rafmacalaba/datause-encoder-data huggingface dataset:
|**DOMAIN**||**INDICATOR OF FORMS OF EMP**|**OWERMENT**|
|---|---|---|---|
|**Sub-domain**|**National**|**Intermediary**|**Local**|
||•Diversity of national labor<br>organizations<br>•Percentage changes in labor<br>market composition per year<br>•Score of civil society<br>advocacy activity for labor<br>protection legislation<br>•Percentage presence in capital<br>intensive/high-skill positions<br>per social/ethnic/religious<br>group<br>•Percentage difference in<br>salary levels by ethnic/<br>social/religious group<br>•Number of industrial disputes<br>resolved equitably per year|•Score of effectiveness of local<br>labor organizations<br>•Diversity of local labor<br>organizations<br>•Number of collective bargaining<br>mechanisms/processes over wage<br>rates/employment conditions|•Score of control over employment/occupation<br>choices (4.53-4.55, 3.41-3.42)<br>•Percentage involved in household work (4.56)<br>•Score of time used for unpaid household work<br>and childcare (4.57-4.58)<br>•Score of division of labor and roles within<br>household (4.59)|
|**Goods**<br>(production/<br>consumption,<br>including basic<br>needs)|•Score of civil society<br>advocacy activity for<br>redistribution of productive<br>assets<br>•Score of civil society<br>advocacy activity for basic<br>needs provision<br>•Percentage awareness of<br>national market prices and<br>conditions<br>•Score of civil society and<br>state advocacy activity for<br>equitable access to markets<br>•percentage change in national<br>asset ownership per social/<br>ethnic/ religious group per<br>year<br>•percentage change in control<br>over national assets per<br>social/ ethnic/ religious group<br>per year|•Score of civil society advocacy<br>activity for (decentralized) basic<br>needs provision<br>•Number of local buyers of<br>products<br>•Number of local suppliers of<br>products<br>•Number of producer<br>cooperatives|•Score of perceived risk/threat of eviction (4.60)<br>•Score of protection from eviction (4.61)<br>•Score of influence of social characteristics on<br>asset ownership/access (4.62-4.63)<br>•Score of gender influence on inheritance rights<br>(4.64-4.66)|

77
acceptable quality range. However, it may also lead to dumping and cream skimming of insured patients or skimping on quality of care. If providers have multiple revenue sources, they may try to shift cost across different financiers (Schneider and Hanson 2007).

Empirical studies with rigorous evidence on impact of capitation payment, on the other hand, are rather limited (Moreno-Serra and Wagstaff 2010; Gosden et al. 2011). Even in the developed countries that have advanced significantly with various methods of paying providers, observational studies typically dominate rigorous evaluation in the literature. To illustrate the point, a recent search of multiple international databases on the impact of capitation, FFS, salary, and mixed system of payment yielded 332 seemingly relevant articles (Gosden et al. 2011). After the authors applied rigorous screening criteria to include only studies with randomized control trials, controlled before and after, or interrupted time series design, eight papers were selected, reporting on four impact evaluation studies (two in the United States, one in Canada, and one in Denmark). The authors commented that the most important conclusion from the review is the scarcity of good evidence, presumably due to the practical difficulty of having robust experimental design for policy intervention such as the method to pay providers (Gosden et al. 2011).

The limited evidence found in the review by Gosden and colleagues nevertheless confirms common wisdom on the impact of capitation versus FFS. Specifically, FFS was found to result in more contacts for primary care, curative, and specialist care. There was no evidence of effects on patient health status.

Outside the developed countries, studies evaluating the impact of provider payment typically rely on small samples, non-experimental design, or qualitative information. An exception is a recent cross-country analysis by Moreno-Serra and Wagstaff (2010). The study 5
<!-- Start of picture text --> 15.0%<br>10.0%<br>5.0% A<br>0.0% : : , mmm Savings reaction<br>ele) 2006 2008 ; @mm Expenditure reaction<br>0% mam Non-oil revenue reaction<br>—— Oil shock<br>-15.0%_ PO<br>-20.0%<br><!-- End of picture text -->
23

**Figure 12:  Belief that privatization has been beneficial in their country (%)**

<!-- Start of picture text --> Argentina<br>Uruguay<br>Paraguay<br>Chile<br>Colombia<br>Bolivia<br>Mexico<br>Guatemala<br>Nicaragua<br>Panama<br>Peru<br>Costa Rica<br>Honduras<br>El Salvador<br>Brazil<br>Venezuela<br>Ecuador<br>0 10 20 30 40 50<br>Percent<br><!-- End of picture text --> Source: Latinobarómetro, 2002

