rafmacalaba/datause-encoder-data huggingface dataset:
- 2 -

4) the range and flexibility of policy instruments the government has at its disposal. Constraints on the use of some policies, such as the inability to charge at different rates for individual treatments in the public sector or to charge at all need to be considered. Similarly, can the private sector be regulated or must its behavior be regarded as a given by the authorities?

One candidate for a criterion on which to base the rationing decision which appears in the lterature has been the cost-effectiveness of interventions. This decision rule implies that the amount of some unit of output (lives saved or, as in a recent World Bank study, discounted healthy life years') per dollar spent on the intervention is calculated and the activities with the highest ratios be undertaken. If correctly measured, this criteria is clearly the proper one by definition. However, the proper measure of this concept depends on dhe factors just listed and these are not usually included in its calculati'n. One aim of the paper is to show under what conditions these commonly calculated versions of costeffectfiveness of medical and public health procedures provides an adequate guide to decision-making. As will be demonstrated, the conditions are so restrictive as to be usable in only very special circumstances. A further goal of the paper is to identify the types of information which do need to be collected in order to make correct public health decisions.

The type of questions which are addressed in the first section of this paper are limited to the treatment of people who voluntarily show up at public health facilities, the prices charged them and the range of disease conditions the health authorities choose to treat. The objective is assumed to be the improvement in health status and the budget is that of the Ministry of Health. Various assumptions concerning the private sector are then made. Broader issues (and in the context of developing countries, very possibly the more important issues) such as the extent of the network of health facilities, the provision of public health measures such as safe water, sanitation or vector control, the regulation of private providers or public information campaigns designed either to change lifestyles and habits or to increase demand for services in public clinics are handled in section 2. In section three, the broader class of problems in which welfare rather than health status is the objective will be examined. This formulation overcomes many of the problems which arise in the first two sections. Since much of the basic analytics for this case are standard in the literature of project evaluation and generally transfer to 'Dean Jamison and Henry Mosley (eds.),(forthcoming), Disease Control Priorities in Developing Countries.
highly educated, who are the least likely to ever return. The implication in terms of brain drain, and lost brain gain, are obvious and potentially very damaging to future development.

**Table 4** _Maximum Likelihood Return Duration Models (log-logistic hazard function)_

||**Coef.**|**Rob. SE**|
|---|---|---|
|origin of spell|-0.137***<br>|0.009|
|gender (female=1)|0.310***|0.076|
|spouse is abroad with migrant|0.897***|0.077|
|coastal region|0.036|0.085|
|central region|0.055|0.085|
|mountain region|0.133|0.094|
|urban areas|-0.158***|0.060|
|age (in years)|-0.023***|0.003|
|years of education|0.240*|0.135|
|years of education squared|-0.025**|0.012|
|years of education cubed|0.001*|0.000|
|no. of household members age 0-14|-0.085***|0.022|
|no. of males in household age 15-35|0.125***|0.031|
|no. of females in household age 15-35|-0.080**|0.037|
|no. of males in household age 36-55|0.320***|0.037|
|no. of household members age >55|0.351***|0.041|
|migrant network in Greece|0.105***|0.032|
|migrants network in Italy and beyond|0.170***|0.044|
|minimum distance to border crossing|0.001|0.001|
|Regularizations (epoch dummy >1998)|0.440***|0.073|
|country of destination|||
|Greece|0.629***|0.074|
|Italy|0.432***|0.087|
|occupation while abroad|||
|agriculture|0.138|0.099|
|crafts|0.493***|0.093|
|service|0.480***|0.113|
|blue collar|0.415***|0.100|
|white collar|0.993***|0.185|
|other|0.232|0.244|
|constant|1.608***|0.515|
|logarithm of gamma|-0.672***|0.028|
|gamma|0.511||
|no. of subjects|2,955||
|no. of failures|984||
|total time at risk|16,736||
|log-likelihood|-1,912||
|chi2|1,285||
|prob.|0.000||
|note: .01 - ***; .05 - **; .1 - *|||

22
_C_ over which _M_ % _i_ , _c_ ,1980 is calculated includes 210 cities from the 1980 census files that are linked to the US patent data described next. The primary measures of _M_ % _i_ , _c_ ,1980 include all individuals regardless of age or education level to form _M_ % _i_ , _c_ ,1980 , only dropping those in group quarters (e.g., military barracks) or not living in an urban area. Extensions test variations on these themes.

