rafmacalaba/datause-encoder-data huggingface dataset:
diversification are, we would argue, due in no small part to its policy-driven transition program, and is unique in the region, insofar as rapid diversification is concerned.

Based on the Herfindahl, most of the export diversification achieved by Syria appears to be due to changes in its larger export sectors, with a decline in oil exports as the most likely driver.<sup>12</sup> As such, it is uncertain whether the moderate diversification levels achieved in 2006 and 2007 are likely to persist, especially if oil prices rise in the medium run.

The 78 percent decline in the Herfindahl-Hirschman is not, however, mirrored in the (aggregated) Theil index (which better tracks changes in the share of smaller export sectors); in fact, the latter increases rapidly from 2001, peaks in 2003, before declining to lower levels that are nonetheless higher than that in 2001. This suggests that, in the 2002/03 and 2004/06 periods, the rapid expansion of export varieties—as evidenced by the number of products—has been mostly skewed toward larger lines; equivalently, export diversification has been due less to new product discovery than export declines along the intensive margin. While part of this result may be an artifact of the degree of disaggregation—the Theil declines more systematically over the period when measured at the 2-digit level<sup>13</sup> —the results nonetheless suggest that substantial degrees of diversification have yet to be achieved in newly emerging export lines.

This result comes into sharper focus when examining concentrated indices corresponding to diversification within sections (columns 5–8). Herfindahls remain fairly stable over the period, with a mean of 0.32 (and standard deviation of 0.09). Theils within sections are similar to their values between all product lines—the correlation coefficient is 0.92—which imply once again that smaller export sectors are not responsible for export diversification patterns. Taken together, the relatively stable Herfindahl and varying Theil indices are indicative of the fact that the median sector’s exports are not due to the introduction of new products, but rather due to declines in traditional sectors occurring at a broader level in the economy.

Syria has also made some modest gains in terms of geographic diversification (columns 9–11). All three indicators corroborate the depiction of expanding export markets given by Figure 2, and suggest that diversification along the spatial dimension is reasonably healthy. It is useful to note, however, that export penetration remains relatively low in absolute terms; while penetration has grown almost fivefold between 2001 and 2007, it

> Herfindahls of 0.07 and 0.03, respectively, which are half to a fifth that of Syrian levels.

> 12Besides the 37.3 percent decline in Syrian oil exports as a share of GDP between 2001–2007, the composition of oil in exports fell from 77.4 to 37.9 percent over the same period.

> 13Specifically, Theil indices calculated at the 2-digit HS level fall by 19 percent between 2001 and 2007, although the rise-and-fall pattern is replicated as well at this level of aggregation.

13
46. A recent study for the Road Maintenance and Rehabilitation Project (Management Services for Rural Accessibility and Mobility Pilot Activity) in Malawi identifies that the choice of IMTs should take into consideration their appropriateness for specific tasks in rural communities, acceptability, availability, affordability in terms of cost (initial plus operating costs), and back-up and repair services.

- _“Appropriateness”_ refers to the goods and services they can carry for the rural farmer, appropriateness of the terrain (whether flat, rolling, hilly, mountainous), appropriateness of rural transport infrastructure (RTI) i.e. whether road, track or footpath.

- _“Acceptability”_ refers to how acceptable is the means of transport by the majority of the rural community.

- _“Availability”_ refers to how readily available are the supply or fabrication sources of the IMT. That is, can it be sourced or manufactured at some points in the rural setting or it has to be always manufactured from cities or manufactured locally. In some cases, shortage of supply can be overcome through training of artisans and establishing of workshop interventions to meet the supply bottlenecks.

- _“Back-up and Repair”_ refers to the potential for local maintenance/repair services and availability of reliable stocks of spare parts in the vicinity or neighboring villages, trading centers or district _Bomas_ .  It is essential that people have to be able to access maintenance facilities and spares without much difficulty. This involves amongst other interventions, issues of partnerships between artisans and private business people (local and semi-urban shops) regarding the stocking of back-up and repair supplies for the IMTs.

