rafmacalaba/datause-encoder-data huggingface dataset:
**_Chile Solidario_ .** Evaluations of _Chile Solidario_ are more abundant, and utilize data collected after full program implementation. _Chile Solidario_ has been evaluated in the short (2 years) and medium (6 years) terms with two different sets of information: the _Chile Solidario_ panel surveys and administrative data. The results of these evaluations consistently point towards two directions: first, the main objective of increased access and use of social programs by the beneficiaries of _Chile Solidario_ has been met, especially for beneficiaries who were not enrolled in social programs before the intervention. Second, improvement in beneficiaries’ ability to independently and permanently escape poverty, reflected in an impact on employment, has remained modest, and been observed only when the supply of training programs has been scaled up to meet the increased demand.

Galasso (2006) presents the first evaluation of _Chile Solidario_ ; she studies the impact of the first two years of operation of the intervention on socioeconomic outcomes such as income and housing programs, employment, health and education. She finds that beneficiaries have better access to direct cash transfer programs, and also better knowledge of the supply of social programs. She also observes small increases in school attendance, literacy, and, to some extent, access to health care, and finds an increase in participation in housing and job training programs. Nevertheless, the higher take-up in job training programs does not translate into an increase in employment or income, at least in the short run. Finally, she finds beneficiaries to be more optimistic about their future socioeconomic status. Perticara (2007) evaluates _Chile Solidario_ using the same data, and finds no impacts on labor market participation or on income in urban areas; nevertheless, she finds some positive impacts in rural areas.

**Table 5: Selected evaluations of** **_Chile Solidario_**

|**Imp**|**act**|**Exposure time**|**Source**|
|---|---|---|---|
|•<br>•<br>•<br>•|**Increases**<br>**participation**<br>**in**<br>**job**<br>**training**<br>**programs, but no effect on employment rate**<br>**or income in the short run.**<br>**Increases participation in housing programs.**<br>**Increases school attendance.**<br>**Some weak increase in the use of health**<br>**services.**|2003-2004|Galasso (2006)<br>Galasso (2011)|
|•<br>•<br>•|**Increases employment rate.**<br>**Increases housing index.**<sup>**6**</sup><br>**Reduces autonomous income.**<sup>**7**</sup>|Between 15 and 48<br>months of intervention|Larrañaga, Contreras and<br>Ruiz (2009)|

6 This index is built using the following variables: roof, floor and walls materials, access to public electricity, drinking water and garbage disposal systems, and the ratio of number of sleeping rooms to number of household members.

35
# 4. Phillips Relations for Turkey

For estimating a Phillips relation we need sufficiently long, unbroken time series of adequate coverage and reasonable quality for nominal wage rates, unemployment rates or other labor market indicators, and some price variable as a minimum.

i) Nominal wage rates. From Section 3 it should be clear that the SII series for insured employees should not be used for this purpose. The SPO series cannot be used either; it covers only the years 1980-86 and its quality is unknown. The SMI series is also ruled out; it misses no less than 8 years between 1960 and 1984 and average wage per person engaged is not really what we need here. This leaves us with no choice but to start out directly from censuses and surveys and establish a series for average wage rate per employee. At this moment I have to leave aside the important problem of computing wage indexes rather than simple averages.

Considering the nature of censuses and surveys for manufacturing I decided to anchor the series in the census averages for employees for 1963, 1970 and 1980 and then to use the annual survey averages for persons engaged for interpolating years between 1963 and 1970 and between 1970 and 1980,

- 63 -
countries with lower GDP may come with a specific heritage of abilities that is not immediately convertible into skills valued on the US labor market. Therefore, such individuals will not attain highly ranked occupations immediately after migration (their initial performance will be lower as suggested by the positive coefficient of GDP in column 1). However, over time they will experience a higher rate of growth reflecting the gradual recognition of their abilities and motivation on the US market (captured by the negative coefficient of initial performance in column 3).

Although found to be the most important determinant, initial performance does not explain the whole variation in the assimilation patterns. Individuals may start from the same point, but have different growth rates. Indeed, Figure 2 shows how a migrant born in Mexico and one born in Uruguay have roughly the same initial occupational placement in 1990, but their predicted improvements differ to a large degree. This could be associated with a qualitative difference most likely related to selection, which in turn is determined by selection-related country attributes. As a confirmation, column 3 finds distance to the US to have a negative and significant effect on growth. Intuitively, migrants coming from distant (not so distant) countries are likely to be positively (negatively) selected from the ability distribution of the origin countries. Mexico’s proximity to the US would thus explain the difference in placement improvement between Mexican migrants and those from Uruguay. Additionally, the positive and significant effect of the communism index could reflect the higher motivation for migrants that do not have the option to return to their countries of origin.

