themselves. For example, we found that just one of the Background Papers to the 1990 _World Development Report_ has been cited 200 times, more than twice the WDR itself. Arguably the citation counts for the background papers owe much to the publicity provided by the flagship reports. But the more important direct channel for scholarly influence may well be the background papers to these reports, which could (at least in principle) have been written without the report.

The most cited single book in the Bank’s history is not any of these flagship series; rather it is Angus Deaton’s _The Analysis of Household Surveys: A Microeconometric Approach to Development Policy_ (1997), with 2,282 citations. This book was commissioned by the Bank’s research department to assist users of household surveys in analyzing the data. This is an example of a class of Bank products that reach out to practitioners—helping to bridge the gap between cutting-edge research methods and routine applications. The book aimed to reach academics and other researchers, and it is reassuring that it clearly proved valuable to them.

The Deaton volume is an outlier amongst Bank books, as is plain in Figure 5, which gives the number of Google Scholar citations received by Bank books plotted against number of publications, ranked by citations. The next most cited volume is _Patterns of Development 19501970_ by Hollis Chenery and Moises Syrquin, published in 1975 and with a total of 831 citations. There are 19 books published by the Bank that received 500 or more citations, while 52 books received more than 300 and 191 received more than 100 (see Table 5).

As noted above, journal articles and working papers have been the main channel for the scholarly influence of the Bank’s publications. The most cited single publication is the paper by Ross Levine and David Renelt, “A Sensitivity Analysis of Cross-Country Growth Regressions”, 18
# **1. Introduction**

Poverty is a central issue for Russian policymakers who view poverty reduction as a cornerstone of the nation’s economic development strategy. Despite a significant decline in poverty over the last decade, the slowing economic growth and a regionally unbalanced pattern of development indicate that poverty will pose major policy challenges in Russia for years to come. To rise to those challenges, the Russian government would need reforms in many areas related to poverty reduction, including the system of social protection and labor market policies (World Bank 2005). Such reforms should be designed based on an extensive analysis of characteristics of poverty, the relationship of poverty and economic development, and poverty dynamics. The success of reforms would depend on the quality of such research.

The history of poverty studies in Russia dates back to the 1920s when the minimum consumer budget, or subsistence minimum, was established by a government decree and was calculated on a yearly basis for several years before being abolished by Stalin (Pisarev 1957). During the Soviet period, the concept of poverty was unacceptable for ideological reasons. However the idea of maintaining a minimum standard of living for the population existed as early as in the 1970s. A minimum consumption basket was developed in the 1970s as a guide for establishing the minimal standard of living for the Soviet population. The conventional, need-based concept of poverty did not gain acceptance in the Soviet Union until the late 1980s (Klugman 1997). In the early 1990s, the Russian government adopted a new food basket (Popkin, Mozhina, and Butrin 1992) and a new poverty line. Russia’s official poverty lines were established under guidelines developed by the Ministry of Labor and Social Development (MLSD, 2000).

Since 1992, Russian social science has witnessed a sharp increase in the number of studies attempting to devise methods to determine poverty lines, describe poverty profiles, and analyze poverty causes. The community of poverty researchers, too, has been growing and, as we show in this paper, while being dominated by economists and sociologists, includes scientists from other fields with different approaches toward the direction and methodology of scientific studies. This diversity of perspectives might be important for a comprehensive analysis of poverty but it could complicate the 2
**Table 1. Intended Beneficiaries of Social Insurance Schemes in Urban China**

||Pension<br>Insurance|Unemployment<br>Insurance|Medical<br>Insurance|Work Injury<br>Insurance|Maternity<br>Insurance|
|---|---|---|---|---|---|
|**_Social Insurance Schemes for_**|**_Urban Wage_**|**_-Based Workers_**||||
|Public Institution Employees|T|M|M|T|T|
|Civil servants|T|T|M|T|T|
|Urban enterprise workers|M|M|M|M|M|
|Self-employed individuals|V||M|V||
|Informal employment|V|V|V|V/M||
|Rural migrant workers|V|V|V|V/M||
|Unemployed workers|V||V|||

# **_Social Insurance Schemes for Urban Residents_**

|Urban residents<br>V|M|
|---|---|

Note: (1) Urban enterprises include SOEs; collective units; joint-ownership; limited liability and share holding companies; Foreign; Hong Kong SAR, China; Macao; and Taiwan, China funded enterprises, private enterprises; (2) M- mandatory by the Social Insurance Law and policies, V- voluntary by the Social Insurance Law and policies, T- traditional defined benefit approach; (3) unemployment insurance, work injury insurance and maternity insurance do not apply to urban residents.