- In Sub-Saharan Africa, a recent AfroBarometer survey of 15 major countries undertaking economic reforms between 1999 and 2001 found that less than 35 percent of the population preferred privatization to state ownership -- ranging from 30 percent or less in Ghana, Lesotho, Mali, Uganda and Zambia to 40 percent or more in Botswana, South Africa, and Tanzania (AfroBarometer 1999/2001). In Ghana, for example, 70 percent of respondents opposed the privatization of public enterprises, with 50 percent “strongly” opposed. In Zambia, focus group researchers found people to be “deeply attached to public ownership and the public provision of employment” (Slattery 2004);

- In Eastern and Central Europe, a survey of 16 countries (excluding Central Asian states) found that 52 percent of the population between 1998 and 2001 supported private ownership over state ownership, with support being the highest (over 80 percent) in the Baltic states (New Democracies Barometer 1998, 2000). Yet, in Russia, 70 percent of people surveyed felt they were worse off after privatization and preferred state ownership, while in countries such as Belarus, Moldova and Ukraine less than 40 percent of the population favored privatization;

- In East Asia, a survey of eight countries (excluding Vietnam, Laos and Cambodia) found that only a third of the population surveyed favored privatization over state ownership (Asia Barometer 2001-02).  While support was quite high in Korea (60 percent), it was low in China (17 percent), Thailand (33 percent), and the Philippines (39 percent).
_Fiscal Crisis in Central Europe_ 13 We chose the periods so that they would be as representative as possible, for each country, of the fiscal performance under the two distinct regimes.'<sup>3</sup>

# **111.1. The Traditional View of the Fiscal Crisis**

Although the direct and indirect budgetary consequences of transition are numerous and complex, the heart of the matter, according to the "traditional" view, seems to be as follows. We take two periods (1985-87 or. 1986-88 and 1991-92) that can be representative of pre- and posttransformation fiscal performance in central Europe (table 3.1).

Table 3.1 Poland, Hungary and Czechoslovakia: Evolution of Deficit , 1986-1992.

|(Percent of GDP)||Poland|||Hungary||C|zechoslova|kia|
|---|---|---|---|---|---|---|---|---|---|
||1985-87|1991-92|| Change|1986-88|1991-92|Change|1986-88|1991-92|<br>Change|
|General Govt Balance|-0.4|-5.4|-5.0|-2.2|-5.3|-3.0|-1.7|-2.8|-1.1|
|Revenues|48.2|41.3|-6.9|61.3|53.3|-8.0|64.6|52.8|-11.9|
|Profit taxes|11.1|5.8|-5.3|10.5|4.0|-6.5|18.6|12.7|-5.8|
|Tumover Taxes I/|11.5|7.2|-3.3|17.3|13.4|-4.0|15.8|12.7|-3.1|
|Expenditures|48.5|46.6|-1.9|63.5|58.6|-5.0|66.4|55.6|-10.8|
|Transfers to H'holds|9.9|19.7|9.9|13.7|24.4|10.7|11.8|16.3|4.4|
|Subsidies|16.2|5.0|-11.2|15.6|5.6|-9.9|26.3|7.9|-18.5|
|Interest|0.9|2.2|1.3|1.8|3.9|2.1|0.0|0.8|0.8|
|Capital Expenditures|5.3|3.0|-2.3|8.0|6.3|-1.7|2.0|4.9|2.9|

Sources: Ministries of Finance; World Bank staff estimates. 1/ In Hungary it includes VAT,

> 13 In Poland. for example. the data for 1989 and 1990 are highly distorted by two phenomena that make their interpretation hopeless: the hyperinflation of 1989 and the subsequent increase in paper profits in enterprises in 1990 (see Barbone, 1992 and Schaffer, 1992). We also checked the sensitivity of the results with respect to the period chosen, and found that the broad picture is not altered by considering different periods.
# **1. Introduction**

As response rates are related to the risk of non-response bias,<sup>1</sup> several techniques have been developed to increase survey response rates, ranging from monetary incentives to personalized invitations.<sup>2</sup> Also telephone reminders are used as a way to boost response rates.

A number of studies have investigated the impact of phone reminders on survey response rates, at least dating back to Roscoe et al (1975). Somewhat surprisingly however, all studies are conducted in the context of postal surveys. This research note aims to complement this field of study by investigating the impact of phone reminders in the context of a web-survey, targeting professional staff in an international organization, i.e., the World Bank. The present paper is related to the work of Smets and Bogetić (2018) who provide a detailed discussion of the underlying survey and its design, methodology and implementation. To the best of our knowledge, this is the first study to examine survey response rates in such a setting.

