rafmacalaba/datause-encoder-data huggingface dataset:
21 those that lack IRA but have PPI. The difference is more pronounced in electricity than in telecoms.

**Table 10 Quality vs. reform policies in 2002**

|||**(standard deviati**<br>|**Average**<br>**on, number of o**<br>|**bservations)**<br>||
|---|---|---|---|---|---|
||**1**|**2**|**3**|**4**|**5**|
||**No IRA**<br>**No PPI**|**With IRA**<br>**Without PPI**|**Without IRA**<br>**With PPI**|**With IRA**<br>**With PPI**|**All countries**|
|Power transmission<br>and distribution losses<br>(percent of output)|18<br>(13,33)|16<br>(10,21)|12<br>(8,2)|18<br>(10,29)|18<br>(11,85)|
|Telephone faults<br>(reported faults/100<br>mainlines)|63<br>(55,7)|41<br>(40,20)|39<br>(26,3)|32<br>(29,25)|40<br>(37,55)|

Source: Authors’ calculations using data from WDI. Note: For some indicators, coverage in 2002 is not as good as coverage for previous years. Thus, for some groups samples are too small to draw significant conclusions. IRA refers to the existence of an independent regulatory agency; PPI refers to the presence of private participation.

Overall, the basic data analysis implies that quality is improving over time in telecoms but not in electricity. Technology is probably a relevant factor. More surprising, perhaps, is the sense that reform policies do not seem to be related to quality improvements in electricity, whereas they do appear to be related to quality improvements in telecoms.

# **6.3 Econometric analysis**

The econometric work reported in Table 11 casts doubt on the conclusions reached from the basic data analysis. However, the diagnostics provided by the econometric analysis are not as reliable for quality as they were for access and affordability. For one thing, the coefficients for the regressions are much less robust—a consequence of the much weaker data coverage, in particular for electricity. Overall, the regressions yield poor results, and our model has a much lower explanatory power for quality than for the other two dimensions of performance. Only the income and the trend variables are significant for both sectors and for a few of the policy variables.

The marginal effects suggest that the creation of an IRA is associated with a statistically significant _deterioration_ in the quality indicators for both electricity and telecoms, and that PPI is not associated with any statistically significant effect on quality in either sector. These are two quite unexpected results. As mentioned earlier, two explanations are possible: (i) performance got worse or (ii) the measurement of actual performance improved with the creation of an independent auditor. In the second case, the apparent deterioration simply reflects better statistics; actual performance may even have improved.
18

**Table 6**

**Earnings Growth Across the Distribution**

||(1)<br>_Actual_|1988-1992<br>(2)<br>Conditional|(3)<br>Conditional<br>at 1988|(4)<br>_Actual_|1992-1998<br>(5)<br>Conditional|(6)<br>Conditional<br>at 1992|(7)<br>_Actual_|1988-1998<br>(8)<br>Conditional|(9)<br>Conditional<br>at 1988|
|---|---|---|---|---|---|---|---|---|---|
||||means|||means|||means|
|Q10|_-0.016_|-0.048|0.034|_0.254_|0.279|0.157|_0.238_|0.232|0.017|
|Q25|_0.037_|-0.040|0.030|_0.170_|0.231|0.157|_0.207_|0.191|0.033|
|Q50|_-0.057_|-0.063|0.027|_0.203_|0.209|0.192|_0.147_|0.146|0.022|
|Q75|_-0.093_|-0.091|0.025|_0.186_|0.186|0.229|_0.093_|0.095|0.003|
|Q90|_-0.214_|-0.115|0.021|_0.229_|0.171|0.257|_0.015_|0.056|-0.015|

Source: computed from results reported in Table 2.
A Duration Analysis of CONALEP

# **7. Conclusions**

The Mexican government introduced CONALEP as an alternative to traditional uppersecondary education in the form of a technical education system. A major transformation of CONALEP took place in 1991, when it reduced the number of courses of study offered from 146 to 29 and introduced modular courses, the forerunner of the competency based education and training model (CBET) now adopted in Mexico.

