rafmacalaba/datause-encoder-data huggingface dataset:
(WHO III), Diazinon (WHO II), Fenvalerate (WHO II), Cartap (WHO II), and Dimethoate (WHO II).

In regards to shipment of pesticides to the shops, it was reported that 60% are delivered by pesticide companies directly, with the remaining 40% (most likely) picked up by the traders themselves. Up to 20% of the shipments arrive at the shop damaged, unsealed or broken, however only <1% of traders (0.05%) actually admitted to repackaging the contents.

# _Training, averting behavior and perception_

As traders work, and surround themselves, with the substances, they are naturally exposed to the toxicity of the chemicals. Exposure to pesticides can lead to an array of health effects, depending on the pesticide’s toxicity and the dose absorbed by the body.<sup>8</sup> However, the health effects of pesticide use can often be reduced significantly by averting behavior – wearing protective clothing (Cropper, 1994) and exercising precaution. The extent of adverting behavior of a trader, in turn, depends, on the perception of risk and training received on safe handling of pesticides. In our survey, although 72% traders reported receiving at least some basic training on use of pesticides and safe handling<sup>9</sup> , 92% openly admitted that they do not take any protective measures during the handling of pesticides.

To measure a trader’s perception of health risk, two questions were asked, “ _whether the trader thought that pesticide handling and/or exposure, overall, has any negative short- or long-term impacts on their health_ ”. The results are summarized in Table 2. Perception was then constructed as equal to one if the respondent replied “Some, Large, or Fatal Effects” for either short or long-term impact (0 otherwise). Note those who

> 8 For pesticides with high acute toxicity, exposure can produce intoxication symptoms within minutes or hours, and these acute effects run from mild headaches and flu like symptoms, to skin rashes, to blurred vision, and other neurological disorders (World Resources, 1998-99).  In addition, prolonged exposure to pesticides can cause many chronic serious health effects: cardiopulmonary problems, neurological and haematological symptoms, and adverse dermal effects (Davies, Freed, and Whittemore, 1982; Spear, 1991). 9 The dominant source of information on pesticide use and handling was by the pesticide supplier or company (67.27%), followed by the Agricultural Ministry (19.09%) and   “self” (10.91%).

9
# **Annex Figure 3: Services trade restrictiveness indices by income group and sector**

<!-- Start of picture text --> Restrictiveness of Services Trade Policies<br>by sector<br>90.0<br>80.0<br>Fin.Serv<br>70.0<br>Telecom<br>60.0<br>50.0 Retail<br>40.0 Transport<br>30.0<br>Prof.Serv<br>20.0<br>10.0<br>0.0<br>Low Lower Upper High<br>income middle Middle income<br>Index of restrictiveness<br><!-- End of picture text --> _Source_ : Gootiiz and Mattoo (2008)

**Annex Figure 4: Services trade restrictiveness indices by region/sector**

<!-- Start of picture text --> 90.00<br>80.00<br>70.00<br>Fin. Services<br>60.00<br>Telecom<br>50.00<br>Retail<br>40.00<br>Transport<br>30.00<br>Professional<br>20.00<br>10.00<br>0.00<br>SAR EAP MENA LAC AFR ECA OECD<br><!-- End of picture text --> _Source_ : Gootiiz and Mattoo (2008) Annex Tables7-9 present measures of restrictiveness of UR Commitments, Doha offers and Actual Policy. At the regional level:

- The ECA and AFRICA regions have actual policies that are significantly more open than their UR (or accession) commitments, and comparable to those of OECD countries. But their Doha offers do not improve significantly their UR commitments and are on average much more restrictive than their actual policies.

- The OECD countries and those in the LAC region also have actual policies that are more liberal than their Uruguay Round commitments.  But their Doha offers improve somewhat their UR commitments and narrow the gap with actual policies.

