rafmacalaba/datause-encoder-data huggingface dataset:
The household survey data used in this paper were collected in two rounds, the second and third wave of the overall study.<sup>12</sup> The first household survey used in this study was conducted approximately 6 months prior to the first HTC data collection between October 2008 and February 2009. The second follow-up household survey was conducted between February and June 2010, just prior to the second round of the HTC testing. In addition to collecting data on the household, more pertinent for this study were the detailed information collected on the selfreported schooling and sexual activity of the respondents, as well as their subjective probabilities of being infected with HIV and their subjective life expectancies to ascertain prior beliefs and changes in those beliefs as a result of receiving HTC.<sup>13</sup> Economic theory suggests that changes in subjective life expectancy may lead to changes in human capital investments. Perhaps the most critical investment that adolescents make is the laborious work of building their own human capital. Because the returns from investments in schooling are largely realized in the distant future they appear particularly informative as to inter-temporal tradeoffs. To measure improvements in student achievement, mathematics and English reading comprehension tests were developed and administered to all study participants at their homes as part of the follow-up data collection effort in 2010. The tests were developed by a team of experts at the Human Sciences Research Council according to the Malawian curricula for these subjects for Standards 5-8 and Forms 1-2.<sup>14</sup> In addition, to measure cognitive skills, we utilized a version of Raven’s Colored Progressive Matrices that was used in the Indonesia Family Life Survey (IFLS-2).

Objective measures of behavior change minimize the risk of social desirability bias in the estimated treatment effects. In addition, the intervention itself might change the self-reporting bias of those receiving HTC. Thus, compared with self-reported sexual behaviors, biological markers of unprotected sex are likely to be preferable.<sup>15</sup> In this paper, we utilize biomarker data on both HIV and HSV-2, collected during HTC. For educational outcomes, we utilize test score data on mathematics, English reading comprehension, and cognitive ability, as they are likely to provide a more accurate measure of human capital investments than self-reported attendance or

> 12 There was also a household survey conducted between October 2007 and January 2008 which served as a baseline for the cash transfer intervention, but is not used for this analysis.

> 13 These surveys, as well as the achievement tests described below, are available from the authors upon request.

> 14 In Malawi, there are eight grades in primary school (Standard 1-8) and four in secondary school (Form 1-4).

> 15 However, such proxies are also imperfect surrogates for HIV transmission (Padian et al. 2011).

8
7 no default if Xv > DI partial default if Di > X > O0 full default if aN < 0 where X, is defined as the debtor country's willingness to pay, D, the face value of external debt at maturity and 7 the maturity period.

These three simple rules can be illustrated as follows. First, the debtor country will reimburse its debt if the payment required to offset the - - penalties applied in case of default is higher than the debt itself. The reimbursement is less expensive than the required payment or the costs of the penalties. Second, if the payment is positive but lower than the face value of the debt, the country will choose to pay rather than to reimburse totally its external debt. Thip. corresponds to the case of partial default in the sense that the debtor country will only pay a fraction of its total debt-service. The third possibility is that the willingness to pay is negative or, in other terms, the country should receive money in order to avoid a penalty by its lenders. This may arise if the economic and political benefits in case of full default are higher than the sanctions applied by the lenders. In this case, the debtor country will call a total default on its external debt.

The major problem related of this approach is that the willingness to pay (X4) is an unobservable variable. The willingness to pay depe-nds on the bargaining outcome between the creditors and the debtor country which, as discussed by Fernandez and Rosenthal (1990), is generally very sensitive to the particular specifications of the institutional structure in which it is embedded. As suggested in the introduction, the idea in this paper is to use the information on the secondary market of the price of debt to obtain a measurement of this variable. More precisely, assuming that the price of debt reflects the repayment prospects of the borrowers countries, we suggest that these prospects are influenced to a large extent by the debtor country's willingness to pay. In continuous time, we can represent this assumption by the following expression:
# Appendix C: Validation of the wave model

