rafmacalaba/datause-encoder-data huggingface dataset:
These univariate graphic illustrations are just that - illustrations. They do not control for other factors affecting outreach. Hence, we now turn to regression analysis for more formal hypothesis testing.

# **B. Foreign bank participation and outreach – the country-level evidence**

Table III presents regressions using country-level data across 36 quarters between 1997 and 2005. The results in Table III Panel A show a positive association between the participation of foreign-owned banks and the share of municipalities served. On the other hand, we find a negative correlation between the foreign bank deposit share and branches and deposits per capita. While the foreign bank share enters negatively in the loans per capita regression, it is not significant.

In terms of economic significance, we find that our regressions predict that a 67 percentage point increase in the foreign bank share (the actual change observed between 1997 and 2005) is associated with a 4.4 percentage point increase in the share of municipalities served, relative to an initial share of 54 percent. On the other hand, this same increase in foreign bank participation is predicted to lead to a decline in 1.8 branches per 100,000 people and 46.6 deposit accounts per 1,000 people. This compares to initial values of 8 for branches per 100,000 and 268 for deposit accounts per 1,000 people. Hence, across the board the effects of changes in foreign bank participation appear to be sizeable and in relative terms (i.e., as a proportion of initial levels) the decline in branches and deposits seems to outweigh the increase in the share of municipalities served.

Table III Panel B and C consider the aggregate behavior of outreach measures for all domestic and, separately, all banks that became foreign-owned, respectively. We find that while 19
_<u>Table 1: Production structure of the economy by aggregate sector</u>_

|Aggregated Sector|Components|Percent of Total<br>Output|
|---|---|---|
|Agriculture|AgricultureForestry andFishing|3.3|
|Fuels & Minerals|Coal Mining<br>Gold and Uranium Ore Mining<br>Other Mining|6.7|
|Food Products|Food<br>Beverages andTobacco|5.5|
|Textiles|Textiles<br>Wearing Apparel<br>Leather and Leather Products<br>Footwear|1.5|
|Other<br>Manufacturing|Wood and Wood Products<br>Paper and Paper Products<br>Printing Publishing and Recorded Media<br>Coke and Refined Petroleum Products<br>Basic Chemicals<br>Other Chemicals and Man-Made Fibers<br>Rubber Products<br>Plastic Products<br>Glass and Glass Products<br>Non-metallic Minerals<br>Basic Iron and Steel<br>Basic Non-ferrous Metals<br>Metal Products Excluding Machinery<br>Machinery and Equipment<br>Electrical Machinery<br>TV Radio and Communication Equipment<br>Professional and Scientific Equipment<br>Motor Vehicles Parts and Accessories<br>Other Transport Equipment<br>Furniture<br>Other industries|23.3|
|Utilities|Electricity Gas and Steam<br>Watersupply|2.4|
|Construction|Constructionand Civil Engineering|4.5|
|Services|Wholesale and Retail Trade<br>Catering and Accommodation<br>Transport and Storage<br>Communication<br>Financial Services<br>Business Services<br>Health Community Social and Personal Services<br>Otherproducers|39.6|
|Government<br>Services<br>Note: Production sh|General Government Administration<br>General Government Defense<br>General Government Law and Order<br>General Government Education<br>General Government Health<br>General Government Social Services<br>GeneralGovernmentEconomic Services<br>ares are calculated fromSASAM 2003.|13.2|

4
POLICY RESEARCH WORKING PAPER 1514

# Summary findings

There are diverging views about how minimum wages affect labor markets in developing countries.

Advocates of minimum wages hold that they redistribute resources in a welfare-enhancing way, and can thus reduce poverty, improve productivity, and foster growth. Opponents, on the other hand, contend that minimum wage interventions result in a misallocation of labor and lead to depressed wages in the very sectors - the rural and informal urban sectors - where most of the poor are found, with the effect of wasting resources and reducing the growth rate.

Data from Colombia and Mexico for the 1980s provide an opportunity to evaluate the impact of minimum wages. In Mexico in the 1980s, the minimum wage fell in real terms roughly 45 percent. By 1990, Mexico's minimum wage was about 13 percent of the average unskilled manufacturing wage.

During the same period, the minimum wage in Colombia increased at nearly the same rate, reaching roughly _53_ percent of the average unskilled wage. Bell charts how the mandated minimum wage affected the demand for skilled and unskilled labor in both countries during that decade. She finds:

* In Mexico, minimum wages have had virtually **nio** effect on wages or employment in the formal sector. The main reason: the minimum wage is not an effective wage for most firms or workers. In the informal sector, in turn, there is considerable noncompliance with the mandated minimum wage, especially among part-time and female workers. As a result, significant numbers of workers are paid at or below minimum wages.