**Table 2.  Population Based Estimates of Social Insurance Participation for Different Groups Of Workers Living in Urban China (%)**

||Local Resident<br>Workers|Migrant<br>Workers|Rural Migrant<br>Workers|Urban Migrant<br>Workers|
|---|---|---|---|---|
|Pension Insurance|||||
|Capital cities|59.0|34.1|12.6|64.7|
|Other cities|32.3|24.1|12.3|53.7|
|All cities|42.9|27.1|12.2|57.9|
|Unemployment Insurance|||||
|Capital cities|44.6|25.7|6.8|52.5|
|Other cities|22.5|13.9|5.6|34.7|
|All cities|27.5|17.5|5.9|41.7|
|Medical Insurance|||||
|Capital cities|63.2|33.3|14.2|60.5|
|Other cities|45.2|26.2|17.2|48.7|
|All cities|49.0|28.2|16.2|53.2|

Source: the National Bureau of Statistics, 2005 One Percent Population Sample.

29
<!-- Start of picture text --> Real Output Growth Weight on Recession Regime - F(z)<br>7.5 0.00<br>5.0<br>-0.25<br>2.5<br>0.0<br>-0.50<br>-2.5<br>-5.0<br>-0.75<br>-7.5<br>-10.0 -1.00<br>1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009<br><!-- End of picture text --> Figure 2: Weight on recession regime and growth recessions
38

**Unsuccessful reforms.** So far, our indexes of reforms consider only successful reforms. This can be problematic as one might wonder whether the findings allow drawing the strong conclusion that structural reforms matter for labor productivity growth. Although it is difficult to find a perfect counterfactual in economics, the MONA database provides an opportunity to explore the impact of unsuccessful reforms.  If the hypothesis that successful reforms raise productivity holds, we should expect unsuccessful reforms to have no impact or a negative impact on productivity. This section examines the impact of reforms not met on labor productivity growth using the same sectorial categorization of reforms as in Table 1 and the Z- score approach described in section III to compute an index of unsuccessful reforms. The estimation strategy and control variables are similar to those described in the baseline analysis. The findings reported in Table 9 below seem to reinforce the conclusion that successful structural reforms matter for labor productivity growth. As can be seen, unsuccessful financial and real sector reforms have negative impacts on productivity. A one standard deviation increase in unsuccessful reforms in financial and real sector reforms decreases labor productivity growth by 1.121 and 3.975 standard deviation respectively. In both cases, the estimated coefficients are highly significant at the 1 percent level. On the opposite, unsuccessful fiscal and trade reforms seem to have a positive impact on labor productivity growth. However, the estimated coefficient for trade reforms is barely significant at the 10 percent level. Although the findings on fiscal reforms might appear counterintuitive, the high proportion of successful fiscal reforms implemented in parallel might drive it. The externality effects of successful fiscal reforms might drive the positive and significant coefficient.

||**Table 9. Impact o**|**f unsuccessful on la**|**bor productivity growth**||
|---|---|---|---|---|
||Financial reforms|Fiscal reforms|Real sector reforms|Trade reforms|
|Reforms|-1.121***<br>(0.091)|0.705***<br>(0.044)|-3.975***<br>(0.308)|0.115*<br>(0.060)|
|Observations|5,126|8,347|7,987|2,615|
|R-squared|0.2376|0.2516|0.2535|0.1783|

Notes: The table presents standardized coefficients of the impacts of reforms Not Met on firm-level labor productivity growth. The specifications include firm’s individual characteristics, sector and year fixed effects. At the macroeconomic level, the specifications include the average growth of GDP, the level of inflation, and the quality of policies and regulations related to the private sector and country fixed effects. All estimates use the weights and are standardized so that can be compared across structural reforms. Robust standard errors clustered at the country level are in parentheses. ***, **, * denote significance at the 1, 5, and 10 percent level.
**Figure 4.** Average height of youth between 20 and 24 years of age in Mexico in 2000, 2006 and 2012, by gender and income decile

<!-- Start of picture text --> Males Females<br>180 180<br>175 175<br>170 170<br>165 165<br>160 160<br>155 155<br>150 150<br>145 145<br>140 140<br>I II III IV V VI VII VIII IX X I II III IV V VI VII VIII IX X<br>Decile Decile<br>2000 2006 2012 2000 2006 2012<br>Centimeters (cm) Centimeters (cm)<br><!-- End of picture text --> Source: estimations of the authors based on the data from the National Health Survey 2000 (ENSA 2000), National Health and Nutrition Survey 2006 (ENSANUT 2006) and the National Health and Nutrition Survey 2012 (ENSANUT, 2012).