- Countries belonging to the MENA, EAP and SAR regions have relatively restrictive policies that do not differ greatly from their Uruguay Round binding commitments. Their Doha offers improve to some extent on the Uruguay Round

27
# **References:**

- Arellano, M. and Bond, S. 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations." Review of Economic Studies 58: 277-297.

- Bhagwati, J. (1965) "On the Equivalence of Tariffs and Quotas," in R.E. Baldwin<sup>(ed.)</sup> Trade. Growth and the Balance of Payments, Amsterdam: North Holland.

- Berman, E., Bound, J. and Griliches, Z. 1994. "Changes in the Demand for Skilled<sup>Labor</sup> within U.S. Manufacturing: Evidence from the Annual Survey of Manufactures." Quarterly Journal of Economics 109 (2): 367-397.

- Bresnahan, T. (1989) "Empirical Studies of Industries with Market Power," in<sup>R</sup> Schmalensee and R.D. Willig eds. Handbook of Industrial Organization Volume 2. (New York: North Holland)

- Burki, S.J. and Edwards, S. 1997. "Latin America after Mexico: Quickening the Pace." In Annual World Bank Conference on Development in Latin America and the Caribbean 1995: the Challenges of Reform, edited by Burki, S.J., Edwards, S. and Aiyer, S. Washington D.C.: The World Bank.

- Burki, S. J. and Perry, G. E. 1997. The Long March: a Reform Agenda for Latin America and the Caribbean in the Next Decade. The World Bank Latin American and Caribbean Studies. Washington, DC: The World Bank.

- Canonero, G. and Werner, A. 1996. "Relative Wages and Trade Liberalization<sup>in</sup> Mexico". Mimeo, IMF.

- Cassoni, Adriana, Steven G. Allen, Gaston J. Labadie (1999) "Union, Labor Market Regulation, and Employment in Uruguay." Mimeo, IDB.

- Chinoy, Saji, Pravin Krishna and Devashish Mitra (1999), "Trade Liberalization and Labor Demand Elasticities: Evidence from Turkey" mimeo, Brown University

- Davidson, C. (1984), "Cartel Stability and Trade Policy," _Journal of International Economics_ 17:219-237.

- Dunnes, T. and Roberts, M. J. 1993. "The Long-Run Demand for Labor: Estimates from Census Establishment data." U.S. Bureau of the Census, Working Paper CES 93-13.

- Easterly, W., Loayza, N., and Montiel, P. 1997. "Has Latin America's Post-reform Growth been Disappointing?" Journal of International Economics 43: 287-311.

24
Table 1: Typical storm surge characteristics for cyclones in Bangladesh

|Wind Velocity<br>(km/hr)|Storm‐Surge<br>Height (m)|Limit to inundation (km)<br>from the coast|
|---|---|---|
|85|1.5|1|
|115|2.5|1|
|135|3|1.5|
|165|3.5|2|
|195|4.8|4|
|225|6|4.5|
|235|6.5|5|
|260|7.8|5.5|

Source: MCSP, 1993 Table 2: Vulnerable Area Estimates (sq km)

|Inundation Depth|2050 Without Climate|2050 with Climate|Percent Change|
|---|---|---|---|
||Change|Change||
|More than 1 m|20,876|23,764|+ 14%|
|More than 3 m|10,163|17,193|+ 69%|
- 10-

distribution, administrative structure and mass media for IE & C. Service (SERV) is the percent<sup>of the</sup> maximum score for each country. The actual values range<sup>from 0 to 78. Population per physician</sup> (PHYS), 1984 and the urban population as percent of total<sup>population, (URB) 1985 are from the _DR</sup> 1987.

