rafmacalaba/datause-encoder-data huggingface dataset:
The Tajik situation illustrates how more Central Asian products could reach regional markets if the cargo capacity of empty trucks departing the leading cities was better harnessed (Table 5). Thousands of trucks leave Tajikistan empty. Between 2007 and 2008, the number of empty trucks departing from Tajikistan increased by 10,000 to reach 21,317. 43 percent of these empty trucks leaving the country were Tajik trucks, 42 percent were going back to non-CIS countries such as Afghanistan, China, Iran and Turkey. Furthermore, Dushanbe and Khujand are quite well connected via rail to major regional markets. By facilitating freight consolidation services, Tajikistan could tap into this potential to scale up its existing exports of agriculture and agro-processed products.

# **Box 1: “Yashar Bar”, a multi-modal freight forwarding company operating from Khujand**

“Yashar Bar”, an Iranian trucking company established in 2002 a Tajik affiliate located in Khujand to provide multimodal transportation services using empty Iranian trucks to export Tajik products to Thailand, Vietnam, China and Korea. The goods are transported to the port of Bandar-Abbas within 8 to 10 days, and then shipped over sea. The same mode of transport (motor and rail, sea) is used while exporting ginned cotton, silk, silk hides, etc. from Tajikistan as well as importing tea and coffee from India, Indonesia, Malaysia, Persian Gulf countries.

Currently a 20ft container from Khujand to the port of Bandar-Abbas costs $1800, including assurance; from Dushanbe, it costs about $2000. A 40ft container from Dushanbe or Khujand to Bandar-Abbas costs $2,650, which is to be compared with $1,800 from Tashkent. However, these tariffs can vary substantially. For instance, the latest freight transportation (May 2009) of “Yashar Bar” was a 40ft container from Khujand to Bandar-Abbas, and it cost $3,300 ($1,800 for the driver’s services and $1,500 for the company’s services). It is necessary to point out that the return trip from Tajikistan can be cheaper if the product transported does not require the use of refrigerators.

Transportation from Dushanbe sometimes requires 2 Invoices to be filled in order to avoid additional costs in using a 40ft container for lower freight volumes. In such case, the company pays for trucks to transport these small amounts of cargo and consolidate them in Khujand before shipping it to Bandar-Abbas, although domestic freight rates can be very high. Yet, the latest statistics of “Yashar Bar” shows that since the beginning of its activities, the company has transported Tajik goods worth $12 million, which suggests that the freight consolidation idea can be scaled up to improve the market accessibility of Tajik products.

Source: World Bank (2011).

17
Belhaj Hassine (2015).<sup>10</sup> Compared to income, consumption expenditure typically produces lower estimates of inequality, especially at the top. This can be explained by a declining marginal propensity to consume and by the fact that consumption surveys tend to understate the spending on durables at the top (e.g. Aguiar and Bils (2015) for the United States). For their study of top incomes in Egypt, Hlasny and Verme (2013) used income as their welfare measure. An argument for using consumption instead of income is that data on the former are often of a higher quality in developing and emerging economies and are less vulnerable to idiosyncratic noise as households tend to smooth their consumption over time. In what follows we will be abusing terminology by often referring to income inequality and the income distribution even though our data measure expenditures, not income.

As discussed in detail in Verme et al. (2014), inequality in Egypt as assessed from household surveys is low and has even declined in the decade before the 2011 revolution. The Gini coefficient of consumption expenditure declined by around 2pp from 32.8 in 2000 to 30.8 in 2009.<sup>11</sup> Our paper tests whether the low estimate in 2009 is robust to replacing the top tail of the income distribution with an estimate that is obtained using a combination of household expenditureand house price data.

