rafmacalaba/data-use-mentions-extended huggingface dataset:
.._<br>_. . . . . _.._. . ._..|_._|
|Source: The Moscow Longit<br>Hous|ehold Survey in Dec|-1994 and Jan-1996.|

Some conclusions from an analysis of the data in Tables 1.9-1.11 follow.

- the concentration of privatized housing in the center of Moscow continued in the period under examination. This was largely determined by the development of the housing market, which in turn was driven by the consolidation of communal apartments (located almost exclusively in the center of the city) accompanied by their transition from municipal to private ownership (Table 1.10);
The baseline data collection for the impact evaluation of the PI/BSED training experiment began in November 2015 and ended in April 2016 as interviews were done on a rolling basis before the entrepreneurs attended a training batch. As a first step, enumerators phoned each female entrepreneur in the list to establish the existence and location of the business since WEDP registration data were somewhat outdated. Baseline data were collected over a 6-month period to tie-in with the implementation of all the training rounds. For each training round approximately 50 women assigned to both the PI and BSED treatment groups were interviewed for the baseline survey and then once the interview was complete the enumerator told the respondent that they were to be offered a training based on the randomization result. Enumerators from the survey company pitched the benefits of the training to the WEDP clients who were invited to attend a training using fliers, a lottery, and successful case studies as examples to motivate take-up among the invited group of entrepreneurs. A baseline survey was administered to the control group concurrently with the treatment groups but when the interview was complete no training was offered.

The follow-up survey was conducted between May and September 2017, approximately one and a half years after the training was received. The timing of the interviews attempted to mimic the timing of the baseline surveys by visiting localities of respondents who were surveyed first during the baseline survey and then moving to localities in sequence. All rounds of data collection included questions on household demographic characteristics, socioeconomic status, business performance measures, business practices and extensive questions on a range of entrepreneurial and psychological characteristics.

# **3.1.3** **_Trainer Surveys_**

The trainer surveys targeted teachers of six TVET colleges and the TVET agency in Addis Ababa who had been trained as trainers for both PI and BSED training. The interviews were conducted by two trained enumerators between August and October 2015 before implementation began. The original trainer sample was 29 trainers but only 21 trainers (5 PI, 16 BSED) who remained throughout the rounds are included
average, while unemployment rates were much higher. Except for Spain and Italy, most countries in Western Europe and North America had higher employment and lower unemployment rates than Latvia.

**Figure 6  Activity and Unemployment Rates a) EU Accession and Candidate Countries (2002), age 15+**

<!-- Start of picture text --> 22<br>PL<br>20<br>SK<br>BG<br>18<br>16<br>LT<br>14<br>LV<br>12<br>EE Employment rate<br>10<br>59-60<br>RO<br>8 CZ 53-56<br>SI<br>HU<br>6 50-52<br>4 CY 46-49<br>2 40-45<br>48 50 52 54 56 58 60 62 64<br>Activity rate<br>Unemployment rate<br><!-- End of picture text -->

