rafmacalaba/datause-encoder-data huggingface dataset:
technologies allow observing actual itineraries and trip times. A recent example is Hernandez (2021) who uses tracking data from GPS devices located in trucks operating within Colombia. With data on locations and time stamps of 15,000 trucks in 186,000 long-haul trips, he calculates waits and delays in road freight transport. In an application to China, Alder et al. (2021) estimate congestion by road segments using real-time GPS information on 1.8 million (20% of the total) long-haul trucks in 2020. Such GPS data, however, may not be readily available for researchers and practitioners. Therefore, node-to-node least-cost path calculations remain the most viable option for a wide range of applications.

Two examples for imputing domestic transport costs are Allen and Arkolakis (2014) and Donaldson and Hornbeck (2016). Using the fast marching algorithm on a detailed map of the transport network across continental U.S. counties, together with information on trade flows from the Commodity Flow Survey, Allen and Arkolakis (2014) embed a mode-specific transport cost minimization to the estimation of general trade costs. Donaldson and Hornbeck (2016) focus on transportation costs alone. While their goal is to analyze the impact of railroads in 19th century U.S. economy, the methodology they follow in constructing a county-to-county transport cost matrix can be applied to other settings. Using information on ton-mile cost of shipping via all available modes—rail, wagon and waterways—and assumptions on transshipment costs between modes, they calculate lowest-cost freight transportation routes and the associated costs in levels between all U.S. counties before the advent of motorized travel.

In a more recent application, Combes and Lafourcade (2005) calculate transport costs between French economic zones in 1978 and 1998. Focusing attention to road transport, they distinguish various road types (tolled and free highways, secondary roads and urban roads). Additional realism comes from separately incorporating itinerary and distance-related costs (fuel, tolls, vehicle and tire depreciation and maintenance) from time-related costs (driver wages and accommodation expenses, insurance and loading/unloading times). Since both are expressed in the same monetary units, the authors can compute general transport costs in levels between any two nodes within France by minimizing the total of distance- and time-related shipping costs. The information used in this calculation comes from surveys (e.g., maintenance costs), administrative data (e.g., driver wages) and price statistics on intermediate inputs used in trucking (e.g., fuel).

In a similar exercise for Spain, Zofío et al. (2014) impute distance (per km) and time (per hour) costs for road freight transportation in Spain at the NUTS-3 level of geographic aggregation. As Combes and Lafourcade (2005), they consider a representative 40 ton articulated truck, which accounts for about 80% of road freight transport in Europe. They convert time costs (Euro/hr) to the same unit as distance 10
**Figure 3.9: Average duration of an outage and average annual outage duration (top) in the US (bottom) in Europe.**

<!-- Start of picture text --> 5,636<br>70 6,000<br>59<br>60 USA 5,000 USA<br>50<br>4,000<br>40<br>30 25 23 3,000 2,143<br>2,000<br>20<br>9<br>10 1,000 195 147<br>0 0<br>10 9 160<br>Europe 140 135 Europe<br>120<br>100 79<br>5 80<br>2 2 60 33<br>1 40<br>20 2<br>0 0<br>duration (h)<br>Average annual outage<br>Average outage duration (h) Natural shocks Non-natural shocks Unknown Loadshedding Natural shocks Non-natural shocks Unknown Loadshedding<br>duration (h)<br>Average outage duration (h) Average annual outage<br>Natural shocks Non natural shocks Unknown Load shedding Natural shocks Non natural shocks Unknown Load shedding<br><!-- End of picture text --> _Source: authors. Averages are computed over 2000-2017 for the US and 2010-2016 for Europe._ Several factors may explain this pattern: natural shocks, such as storms, extreme temperatures, or wildfires, tend to affect large segments of the power network at once. This means that one natural shock can affect the power system in multiple – potentially unexpected – locations, some of which may be difficult to locate and access. For instance, as Section 4.1.1 shows, storms are particularly likely to cause outages in heavily forested areas. Falling trees and branches are among the most common cause of damages to electricity transmission lines following heavy storms. These damages tend to affect transmission lines along large distances, thus requiring extended periods for repairs. Moreover, natural shocks often have extended durations themselves thus preventing immediate fixing of damages to the system, e.g. hurricanes that last several days, or wildfires that cannot be controlled rapidly. In contrast, equipment failures or vandalism tends to occur in single locations, thus making immediate repairs easier.