# _US Patenting Data_

The second building block for the instrument is the trend in patenting for each city _Techck_ ,, _tA_ − _S_ . These series are quantified through individual records of all patents granted by the United States Patent and Trademark Office (USPTO) from January 1975 to May 2009. Each patent record provides information about the invention (e.g., technology classification, citations of patents on which the current invention builds) and inventors submitting the application (e.g., name, city). USPTO patents must list at least one inventor, and multiple inventors are allowed. Approximately 7.8 million inventors are associated with 4.5 million granted patents during this period. The online supplement documents how the patent data are augmented in terms of city and industry definitions. Only patents with all inventors living in the United States at the time of their patent application are included, and multiple inventors are discounted so that each patent receives the same weight when measuring inventor populations. Concordances link USPTO technology classes to ISIC3 industries in which new inventions are manufactured or used. The main estimations focus on industry-of-use, affording a composite view of the technological opportunity developed for an industry.

The probable ethnicities of inventors are estimated through the names listed on patents (e.g., Kerr 2007). This procedure exploits the fact that individuals with surnames Gupta or Desai are likely to be Indian, Wang or Ming are likely to be Chinese, and Martinez or Rodriguez are likely to be Hispanic. The name matching work exploits two commercial databases of ethnic first names and surnames, and the procedures have been extensively customized for the USPTO data. The match rate is 98% for US domestic inventors, and the process affords the distinction of nine ethnicities: Anglo-Saxon, Chinese, European, Hispanic, Indian, Japanese, Korean, Russian, and Vietnamese. Most
were extracted from China Data Online. Linear interpolation was used to impute the death rate and birth rate for Heilongjiang and Shaanxi in 2000. This yielded a 10 year panel data set for 31 provinces in China.

# _Regression Analysis—Panel Data_

The panel data were used to test for contemporaneous correlation between the size of laid-off workers and the death rate. This is the so-called “instantaneous causality” in the sense used by Granger.

_Deathit_ = α _i_ + β 1 _SOEit_ + β 2 _GDPit_ + β 3 _Urbanit_ + β 4 _Industryit_ +ψ _i_ + ε _it_ Deathit indicates the death rate for a province in a specific year; SOE is the number of workers laid-off by province for a given year. GDPit, Urbanit, Industryit are respectively province-year specific GDP per capita, urbanization rate, and industrial GDP as a percentage of total GDP. As was the case earlier, fixed effect panel regression models are used to identify the contemporaneous correlation since all the provinces are included.

# _Preliminary Results_

Our preliminary regression results suggest that the number of laid-off workers from SOEs is positively correlated with the death rate. The effects become smaller after controlling for GDP and industrial production but remain marginally significant at the 10 percent level (see Table 4). Urbanization rate and GDP per capita are found to have a negative effect on the death rate whereas industrial production is positively correlated with the death rate. This positive correlation may be because the industrial production includes the mining industry which experienced a high incidence of accidents and a number of catastrophic events.

# _Future research_

Our results are based on the assumption that loss in employment affects health instantaneously. However, it is also reasonable that that the loss of jobs may not lead to a significant change in health outcomes in the same year. The existing literature does not offer any guidance as to the correct or optimal lag structure on this matter. Hence this 24
- more than 53 percent of respondents were not happy with interruption frequency and durations

- 48 percent were not satisfied with response times to repair faults

- 28 percent of respondents felt that they were not adequately consulted or informed about planned outages

- 47 percent of respondents indicated that power quality was not adequate (low voltage and dips).