We randomly assigned the reminder treatment to 248 survey participants. During the telephone call we briefly explained the purpose of the reminder, verified whether participants already filled out the survey and offered to resend the survey link immediately after the call in case they had not.

> 1 Response rates set bounds to the maximal non-response bias. However, it is important to note that also other factors such as measurement error, coverage error or editing error may bias survey estimates (e.g., see Davern, 2013; Meyer et al, 2015).

> 2 See Edwards et al (2009) or Fan and Yan (2010) for a recent systematic review of the methods to increase response rates in postal and web-based surveys.

2
prior to this study. Prior to this study, travel outside of the village cluster was infrequent and most transport was pedestrian or by bicycle. This particular market town offers dozens of stores providing domestic goods and agricultural inputs. There is also a weekly market in the town that brings traders from disparate areas to sell their goods.

In the study, after a baseline survey, households were randomly assigned to one of seven bus pass categories, with each category assigned a unique price between zero and 500 Malawi kwacha (US$3.57). Over the course of the project, take up of the bus was recorded (See Goldberg et al., 2010 for a full set of results).

There were significant differences in take up based on the price level assigned to a household. Even small positive prices (far below the marginal cost of a ride) lead to substantial declines in demand for a bus ride.<sup>6</sup> The experiment demonstrates that households from villages are not willing or cannot afford to pay more than the break-even point for the bus operator<sup>7</sup> . There are two important policy implications of these findings. First, if a bus service is not subsidized, a road in relatively good condition may continue to be used mainly by bicycles and pedestrians. Second, if subsidies are not possible in most rural areas in Malawi (or more generally in SSA), there may be a need to adjust more carefully investments to the potential demand and link it to the types of services provision used in the areas.

The second section describes the experiment protocol and data. Then, results are presented in terms of take up and potential revenues for a bus operator at different prices. The fourth section discusses the policy implications of the results and the final section concludes and presents some ideas for future research in this area.

# **2. Description of the data and experiment**

> 6 This concurs with findings from Hine and Rutter (2000), who found out that, for these reasons of affordability of transport services, the poorest segment of rural areas populations continue to walk and do not necessarily benefit from rural roads investments.

> 7 Results could have differed if the experiment would have been longer (over a year). However, we also think that results over six months are significant.

5
<!-- Start of picture text --> Food Deprivation - by State in Food Deprivation - by State in Food Deprivation - by State in<br>North Central - MICS North East - MICS North West- MICS<br>80% 80% 80%<br>70% 70% 70%<br>60% 60% 60%<br>50% 50% 50%<br>40% 40% 40%<br>30% 30% 30%<br>20% 20% 20%<br>10% 10% 10%<br>0% 0% 0%<br>child 0-4 child 0-4 child 0-4<br>Benue FCT Abuja Kogi Kwara Adamawa Bauchi Borno Jigawa Kaduna Kano Katsina<br>Nasarawa Niger Plateau Gombe Taraba Yobe Kebbi Sokoto Zamfara<br>d) e) f)<br>Food Deprivation - by State in Food Deprivation - by State in Food Deprivation - by State in<br>South East - MICS South South MICS South West- MICS<br>80% 80% 80%<br>70% 70% 70%<br>60% 60% 60%<br>50% 50% 50%<br>40% 40% 40%<br>30% 30% 30%<br>20% 20% 20%<br>10% 10% 10%<br>0% 0% 0%<br>child 0-4 child 0-4 child 0-4<br>Abia Anambra Ebonyi Enugu Imo Akwa IbomDelta BayelsaEdo Cross RiverRivers Ekiti Lagos Ogun Ondo Osun Oyo<br><!-- End of picture text --> Source: Author’s estimates based on MICS 2016/17 Note: Individuals with missing age were dropped from the analysis. Total refers to all individuals with known age.

Figure 20 displays a further breakdown of the state level estimates by gender and sector. While evidence from Bangladesh and India (see Khatun et al. 2004; Pande, 2003) as well as different development programs suggests that girls are disadvantaged compared to boys in terms of nutrition, the estimates based on the 2016/2017 MICS show that only in certain states, such as urban Borno and Kebbi and rural Lagos such hypothesis is found to be in line with Bangladesh and India. But in most cases, evidence for the opposite is found. The finding that boys are in many states more likely to be food deprived than girls is though consistent with results of girls and boys overall based on the National Nutrition and Health Survey 2018 data discussed in NBS (2018).This finding is also consistent with findings from a meta-analysis using DHS data from 10 Sub-Saharan African countries by Wamani et al. (2007).Also, there are sizeable differences between urban and rural findings within states in the north, which may call for further research. These estimates should however be treated with caution since a detailed breakdown has severely reduced sample sizes.