- “ _Affordability/cost (in terms of initial plus operational cost_ ) refers to ability to buy on cash basis by the rural households and what are the operational costs. In some cases, low purchasing power of IMTs by rural households can be overcome by providing mechanisms for a credit facility. This involves look into issues of whether establishing an appropriate credit facility would help in promoting ownership and use of IMTs.

47. The other criterion employed is how the IMTs reduce the travel and transport burden of women. The choice of the IMT will also be determined to some extent by the potential market and the marketing strategy to be deployed. How marketable is the IMT, are groups or individual able to use it and get opportunity to hire it out to help repay the loan. The IMTs have been examined for suitability for Ntchisi district based on the above-mentioned criteria.

- 21 -
The estimation results of hedonic regression models demonstrate that the JAIs—distance from CBD and share of accessible jobs by foot or minibus—are positively correlated with housing rents even after observed dwelling and neighborhood characteristics are controlled for. Monthly rents of housing units located 1 km closer to the CBD tend to be 1.4 percent higher than the other units with comparable characteristics (column 1). The relationship appears to be non-linear (column 2). In addition, the share of accessible jobs by foot is correlated with housing rents (columns 3 and 4). An additional 1 percentage point share of accessible jobs is related to 0.8 percent higher housing rents. Using the JAI calculated for different types of jobs (employers, employees, and own-account workers) does not substantially change the results (Table 5). Compared to the JAI based on foot, the share of accessible jobs by minibus is less clearly correlated with housing rents once observed characteristics are controlled for (columns 5 and 6). This is probably because minibuses are mainly accessible to neighborhoods with better quality of housing.

**Table 5. Estimation results of hedonic regression models with accessibility to different types of jobs**

||JAI<br>|=Share of ac<br>|cessible jobs<br>|by foot<br>Own-account|JAI=<br>|Share of acc<br>|essible jobs b<br>|y minibus<br>Own-account|
|---|---|---|---|---|---|---|---|---|
||All|Employer|Employee|worker|All|Employer|Employee|worker|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|JAI|0.008<sup>***</sup>|0.007<sup>***</sup>|0.008<sup>***</sup>|0.006<sup>**</sup>|-0.009<sup>*</sup>|-0.002|-0.009<sup>*</sup>|-0.011<sup>*</sup>|
||(0.002)|(0.002)|(0.002)|(0.003)|(0.004)<br>|(0.004)|(0.005)<br>|(0.007)|
|JAI squared|||||0.000<sup>**</sup>|0.000|0.000<sup>**</sup>|0.000|
||||||(0.000)|(0.000)|(0.000)|(0.000)|

_Note:_ Robust standard errors in parentheses.<sup>*</sup> _p_ < 0.1,<sup>**</sup> _p_ < 0.05,<sup>***</sup> _p_ < 0.01. Dependent variable is the natural logarithm of monthly housing rents.

Figure 7 visually illustrates the results. Without controlling for observed characteristics, housing rents are strongly correlated with the JAIs. Obviously, housing rents with better JAIs are higher not only due to the JAIs but also better structural and neighborhood quality. For example, the average monthly rents of housing located 2−3 km away from the CBD are 1.5 times as high as the average rents of units 6−7 km away from the CBD (panel A). The predicted rent curve over the distance from the CBD after controlling for observed characteristics is flatter but still positively correlated. Similarly, controlling for quality differences makes the predicted rent curve over the share of accessible jobs by foot in 60 minutes (panel B) flatter. In particular, rents become inelastic to the JAI between the 1 and 9 percentage point range, where informal dwellings are concentrated. In case of the minibus-based JAI (panel C), the result implies that housing rents with higher JAI have higher rents because they tend to have better quality.

16
And sometimes training centers aim to reduce the risk of a mistaken choice by arranging the training so that it begins by catering to a cluster of related occupations and then becomes progressively more occupation-specific, as in some apprenticeship schemes, allowing the trainee to defer a final commitment.