# **6. CONCLUSIONS**

This study investigates how patterns in occupational placement of skilled male immigrants on the US labor market vary over time and by country of origin when education and other human capital characteristics are kept constant. By focusing on occupational placement rather than earnings, the analysis reaps the former’s benefit of better comparability across regions and in time.

Employing three US Census samples, 1980, 1990, and 2000, to follow the progress of cohorts who arrived during the 1970s and 1980s, it is found that both initial occupational placements by country and improvements in occupational placements within the first 10 or 20 years since arrival are highly heterogeneous. Furthermore, immigrants from countries with a low initial occupational placement are shown to progress faster than those from countries with better placement around migration time. Nevertheless, the magnitude of the convergence factor is not 28
Making it easier to formally register a business is the area of business regulatory policy that has seen most attention from policymakers over the past decade, with the _Doing Business_ project of the World Bank finding 368 reforms took place in 149 economies between 2003 and 2012. As a result of these reforms, the world average time to start a business has fallen from 50 days to 30, while the cost of starting a business is one-third of what it was (World Bank, 2013).

However, despite these reforms, the majority of businesses in most developing countries remain informal. By formality, we mean whether a business is registered for the relevant municipal licenses and with the tax department. For example, Brazil simplified its taxation system for small businesses and the state of Minas Gerais introduced a “one-stop shop”, which is a popular way of streamlining the registration process for firms worldwide. After these efforts, a government survey found 72 percent of enterprises in the state were still informal (Andrade et al, 2013).

Informality rates are highest for low-scale enterprises: de Mel et al. (2013) report that only 39 percent of Sri Lankan businesses with one worker are registered for taxes, compared to 68 percent of those with five workers and 78 percent of those with 10 workers. Most small firms in developing countries have only one or two workers. For example, in Mauritius, out of the 91,980 units with 9 or fewer workers, 70.6 percent have only one or two workers, and only 6.2 percent have five to nine workers (McKenzie, 2011). By virtue of the sheer quantity of one and two person firms, and their much greater prevalence to be informal, most of the stock of informal firms in developing countries will consist of low scale enterprises consisting of the owner and at most one other paid worker.

The key question for policymakers is then what, if anything, should they attempt to do about this vast quantity of small-scale informal firms? One view, popularized by Hernando de Soto (1989), is that these informal firm owners would like to be formal, but costly regulations and bureaucracy prevent them from doing so, causing a productivity loss for these firms. The implication is that policymakers should attempt to reduce these barriers and bring these firms into the formal sector. A competing view, associated with Maloney (2004) and others, is that firms which would benefit from formalizing do so, while smaller and less productive firms rationally opt out of the formal sector since they perceive little benefits from becoming formal. A related view is the segmented labor market perspective, in which the informal sector is seen as “the free entry sector of last resort” catering for individuals who would rather be in paid employment but are unable to find formal wage jobs (Fields, 2004, p.17). An implication is then that it is not privately optimal for these firms to formalize, so policymakers should only try and bring them into the formal sector if there is a compelling public rationale for doing so.

2
|||6. Strengthening of territorial gender<br>mechanisms.<br>7. Pacto por la Equidad de las<br>Mujeres Rurales.<br>_Places and protection:_<br>8. Casa de Mujeres Empoderadas<br>program.<br>9. Protocol for the prevention of<br>violence against women in politics.|
|---|---|---|
|5. Cross-sectional to the prior<br>strategies.|Policies and regulations that outline<br>comprehensive<br>institutional<br>frameworks to promote actions in<br>favor of gender equality.|1. Pacto XIV “Pacto de Equidad<br>para las Mujeres”.<br>2. Mecanismo de Protección al<br>Cesante - SPE y FOSFEC.<br>3. Resolution 758 of March 07,<br>2016:<br>creates<br>the<br>Gender<br>Subcommittee, which reports to the<br>Comisión<br>Permanente<br>de<br>Concertación de Políticas Salariales<br>y Laborales of the Ministry of<br>Labor.|

Notes:* Categories from the four key areas of the World Bank's strategies on gender equality (World Bank Group, 2015).

