rafmacalaba/datause-encoder-data huggingface dataset:
# TABLE 4B

# TOTAL EXTERNAL SHOCKS

||1981-84<br>Relative<br>to 1970-80|1985-88 Relative<br>to 1970-80|1985-88<br>Relative<br>to 1981-84|
|---|---|---|---|
|EIAL<br>average|-12.4|-9.2<br>|0.9<br>|
|Median|-13.6|-10.1<br>|0.7<br>|
|,St<br>quartile|-17.1|-13.3|-2.3<br>|
|3 <sup>rd quartile</sup>|-8.9|-3.3|3.4|
|CAL<br>average|-4.9|-7.0|-1.0<br>|
|Median|-6.3|-6.9<br>|-1.5<br>|
|]st<br>quartile|-16.8|-13.1<br>|-5.2<br>|
|3 <sup>rd quartile</sup>|-1.9|0.5|2.1|
|NAIL average|-11.6|-15.9|-3.6<br>|
|Median|-10.8|-11.2|-1.6|
|rSd quartile|-20.6|-25.0|-7.1<br>|
|3<sup>r</sup><br>quartile|-2.1|-5.2|0.0|

Source: *orld Bank **data,**

**Note:** _The_ total **effoct** of the **external** shocks **as a** X of CDP **is** computed **as** tho **sum** of **the real** interest **rate s^a** te-.s of trade *ffects. **The** ;nterest rate effect **is** calculated **ae** -(r-rb,Se)*(debt/COP)b* 9<sup>, whern</sup> r **iS** the **reoal** --. eest **rate** computed **as** (i-dp/p)/(l-dp/p); rrbs **is the averago** real intorest **rete** in **base** poriod (1975-80); (198 -84. is **the** ratio of interest **peyments** to tote1 **debt;** interest payments **are** calculated by adding public and privste -te-est payments; **privste** interest **payments are** proxied by multiplying private debt by L (L oquolo three-month annualized .:39R plIQ 1%); private debt **is estimated** by subtracting public and publicly guaranteed debt from totol debt; _dp,p_ S 'world' inflation (proxied by **the percentage** change in the CNP deflator of **the** US, end (debt/gdp)bl 9 ie **the** aSt o _6f_ debt to GOP in the **year** preceding **the** beginning of tho and period. **The** debt **data** correspond to total d sb..sed guaranteed and non-guerenteed debt. Oebt and **interest** rate informaeion **is avsi lable** starting in 1975 only. Yhsefo e **the** average for the period 1970-80 is ***etimated** using information for **the** period 1976-80. **Tie** effect of the **terms** of **trade is** computed **as** ((PX/PXbaa )- **)C(X/GOP)b4** -((PM/pMb **se)-)*(W/CDP)beg,** wh **vs** Px I'd P4 **are** the **everage** export **and** import **price** indices **deflate** by the US **CNI9** deflator, respectively; PXb4se sd oase **a-a** the **evorage** price indices of **the** base period, X **and** M **are** exports **and** imports of GNFS; **and** (X/COP)b.n **and** (Wi/ZP p a,o **the ratios** of X **and** W to COP respectively **at the** year preceding the 6.ginning of the **end** period. A I th **oa** . *s9 **a-e** denominsted in current US **dollars.**

. **5,** _,005_ **3*** }.i
school time, community participation) is not possible since participation in those sub-components was either universal or voluntary, which causes identi...cation problems that we cannot solve with the data available. Nevertheless, in this section we use estimates of costing data from ANEP to try to shed some light on the cost and bene...t implications of an expansion of the program.

