rafmacalaba/data-use-mentions-extended huggingface dataset:
and females.<sup>10</sup> The results are shown in table S.1 in the supplemental appendix. The baseline effects of basic schools on educational attainment and their effects on mobility are stronger and often more significant than those estimated in table 4 for both males and females.

A second concern is that Jordan received a large influx of Palestinian refugees in the aftermath of the 1967 Arab-Israeli War. While refugees benefited from the UNRWA basic schools, their educational attainment and intergenerational educational mobility were perhaps subject to a different set of constraints than those facing other Jordanians. Thus, as a robustness check, individuals who are likely to be Palestinian refugees were excluded from the sample. Since the JLMPS 2010 does not allow directly identifying Palestinian refugees who are now mostly Jordanian citizens, two indirect methods were employed to identify individuals who are likely to be Palestinian refugees. Method 1 excludes individuals born in subdistricts where the percentage of individuals who were ever enrolled (or are currently enrolled) in an UNRWA school exceeds ten percent out of all individuals below 36 years of age in the sample. Method 2 excludes individuals born in subdistricts where the percentage of UNRWA schools exceeds ten percent of the total number of schools. The results for the restricted sample according to both methods are shown in tables S.2 and S.3 respectively. Overall, the results remain unchanged from those in table 4.

A third concern is that the samples of males and females that are employed in the analysis may include adult siblings who belong to the same household. This could introduce intrahousehold serial correlation among these observations. Thus, as a robustness check, the sample is restricted to males and females who are household heads or their spouses, hence excluding adult

> 10. This results in excluding 381 “movers” among males and 371 “movers” among females, or roughly 9 percent of the original samples.

23
Policy Research Working Paper 9898

# **Abstract**

This study employs a synthetic panel approach based on nationally representative micro-level data to track poverty and income mobility in Malaysia in 2004–16. On aggregate, there were large reductions in chronic poverty and increases in persistent economic security, but those who remained poor in 2016 were increasingly likely to be poor in a structural sense. Further, the poverty and income dynamics differ notably across geographic dimensions. Such disparities are most striking when comparing affluent urban Peninsular Malaysia with poorer rural East Malaysia. Although there are important differences in welfare levels between the main ethnic groups in Malaysia, the mobility trends generally point in the same direction. While the findings show that there is still scope for poverty reduction through the reduction of interethnic inequalities, the study underscores the importance of taking regional inequalities into account to ensure a fairer distribution of socioeconomic opportunities for poor and vulnerable Malaysians. Hence, addressing chronic poverty is likely to require additional attention to less developed geographic areas, as a complement to the current policies that are largely ethnicity-based.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at g.rongen@aighd.org and zaliahmad@worldbank.org.

_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 views of the International Bank for Reconstruction and Development/World Bank and
Table 7: Components of Effort Index

|||Panel A||
|---|---|---|---|
||(1)|(2)|(3)|
|Dependent Variable:|Studied regularly|Tried to do well|Tried to get<br>better score|
|Goal-Setting|0.055|0.058|0.069*|
||(0.038)|(0.040)|(0.039)|
|Goal-Setting + Recognition|0.033|0.032|0.050|
||(0.040)|(0.043)|(0.044)|
|Observations|12,418|12,903|13,028|
|Baseline Outcome Controlled|No|No|No|
|||Panel B||
||(1)|(2)|(3)|
|Dependent Variable:|Participated in<br>class discussions|Prepared Lessons|Organized<br>school work|
|Goal-Setting|0.076**|0.046|0.056*|
||(0.034)|(0.034)|(0.032)|
|Goal-Setting + Recognition|0.056|0.000|0.012|
||(0.042)|(0.042)|(0.034)|
|Observations|12,601|11,902|12,490|
|Baseline Outcome Controlled|No|No|No|

_Notes_ : This table reports the result of estimating equation 1 on individual components of Effort Index. All the components are discussed in Section 2. Standard errors are clustered at the level of school. *p<0.1; **p<0.05; ***p<0.01.

