rafmacalaba/datause-encoder-data huggingface dataset:
The keys to flexible and responsive systems are: (a) an orientation of the national planning authority towards decentralized decision-making, (b) the existence of links between training providers and employers, either in the form of direct association or through dissemination of appropriate and upto-date labor market information, and (c) the ability of training providers to adapt the volume and curricula of their programmes in response to signals from employers or the labor market.

# Need for decentralized decision-making

There are three reasons why it is important that a national planning authority adopt a decentralized approach to detailed decision-making concerning the provision of training.

First, it is utterly unrealistic to expect a central agency with finite staff to be able to monitor the myriad varieties of training that exist in most countries. Information processing is expensive and since it is subject to sharply diminishing returns, the point is soon reached where other activi.ties have a higher claim on resources.

Second, with limited experience and expertise, the staff of a national agency are less well qualified to take training-relate **d** ecisions than those directly involved, the staff of the training providers and the employers of the trained. They are recruited for their analytical and administrative abilities and it is much more important that they should have a good general understanding of how education, occupational training and employment are interrelated than that they should have detailed knowledge of the specifics of training for a particular occupation.

In practice, in developed as well as developing countries, even the general understanding is frequently lacking. For example, a thorough study of training provision in New York City states, among its conclusions, that "an unavoidable one is that at the highest policy levels, whether legislative or administrative, there is a critical lack of awareness of how complex the labor market really is." (Lynton et. al., 1979, p. 289). This observation applies worldwide, and to donor agencies as well as governments.

Third, centralized decision-making is generally implemented more clumsily, slowly and expensively than decisions made on the spot. The inevitable filtering of information transmitted to the central agency undermines the capability of national staff to devise the most appropriate policy, and it takes time and costs money to gather the information that is transmitted.

The conclusions of a recent World Bank survey of training institutions in the Middle East are representative in this respect. It found that highly centralized systems suffered from a lack of flexibility in response to change, particularly in local labor market areas in the larger countries; that educational resources were being used inefficiently, partly because communications were slow, but more importantly, because decisions were not being taken by those best placed to take them; that directors and

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Finally, the climate forecasts may need refining furthermore in terms of spatial representation. The above discussion partly depends on the global climate change model for one-step-ahead climate projections. Ideally, however, the basin-level climate forecasts would be more appropriate input (e.g., Kothyari and Singh, 1996; Pant and Kumar, 1997; Lal and Aggarwal, 2001). The above analytical framework implicitly assumes that temperature and precipitation data at or close to the project site could represent all climate conditions over the upper basin—e.g., surface water, groundwater and soil moisture—that would result in flow at the dam location. This may not always hold. At the same time, however, if all the relationship were modeled in a physical hydrologic manner, there would be no room where the statistical hydrology approach could be performed, because there would be no degree of freedom. In other words, a missing gap that should be bridged is, to my best knowledge, the comparison between those two approaches. A further research will be needed to answer whether or not they are compatible and which is better if not.

# **VI. CONCLUSION**

The world economy is now faced with considerable risk and uncertainty caused by climate changes. Increasing attention has been paid to hydropower generation in recent years, because it is renewable energy. However, hydropower is one of the industries that would be most likely to be affected by changes in global and regional climate. The paper applies a hydrological model using a VAR technique to three hydropower projects in India, Sri Lanka and Vietnam.

The possible climate change impacts have rarely been evaluated in an explicit manner when a hydropower project is ex ante assessed in economic terms. Conventionally, the 90 percent dependable hydrological level is used as a forecast of water flow in the future. However, it is shown that the hydrological forecasts calibrated from the empirical VAR models are very different from the conventional projections.
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# **ITALY** (2)

According to Dr. Ranieri Guerra, who has the responsibility for preparing official Italian health sector aid statistics, there is a current portfolio of 333 multiyear projects, of which approximately 100 projects with a total value of S529.3 million have id, itiflable maternal health components. These components include maternity hospitals, general hospitals, health systems, maternal and child health programns, essential drug distribution, nutritional support, and emergency services. Assuming a 10 percent share goes to maternal health, the conitribution to SM may be about S52 million.

The outlook for continued support in maternal health is favorable. Italian aid planners feel that funds are not a limitation; the problem is identifying and preparing field projects.

