rafmacalaba/datause-encoder-data huggingface dataset:
# **1. INTRODUCTION**

Compared to the vast empirical literature on policies affecting trade in goods, the empirical analysis of services trade policy is still in its infancy. A major constraint has been inadequate data on policies affecting services trade, especially in developing countries. Previous research has tended to rely on secondary sources and policy commitments under international agreements (e.g. Hoekman 1996). However, it is widely recognized that these measures bear little resemblance to policy reality today, even if they approximated policy in the past. More recent work tends to be confined to specific countries and sectors (Warren and Findlay 2000, Centre for International Economics 2010, OECD 2011, Reisman and Vu 2012) or to restrictions on FDI alone (Golub and Koyama 2006, Golub 2009, World Bank 2010).

Our limited knowledge of the pattern of services policy contrasts with our growing awareness of the importance of services in economic activity. Today, some 80 percent of GDP in the US and the EU originates in services, and the proportion is well over 50 percent in most industrial and developing countries. As countries confront the challenge of boosting productivity, services policy reform is being identified as a priority from Europe to South East Asia, but with surprisingly little empirical evidence on how such reform is best designed. The US and EU account for over 60 percent of world services exports, and the service exports of India, China and Brazil have grown by well over 15 percent every year for the last decade. As these countries seek to sustain export growth and others to replicate it, international negotiators have been struggling to negotiate away policy barriers but with only limited knowledge of what these barriers actually are.

This paper describes a new Services Trade Restrictions Database (STRD), which collects and makes publicly available information on services trade policy assembled in a comparable manner for 103 countries and five sectors – financial services (banking and insurance), telecommunications, retail distribution, transportation and professional services (accounting and legal). We also make a small methodological contribution by proposing and comparing alternative ways of measuring the restrictiveness of services trade policy. In the process, we 2
Parenting education from the prenatal stage and throughout the early years is needed at scale across Pakistan, especially relative to early stimulation. Research in Pakistan and other South Asian countries such as India and Nepal have demonstrated the effectiveness of parental education programs on early stimulation and responsive care in improving children’s development (ARNEC, 2019; Devercelli et al., 2022; Khan et. al, 2019; Sesame Street, 2019; Yousafzai et al. 2014), but there is need to build on them to provide programs at scale. Employing flexible, participatory, and multimodal approaches that are designed to meet the needs of extended-family caregivers is recommended (ARNEC, 2019), and programs should emphasize quality, frequency, and variety in interactions (Nieto, 2019). Programs can serve as distribution mechanisms to get books and learning and play materials into households and, when modeling and hands-on practice are involved, can strengthen caregiver-child bonds.

# Prioritizing Early Childhood Education

ECE enrollment was the strongest predictor of school readiness in this study, and it is an essential area for enforcing and strengthening policy in Pakistan. Just 19 percent of children aged 3-5 are enrolled nationally, and the rates are even lower among vulnerable populations (Tomlinson et al., forthcoming). There is global evidence showing that including ECE in compulsory education effectively increases enrollment rates (e.g., Tanzania; UNICEF, 2019). In Pakistan, children aged 5 years are considered primary students in some data sets and preprimary in the National Education Policy 2009—regardless, 58 percent of 5-year-olds are not enrolled in school at any level (Tomlinson et al., forthcoming). Given the strong link shown in this study between school enrollment and school readiness levels in Pakistan, supported by a deep body of research internationally, Pakistan would benefit from both enforcing existing policies and ensuring that programs are widely available and of high quality. Further clarity in policy documents citing national or provincial goals for intensity and duration of enrollment, backed by data gathering on key performance indicators, would elevate ECD and school readiness as national priorities.

Our findings that show that most parents believe children should be enrolled in school between ages 4 and 5 contrast with high levels of non-enrollment at those ages, which suggests barriers to enrollment need to be better understood and removed. The ITA (2021) study in Punjab reported that costs, transportation, lack of information about program quality, and clarity on parents’ rights and responsibilities were barriers to participation (World Bank, 2019). Given Pakistan’s successes with deploying and expanding cash transfer programs, the expansion of early childhood education could also be supported using this approach. The lack of ECE-oriented information and school accountability can be addressed via community-driven interventions that leverage local community and religious leadership to participate in awareness raising, cultivating a culture that elevates the importance and benefits of ECE.