This paper evaluates the benefits of the introduction of modular courses by examining graduates from before and after the reforms. Results indicate that graduates from the pre-reform program (1994 Survey) had to search longer for a job compared with those of the post-reform program (1998 Survey). Moreover, graduates from the post-reform program have 45 percent higher probability of finding a job than those from the pre-reform program. However, the 1994 Survey cohorts earned higher hourly earnings than the 1998 Survey cohorts. A plausible explanation is that since 1994, real wages have decreased in Mexico by almost 40 percent.

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# _Concentration of financial asset holdings_

Just as the share of financial assets in the total increases with mean income across countries, the distribution of financial wealth within advanced economies appears to be more concentrated than nonfinancial nonhuman (and than human wealth or income; cf. Figure 1 for the US data). This may be less true in developing countries. For example, Indian survey data suggest that the share of financial in nonhuman wealth is not monotonically increasing in wealth (Subramanian and Jayaraj, 2006). The relatively undeveloped equity markets—limiting the availability of sophisticated financial claims on the local capital stock—the importance of land holding and the fact that most businesses are closely-held would be contributing factors to this difference. In China too, financial wealth as surveyed is _not_ more concentrated than other wealth (Li and Zhao, 2006); however, China’s status as a transition economy must be taken into account in considering the relevance of this observation for other countries.

Nevertheless, it is true for all countries that the bulk of financial assets is held by relatively wealthy households. Indeed, the bottom half of the wealth distribution in the USA holds no more than 3 percent of the system’s financial assets. The same group holds about 4 percent of the risk-free assets and 2 percent of the risky assets.

Given the fact that a much larger fraction of the population in poor countries holds no financial assets at all, and given that income is in most cases more unequally distributed in developing countries, it would seem likely that the share of financial assets held by the lower deciles would be even lower in the typical low or middle-income country. In other words, concentration of financial asset ownership is surely even higher in poor countries. This conjecture is not, however, strongly confirmed by the available survey data. In India—where the data on risk-free financial assets includes cash holdings – the bottom half of the wealth distribution hold about 6 percent of risk-free assets, and less than 3 percent of risky assets (shares). For three other countries, Ghana, Jamaica and Vietnam (Figure 3), in the absence of wealth deciles, we calculated mean savings balances for expenditure/consumption deciles. One expects a higher percentage of total savings held 9
# **4. Empirical Analysis**

# **_1. Effect of business-as-usual approach on labor reporting_**

To understand the effect of survey approach on labor reporting, we estimate the following equation separately for the samples of men and women aged 18-64: 1 + γ (1) iih 1iih iih yy = ∝ + ββ TT + εε Above, _i_ and _h_ represent individual and household, respectively; _y_ represents individuals’ labor outcomes (as presented in Table 2); and _α_ and _ɛ_ represent constant and error terms, respectively. 1 is a binary variable identifying the adults in the IHS4 sample, with the individuals in the IHPS constituting the comparison category. _D_ is a vector of individual and household attributes TT presented in Table 1 earlier to capture any remaining unobserved heterogeneity that may also jointly determine both the dependent variable and the likelihood of being selected for one survey versus the other.

The aim is to understand how the business-as-usual survey setting compares to the best-practice approach of conducting individual interviews with self-reporting respondents. For the binary outcome variables, Equation (1) is estimated as a linear probability model with probability weights adjusting for non-response.<sup>15</sup> For weekly hours across activities, and annual hours and earnings in wage and _ganyu_ , OLS regressions are run on the conditional sample of respondents (those who reported working in that activity over the relevant reference period).<sup>16</sup> Standard errors are clustered at the enumeration area level.