32
The black market premium on foreign exchange (BMP) measures restrictions on the - availability offoreign currency, which are usually imposed in regimes with multiple exchange rates and misaligned official rates. As Table 4 shows, by 1995 most countries in the region had negligible blackmarket premium rates; that is, their official exchange rates equaled their market rates, except for small differentials due to transaction costs. The black-market premium on foreign exchange, persistently large in the 1980s, had dropped dramatically in the early 1990s as restrictions on foreign currency transactions were abolished; mostly, this occurred either because a regime of flexible exchange rates was adopted (asin Peru) or because a fixed exchange-rate system was made credible (as in Argentina). Even Guyana, Haiti, and Suriname, which had BMPs of well over 100 percent in the 1980s and early 1990s, had seen a sharp drop in their respective black-market premia (to less than 5 percent in the case of Guyana). Of the larger countries, only Venezuela and Paraguay had BMPs of more than 10 percent in 1995,

### B. Financial Development

.

Ample evidence from recent empirical studies, including firm-level, industry-level and countrylevel studies, indicates that well-functioning financial markets promote long-run economic growth."” The relationship between finance and economic activity goes, then, beyond the effect of financial instability on short-term macroeconomic fluctuations. Previous literature had emphasized the recessionary impact of financial crises (currency and bank runs) but had not given to financial development a positive, causal role in long-term economic activity. At present, the growing consensus is that the development of financial institutions and markets promotes more efficient investment, and thus, higher long-run growth.!* i . Well-functioning financial systems act positively on economic efficiency through different channels. They facilitate the trading, hedging, diversifying, and pooling of risk; they mobilize savings, and thus, allocate resources for investment. Financial systems also monitor managers and exert corporate control by allowing the market to price companies according to their expected performance;

## 7 See Levine (1997).

# oe

|

"8 See McKinnon (1973), Atle and Jovanovic (1993); Demirguc-Kunt and Levine (1996); Hubbard, Kashyap, and Whited (1995), King and Levine (1993); and Roubini and Sala-i-Martin (1992).

7
**Table 31: Cruise Visitor and Cruise Visitor Spending in 2012**

|**Year**|**Country**|**Cruise**<br>**Visitors**<br>**(in**<br>**Thousands)**|**Total**<br>**Visitors (in**<br>**Thousands)**|**Cruise**<br>**Visitors**<br>**(% of total**<br>**visitors)**|**Cruise**<br>**Visitors**<br>**Spending**|**Total**<br>**Visitors**<br>**Spending**<br>**(in**<br>**Millions)**|**Cruise Visitors**<br>**Spending**<br>**(% on total**<br>**spending)**|
|---|---|---|---|---|---|---|---|
|2012|Antigua & Barbuda|608|855|71|40.4|319|13|
|2012|Bahamas, The|4,440|5,862|76|320.8|2,058 ***|16|
|2012|Barbados|727|1,263|58|45.7|274 ***|17|
|2012|Belize|682|959|71|51.9|264 ***|20|
|2012|Dominica|336|410|82|16|113.8|14|
|2012|Dominican Republic|263|4,826|5|17.5|4,209 ***|0.40|
|2012|Grenada|320|433|74|13.2|121.6|11|
|2012|Jamaica|1320|3,306****|40|89.5|2,001 ***|4|
|2012|St. Kitts and Nevis|632|736|86|65.7|95|69|
|2009|St. Lucia|646|924|70|40.8|337.3|12|
|2012|St. Vincent and the<br>Grenadines|66|140|47|1.7|94.1|2|
|2009|Trinidad and Tobago|102***|488***|21|2.3|393 ***|6|

_Source: Cruise Industry News Annual Report (2012). ** Data from ECCB (2013)._ _***Data from UNWTO (2010)._ _****Data From Jamaica Tourist Board (2012)._

# _ii. Cruise Ship Visitors vs. Stay-over Visitors_

The Caribbean cruise industry has shown substantial growth, typically growing faster than the stay-over arrivals for most of the countries. St. Kitts and Nevis has the highest proportion of cruise ship visits, with cruise ship visits representing 86 percent of their total visits, followed by Dominica with 82 percent (Figure 32). St. Vincent has a more balanced division between stay over and cruise visits, with stay over visitors dominating with 53 percent.