Source: Own elaboration based on information from the official websites of the Ministry of National Education, Ministry of Labor, Ministry of Agriculture and Rural Development, National Planning Department, and Presidential Advisor's Office for Women's Equality.
WPS3787

# **Public Health in India: An Overview**<sup>**1**</sup>

## **_Monica Das Gupta Development Research Group, The World Bank Email:_** **_<u>mdasgupta@worldbank.org</u>_**

## **Abstract**

Public health services, which reduce a population’s _exposure_ to disease through such measures as sanitation and vector control, are an essential part of a country’s development infrastructure. In the developed world and East Asia, systematic public health efforts raised labor productivity and life expectancies well before modern curative technologies became widely available, and helped set the stage for rapid economic growth and poverty reduction. The enormous business and other costs of the breakdown of these services are illustrated by the current global epidemic of avian flu, emanating from poor poultry-keeping practices in a few Chinese villages.

For various reasons, mostly of political economy, public funds for health services in India have been focused largely on medical services, and public health services have been neglected. This is reflected in a virtual absence of modern public health regulations, and of systematic planning and delivery of public health services. Various organizational issues also militate against the rational deployment of personnel and funds for disease control. There is strong capacity for dealing with outbreaks when they occur, but not to prevent them from occurring. Impressive capacity also exists for conducting intensive campaigns, but not for sustaining these gains on a continuing basis after the campaign. This is illustrated by the near-eradication of malaria through highly-organized efforts in the 1950s, and its resurgence when attention shifted to other priorities such as family planning. This paper reviews the fundamental obstacles to effective disease control in India, and indicates new policy thrusts which can help overcome these obstacles.

### World Bank Policy Research Working Paper 3787, December 2005

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

**_Acknowledgements:_** I am very grateful for comments from Kaushik Basu, Salim Habayeb, Barbara Harriss, Nirmal Jhala, T. Jacob John, Peter Miovic, Rajiv Misra, Dilip Mookherjee, Lalit Nath — and from Indian government officers, including K.K.Bagchi, K.P.Krishnan, Suresh Kumar, M.N.Roy, and Rajendra Shukla.

1 A shorter version of this is forthcoming in Kaushik Basu, ed., The Oxford Companion to Economics in India.
<!-- Start of picture text --> Figure 16: Crime and Violence as a constraint to growth<br>Panel A. Inequality and crime as a barrier to growth<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>25 30 35 40 45 50 55 60 65<br>Gini index (%)<br>Panel B. Inequality and crime<br>100<br>80<br>60<br>40<br>20<br>0<br>40 45 50 55 60<br>Gini index (%)<br>Panel C. Crime as a barrier to growth<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>LAC EAP SSA MENA ECA<br>Crime as a barrier to growth (%)<br>Homicides rate per 100.000<br>% of firms who think so<br><!-- End of picture text --> Note: Crime as a barrier to growth indicates the % of firms that find crime and violence to be a major constraint to growth in each country. Source: World Bank Enterprise surveys 22
# **6.2 Results**

Figure 7 shows the results for the main outcomes. The left-hand panels display the eventstudies in levels, while the right-hand panels display the regression-based event-studies. The top panels show that for trade openness the synthetic control matches the average treated country closely during the 10 years prior to the event.25 Trade openness increases in the year of the event and its trend changes in post-reform years, compared to the stable pre-trends. The absence of a dip in the immediate pre-reform years limits concerns about intertemporal substitution, although some liberalization events were predictable (especially in China and Mexico where the event is World Trade Organization accession). Overall, as expected, trade increases substantially when countries slash their import tariffs.

Turning to our outcomes, we see that trade liberalization events coincide with a positive break from trend in the capital share of domestic product. The synthetic control continues on its slight upward trend.26 The impacts on factor taxation are displayed in the bottom set of panels of Figure 7. We observe that _ETRK_ sharply increases following the liberalization event. Both _ETRK_ and _ETRL_ break from the stable pre-trend at the time of liberalization, but the effect on capital taxation is about double that on labor. Despite the small sample size, the dynamic post-treatment effect coefficients are typically significant at the 5% level. The p-value for the joint significance of all post-reform dummies are well below 0.05. Based on the difference-in-differences model, the liberalization events led to a 10 percentage point rise in trade openness over 10 years and a 4.8 (2.0) percentage point increase in the effective tax rate on capital (labor) (Table A2).

# **6.3 Robustness, interpretation and limitations**

To test for robustness of the event-study results, we conduct several checks. First, we jointly match on all four outcomes for each event to create synthetic controls, instead of creating outcome specific synthetic controls. Figure A10 shows that this leads to a small deterioration of the pre-trends, but to very similar point-estimates. Second, to check that

> 25Table C1 details the synthetic control matches for each event and outcome.