# _A. Intergenerational mobility_

Studies on intergenerational mobility have thus far ignored health, despite its central importance in well-being (Halliday, Mazumder and Wong, 2018). We hypothesize that this is mainly due to the difficulty of obtaining data on a longitudinal panel that includes health indicators. This study incorporates health as a measure of intergenerational mobility and contributes to addressing this gap in the intergenerational mobility literature.

The mobility literature that intersects with health has noted that health conditions are important determinants of income differentials and that inequality in income tends to be correlated between generations, in part due to the intergenerational associations between education and health (Ahlburg, 1998).

Recently, the importance of analyzing intergenerational mobility in health to understand the persistence in socioeconomic differentials has been emphasized. This area of study seeks to identify the specific role that transmission of health status plays as a determinant of social mobility (Akbulut-Yuksel and Kugler, 2016). Some analyses have also documented the transmission potential of risk behaviors for health, indicating that parental behaviors tend to be replicated by adolescents, and specifically follow a transmission pattern from father to son and mother to daughter (Wickrama et al., 1999).

In Mexico, recent studies have found low intergenerational social mobility, characterized by intergenerational transmission that is greater for health than for education, which parallels the existence of an intergenerational correlation in life expectancy (Delajara et al., 2018; MorenoJaimes, 2017). According to the literature, the degree of persistence in health between generations is affected by the context in which someone is born and where their child and youth development occurs. Hence, there is a greater persistence of poor health when the beginning of life occurs under conditions of socioeconomic vulnerability (Bhalotra and Rawlings, 2013) .

13
Table 10: Mean and standard deviation of Indonesia standard

||Indonesia|standard<sup>1</sup>|
|---|---|---|
||Mean|S.D.|
|Kindergarten|2.944|1.041|
|Islamic kindergarten|2.521|0.756|
|Non-project playgroup|2.659|1.007|
|Project playgroup|3.090|1.002|
|Overall|2.932|1.014|

> 1 The Indonesia ECED standard is an alternative measure of observed classroom quality that only includes the 28 common items between the ECERS-R and the national standards for ECED.

27
# **Figures and Tables**

**Figure 1: Evolution of the premium on industry-level Suharto family connectedness – individual competition indicators**

<!-- Start of picture text --> Entry Exit<br>'93'94'95'96 '00'01'02'03'04'05'06'07'08'09 '93'94'95'96 '00'01'02'03'04'05'06'07'08'09<br>Suharto era Post Suharto era Suharto era Post Suharto era<br>PCM PE<br>'93'94'95'96 '00'01'02'03'04'05'06'07'08'09 '93'94'95'96 '00'01'02'03'04'05'06'07'08'09<br>Suharto era Post Suharto era Suharto era Post Suharto era<br>Herfindahl MS4<br>'93'94'95'96 '00'01'02'03'04'05'06'07'08'09 '93'94'95'96 '00'01'02'03'04'05'06'07'08'09<br>Suharto era Post Suharto era Suharto era Post Suharto era<br>lnN lnP<br>'93'94'95'96 '00'01'02'03'04'05'06'07'08'09 '93'94'95'96 '00'01'02'03'04'05'06'07'08'09<br>Suharto era Post Suharto era Suharto era Post Suharto era<br>.4 .2<br>.2 .1<br>0<br>0<br>PC family PC family<br>β β -.1<br>-.2 -.2<br>-.4 -.3<br>.2 4<br>0 2<br>PC family-.2 PC family0<br>β β -2<br>-.4<br>-4<br>-.6<br>.4 .4<br>.2<br>.2<br>0<br>PC family PC family<br>β 0 β -.2<br>-.2 -.4<br>.5 .5<br>PC family0 PC family0<br>β -.5 β -.5<br>-1 -1<br><!-- End of picture text --> _Note:_ The figure depicts annual variation in the estimated impact of the market share of Suharto family firms on the outcome of interest. The dots depict the coefficient estimates ′93 ′94 ′09, estimated using the regression: = ∑ Y Y which are presented in Table jjii αα , αα , ... ... . αα YY C5.1, with 1996 as the omitted year. ii=1993,..,2009 ii jj ii=1993,..,2009 measures the aggregate market share of Suharto family firms (the average of ii jjii jj ii jjii αα PC (MMSS) ∗DD(Y = tt) + ∑ γγ SS ∗DD(Y = tt) + ππ + ττ + εε their aggregate market share in 1996 and 1997), jj measures Suharto-era (time-invariant) industry characteristics, is a PC (MMSS) vector of industry fixed effects, and is a vector of year fixed effects. The vertical bars indicate the 95% confidence interval jjii jj SS ππ associated with the estimates. ii ττ 29