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**Table 6a: Tests of the Overall Significance of the Association of Regions With Governance Structures for Supplier-Relations**

||||FDR<br>|||FWER<br>||
|---|---|---|---|---|---|---|---|
|Sub-regions of|p-value|1%|5%|10%|1%|5%|10%|
|Argentina|0.000***|0.0017***|0.0083**|0.0167*|0.0017***|0.0083**|0.0167*|
|Bolivia|0.390|0.0100|0.0500|0.1000|0.0100|0.0500|0.1000|
|Ecuador|0.000***|0.0033***|0.0167**|0.0333*|0.0020***|0.0100**|0.0200*|
|Paraguay|0.000***|0.0067***|0.0333**|0.0667*|0.0033***|0.0167**|0.0333*|
|Peru|0.000***|0.0050***|0.0250**|0.0500*|0.0025***|0.0125**|0.0250*|
|Uruguay|0.019**|0.0083|0.0417**|0.0833*|0.0050|0.0250**|0.0500*|

* significance at 10%, ** at 5%, *** at 1%.

**Table 6b: Tests of the Overall Significance of the Association of Regions With Governance Structures for Customer-Relations**

||||FDR<br>|||FWER<br>||
|---|---|---|---|---|---|---|---|
|Sub-regions of|p-value|1%|5%|10%|1%|5%|10%|
|Argentina|0.040**|0.0033|0.0167|0.0333|0.0020|0.0100|0.0200|
|Bolivia|0.140|0.0050|0.0250|0.0500|0.0025|0.0125|0.0250|
|Ecuador|0.000***|0.0017***|0.0083**|0.0167*|0.0017***|0.0083**|0.0167*|
|Paraguay|0.780|0.0100|0.0500|0.1000|0.0100|0.0500|0.1000|
|Peru|0.270|0.0067|0.0333|0.0667|0.0033|0.0167|0.0333|
|Uruguay|0.520|0.0083|0.0417|0.0833|0.0050|0.0250|0.0500|

* significance at 10%, ** at 5%, *** at 1%.

36
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|**Table 9: FOREIGN**|**WORKERS IN JAPAN (2002)**<br>4156|
|---|---|
|Legal foreignworkers|3,3|
|Skilled workers|(179,639)|
|Migrant workers of Japanese origin|(233,897)|
|Illegal foreign workers|220,552|
|Total|634,088|
|**Total Labor Force InJapan **|**66,490,000**|

Source: Japanese Ministry of Labor.

**Table 10: Illegal Foreign Workers Apprehended, by Country of Origin (2004)**

||<br>|Number<br>|<br>|<br>|Shar<br>|e(%)<br>|
|---|---|---|---|---|---|---|
||Total|Male|Female|Total|Male|Female|
|Total|55,351|31,100|24,251|100.0|56.2|43.8|
|China|15,702|9,536|6,166|100.0|60.7|39.3|
|Taiwan (China)|503|156|347|100.0|31.0|69.0|
|Hong Kong|66|37|29|100.0|56.1|43.9|
|Philippines|8,558|2,975|5,583|100.0|34.8|65.2|
|Korea|7,782|2,781|5,001|100.0|35.7|64.3|
|Thailand|3,572|1,384|2,188|100.0|38.7|61.3|
|Indonesia|2,103|1,463|640|100.0|69.6|30.4|
|Malaysia|1,575|1,141|434|100.0|72.4|27.6|
|Myanmar|1,466|1,179|287|100.0|80.4|19.6|
|Brazil|1,338|833|505|100.0|62.3|37.7|
|Bangladesh|1,312|1,215|97|100.0|92.6|7.4|
|Peru|1,292|775|517|100.0|60.0|40.0|
|Other|10,082|7,625|2,457|100.0|75.6|24.4|

Source: Japanese Ministry of Justice 32
firms. Still, the value of funding is 15% lower, while the first valuation of the firm is 12% lower. Once again, this could potentially be explained by some risk considerations. On the other hand, these firms exhibit 4.7 percentage points higher probability of success and an average 46% larger valuation growth over the life cycle of the firm. Furthermore, they tend to receive deals later on. The results do not much if we con- larger change only sider those firms that were born after the technology; that is, those firms that potentially were created with these disruptive technologies embedded in their offering rather than adopted them afterward.<sup>19</sup> The results for LAC do not differ significantly against Africa, except for the case of the probability of success, which, though still larger than non-disruptive firms, is lower than the one observed for disruptive firms in Africa. Still, when we consider only those firms that started operations after the technology was created, we see that the ticket value, though still lower for disruptive firms, is not as low as the one observed in Africa.