# **3.2 Real Estate Data**

In late 2014/early 2015 we obtained data on houses and apartments for sale from two Egyptian real estate firms: Betak-online and Bezaat.<sup>12</sup> The two rank among the larger real-estate firms whose listing database can be accessed online; analogous to Redfin and Zillow in the United States. The data differ in detail but a listing typically consists of the asking price, the location (the city or a further subdivision), and the date when it was listed. Interviews with the Ministry of Housing in Cairo confirmed that the listing price provides a good approximation to the actual sales price.<sup>13</sup> We keep listings classified as houses, apartments, flats or villas, since these refer to private housing. There are a number of other types of listings which we exclude, the three largest groups being land, shop, and chalet.

The model that relates the value of the house to household expenditure (per capita) is estimated using the household survey data, which report (imputed) rents not property prices. We will be assuming that rent- and sale (or listing) prices are proportional to each other, which is sufficient for our needs.

> 10For a recent discussion of challenges with real consumption measurement, see e.g. Van Veelen (2002) and Van Veelen and Van der Weide (2008).

> 11Source: PovcalNet, accessed 31 October 2015.

> 12The URLs are respectively: www.betakonline.com; and www.bezaat.com.

> 13For our purposes it is sufficient that the actual price is proportional to the listing price.

14
# Talk or Text? Evaluating Response Rates by Remote Survey Method during COVID-19

*

Sofia A maral<sup>†</sup> Lelys D inarte-Diaz<sup>‡</sup> Patricio Dominguez<sup>§</sup> Santiago M. Perez-Vincent<sup>¶</sup> Steffanny Romero<sup>||</sup>

**Keywords:** Phone surveys, WhatsApp surveys, Response rate, Survey Experiments

> *We thank Nathan Fiala, Pablo Kolb, and seminar participants at ifo Institute and the Innovations for Poverty Action-Northwestern University Methods and Measurement Conference. We also thank the research assistance of Miguel Paniagua, and the implementation partners of Glasswing International. This work was supported by the IDB-COVID 19 Call for Research Projects and the World Bank Research Support Budget. This research project’s protocol was reviewed and approved by the Institutional Review Board (IRB) at the _Universidad Francisco Gavidia_ in El Salvador in April 2020 with the approval ID No. 003-2020. The authors have no conflicts of interest to report. The findings, interpretations, and conclusions expressed in this report are entirely those of the authors. They do not necessarily represent the views of the Inter-American Development Bank, its Board of Directors or the countries they represent, or those of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. All errors are due only to the authors.

> †ifo Institute at the Ludwig Maximilian University of Munich and CESifo. Email: amaral@ifo.de

> ‡Development Research Group. The World Bank. Email: ldinartediaz@worldbank.org

> §Pontificia Universidad Cat ́olica de Chile. Email: pdomingr@uc.cl

> ¶Inter-American Development Bank. Email: santiagoper@iadb.org

> ||Universidad del Rosario and The World Bank. Email:steffanny.romero@urosario.edu.co
or official registries validate broad orders of magnitude of our generated stocks. In some cases, such as Brazil, registry with the government was required to be a practicing engineer. What is considered an engineer, however, is less clear and hence these measures are less definitionally tight. In other countries, such as Colombia or Argentina, membership in Engineering associations was not required so registration likely underestimates.

_Census Data_ : Census data are also available in several countries. Census data have the advantage of being collected over time by several countries and across sub-national units. However, here, also, it is the individual respondent who is deciding whether he is an engineer or not with limited institutional confirmation, or detail on the actual level of education. This is fine for within country analysis but less reliable for cross country comparisons.<sup>12</sup> Sub-national data derive from the Argentine census of 1895, Mexican National Census of 1895, Chilean Census of 1907, Colombian census of 1912, Venezuelan Census of 1926, and US Census of 1900. For the US county level data, we use the census of 1880 to generate measures of literacy, and density of engineers, lawyers and medical doctors.

Annex I discusses how these three sources of data were employed for each country in detail.

