rafmacalaba/datause-encoder-data huggingface dataset:
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Girma, S., Görg, H. and Hanley, A. (2008) R&D and exporting: A comparison of British and Irish firms. _Review of World Economics_ 144: 750-773.

Geroski, P. (1990). Innovation, technological opportunity and market structure”, Oxford Economic Papers 42: 586-602.

Geroski, P., J. Van Reenen and C. Walters. 2002. “Innovations, Patents and Cash Flow,” in A. Kleinknecht and P. Mohnen (eds.): _Innovation and Firm Performance. Econometric Explorations of Survey Data_ , Palgrave, London, chapter 2, 31-55.

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38
experiments involve randomly allocating respondents into two groups. They are then shown a list of statements and asked to state the number of statements (but not which specific statements) are true in their case. The list shown to the ”treatment” group includes one extra statement about the sensitive issue (e.g., not paying all the taxes that they owe). While it is not known which specific respondents have agreed with the statement on the sensitive issue, differences in the average number of statements reported as true between the treatment and control groups can be used to estimate the prevalence of the sensitive response. If respondents do not engage in sensitive activities, the mean number of items should be the same between the control and treatment groups. The double list experiment approach is an extension of the traditional single list experiment: respondents complete two list experiments sequentially and are randomly allocated to the treatment group in one of the two.

The double list experiment included as part of the WBES is shown in Table 1. Respondents were randomly assigned to either Group A or Group B. Each group was given two list questions to respond to, but with a slight variation between the groups. Group A received the treatment in List 2 while being the control for List 1 (note the statement about taxes in Group A’s List 2). Group B had the opposite arrangement, receiving the treatment in List 1 while serving as control in List 2. The treatment is the inclusion of a sensitive item asking about tax evasion, specifically “This establishment does not pay all the taxes it is required to pay.” The exact location of this statement in the list of statements was randomized. This text is identical to what was used in previous studies asking directly about tax evasion and has been trialed as part of single list experiments on firms in other middle-income countries (e.g., see Dom et al., 2022). The other statements in the double list experiment were carefully determined to minimize the risk that respondents could gauge the focus of the experiments. Consultations with private sector experts in Indonesia were conducted to ensure the statements achieve this aim, and they were subsequently fine-tuned through extensive piloting. In the case of List 1 in Table 1, the first statement is expected 9
Policy Research Working Paper 9590

# **Abstract**

Mobile technologies show great potential to accelerate internet access and usage, especially in developing countries. A better understanding of key drivers and main constraints for mobile internet access is the first prerequisite for governments to design targeted policy solutions. This study exploits a household survey that collects information on information and communications technology access and usage at the household and individual levels in 22 countries in the Global South. The study finds that in addition to infrastructure investment, which has been the main focus of many developing countries, other demand-side factors are of critical importance. Across the developing world, females, the elderly, those who live in rural areas, and those who have a relatively low level of income or education are less likely to adopt mobile internet. Social network effects are found to have a significant positive impact on the usage of mobile internet. Those who have more close friends using an online social network are more likely to adopt mobile internet. Individuals whose five closest friends are using an online social network (such as Facebook or Twitter) are 63.1 percent more likely to adopt it than those without any close friends using such online social network sites/apps. Across regions, although the factors affecting the adoption of mobile internet remain largely the same, the magnitudes of their impacts vary. In Asia, gender differences are negatively associated with mobile internet. In Africa, the impact of education level is more salient than in the other two regions, implying an urgent need to improve digital literacy.

This paper is a product of the World Bank’s _World Development Report 2021_ Team, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/ prwp. The author may be contacted at rchen5@worldbank.org.

_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 views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **1 Introduction**

While the costs of AIDS in terms of human suffering and lives lost are undeniably large, estimates of the associated macroeconomic costs have tended to be more modest. For example, studies that focus on Africa – the continent where the epidemic has hit the hardest – calculate the annual loss of GDP to be around one percent (see Table 1). These estimates all stem from a particular view of how the economy functions, namely, where the AIDS-induced increase in mortality reduces the pressure of population on existing land and capital, thereby raising the productivity of labor. Even if there is a decline in savings and investment (from the reallocation of expenditures towards medical care), its impact on GDP growth is dampened by the countervailing effect of increased labor productivity. Consequently, the net effect on the growth rate of per-capita GDP is very modest.

