rafmacalaba/datause-encoder-data huggingface dataset:
|Pe|ObservedValues||PredictedValues|
|---|---|---|
|All Entries<br>||<br>35.31|
|Level<br>|||
|Elementary<br>||19.37<br><br>|
|Middle|a<br>ee|ee<br>ee|
|jFous|||
|||27.56<br>|
|Region<br>|||
|Northeast<br>||18.15<br>|
|Southeast|a|10.67|

||Ss|AWards E|xceptWard 3|| Wards|7 and 8|
|---|---|---|---|---|
|School Level|||||
||0.074|||0.084|
|Elementary/Middle<br>|||-0.547||
|Middle<br>|-0.011|0.614<br>||0.078<br>|
|Middle/Highand High||-0.653|-0.878|-0.618|

Note: school value added is the residual of the mininmmm-distance estimation regression of campus fixed effects on time-invariant school characteristics. Statistics weighted by Fall 2007 enrollment.
# **2. A Simple Model of Investment with Poor Transparency**

Suppose an economy with many heterogeneous projects (firms). Each project yields different returns for the same level of investment. The return of each project increases with the level of investment but at a decreasing rate i.e., marginal productivity is positive and decreasing. There is a free entry to each project. If there is more than one investor in a given project, then investors receive the average return of the project. Specifically, assume that there is a continuum of projects, distributed uniformly along the unit interval. Let _R;,_ be the return of project j. _R;,_ depends on three elements - a project specific quality (productivity) 9;, the level of investment in the project, **Ij,** and an aggregate shock, V, that affects all projects in the economy. V represents a productivity shock, government's policy (fiscal, monetary, trade), and so on.

_wt;(O,Ij ,V)_ .1

**-R>0** _aR0_ **_a->_ <** _AR_ **>0** _89 ai_ 829 _aV_

The discussion above describes investment opportunities in the economy, i.e., the demand for credit. In the next section, we discuss the supply of funds to investors.

# 2.1 **Financial Institutions**

The supply of funds to projects is provided by financial institutions that operate in a perfect competition environment taking the interest rate for deposits and the interest rate for borrowers (investors) as given. Financial institutions have reserve requirements. Each institution is required by regulators to hold equity proportional to their lending (deposits). We 4
|**Transports**|57.76|48.03|27.33|50.00|11.38|51.64|
|---|---|---|---|---|---|---|
|**Other Services**|59.61|46.34|28.54|19.66|14.56|44.61|
||||**2005**||||
|**Agriculture**|66.94|69.00|61.23|45.60|77.83|66.95|
|**Industry**|44.77|39.99|29.27|18.37|5.06|40.31|
|**Commerce**|42.07|32.05|26.37|12.34|1.17|38.04|
|**Transports**|43.65|42.93|18.77|14.33|0.00|40.39|
|**Other Services**|48.51|39.28|23.74|18.99|7.79|35.63|
||||**2011**||||
|**Agriculture**|63.55|57.61|56.63|57.58|8.18|62.01|
|**Industry**|46.02|40.00|27.90|6.79|2.58|38.19|
|**Commerce**|36.47|28.80|23.96|12.11|10.22|32.73|
|**Transports**|43.40|54.08|13.18|15.13|1.88|36.54|
|**Other Services**|41.83|40.10|24.01|22.54|12.37|34.90|
|**Source: ESAM200**|**1, ESPS2005, E**|**SPS2011 and**|**authors’ calcu**|**lations**|||

However, a deepening of the information economy through ICT has the potential to reverse this trend. Consider the case of mobile technology services. Mobile phones enhance access to information, and as a consequence, reduce search costs, improve coordination between economic agents, and thus increase market efficiency. While direct employment benefits of mobile technology for the unskilled population may be limited to jobs in airtime sales, repair and support services including battery charging, the indirect benefits through an efficient information system can be substantial. Evidence shows that real-time information on agricultural prices in local and international markets facilitated by the Manobi platform is associated with more than 40 percent increase in farmers’ incomes.<sup>10</sup> Such increase in incomes can yield substantial employment and instant poverty effects.