Table 5: Disruptiveness and Performance

||Years Until<br>First Deal|First<br>Deal Value|First<br> Valuation|Success<br> Probability|Value<br> Growth|Value Annual<br>Growth|Deal<br>Growth|
|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|||Pa|nel a. All Fi|rms||||
|Disruptive|-0.655***|-0.153***|-0.116***|4.662***|0.455**|0.053|0.039*|
||(0.190)|(0.031)|(0.030)|(1.035)|(0.168)|(0.041)|(0.023)|
|Disruptive_×_LAC|0.304|0.071|0.052|-2.990*|-0.142|-0.116**|-0.004|
||(0.275)|(0.054)|(0.049)|(1.760)|(0.167)|(0.056)|(0.032)|
|_R_<sup>2</sup>|0.286|0.172|0.088|0.235|0.231|0.106|0.152|
|Observations|2065|2327|2327|2327|365|344|1851|
|Countries|51|53|53|53|34|34|47|
||P|anel b. All F|irms born a|fter technol|ogy|||
|Disruptive|-0.917***|<br>-0.172***|<br>-0.129***|<br>5.517***|<br>0.477***|0.055|0.049***|
||(0.277)|(0.042)|(0.031)|(0.795)|(0.169)|(0.044)|(0.018)|
|Disruptive_×_LAC|0.160|0.089|0.047|-3.287**|-0.118|-0.118*|0.003|
||(0.346)|(0.058)|(0.053)|(1.482)|(0.164)|(0.061)|(0.027)|
|_R_<sup>2</sup>|0.266|0.170|0.089|0.239|0.234|0.105|0.158|
|Observations|2023|2273|2273|2273|354|334|1813|
|Countries|51|53|53|53|34|34|47|

Clustered errors in parentheses. *** 10%, ** 5% and * 1%. All regressions include as controls age (in IHS transformation), dummies for 9 categories of employment size, number of similar firms (in IHS transformation, dummies for the number of overlapping sectors where the firm operates (one or two additional sectors). Standard errors clustered at the country level.

> 19’Success probability’ is based on the PitchBook VC Exit Predictor model, which leverages machine learning and our vast database of information about VC-backed companies, financing rounds, and investors to assess a startup’s prospect of a successful exit. ’Value growth’ is defined as the ratio between the last and the first valuation.

25
database and covers the period of 1980-2014 at annual frequency. This data are in national currency and we convert it into real terms using the GDP deflator.

Next, to control for the potential effects of governance, political, economic and financial risk, and political conditions on the business cycles characteristics, we also use the _International Country Risk Guide_ (ICRG) database. This data covers the period going back to 1984.

Lastly, to assess the effects of fiscal rules on business cycles dynamics we rely on the International Monetary Fund’s _Fiscal Rules database_ which contains information on the type of fiscal rule in place, year of implementation, monitoring and enforcement procedures used. This data set is at annual frequency and covers 1985-2014 period.

To have the broadest coverage possible, in our analysis we consider all countries and all variables for which we have at least 30 years of annual data. We also exclude countries that are non-sovereign states. This gives us a sample with a maximum of 138 countries (for GDP) and a minimum of 20 countries (for government investment).

# **Measures of size**

We begin by characterizing measures of size we use in our analysis. We consider three key variables – population, labor force and geographic area.<sup>11</sup> For each variable we compute the average value over the sample period of 1960-2014 in each country. Using _average_ values for population and labor force, rather than the _end of period_ values, has the advantage of allowing to capture longer histories of size dynamics. This becomes especially relevant when using thresholds to separate countries into different size groups. For instance, several small countries in our data set have transitioned by 2014 out of the small group after being in it for most of the period. Using average size allows to account for such transitions and allocate these countries into the small size group.

The distributions of average values of size variables across countries are presented in Figure 1. Given our interest in the Latin America and Caribbean (LAC) region, we also show where LAC countries fit within those distributions.