* In Colombia, minimum wages have a much stronger impact on wages, judging from their proximity to the average wage and both cross-section and time series estimates. The estimates imply that the elasticity of lowpaid unskilled employment with respect to minimum wages is in the range of 2 to 12 percent.

- This papera product of the Poverty and Human Resources Division, Policy Research Department is part of a larger effort in the department to analyze the implications of labor market distortions. The study was funded by the Bank's Research Support Budget under the research project "The Impact of Labor Market Policies and Institutions on Economic Performance" (RPO 678-46). Copies of this paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Sheila Fallon, room N8-057, telephone 202-473-8009, fax 202-522-1153, Internet address sfallon@worldbank.org (41 pages). September 1995.

_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_** _used atnd cited accordingly. The findinzgs, interpretations, and conclusions are the authors'_ **_own_** _and should not be attributed to the Wlorld_ **_Bank,_** _its Executive Board of Directors, or_ **_anv_** _of_ **_its_** _member countries._

## Produced b) the Policy Research Disscmination Center
- 64 -

Table 28: Regional Profile **ot** Malnutrition Among Children (Percentage of Severely Malnourished Children (gradofi Ill and IV)) In ICDS Project Areas During 198 4 -85 a

|||||||Ch|ild|Di|strict||
|---|---|---|---|---|---|---|---|---|---|---|
|||||Perc|ent|morta|lity|chara|cteristics||
|||||malnouri|shed|ra|te||AVA||
|Sn||District|Type of|0-3|3-6|0-2|0-5|SC+STd|<br>pOWe|IRRf|
|no,|State|name|projectb|(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|||||||||CS)|(Rs)|(%)|
|1|Andhra Pradesh|Guntur|Rural|8.80|11.30|99|142.00|13.00|317.00|39.00|
|||Vizianagaram|<br>Tribal|22.20|32.50|169|196.00|19.00|61.00|30.00|
|2|Karnataka|Dharwar|Rural|15.40|12.90|124|182.00|15.00|307.00|<br>6.00|
|||Mysore|Rural|17.20|10.80|109|149.00|24.00|270.00|17.00|
|3|Tamil Nadu|Kanyakumari|Urban|5.70|4.60|70|80.00|5.00|161.00|52.00|
|||Salem|Urban|5.70|0.30|74|101.00|20.00|245.00|22.00|
|4|Kerala|Mallapuram|Rural|1.20|4.30|66|104.00|9.00|355.00|57.00|
|||Palghat|Rural|0.70|4.00|74|116.00|19.00|421.00|57.00|
|5|Madhya Pradesh|Jabalpur|Rural|34.40|16.90'|220|265.00|29.00|152.00|5.A0|
|||Dhar|Tribal|26.00|17.30|138|174.00|59.00|350.00|7.00|
|6|Uttar<br>Pradesh|Pratapgarh|Rural|14.60|13.00|163|211.00|22.00|222.00|28.00|
|||Kheri|Rural|6.10|3.10|154|187.00|27.00|587.00|10.00|
|7|Rajasthan|Bharatpur|Rural|12.40|n.a.|214|252.00|24.00|369.00|20.00|
|||Banswara|Tribal|14.20|0.70|170|169.00|25.00|235.00|<br>7.00|
|8|Maharashtra|Yaystmal|Rural|22.30|25.10|177|<br>227.00|26.00|264.00|2.00|
|||Nanded|Urban|12.00|10.20|87|107.00|21.00|289.00|<br>3.00|
|9|Gujarat|Valsad|Tribal|4.C0|3.30|91|96.00|57.00|192.00|13.00|
|||Baroda|Tribal|7.30|5.60|115|129.00|31.00|206.00|21.00|
|10|Orissa|Cuttack|Rural|3.20|2.80|196|204.00|21.00|271.00|32.00|
|11|West Bengal|Nadla|Rural|21.30|12.20|115|149.00|28.00|268.00|33.00|
|||Bankura|Tribal|6.50|8.20|77|89.00|40.00|427.00|33.00|
|12|Haryana|Hassar|Rurai|6.70|4.20|120|146.00|22.00|901.0|064.00|
|||Ohiwani|Rural|5.50|0.70|114|129.00|18.00|558.00|20.00|

aThe data in columns 1 and 2 are taken from ICDS Project-wise Progress Report for 1984/85, for those projects which were sanctioned during 1983/84. As such, these figures reflect the nutrition situation at/about the commencement of ICDS in these districts.

bR = rural; T = tribal; U = urban.