3.3 In the simulations, the population of women of childbearing age in<sup>1985 is taken from</sup> WISTAT. This measure, women aged 15-44, omits<sup>women in the 45-49 bracket because the data as</sup> presently organized and published (which is for ages 15-19, 20-24,<sup>25-44 and 45-59) does not enable us</sup> to compute the number of women in this older cohort. The number<sup>of births in this age cohort, however,</sup> is quite small, and as such may not significantly understate<sup>the births and deaths simulated in section 5.</sup>

# 4. Results and Discussion

# A. Education. Family Planning Services, and Fertility

4.1 In the literature, several alternative specifications of education variables have been used. In the present study, female and male gross secondary<sup>school enrollment rates, lagged by approximately</sup> 10 and 15 years, were used, the inference being that the higher the<sup>enrollment rates in the lagged) years,</sup> the higher the proportion of mothers (fathers) with secondary schooling<sup>in the year 1985, in each of the</sup> countries for which data on all the variables are available. Data<sup>limitations prevented looking at age</sup> cohorts separately. Considering tk 'high proportion of births (i.e.<sup>a high proportion of the life-time,</sup> realized total fertility rate) occurs before a woman reaches the age<sup>of 25-29, 15 and 10 year-lagged school</sup> I A beter approach which was not **used** in this paper for **lack**<sup>of data would be to</sup><sup>**use years**of</sup><sup>**schooling**completd (or</sup> estimate of same) which would take **into** account **primary enrollment**<sup>more</sup><sup>**effectively**(see Schultz 1989).</sup>
to be reformed to become more efficient and to rely on more sustainable sources of finance. Thus, DBE shall be allowed to mobilize resources either by mobilizing time deposits or by issuing long‐term bonds.

Opening the banking sector to foreign participation. Over the medium‐term, the financing of the economy would benefit from more modern, diversified and competitive banking services. In connection with the process of WTO accession, which has been reinvigorated, the authorities should envisage a revision of the investment law to allow foreign investment in the banking and insurance sectors.

# 4.4. Issuing marketable government securities

Supplying marketable T‐bills. With or without a formal debt management strategy (see below), the MOF (debt management office) could start issuing marketable government securities. It would need to develop an issuance plan and make tactical choices regarding the instrument, size and timing of the T‐bill issuances (see Box 6). Development of such an issuance plan would also be important to attract and retain domestic (and ultimately foreign) investors in the market.

## **Box 6. Steps in Developing an Issuance Plan for T‐bills**<sup>**98**</sup>

The legal, regulatory, and accounting framework governing debt issuance and redemption, and the operational infrastructure, should allow the debt manager to design an issuance plan that enables both the financing of the budget and risk management. The following steps have been identified to develop a government securities issuance plan:

1. Determine financing need to be met by government securities issuance in the domestic market (proportion and weekly breakdown of gross borrowing requirement to be financed with domestic marketable debt)

2. Select instruments: instrument types and tenors (e.g. 6‐month treasury bill, 12‐month treasury bill, 3‐year bond, 5‐year bond) 3. Organize auctions: auction size, frequency and sequencing (e.g. bills auctioned every week, 10‐ year bond auctioned every quarter) 4. Organize maturities (standard maturity months, specific maturity dates) 5. Determine liability management operations (securities and timing of buybacks and exchanges, if any) 6. Develop the auction schedule (timing of each auction, and the instrument and amount to be issued at that auction 7. Determine the frequency, format, and detail of market communication: announcements (indicative annual auction calendar, more detailed quarterly calendar, more details/adjustments on a monthly/weekly basis), reporting (auction results, monthly and annual reports on issuance plan implementation), consultation (quarterly or monthly meeting with primary dealers and/or other investors, ad hoc consultation before auctions and on special operations) 8. Review and adjustments: periodic (e.g. quarterly, monthly/weekly) review of the issuance plan based on market consultation and updates to the gross borrowing requirement and cash flow forecasting.

98 This box draws on World bank (2015). Issuance Plan for Government Securities: Guidance Note. World Bank Group, Washington D.C.