According to ANEP, FTS have on average 50 percent more recurrent costs (excluding teacher training) than regular urban schools,<sup>8</sup> mostly due to the increase in the cost of teacher salaries, which explains 71.2 percent of the di¤erence in costs. Nutrition interventions account for an additional 19 percent, while the remaining cost increase is accounted for by the extra-curricular activities that are associated with the implementation of the new padagogical approach in FTS schools. If we also include teacher training in the costing, FTS turn out to cost 60 percent more than the average regular urban schools. Assessing whether the increase in learning compensates this extra cost requires some degree of subjectivity, given the analysis we are able to perform. However, it is important to note the following: First, even though FTS are more expensive to run than regular urban schools, this does not necessarily imply that they are too expensive. On the contrary, it may indicate underspending in the rest of the education system. In fact, by international comparisons, Uruguay underspends in the education sector given its level of income. The average per-student expenditure in primary and secondary schools is 7.2 percent of GDP per capita, well below the regional average of 13.1 percent.<sup>9</sup> Thus, the additional cost of FTS, while substantial when compared the cost of regular urban schools, would only bring Uruguay closer to the regional average. This by no means means that the program should be scaled up universally, but provides a relative measure of the increase in costs from the program. The second important point is that the program has a large e¤ect in schools with students from very disadvantaged backgrounds. These are the students for whom the bene...t of a marginal increase in learning would be the largest, assuming that this increase in learning results in a higher probability of completing secondary and post-secondary education. Thus, e¢ ciency and equity arguments would recommend a targeting mechanism that ensures that the participating schools serve disadvantaged populations.

# 7 Conclusions

Our preferred estimates show that the full-time school program increased student test scores in third grade by 0.063 standard deviations per year in mathematics and 0.044 standard deviations

> 8 MCAEP ANEP, "Estimacion del gasto por alumno en Educación Primaria Pública y costos comparados de la educacion comun y de tiempo completo". These estimates control for the size of the school.

> 9 Source: The World Bank (SIMA) and EdStats, 2004.

22
74 RENT CONTROL IN KUMASI, GHANA Any renter opposing the landlord and seeking satisfaction from the Rent and Housing Committee may win his case but would find that the provision in the rent laws allowing eviction in order to accommodate the owner's family members would nullify his pyrrhic victory.

Wnile advances are and were growing in amount and frequency, they were not sufficiently widespread in 1986 to have much effect on rents in the aggregate. Table 5.2 presents the comparisor, of net and gross rents. While it doesn't make much difference with the 1986 sample, we will henceforth work with gross rents.

Table 5.2: Gross and Net Rents Compared

||Net<br>Rent<br>(cedis)|Net Rent to<br>Consumption|Gross<br>Rent|Gross Rent to<br>Consumption|
|---|---|---|---|---|
|Units<br>Pavinx<br>Some Advance|||||
|Median|300|.04|318|.04|
|N|105|105|**105**|105|
|**All.**Units|||||
|Median|300|.02|300|.02|
|N|**754**|722|754|722|

Note: Unvei 6 hted statistics, government and high cost units omitted.

# C. PcQc: Current Rent Paid

The first piece of information, the rent currently paid in the controlled unit, PcQc, is directly available from the sample survey. Again, to improve comparability, government and high cost units are omitted from the sample. The distribution of gross rents paid in the two remaining (arnd largest) sectors Is presented in Table 5.3 and corresponding Figure 5.3.11

- 12/ In Figure 5.3, as in similar figures below, the first and third quartiles of each variable are represented by the top and bottom 'ticks" or horizontal line; the median by the middle tick.
||InSch<br>|ool<br>|OutofSc<br>|hool<br>|
|---|---|---|---|---|
||Meanor Pct.|Std.Dev.|Meanor Pct.|Std.Dev.|
|School/Work Status:<br>school only|0.88||||
|both school and work<br>work only|0.12||0.15||
|neither work nor school|||0.85||
|Worked past 12 months|0.27||0.47||
|Girl|0.54||0.36||
|Age|15.11|1.71|16.38|1.65|
|Race: non-white|0.56||0.56||
|Suffered hunger|0.17||0.36||
|Dependent children (y/n)|0.04||0.30||
|Ideal age first sex|17.89|3.28|17.29|2.55|
|Ideal age first sex <=17 years old|0.38||0.45||
|Monthly reservation wage (BRL)|215.72|118.39|253.25|129.35|
|Father's schooling >=interm. compl.|0.06||0.08||
|Father's schooling >=interm. compl.|0.06||0.09||
|Schooling teenager:|||||
|elementary inc.|0.68||0.73||
|elementary compl.|0.09||0.09||
|intermediate inc.|0.21||0.05||
|intermediate compl.|0.02||0.13||
|N|<br>364||78||