**b) Baltic Countries, EU-15 Average, and Selected OECD Countries (2002), age 15-64**

<!-- Start of picture text --> 16<br>LT<br>14<br>LV<br>12 ESP<br>EE<br>10<br>ITA FRA FIN<br>DEU<br>EU Employment, age15-64<br>8 CAN<br>BEL 73-78<br>6 USA 69-72<br>SWE<br>DNK<br>IRL 64-66<br>NOR<br>4<br>NLD 60-62<br>2 56-59<br>60 70 80 90<br>Activity rate, age 15-64<br>Unemployment rate, age 15-64<br><!-- End of picture text --> _Note:_ UK and Portugal have virtually identical indicators as Sweden and US respectively. _Source_ : Canstat 2003/2, national statistical offices of Estonia, Latvia,
||Italy, the<br>Netherlands,<br>Spain, and<br>United<br>Kingdom||||of welfare, even when<br>usage demand is held fixed|
|---|---|---|---|---|---|
|Austin & Dinan<br>(2005)|United States|2001|Prices, unit sales, and fuel-<br>economy ratings for<br>vehicles sold|Simulation model|A gasoline tax would<br>produce greater immediate<br>savings by encouraging<br>people to drive less, and<br>eventually to choose more-<br>fuel-efficient vehicles|
|Jacobsen<br>(2013)|United States|1997-2001|Household demand data<br>from National Household<br>Travel Survey and supply<br>data, vehicle characteristics|Simulation model|Dynamic impacts in the<br>used car market comprise<br>nearly half the gross<br>welfare cost of corporate<br>average fuel economy and<br>fall disproportionately on<br>low-income households|
|Anderson &<br>Sallee (2016)|United States|NA|NA|Theoretical Model|Standards are substantially<br>less efficient than a fuel<br>tax|
|Parry & Small<br>(2005)|United States<br>and United<br>Kingdom|NA|VA|Theoretical Model and<br>Empirical Estimations<br>based on parameter<br>values from the<br>literature|A direct tax on amount of<br>travel (vehicle-miles)<br>performs better|
|Ito & Sallee<br>(2018)|Japan|2001-2013|Characteristics of new<br>vehicles sold|Simulation|Attribute-based regulation<br>is an imperfect substitute<br>for flat policies with<br>compliance
Costs associated with registering, along with taxes and meetings or inspections with government officials were reported as the main reason for 12% and 3% of businesses, respectively. Overall, the primary reasons for not registering appear to be related to either a lack of benefit or the presence of additional costs for over 75% of businesses. On the other hand, a lack of information does not appear to be the driving force behind a reluctance to formalize, cited by less than 13% of businesses as their main reason for not registering. This is consistent with findings from studies based on field experiments that show limited formalization following the presentation of information pertaining to the registration process (De Mel et al., 2013; Benhassine et al., 2018; Campos et al., 2018). It is therefore unsurprising that under 15% of businesses report having considered formally registering their businesses in the three years prior to the Informal Sector Enterprise Survey interview.

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Using the SD approach, our simulated median gains in production for different crops range between 29.57% and 47.96% for barley, 71.87% and 76.35% for millet, 89.38% and 107.99% for maize, 105.64% and 108.09% for rice, 59.99% and 89.49% for sorghum, and 27.97% and 38.96% for wheat. The corresponding gains using the SRHS approach are between 33.28% and 41.87% for barley, 106.64% and 123.26% for maize, 112.56% and 114.64% for rice, 93.38% and 129.42% for sorghum, and 53.08% and 60.11% for wheat. Our results are more or less consistent despite considering a combination of conditions imposed.

# **7.2 Considering a Different Dataset for Water Supply**

Our groundwater supply measure comes from Rodella et al. (2022). We test if our results remain robust to using a different dataset for water supply, especially because groundwater volume computations tend to be probabilistic in nature. We use the Groundwater Storage Map in the digital groundwater maps of Africa<sup>10</sup> collected by MacDonald, Bonsor, ́O Dochartaigh, and Taylor (2012) to obtain a measure of groundwater storage.

In our main simulations, we rely on the volumes of groundwater associated with the local shallow groundwater aquifer classification. However, the classification system we used—including the “local shallow aquifer” classification—is not consistent with hydrogeological classifications of groundwater aquifers. Thus, we consider the subset of aquifers that closely resemble the characteristics of local shallow aquifers. These aquifers include the following:

- Unconsolidated Sedimentary (U): These aquifers consist of loose sediments, such as sand and gravel, which allow water to flow more easily.

- Consolidated Sedimentary Fracture (CSF): These
Quad (Canada, EU, Japan and US) countries which account for the bulk of developing country exports to developed country markets. These analyses were supplemented by informnation gathered from TPRs of major developed countries as they relate to market access conditions for developing countries.

# A. Tariffs

# 1. Overall Averages

The results of the 'URA on the MFN tariffs of the developed countries have been studied extensively in previous studies whose main findings will be summarized here (Martin &Winters, 1996; UNCTAD/WTO, 1997;OECD, 1997). Broadly speaking, tariffs on imports of manufactures into the major industrial countries markets were reduced by an average of 40 per cent from a trade weighed average of 6.3 per cent to 3.8 per cent with the reductions to be phased in over five years and the first instalnent to be put in place on January 1, 1995.19 Countries have reduced their tariff rates accordingly since then. Moreover, in 1997, following the Information Technology agreement, duties on a number of products in this sector were reduced to zero on an MFN basis (See Finger and Schuknecht, 1999).