- cDistrict-wise child mortality rates for 1981 for the age groups less than 2 and less than 5 years were made available for the first time in the

- Occasional Paper 5, 1988, Office of Registrar-General, Ministry for Income Affairs.

dPercent SC/ST to total population.

eAgricultural value-added.

fIrrigated area as a percentage of total cultivated area.

Note: Grades III and IV = '60 percent weight for age. Source: Subbarao (1989)
Olarreaga (2008) provide estimates of exactly the own-price elasticities required for this approach.<sup>2</sup>

# **III. Data and Tariff Formulas**

We use the MAcMapHS6 v1.1 database (Bouët et al. 2008) on applied protection in the base year for the negotiations, 2001. This dataset includes key features such as the _ad valorem_ equivalents of specific tariffs; an assessment of the impact of tariff-rate quotas (TRQs) on many key commodities; tariff preferences, and import values. The analysis is carried out at the finest level at which country classifications are internationally compatible: the six-digit level of the Harmonized System.<sup>3</sup> The protective effect of TRQs is represented by using the in-quota tariff when the quota is less than 90 percent filled; the out-of-quota tariff when the quota is filled; and their average in between. Adjustments were made for Korean corn and soybeans, where imports over high out-of-quota tariffs appear to be very large, but the TRQs are, in fact, expanded to meet demand. A preexperiment introduced reforms that will proceed irrespective of the Doha outcome, including expansion of the European Union, the phase-in of remaining agricultural commitments by developing countries,<sup>4</sup> and reforms agreed by WTO accession countries.

The negotiations specify cuts in WTO bound tariffs, which are frequently well above applied rates. This binding overhang means that reductions in bound tariffs will not always bring about corresponding reductions in applied rates or increases in market access. A detailed dataset on bound duties (see Bchir et al. 2006) conformable with the MAcMapHS6 applied rate data was used to specify the cuts in bound rates. Applied rates were reduced to the extent that the new bound rate declined below the initial applied rate.

11
|**Appendix table 4:**|**Distribution of**|**farm TFP b**|**y farm siz**|**e and owne**|**rship type**|||||
|---|---|---|---|---|---|---|---|---|---|
|**Size group**||**Total**||**Legally**|**registered**|**farms**|**In**|**formal far**|**ms**|
||**T**|**FP**|**No.**|**TF**|**P**|**No.**|**TF**|**P**|**No.**|
||**Mean**|**CV**|**obs.**|**Mean**|**CV**|**obs.**|**Mean**|**CV**|**obs.**|
|<50 ha|0.908|0.266|226|0.951|0.255|49|0.896|0.268|177|
|50-120 ha|1.043|0.218|375|1.045|0.216|183|1.042|0.221|192|
|120-500 ha|1.085|0.225|240|1.078|0.221|166|1.100|0.234|74|
|>=500 ha|1.155|0.184|100|1.158|0.187|95||||
|**Total **|1.033|0.238|941|1.068|0.221|493|0.995|0.253|448|
|_Note:_As discussed<br>mean farm TFP in th<br>than 500 ha categor|in the text, infor<br>e less than 50 ha<br>y at 1%. For info|mal farms a<br>, 50-120 ha<br>rmal farms,|re either o<br>and 120-5<br>mean farm|perations ru<br>00 ha catego<br>TFP in the|n by individ<br>ry is statisti<br>less than 5|uals or by<br>cally differ<br>0 ha catego|FOPs. For<br>ent from the<br>ry is statisti|legally regi<br>mean TFP<br>cally differ|stered farms,<br>in the greater<br>ent from that|
|of 120-500 ha catego<br>at 10%.|ry at 1% while t|he equality|of mean TF|P between 5|0-120 ha a|nd the 120-|500 ha categ|ory can onl|y be rejected|

35
The sugar industries of the Caribbean have been in decline since at least the 1970s, and repeated efforts to revitalize them have not been successful. Production and exports have declined by about half since 1970 (Figure 1).

**<u>Figure 1. Caribbean Sugar Production, Consumption, Exports and Imports, 1970-2003</u>**

<!-- Start of picture text --> Sugar Production and Consumption Sugar Exports and Imports<br>3.0<br>2.5<br>2.5<br>2.0<br>2.0<br>Production 1.5<br>1.5 Exports<br>1.0<br>1.0<br>0.5 Consumption 0.5<br>Imports<br>0.0 0.0<br>1970 1980 1990 2000 1970 1980 1990 2000<br>Million Tons Million Tons<br><!-- End of picture text --> Source: FAOSTAT data and authors calculations.