> 26The stability of these patterns helps alleviate concerns that the true counterfactual level would be overstated if trade flows and returns to capital were diverted away from countries in the synthetic control.

22
Goldin, Claudia. 1995. “The U-Shaped Female Labor Force Function in Economic Development and Economic History.” In: Schultz, TP, _Investment in Women’s Human Capital and Economic Development_ . University of Chicago Press, pp. 61-90.

Holloway, Kyle, Zahra Niazi and Rebecca Rouse. 2017. _Women’s Economic Empowerment Through Financial Inclusion: A Review of Existing Evidence and Remaining Knowledge Gaps._ Innovations for Poverty Action, Financial Inclusion Program.

Ibrahim, Kasirye, 2013. "Constraints to Agricultural Technology Adoption in Uganda: Evidence from the 2005/06-2009/10 Uganda National Panel Survey," Research Series 151979, Economic Policy Research Centre (EPRC).

International Finance Corporation (IFC). 2016. _Investing in Women along Agribusiness Value Chains._ World Bank.

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ILO. 2018b. _World Employment Social Outlook: Trends 2018._ Geneva.

ILO. 2018c. _Data collection guidelines for ICSE-18._ 20th International Conference of Labour Statisticians, Room Document No. 4.

ILO. 2018d. “Exploring Light Time-Use approaches for measuring productive activities.” What Counts: Statistics on Work, Brief No. 1, August.

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ILO. 2013. _Resolution I concerning statistics of work, employment and labour underutilization._ 19th International Conference of Labour Statisticians, Geneva.

Jayachandran, Seema. 2015. “The Roots of Gender Inequality in Developing Countries.” Annual Review of Economics 7: 63-88.

Johnston, Deborah, Sara Stevanob, Hazel J. Malapit, Elizabeth Hulla, and Suneetha Kadiyala. 2018. “Time Use as an Explanation for the Agri-Nutrition Disconnect: Evidence from Rural Areas in Low and MiddleIncome Countries.” _Food Policy_ 76: 8-18.

Jones, Nicola, Yisak Tafere and Tassew Woldehanna. 2010. “Gendered risks, poverty and vulnerability in Ethiopia: to what extent is the Productive Safety Net Programme (PSNP) making a difference?” Working paper, Overseas Development Institute.

Kabeer, Naila. 2012. “Women’s Economic Empowerment and Inclusive Growth: Labour Markets and Enterprise Development.” IDRC Research Paper.

26
# **Learning the Impact of Financial Education When Take-Up Is Low**<sup>**#**</sup>

Gabriel Lara Ibarra _World Bank_ David McKenzie _World Bank_ Claudia Ruiz Ortega _World Bank_ _JEL Classification Codes:_ D14, G21, G28, O12.

_Keywords:_ financial literacy; credit-card behavior; low take-up

> # We thank Adolfo Albo, Juan Luis Ordaz, David Cervantes and the BBVA Bancomer Financial Education Team for their collaboration on the experiment and for providing us with the anonymized customer data used in this paper. We would also like to thank the participants at the EduFin Summit 2017 in Mexico City for comments and suggestions. The authors of the paper received no funding for this work from BBVA Bancomer, and maintained independence in their analysis and reporting of the results. The findings, interpretations, and conclusions expressed in this paper are those of the authors and do not necessarily represent the views of the World Bank, its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
This would simplify the drug analysis, and make it feasible to use pharmacy tally cards to note the issue of supplies for inpatient and outpatient use.

Finally, in any discussion of further hospital cost analysis, consideration should be given to the virtues of a prospective rather than retrospective analysis. This has proved feasible in Malawi in the past (Ministry of Health, Malawi, unpublished report, 1975), and enables temporary changes to be made in information systems to permit the desired analyses. It also helps to ensure that existing information systems are well kept, which is particularly vital in the case of hospital and health centre activity statistics. As the analysis here has shown, inaccuracies in activity statistics make assessments of hospital efficiency extremely difficult, and such statistics are unlikely to be well kept unless it is known they will be used.

The case study also provides conclusions of relevance to other countries. It was found to be extremely useful to look in detail at the allocation of resources within hospitals, especially of staff time and drugs. The inpatient/outpatient allocation of resources is particularly important to investigate, rather than simply apportioning costs on some assumption of the ratio of cost per outpatient to cost per inpatient day, as is often done. It is also important to look at the hospital's role in the district health system, and the extent to which its resources and skills serve the district as a whole.

25