23
Information on company affiliation with the<sup>top 30 chaebol is provided by the Korean Fair Trade</sup> Commission on an annual basis. We use<sup>group-affiliation data from the 1994-1997 lists of business</sup> groups. This is because the 1998 list contained<sup>a number of ownership changes, which would have</sup> biased our results. Several debt-ridden business<sup>groups were forced to sell bankrupt firms in 1997</sup> and 1998, which were in some cases subsumed<sup>into larger business groups and/or taken over by</sup> foreigners. A firm's openness to foreign investment<sup>is thus related to its membership at the time of</sup> divestiture. The list of chaebol is fairly<sup>robust from 1994 to 1997, with the same chaebol occupying</sup> the top 25 spots throughout the period. There<sup>was some variation among the bottom five chaebol,</sup> with three chaebol leaving the list by 1996 or 1997.<sup>In the interest of comprehensiveness, we follow</sup> all companies affiliated with the 33 chaebol<sup>that appear on the Korean Fair Trade Commission lists</sup> in 1994-1997.

# **5. The Pattern of FDI**

# **5.1. Mergers and Acquisitions**

The theoretical framework suggests that if<sup>technology transfer or access to local distribution net-</sup> works were important, then the industries<sup>of targets of foreign investment and the industries of</sup> foreign acquiring firms and domestic acquiring<sup>firms should be different. Figures 2 and 3 show the</sup> percentage of foreign and domestic transactions<sup>by target industry and parent industry, respec-</sup> tively. In general foreign investors target<sup>firms in similar industries to Korean firms. The simple
%|7%|6%|13%|

Note: Overall is the average of Brazil, Vietnam, and Senegal. Relative gap is the difference between Brazil and Senegal relative to the maximum technology gap (( _Brazil − Senegal_ ) _/MaximumGap_ (4)). For the columns on SSBF, the sample is restricted to the firms having sector-specific technologies. Technology measures are weighted by the sampling weights.

72
her developing<br>countries|
|Effectivepower tariff|Residential at 100 kWh|3.72||10.27|||
|Effective power tariff|Commercial at 100 kWh|4.88||11.73||5.0–10.0|
|Effective powertariff|Industrial at 50.000 kWh|4.88||11.39|||

_Source:_ Data for aggregates for low-income, middle-income, and fragile states based on data for 2005 unless indicated otherwise <u>(www.infrastructureafrica.org/tools/data). Data for access to electricity, installed and operational capacity, collection rate, and system losses</u> provided by World Bank specialists (2011). Data on revenue per unit, cost recovery, and hidden costs based on information from World Bank (2010a). Firms that find power to be a constraint taken from World Bank (2007b). Value lost and outages per year is from enterprise surveys and is from World Bank (2010b). _Note:_ kWh = kilowatt-hour; MW = megawatts Additionally, even though power availability has improved, service continues to be relatively unreliable, with growing recourse to emergency rentals to safeguard supply. Despite the steep growth in power production, World Bank investment climate surveys in 2007 reported that around 84 percent of firms experience power outages, lasting around 21 hours, on average 8 times a month. Large firms indicated a more acute problem, with at least 16 outages a month; the manufacturing sector overall was the worst affected. The problems were reportedly worse outside Luanda (World Bank 2007b). In 2010 results from the enterprise showed marginal improvement, with Angolan firms enduring a modestly better 6 outages a month lasting around 14 hours (World Bank 2010b). Overall 36 days were spent without electricity, twice the time endured by other resource-rich African countries.

