rafmacalaba/datause-encoder-data huggingface dataset:
teaching; but there is a significant positive change in the returns to hours teaching. This alone accounts for 16 percent of the improvement in test scores over time. This shows that Jordanian teachers have become more effective at conveying the material in the classroom.

# **Conclusions**

Over the last two decades, the Jordanian education system made significant advances. Significant gains were made in international surveys of student achievement, with a particularly impressive gain of almost 30 points in science. This paper shows that several policy actions, spurred by initial reactions to the shock of low scores in international comparison, and practical guidance from policymakers to implementers and teachers, were responsible for the gains in student achievement. Benchmarking education systems and constant feedback between researchers and providers contributed to this achievement.

Therefore, education systems can stand to learn from the Jordanian experience. The proper use of assessment results can provide significant returns. Also, the cost of assessment is worthwhile, given the significant benefits that the system receives. While there are many uses to assessments – national and international – primarily as part of the effort to evaluate the education system, this case shows that it can be a wake-up call for action, a tool for informing the system, and an objective metric to monitor progress over time.

Assessments, therefore, can be used to establish benchmarks – in international comparison and as national standards. Most importantly, assessments can be used to inform policy responses, and to generate real-time, useful information to providers.

Jordan’s experience suggests how countries can use international assessments and education reforms to improve the quality of their education systems. First, participation in international assessments is a must. It provides the country with useful international benchmarks and a wealth of information. Second, rigorous analysis of the determinants of learning and comparison with top performers is needed. Third, implementation of the benchmarks and analyses into curriculum development and teacher training is needed. There must be feedback loops between the research, curriculum and professional development as part of a comprehensive reform. Finally, monitoring of implementation and results must be continuous and meaningful.

12
and V. We find, as expected, that a higher standard deviation on B increases the probability of errors; and that the last bit of improvement in precision (to perfect information) has a particularly large impact. Note that with independent B and V, EZ = EB – EV, and var Z = var B + var V.

Improved decisions to protect the resource can occur either in terms of more precise B, or more precise V given that B and V are uncorrelated. In either case, only the total variance on Z matters, and this is affected in symmetric fashion by each. It also follows that the most valuable information improvements are those that most reduce this total variance.

These probabilities serve as a backdrop to the analysis of VOI, to which we now turn.

# **4. The Value of Perfect Information about B**

# **4.1  Analytical framework**

This section attempts to answer the following basic question: What is the additional value of perfect information about B to P, in the context of the decision problem studied here (optimal forest protection), when information is asymmetric, only S knowing the resource opportunity value, B, for certain? Under imperfect and asymmetric information about B, and given that P perfectly incorporates the outcome for S (α=1 above), two types of mistakes are made: the resource can be converted when it should not be; and the resource can be saved when it should not be.<sup>10</sup> This leads to welfare losses (to P and the world), in an ex ante expected sense. These losses can, at least in some cases, be avoided when information is perfect and P acts optimally upon this information.

Collecting more information about the value of B will lead to less uncertainty about this value for P, and, plausibly, to a smaller welfare loss due to incorrect decisions: thus, to higher overall expected welfare. We will here formalize this welfare improvement, as evaluated ex ante, in the (admittedly, special) case where all uncertainty is resolved ex post.

Define the standard deviations of B and V by σB, and σV, respectively. The perfect information case with σB = 0 and thus no uncertainty about B, is useful as it provides us with an appropriate benchmark for the study of informational values in intermediate and more realistic, but also more complex, cases where the initial uncertainty is only partly resolved.

From the point of view of an individual decision maker or buyer, deriving the optimal solution is now straightforward. In the objective function (4) one now only needs to replace EB by the now known B, and the optimal solution is (5), also only replacing EB by B. Define also D = B-H = the net realized value for the buyer related to this particular unit. We can in this case express the expected gain to P, for given B and α, as:

> 10 Appendix B derives expressions for these probabilities, and simulates them in some stylized cases.