Table 1 - Comparison of teenagers in school and those out of school. Source: Own calculations based on World Bank, Fortaleza Survey 2003 The issue is therefore: What distinguishes teenagers who are in school from those who have dropped out? Table 1 reports the comparison. As suggested by the previous graphs, girls are less represented among those out of school; older teens are more likely to have dropped out. In terms of race, no differences are apparent. Two remarkable differences stand out. Over one-third of the youngsters out of school declare to have suffered hunger at some point in their lives, compared to 17 percent for those in school. Also, almost one-third of those out of school have had children themselves, which compares to 4 percent for the teenagers attending school. When asked which age they considered as the ideal one to first have sexual relationships, almost half the teenagers out of school declared an age below or at 17 years old; 38 percent of those in school shared that benchmark. Even though the share of teenagers currently working is not very different across the groups in- and out-of-school, a larger share of those out of school has worked at some point during the past year.

10
by five sub-dimensions (income generated by work, occupational status, tenure, social security affiliation, and excessive working hours). Consistent with the findings of Brummund et al. (2018), they observe that Chile, Uruguay, and Brazil outperform their regional peers. Furthermore, they identify a gender gap in employment quality across all countries in their study, particularly in the dimensions of income and tenure. Similarly, Apablaza et al. (2021) employ a similar method to evaluate employment quality across regions in Chile between 1996 and 2017. Their results highlight the heterogeneity of job quality across the country but also indicate a process of convergence driven by minimum wage regulations and the statutory working week.

Another set of studies has developed job quality indices using alternative methodologies. For example, Del Carpio et al. (2017) examine the dynamics of job quality in Turkey between 2009 and 2016. The authors define various components related to job quality and employ the principal component analysis (PCA) method to aggregate them into a composite index. Their findings reveal an improvement in the quality of wage employment at the aggregate level over the specified period. These improvements are largely attributed to a shift towards more formal wage jobs. However, the authors also observe a wide distribution of employment quality across Turkey.

Closely related is a study conducted by Ya ̃nez (2018), which examines the evolution of job quality in Bolivia from 2006 to 2015. The author employs the National Household Surveys as the primary dataset and constructs a job quality index using the fuzzy sets theory developed by Zadeh (1965).<sup>5</sup> The index incorporates variables such as labor income, weekly hours worked, unemployment, number of jobs, contract availability and tenure.<sup>6</sup> The findings indicate that the index witnessed a modest increase of approximately 0.7 percent over the decade, which is lower than anticipated given the commodity boom period. Consistent with other research, the study highlights the presence of a gender gap in employment quality, as well as a widening disparity in job quality between urban and rural areas.<sup>7</sup> The most recent contribution to the literature, Hovhannisyan et al. (2022 _a_ ), aims at measuring job quality with a global view, using a harmonized dataset for 40 developing countries and across four dimensions: sufficient income, access to employment benefits, job stability, and adequate working conditions. Employing the Alkire and Foster framework, it

> 5The Fuzzy Sets theory had been traditionally used to construct a multidimensional poverty index. Lelli (2001) provides a solid review and comparison between factor analysis and the use of fuzzy sets.

> 6The social security benefits and workplace variables are also included as components of the index.

> 7We replicate the model presented by Ya ̃nez (2018) using the Bolivian household surveys. Similarly, we also find a steadiness of the job quality index based on the fuzzy sets theory.