28
<!-- Start of picture text --> 2<br>1.8<br>1.6<br>ene<br>ul<br>Re<br>S 1.2<br>=<br>® 1<br>°<br>=<br>a 08<br>o<br>a 0.6<br>0.4<br>0.2<br>0<br>cS2) & & PP<4 > PPa) \ KF> PSPs LK> LK<2] LSs\ & cSyy s<br>Year<br>—¢— Real Cocaine Price —#-— Real heroin Price —*— Real Marijuana Price<br><!-- End of picture text --> <!-- Start of picture text --> 60<br>50<br>40<br>5<br>o 3<br>é<br>20<br>10 ia a<br>0 —_ i _A2—_A— 4 —— ————_ i —— 1 ——_ > _ 5 8 TL 8<br>© 20 MA 2 2S & & o a 6 © A > oS A YS 6 OA 2 DO AS %<br>Year<br><!-- End of picture text --> —¢*— Marijuana Participation —TM- Cocaine Participation —&— Heroin Participation
|Gibson &<br>Carnavale<br>(2015)|Milan, Italy|2008-2012|Traffic, pollution and<br>weather|OLS||
|---|---|---|---|---|---|
|Kreindler<br>(2018)|India|2017|GPS location data for trips<br>of car and motorcycle<br>commuters and survey|Randomized<br>Experiment|The costs of rescheduling<br>travel to inconvenient<br>times will almost entirely<br>offset the benefits of the<br>saved travel time, resulting<br>in only a small consumer<br>welfare gain|
|**_Subsidies for Ad_**<br>|**_option of Altern_**<br>|**_ative Fuel V_**<br>|**_ehicles_**<br>|||
|Huse &<br>Lucinda (2014)|Sweden|2004-2009|Car Registrations,<br>Characteristics, Fuel Data,<br>Mileage Data|Structural model to<br>examine a number of<br>counterfactuals to the<br>actual policy.|Substantial share of FFV<br>consumers in would have<br>purchased FFVs in the<br>absence of the cash rebates<br>because of the vehicles’<br>lower operational costs|
|Xing et al<br>(2019)|United States|2010-2014|Characteristics of gasoline<br>and electric vehicle<br>models|Simulation|Cost effectiveness is<br>greater for policies that<br>that eliminate or reduce<br>subsidies for high-income<br>households, and provide<br>more generous subsidies<br>for low-income households|
|Muehlegger &<br>Rapson (2018)|United States|2012-2018|Disadvantaged community<br>designations, program<br>rebate data, transaction-<br>level data on the universe of<br>new and used EVs<br>purchased by California<br>buyers|OLS, using the count of<br>EFMP transactions as<br>an IV|EV demand by low- and<br>middle-income households<br>is price elastic, and that the<br>pass-through of the<br>subsidy is complete among<br>these consumers|
|Allcott et al<br>(2015)||Various|Various surveys from<br>different sources|OLS|Efficiency gains from<br>“tagging’’are larger when|

49
Table 2: Characteristics of respondents relative to internet and adult population by country

||SUR<br>SAM|VEY<br>PLE|INT<br>POPU|ERNET<br>LATION|A<br>POPU|DULT<br>LATION|
|---|---|---|---|---|---|---|
||Male|18-24|Male|18-24|Male|18-24|
|Angola|0.79|0.50|0.57|0.36|0.47|0.27|
|Argentina|0.45|0.11|0.50|0.17|0.47|0.15|
|Bangladesh|0.71|0.40|0.58|0.24|0.48|0.19|
|Bolivia|0.59|0.24|0.52|0.23|0.48|0.18|
|Ecuador|0.49|0.23|0.5|0.20|0.48|0.19|
|Egypt|0.51|0.29|0.51|0.22|0.50|0.18|
|Ghana|0.57|0.33|0.57|0.31|0.46|0.23|
|Indonesia|0.51|0.27|0.52|0.23|0.50|0.16|
|Kazakhstan|0.50|0.17|0.51|0.14|0.44|0.12|
|Nigeria|0.58|0.34|0.57|0.36|0.48|0.22|
|Pakistan|0.64|0.34|0.63|0.27|0.48|0.25|
|Vietnam|0.51|0.19|0.52|0.16|0.48|0.12|
|AVERAGE|0.57|0.28|0.54|0.24|0.48|0.19|