18
**Table 2: Individuals with mobile phone access, 2014**

||All<br>(percent)|Ratio<br>rural /<br>urban|Ratio<br>women /<br>men|Ratio<br>age 45+ /<br>15-24|Ratio<br>bottom40 /<br>upper60|
|---|---|---|---|---|---|
|South Africa|84.2|0.94|0.96|1.04|0.89|
|Botswana|80.0|0.80|1.09|0.86|0.76|
|Kenya|74.0|1.01|0.81|1.09|0.73|
|Nigeria|66.4|0.86|0.72|0.87|0.74|
|Ghana|59.5|0.61|0.95|1.09|0.60|
|Namibia|56.1|0.60|1.04|0.85|0.57|
|Uganda|46.7|0.78|0.61|1.40|0.65|
|Cameroon|44.5|0.31|1.02|0.92|0.53|
|Mozambique|42.5|0.44|0.99|0.77|0.49|
|Tanzania|35.8|0.46|0.74|1.31|0.49|
|Rwanda|24.4|0.38|0.77|0.52|0.36|
|Ethiopia|18.3|0.22|0.42|0.79|0.27|

<mark>Source: Gallup World Poll (various years). See World Bank (2016). Ratios refer to percentages, e.g., percent rural / percent urban.</mark>

**Table 3: Individuals with internet access, 2014**

||All<br>(percent)|Ratio<br>rural /<br>urban|Ratio<br>women /<br>men|Ratio<br>age 45+ /<br>15-24|Ratio<br>bottom40 /<br>upper60|
|---|---|---|---|---|---|
|South Africa|34.1|0.52|0.70|0.32|0.74|
|Botswana|29.0|0.55|0.81|0.23|0.51|
|Kenya|26.3|1.02|0.57|0.54|0.46|
|Nigeria|18.4|0.69|0.59|0.23|0.40|
|Namibia|16.2|0.15|0.76|0.37|0.32|
|Cameroon|14.1|0.11|1.09|0.48|0.48|
|Ghana|12.7|0.61|0.48|0.44|0.29|
|Mozambique|11.1|0.13|0.74|0.27|0.24|
|Uganda|7.9|0.38|0.26|1.92|0.28|
|Rwanda|6.0|0.24|0.76|0.58|0.15|
|Tanzania|3.5|0.20|1.04|0.60|0.22|
|Ethiopia|2.7|0.14|0.28|0.54|0.23|

<mark>Source: Research ICT Africa surveys (various years). See World Bank (2016). Ratios refer to percentages, e.g., percent rural / percent urban.</mark> <mark>Second, studies reviewed in this paper suggest that basic price and market information systems can improve efficiency and welfare. The evidence, though strong, is still limited to certain countries and in certain contexts. A number of recent studies have cast doubt on the overall</mark> 23
personality traits.<sup>9</sup> While these provide some insights, they are too aggregated to be useful for policymakers to design education and training systems and programs. Third, supply side surveys rarely measure technical skills. While they may ask the respondent whether she uses a technical skill in her work, this is more a measure of the skills profile of the job rather than the skills the person possesses. Fourth, the results from the supply side data measure the equilibrium observed by the current supply and demand of skills, rather than allowing for an unconstrained revealed preference of employers.

The lack of employer voices in this debate is not surprising given how recent the economic research on this topic is and how far employers often are from education policy circles. However, small surveys in a range of countries have produced several data points to allow us to sketch a picture of employer preferences and demands.

This paper posits that employers demand a different set of skills than traditional education and training systems are designed to deliver and that there is a gap in the types of skills that employers value in the work place and those that the labor force acquires. Implicitly, it examines whether there is a disconnect between the skills formation system and the skills utilization system. And, if there is such a disconnect between the supply and demand for skills, what public policies and programs can fill these gaps. It also tests the assumptions that higher-order and non-cognitive skills are only a developed-world need and that these skills are relevant for only a sub-set of occupations.