5
mortgage debt as rapidly as possible. In recent years, the household debt-to-GDP ratio for European accession countries was 12 percent, Thailand’s was 29 percent, those of Hong Kong, South Korea and Malaysia, ranged between 60 and 65 percent, and the U.S. rose to 107 percent (Fitch, 2007, BIS, 2008, Coricelli, et al, 2008). Thirty-nine percent of Thailand’s Government Housing Bank mortgage borrowers are civil servants, and 50 percent are employed in the formal private sector (Fitch, 2007). Partial prepayments in Colombia in the early part of the 2000s ran at 8 percent per year, as consumers sought to retire inflation-indexed mortgages as quickly as possible.<sup>49</sup>

- Given the overall lack of access to credit, and the relatively high cost of registering and enforcing a mortgage lien, emerging market banks have been slow to move down market with mortgages. Mortgage lending is typically less than 20 percent of GDP in emerging markets, while it ranges between 40 and 100 percent of GDP in developed countries. (Chart 5.)

- Mortgage credit in emerging markets carries relatively low LTVs and short maturities. LTVs in China, Hong Kong, Indonesia, and Korea range between 70 and 80 percent (Zhu, 2006). LTVs at origination in Mexico range between 60 to 80 percent and only recently were permitted to rise to 90 percent.<sup>50</sup> Loan maturities for nominal local currency loans in Mexico, Peru, and China run typically between 10 and 15 years.<sup>51</sup>

- Since the macroeconomic crises of the late 1990s, low interest rates, low inflation, and financial sector reforms have caused mortgage default rates to fall dramatically. In Thailand, NPLs on housing loans dropped from 30 percent in 2000 to 7.6 percent at the end of 2006 (Fitch, 2007).  Default rates in Mexico fell from 33 percent in 1998 to 3.2 percent in 2005 (BBVA, 2008). In India, 90 day delinquency rates range between 2.7 and 6.8 percent, as a function of the LTV ratio (Government Housing Bank).

- Many emerging mortgage markets lack long term funding tools such as covered bonds and securitization that permit lenders to extend the maturity of their loans. In East Asia, the first MBS were issued in China, Hong Kong, and Singapore within the past four years (BIS, 2006). Within Latin America, active large scale mortgage securitization markets have emerged only in Mexico, Colombia, and Chile (BBVA, 2008), and only Chile has a widespread covered bond market.

> 49 Source: Author interviews with Titularizadora Colombiana. 50 Source: Author interviews with Sociedad Hipotecaria Federal.

> 51

> In the case of Mexico and Peru, this refers to loans without inflation indexing.

31
governance attributes and three informal (practice/process) attributes. This is shown in the reformulated version of the key summary table of the report shown below<sup>22</sup> .

**_The key point to note in Table 2 is that, with the exception of Indian gas and telecoms, all the scores on the informal attributes of regulatory governance are lower than the scores for the formal, legal attributes._** The scores for transparency are particularly low.

It is also worth recognizing:

- (i) _In retrospect, the NERA 1998 survey over-estimated achievements in developing effective regulatory frameworks in practice in the Asian countries considered_<sup>_23_</sup> .

The scores on the three informal accountability attributes would have been significantly reduced for the highest marked sectors if the study had been carried out 1-2 years later. This applies to Orissa electricity, Indian telecoms and (particularly) Pakistan electricity, the main apparent successes as seen in 1997-8. In retrospect, for all three cases, and particularly Pakistan electricity, too much weight was given in the survey to stated plans for the establishment and enhancement of regulation rather than to actual achievements. This shows the inherent risks of optimism bias in even the best surveys.