Instituto Superiore di Sanita (National Institute of Health) Aula MLisiroli via del Castro Laurenziano, 25 (also V. le Regina Elena 299) 00161 Rome
foreign sources. Even though FDI and remittances have been on the rise, there is still a gap that is now predicted to be filled by an increasing amount of foreign aid.

**Table 12: Balance of Payment Items, Togo, 2003‐2007.**

|**Column1**|**2003**|**2004**|**2005**|**2006**|**2007**|**2008**|
|---|---|---|---|---|---|---|
|Domestic PrimaryBalance(% of GDP)|4.5|3.2|‐0.5|‐1.1|0.2|0.4|
|Trade Balance(% of GDP)|‐14|‐15|‐16.9|‐19.6|‐10||
|Current Account Balance(% of GDP)|‐4.2|‐3|‐5.3|‐6|‐3.9||
|Gross int. reserves (months of imp)|2.3|3.6|2|3.2|3||

_Source:_ International Financial Statistics, IMF.

**Fiscal policy has meet and even gone beyond its targets, although this is partly a consequence of limited execution on the expenditure side.** The domestic primary balance was +0.4% of GDP in 2008, and tax and custom revenue collection were higher than expected. Current expenditures represented 87% of total expenditures while investment spending represented 13%. Capital spending was under executed (among the lowest in SSA as reflected in the low public investments in Figure 44), mainly due to capacity constraints and complex procurement procedures. This may turn out to be an important indirect binding constraint as the public investments expenditures are supposed to finance crucial elements of future growth in Togo (see further Section 5.6 below).

**Figure 44: Public Capital Investments, WAEMU, latest available data (% of GDP)**

<!-- Start of picture text --> 14.0<br>12.0<br>10.0<br>8.0<br>6.0<br>4.0<br>2.0<br>-<br>Niger Burkina Mali Benin Senegal Cote WEMU Togo<br>Faso d'Ivoire<br>Total Domestically financed Foreign financed<br><!-- End of picture text --> _Source_ : IMF (2009a).

**Togo qualified for the HIPC initiative and will upon completion point qualify for the Multilateral Debt Relief Initiative (MDRI)** . Togo’s NPV of debt‐to‐revenue ratio in end‐2007 was 309%, and to reach 250% requires 270 million USD in HIPC relief. The MDRI is then expected to reduce the debt with another 404 million USD. The development of an interim PRSP and now a PRSP, as well as the progress on triggers related to macroeconomic stability, public financial management, governance, debt management and social sectors – monitored under the IMF’s PRGF program and IDA’s Development Policy Operations – have made it possible for Togo to make significant progress towards the completion point, which the government is hoping to reach in early 2010. Togo stands out in terms of the share of arrears in the external debt, but many of these arrears have been cleared during 2008 and the remaining is under process of being cleared or rescheduled (World Bank, 2008).

**Both trade partners and sources of remittances are relatively diversified, lowering Togo’s macroeconomic vulnerability.** As previously reported, remittances have started to make a significant contribution to Togo’s economy. Of the remittances, 30% come from Europe (mainly France), 20% from the US and 15% from within the WAEMU. The diversity of countries is also reflected in the number of trading partners (Figure 45).

42
37 We evaluated such a strategy for the 1987-1991 period (see also Larson and Coleman (1991) who use this methodology for agricultural commodities). The strategy simulated was as follows: in early 1987, the GOV buys a series of put options with strike prices set at an oil price of $20 and expiring over the next five months. The GOV also sells call options at strike prices of $24 for the next five months, provided calls with a strike price of $24/barrel are traded (during most of this period they were not traaed). Once the "collar" is in place, GOV rolls forward the hedge every day by buying the next day's five-month maturity $20 put and selling the next day's five-month maturity $24 call (if available). Consequently, the GOV will always have covered the next five months of its exports with a lower bound, which is financed by selling an upper bound. Figure 5 shows the bands and the periods when the put and call options were exercised.

Depending on movements in the spot price during the period the option hedge is in place, GOV will either exercise the put options at the various maturity dates, or be required to provide the necessary funds when the calls are exercised, or do nothing when the price remains within the band of $20 to $24. We simulated this option strategy until just before the Gulf war, August 1990--implying that the GOV would have bought the last option on March 1, 1990, five months before.