The wave transformation model is validated against field wave measurements collected at a salt marsh fringe by Vuik et al. (2016). Wave propagation through the salt marshes is modeled for a significant wave height of = 0.6 m and a peak period of = 3.5 s at the offshore boundary. The bathymetry varies between an offshore water depth of 2 m, and a mm0 cc HH TT nearshore water depth of 0.5 m. The salt marshes extend over a length of 55 m and have varying vegetation properties across the profile, but uniform properties over the vertical coordinate. The vegetation properties are summarized in Table C1. A drag coefficient of = 0.4 is used in the simulations, which is equal to the value calibrated by Vuik et al. (2016). DD,ww cc _Table C1. Salt marsh properties used for the validation from Vuik et al. (2016), consisting of the mean vegetation height hv, the mean stem density Nv, and the mean stem width bv. The location of the sections across the profile is indicated in Vuik et al. (2016)._

|Section|hv,mean (m)|Nv (plants/m<sup>2</sup>)|bv (m)|
|---|---|---|---|
|S1-S2|0,2|944|0,030|
|S2-S3|0,29|1136|0,034|
|S3-S4|0,27|1520|0,037|

The wave propagation model shows good agreement with the model predictions and field measurements of Vuik et al. (2016), as shown in Figure C1. The agreement is good both for a situation without vegetation, and with vegetation, which indicates that both wave breaking and the vegetation module are well implemented.

47
with firms that produce output with only two types of workers, A and B, which are perfect substitutes. Let φ be the marginal product of type A relative to type B and λ be the relative wage. If φ = λ , firms in this economy will be indifferent among any combination of type A and type B under a profit-maximizing or cost-minimizing behavior.<sup>4</sup> However, if the inequality does not hold, firms will hire only one kind of labor. Then, the only equilibrium in this economy is when the marginal product equals the relative wage.

Whenever wage and productivity differentials are not equal then there is a deviation from the competitive spot labor markets assumption. It can be the case that long-term contracts justify a lower relative wage in exchange for job security, or that firms and workers do not share evenly the benefit from some productivity-enhancing trait – such as better training – because of unequal bargaining power.

We use simultaneous non-linear production functions and earnings equations at the plant level to obtain estimates of parameters φ (marginal productivity of one type of worker relative to the base case) and λ (relative wage of one type of worker to the base case) using maximum likelihood methods. The equations that make up the system are the following<sup>5</sup> : where: _Y_ value added productivity in the firm _w_ wages paid to all workers in the firm<sup>6</sup> _K_ capital (fixed assets)

> 4 Whenever φ≠ 1 , we say that the types of labor are distinguished by a different _quality of labor_ . 5 The production function is an extended Cobb-Douglas function. The wage equation is a definitional equation, not a behavioral equation. Suppose two types of labor, A and B. Then, if we define wages in a firm as the weighted average of each type of labor’s wages: _w_ = _wA LA_ + _wB LB_ = λ _wB LA_ + _wB_ ( _L_ − _LA_ ) = _wB_ [ _L_ + ( λ− )1 _LA_ ] . In logs and aggregating over all firms, this would yield equation (2) with the quality of labor aggregate as defined in (3) below. 6 In the survey, all monetary figures are in nominal terms, corresponding to December 2000, except for the wages which are presented in June 2000 prices. Therefore, to express the wages in December 2000 prices as well we used _wage price indices_ produced by Banco de México.