- (ii) _In retrospect, the degree to which the NERA survey captured aspects of regulatory practice was relatively limited._

The regulatory bodies, particularly the new, independent ones were, in 1998, simply too recently established to be have enough of a track-record of experience on which they could be appraised. In consequence, both the topic list in Table 1 above and the results are heavily weighted to aspects of the law and to legal obligations relative to actual regulatory practice. This is true even for aspects of regulatory practice such as Transparency and Predictability. This was unavoidable at the time but means that current and future studies should enhance the “what regulatory agencies <u>actually</u> do” aspect relative to the “what regulatory agencies are required by the law to do”.

> 22 For clarity, the scores in Table 2 above have been converted from the published A- E to 1-5, as was originally intended.

> 23

> The same is true of the results in the Stern-Holder paper which were drawn directly from the 1997 NERA survey.

15
<!-- Start of picture text --> 16%<br>14% 7 <<br>77 x.<br>, \<br>12%<br>‘N<br>/ ~ eA.<br>7 N<br>10%<br>¢ ‘XN<br>7 Ny = -AL average calibrated and<br>2% i a ~ Kalman filter/ real GDP<br>—— — AL (calibrated and Kalman<br>6% averaged)ged) // KS<br>4% |, Si<br>2%<br>0%<br>1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013<br><!-- End of picture text -->
SIERRA LEONE‘S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Figure 11. Sierra Leone’s spending is not sufficient to cover maintenance and rehabilitation needs**

<!-- Start of picture text --> 150<br>100<br>50<br>0<br>-50<br>-100<br>Maintenance Rehabilitation<br>Spending as % of requirements<br><!-- End of picture text --> Source: Gwilliam and others 2009.

Sierra Leone has to improve rural access roads to productive agricultural land. About 74 percent of the country‘s area is considered suitable for crop production, of which about 11 percent is cultivated.<sup>5</sup> Around two-thirds of Sierra Leone‘s population is employed in agriculture, which accounts for more than half the country‘s $2 billion GDP. In addition, cocoa exports generate an important stream of hardcurrency revenues. Despite this agricultural potential, the road network is a big constraint to developing the sector. Just 21 percent of the rural population lives within two kilometers of an all-season road. Commercial agriculture in Sierra Leone suffers not only from low access to roads, but also from the poor and deteriorating condition of the existing rural roads,. half of which are in poor condition. The roads need new investment, particularly in the less accessible areas of the southeast. Sierra Leone would need to add about 5,000 kilometers of road in order to provide access to the land that accounts for 80 percent of agricultural value.

Sierra Leone also needs to become a part of the regional transit network. While rebuilding national road infrastructure to ensure nationwide connectivity is of paramount priority, regional interconnectivity is also very important. Sierra Leone is a bottleneck on the ECOWAS Trans–West Africa Coastal Highway. More than 80 percent of this route is completed. Most of the remaining sections of the road are in Sierra Leone as well as in Liberia and Côte d‘Ivoire, the two other fragile countries. The highway will pass through Freetown, connecting its port to the regional corridor.

# Ports

## **Achievements**

Sierra Leone has one of the Africa‘s largest natural harbors, and is taking advantage of its geographical location by reconstructing its three major ports. Freetown is the major port of Sierra Leone. The port of Sherbro is designed to handle bauxite and rutile exports, and Pepel was built to facilitate the