Table 1: The Impact of AIDS on GDP Growth: Selected Studies

|Author(s)|Countries|Method|Effect<br>on<br>growth (%)|GDP|
|---|---|---|---|---|
|Arndt<br>and<br>Lewis<br>(2000)|South Africa|CGE simulations|–0.8 to –1.0||
|Bonnel (2000)|47 Countries|Cross-country regres-<br>sion|–0.7<sup>_a_</sup>||
|Kambou et al. (1992)|Cameroon|CGE simulations|–0.5 to –1.2||
|Over (1992)|30 Countries|Demographic/<br>eco-<br>nomic modeling|–0.3 to –0.6||
|Sackey and Raparla|Lesotho, Namibia,|Demographic/<br>eco-|–0.8 to –1.5<sup>_a_</sup>||
|(2000, 2001a,b)|Swaziland|nomic modeling|||

> _~~a~~_ GDP per capita

In this paper, we argue that the long-run economic costs of AIDS are almost certain to be much higher – and possibly devastating. We take a very different view of how the economy functions over the long run, one which emphasizes the importance of human capital and transmission mechanism across generations. The formation of human capital, which should 5
Do such breaks in the time series characteristics of these variables reflect fundamental changes in the government budget process? Was this change necessitated by the unsustainable nature of fiscal policy prior to the "data break?" Or is the change in the time series properties of the data merely reflecting changes in short-run dynamics rather than longrun relationships among fiscal variables? When there are data breaks, we should presumably focus on the more recent government budget process instead of the government budget process over the whole period if we want to assess the sustainability of current fiscal policy. The entire data sample would be used in assessing the sustainability of fiscal policy, past and present, allowing for shifts in policies over time (perhaps caused by the desire to insure sustainability).

Ahmed and Roger's (1995) analysis of sustainability of fiscal and current accounts in the United States and the United Kingdom includes annual data from 1792 and 1692, respectively. The U.S. sample, therefore, includes major wars such as the civil war, World War I and World War II. The U.K. sample includes the wars of Spanish Succession, Austrian Succession, the Seven Years' War, American Independence, wars with France, the Crimean and Boer wars, and World Wars I and II. The authors carry out a thorough analysis of the cointegration relationship implying sustainability taking into account the above-mentioned break points. While the U.K. results are somewhat inconclusive, they conclude that: "despite the recent U.S. twin deficits problem, the currently expected future course of fiscal policy might plausibly be regarded as sustainable. However, it is clear that to formally conclude this with any substantial degree of confidence--given the nature of the tests involved and the need for a long span of data that we have argued for--must await the availability of much more data" (p. 18). In the LDC context, of course, the econometrician Oliver Twist would certainly be chastised for calling out "More, Sir" after being given three hundred years of data.

31
|Cyangugu|0.29|-0.54|0.31|0.05|
|---|---|---|---|---|
||(0.01)|(0.004)|(0.01)|(0.01)|
|Gikongoro|4.56**|0.72|1.48**|3.26**|
||(0.02)|(0.01)|(0.01)|(0.02)|
|Gisenyi|-3.48**|-1.39**|-1.39**|-1.41|
||(0.01)|(0.002)|(0.003)|(0.01)|
|Gitarama|0.71|-0.65*|-0.37|1.98*|
||(0.01)|(0.003)|(0.005)|(0.01)|
|Kibungo|-0.001|0.01|-0.60|1.67|
||(0.01)|(0.005)|(0.01)|(0.02)|
|Kibuye|2.63|-1.06**|-0.73|4.01**|
||(0.02)|(0.002)|(0.005)|(0.02)|
|Kigali Ngali|2.91*|-0.64|0.48|3.35**|
||(0.02)|(0.003)|(0.01)|(0.02)|
|Ruhengeri|7.17**|-0.54|0.86|7.02**|
||(0.03)|(0.005)|(0.01)|(0.03)|
|Umutara|1.37|-0.20|0.78|0.67|
||(0.02)|(0.01)|(0.01)|(0.01)|
|_Community’s characteristics_|||||
|More arrivals in community|||||
|More departures|0.24||0.17|0.11|
||(0.01)||(0.003)|(0.004)|
|An equivalent number|2.96||1.49|1.34|
||(0.02)||(0.01)|(0.02)|
|No arrivals, no departures|1.11||0.48|0.49|
||(0.01)||(0.01)|(0.01)|
|Daily market|||||
|Weekly market|-1.59|-0.73|-0.83*|-0.09|
||(0.01)|(0.005)|(0.004)|(0.01)|
|No market|-3.17**|-1.17|-1.73**|-0.68|
||(0.02)|(0.01)|(0.01)|(0.01)|
|No road|||||
|Road sometimes inaccessible|0.61|-0.05|2.13|-0.41|
||(0.01)|(0.01)|(0.02)|(0.01)|
|Road always accessible|1.94*|-0.09|2.01*|0.38|
||(0.01)|(0.01)|(0.01)|(0.01)|
|Distance to extension services|-0.06**||-0.05**|-0.01|
||(0.0003)||(0.0002)|(0.0002)|
|Distance to health clinic||-0.07*|||
|||(0.0004)|||
|Observed probability %|4.77|2.90|2.27|2.52|
|Predicted probability %|3.54|1.12|1.25|1.79|
|Observations|6789|6803|6789|6747|