# **4. THE SERVICES SECTOR, PLAN SENEGAL EMERGENT, AND FUTURE OF THE EONOMY**

Katz and Koutroumpis (2014) estimate the direct and indirect impacts of ICT on the Senegalese economy. Taken together, these impacts amount to 13.1 percent of GDP in 2012 and contributed 22.6 percent of growth between 2005 and 2012. Their estimates, based on a linear production function which has capital, labor and mobile penetration as input factors, yielded an elasticity estimate of 0.061, associating a 1 percent increase in mobile penetration with a 0.061 percent

> 10 Dalberg (2013). “Impact of the Internet in Africa.”

21
# **6. Conclusion**

The aim of this study was to examine the role of market remoteness in explaining maize price volatility in Burkina Faso over the period July 2004-November 2013. To reach this objective, we develop a model of price formation and transport costs between rural and urban markets and also captures the implications for price volatility in rural market. We explore the empirical implications of our conceptual model by using the autoregressive conditional heteroskedasticity (ARCH) model introduced by Engle (1982). The empirical estimations with data on 28 markets established that markets that are close to the main cities, where quality road infrastructure is available, display less volatile price series. The results also show that maize-surplus markets and markets bordering Côte d’Ivoire, Ghana and Togo have experienced more volatile prices than maize-deficit and non-bordering markets. Furthermore, we find strong evidence of a seasonal pattern in maize price volatility across Burkinabe markets.

These findings suggest that policies targeted towards infrastructure development and better regional integration and economic development within the ECOWAS area would reduce maize price volatility. For instance, authorities could support remote markets by linking them through better roads with major consumption centers across the country as well as in neighboring countries. This will be key to improve the commercialization of agricultural products in remote areas and reduce price volatility across markets in Burkina Faso.

# **References**

Abdulai, A., 2000. Spatial price transmission and asymmetry in the Ghanaian maize market. J. Dev. Econ. 63, 327–349. doi:10.1016/S0304-3878(00)00115-2 Badiane, O., Shively, G.E., 1998. Spatial integration, transport costs, and the response of local prices to policy changes in Ghana. J. Dev. Econ. 56, 411–431. doi:10.1016/S03043878(98)00072-8

- Baillie, R.T., Bollerslev, T., 1990. A multivariate generalized ARCH approach to modeling risk premia in forward foreign exchange rate markets. J. Int. Money Finance 9, 309– 324. doi:10.1016/0261-5606(90)90012-O

- Barrett, C.B., 1996. On price risk and the inverse farm size-productivity relationship. J. Dev. Econ. 51, 193–215. doi:10.1016/S0304-3878(96)00412-9

- Barrett, C.B., 1997. Liberalization and food price distributions: ARCH-M evidence from Madagascar. Food Policy 22, 155–173. doi:10.1016/S0306-9192(96)00033-4

- Beck, S.E., 1993. A Rational Expectations Model of Time Varying Risk Premia in Commodities Futures Markets: Theory and Evidence. Int. Econ. Rev. 34, 149–168. doi:10.2307/2526954

- Bollerslev, T., 1986. Generalized autoregressive conditional heteroskedasticity. J. Econom. 31, 307–327. doi:10.1016/0304-4076(86)90063-1

- Deaton, A., Laroque, G., 1992. On the Behaviour of Commodity Prices. Rev. Econ. Stud. 59, 1–23. doi:10.2307/2297923

24
and 17 were not competitive enough against the right answer. Also, items 13, 19, 20, 21 and 22 show similar percentage of selection of each alternative (one third), as it is expected for random answers. Finally, question 23 has one distracter that has been chosen more often than the right answer.

In conclusion, the item analysis shows that items 13, 22 and 23 do not meet the criteria for good psychometric behavior. The high percentage of right answers in items 1 through 9 and 17 indicate that these items cannot discriminate between children with adequate and inadequate reading comprehension levels in the sample. It is likely that right answers in items 13, 19, 20, 21 and 22 were due to random choice. Finally, item 23 has a distracter with higher proportion of response than the right answer. This indicates that there were problems either in the construction of the test or in the administration of it during this study. It would be useful to compare these results with those of the national census 2006 to confirm where the problem lies.