9
# **Figure 2. The share of commercial services in total exports, %**

<!-- Start of picture text --> 30<br>25<br>20<br>China<br>15<br>India<br>10<br>5<br>0<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003<br>%<br><!-- End of picture text --> Source: World Bank, World Development Indicators database.

There have also been sharp changes in the composition of services exports as noted in Dimaranan, Ianchovichina and Martin (2006). In India, the main development was a dramatic increase in the importance of communications and computing services, from approximately 40 percent of all services exports in 1990 to roughly two-thirds in recent years. In China, travel and tourism services rose from a little more than 20 percent of all services exports in 1990 to approximately 50 percent in 2002. In 2003, the share of travel and tourism declined, while the share of communication and computing services expanded from about 25 percent to more than 50 percent.

# **Merchandise Trade**

Although both China’s and India’s merchandise exports are dominated by manufactures (World Bank 2003) the composition of these manufactures and the approach to their production differs considerably. For the purpose of discerning these differences we look at information on export and import patterns for each country using data by stage of production from the United Nations’ Broad Economic Classification (BEC) system (Table 1). Because of the very different importance of fuel imports and exports to the two countries, we discuss only non-fuel products.

If we look first at the import data for 2004, we find that 63 percent of China’s non-fuel imports are of manufactured intermediate inputs, while these account for 60 percent of India’s imports. Only when we 6
are large, meaning we cannot reject equality of the e¤ect of cash and in-kind grants on capital stock. Panel B shows stark di¤erences between the women whose pro...ts were initially low and those who had higher initial pro...ts –there are large increases in capital stock for the high initial pro...ts group, and no increase in capital stock for the low initial pro...ts group that received the cash treatment. After truncating outliers, we can reject equality in treatment e¤ects for the low and high initial pro...ts groups for both cash and in-kind grants.

Figures 3 and 4 show the empirical CDFs of the post-treatment capital stock distribution by treatment group and gender for the ...nal two waves of the survey. For males, Figure 3 shows a similar pattern to that of pro...ts – namely that the distribution of the in-kind treatment group is shifted to the right compared to that of the control group across the distribution. The cash distribution is in between, although right at the top of the distribution crosses the control distribution curve several times, which explains the sensitivity of the cash treatment e¤ect to where we truncate the data. For females, Figure 4 shows that both treatment groups overlap with the control group for the bottom 60 percent of the distribution, a pattern similar to that seen for pro...ts. The in-kind grant distribution then separates from the control above this, with women in the in-kind treatment group having higher 70, 80, and 90th percentiles of their capital stock distributions than the control group. The cash treatment group lies in between, and, unlike in the case of pro...ts, does separate somewhat from the control group at the top of the distribution, suggesting some increases in capital for some ...rms as a result of the cash treatment.

Next we examine where the grants are going if not into the business. Beginning in wave 4, ...rm owners were asked “During the past three months, did you make any payments in cash or goods to people living outside your household?”and if so, the value of such transfers. Columns 3 and 4 show that women who received the cash grant were more likely to have made such a transfer, and to have given more. On average they are estimated to have given 8 cedis more a quarter over the last 3 quarters of the survey. This does not account for any transfers out made in the ...rst quarter after treatment by ...rms treated after wave 2, since the wave 3 survey did not collect transfers data. However, restricting the analysis to the control group and ...rms treated after wave 3 only marginally increases the coe¢ cient on the cash treatment, raising it to 8.9 cedis.