# Quality of training inputs

## Budgets

Irrespective of its merits on other grounds, a training mode cannot be expected to be cost-effective if any component of its budget is allowed to faLl below the threshold amount required to make it operational. As the survey of training institutions in the Middle East warns, "countries like Jordan and Egypt which have experimented with control of unit costs have discovered very clear trade-offs between quality of training and cheapness. While margins can indeed be cut to reduce costs, beyond a certain point, cuts quickly become counter-productive, impacting negatively on quality. For example, instructors working long shifts suffer a marked reduction in motivation, teaching standards may fall, the number of accidents increases, and student drop-out rates tend to increase. **.** A final, but crucial point, reinforced repeatedly during the Review is the need to maintain standards in this type of training. This is clearly an area in which there exists an absolute minimum of skill level, below which labor productivity (in a particular job) is unacceptably low. There is, therefore, an overwhelming need to preserve resources to ensure that graduates reach this critical standard. If cutting costs results in depression of quality of graduates beneath this critical level, the efforts to reduce unit costs become utterly self-defeating.' (World Bank, 1986).

Nevertheless it is common to find instances of unit expenditures being allowed to fall well below the critical minimum, and publicly-supported institutional training is especially vulnerable (Herschbach, 1985). An example is provided by the government-financed Industrial Training Institutes in India: in 1977 a government committee found that 21% of their graduates were unemployed, despite a widespread shortage of skilled workers in the appropriate trades, a fact ascribed to "the poor quality of education and training at some Industrial Training Institutes where tools and training materials have been reported lacking, along with inadequately qualified instructors' (Nigam, 1986).

The cause of this underfunding is not an overzealous desire to reduce unit costs as such--indeed it is unusual to find that the institution has calculated them--but a retrenchment in the budget forced by recession and a fall in public revenue or, on occasion, by a failure to make an accurate estimate of the recurrent cost in the first place. As Herschbach (1985) observes, donor agencies are sometimes partly to blame: "Although the host country bears direct responsibility for expanding programs without-sufficient resources, the donor agency generally does little to prevent the foreseeable consequences... Although many Third World countries cannot afford to take on any additional obligations, few of these countries resist donor assistance, and some actively seek it." 64 -

-
and the nutritional status of the child.<sup>6</sup> In regions in which agriculture is the dominant economic activity, food prices, through their effects on incomes and revenues for the state and local authorities, can also affect both the demand and provision of health, education and sanitation.

Studies examining the association between changing food prices and child nutritional outcomes are limited. Arndt _et al.,_ (2016) use household survey data and food price inflation rates to study the relationship between shifts in food prices and child nutrition status in Mozambique. Using propensity score matching, the study shows that nutrition measures (weight for height and weight for age) improve significantly when the inflation rate for food products is low. However, their analysis focuses on general price inflation and covers changes between quarters within one year and so does not allow for longer term impacts.

Torlesse, Kiess, and Bloem (2003) find that in the 1990s the price of rice was correlated with the percentage of underweight preschool children in rural Bangladesh. This seems to reflect a lack of substitution away from rice as the amount of rice consumed per capita did not change in response to price changes. As a result, household expenditure on rice varied with the fluctuations in price and less was spent on non-rice foods when rice expenditure increased. Expenditures on non-rice products were found to be negatively correlated with the percentage of underweight children.

Vellakkal _et al._ , (2015) investigate the association between food price hikes in the 2000s and child undernutrition in India. They first look at the association between changes in food prices and food consumption, and then the relation between these consumption changes and child nutrition. The study suggests that rising food prices were associated with an increased risk of undernutrition among children.

Miller and Urdinola (2011) investigate how child survival in Colombia responds to fluctuations in world coffee prices. They argue that the health of children depends on time consuming tasks such as breastfeeding, bringing clean water from far away or taking a child to a health clinic for primary care services or vaccinations. When coffee prices increase, workers spend more

> 6 Azzarri _et al_ (2014), for example, find a high elasticity of stunting to income in Mozambique. In addition to income, the most important factors correlated to chronic child undernutrition are mothers’ characteristics and fertility history, and parents’ human capital endowments. They conclude that improved income-generating opportunities are crucial for improving child nutritional status.