**Table 23. Response distribution by Item for the ECE test (N=1001)**

||**N**|**Freq**|**uencie**|**s**||**N**|**Pe**|**rcenta**|**ges**|**Percent of**|
|---|---|---|---|---|---|---|---|---|---|---|
|**Question**|**o**<br>**response**|**a**|**b**|**c**|**key**|**o**<br>**response**|**a**|**b**|**c**|**correct**<br>**response**|
|1|26|970|0|5|a|2.6|96.9|0.0|0.5|96.9|
|2|27|5|11|958|c|2.7|0.5|1.1|95.7|95.7|
|3|31|11|948|11|b|3.1|1.1|94.7|1.1|94.7|
|4|23|11|109|858|c|2.3|1.1|10.9|85.7|85.7|
|5|21|956|10|14|a|2.1|95.5|1.0|1.4|95.5|
|6|31|9|954|7|b|3.1|0.9|95.3|0.7|95.3|
|7|31|9|5|956|c|3.1|0.9|0.5|95.5|95.5|
|8|28|66|8|899|c|2.8|6.6|0.8|89.8|89.8|
|9|27|7|958|9|b|2.7|0.7|95.7|0.9|95.7|
|10|57|56|719|169|b|5.7|5.6|71.8|16.9|71.8|
|11|45|736|134|86|a|4.5|73.5|13.4|8.6|73.5|
|12|62|574|225|140|a|6.2|57.3|22.5|14.0|57.3|
|13|66|277|379|279|b|6.6|27.7|37.9|27.9|37.9|
|14|62|479|219|241|a|6.2|47.9|21.9|24.1|47.9|
|15|66|82|320|533|c|6.6|8.2|32.0|53.2|53.2|
|16|55|772|68|106|a|5.5|77.1|6.8|10.6|77.1|
|17|60|802|60|79|a|6.0|80.1|6.0|7.9|80.1|
|18|73|253|156|519|c|7.3|25.3|15.6|51.8|51.8|
|19|65|291|390|255|b|6.5|29.1|39.0|25.5|39.0|
|20|71|292|273|365|c|7.1|29.2|27.3|36.5|36.5|
|21|74|324|345|258|b|7.4|32.4|34.5|25.8|34.5|
|22|71|308|253|369|a|7.1|30.8|25.3|36.9|30.8|
|23|74|436|202|289|c|7.4|43.6|20.2|28.9|28.9|

To sum up, there are six items that do not provide adequate information to discriminate reading abilities when reported in raw scores, and these items account for 10 of the 23 questions in the test. In contrast, there are only three items that do not adjust well to the Rasch model, though even then, they can be used –with caution– to calculate the model and take advantage of the additional information it provides.

71
_of Economic Perspectives_ , **25** (3), 83–106.

- Combes, J.-L., Ebeke, C., Etoundi, M. N. and Yogo, T. (2014). Are foreign aid and remittance inflows a hedge against food price shocks in developing countries? _World Development_ , **54** (1), 81–98.

- Cooray, A. and Mallick, D. (2013). International business cycles and remittance flows. _The B.E. Journal of Macroeconomics_ , **13** (1), 1–33.

- Dabla-Norris, E. and Bal-Gunduz, Y. (2012). _Exogenous shocks and growth crises in lowincome countries: a vulnerability index_ . IMF Working Papers 12/264, International Monetary Fund.

- de la Briere, B., Sadoulet, E., de Janvry, A. and Lambert, S. (2002). The roles of destination, gender, and household composition in explaining remittances: an analysis for the Dominican Sierra. _Journal of Development Economics_ , **68** , 309–328.

- Docquier, F., Rapoport, H. and Salomone, S. (2012). Remittances, migrants’ education and immigration policy: Theory and evidence from bilateral data. _Regional Science and Urban Economics_ , **42** (5), 817–828.

- Durdu, C. B. and Sayan, S. (2010). Emerging market business cycles with remittance fluctuations. _IMF Staff Papers_ , **57** (2), 303–325.

- Ebeke, C. and Combes, J.-L. (2013). Do remittances dampen the effect of natural disasters on output growth volatility in developing countries? _Applied Economics_ , **45** , 2241–2254.

- El-Sakka, M. I. T. and McNabb, R. (1999). The macroeconomic determinants of emigrant remittances. _World Development_ , **27** (8), 1493–1502.

- Faini, R. (1994). Workers remittances and the real exchange rate: a quantitative framework. _Journal of Population Economics_ , **7** (2), 235–45.

- (2007). Remittances and the brain drain: do more skilled migrants remit more? _World Bank_

- _Economic Review_ , **21** (2), 177–191.