_Patenting_ For the US, we also construct a measure of average patenting activity from 1890-1910 drawing on patents granted by the United States Patent and Trademark Office (USPTO) again, at the county level, provided by Acemoglu et al. (2013). This is likely to capture Mokyr’s more structured scientific inquiry at the frontier that began to assume a central role in the Second Industrial revolution in addition to its direct interpretation as new ideas. It does not appear driven by engineers or the other human capital variables and hence interpret it as captures a distinct type of human capital (see Sokoloff (1988). Comparable patent data is not available for the Latin American countries and hence the variable only

> 12As numerous local historians have noted (Serrano (1993) in Chile, Bazant de Salda ̃na (1993) in Mexico) and in the case for which we have the best information, the US, censuses are often substantially higher than the actual graduates of engineering programs.

7
Married women whose husbands are absent have the highest income among women-headed households -- about two-thirds the income of their counterparts in male-headed households (World Bank, 1989). They often receive cash transfers in the form of remittances from their absent husbands. These women tend to be younger than those who head households with no husbands and therefore may have a greater chance of seeing an increase in income (GOK and UNICEF, 1984). Even so, the remittances may not be sufficient to compensate for the household's weak position with regard to labor availability.

Research on the implications of type of household for nutritional wellbeing shows the complexities of the issue and the importance of differentiating by type of women-headed household. On the one hand, children in women-headed households may be more at risk since the household is poorer and mothers have less time to devote to food preparation and health care (GOK and UNICEF, 1984). Data from a 1977 child nutrition survey, for example, revealed that the worst nourished children came from households headed by unmarried females (ILO, 1976).

On the other hand, the 1977 data also show that the best nourished children came from households headed by married women who received income transfers from absent husbands (ILO, 1986). More recent information from Southwestern Kenya comparing preschoolers among sugar and non-sugar farming households, also found that children in women-headed households had significantly better nutritional status than children from other households. This result appeared to be linked to the fact that these women had a greater role in decision-making and placed more emphasis on nurturing activities (Kennedy, 1988).

# 5. Women's groups

Women's groups are a ubiquitous and dynamic part of Kenya's rural sector. The Ministry of Culture and Social Services has 25,000 registered women's groups and there are many more still throughout the country that are not registered. Originally formed as mutual assistance groups or traditional savings societies, often with social welfare goals, many of these groups have evolved into productive and economic entities engaged in a variety of community development, agricultural development and income-generating activities. As such, these groups have become popular targets for assistance from almost all donors: "The massive organization of Kenyan women into women's groups, has been taken as a sign of progress, and the groups have been regarded as the perfect instrument for the implementation of female-directed development assistance. Hence, a major part of aid resources targetted towards women has been channelled through women's groups' (Vintage Management Enterprises, n.d. cited in Monsted and Riunge, 1987).

As studies began to document the heterogenity and multi-purpose nature of women's groups, questions of the financial and support requirements of different groups as well as their capacity to effectively absorb assistance began to emerge. Distinctions were made between different types of women's groups: 1) groups that require only limited monetary contributions from members and that 26
noted earlier, is whether the reliance on aid has led to a decrease in tax effort. At the same time, however, we observe a fairly close relationship, except for the early 1990s, between nonfood aid and public investment (see Figure 5). As discussed later, this correlation is corroborated by more formal econometric tests.

During the 1990s, public investment increased significantly in proportion of GDP (see Figure 6), much of it going to infrastructure (transportation, energy, and telecommunications) and education (Figure 7). On average, during 1991-2002, public investment accounted for more than half (around 54 percent) of total fixed capital formation. The road network, for instance, expanded from 19,000 km in 1991 to around 34,000 km in 2003, whereas power generation doubled over the same period. Primary school enrollment rose from 20 percent in 1993 to 62 percent in 2002. According to our index of quality of public infrastructure, which is based on the methodology proposed by Hulten (1996), quality, which appears to have been quite low during the 1970s and 1980s, improved significantly during the late 1990s (see Figure 8).<sup>13</sup> Road infrastructure appears to generate substantial externalities (see Dercon (2004)). Yet, connectivity remains underdeveloped: all infrastructure networks (telecommunications, roads, energy, and water) have coverage well below averages for sub-Saharan Africa. Also, the needs for education and health services remain enormous.