The tariffication of various measures of support and protection in the agricultural sector has resulted in substantial increases in the initial tariff levels applicable to a wide range of agricultural products in some major markets. Thus, the average applied MFN rate for agricultural commodities (production weighted) in 1996 ranged from 7.9 per cent in the U.S, and 10.7 per cent in the EU, to 0.5 per cent in Australia (OECD, 1997, Table 3.1). Subsequently, developed countries are to reduce agricultural tariffs by 36 per cent across the board, at the same time as access for agricultural products is being enhanced through reductions in domestic support measures.

> 'sSee Article 15 of the.UR Agreement on the Procedures for Implementation of GATT Article VI.

> '<sup>9</sup> The EU advanced from January 1,
impacts on home environments and children’s language development, lasting well beyond the conclusion of the program.

Our data come from a large-scale field experiment with two treatment arms and a control group. Parents in the control group have access to regular health preventive services offered by the primary health care system.<sup>2</sup> Parents in the first treatment arm (NEP-Basico, or NEP-B) are invited to participate in a group-parenting program where only caregivers are allowed to attend the meetings (no children), consisting of 6 to 8 weekly group sessions with 6-12 caregivers. The second arm (NEP-Intensivo, or NEP-I) complements the caregiver-only sessions with two additional structured sessions where children participate together with their parents, and which are focused on the importance of language and play. The target population are parents with children aged 0 to 5 who are enrolled in the public health system, especially those who are particularly vulnerable, such as adolescents, single parents, and geographically or socially isolated households.

The duration of the intervention is short, and our focus is on its medium-term impacts, measured long after program completion. A full program cycle of 6-8 sessions lasts only for two to three months. We administered a baseline survey in 2011, right before parents in the treatment groups received the invitation to participate in the program, and re-surveyed the same parents and respective children in 2014, three years after the conclusion of these households’ participation in

> 2 The national child health care program includes services such as developmental screenings, vaccinations, nutritional supplementation and regular check-ups until the child is 6 years old.

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work in the private sector, they will deal with me in a good way, they will offer me a good salary and even the benefits they will provide will be comfortable. They provide benefits, money and even the moral and psychological way of dealing is better in private sectors.” A male youth from Khartoum who had a university degree but did not have a job said, “Private sector for sure. Private sectors are definitely better financially that is the first thing, plus you can transfer and move from one company to another more easily than in public sectors.” A woman from Madani who had a university degree but did not have a job said, “Because the private sector is somehow affording you the specifications you are seeking nowadays. If you are seeking promotions and retirement pension and so on, you may find it at a governmental job. Yet the private sector nowadays provides you what you wish for. Most of the people are aiming at travelling abroad ... So, the private sector is more comforting in that regard if I’d say so.” While a female youth from Madani who had a university degree but was not working said, “I prefer the private sector. First of all, because of the salary, it’s better. Also, in the private you can increase your relations but the government the field is kind of limited.”

# **Low access to banking and finance limits entrepreneurial activity**

One of the main obstacles to improving Sudanese women’s economic empowerment is that assets and credit are difficult for Sudanese women to obtain. This was noted in the 2007 Women Empowerment Policy document, which identified six “areas of concern,” one of which was “economic empowerment,” and where it was specifically noted that investment policies favor large-scale projects over medium- and small-scale projects in which women are more likely to become engaged. A 2016 study based on a crosssectional survey of 250 women from Sinnar State reaffirms this observation, showing that 79
taxed in previous years. By comparing the red and blue series, our calculations indicate that Argentina could have collected approximately 75% more wealth tax revenue in 2015 if these assets had been reported as they should have been. In terms of the total revenue loss for the period spanning from 2002 to 2015, this amounts to USD 8.4 billion or 1.8% of GDP in 2015. Interestingly, the penalty for participating in the 2016 amnesty contributed roughly 1.8% of GDP. This suggests that Argentina, through the amnesty fee, managed to recoup the entire sum of forgone revenue from the period spanning 2002 to 2015.