Domestic consumption has increasingly been satisfied by imports rather than production. Costs per unit of production have increased due to rising wages, deteriorating field and factory performance, and inefficiencies which have come with public sector control and management. Untimely strikes and high rates of absenteeism have further contributed to the deterioration of the sugar industries. Labor for undesirable tasks, such as cane cutting, is increasingly difficult to obtain and temporary workers for these jobs are often brought in from other countries. Losses accumulated over many years have led to large debts that further add to the cost of operation and limit capital for modernization.

While the situation varies by country, most of the Caribbean’s sugar producers would not be operating without preferential access to the EU and U.S. sugar markets that pay two to three times world market prices for imports from quota holders. These preferences have eroded over time as the quantities of imports have declined, especially in the United States. Further erosion is expected as the EU and U.S. face internal and external pressures for reform of their sugar programs. The quantities of EU and U.S. imports are now largely bound by international agreements, but the prices are not bound and are expected to decline with reforms. Many Caribbean countries have abandoned their U.S. quotas because they do not produce enough sugar to meet both their EU and U.S. quotas and the EU quotas have higher prices. Some countries, such as Barbados, have had their EU quotas reduced and assigned to other countries because they did not meet them. Despite this, export earnings for the Caribbean region still averaged US$406 million during 1999-2001 and 60 percent of these earnings were due to preferential access to the EU and U.S. sugar markets.

While production costs have increased and production and exports have fallen in many Caribbean countries, the opposite has occurred in many other sugar producing countries. World sugar production costs have declined by about 40 percent (real terms) since 1980 (LMC International, 2001), as production has increased most rapidly in lowcost producers such as Australia, Brazil, Colombia, Guatemala, South Africa, and Thailand. The combined share of world exports of these low-cost producers has increased from 24 to 52 percent since 1980.

2
Greene, W. (2003) _Econometric Analysis 5_<sup>_th_</sup> _Edition_ . Upper Saddle River, NJ: Prentice Hall.

Gwartney, J., and R. Lawson. (2004) _Economic Freedom of the World 2012_ . Vancouver: Fraser Institute.

Helpman, E., M. Melitz, and R. Rubinstein. (2008) “Estimating Trade Flows: Trading Partners and Trading Volumes”, _Quarterly Journal of Economics_ , 123(3), 1061-1110.

Jensen, B., and L. Kletzer. (2005) “Tradable Services: Understanding the Scope and Impact of Services Outsourcing”, _Working paper_ , No. 05-9, Institute for International Economics.

Levchenko, A. (2007) “Institutional Quality and International Trade”, _Review of Economic Studies_ , 74(3), 791-819.

van der Marel, E. (2011) “Determinants of Comparative Advantage in Services”, _GEM Working Paper_ , Groupe d’Économie Mondiale, Sciences-Po.

van der Marel, E. and B. Shepherd (Forthcoming) "Services Trade, Regulation, and Regional Integration: Evidence from Sectoral Data”, _The World Economy_ .

Mattoo, A. (2004) “The Services Dimension of China’s Accession to the WTO”. In D. Bhattasali, and W. Martin (eds). _China and the WTO: Accession, Policy Reform, and Poverty Reduction Strategies_ . Washington, D.C.: World Bank.

Miroudot, S., J. Sauvage, and B. Shepherd. (Forthcoming) “Measuring the Costs of International Trade in Services”, _World Trade Review_ .

Miroudot, S., and B. Shepherd. (2013) “Trade Costs and RTAs in Services”, _Working Paper._ Romalis, J. (2004) “Factor Proportions and the Structure of Commodity Trade”, _American Economic Review_ , 94(1), 67-97.

32
> Next, we construct entry ( _ERit_ ), exit ( _XRit_ ), and turnover ( _TRit_ ) rates as:

The denominator for both entry and exit rates is the total number of firms in bucket i in year t-1. This is because we want to capture the pool of potential exiting firms. These measures are comparable to gross measures of entry and exit and allow us to compare our findings to those of US firm studies.

We also construct survival rates as the probability of exiting at _t_ using the Kaplan-Meier estimator such that: S(t) is the estimated survival function, n is the total number of firm lifespans, and (δ)t is a dummy equal to one for completed spells and 0 for censored spells. In our sample we find that the average lifespan of firms is 6.9 years, with a median of 5.0 years.