8
||PP|R Working Paper Series|||
|---|---|---|---|---|
||Title|Author|Date|Contact|
|WPS36|Means and Implications<br>of Social<br>Security Finance In Developing<br>Countries|Douglas J. Puffert|August 1988|R. Blade-Charest<br>33754|
|WPS37|Black Market Premia, Exchange Rate<br>Unification<br>and Inflation in<br>Sub-Saharan<br>Africa|Brian Pinto|July 1988|R. Blade-Charest<br>33754|
|WPS38|Intergovernmental<br>Grants in<br>Developing<br>Countries|Larry Schroeder|September 1988|<br>R. Blade-Charest<br>33754|
|WPS39|Fiscal Policy in Low-Income<br>Africa|Stephen A. O'Connell|<br>July 1988|R. Blade-Charest<br>33754|
|WPS40|Financial Deregulation<br>and the<br>Globalization<br>of Capital Markets|Eugene L. Versluysen|<br>August 1988|R. Blade-Charest<br>33754|
|WPS41|Urban Property Taxation in<br>Developing<br>Countries|William Dillinger|August 1988|R. Blade-Charest<br>33754|
|WPS42|Government<br>Pay and Employment<br>Policies<br>and Government<br>Performance in||||
||Developing<br>Economies|David L. Lindauer|August 1988|R. Blade-Charest<br>33754|
|WPS43|Tax Administration<br>in Developing<br>Countries: Strategies<br>and Tools<br>of Implementation|Tax Administration<br>DlvibIon|||
|WPS44|The Size and Growth of Government<br>Expenditures|David L. Lindauer|||
|WPS45-<br>WPS60|Assigned to WDR||||
|WPS61|Student Performance<br>and Schools Costs<br>in the Philippines'<br>High Schools|Emmanuel Jimenez<br>Vicente Paqueo<br>Ma. Lourdes de Vera|August 1988|T. Hawkins<br>33678|
|WPS62|Universities<br>in Arab Countries|George 1. Za'rour|September 1988|C. Christobal<br>33640|
_Low-Income Countries’ Access to Private Debt Markets_ of currency appreciation (often in commodity-exporting countries that benefited from rising commodity prices until mid-2008). Moreover, much of domestic public debt in low-income countries has a short-term maturity (under a year) (figure 22),<sup>22</sup> making rollover-risk a major concern as well.

# **Figure 21 Gross Public Domestic Debt as a share of GNI in developing countries, 2005**

<!-- Start of picture text --> Gross public domestic debt/GDP (%)<br>75<br>R 2 = 0.04<br>50<br>25<br>0<br>4 5 6 7 8 9<br>GNI per capita<br><!-- End of picture text --> _Sources:_ World Bank staff calculations based on estimates reported by Christensen (2005), Jeanne and Guscina (2006) and Cowan and others (2006).

> 22 Calculations reported by Christensen (2005, Table 5) indicate that domestic debt issued by governments in low-income SubSaharan Africa countries have an average maturity ranging from just a few months (Burundi and Uganda) to just over a year (Kenya). In contrast, calculations reported by Jeanne and Guscina (2006, Figure 7) indicate that a significant portion of government debt issued in domestic markets in Asia and Latin America is medium and long term. Estimates compiled by Cowan and others (2006) indicate that the proportion of domestic public debt that is short term (original maturity of less than one year) ranges from almost one half for Brazil to less than one percent in Nicaragua, El Salvador and Colombia.

27
educated/skilled workers. Galbraith and Liu (2001), for example, find a worldwide trend toward greater wage inequality among industries; that is, wages in skill-intensive industries such as aircraft production have been going up faster than wages in low-skill industries such as garments.

If wage inequality is going up worldwide, how can it be that income inequality is not rising in most countries? There are several reasons why these two trends are not inconsistent. Most important, in the typical developing country wage earners are a small fraction of the population. Even unskilled wage workers are a relatively elite group. Take Vietnam as an example, a low-income country where we have a survey of the same representative sample of households early in liberalization (1993) and five years later. The majority of households in the sample and in the country are peasants. What we see in the household data is that the price of the main agricultural output (rice) went up dramatically while the price of the main purchased input (fertilizer) actually went down. These price movements are directly related to globalization, because over this period Vietnam became a major exporter of rice (supporting its price) and a major importer of fertilizer from cheaper producers (lowering its price). The typical poor family got a much bigger “wedge” between its input price and output price, and their real income went up dramatically (Benjamin and Brandt, 2002). So, one of the most important forces acting on income distribution in this low-income country has nothing to do with wages.