- Frankel, J. (2011). Are bilateral remittances countercyclical? _Open Economies Review_ , **22** (1), 1–16.

- Freund, C. and Spatafora, N. (2008). Remittances, transaction costs, and informality. _Journal of Development Economics_ , **86** (2), 356–366.

- Giuliano, P. and Ruiz-Arranz, M. (2009). Remittances, financial development, and growth. _Journal of Development Economics_ , **90** (1), 144–152.

- Gupta, S., Pattillo, C. A. and Wagh, S. (2009). Effect of remittances on poverty and financial development in Sub-Saharan Africa. _World Development_ , **37** (1), 104–115.

- Hoddinott, J. (1994). A model of migration and remittances applied to Western Kenya. _Oxford Economic Papers_ , **46** , 459–476.

- International Monetary Fund and World Bank (2011). _Managing volatility in low-income countries: the role and potential for contingent financial instruments_ . Tech. rep., IMF and The World Bank, Washington, DC.

- Jimenez-Martin, S., Jorgensen, N. and Labeaga, J. (2007). _The volume and geography of remittances from the EU_ . Tech. rep., Report to the European Commission.

- Lucas, R. E. and Stark, O. (1985). Motivations to remit: evidence from Botswana. _Journal of_

18
These data include the breakdown of various phases in transit but not data of individual shipments. The lead time probability distribution function (p.d.f.) is asymmetric with a broad tail, as shown in Figure 5 and Table 6 below.

# **Figure 5. Distribution of Dwell Time of Transit Containers in Mombasa Port**

<!-- Start of picture text --> 160<br>140<br>120<br>100<br>30+<br>80<br>60<br>40<br>20<br>0<br>1 3 5 7 9 11 13 15 17 19 21 23 25 27 29<br>Time Taken in Days<br><!-- End of picture text -->

**Table 6. Various Transport Times in Mombasa Port and on Transit Between Kenya and Uganda (2005)**

||Mode|Median|Mean|95<sup>th</sup>Percentile|
|---|---|---|---|---|
|Port Dwell Time in Mombasa|4.5 days|8 days|13 days|27 days|
|Transit Through Kenya and Uganda|3.5 days|4 days|5 days|10 days|

_Source: Authors’surveys._ In East Africa, along the Central corridor from Dar-es-Salaam to Kampala, transit time usually reaches eight days, which imply a return trip of less than twenty days. However, according to some freight operators the return trip may take up to 45 days (20 days to go, 5 days for clearance, and 20 days to return) (Figure 6 for distribution of transit time between Mombasa and Kampala). Similarly, bringing goods from Douala to Chad can 28
**Fig. 3. Newly-Initiated Trade Remedy Investigations, 1Q 2007 - 3Q 2009** (non-redundant AD, SG, CSG, CVD at the product level)

<!-- Start of picture text --> 50<br>45<br>40<br>35 Initiated by<br>30 developing<br>economies<br>25<br>20<br>15 Initiated by<br>developed<br>10<br>economies<br>5<br>0<br>1Q- 2Q- 3Q- 4Q- 1Q- 2Q- 3Q- 4Q- 1Q- 2Q- 3Q-<br>2007 2007 2007 2007 2008 2008 2008 2008 2009 2009 2009<br><!-- End of picture text -->

**Fig. 4. Newly-Imposed Trade Remedies, 1Q 2007 - 3Q 2009** (non-redundant AD, SG, CSG, CVD at the product level)

<!-- Start of picture text --> 30<br>25 Imposed by<br>developing<br>20 economies<br>15<br>Imposed by<br>10 developed<br>economies<br>5<br>0<br>1Q-2007 2Q-2007 3Q-2007 4Q-2007 1Q-2008 2Q-2008 3Q-2008 4Q-2008 1Q-2009 2Q-2009 3Q-2009<br><!-- End of picture text -->

**Fig. 5. Share of Completed Investigations Resulting in Definitive Import Barriers, by Investigating Country Category, 1Q 2007 - 3Q 2009**

<!-- Start of picture text --> 1<br>0.9<br>0.8<br>0.7<br>0.6<br>0.5<br>0.4 Developed<br>0.3 Developing<br>0.2<br>0.1<br>0<br>1Q-... 2Q-... 3Q-... 4Q-... 1Q-... 2Q-... 3Q-... 4Q-... 1Q-... 2Q-... 3Q-...<br><!-- End of picture text --> Source: Bown (2009a,c).