In the Dominican Republic, Jamaica, and Trinidad and Tobago, stay over visitors dominate the tourism market. In the Dominican Republic, cruise visitors represent only 5 percent of their total visitors. The Bahamas and Barbados have the highest number of cruise passenger visits in the region. In The Bahamas cruise visits dominate stay over visits with 76 percent of the market. On the other hand, cruise visits represent only 58 percent of total visits for Barbados.

73
THE CENTRAL AFRICAN REPUBLIC’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE The CAR’s infrastructure spending needs, at 17.5 percent of GDP (using 2009 GDP), are among the average level for Central African countries and lower than comparable fragile states. Capital investment would absorb around 10 percent of GDP, somewhat less than what China invested in its infrastructure during the mid-2000s. Spending needs for O&M account for around 7 percent of the CAR’s GDP (figure 16).

Spending needs in the transport sector are mainly driven by needs in the road sector, in particular in capital expenditure. Whereas road needs account for $158.2 million per year, needs for the air transport sector are only $1.5 million per year (table 16).

**Figure 16. Infrastructure spending needs in the regional context**

<!-- Start of picture text --> As percentage of GDP<br>SSA<br>Fragile states<br>Low income countries<br>Resource-Rich<br>Middle income countries<br>DRC Congo, Dem. Rep.<br>Niger<br>Congo, Rep.<br>Chad<br>CAR<br>Rwanda<br>Sao Tome and Principe<br>Seychelles<br>0 10 20 30 40 50 60 70<br>% of GDP<br>Capex O&M<br><!-- End of picture text --> _Source:_ Foster and Briceño-Garmendia 2009. _Note:_ O&M= operations and maintenance; CAPEX = capital expenditure; GDP = gross domestic product; SSA = Sub-Saharan Africa; the CAR = Central African Republic.

To ensure regional connectivity, the CAR must have access to the Port of Douala. National connectivity is provided by a transport network that links each country’s provincial capitals and cities with a population of at least 25,000. High capital expenditure on transport is justified by substantial upgrades of the road sector ($81.2 million per year). O&M needs are calculated assuming that all transport infrastructure is maintained in fair condition.

**Table 16. Transport needs**

<u>$ millions per year</u>

||Improve<br>condition|Upgrade<br>category|Expand capacity|Capital|Operations and<br>maintenance|Total|
|---|---|---|---|---|---|---|
|Roads|8.2|81.2|0.2|89.6|68.6|158.2|
|Regional|1.4|42.5|0|43.9|17.9|61.8|
|National|0.3|35.4|0.2|35.9|14.3|50.2|
|RAI|0.3|3.3|0|3.6|32|35.6|
|UAI|6.2|0|0|6.2|4.4|10.6|
|Airports|0|1|0|1|0.4|1.5|
|Total|8.2|82.2|0.2|90.6|69.1|159.7|

_Source:_ Carruthers, Krishnamani, and Murray 2009. _Note:_ RAI= Rural accessibility index; UAI= Urban accessibility index 37
find positive peer effects from social ties. In line with the results by McKenzie and Puerto (2021) and contrasting those in Cai and Szeidl (2022) and Bakhtiar, Bastian, and Goldstein (2022), our results suggest that successful women entrepreneurs generate positive economic spillovers.

Combined, our results show that building skills can be an effective tool for improving economic inclusion among ultra-poor, rural women. We find that skills increase the likelihood that women in our sample independently generate and control income, and improve their resilience to shocks. Although the results we observe are far from transformative for poverty alleviation or private sector development, they provide key evidence on the importance of skills in larger efforts to promote women’s economic inclusion.

# **2 Background and Context**

Based on the 2018 Living Standards and Measurement Survey (LSMS) in Uganda, 74% of rural women are employed in some form of productive activity (including paid work, self-employment, and unpaid work in family businesses). Thirteen percent of rural women engage in self-employment. In central Uganda, the region where our study is based, average monthly household expenditures are UGX 678,876 (USD 172.52 with a median of UGX 504,966) per household, and the median household size is four.

Although our partner implements its programs throughout Uganda, the women in our sample reside in five communities in central Uganda. Our implementing partner selected all study locations based on conversations with community leaders, their evaluation of the economic needs of the communities, and their estimate of the population of women who might be interested in participating.<sup>9</sup> Of the five communities where we worked, four are rural and

> man and Magruder (2012) show that women are less likely to get job referrals than equally qualified men.

> 9Allowing our partner to select the study locations precludes random site selection; however, we argue that it yields representative study sites given that the program we study and others like it are unlikely to work in communities that are uninterested in participating or otherwise unable to participate.

8