Quite a few rural households also sent a family member to a nearby city to work in a factory for the first time. I worked on Vietnam for the World Bank from 1989 to 1995, and one of the issues that I covered was the manufacturing sector. When I first started visiting factories in the summer of 1989, the typical wage in local currency was the equivalent of $9 per month. Now, factory workers making contract shoes for U.S. brands often make $50 per month or more.

26
by Save the Children staff with assistance from preschool instructors and community health workers, following an appreciative inquiry approach in which knowledge is built from existing positive parenting practices and harmful practices are brought to light and modified with strategies such as the use of positive deviance to model new behaviors.<sup>12</sup> The program was implemented in three districts of Gaza Province (Manjacaze, Xai Xai and Bilene) where Save the Children had an established operational presence. Program requirements narrowed eligibility to rural communities with between 500 and 8,000 residents, located within operational areas of sufficient geographic proximity so program field teams could travel between assigned communities in a single day.<sup>13</sup> As a pre-condition for funding, communities committed to the contribution of land, materials, and labor. The intervention rolled out in 2008 with the formation of preschool committees, recruitment and training of teachers and construction of classrooms. Some communities initiated teaching activities prior to completion of the physical infrastructure, meeting outdoors or in other community structures while the preschool facilities were built.

Enrollment was restricted to children between three to five years old with residence in the community, though age and residency requirements were difficult to monitor and were not always strictly enforced. Enrollment in the preschool program was voluntary and participating parents were encouraged to send their children to preschool daily, to attend the monthly parenting meetings, and help with preschool maintenance activities such as supplying clean drinking water and cleaning. Monetary contributions from families were minimal, as the program covered the costs of instructor stipends and basic materials during the first two years of operations. While in principle the program was targeted to the poorest and most vulnerable children in each community, in practice we observe that children who enrolled in preschool were more likely to speak Portuguese, scored higher on some child development indicators, and tended to have more favorable nutritional indicators. We also found differences in caregiver characteristics and behaviors in our baseline survey, with parents of enrolled children more likely to speak

> 12 Positive deviance models behaviors on the successful strategies of peers in the community.

> 13 The population criteria were established to reach enough children for at least one classroom at the lower limit, while enabling community mobilization in larger communities. The program financed 5 field teams, each of which was responsible for implementing the program in 6 communities. To reduce travel time and costs, each group of 6 treatment communities needed to be located within sufficient proximity so that a field team could travel between its assigned communities within the same day. Operational areas corresponded closely with administrative posts, the intermediate administrative unit between district and community.

8
# <u>7) Conclusion</u>

This paper presents a systematic methodology to evaluate systems of housing subsidies. The methodology is applied to the system of housing subsidies prevailing in Morocco in 1995 and 2002. The various parts of the housing subsidy system are described, and rated along public finance criteria. The framework used here provides a synthetic overview of the housing subsidy system of Morocco. It may be used to compare the Moroccan system to those of similar countries. To illustrate this possibility, Figure 10 presents some of the results in a different manner.

<u>Figure 10 : Expenditures on Housing Subsidies by Type – comparison 1995-2002</u> <!-- Start of picture text --> Subsidies amounts by degree of Subsidies amounts by degree of targeting<br>transparency<br>Very Good<br>Very Good<br>Good<br>Good<br>Fair<br>Fair<br>Poor Poor<br>Very Poor Very Poor<br>0 1000 2000 3000 4000 5000 0 1000 2000 3000 4000 5000<br>Amount in 2004 (Mdhs) Amount in 2004 (Mdhs)<br>Subsidies amounts by degree of Subsidies amounts by degree of<br>efficiency sustainablility<br>Very Good Very Good<br>Good Good<br>Fair Fair<br>Poor<br>Poor<br>Very Poor<br>Very Poor<br>0 1000 2000 3000 4000<br>0 1000 2000 3000 4000<br>Amount in 2004 (Mdhs)<br>Amount in 2004 (Mdhs)<br>Targeting<br>Transparency<br>Efficiency<br>Sustainability<br><!-- End of picture text --> The paper shows that the most visible subsidies have been neither the most inefficient nor the most resource consuming for the state. Examination of changes since 1995 shows that while the most visible subsidies have received nearly all the attention, large invisible subsidies remain at the heart of Morocco’s housing policy. For example, the decision to phase out interest rate subsidies was accompanied by the creation of the Fund for Social Housing, whose cost is twice as large, and whose characteristics may lead to economic inefficiencies and to greater opacity for Moroccan taxpayers.