Additionally, the improved compliance with the wealth tax should lead individuals who had previously concealed their assets to declare the _return_ of these assets, leading to an increase in reported capital income. According to Argentine law, individuals are required to report both their foreign and domestic income in their personal income tax returns. They are subject to taxation based on their worldwide income and may obtain a foreign tax credit for taxes paid on income from foreign sources. Consequently, we anticipate that asset disclosures can potentially raise capital income taxation.

To gauge the impact on compliance with the capital income tax, we turn to the personal income tax data. Since participants in the tax amnesty disclosed their previously undeclared assets held as of July 22, 2016, and the amnesty continued until March 2017, we would expect reported capital income to start increasing from 2016 and fully reflect the asset disclosures by 2017.

Figure 11(a) compares the number of taxpayers reporting some capital income, while Figure 11(b) compares the total reported capital income amount. The data shows no significant changes in these series before 2016, followed by a substantial increase in reported capital income starting in 2016. Specifically, the number of taxpayers reporting some capital income doubled, and the capital income tax base tripled during this period. In contrast, the other three sources of income—wages, rental income, and business income—
roughly 2 and 3 weeks’ worth of consumption. Hence, even though the data are from 2-week transaction diaries, for most items the relevant time frame for storing and consuming a bulk purchase is substantially shorter. Bulk purchasing in this setting involves avoidance of very small quantities, rather than stocking up on several weeks’ or months’ worth of an item.

# **Liquidity constraints**

A natural hypothesis for the financial losses in our data is that people would like to take advantage of bulk discounts, but they lack the liquidity to do so. Prior work has argued that poor households may pay higher unit prices than wealthy households because binding liquidity constraints prevent the poor from buying in bulk. This is an intuitive idea. Credit constraints are well understood to be an important barrier to investment in low-income countries, so it is reasonable to wonder whether they are a binding constraint here.

For a liquidity constraint to drive small-quantity purchasing, a household must be unable to gather the cash needed to buy _qmin_<sup>_∗_,theminimumquantityrequiredtobuyat</sup> 19
and a representative of the Shariah Council to oversight consumers‟ interests.

The most recent survey of Takaful insurers carried out by the Middle East Insurance Review show that Malaysia and the GCC region continue to be the main areas of activity. Summary MENA data is shown in Appendix Table 1.

# **Appendix Table 1**

|**Country**|**No. Takaful Insurers**|
|---|---|
|Algeria|1|
|Bahrain|9|
|Egypt|6|
|KSA|26|
|Kuwait|13|
|Jordan|3|
|Lebanon|1|
|Oman|1|
|Qatar|6|
|Syria|2|
|Tunisia|2|
|Yemen|2|

Source: Middle East Insurance Review 41
2.0|10.5|9.6|1.1|1.0|35.7|54.6|2.1|0.4|12.3|1.3|
|**RU**|453,193|13,369|7|14|25|49|4.4|1.7|9.5|9.4|1.4|1.3|39.3|56.2|3.5|0.6|19.7|2.3|
|**SI**|50,483|364|7|22|18|62|9.8|1.5|11.5|11.4|2.0|1.4|65.1|48.7|4.9|1.2|14.6|3.0|
|**UA**|125,312|2,637|11|15|22|41|2.8|0.4|9.4|8.5|1.2|1.2|54.5|75.2|2.4|0.2|10.4|0.5|

_Note: *Labor productivity is measured as the logarithm of operating revenues per worker. Source: Author’s calculations using WB BOS database and ORBIS._ Some authors argue that firms owned by the state are not always operating under a profitmaximizing behavior as they may pursue public mandates (Matuszak & Kabaciński, 2021). Hence, some performance differentials are expected (Lawson, 1994) (Bozec, Breton, & Coté, 2002). Previous studies have tried to account for commercial and non-commercial mandates assigned to SOEs. However, there are two caveats on former attempts to do so.