The remaining columns report the estimated impacts on household expenditure, which was 28
||Pr(IQ=1,IV=1)|**0.017**|**-0.006**||**-0.006**|||
|---|---|---|---|---|---|---|---|
||Pr(IQ=0,IV=1)|**2.470**|-0.920|0.010|**-0.826**|||
|marginal efects|Pr(IV=1|IQ=1)|**1.605**|-0.597|0.007|**-0.533**<br>iables) marginal|lue 1 if the frm<br>the introduction|are statistically<br>nifcant results.|
|) : Standardized|V=1)<br>Pr(IV=1)|**2.501**|**9**<br>**-0.920**|0.010|**-0.832**<br>e explanatory var|my that takes va<br>the frm reports|l, the other results<br>on statistically sig|
|s (IV|(IQ=1,I|0.212|**-0.04**||on of th|a dum<br>lue 1 if|% leve<br>ts of n|
|creation of new good|Pr(IQ=1,IV=0)<br>Pr|**0.053**|**-0.017**||y the standard deviati|dependent variables is<br>a dummy that takes va|ally signifcant at the 1<br>port the marginal efec|
|ing (IQ) and|Pr(IQ=1|IV=1)|**0.706**|**-0.247**||tandardized (b|it. One of the <br>. The other is|old are statistic<br> We do not re|
|lity upgrad|Pr(IQ=1)|**0.3105**|**-0.104**||ble presents s|-variate prob<br>y up-grading|Results in b<br> the 5% level.|
|Table 12: Qua|||tors*Know.spillovers|.spillovers|tional Innovators<br>ow.spillovers<br>Note: This ta|efects of a bi<br>reports qualit|of new goods. <br>signifcant at|
||||va|ow|na<br>n|||
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33
firms, or firms located outside the capital city). The program could then adjust its marketing efforts for future rounds to ensure it reaches out to these groups. Each subsequent funding round would again follow the same procedure of randomly selecting the target number of recipients from among the eligible firms.

We also considered two alternative forms of randomization. The first was a _phase-in design_ , in which some firms would receive the funding now, and others would receive it later. This did not seem practical for three reasons. First, not all firms apply at once. Second, if firms knew that they might receive the funding in the future, they might adjust their behavior today, and third, some of their funding requests might be time-sensitive.

The second alternative was a _randomized encouragement design_ . Under this approach, the program is open for all firms to apply. A baseline survey of firms would be conducted to learn about the potential demand among firms for the program, and to provide data for monitoring purposes on firms that get the grants and firms that do not. During the process of conducting the baseline survey, firms will be randomly chosen to receive additional “encouragement” to apply for the matching grants. This encouragement would be in the form of different marketing and informational approaches to increase awareness about the program. Since resources are limited and it is costly to visit firms individually, this approach would clearly not be feasible to follow for all firms. Therefore, the program fairly gives all firms the same _ex-ante_ chance of receiving this additional encouragement, and uses this to learn about the needs of firms for the program, the effectiveness of different marketing strategies, and the impact on firms of getting the matching grants. The danger with this approach is that the encouragement may fail to encourage many firms into applying, so larger samples are typically needed than with a randomized experiment of applicants. In our first attempt to evaluate a matching grant project, we tried unsuccessfully to use this type of encouragement design to measure the impact of the Small Enterprise Development Agency (SEDA) in South Africa. The main reason for trying this approach was that SEDA had been operating on a first-come first-serve basis since 2004. Additionally, the government was reluctant to limit eligible applicants from receiving the grant, making randomization difficult to implement in practice. Given the lack of success in this first attempt, we considered this encouragement option as a less desirable alternative to randomization in subsequent evaluations (Goldstein, 2011).

17
8 Traditional Medicine in Sub-Saharan Africa

# _Changes in Traditional Health Care in Response to Modernization_

22. Traditional medical practice is changing in Africa in response to development in other parts of the social and economic system. For example, modernization of the economy has affected the way in which many traditional practitioners operate. In Nigeria and Ghana, traditional healers have begun to adopt many of the practices of modern health care, such as prescribing antibiotics, dressing in white coats, and operating from modern clinical facilities. In Nigeria, clinics have waiting rooms, and traditional healers use stethoscopes and kaep record cards (Oyenye 1985). These developments refle't not only increasing competition with modern health care providers, but also changes in the content of traditional health care.

23. Traditional practitioners are also becoming increasingly professionalized. Oyeiiye has reported that traditional healers in Africa are both specializing and referring cases to each other. The development of professional associations of traditional healers has been faster in Africa than anywhere else. Today, according to WHO, healers' associations are official'y recognized and operating in 12 countries. Last (1986) argues that this recent trend is a direct response to competition from an expanding medical profession.