Based on equation (1), Tables 3 and 4 summarize the effect of the business-as-usual survey setting on the estimation of different labor statistics (for the full sample, and for men and women separately). On the whole, after controlling for demographic and survey characteristics, we find that the business-as-usual scenario (relative to the individual interviews) underestimates men’s and women’s participation in livestock, managing or working in an NFE, as well as wage employment for men. After controlling for demographic and survey characteristics, we find that the businessas-usual scenario significantly underestimates participation in the last 7 days in livestock, NFE management and supporting work (for both men and women), with weakly significant effects on wage employment for men. The effects are quite large, given participation rates in Table 2, and tend to be stronger for women. Among women, for example, Table 4 shows underreporting under the business-as-usual approach ranging from 3.2 percentage points for livestock (which, given mean participation for women in the IHS4, is a relative decrease of 20 percent); 3.9 percentage

> 15 The reported regression coefficients are qualitatively similar to the marginal effects derived from logit and probit regressions, which are available upon request.

> 16 Since the survey experiment/setting is exogenous, and we are focused on the conditional sample, we do not use a selection model in the analysis.

13
- **Data Governance: Privacy and Sharing.** Establishing data governance frameworks that safeguard individual data and privacy while expanding the development benefits of that data to many stakeholders is challenging. Frameworks for supervising and enforcing new laws with respect to data that are designed for developed economies may not transfer well to weaker institutional environments.

- **Ownership: Democratizing Data.** By crowd‐sourcing information to facilitate more responsive governance, and by giving citizens the ability to conduct their own surveys and analyze the data over large numbers of people, data can foster voice, government accountability, and transparency. Examples of such projects are underway in both India and Indonesia.<sup>105</sup>

- **Measures to Avoid Politicization of Data.** Personal data are now widely available and can be manipulated to further the private interests of firms leading to fears of “surveillance capitalism.” There is also a fear that governments will use individuals’ digital data to pursue political objectives, centralize power, and discourage dissent.<sup>106</sup> This calls for data governance frameworks to safeguard privacy, and give citizens more control over the use of their personal data.

- **Making Traditional and New Data Work Together.** Most new data are generated by individuals through their interactions on mobile devices and computers. In some places, the digital user population may approximate the overall population. In other contexts, including many developing countries, large swaths of the population who are not digitally connected will not be reflected. Data collected via traditional methods, which sample the entire population, can speak to the validity of, for example, poverty maps generated using digital data, and help identify which sub‐ populations are systematically under‐represented in these applications.

> 105 Yuen Yuen Ang (2019), _Integrating Big Data and Thick Data to Transform Public Service Delivery_ ,” IBM Center for Business and Government.

> 106 Shoshana Zuboff, “Big Other: Surveillance Capitalism and the Prospects of an Information Civilization,” Journal of Information Technology 30 (1) (2015): 75 – 89; and Dirk Helbing, Bruno S. Frey, Gerd Gigerenzer, et al., “Will Democracy Survive Big Data and Artificial Intelligence?” Scientific American, February 25, 2017.

32
left panel of Figure 2 illustrates, as of 2021, the average number of leave days for mothers is the third highest in this region.

Turning to the right panel of Figure 2, several facts are immediately clear. Firstly, noting that the scale on the right panel is much lower than that on the left, we can see that the total number of leave days available to fathers is only a fraction of that which is available to mothers in all regions. Secondly, it is also clear that, with the exception of OECD high-income economies, progress in allocating more leave to fathers upon the birth of a child has been very slow over time. Indeed, globally, the average number of leave days for fathers increased by fewer than 20 days over the 52-year period (the median has increased by two days). In 1970—the first year of data—only 13 of the 190 countries covered in the dataset had policies in place granting leave to fathers after the birth of a child. The third fact highlighted by the right panel of Figure 2 is that, over the past five decades, OECD high-income economies have made significant progress in increasing leave allocation to fathers. While in 1970, the average number of leave days for fathers in OECD high-income economies was less than half a day (with a median of zero); by 2021, this had increased to an average of 83.7 days (median equal to 45.5 days). In contrast, the progress was significantly slower in other regions. As of 2021, the Europe and Central Asia and East Asia Pacific regions have the second and third highest allocation of leave to fathers but, at an average of only 11 days (and a median of 2.5 and zero days, respectively), these regions are still far behind the OECD average.