We use daily option prices obtained from NYMEX (settlement prices), eliminating those for which the outstanding interest (number of contracts bought or sold) is zero (when no prices are available for the exercise prices of interest, $20 and $24, we estimate the options premiums
Limiting attention to road transport costs might be problematic if rail played a major and independent role. However, roads dominate transport in Africa, carrying 80 to 90 percent of passenger and freight traffic (Gwilliam, 2011). In most countries, rail only exists along a few corridors that are also served by roads. Of course, regardless of rail’s importance, for the purposes of this paper, it is still a transportation form that uses energy generated from fossil fuels, so including rail would likely have little effect.<sup>31</sup>

# **4 Empirical specification**

My baseline specification testing the effect of transport costs in Equation (10) is: where _yit_ is light output for city _i_ in year _t_ , _pt_ is the price of oil, _xi_ is the distance between city _i_ and its country’s primate city along the road network, _λct_ is a country-year fixed effect (FE), _γi_ is a city fixed effect, and _ωit_ is a linear city-specific time trend. Standard errors are clustered at the city level.<sup>32</sup> The regression sample is limited to cities with a 1992 population of at least 20,000, lit in more than one year, because populations and locations of cities of less than 20,000 are not available for several countries, and cities lit in only one year add no intensive margin information because of the city fixed effects. The time period is limited to 1992–2008 because of the lights data availability. Summary statistics for the resulting sample of 287 cities in 17 years are in Table 2. Distances are measured in kilometers, and prices are in dollars.

As oil prices increased over the course of the last decade, I expect that transport costs increased more for cities farther away from their country’s core. Thus, I can use static distance measures interacted with the exogenous oil price increase to identify the differential change in transport costs faced by near and far cities. I expect that among most periphery cities without significant manufacturing, the less-connected will experience a relative loss in economic activity. This effect may be mitigated or even reversed in cities that do have manufacturing, if they have enough of a home market that its protection outweighs decreasing access to the primate and international markets. However, I have no systematic information on manufacturing. To the extent that this effect is present, it is driving my estimate of _β_ toward zero.

> 31Rail is also less likely to matter than roads because of its higher fuel efficiency and greater dependence on parastatals with long term contracts.

> 32If, alternatively, the methods of Conley (1999) are used to account for spatial and temporal autocorrelation, the resulting standard errors are smaller.

13
**Table 5. Socio‐economic characteristics of sub‐samples with private connections, shared** **<u>connections and all sample, (Addis Ababa, 2016)</u>**

||**P**<br>**(ex**|**rivate co**<br>**electric**<br>**clusive u**<br>**mem**|**nnectio**<br>**ity & w**<br>**se of ho**<br>**bers) ***<br>|**ns for**<br>**ater**<br>**useho**<br>|<br>**ld**|**or**|**Shared**<br>**no-wate**|**connect**<br>**r conne**<br>|**ions**<br>**ction****|||**All s**|**ample**<br>|||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||**Mean**|**Median**|<br>**St.**<br>**Dev**|**p10**|**p90**|**Mean**|**Median**|**St.**<br>**Dev**|**p10**|**p90**|**Mean**|**Median**|**St.**<br>**Dev**|**p10**|**p90**|
|Head of household is<br>female|0.32|0|0.47|0|1|0.28|0|0.45|0|1|0.30|0|0.46|0|1|
|Years of school of head<br>of household|8.99|11|5.02|0|14|8.27|10|4.57|0|14|8.55|10|4.76|0|14|
|Household size|4.95|5|2.03|2|7|3.43|3|1.87|1|6|4.02|4|2.07|1|7|
|Number adults in<br>household|3.55|3.00|1.53|2|6|2.42|2|1.33|1|4|2.86|2|1.51|1|5|
|Total household<br>monthlyincome(USD)|398|256|492|68|829|210|155|191|58|411|283|193|353|58|556|
|House owership|0.51|1.00|0.50|0|1|0.29|0|0.45|0|1|0.37|0|0.48|0|1|
|Electric injera stove|0.93|1.00|0.26|1|1|0.48|0|0.50|0|1|0.65|1|0.48|0|1|
|Cook with biomass|0.21|0.00|0.41|0|1|0.33|0|0.47|0|1|0.28|0|0.45|0|1|
|Number of mobile phones<br>in<br>household|3.26|3.00|1.71|1|6|2.23|2|1.26|1|4|2.64|2|1.54|1|5|
|Access to internet|0.81|1.00|0.39|0|1|0.63|1|0.48|0|1|0.70|1|0.46|0|1|
|TV|0.97|1.00|0.16|1|1|0.81|1|0.39|0|1|0.87|1|0.33|0|1|
|Computer (laptop<br>or desktop pc)|0.30|0.00|0.46|0|1|0.12|0|0.32|0|1|0.19|0|0.39|0|1|
|Car|0.25|0.00|0.43|0|1|0.05|0|0.21|0|0|0.12|0|0.33|0|1|
|Washing machine|0.21|0.00|0.41|0|1|0.05|0|0.22|0|0|0.11|0|0.32|0|1|
|Refrigerator|0.81|1.00|0.40|0|1|0.38|0|0.49|0|1|0.54|1|0.50|0|1|
|Separate kitchen inside<br>the house|0.31|0.00|0.46|0|1|0.09|0|0.28|0|0|0.18|0|0.38|0|1|
|Toilet inside home|0.72|1.00|0.45|0|1|0.45|0|0.50|0|1|0.56|1|0.50|0|1|
|Use of bottled water|0.18|0.00|0.38|0|1|0.13|0|0.33|0|1|0.15|0|0.35|0|1|
|Dwelling with low-<br>qualitymaterials***|0.05|0.00|0.21|0|0|0.25|0|0.43|0|1|0.17|0|0.38|0|1|
|Number of rooms<br>|3.55|3.00|1.70|2|6|1.91|2|1.08|1|3|2.55|2|1.57|1|5|
|in dweling<br>* Household survey data m<br>** This category shows a s<br>*** Walls made of wood an|atched to<br>umbsamb<br>d mud a|utility bi<br>ple of ho<br>nd floor|lling rec<br>useholds<br>made of|ords f<br>that<br>mud/d|or both<br>have ele<br>ung.|water an<br>ctricity o|d electric<br>r water s|ity.<br>hared co|nnecti|ons or|no water|connectio|n.|||