Inadequate power supply is a huge impediment to private sector activity. In 2007 at least 68 percent of Angolan firms surveyed
# **2. Literature Review**

Our paper is related to three different strands of literature. <mark>First, we relate to studies analyzing changes in the demand for skills and employment due to ICT adoption. The available evidence is mainly focused on developed countries. These studies show that computers substitute for workers carrying out routine tasks, but complement workers carrying out activities difficult to automate, such as non-routine analytical and interpersonal tasks. A pattern of employment polarization emerges as a consequence of computerization, where low- and high-skilled occupations gain share in total employment at the expense of middle-skilled occupations. These studies include Acemoglu (1999), Autor et al. (2003), Acemoglu and Autor (2011), A</mark> utor and Dorn (2013) and Autor (2014) for the U.S., <mark>Goos and Manning (2007) for</mark> the United Kingdom, and <mark>Goos et al. (2014) and Michaels et al. (2014) for European countries more broadly.</mark> <mark>The evidence for developing countries is scarcer. Among the studies using household and labor force surveys or administrative data in developing countries, there is evidence that occupations using ICT more intensively have a high demand for cognitive skills and a low demand for routine and non-routine manual skills (Santos et al., 2015). Poole et al. (2017) find that technological change, as measured by the share of households connected to the internet, does not appear to be a main driver of the demand for skills in Vietnam. In a similar study, Poole and Santos-Paulino (2017) show that the adoption of computers by households in Vietnam is strongly associated with increases in the demand for non-routine manual tasks and routine cognitive tasks. Based on employer-employee data from Brazil, Almeida et al. (2017a) find that the rollout of the internet between 1996 and 2006 was associated with a reduction in employment and a fall in demand
_MACHINE LEARNING AND HIGH-FREQUENCY SURVEYS IN PAPUA NEW GUINEA 9_ need to be produced at each imputation step. For 20 food items, 8 iterations, and 5 imputations, the total number of models involved is 16,000, highlighting the need for fast model building.

# _C. Validation and optimization_

Since the food price data is incomplete, the true inflation of the food basket is never observed. This makes validation against true data particularly difficult. Cross-validation techniques are used to assess the predictive accuracy of the many individual price prediction models involved at the level of individual prices.

Since there are many food items (here _d ∈_ 1 _, ..., D_ ), each predicted by an ensemble of multiple models (here _m ∈_ 1 _, ..., M_ ), the robustness of the final estimate for the overall food basket imputation is summarized in a single score that summarizes the prediction accuracy of all models involved. First, a normalized MAE for the log price of food item _d_ is constructed as the ratio of the MAE of the model for that food item to the MAE obtained by a simple mean prediction. Since each MAE estimate represents an average point percent error rate due to the log nature of the price data, the individual MAE values are averaged geometrically.

where _MAE_<sup>�</sup> _m,d_ is a cross-validation estimate of MAE using the standard formula for MAE, _MAEd|μ_ ˆ is the MAE calculated using observed data and the sample estimate for the unconditional mean. Since the true data range is not observed, and averaging is known to improve ensemble performance, the quantity from equation 3 is likely a conservative estimate of true error.

� The focus next is on the quantity 1 _− NMAE_ , which is the share of the total absolute variation in the demeaned log price data explained by the imputation model. The _D_ values are averaged as follows.

where _Z_ is the Fischer Z-transformation and _Z_<sup>_−_1</sup
# **<u>1. Introduction</u>**

Youth employment is at the center of the policy agenda around the world. The 2013 World Development Report emphasizes that employment not only matters for individuals’ welfare, but also for social cohesion (World Bank, 2012a). The Arab Spring highlighted the dramatic consequences of high youth unemployment in countries such as Egypt or Tunisia. Throughout most of the Middle East and North Africa, youth unemployment rates are particularly high among university graduates, and policymakers often look for innovative and effective policies to facilitate the transition of youth from education to work (World Bank, 2012b).

In economies characterized by constrained labor demand from the private sector and high rates of youth unemployment, entrepreneurship-support interventions targeting students are promising policy options. Entrepreneurship training has the potential to enable graduates to gain skills and create their own jobs, as well as possibly also better align their skills with private employers’ needs. Some OECD countries are providing entrepreneurship education to university students (Oosterbeek et al., 2008). Yet despite the potential of entrepreneurship training, evidence on how such programs shape students’ skills and facilitate entry into self-employment remains thin.