> 5 http://www.eoearth.org/article/Water_profile_of_Sierra_Leone

24
# Table 8

# What Aspects of Corruption do Broad Perceptions Measures Capture? Evidence from the 2005 BEEPS and WEF

||NIT|ICRG|CPIA|EIU|Obstacle|TI|WBI|
|---|---|---|---|---|---|---|---|
|||**BEEPS**||||||
|Bribe tax(Q40)|.54|-.50|-.44|.52|.37|-.48|**-.51**|
|Bribefrequency (Q39a)|.57|-.52|-.54|.80|.60|-.60|**-.58**|
|Bribe predictability (Q39b)|.56|-.48|-.52|.65|.52|-.61|-.58|
|Obstacle to business (Q54q)|.31|-.35|-.12|.50|--|-.46|**-.33**|
|Kickback in govt. contracts|.14|-.04|-.04|.19|.33|-.15|-.12|
|(Q42)||||||||
|**Administrative corruption**||||||||
|Utilities (Q41a)|.50|-.34|-.52|.60|.54|-.60|-.55|
|Licenses & permits (Q41b)|.68|-.58|-.66|.82|.59|-.70|-.70|
|Government contracts (Q41c)|-.08|-.07|_.21_|.01|.57|-.06|_.05_|
|Health/safety inspections<br>(Q41d)|.05|-.33|_.02_|.38|.54|-.17|-.09|
|Fire/building inspections<br>(Q41e)|.50|-.52|-.43|.58|.18|-.45|-.50|
|Environmental inspections<br>(Q41f)|.43|-.42|-.34|.52|.53|-.40|-.41|
|Taxes & tax collections<br>(Q41g)|.65|-.58|-.68|.79|.49|-.66|-.69|
|Customs/imports (Q41h)|.38|-.41|-.35|.58|.72|-.46|-.42|
|Courts (Q41i)|.30|-.40|-.22|.47|.67|-.41|-.33|
|**State capture**||||||||
|Influence legislation/rules<br>(Q41j)|.03|-.20|_.03_|.09|.62|-.11|**-.04**|
|Impact of capture: parliament<br>(Q44a)|.15|-.39|-.08|.36|.68|-.28|-.19|
|Impacted of capture: govt. off.|.13|-.29|-.06|.32|.73|-.27|**-.17**|
|(Q44b)||||||||
|||**WEF**||||||
|Favoritism indecisions|-.34|.49|.28|-.43|-.52|.52|.39|
|Diversionofpublicfunds|-.52|.56|.42|-.66|-.83|.67|**.58**|
|Business costs ofcorruption|-.72|.65|.72|-.79|-.68|.80|**.79**|
|Financial honesty ofpoliticians|-.22|.44|.04|-.36|-.63|.40|**.24**|
|Irregularpaymentsin...||||||||
|...exports &imports|-.73|.59|.77|-.68|-.57|**.85**|**.79**|
|...public utilities|-.73|.58|.78|-.73|-.55|**.86**|**.81**|
|...taxcollection|-.74|.69|.77|-.68|-.49|**.82**|**.80**|
|...public contracts|-.26|.05|.27|-.10|-.40|**.53**|**.35**|
|...judicialdecisions|-.69|.57|.67|-.57|-.55|**.82 **|**.75**|

Correlations with counterintuitive signs are shown in italics. Correlations in bold indicate correlation by construction; i.e. the variable is a component of the composite index in question.

54
It is possible ⎯ but far from certain ⎯ that the cost savings associated with the removal of border frictions and protection for caustic soda producers would be sufficient to induce producers to invest in marketing and in re-tooling. If this were to happen, a discrete surge in Mexican detergent exports might occur.

The final basic message is that the SDS sector rapidly improved its value-added per worker after the mid 1990s, and that this reflected a combination of labor-shedding and innovative activity. The latter was facilitated by the presence of multinationals in several respects. Most directly, SDS subsidiaries drew on the research efforts of their headquarters abroad. But the Mexican-owned firms also benefited from multinationals, both through imitation and through their interactions with foreign-owned suppliers, who regularly approached them with new inputs and suggestions for new products and processes. Additionally, large retailers, such as Walmex, provided a stimulus for small and medium-sized suppliers to adopt innovations and improve production efficiency.

# **II. Wal-Mart’s entry: a revolution in retailing**

# _The ascendance of Walmex_

As the Mexican economy began to open in the mid 1980s, its retail sector began a process of profound transformation. Drawing on interviews with industry managers and supporting data from INEGI, Chavez (2002) provides an excellent synopsis and interpretation of the changes that occurred. This subsection summarizes his main findings, devoting particular attention to the changes that were important for the performance of the SDS industry.

4