This brief review suggests that, despite significant improvements in living standards during the second half of the 1990s, reducing poverty remains a challenge. Ethiopia continues to be a very destitute country adversely affected by acute diseases (malaria and the HIV/AIDS epidemic) and periodic famines. The evolution of life expectancy, a good indicator of whether a country is meeting its basic needs, and which is strongly correlated with per capita growth, illustrates this point quite well.

> 13Hulten (1996) drew attention to the importance of taking into account the efficiency with which the public capital stock is used, in addition to the absolute amount of that stock. He proposed a measure of public capital efficiency based on four indicators: _a_ ) mainline faults per 100 telephone calls for telecommunications; _b_ ) electricity generation losses as a percent of total electricity output; _c_ ) the percentage of paved roads in good condition; and _d_ ) diesel locomotive utilization as a percentage of the total rolling stock. Due to data limitations, however, we used only _b_ ) and _c_ ) in calculating our

28
Policy Research Working Paper 6585

# **Abstract**

This paper uses Zambia as a case study to assess empirically whether political interference in a lowgovernance environment has diminished in the past years as expected after a semi-autonomous agency model was set up ten years ago. The road sector in Zambia has experienced some significant developments since then. The paper uses data on contract from 2008 to 2011 and analyses a number of key trends related to Road Development Agency governance and staffing dynamics as well as procurement and project selection within the institution. The main findings indicate that, after some years of implementation of these reforms, there is reason to question whether the model of semi-autonomous agency enables road management to be shielded from political interference. Zambia may be an isolated case but, so far, this model does not seem to have been able to decrease political interference in the selection or supervision of projects and there seems to have been an increased lack of accountability of civil servants working in this sector.

This paper is a product of the Poverty Reduction and Economic Management Unit, Africa Region. 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://econ.worldbank.org. The authors may be contacted at graballand@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
**A1.12 Institute for Management Development (WCY)**

The Institute for Management Development is an research and educational organization based in Lausanne, Switzerland. As of May 1999, it can be reached at http:Ilwww.imd.ch.

The Institute for Management Development has published the World Competitiveness Yearbook since 1987. Until 1996, this was a joint effort with the World Economic Forum. We use data from the 1998 edition of the World Competitiveness Yearbook.

The World Competitiveness Yearbook analyzes the competitive environment in 47 countries. It is based on both objective data and surveys of perceptions. The survey questions over 4,000 local and foreign enterprises operating in the countries under analysis. Mean scores on the survey questions are reported in the yearbook for all countries. In Table A1.12 we list the questions included in the governance database.

<!-- Start of picture text --> Table A1.12 World Competitiveness Survey<br>Number Question<br>Domestic economy<br>1 y108 The parallel economy as an obstacle to business development<br>Internationalization<br>2 y230 Protectionism as an obstacle to imports from abroad<br>3 y231 Controls on foreign investors ownership of companies<br>4 y232 Obstacles to foreign bidders on public contracts<br>Government<br>5 y316 Real personal taxes as a burden to work initiative<br>6 y320 Improper practices in the public sphere<br>7 y321 Real corporate taxes as a burden to entrepreneurial activity<br>8 y324 Extent of tax evasion<br>9 y326 Legal framework as an obstacle to compettiveness<br>10 y328 Transparency: The government communicateit s intention s uccessfully<br>11 y329 Political system as an obstacle to development<br>12 y330 Exposure of public service to political interference<br>13 y331 Bureaucracy as an obstacle to business development<br>14 y332 Effective implementati o n f govemment decisions<br>15 y333 Custom's administration as a burden to intemabonal trade<br>16 y336 Price controls<br>17 y340 Competition laws as an obstacle to fair competiton<br>18 y341 Confidence in the fair administration ofjustice in the society<br>19 y343 Confidence among people that their person and property is protected<br>Finance<br>20 y420 Legal Regulation of Financial Institutions<br>Science<br>21 y720 Protection of intellectual property<br><!-- End of picture text --> 52
Table 1: ITT Effects: Skills