<u>Figure 1. Distributions of country size</u> <!-- Start of picture text --> 10 15 20 0 5 10 15 20 10 12 14 16 18 20<br>all countries LAC all countries LAC all countries LAC<br>(a) (log) average population (b) (log) average land area (c) (log) average labor force<br>30 20 30<br>15<br>20 20<br>10<br>Frequency Frequency Frequency<br>10 10<br>5<br>0 0 0<br><!-- End of picture text --> 11 We also used total employment and found the results to be robust. The disadvantage of using employment as a measure of size is that employment data are available only for 30 countries in our sample.

12
CROP PRODUCTION AND ROAD CONNECTIVITY IN SUB-SAHARAN AFRICA

## **Figure 2.4 Sub-Saharan African crop balances by country and pixel**

<!-- Start of picture text --> Count<br>Raster_cro<br>-299.0<br>-1.06 -<br>-0.45 -<br>-0.24 -<br>-0.12 -<br>-0.05 -<br>-0.01 -<br>0.04 -<br>0.36 -<br>1.4 - 2<br><!-- End of picture text --> _Source:_ Own calculations.

# 3   Conceptual framework and model

In assessing the implications of location and investments in transport costs on crop production and productivity in Sub-Saharan Africa, we adopt a conceptual framework in which transport investments affect both the supply and demand for crop production.

On the supply side, production of crop _j_ under production system _l_ in location (pixel) _i_ depends on the agronomic potential p _j_ , under the production system _l_ in location _i_ , and unobserved location-specific variables ( _Ωi_ ) such as output and factor prices and available technology.

Demand for a crop produced in location _i_ depends on the size of the local market surrounding location _i_ , which is in turn determined by population, distribution of per capita incomes, and the trade regime (especially whether the domestic market is integrated with the international market).

12
# **4. Utilities Social Policy**

The previous sections have highlighted the gap that still remains between residential utility tariffs and full cost recovery. Moreover, it has been shown that within Latin America, genuine affordability problems appear to be confined to those in the bottom quintile of the income distribution, and in the lower income countries that face international prices for water and electricity services. These considerations suggest that, in principle, it should be possible to reconcile the objective of cost recovery and social protection through the application of targeted safety nets for utility services. Social tariff schemes for water and electricity, of diverse kinds, are in fact already widespread in Latin America. This section reviews the available evidence on the design and performance of these social policies, and evaluates the extent to which they contribute towards the reconciliation of economic and social objectives in these sectors.

# **_Water_**

The analysis of the water sector is based on a detailed review of the tariff structures of some 17 major water utilities in eight countries drawn from around the region (ADERASA, forthcoming). To complement this general overview, the results of a number of detailed evaluations of existing social tariff schemes are also presented.

By far the most commonplace social policy in the water sector is the Increasing Block Tariff (IBT) structure, whereby consumers are able to access the first consumption block at a concessional rate, and pay increasing prices at the margin for additional blocks of consumption. The IBT offers an implicit social safety net in so much as the first block should provide all families with access to a subsistence level of consumption at below the full economic cost. In theory at least, the IBT should still allow utilities to recover the full costs of service provision by charging above cost on higher blocks of consumption. A well-designed IBT should therefore incorporate a relatively small first block, that genuinely relates to subsistence consumption needs. Thereafter, the gradient between marginal tariff and consumption should be steep enough to allow prices to reach cost recovery levels within a normal range of consumption.

IBTs are almost universal among the 17 Latin American water utilities surveyed in this study. Analysis of these tariff structures suggests that there are a number of common problems with their design (Table 9).

First, the size of the subsistence block ranges from 15-40 cubic meters per month, with an average value of 25 cubic meters per month. This value is relatively high, both in relation to the average residential consumption of 20 cubic meters per month in most of these cities, and to benchmark levels of subsistence consumption of 8-16 cubic meters per 23
Roberts, D. (2004) The Multilateral Governance Framework for Sanitary and Phytosanitary Regulations: Challenges and Prospects. Prepared for World Bank training seminar on Standards and Trade, January 27-28, 2004. Washington, D.C.

Roberts, D. and Orden, D. Determinants of Technical Barriers to Trade: The Case of US Phytosanitary Restrictions on Mexican Avocados, 1972-1995. (1997).In: Orden, D. and Roberts, D. (eds.). _Understanding Technical Barriers to Trade._ International Agricultural Trade Research Consortium, University of Minnesota.