# Why African Governments Should be Concerned with Traditional Health Care

24. Most African governments have withheld formal recognition from traditional medicine despite the importance of the sector as a source of health care in many African communities and the encouragement of WHO. However, governments increasingly are aware of its crntributions. In attempting to devise a public policy toward traditional medicine, governments must now weigh the political risks of alienating both traditional and modem health practitioners and their respective clients. Several countries (Ethiopia, Ghana, Mali, Niger, Nigeria, Senegal, and Zaire) have established institutes of traditional medicine for research and provision of therapeutic services. At least five have initiated some efforts to involve traditional practitioners in national health care systems (Zimbabwe, Liberia, Ghana, Nigeria, Sierra Leone, and Botswana). However, only Zimbabwe and Nigeria are expanding the role of traditional medicine. The fo"owing discussion reviews some of the possible public policy options with regard to traditional healers.

# _Leaving Traditional Health Care Alone_

25. Many governments have chosen simply to ignore traditional health care, leaving traditional healers unrecognized, unreg -. 1 ed, and free to respond to demands for their services. This strategy clearly precludes governments from supervising the training of traditional health workers or regulating traditional health care practice. It also forecloses the possibility of including traditional medicine in national health plans for health manpower development and service expansion. Moreover, ignoring traditional medicine frustrates the exchange of information between modern health care and traditional practitioners. Reliance on traditional
Cunat, Alejandro and Marc J. Melitz (2009), “Volatility, Labor Market Flexibility, and the Pattern of Comparative Advantage,” forthcoming in Journal of the European Economics Association.

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20
who put emphasis on the quality of their offspring should then time birth following the horoscope. Consequently, Vietnamese children born in auspicious cohorts are more likely to have been the fruit of fertility planning. The marginal child in this context is then assimilated to the child born in a non-auspicious year. Family fi xed-effect estimations allow us to make an even stronger case: by comparing siblings, we can control for any latent heterogeneity stemming from parental time-invariant characteristics.

For our empirical investigation, we use household surveys undertaken in Vietnam in 1992-93 and 1997-98 to compare birth cohorts across years. Years that are believed to bring good luck to either boys or girls have birth cohorts on average 7 percent larger than other years. Furthermore, sex ratios seem to follow the Vietnamese horoscope: in auspicious years for boys, there is an average of 106 boys for 100 girls, suggesting that the practice of astrology-driven sex-selective abortion might be taking place in Vietnam. When we turn to human development outcomes, we fi nd that children born in these auspicious cohorts have higher levels of human development. While local or family-level characteristics might simultaneously affect the likelihood of having a child born in an auspicious year and his or her subsequent human development, explicitly controlling for these factors mildly affects the observed correlation between horoscope and health or education outcomes. Family fi xed-effect estimations indicate that a child born in an auspicious year for either boys or girls has a body-massindex-for-age z-score 0.12 points higher, and will attend school an extra 0.36 years or 0.10 standard deviations more than his or her sibling born in an inauspicious year. Our results moreover suggest that better health outcomes are driven by improvements in weight rather than height. If familylevel time invariant characteristics cannot alone explain the observed differences, we are left with two competing mechanisms: it might be the case that children born lucky are either truly more fortunate, feel more con fi dent by being told so, or receive more attention because their environment believes so (the “horoscope” effect); alternatively, children born in auspicious years might have parents that are then better prepared to raise them as they are the fruit of careful fertility planning. Using the fact that auspicious years differ across gender, and gender is not known by the time of the fertility decision, we disentangle these two channels and fi nd strong evidence that fertility planning is an important determinant of subsequent human development: once controlling for the fertility planning, the “horoscope” effect is not signi fi cant, and the coefficient capturing the fertility-planning effect is almost unchanged. Furthermore, among children born unlucky because horoscope and gender do not match, those who are more likely to have been planned exhibit better health and educational outcomes later on. These results strongly suggest that children, in addition to gender and birth order 3
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