Note: Marginal effects in percentage points, they are the change in the probability for an infinitesimal change in each independent, continuous variable and, the discrete change in the probability for dummy variables. These changes are calculated at the mean predicted probability.

Robust standard errors in parentheses, corrected for clustering; ** significant at 5% level; * significant at 10% level. Dependents ratio: Ratio of dependents to total number of household members.

25
- Finally, the _Open Knowledge Repository_ (OKR) makes all World Bank publications available to the public at large. Long-running periodical series and the annual workplans of various World Bank units determine which documents are to be disseminated through this repository. However, as the name of the database indicates, all the documents in it can be deemed related to knowledge.

The matching exercise was conducted for documents filed in the IB database between July 1, 2015, and June 30, 2019, a period that corresponds to the World Bank Fiscal Years 2016 to 2019, or FY16-FY19 for short. In the case of the WH database, the matching concerned all budget codes that had been deemed completed in FY16-FY19, plus all active codes as of June 30, 2019. Including the latter group is justified because documents may be filed in the IB database before the corresponding budget codes are closed. Similarly, to account for delays linked to administrative clearances and production processes, all publications released through the OKR database after July 1, 2015, were included in the exercise.

An important challenge was to determine which of the documents in the IB database had substantial knowledge content. Documents are filed there under one of more than two dozen headings, such as Country Economic Memorandums, or Policy Notes, or Sector Strategies (table A.1). However, several thousand documents were not tagged to any of these ten categories and needed to be individually checked to determine whether they qualified as knowledge products.

Similarly, only a fraction of the budget codes in the WH database support knowledge work. ASA codes in principle do, so they were all included in the matching exercise. But knowledge work is also supported by budget codes funding DEC research, as well as by the preparation of regional and sectoral strategies, country partnership frameworks, and training, among others. Conversely, a considerable amount of knowledge work is produced without mobilizing earmarked budget resources.

The matching process focused first on budget codes, which are at times mentioned in the documents filed in the IB database and in the publications released through the OKR database. Successful matches were indexed by the number of the corresponding budget codes in the WH database, known as P-codes in World Bank parlance. When no P-code could be identified in IB documents or OKR publications, the matching process relied on information about the titles of the entries and the names of their authors. Further confirmation that the matching was correct was provided by the regions or countries these entries covered and the sectors they were mapped to. Entries without associated P-codes were indexed with numbers allocated sequentially; these numbers are identified in what follows as Z-codes.

13
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> <sup>13</sup>

necessary condition for religious polarization. This is not the case with respect to ethnic fragmentation: ethnic groups are politically organized only if politicians organize them.

# **Measuring credibility**

The estimations below use political measures that are new to the conflict literature: the continuous years of competitive elections; years in office of the executive and the age of the largest government party; and a dichotomous variable tracking whether the main government party is programmatic or not. Each of these indirectly measures the degree to which politicians can make credible promises to citizens. The years of continuing competitive elections is from the Database of Political Institutions (Beck, et al. 2001) and covers the period 1975-2004. This variable takes a zero in countries where leaders have not been elected by competitive elections (elections in which multiple candidates compete in legislative and executive elections and none gets more than 75% of the vote, as judged by the Legislative and Executive Index of Electoral Competitiveness from the DPI).