Note: This table compares the share of the survey sample by age and sex, with the internet-using population and general population in each country. Sources: ITU (2023); Household Income and Expenditure Surveys.
EAST AFRICA’S INFRASTRUCTURE: A REGIONAL PERSPECTIVE

# **Box 4.4 . Methodology for calculating benefits of ICT**

Affordability significantly affects access to telecommunications services. As the price of broadband service rises, the number of fixed broadband subscribers per 100 inhabitants drops (see figure).

# **Relation between broadband penetration and broadband affordability, world**

<!-- Start of picture text --> 10<br>y = 16.928x -1.092<br>1 R2 = 0.7842<br>0.1<br>0.01<br>0.001<br>0.10 1.00 10.00 100.00 1000.00 10000.00<br>Fixed broadband basket as % of GNI per capita, 2009<br>bscribers per<br>100 inhabitants, 2008<br>Fixed broadband su<br><!-- End of picture text --> The cost of Internet access largely depends on the wholesale price paid for international Internet connectivity. Presently, African countries rely heavily on satellite connections for Internet access. But fiber optic cable can lower the cost of Internet access provided countries allow Internet service providers (ISPs) open access to the cable. For example, in Kenya, connectivity to the fiber optic cable produced a 75 percent drop in international bandwidth prices.

Assuming Kenya’s wholesale cost reduction were applicable to other countries and that international wholesale prices account for half of the ISPs’ cost structure, the reduction in retail prices is assumed to be 37.5 percent. The potential savings for consumers in African countries, once they have open access to undersea fiber optic networks, can then be estimated. The revised broadband tariff is used to estimate the number of new broadband subscriptions based on the equation shown in the figure. Based on these assumptions, it is estimated that a 37.5 percent reduction in retail broadband prices would result in a _consumer_ savings of $159 million for existing subscribers. The lower broadband prices would trigger new subscriptions estimated at around 2.7 million (compared with 833,000 in 2008). These new subscriptions would generate an additional $800 million of new revenue.

Certain assumptions in the model should be noted. The model assumes a standard broadband tariff, even though several packages are typically available, priced according to their speed. The model assumes a scenario similar to Kenya’s in terms of the degree of the price reduction, and that half of the wholesale price reduction will be passed through to retail prices. It also assumes that there is a lone relationship between broadband pricing and take-up, even though other variables such as education and infrastructure availability will also have an impact. Finally, the model shows the one-off effect of a 37.5 percent reduction in retail tariffs. The timing of the full reduction is likely to spread over several years in some countries.

<u>Source: AICD.</u> 57
**Table 26. Governance-related drivers of legal and regulatory obstacles: Bureaucratic discretion**