Tunisia has long experienced high unemployment, particularly among new university graduates. For instance, 46 percent of graduates of the 2004 class were still unemployed eighteen months after graduation (MFPE and World Bank, 2009). Recent data show that graduates’ unemployment has been rising. Based on the Tunisian Labor Force Survey, unemployment among youth holding a university degree increased from 34 percent in 2005 to 56 percent in 2011. In this context, Tunisia has attempted various reforms aiming to promote employability or self-employment among university graduates. This paper presents results from a randomized control trial evaluating a unique reform: the introduction of an innovative entrepreneurship track in the university curriculum.

In 2009, Tunisia mainstreamed a new entrepreneurship track into the applied undergraduate ( _licence appliquée_ ) curriculum. Students enrolled in the last year of their _licence appliquée_ were invited to apply to the entrepreneurship
iow education, increase in themselves the probability to be unemployed), the presence of an unemployed household member reduces household welfare by 10-12 percent.'<sup>4</sup> A significant number of households in Eastern Europe have more than one unemployed member.

As one can expect, household size is negatively related to household welfare (since we defined the latter as household expenditure per equivalent adult). However, what is of interest is the role of household composition, as reflected in the magnitude of the coefficients for each type of household member. Except for Bulgaria, the strongest negative coefficient is found for the number of children. The implication is that households do not succeed in maintaining their welfare levels when the number of children increases-in spite of the generous social transfers in Eastern Europe and the presence of general entitlement programs such as the family allowances which are targeted on children. Given the positive correlation between household size and poverty, it may well be needed that child-oriented transfer programs move away from being general entitlements to being more poverty-targeted by paying larger amounts to poor families with children.

The pattern of the coefficients of the other demographic variables is country specific. With respect to age of the head of household, each of the three countries indicates an inverted-U life-cycle pattern with welfare levels rising over most of the adult

> _4_ One can assume that the effect is the most severe if the head of household is unemployed. Grootaert (1997a) contains some evidence to that effect for Hungary. Since the household head was defined as the main earner in the Poland and Hungary household surveys used for the HEIDE database, few heads of household are classified as unemployed for those countries.

60
3 climate reforms proposed by the coordinating ministry of economic affairs. These proposed changes, however, were put on hold in April 2006, after large demonstrations were organized by labor unions (Manning and Roesad, 2007).

Given the controversy surrounding severance pay in Indonesia, an analysis of survey data can impart important information on the performance of the current severance pay regulations. We exploit two household surveys that contain information on the receipt of severance pay following job separation: The Indonesian Family Life Survey (IFLS), which collected data on severance pay for the first time in 2007, and the National Labor Force Survey (Sakernas) which collected data on severance pay for the first time in 2008. These surveys provide a unique opportunity to conduct the first household-level analysis of severance pay in Indonesia, and to our knowledge, the developing world (Holzmann, et al, 2011).<sup>3</sup> The results show that compliance is low – only a third of workers entitled to severance pay report receiving it, and on average workers only collect 40 percent of the payment due to them. Eligible female and low-wage workers are least likely to report receiving payments. Widespread non-compliance is consistent with trends in employment rigidity, which essentially remained constant following the large increases in severance mandated by the 2003 law. Weak enforcement in practice suggests that workers may benefit from a compromise that relaxes severance pay regulations while establishing a system of unemployment benefits. Enforcement can also be improved by establishing an administrative entity dedicated to monitoring compliance with severance pay regulations can improve the existing system. Other countries with severance pay programs, such as Barbados and Slovenia, have established arrangements to oversee severance pay statutes.