Progress in granting additional leave days to fathers has been particularly slow in countries in the Middle East and North Africa and in Sub-Saharan Africa, where the average number of leave days granted to fathers in 2021 were two days and 2.7 days, respectively (median of zero days and one day, respectively). Of the 19 countries in the Middle East and North Africa region, parental leave is, according to 2021 data, most generous in Iran at 14 days, followed by the United Arab Emirates at seven days. Ten countries in the region do not have legislation in place granting any leave to fathers upon the birth of a child. The stark difference in leave allocation to mothers and fathers in the Middle East and North Africa region is highlighted in Figure 3 below. This graph shows, sorted by largest to smallest, the leave allocation to mothers in 2021. It also illustrates fathers’ leave day allocation, as a fraction of what mothers receive.
In econometric analysis (nor reported for brevity), we find that investment growth had a sharper correction in India, and picked up in the years when government expenditure grew, which is indicative of a boost through public rather than private investment. While credit to the private sector as a percent of GDP remained resilient to the GFC in the initial years after the crisis, it has since declined, and the growth rate of private sector credit has been consistently lower than in comparator countries. Interestingly, as credit growth slowed in other countries in 2008 itself, in India it remained high until later. As we discuss below, export growth slowed in India, due to the global slowdown in trade, and India’s decreasing share in world exports.<sup>25</sup>

# **Figure 9: India grew faster prior to the GFC, and the correction was sharper after the GFC**

9 A: GDP growth was far more rapid in India prior to the GFC 9 B: Investment growth in India outpaced growth in the EM7 before the GFC, and the correction was sharper...

<!-- Start of picture text --> 12 30<br>10 25<br>8 20<br>6 15<br>4 10<br>2 5<br>0 0<br>-2 -5<br>-4 -10<br>GDP Growth (India) Investment Growth (India)<br>GDP Growth (Median of EM7) Investment Growth (Median of EM7)<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br><!-- End of picture text --> 9 C: ...as was also the case with credit growth 9 D: ...and growth of exports

> 25 Some features of the economy during this period look similar to those pointed out in the literature as being associated with a credit boom, surge in capital flows and in investment levels. A significant percentage of such episodes result in growth slowdown (see for example, Dell’Ariccia et al. 2011).

19
# **Policy Preferences in Response to Large Migration Inflows**<sup>*</sup>

William Allen University of Oxford william.allen@politics.ox.ac.uk Isabel Ruiz University of Oxford isabel.ruiz@bsg.ox.ac.uk Carlos Vargas-Silva University of Oxford

- & Peace Research Institute of Oslo (PRIO) carlos.vargas-silva@compas.ox.ac.uk

**Keywords:** Policy preferences, migration, humanitarianism, conjoint experiment, Venezuela, Colombia.

**JEL Codes:** F22, F51, J61, J68

> * <mark>This paper was commissioned by the World Bank Social Sustainability and Inclusion Global Practice as part of the activity “Preventing Social Conflict and Promoting Social Cohesion in Forced Displacement Contexts.” The activity is task managed by Audrey Sacks and Susan Wong with assistance from Stephen Winkler. This work is part of the program “Building the Evidence on Protracted Forced Displacement: A Multi-Stakeholder Partnership''. The program is funded by UK aid from the United Kingdom's Foreign, Commonwealth and Development Office (FCDO), it is managed by the World Bank Group (WBG) and was established in partnership with the United Nations High Commissioner for Refugees (UNHCR). The scope of the program is to expand the global knowledge on forced displacement by funding quality research and disseminating results for the use of practitioners and policy makers. This work does not necessarily reflect the views of FCDO, the WBG or UNHCR.</mark>
social and economic characteristics such as educational attainment, occupation, and region, which provides us with an excellent opportunity to look into the issue of migration into towns and its determinant and consequence.<sup>2</sup> Specifically, we focus on three issues: (1) Does migration into towns stall? (2) Has development in town absorbed more educated people? Do these in-migrants in towns come locally or from other provinces? (3) What is the consequence of in-migration on labor market in towns? Does labor market in towns become more flexible to accommodate highly skilled labor or labor market remains segregated between migrants and non-migrants?