|VARIABLES|(1)<br>OLS|(2)<br>OLS|(3)<br>OLS|(4)<br>OLS|(5)<br>Ologit|(6)<br>Ologit|(7)<br>Ologit|(8)<br>Ologit|
|---|---|---|---|---|---|---|---|---|
|Services|0.0144|0.00242|||0.0175|0.0105|||
||(0.0590)|(0.0578)|||(0.111)|(0.116)|||
|Export % of sales|-0.00211***|-0.000516|-0.00196**|-0.000434|-0.00394***|-0.00107|-0.00370**|-0.00108|
||(0.000792)|(0.000791)|(0.000797)|(0.000791)|(0.00148)|(0.00154)|(0.00154)|(0.00161)|
|Share of sourcing via imports|0.00248***|0.00153*|0.00250***|0.00148*|0.00485***|0.00349**|0.00498***|0.00338*|
||(0.000847)|(0.000845)|(0.000874)|(0.000870)|(0.00159)|(0.00171)|(0.00170)|(0.00180)|
|High-income source country|-0.142*|-0.0518|-0.138|-0.0324|-0.266*|-0.103|-0.277*|-0.0706|
||(0.0832)|(0.0846)|(0.0838)|(0.0837)|(0.161)|(0.175)|(0.167)|(0.179)|
|>250 employees|0.0643|0.0447|0.0421|0.0256|0.0664|0.0519|0.0244|0.0152|
||(0.0686)|(0.0685)|(0.0689)|(0.0686)|(0.123)|(0.133)|(0.128)|(0.137)|
|Cumulative inv. >US$10M|-0.00621|-0.0810|-0.0231|-0.0915|0.00788|-0.163|-0.0309|-0.189|
||(0.0711)|(0.0691)|(0.0703)|(0.0691)|(0.130)|(0.137)|(0.134)|(0.141)|
|Years in country|-0.00114|-0.00148|-0.000676|-0.00102|-0.00243|-0.00400|-0.00156|-0.00324|
||(0.00212)|(0.00206)|(0.00204)|(0.00204)|(0.00360)|(0.00388)|(0.00365)|(0.00395)|
|Level of foreign ownership (%)|-0.00267**|-0.00132|-0.00303***|-0.00130|-0.00474**|-0.00256|-0.00532**|-0.00256|
||(0.00111)|(0.00117)|(0.00110)|(0.00114)|(0.00211)|(0.00235)|(0.00215)|(0.00232)|
|Country fixed effects||X||X||X||X|
|Subsector fixed effects|||X|X|||X|X|
|Observations|2,424|2,424|2,424|2,424|2,424|2,424|2,424|2,424|
|R-squared|0.021|0.130|0.055|0.151|||||

Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 The dependent variable in all models is an ordered categorical variable corresponding to responses to the following question: "In general, how much of an obstacle were the following factors in this country? [Discretion of the bureaucracy]". Higher numbers denote more significant obstacles. Subsector fixed effects are at the ISIC A38 level.

Coefficients for constants (for OLS), cut points (for ordered logit), and fixed effects not shown in table.

43
In Mexico, the non life sector was showing levels higher than the data set average and progressively moved toward the data set average. For the life sector, a sharp increase to levels above average was quickly reversed and more recent stability is close to the data set average.

<!-- Start of picture text --> 12,010<br>10,010<br>8,010<br>6,010<br>4,010<br>2,010 Life Insurance<br>Non Life Insurance<br>10<br>1991 1996 2001 2006<br>Year<br>In Singapore, both trends consistent with the<br>hypothesis are obvious. The life sector gradually sees<br>the index fall and the non life sector sees an increase<br>from very low levels.<br>2,010<br>1,810<br>1,610<br>1,410<br>1,210<br>1,010<br>810<br>Life Insurance<br>610 Non Life Insurance<br>410<br>210<br>10<br>1991 1996 2001 2006<br>Year<br>Herfindahl Value<br>Herfindahl Value<br><!-- End of picture text --> In Singapore, both trends consistent with the hypothesis are obvious. The life sector gradually sees the index fall and the non life sector sees an increase from very low levels.

<!-- Start of picture text --> 3,510<br>3,010<br>2,510<br>2,010<br>1,510<br>1,010<br>510 Life Insurance<br>Non Life Insurance<br>10<br>1991 1996 2001 2006<br>Year<br>Herfindahl Value<br><!-- End of picture text --> In Poland, with the longest history in the data set, the move from a monopoly situation to the overall average is clear. For non life insurance, the sector liberalization over the period has also seen levels moving toward the data set average.

<!-- Start of picture text --> 3,010<br>2,510<br>2,010<br>1,510<br>Life Insurance<br>1,010<br>Non Life Insurance<br>510<br>10<br>1991 1996 2001 2006<br>Year<br>Herfindahl Value<br><!-- End of picture text --> In Malaysia, both levels are below the data set averages. Increases have been more organic in the non life sector. In contrast, the life sector has seen drift in the measures with a step change in a single year.

7