We follow Haltiwanger et al.'s (2008a) analysis of business dynamics in the US where firm-level employment growth is:<sup>16</sup> and aggregate employment growth is given by the weighted average of firm-level growth: Employment growth can be decomposed into creation and destruction:

> 16 This follows the methodology of Davis et al. (1994).

13
costs and the benefits of schooling (as in Card 1999). Individuals select into schooling in part on the basis of expected gains—what Heckman, Urzua, and Vytlacil (2006) call “essential heterogeneity” (also Carneiro, Heckman, and Vytlacil 2006; Carneiro and Lee 2008). In the absence of a scholarship program, children with higher ability are more likely to stay in school than lower-ability children because for them the expected returns are high; higher-ability children also learn more while in school. Conversely, lowerability children, for whom the expected returns to school are low, are more likely to drop out of school; these children would not have learned much had they stayed in school. The CSP program lowers the costs of education for scholarship recipients, and some of the lower-ability children who under normal circumstances would have dropped out now stay in school. However, the test performance of these children is not improved by their additional schooling.

To investigate this hypothesis we proceed in two complementary ways, both of which involve comparisons of the distribution of test scores of CSP recipient and non-recipients, conditional on attaining a certain school grade.

To begin, we restrict the sample in the household survey to children who were enrolled in 8<sup>th</sup> grade at the time they took the test. In the case of the school-based mathematics test, no such restriction is necessary, as test scores are only available for those who were enrolled in 7<sup>th</sup> grade (and were present on the day the test was applied). Also, it is useful to rescale the samples so that there is one recipient for every non-recipient “at baseline” (at the time the application for the CSP was completed). This rescaling does not affect the analysis, but allows for an easier visual inspection of patterns.<sup>19</sup> Our first approach involves generating histograms of the number of children with a given test score, separately for CSP recipients and non-recipients. These histograms are presented in the upper panel of Figure 5, with each figure corresponding to a different test. The lower panel of the figure plots the _ratio_

> 19 As described above, there were about 26,537 applicants for CSP scholarships, and 3,800 scholarships were offered. We therefore rescale the sample used for the analysis of the school-based test by giving each non-recipient applicant approximately one-sixth the weight of each recipient applicant. In the household survey there are approximately twice as many recipients as non-recipients, by construction. We therefore rescale this sample by giving each recipient applicant a weight which is approximately one-half the weight of each non-recipient.

18
- 58 -

- government investment by economic activity (GOVIN)

- private investment by econornic activity (PRIVIN)<sup>6 1</sup>

- number of workers by economic activity (TOTLAB)

- wages by economic activity (TOTWAGN)

- final consumption at market prices by the public sector<sup>(GOVCONN)</sup>

- government investment in agriculture and irrigation (GVIAGN)

- governrent investment in electricity (GVIELECN)

- government investment in construction (GVICONN)

- government investment in transportation (GVITRNN)

- government investment in communications (GVICOMN)

- government investment in utilities (GVIUTILN)

- investment costs in machinery (ICMACHN)

- investment costs in buildings (ICBLDGN)

- investment costs in transport equipment (ICTRANSN)

- investment costs in other (ICOTHERN)

- gross domestic product at factor costs disaggregated by economic activity

World Bank, "Arao Republic of Egypt: Issues of Trade<sup>Strategy and Investment Planning,"</sup> January 1983.

- gross domestic product at factor prices (GDPN)

- GDP from the petroleum sector (GDPPETRN)

- government deficit (GOVDEFN)

- domestic bank financing of the government deficit (DBFGDN)

- total government tax revenue (GVTXRVN)

World Bank, "Arab Republic of Egypt. Current Economic<sup>Situation and Economic Reform</sup> Program," July 1986.

- gross domestic product at factor prices (GDPN)

- GDP from the petroleum sector (GDPPETRN)

- government investment in infrastructure (GVIINFN)

World Bank, "Arab Republic of Egypt: Country Econormic<sup>NMemorandum,"</sup> September 1988.

- gross domestic product at factor prices (GDPN)

- GDP from the petroleum sector (GDPPETRN)

- government investment in infrastructure (GVIINFN)

- government expenditure (GOVEX)

**61** The Shura Council data on private and government investment<sup>by economic activity were compared</sup> with the figures given in various issues of the Ministry of Planmng's<sup>Follow-up Report to the Five Year</sup> Plan. The figures were generally consistent and discrepancies could<sup>usually be explained by differences</sup> in definLitions and categories used.