The structure of the paper is as follows. In section two, we review the concerns of both the business community and employee representatives and present evidence on aggregate trends in labor market rigidity. Section three turns to the survey data, and demonstrates that not only are few workers eligibile for severance pay, but most eligible workers do not
-0.27|0.01|-0.40|
||||Total|0.86|0.81|1.24|0.68|1.47|0.67|0.89|1.23|0.59|
|Pakistan|2005 -<br>2014|LFS|Male|0.70|0.36|1.18|0.67|1.49|0.65|0.82|0.94|0.02|
||||Female|1.57|1.83|1.50|0.68|-0.41|0.78|1.36|4.07|1.28|
||||Total|0.21|0.09|0.17|0.15|n/a|-0.10|0.75|0.33|0.02|
|Sri Lanka|2001 -<br>2015|LFS|Male|0.16|0.06|0.12|0.04|n/a|-0.16|0.67|0.24|-0.29|
||||Female|0.31|0.13|0.23|0.52|n/a|-0.01|0.99|0.71|0.19|

**Note:** n/a: information not available. **Source:** South Asia Employment Dataset.

17
|Republika Srpska|||D+|A||D+|
|---|---|---|---|---|---|---|
|Kosovo|..|..|C|B|C+|A|
|North Macedonia|37|6|D|B|D+|C+|
|Montenegro|..|5|C|B|C+|D+|
|<br>Serbia|43|21|C|B|D+||

Sources: International Budget Partnership; Wang, Irwin, and Murara (2015); latest PEFAs.

# **These problems frustrate the effective implementation of fiscal rules:**

- The incomplete coverage of general government makes the rules less effective. It may also make future compliance with the EU’s fiscal rules more difficult than it may it first appear, since Eurostat will examine the coverage and may conclude that it should be broader than it currently is. Similarly, the absence of accrual accounts will make compliance with the EU’s accrual-based deficit more difficult—though there are procedures for estimating accrual deficits on the basis of cash data.

- There is too little information to show whether the letter of the fiscal rules has been followed only by violating their spirit. For example, have the rules been complied with only by allowing arrears and other accounts payable to accumulate? Or have they have been complied with only by moving public spending and borrowing to state-owned enterprises and other entities not included in the scope of the rules?

- Problems in forecasting and medium-term fiscal planning also make it harder for governments to comply with the rules and, if compliance is nevertheless achieved, may encourage abrupt rather than smooth adjustments.

# **V. PRINCIPLES TO GUIDE POLICY TOWARD FISCAL RULES**

**What principles should guide policy toward fiscal rules in the Western Balkans?** Although the evidence about the effectiveness
sup>20</sup> Unfortunately, the maps are not very disaggregated (ten by ten degrees in latitude and longitude). In principle, the flooding caused by any of the types of rainfall might have been picked up already by the localized flooding dataset. What would not be picked up is when rainfall in one place is transported by rivers or terrain to another place or when high tides push ocean water inland.

Given the focus here on riverine and coastal floods and to better pinpoint the locations that actually experienced riverine or coastal floods, the DFO flood maps were overlaid with the location of the rivers taken from the Hydroshed project (Lehner et al., 2008). Only the major rivers were mapped as these will have sufficiently large catchment areas exposing the downstream areas they traverse to (non‐localized) flooding. Riverine and coastal flood bands were then derived by considering DFO flooded areas within 2, 5 and 8 meters elevation difference from the closest point on the major river or the coast using a Digital Elevation Model from GLOBE (GloBe Task team, 1999).

The recorded riverine and coastal floods using bands of 2 m elevation difference for each year from 2001 to 2006 are in Figure 6. First, there is little overlap over the years between the localized and riverine flood maps, confirming the complementary nature of both flood indicators.

> 19 Because the construction of interpolated daily rainfall maps was very data and time intensive, interpolation was limited to the IDW technique only.

> 20 Many floods have now also been imaged by satellite or airborne sensors, and many of them have been translated by DFO into maps of inundation events.  Yet, as these satellite based maps did not cover all floods, partly because at times the images were obscured by cloud cover and partly because not all floods have been imaged, it was decided not to use this data source to ensure consistency.