*

A separate survey was circulated to all distribution licensees (235 at that time) who were requested to provide data on network performance. The survey found that:

- the quality of information submitted varied drastically

- only 30.7 percent of distributors responded and since the data requested was based on “of the shelf” information, it was concluded that these performance data were not being collected

- of the data supplied on 26 percent could be described as of reasonable quality, in terms of completeness and accuracy

- 49 percent of respondents did not meet the minimum requirements for restoration of supply

- 45 percent of respondents failed to identify areas requiring corrective action and only 2 percent were able to indicate what corrective actions they were taking

- network performance in rural areas was found to be much worse than in urban areas

- a general lack of understanding of Power Quality and Performance issues was identified

- those who based their responses on estimations demonstrated that their network performance was deteriorating

- there was no common yardstick for measuring performance

- some utilities were storing performance data only for annual submissions to NER, thus losing the value of analysis and corrective action

- investigations on large power interruptions were being done or only done on NER request.<sup>39</sup>

The experience with supply interruptions in South Africa highlights the crucial role of the distribution system in the security and availability of supply to customers. In general, the higher voltage systems (EHV, 132 kV and transmission systems) have duplicate supplies so that most faults at these voltages do not result in an interruption of supply to customers. Almost all planned interruptions to supplies occur due to work on the LV and HV distribution networks. Especially the HV system can have a large impact on overall system performance because much of it does not have duplicate or alternative supplies and each fault can affect a large number of customers. And while each LV fault

> 39 This section is based on Balgobind, P.  2003. “National Summit on Maintenance of Electricity Distribution Networks”.  National Electricity Regulator. _Quarterly Journal_ 2(2): 3-7.

25
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to obtain jobs according to their qualifications.<sup>21</sup> In other words, in our counterfactual scenario every Venezuelan migrant earns the wages of native workers in the same province of residence with the same education level.<sup>22</sup> As discussed earlier, a policy that would help approximate this situation is to facilitate the registration of Venezuelan college degrees with the corresponding Ecuadoran agency.

Table 11 presents our findings (column 1). The top panel reports the estimated increase in GDP at the national level. Relative to the baseline value, GDP would increase by 1.9% if all migrants with tertiary education were able to transition to highly skilled jobs. More specifically, we estimated that Venezuelan migrants account for 0.4%, 2.4% and 4.9% of the primary, secondary and tertiary employment in Ecuador, respectively. Further, we found that the wages of Venezuelan workers are 37%-61% (Table 4) lower than the wages of Ecuadoran workers with the same education level and living in the same canton. Closing the migrant-native wage gap for each education group entails a substantial salary increase for the Venezuela-born workers (who account for 3% of Ecuador’s employment), resulting in an aggregate 1.9% increase in Ecuador’s GDP.

The bottom panel of the table shows the estimated GDP gains for the two provinces with the largest Venezuelan resident populations. Respectively, GDP in Pichincha (capital Quito) and Guayas (capital Guayaquil) is estimated to increase by 3.5% and 2.1%. These estimates are in line with the density of Venezuelan migrants in these provinces, which we estimated at 3.3% and 2.0%, respectively (Table 1).

# **6.2.2 Upgrading in Terms of Occupation**

As discussed earlier, it seems reasonable to assume that education levels in Venezuela and in Ecuador are comparable. However, this assessment was based on very limited data. This raises concerns about the realism of the previous simulation where we relied heavily on the comparability of the education levels across the two countries. This section performs an alternative simulation that avoids this issue altogether.

As documented earlier (Section 5.2), Venezuelan migrants in Ecuador have experienced substantial occupational downgrading, relative to their last occupations prior to emigrating from Venezuela. The EPEC data show that 12,255 Venezuelan migrants are employed as day laborers in Ecuador, one of the low-pay occupations. However, only

> 21We switch our geographic unit to Ecuador’s 24 provinces, as opposed to 221 cantons. This higher level of aggregation increases sample size and delivers more robust findings.