5
29 .

Having validated their model over the period 1973-77, Dervis and Robinson go on to ask in a set of cumulative experiments (where each new factor is added on to the previous one) what would have been the equilibrium real exchange rate, had Turkish inflation equaled OECD inflation, had external borrowing been equal to GDP growth, had there been no rise in oil prices or OECD export prices beyond the rise on world prices in Turkey's export markets, and had workers remittances grown at the same rate as GDP.

The results of the contribution of each element of this counterfactual history are reported in table 6. The exercise shows that differential inflation was only a small part of the story. Of course the mo~el structure

# Table 6

Factors Contributing to the Change in the Equilibrium Real Exchange Rate in 1977 (%)

|Differentialinflation|37|
|---|---|
|Oilpricerise|21<br>|
|HigherOECDexportprices|11|
|Lowerremittances|18|
|Otherfactors(residual)|13|
|100||

Source: Dervis and Robinson (1982, table 5) is imposed rather than tested and there certainly was interaction among some of the variables that were treated exogenously or feedback mechanisms from endogenous to exogenous variables. But it remains that in a world where economies undergo multiple exogenous shocks, partial equilibrium analysis or simplistic calculations are likely to be misleading.

> - ~ '.
# **Table A8: How much difference would this make for an investor taking a profit share in the top 100 firms?**

|||Model|Predictors|Non-Winners|Winners|
|---|---|---|---|---|---|
||1|OLS|Random|3,943,960|5,319,813|
||2|OLS|Application Score|4,958,110|8,774,139|
|Judges|3|OLS|Business Score|2,794,840|10,093,147|
||4|OLS|SubScore|3,631,660|4,904,253|
||5|OLS|Gender|3,832,820|9,852,094|
||6|OLS|Age|5,723,710|9,474,214|
|Sinle|7|OLS|Necessity Firm|2,971,470|7,216,015|
|g<br>Pdit|8|OLS|Grit|6,715,710|9,731,715|
|recor|9|OLS|Digit-span Recall|3,743,760|11,151,475|
||10|OLS|Raven Test|4,892,010|11,587,300|
||11|OLS|Registrationtime|4,308,850|6,969,259|
||12|OLS|McKenzie|5,008,910|10,140,434|
|EconomistModels|13|OLS|FaWo|6,395,860|22,344,000|
||14|OLS|FaWo+ BusScores|5,873,460|22,217,115|
||15|Post-LASSO|All|4,009,350|4,255,990|
|Machine-Learning|16|SVR|All|5,597,660|4,542,629|
||17|Boosting|All|5,494,360|7,152,821|

Notes: Profits in Nigerian Naira (1 Nigerian Naira equals around 0.0028 US$). For each model, we have taken the predicted profits computed in Table 5, sort firms in the test sample based on these predicted values, selected the top 20 firms (equivalent to around 10% of the test sample), summed the profits in these selected firms, and repeated this procedure for each of the 5 folds. We have reported the average total profits in the 5 folds. Models are estimating separately for competition non-winners and winners. Judges use scores from competition judges to predict the outcome. Single predictor models use a single survey measure. The economist models are the models of McKenzie (2015) and Fafchamps and Woodruff (2017) (abbreviated as FaWo) used in Tables 1-3. The three machine learning models are based on 393 predictors, along with interaction terms in the case of post-LASSO. All models include a dummy for whether the applicant was for an existing firm compared to a new firm, and models for winners also control for the total award received (in logs).
higher the inequality and the higher the incidence of low-and high-pay. It is the lowpaying jobs that are the focus of social policy. On the one hand, low-paid workers are preponderant among the working poor. On the other hand, for many low-productivity workers getting a job, even a low-paid job, is the only way to escape poverty. This is yet another reflection of ambiguity associated with earnings inequality that we have encountered earlier.