First, most studies are country-specific hindering external validity and comparability of the findings. Second,
2

# **1. Introduction**

Since 2000, banking credit to the private sector has declined in real terms and as a share of Egypt’s GDP. During the past decade the banking system witnessed recapitalization of public banks and two different cycles of external capital flows. Capital flowed in until mid-2008 when the global financial crisis erupted, and flowed out until mid-2009. As global risk appetite recovered, capital flowed back in until the last quarter of 2010, when global capital markets tightened again and the January 2011 uprising accentuated the capital outflow.

Aside from the capital flows’ stop-go cycles, public finance deficits and financing needs created an expansion-contraction-expansion cycle that affected bank credit to the private sector. Output fluctuations with episodes of high growth as well as output contractions affected the private sector’s demand for credit. This paper describes how these factors interact to produce a decline in credit to the private sector.

The paper first examines the stylized facts of bank credit to the private sector in an international context, benchmarking the expected amount of private sector credit for a country with Egypt’s characteristics (using FINSTAT, a benchmarking tool developed by the World Bank). It also explores the evolution of banking sector sources and uses, based on its aggregate balance sheet and similar exercises performed for Latin America and the MENA regions (Barajas et al., 2002; 2010).

The central objective of the paper is to estimate credit supply and demand equations in line with the abundant empirical literature on the topic. Some studies examine the issue assuming that prices are flexible enough to clear the market by equalizing supply and demand. Others assume that prices are not perfectly flexible and estimate demand and supply equations using the short-side rule (i.e. that observed credit quantities can occur on the demand or supply schedules, whichever is smallest, at a given interest rate). Assuming an excess supply or demand at a given point, the researcher infers the likelihood of the observed quantity being on the supply or demand regimes. Empirical
# **6. Effects on son and fertility preferences of couples by housing ownership status**

A last question to consider is whether groups that do not have substantial assets or wealth exhibit the differential effects by religion, sibling composition and time that have been associated with the change in Islamic inheritance law. If son preference among Muslims is truly influenced by the Islamic inheritance exclusion rule, the effects observed among couples who have little or no estate should be small or insignificant.

In Indonesia, housing, land and durable goods are the most important assets in an individual’s estate (Cammack 1999b). The 2007 DHS collects information on the ownership status of the dwelling unit and on the possession of durable goods, but not on land ownership or income. Land ownership can only be imperfectly inferred for men and women who worked in agriculture during the 12 months preceding the survey (25 and 39 percent of the sample, respectively). Only they were asked whether they worked on their own or someone else’s land. Wealth quintiles are included in the dataset and are reported for all observations. However, they are constructed based on an index that aggregates household possessions, dwelling characteristics, source of drinking water and other measures. The elements of the index are possibly endogenous to the sex composition and size of the family.<sup>15</sup> In order to maximize sample size and minimize potential endogeneity problems, I use the indicator of housing ownership in the analysis. Virtually all couples provide information on the tenancy status of their dwelling (99.6 percent of the sample). Although this indicator does not represent the economic conditions that prevailed when fertility decisions were made, it is a reasonable proxy. I compare the effects of the inheritance exclusion rule between couples who own and do not own housing. I follow the same specification described for the couple-level analysis of son and fertility preferences and fertility outcomes.

> 15 Some durable goods, for instance tools or vehicles, may be a function of the
.

# **3.3 Sample Characteristics**

Table 1 describes the baseline characteristics of the young women in our sample. As expected, there is little variation in age: 94.6 percent of the young women in the sample were 18, 19, or 20 years of age at baseline. 11.6 percent of women in our sample did not have a living parent at the time of the baseline survey. 16.5 percent were married or cohabitating,

> 9Though the US dollar value of the shilling has since declined, the exchange range was fairly constant during the grant disbursement period (from November 1, 2013 to January 13, 2014). The value of the grant was selected to make it roughly comparable to the value of the microfranchising package of training and capital; the 20,000 shilling amount is also identical to the grant size in another study of cash grants for Kenyan youth (Hicks, Kremer, Mbiti, and Miguel 2016).

> 10We also conducted an extremely brief phone survey 2 to 5 months after the intervention, but we did not ask about income-generating activities at that time. The goal of that survey was to collect better contact information than had been gathered at baseline.

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