The general GATT national treatment rule does not apply to public procurement. Instead, nondiscrimination disciplines apply through the plurilateral Agreement on Government 17
# **References**

- [1] Daron Acemoglu et al. “Import Competition and the Great US Employment Sag of the 2000s”. In: _The University of Chicago Press Journal_ (2016). URL: https://www.journals. uchicago.edu/doi/full/10.1086/682384.

- [2] David H. Autor, David Dorn, and Gordon H. Hanson. “The China Syndrome: Local Labor Market Effects of Import Competition in the United States”. In: _American Economic Review_ (2013). URL: https://www.aeaweb.org/articles?id=10.1257/aer.103.6.2121.

- [3] Rafael Dix-Carneiro and Brian K. Kovak. “Trade Liberalization and the Skill Premium: A Local Labor Markets Approach”. In: _American Economic Review_ (2015). URL: https: //www.aeaweb.org/articles?id=10.1257/aer.p20151052.

- [4] Carlos G ́oes, Gladys Lopez-Acevedo, and Raymond Robertson. “Gender-Segmented Labor Markets and Trade Shocks”. In: _IZA Discussion Papers 15892, Institute of Labor Economics (IZA)_ (2023). URL: https://ideas.repec.org/p/iza/izadps/dp15892.html.

- [5] Prodyumna Goutam et al. “Does Informal Employment Respond to Growth Opportunities? Trade-Based Evidence from Bangladesh”. In: _RAND Corporation_ . Working Paper (2017). URL: https://www.rand.org/content/dam/rand/pubs/working_papers/WR1100/ WR1198/RAND_WR1198.pdf.

- [6] Brian McCaig and Nina Pavcnik. “Export Markets and Labor Allocation in a LowIncome Country”. In: _American Economic Reviewn_ . 108 (7): 1899–941 (2018). URL: https:// www.aeaweb.org/articles?id=10.1257/aer.20141096.

- [7] Justin R. Pierce and Peter K. Schott. “The Surprisingly Swift Decline of US Manufacturing Employment”. In: _American Economic Review_ (2016). URL: https://www.aeaweb.org/ articles?id=10.1257/aer.20131578.

20
For accurate estimation of the standard error of W, ELL advocate repeated MonteCarlo simulations. In each round, a simulated regression coefficient  ~( _r_ ) is drawn (from its estimated distribution), where r denotes the _r-th_ round of simulation. Further,  ~ _c_ ( _r_ ) and ~ ( _r_ )  _ch_ are drawn from their estimated distributions, which means we will have a simulated cluster error for each cluster and a simulated household error for each household in the census. The imputed dependent variable for household h in cluster c, in the r-th round, is therefore given by: Each round of simulation yields a new estimate _W_ ~ ( _r_ ) . By taking the average and standard ~ ( _r_ ) deviation over the _r_ different simulated values of _W_ , we obtain both the point estimate and the corresponding standard error.

In this paper, we use measure poverty using three Foster-Greer-Thorbecke (FGT) poverty indexes including the poverty headcount index, poverty gap index and poverty severity index (see Foster et al, 1984). Inequality is measured by the Gini coefficient. The FGT indexes and Gini index are the most popular measures of poverty and inequality, especially for developing countries. They are often reported in poverty assessment studies in Vietnam such as Vietnam Development Reports (see World Bank, 2003; World Bank, 2007).

# _III.2 Two key assumptions_

The ELL method is based on two key assumptions: _The model is accurate at each level it is applied_ : Tarozzi and Deaton (2007) refer to this as the `area homogeneity’ assumption. While the model is typically estimated at the regional level, predicted expenditures are aggregated over much smaller areas (think of provinces and districts). Consistency therefore requires that any omitted variables, which end up in the error term, have zero expectation at any level of aggregation.

_Spatial correlation is accurately accounted for_ : The errors for different households are likely to exhibit a level of correlation, in particular when the households live close to each other such that they are subject to similar (unobserved) geographical effects. An accurate account of this spatial correlation is important for the precision of the standard errors of the SAEs.