Quite surprisingly, the incidence of low-pay is relatively high in Lithuania, especially given its modest level of wage inequality. This reflects the fact that the earnings distribution in Lithuania is strongly positively skewed, i.e., has a short but "heavy" lower tail. As shown in Figure 2.3, the proportion of low paid jobs is high (this proportion is depicted as the area under the curve left to the first vertical line), however these jobs are not very much different (in money terms) from middle paying jobs (depicted as the area under the curve between the two vertical lines).

Specifically, defining low pay in a common way as earnings less than two-thirds of the median, we find that 23 percent of workers in Lithuania are in low-paid employment. This proportion is high by OECD standards, (although not by transition economies standards) and is higher than in countries with a comparable level of inequality. For comparison, the incidence of low-pay in the Czech Republic (a low inequality country) is around 16 percent, in Poland (moderate inequality country) is 18 - 19 percent, an in Latvia (relatively high inequality country) is over 26 percent. In most of the EU countries the incidence of low pay does not exceed 15 percent.

The bottom line is that there is a lot of low-paid jobs in Lithuania, but in relative terms they are only moderately, not extremely, low-paid. The implication of this is that wage flexibility is probably sufficient to provide jobs for less skilled workers skills, but it may be insufficient to provide jobs for workers with no or little skills, which are disproportionately represented among the unemployed.

60
# <u>2. Global inequality in the early 21</u><sup>st</sup> <u>century</u>

If we use the same decomposition between location and class today, when our data are much better than for the past, we find that of the global Gini, which amounts to 65.4 points, 56.2 Gini points or 85 percent is due to differences in mean country incomes, and only 9.2 Gini points (15 percent) to ―class‖.<sup>8</sup> Not only is the overall inequality between world citizens greater in the early 21<sup>st</sup> century than it was more than a century and a half ago, but its composition has entirely changed; from being an inequality determined in equal measures by class and location, it has become preponderantly an inequality determined by location only. This fact is of great political and economic significance.

Figure 1 helps us visualize this new reality. On its horizontal axis we draw the population of a given country divided into twenty equally-sized groups, called ventiles, each including 5% of the population, ranked by their average per capita incomes. Thus, value 1 on the horizontal axis corresponds to the poorest 5% of the population in a given country, and value 20, to the richest 5% of the population. On the vertical axis we show the global percentile position of each national ventile. The vertical height, corresponding for example to the bottom ventile in the US, is y=60 and it indicates that the poorest 5% of Americans have an income that places them at the 60<sup>th</sup> global percentile.<sup>9</sup> In other words, they are better-off than 60 percent of world population. The same interpretation applies to any other national ventile. Figure 1, using the example of BRIC countries (Brazil, Russia, India and China) and the US, illustrates vast differences in incomes which exist between countries, and in particular between the poorest ventiles of the population. While the poorest Americans are (as we have just seen) at the 60<sup>th</sup> global percentile, the poorest Brazilians and Indians are at the 3<sup>rd</sup> or 4<sup>th</sup> global percentile, that is among the poorest people on the planet. The poorest Chinese are around the 16<sup>th</sup> global percentile, the poorest Russians around the 37<sup>th</sup> percentile. Even more striking is the comparison of the income of the

> 8 All 2005 global data derived from nationally-representative household surveys conducted around year 2005 (see World Income Distribution (WYD) database available on http://econ.worldbank.org/projects/inequality).  In order to keep comparability with the precedent calculation for mid-19<sup>th</sup> century, I use price levels and PPPs that are commensurate with 1990 PPPs rather than the most recent version of PPPs  (year 2005). The latter gives an overall higher global inequality (70 Gini points rather than 65.4; see Milanovic 2011, and Milanovic 2012).  The share of the between-country component is also about 85 percent if we use more up-to-date PPPs.

> 9 The position of the poorest ventile of the rich country is indicated by a broken line in this and following graphs.

7