Roberts, D., T. Josling and D. Orden (1999) “A Framework for Analyzing Technical Trade Barriers in Agricultural Markets,” United States Department of Agriculture, Economic Research Services. Washington, D.C.

Roberts, D., B. Krissoff (2003) The WTO Agreement on the Application of Sanitary and Phytosanitary Barriers. United States Department of Agriculture. Economic Research Service.

Roberts, D., B. Krissoff (2004) Regulatory Barriers in International Horticultural Markets, U.S. Department of Agriculture, Economic Research Service.

Salay, E. (2003) Case Study: Reducing Mycotoxins in Brazilian Crops, in Food Safety in Food Security and Food Trade, edited by L. Unnevehr, International Food Policy Research Institute, Washington, D.C.

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Tangthirasunan, T. (n.d.) Mycotoxin Economic Aspects. Mimeo. FAO.

Unnevehr, L. (2000) “Food Safety Issues and Fresh Food Product Exports from LDCs,” Agricultural Economics 23 (2000): 231-240.

(2003) Food Safety in Food Security and Food Trade: Overview. In Food Safety in Food Security and Food Trade, edited by Unnevehr. International Food Policy Research Institute, Washington, D.C.

Unnevehr, L. and N. Hirschhorn (2001) Designing Effective Food Safety Interventions in Developing Countries. World Bank, Washington, D.C.

Weatherspoon, D.D. and Reardon, T. (2003). The Rise of Supermarkets in Africa: Implications for Agrifood Systems and the Rural Poor. _Development Policy Review_ , 21 (3), 1-16.

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42
**<u>Table 10: Comparative overview of water subsidy schemes</u>**

||**Argentina**|**Chile**|**Colombia**|**Paraguay**|
|---|---|---|---|---|
|**Design**<br>Consumption limit|Unmetered|15m<sup>3</sup>/m|20m<sup>3</sup>/m|15m<sup>3</sup>/m|
|Eligibility criteria|Variable by<br>Jurisdiction|Household<br>characteristics|Neighborhood<br>characteristics|Housing<br>characteristics|
|Discount|50-70%|15-85%|30-70%|30%|
|Administration|Local government<br>or localutility|<br>Local<br>government|Local<br>utility|Local<br>utility|
|**Scale**|||||
|Total beneficiaries<br>(as<br>percentage<br>population)|0.1m<br>(<1%)|0.6m<br>(20%)|30m<br>(90%)|5,000<br>(<0.1%)|
|Total cost<br>(of which fiscal cost)|<US$10m<br>(<50%)|US$40m<br>(100%)|US$250m<br>(60%)|<US$0.1m<br>(0%)|
|**Performance**<br>Error of inclusion<br>Error of exclusion<br>• Connected poor<br>• All poor|44%<br>73%<br>76%|32%<br>89%<br>96%|51%<br>1%<br>13%|26%<br>82%<br>89%|
|Leakage rate||44%|56%|61%|
|Coady statistic||1.40|1.10|0.97|
|Concentration<br>coefficient|-0.15||+0.11|-0.39|

Source: Gomez-Lobo and Contreras, 2002; Foster, 2004; World Bank, 2004

# **_Electricity_**

The analysis of the electricity sector is based on a detailed review of the tariff structures of some 44 major electric utilities in fourteen countries drawn from around the region (CIER, 2003). Since tariff designs are relatively homogeneous within countries, the discussion will be based on average or modal characteristics at the country level. To complement this general overview, the results of a number of detailed evaluations of existing social tariff schemes are also presented.

In contrast to the water sector, there is a much greater variety of tariff structures in use in the electricity sector (Table 11). Six of the countries surveyed rely primarily on linear tariff schedules for residential customers, while the remaining eight use IBT structures. The three utilities serving Buenos Aires (Argentina) stand out as being the only ones that offer a declining block structure such that the average tariff for residential customers declines as consumption increases. Residential tariff structures are almost always based solely on volumetric considerations, with Chile and Uruguay being the only countries that apply time sensitive and load based charging systems to residential customers.

Nine of the countries in the sample offer parallel social tariff schemes, and the vast majority of these are based on IBT structures, even when the main residential tariff is 29