The paper is organized as follows. In the next section, we briefly discuss policy on town migration and provide an overall view of town in-migration in China. Then, we discuss population composition, employment opportunities and other economic conditions in towns in three provinces and patterns of town in migration. It is followed by examining the in-migrants’ differentials in education and the impact of in-migration on town labor market. The paper is concluded with a summary and some policy recommendations.

# **2. Brief view on town migration in China**

Migration used to be an area of heavy state control, and conventional _hukou_ system classifies all the people as either “agricultural population” or “non-agricultural population”. The conversion from the one status to another was subject to strict quota controls. With market reforms in 1978, tremendous non-agriculture employment opportunities have been created in town and village enterprises (TVEs), attracting large migrants form rural areas. Grains and almost all kinds of commodities have been available from markets at reasonable prices, which essentially enabled people to choose where to work and reside despite their _hukou_ status.

The migration policy became increasingly flexible as reforms proceeded (Chan 2001). A “self-supplied food grain” _hukou_ , a new type of urban _hukou_ in rural market towns, was issued to farmers who ran business or undertook industrial or commercial activities in rural market towns. Later, a more formal urban _hukou_ was issued to those people who had stable non-agricultural jobs and accommodations in selected cities and designated towns. Thus, a more flexible migration policy could have facilitated migration into towns.

Data on national migration flows (Table 1) tend to speak for the possible impacts of migration policy and development of TVE. It shows that the migration into towns was at its highest during the period of 1982-87; of total migration population, about 40% of them went to the towns. This was probably due to booming of TVEs in the rural towns in the late 1970s and earlier 1980s. The in-migration into towns started to diminish since

> 2 In the time of completing this paper, author does not have access to the 1 per 1,000 micro-data set of long form questionnaire, and will do more empirical testing whenever data are available.

3
# **II.B. What Is Causing a Possible Reversal?**

**Technology:** There are two reasons one might suspect that the slowdown of trade (as percent of GDP) since the financial crisis could be technologically driven.

The first reason is that the fragmentation of production underlying the expansion of global value chains (GVCs) and trade would eventually reach its technological limit. In fact, some have viewed the decline of trade in intermediates (evident in Figure 2) as evidence that the fragmentation of production has run its course. However, as Goldberg (2019) argues, this evidence is far from conclusive. Apart from the fact that the decline in intermediates trade is too small to support such a conjecture, the _value_ of trade in intermediates is influenced by several factors, including commodity prices. An alternative measure of fragmentation that is more closely associated with GVC trade, the share of parts and components in _volume_ terms in manufacturing trade, has increased at a moderate pace since the 1990s and has not shown any signs of reversal since the global crisis. Accordingly, the evidence on this point is mixed.

The second argument is that recent technological advances, e.g., automation, 3D, now favor reshoring of economic activity, as the production process relies less on low-skill labor than in the past. However, this argument does not withstand scrutiny for three reasons.

First, as the WDR 2020 showed, recent technological advances also create additional scope for trade. Indeed, the evidence to date suggests that those sectors most affected by automation (e.g., the automobile industry) expanded intermediate product imports, especially from developing countries, as the scale of production increased.

Second, as Antràs (2021) has argued, the presence of sunk costs in foreign investments implies that reshoring is not symmetric to offshoring; even if the incentives to produce abroad may not be as strong today as they were in the 1990s, GVCs will not abandon their activities in other countries given that the large sunk costs they have incurred in the past.

Finally, it is conceivable that the advances in modern technology, especially in information and communication technology, lead us in the opposite direction, fostering another wave of globalization, this time driven by trade in services. The increase in remote work and internet-based services and commerce during COVID have contributed to this trend. However, 14
Property Rights in a Very Poor Country: Tenure Insecurity and Investment in Ethiopia Daniel Ayalew Ali* Stefan Dercon** Madhur Gautam*

*The World Bank **University of Oxford *The World Bank

Keywords: property rights, investment, agriculture, Ethiopia, Africa JEL classification: O17, O13, Q15 Corresponding author: Daniel Ayalew Ali, <u>dali1@worldbank.org</u>