> 22We note that our simulation keeps relative wages across education levels constant. This is a reasonable assumption given that Venezuelan migrants are only around 2.9% of Ecuador’s employment.

18
as low as US$2335 and trade-GDP shares surging at 53 percent, below the leading MENA countries. However, a slightly different story emerges when comparing resources (minerals, gas, and oil) rents during 1991–1995: SSA countries dominated GDP shares of mineral rents at 0.84 percent, while MENA countries had larger GDP shares in gas rents (1.96 percent) and oil rents (19.33 percent).

Table 1: China’s WTO accession and it’s economic and trade implications in the developing world.

|Category|GDP growth<br>(%)|GDP per capita,<br>PPP(2011 US$)|Trade (%<br>of GDP)|Mineral<br>rents (% of<br>GDP)|Gas rents (%<br>of GDP)|<br>Oil rents (%<br>of GDP)|
|---|---|---|---|---|---|---|
|||**1991-19**|**95**||||
|Least developed countries|-0.08|1249|45.44|0.51|0.31|3.10|
|Low income|-2.10|1024|49.58|1.15|0.00|0.12|
|Middle East & North Africa|0.53|11303|65.86|0.03|1.96|19.33|
|Sub-Saharan Africa|-1.73|2335|53.29|0.84|0.15|5.42|
|||**1996-20**|**01**||||
|Least developed countries|2.15|1362|55.77|0.24|0.45|4.12|
|Low income|1.23|1059|51.21|0.39|0.00|0.20|
|Middle East & North Africa|2.04|12423|62.99|0.03|2.92|16.72|
|Sub-Saharan Africa|0.77|2365|62.85|0.36|0.31|6.39|
|||**2002-20**|**07**||||
|Least developed countries|3.44|1595|58.66|0.82|1.00|11.07|
|Low income|2.30|1148|62.41|0.96|0.29|1.66|
|Middle East & North Africa|3.46|14410|80.91|0.12|5.70|26.95|
|Sub-Saharan Africa|3.53|2699|64.25|1.05|0.88|11.15|
|||**2008-20**|**13**||||
|Least developed countries|2.50|1942|62.42|2.19|1.06|11.72|
|Low income|2.77|1374|65.32|2.84|0.31|1.63|
|Middle East & North Africa|1.38|16866|88.26|0.44|4.21|27.57|
|Sub-Saharan Africa|1.68|3151|65.28|2.26|0.67|11.65|

Source: Authors’ construction using World Development Indicators, World Bank 2014 The period from 1996 to 2001 saw two major patterns in the developing world. The first was positive increase in income growth and modest increases in both per capita income and trade shares with SSA countries experiencing a positive average increase of 0.77 percent in income growth, a mild 1.3 percent average increase in income per capita (from US$ 2335 during 1991–1995 to US$2365 during 1996–2001), and a 9.56 percent increase (from 53.29 percent to 62.85 percent) in trade-GDP shares. The second pattern was a significant decline in mineral rents (to 0.36 percent), a doubling of gas rents (to 0.31 percent), and a modest increase in oil rents (to 6.39 percent). As explained below, income, trade, and resource rents indicators improved considerably 5
(2014) designed an experiment where hiring authorities were given no information about candidates other than their appearance, and found that men were twice as likely to be hired for a mathematical task as women were. If ability was self-reported, women still suffered and the authors attribute this to the fact that employers may not fully account for men’s “tendency to boast about performance”. When full information about candidates’ past performance was provided, it reduced “discrimination” but did not eliminate it. The authors conclude that implicit stereotypes predict not only the initial bias in beliefs but also the “suboptimal updating of gender-related expectations when performance-related information comes from the subjects themselves” (Reuben 2014: 4403).