This paper contributes to the literature in three ways. First, it uses results from employer surveys to develop a skills demand profile of employers. It is the first review article, to our knowledge, that systematically pulls together information on employer demand for skills across countries and various studies. Second, it is the first review article that provides cross-country comparisons to conclude whether or not employer skills demand profiles are unique to certain countries, industries, sectors, etc. or if there are common patterns that cut across markets. Finally, it brings together two policy lines that often move in parallel although they are intricately linked: education and labor.

# **II. Concepts and Definitions**

For the purposes of this paper, “skills” are defined as the capacity to perform a specific task. We break skills that are useful for the labor market into three categories: cognitive, technical, and socioemotional.

> 9 A commonly used measured of personality traits is the Goldberg Big Five.  The survey instrument asks a series of questions and then uses a factor analysis to extract personality traits.  Commonly, five factors break out.  Each personality trait has been associated with labor market outcomes in various studies (Barrick and Mount 1991).

5
**Figure 1: Enrollment in primary school by age (months)**

<!-- Start of picture text --> enrolment age in primary school<br>40 50 60 70 80<br>age at school entry october 2010<br>Village with preschool village without preschool<br>Kernel Density<br>.05<br>.04<br>.03<br>.02<br>.01<br>0<br><!-- End of picture text --> In Cambodia, children aged 70 months when school starts in October are supposed to register in primary school. No-one below this threshold should be officially registered. A birth certificate is necessary for official registration in primary school, but only about two-thirds of the children in a typical classroom are officially registered; the others attend informally. Consequently, many children are enrolled before they are 70 months old, others are registered at a later age, and classrooms have a mix of age groups. Figure 1 shows that in villages where no preschool is available, 55 percent of children register in primary school before the age of 70 months (solid line).

In villages where a preschool is available, there is a clear shift in enrollment age: Only 40 percent of children are below 70 months when they enter primary school (dashed line). The average age of entry moves from 68 months in villages without a preschool to 71 months in villages with a preschool. The shift primarily results from young children enrolling later in primary school, not from older children behaving differently (both curves display a similar pattern after month 75). The qualitative fieldwork revealed potential explanations for this impact: Although some parents confirmed that it was still possible to register informally, the registration age limit seemed to be enforced more in villages with a new preschool/primary school compound. In such villages, the school administration might have become more aware of the enrollment rule and more willing to enforce it, perhaps because officials from the ECE 12
# **IV. Objectives and empirical strategy**

The aim of this paper is to offer a first explorative analysis of the extent of work-related inequalities in social wellbeing and social cohesion across high, middle, and low income countries. Our analysis focuses on two things.

i. First we document self-reported job preferences and differences in self-reported (subjective) wellbeing between the employed and the unemployed. Following our discussion above we compare self-reported job preferences as an indicator of possible differences in priorities for labor market policies in high and lower income countries (see below). In addition, we hypothesize that the extent of variations in life satisfaction across different groups in the labor market may be seen an indirect measure of the inclusiveness - or lack thereof - of a country’s social and political institutions. To this end we also discuss how levels of subjective wellbeing for the employed and unemployed co-vary along with other economic and institutional attributes of a society.

ii. As a second step we explore whether or not uneven levels of wellbeing between the employed and unemployed translate into differences in social activism and other outcomes that could serve as more direct proxies for the level of social cohesion in a society. Our main indicators are self-reported levels of trust in people, a variable that is often used in the literature to approximate levels of social cohesion in a society (see for instance Knack and Keefer 1997, Larsen 2007). Other outcomes include people’s membership in civic associations, levels of political activism and attitudes towards formal governance institutions. We study these outcomes to gain an impression how effectively groups with different links to the labor market are able to participate in the social and political institutions of their countries. Again, our analysis distinguishes between higher and lower income countries.