|||||||Loc|us of Con|trol<br>I|ncome Aspirations||
|---|---|---|---|---|---|---|---|---|---|---|
||(1)<br>Tracking|(2)<br>Price Mgmt.|(3)<br>Work Hours|(4)<br>Goal Setting|(5)<br>Grit|(6)<br>Internal|(7)<br>PO|(8)<br>Chance|(9)<br>Levels|(10)<br>Index|
|||||_Panel A: Midli_|_ne (6 mo_|_nths)_|||||
|ITT|0.319<sup>_∗∗_</sup>|0.472<sup>_∗∗∗_</sup>|13.507<sup>_∗∗∗_</sup>|0.340<sup>_∗∗_</sup>|1.014<sup>_∗∗_</sup>|-0.004|0.115|0.362|13807.09|0.19<sup>_∗∗_</sup>|
||(0.145)|(0.164)|(4.713)|(0.143)|(0.486)|(0.215)|(0.401)|(0.342)|(246678.64)|(0.08)|
||[0.099]|[0.050]|[0.050]|[0.089]|[0.109]|[1.000]|[0.990]|[0.683]|[1.000]|[0.089]|
|Observations|290|281|228|243|544|543|543|544|430|546|
|Control Mean|0.957|1.012|27.909|0.643|29.488|15.836|-12.914|-14.645|1504624.45|-0.10|
|Adj. R<sup>2</sup>|0.167|0.114|0.265|0.145|0.108|0.029|0.146|0.094|0.225|0.197|
||||_P_|_anel B: Endline _|_(18–24 M_|_onths)_|||||
|ITT|0.222|0.311<sup>_∗_</sup>|7.402<sup>_∗_</sup>|0.264<sup>_∗_</sup>|0.917<sup>_∗_</sup>|0.330|0.443|-0.224|-331680.85<sup>_∗_</sup>|0.12|
||(0.145)|(0.174)|(4.468)|(0.153)|(0.485)|(0.246)|(0.441)|(0.352)|(194343.19)|(0.08)|
||[0.485]|[0.455]|[0.485]|[0.485]|[0.406]|[0.485]|[0.495]|[0.525]|[0.485]|[0.485]|
|Observations|286|274|229|231|541|540|540|541|441|544|
|Control Mean|1.133|1.239|34.850|0.688|30.094|15.801|-12.121|-14.191|1577941.91|0.01|
|Adj. R<sup>2</sup>|0.060|-0.011|0.145|0.047|0.110|0.043|0.037|0.046|0.062|0.116|

_Note:_ Coefficients are ANCOVA estimates that control for the outcome at baseline, the respondent’s location, marital status, household size, number of children, age, network size and level of education. ITT shows traditional intent to treat effects of participating in SBS. Tracking is an index about record keeping for the business with a maximum value of 3. Price management is an index about setting prices, running promotions, comparing prices with competitors, and negotiating for better prices with suppliers with a maximum value of 4. Goal setting is an index about setting goals for the business over various time horizons with a maximum value of 3. Work hours is the number of hours the respondent typically works in her main business. Our measures of grit follow Duckworth, Peterson, et al. (2007) and Duckworth and Quinn (2009). We draw our locus of control measures from Levenson (1973). Internal, PO, and Chance is the dimension of the locus of control score. Positive values for Internal, PO and Chance provide evidence of improvements in locus of control measures independent of type. Index is an Anderson index of all outcomes using the swindex command in Stata. We winsorize the income aspirations variable at the 99th percentile. Values in columns marked with heading _Levels_ are values in UGX. We report White robust standard errors in parentheses. Romano-Wolf multiple hypothesis test q-values are presented in brackets. Q-values include the same controls as above and are computed within pre-specified families of outcomes.