Occupation segregation based on caste represents an extreme form of institutionalized labor market discrimination. Caste is a system of social stratification prevalent in India and Nepal, as well as in other South Asian countries and is closely tied to norms (such as of purity and pollution) and in turn, to the life chances of individuals from lower castes. In short, the caste system is an occupational division of labor, canonized in an elaborate religious ideology. Sub-castes are assigned to specific occupations that also determine their social standing. Lower castes are thus restricted to menial, low paying and often socially stigmatized occupations while upper caste groups are concentrated in preferred occupations. This horizontal segregation results in workers from different social groups being ascribed into different occupations and jobs and being socially constrained from moving out. All these have an impact on the world-view of both privileged and underprivileged groups and spill into market interactions as well – most notably in labor market interactions. From an epistemological perspective, these characteristics set the caste system apart from other forms of stratification (such as gender or race) and their bearings on the labor market.

Using data from India, and comparing Scheduled Castes<sup>2</sup> and non-Scheduled Caste males, Das (2006) and Das and Dutta (2008) devise a notion of _“glass walls”_ where individuals historically assigned to certain occupations based on their caste, also face barriers to leaving

> 2 The term Scheduled Castes is used to refer to the erstwhile untouchables – lowest in the Indian caste hierarchy. After independence, the Indian Constitution abolished untouchability, and former untouchables came to be known in administrative and legal parlance as Scheduled Castes (SCs) through Constitution (Scheduled Castes) Order 1950.

8
psychologist). Oil-dependent economies tend to be subject to more power distance, avoidance of uncertainty and less individualism than diversified economies (see Figure 3.5).

Overall, oil-dependent economies tend to innovate much less than non-dependent economies. Indeed, a casual look suggests that natural resource dependent economies, not just those dependent on oil, spend far less on R&D (see Figure 3.6 and Figure 3.7). There is however substantial heterogeneity across economies.

But it is not only external factors (institutions that mediate interaction “between firms”) that explain differences in performance across resource economies; factors that relate to “within firm” governance are also important and have received little attention.

**Figure 3.5 Attitude toward innovation**

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It is well understood, as discussed above, that group differences within a community can be observed among a range of static and dynamic factors. But unless we can observe these differences, we have to rely on the ATE of our policy, which does not fully appreciate the unique costs and benefits felt by each group. For example, a defensive policy aimed at reducing domestic terrorism and violence may have significant distributional costs and benefits across the population and, therefore, relying on the ATE could overestimate the effects on some in the population but underestimate the effects on others. So, if one of our variables of interest was social dominance orientation (SDO) (intellectualized as an individual’s preference for inter-group hierarchies within a social system or group-based discrimination), we must capture the levels of SDO that exist across our population. We note here that individuals with high SDO are more likely to support public policies that promote or recreate social hierarchies, while people with low SDO favor more equality-based policies (Pratto et al., 1994). Of course, there are many other variables that we can use to study the heterogenous effects on such a policy, which allow us to separate individuals and groups within the population that are affected by the policy and thus allowing for a comprehensive understanding of the economic implications of our policy decisions. The question now is, how can we disaggregate the population according to the observed and sometimes unobserved differences?

# **_Quantile treatment effects_**

There exists a number of methods to capture heterogeneous effects. To capture such variation we outline, in what is a standard approach, the method used by Kristensen et al (Kristensen et al., 2017). The authors apply a method that, like us, attempts to monetize the economic benefits associated with an intervention. In addition, the authors clearly outline how they overcome the shortfalls of traditional CBAs, which focus exclusively on ATEs. In this study the authors employ a randomized control-trial experiment to examine the heterogenous impact of the Danish return-to-work program. The authors successfully demonstrate: (i) the benefits of estimating quantile treatment effects (QTE) (a well-established technique used widely in the social sciences and also included in a range of statistical programs<sup>9</sup> ); and (ii) the use of the efficiency potential (what we call potential efficiency gain) to assess the net benefits resulting from the reallocation of resources sensitive to the QTE. Kristensen and colleagues, based on their results, propose a screening system to triage participants in order to

> 9 See for example,  Frölich, M. and Melly, B. (2010). Estimation of quantile treatment effects with Stata. Stata Journal. 3:10, 423-357.

15