We use data from the fifth round of the World Value Survey (2005-6), to our knowledge the largest freely available and internationally comparable data base with information on social wellbeing outcomes.<sup>11</sup> Surveys include a large number of questions on social wellbeing and associations, political attitudes and other outcomes that can be used as indicators (direct or indirect) of social cohesion. The surveys are coordinated by an international network of researchers from 54 nations, which ensures comparability of questionnaires and interview protocols across countries. Since we are interested in the gradation in work and social cohesion outcomes across national income levels we divide the sample according to World Bank country and lending groups (see Table 1). While the total sample size includes over 82,000 individuals, we

> 11 See http://www.worldvaluessurvey.org/ for data and documentation.

9
# **Need for Further Research**

The findings of this study suggest a need for more comprehensive ECA region-wide policy and empirical research focused on rental tenure choice and sector, so that a full comparative understanding can be compiled including actual practice cases of various policies, programs, and instruments for others to learn about, discuss, and possibly adapt to their own countries. Regardless of the number of countries covered, there is a need for follow-up research on both empirical and policy themes.

In empirical research there is a need for institutionalized monitoring of the rental sector, through improved census work and housing sector reporting, and supplementary specialized surveys on rental housing at various levels of government.<sup>2</sup> For tenure policy research two themes are relevant: (i) detailed analysis of country rental housing policy frameworks; and (ii) cross-country comparative policy studies to deepen understanding of actual practice. There is also a need for better understanding of the impact and constraints of specific policy measures and programs. Analogies from other sectors could broaden the feasible policy menu. This should include alternative taxation models and regulatory incentives or impediments.

Linkages to broader economic issues should include the role in poverty alleviation and labor mobility strategies of the public sector acting as a rental housing investor providing “market additionality”, while not replacing the formal private rental market. Partly due to political and ideological inclination toward homeownership, research into new public investment strategies in the form of rental PPPs, or non-profit rental forms has almost subsided over the recent decades, so there is a need to resume research in these directions.

The issue of inter- and intra-governmental housing policy institutional architecture should be studied to improve understanding of where housing policy is formulated and implemented. Anecdotal evidence suggests a wide variety of institutional anchors for housing policy both within central governments and between central, regional, and local government levels. The institutional fragmentation of housing policy formulation and implementation has discouraged development of comprehensive and cohesive housing strategy in many countries. Realignment of institutional infrastructure towards stronger coordination should be investigated.

> 2  See Annex 2 for an outline of survey contents assuring consistency.

vii
# WPS4275

CAN FOREIGN LOBBYING ENHANCE DEVELOPMENT? THE CASE OF TOURISM IN THE CARIBBEAN

**KISHORE GAWANDE**<sup>**1**</sup> **TEXAS A&M UNIVERSITY**

**WILLIAM MALONEY WORLD BANK**

## **GABRIEL V. MONTES ROJAS UNIVERSITY OF ILLINOIS, URBANA-CHAMPAIGN**

**Abstract:** There exist legal channels for informational lobbying of U.S. policymakers by foreign principals.  Foreign governments and private sector principals frequently and intensively use this institutional channel to lobby on trade and tourism issues. This paper empirically studies whether such lobbying effectively achieves its goal of trade promotion in the context of Caribbean tourism and it is the first paper to examine the potential for using foreign lobbying as a vehicle for development.  Panel data are used to explore and quantify the association between foreign lobbying by Caribbean principals and U.S. tourist arrivals to Caribbean destinations.  A variety of sensitivity analyses support the finding of a strong association. The policy implications are obvious and potentially important for developing countries.

Keywords: Foreign Lobbying; Tourism; Panel data. Fixed Effects.

JEL Code: F13, O54, C2, C3.

## World Bank Policy Research Working Paper 4275, July 2007

_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 cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._ 1 Corresponding author. Bush School of Government and Department of Economics, Texas A&M University. Phone: (979) 458-8034. Email: <u>kgawande@tamu.edu.</u> Funding from the World Bank is acknowledged.
(2015) highlight numerous ways in which the insured took advantage of the NHIS, such as frequent and unnecessary visits to health facilities, impersonation, or even feigning sickness to collect drugs for non-insured persons.