50
With imperfect credit markets, some households will be able to buy and accumulate land not because they would be more productive but due to their ability to better overcome such market imperfections (Carter and Salgado 2001, Zimmerman and Carter 2003). Similarly, others may be forced to sell land in exchange for less risky assets to minimize their exposure to risk even though they would be able to make more productive use of the land than those who acquire it (Rosenzweig and Binswanger 1993). Thus, in addition to productivity, macroeconomic conditions, expectations of future land price movements, lack of sufficiently attractive alternative assets, and policies, are all factors that can compound, and possibly overwhelm, the impact of innate productivity on households‟ land sales market participation and is that the productivity- and equity impact of land sales market operation will depend on the extent to which other markets function and net effects of land sales markets are ambiguous _a priori._ To estimate the model empirically in a way that allows drawing comparisons, we use the maximum likelihood model introduced earlier for land rental markets. Latent demand for land is assumed to depend on long-term productivity which can be expressed as a reduced form equation and thresholds for the transition between sales and autarky and autarky and purchase are defined in a similar way to the land rental market model. Factors affecting the extent of participation in the main equation are the level of ability and the household‟s endowment of land, labor, and other assets. We expect high levels of ability to increase producers‟ marginal product and their competitiveness in land markets while standard assumptions for the production function imply a negative relationship between the land endowment and its marginal product. Higher agricultural ability or lower land endowments will make it more (less) likely for a household to shift from autarky to being net purchaser (seller) of land. In addition, imperfections in credit and labor markets imply that higher levels of wealth or family labor will affect a household‟s marginal productivity.<sup>11</sup>

# **4. Empirical evidence**

The frontier production function provides interesting insights, but does not support the notion that fragmentation reduces the level of productive efficiency on land currently cultivated. However, the survey points towards a significant share of land having remained idle for a sustained period of time because of land market imperfections. Descriptive and analytical evidence on land market functioning suggests that lease but not sales markets transfer land to younger and more productive farmers. Eliminating impediments to their functioning would appear to offer an opportunity to increase the level of economic activity and welfare in Albania‟s rural areas.

# **4.1 Determinants of technical efficiency in agricultural production**

> 11 As the survey includes data on land sales for the last 5 years, the number of observations is comparable to what is available for rental markets.

12
The source of paid-in capital has a negative main effect and a positive year effect on volatility change (Figure 5). Figure 8 shows that the negative main effect results essentially from the reduction of the shares of state-owned firms and collective firms, which are generally more volatile in the period of this study (see Tables 1 and 3); whereas the positive year effect is due to the strengthening of the effect of firms with corporate capital on enhancing productivity volatility and the weakening of the effect of firms with foreign capital in reducing productivity volatility (see Table 4).

**Figure 8 – Contribution of firm ownership to the changes in firm’s productivity volatility**

<!-- Start of picture text --> State Collective Corporate Private Foreign<br>Main effect Year effect<br>Reference: Hong Kong, Macao & Taiwan capital<br>.4<br>.2<br>Effect 0<br>-.2<br>-.4<br><!-- End of picture text --> As we have seen above (Table 4), the ratio of export delivery value to total output value has a positive effect on volatility in 2001; but the effect is not significant in 2005. That leads to a negative year effect, reducing productivity volatility.

Finally, the share of firms located in coastal provinces, that are less volatile, increased from 2001 to 2005 (Table 3), which results in a negative main effect. On the other hand, the effect of coastal region on reducing productivity volatility also increased from 2001 to 2005 (Table 4), which 21