The continuing years of competitive elections have a striking effect on a broad array of policy outcomes, ranging from corruption and bureaucratic quality to government control of the print media and public investment (Keefer 2005). The only theoretical explanation that fits this pattern of results (younger democracies provide fewer public goods, more targeted goods and are more corrupt) is that politicians in younger democracies are less able to make credible promises to a large fraction of the electorate (Keefer 2005).

The difference between the age of the largest government party and the years in office of the executive are measures of party institutionalization. Parties are more institutionalized the less dependent they are on individual leaders. From the foregoing discussion, we expect that where the government party is older than the executive’s tenure in office, it is more likely that party institutions can constrain the executive from reneging on agreements with party members. The larger is the age of the party relative to the executive’s years in office, therefore, the lower should be the likelihood of conflict.

The final political variable that is considered below is dichotomous, indicating whether the main governing party is programmatic. The DPI indicates whether parties can be judged as right, left, or center. If they can be, this is an indication that they can make more programmatic appeals to citizens. The DPI assessment of this variable is based on sparse information. However, Keefer (2005b) compares this variable to detailed regional
BURKINA FASO’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE The urban-rural service gap has also been reduced. Between the early and late 2000s, the rural-urban gap decreased by 20 percentage points in improved water and about 4 percentage points in sanitation (figure 15). Burkina Faso also adopted important reforms in the rural water and sanitation sector, such as the adoption of a rural water policy, the establishment of a dedicated budget, and the creation of a map of rural water points. At the same time, the country made some initial progress by establishing a rural water fund, introducing a cost-recovery policy, and closing the urban-rural gap.

**Figure 15. Urban and rural use of improved water and improved sanitation**

a. Trend in urban-rural access to improved water and sanitation b. Decrease (increase) in rural-urban gap between early 2000s and late 2000s

|||**1993**|**1999**|**2003**|**2007**|25.0||
|---|---|---|---|---|---|---|---|
|Improved water<br>|Rural<br>|38.9<br>|43.3<br>|52.0<br>|69.9<br>|20.0<br>**e**||
|services|Urban|71.1|80.9|93.6|91.8|<br>**ang**||
|Improved|Rural|7.0|6.8|7.4|18.8|<br>15.0<br>**nt ch**||
|sanitation|Urban|46.7|45.1|50.5|58.2|10.0<br>**poi**||
|||||||(50)<br>0.0<br>5.0<br>**Percentage**|Burkina<br>Cote<br>Liberia<br>Mali<br>Senegal|
|||||||(10.0)<br>.|Faso<br>d'Ivoire|
||||||||Improved Water<br>Improved Sanitation|

_Source:_ WHO Joint Monitoring Program 2010; for Mali from Demographic and Health Surveys for 1993, 1999, and 2003 and Questionnaire à Indicateur de Base du Bien-Etre for 2007; for other countries from Demographic and Health Surveys for different years.

# **Challenges**

According to official figures, the country will not reach the MDGs in either water supply or sanitation. In the case of access to improved water, the Burkinabè government reports that 58 percent of the population had access in 2009—against the MDG target of 79 percent in 2015—which means that it is admittedly off track in achieving the MDG for water supply. On the contrary, figures reported by the JMP present a much more positive view, indicating 79 percent access in 2009 and suggesting that if progress is maintained, the MDG will be comfortably surpassed (table 10).

**Table 10. Evolution of operational indicators associated with ONEA**

|% population with access||Government|Joint Monitoring Programme|
|---|---|---|---|
||Rural|55|76|
|Improved water supply|Urban|72|87|
||Total|58|79|
||Rural|—|54|
|Improved sanitation|Urban|19|57|
||Total|13|55|

_Source:_ Government of Burkina Faso 2010; WHO 2010. — = Not available.

25
**Figure 3.  Selected Countries with Peak in Youth Population in 2000-2010 Population Aged 12-24 (1950=100), U.N. Medium Variant Projections**

<!-- Start of picture text --> 600<br>Costa Rica<br>Mexico<br>500 Brazil<br>Viet Nam<br>Indonesia<br>400<br>300<br>200<br>100<br>0<br>1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050<br>Year<br>Population (1950=100)<br><!-- End of picture text --> 29