# **3 Data and Research Design**

## **3.1 Data**

To analyze the effects of NHIS implementation on risk coping mechanisms with a focus on child labor impacts, we use household data from the fifth round of the Ghana Living Standards Survey (GLSS), collected from October 2005 to September 2006. The fifth round of the GLSS interviewed 37,128 individuals in 8,687 households. We define a child as aged 5 to 17 years and limit the sample to those households composed by at least one adult and one child (30,060 individuals in 7,982 households), i.e., households with at least one potential child laborer.

Because the timing of implementation of the NHIS is non-random,<sup>7</sup> our empirical strategy relies on within district variation as opposed to cross-district variation. Correctly identifying geographic information is therefore central to our analysis. The finest within-district level reported in the survey is the enumeration area (EA), which roughly corresponds to villages (in rural areas) and neighborhoods (in urban areas). EAs within the same district were surveyed at different times, with no systematic order. Importantly, the date of the survey of each EA is orthogonal to key defining characteristics, such as population, economy, infrastructure, provision of education, and health care facilities.<sup>8</sup> This orthogonality is key for the identification of the treatment effect of insurance, as we will explain below.

We link the survey data to information on the exact implementation date of the NHIS at the district level. We collected these data from several sources, ranging from district level NHIS web-pages to newspaper articles and phone calls to district level NHIS authorities.<sup>9</sup> During the period of the survey, 53 districts adopted the NHIS. Of these, 52 districts had at least one EA surveyed before and one after the adoption of the NHIS. We only keep households in such districts, resulting in a final sample of 16,556 individuals in 3,493 households.

> 7The adoption date of the NHIS was negatively correlated with the level of district-level health care provision.

> 8Regressing the date of the interview on a wide range of EA characteristics yields mostly insignificant point estimates. The correlation between EA characteristics and the date of interview is always below 0.15. 9 We were unable to find information on the exact implementation date for 18 districts of the 110. We drop observations from these districts.

7
<!-- Start of picture text --> 4.5<br>o 4<br>oO<br>a<br>no}<br>o<br>N<br>‘G<br>E<br>{e)<br>z<br>3.5<br>3<br>3 3.5 4 4.5<br>Inverse Normal<br>Normality tests (p-value):<br>Shapiro-Wilk: 0.000<br>Shapiro-Francia: 0.013<br>D'Agostino, Belanger, and D'Agostino: 0.013<br><!-- End of picture text -->
increased time is likely due to some brokers taking on additional risks in the clearance process, resulting in a longer clearance time.

By contrast, short dwell times may reflect the significant network of personal contacts at work, developed by informal brokers among the low-level staff of private and public agencies. Such staff members regulate the port exit and can delay or accelerate procedures. For example, staff members may deliver the receipts or documents required for the successive steps of the clearance process.

Several factors seem to play a part in identifying professional informal importers and brokers: the number of containers; the quantities of products imported; sourcing, transit, and marketing strategies; and the customer base. Moreover, based on interviews, recent customs reform seems to have had an interesting result: despite relatively persistent corruption and fraud, it has become more difficult for informal brokers to find corruptible customs agents willing to allow informal brokers to elude increased declaration values (however, the remaining informal brokers are the least risk-averse).

The rest of this paper delves further into the determinants and descriptions of such business models and clearance practices. The section that follows presents a literature review, followed by sections devoted to the data collection methodology, some quantitative information on informal practices for car imports and garments, a demonstration of how crucial brokering practices are in understanding informal importers’ practices, the heterogeneity of importers’ sourcing strategies and clearance strategies, and the relationships between informal importers and brokers. The final section presents our conclusions and provides lessons for customs reform in a low-governance environment.

# **1. Literature Review**

The performance and practices of informal traders in international trade has not been studied extensively. Despite a lack of material, Akinboade and Kinfack (2012) have demonstrated that tax burdens discourage informal firms from registering their small and medium enterprises (SMEs) in Cameroon, especially in the area of customs regulations. Using a data set of detailed 5