ELL accommodate spatial correlation by assuming that the error can be decomposed into a cluster error (an error that is shared by all households living in the 7
**Table 8: School Construction and Child Activities Inventory: Difference-in-differences estimates.**

||1966-1970 Materna|l Cohort|Differen|ce in Diff|erences|
|---|---|---|---|---|---|
||High INPRES<br>High-L|ow INPRES||||
||Mean|Gap|[1]|[2]|[3]|
|Child read books/magazines last week (Yes=1)|0.84|0.00|-0.018|-0.014|-0.014|
||||(0.035)|(0.035)|(0.035)|
||||[0.616]|[0.716]|[0.708]|
|Child told tale/story last week (Yes=1)|0.40|0.17|-0.05|-0.045|-0.044|
||||(0.032)|(0.031)|(0.031)|
||||[0.128]|[0.164]|[0.192]|
|Child drew last week (Yes=1)|0.91|0.05|-0.034|-0.031|-0.029|
||||(0.016)|(0.016)|(0.017)|
||||[0.096]|[0.108]|[0.124]|
|Child played music last week (Yes=1)|0.68|-0.09|-0.091|-0.082|-0.081|
||||(0.041)|(0.039)|(0.039)|
||||[0.020]|[0.036]|[0.028]|
|Child played with toys last week (Yes=1)|0.90|0.01|-0.076|-0.070|-0.069|
||||(0.026)|(0.026)|(0.026)|
||||[0.072]|[0.084]|[0.100]|
|Child did household chores last week (Yes=1)|0.59|-0.07|-0.022|-0.003|-0.004|
||||(0.030)|(0.035)|(0.035)|
||||[0.496]|[0.868]|[0.864]|
|Child played outdoors last week (Yes=1)|0.86|-0.09|0.018|0.011|0.011|
||||(0.020)|(0.021)|(0.021)|
||||[0.404]|[0.656]|[0.712]|
|_Controls (D-in-D’s)_||||||
|Caregiver district and year of birth FE’s|||YES|YES|YES|
|Treated cohort interaction with # school-aged ch|ildren in 1973 (ln scale)||NO|YES|YES|
|Child gender|||YES|YES|YES|
|Child-age FE’s|||YES|YES|NO|
|Child’s age(linearly,in months)|||NO|NO|YES|

Notes: Sample is 2,118 children. Standard-errors in parentheses are clustered at the district of maternal birth. Wildbootstrap significance p-values in brackets.
order to attract world-class creative people, Singapore must be able to provide world-class artistic and cultural performances.

It remains to be seen how much direct economic spin-off the Esplanade will generate. Its main target audience so far has been domestic (which includes a high proportion of expatriates working in Singapore). Tourist dollars account for only about 10% of total ticket sales. At the same time, there are concerns that the massive funding requirement of Esplanade -- which has a yearly running cost of S$30 million, mostly paid for by government subsidy and corporate sponsorship – will choke off the sponsorship money for other artistic and cultural groups in Singapore, and retard rather than promote the performing arts in Singapore.

One-North and Esplanade may be the most visible symbols of Singapore’s desire to become an innovation hub, but there are other important innovation infrastructures are also being built.

# **Intellectual Property Rights Laws**

Protection of intellectual property rights (IPR) is one of the most important supporting infrastructures for individuals engaged in innovation work. Recognizing the long term benefits of having a stronger IP culture (in terms of its impact on innovation), a number of Asian countries are beginning to pay more serious attention to the enactment and enforcement of such laws. The proliferation of free trade areas in the region has also compelled many to set higher legislative standard in this area.

Singapore sees the need for a strong IP infrastructure not only to support innovation in the local economy but also to give the country a head-start in becoming the regional hub for IP management. Describing IP as “new gold of our time, waiting to be unearthed and exploited”, the government has likened the development of the IP infrastructure as preparation to “join the gold rush”.<sup>29</sup> What is needed is not only a set of well-defined and vigorously enforced IP laws, but also institutions that help keep Singapore at the forefront of IP knowledge.

To this end, the government upgraded the Registry of Trade Marks and Patents to a full statutory board called the Intellectual Property Office of Singapore (IPOS) in 2001. Besides being the lead government agency that formulates and regulates the entire range of IP legislations, IPOS has the mandate of “building an environment that promotes greater IP

> 29   Speech by Ho Peng Kee, Senior Minister of State for Law, 11 September, 2002.

17