16
<!-- Start of picture text --> Global Ratification of CRC and its Protocols<br>200<br>180<br>160<br>140<br>120<br>100<br>80<br>60<br>40<br>20<br>0<br>1980 1984 1988 1992 1996 2000 2004 2008<br>YEAR<br>CRC CRCAC<br>CRCSL<br>No. of Countries<br><!-- End of picture text -->

**Figure 2: Global Immunization Coverage Rates**

<!-- Start of picture text --> Global Immunization Coverage Rates<br>1980 1990 2000 2010<br>YEAR<br>DPT Measles<br>90<br>80<br>70<br>60<br>Immunization Rate<br>50<br>40<br><!-- End of picture text -->

**Figure 3: DPT Immunization Rates Over Time by Income Levels**

16
following a mean-variance approach. The results are robust to many types of estimations that take into account expected returns, variances, and benchmark effects.

We also use the simulated global funds to look beyond a mean-variance framework and explore the possibility that there is an insurance premium in the returns of global funds. Because global funds, unlike specialized funds, can secure gains by moving away from troubled countries during crisis times, investors might be willing to pay for this benefit by accepting lower expected returns. Our results indicate that global funds do not seem to better shield investors from tail risk. We find that the skewness and kurtosis of global fund returns are similar to those of the simulated global funds. Higher moments of the distribution of returns are important if global funds were to minimize losses during bad times instead of following standard mean-variance models. Moreover, conditional on large negative returns on either specialized funds or the MSCI Emerging Market Index, we find that returns of the simulated global funds are broadly similar to those of global funds. In sum, the lack of diversification does not seem to be explained by a better performance of global funds during turbulent times. It is nevertheless possible that global funds provide some other unobservable benefits that are not captured by the meanvariance and other analyses performed in this paper.

Our findings contribute to several strands of the literature. First, our paper relates to a large literature on the extent of investor international diversification. Most of this research has concentrated on aggregate measures to explain the determinants of international investments and on country portfolios to study the degree to which countries hold assets abroad.<sup>5</sup> More recently, researchers have begun to exploit asset-level data based on institutional investor portfolios, although the evidence remains scarce.<sup>6</sup> Our findings on mutual funds with global reach reinforce the existing evidence of growing but still limited international diversification. Furthermore, our results provide evidence that some of the usual explanations for these international investment patterns, such as the relevance of transaction costs and the lack of available information, are not sufficient to

> 5 A large part of the literature has focused on the home bias puzzle, starting with the seminal work of French and Poterba (1991). See Tesar and Werner (1995), Brennan and Cao (1997), Kraay, Loayza, Serven, and Ventura (2005), Portes and Rey (2005), Aviat and Coeurdacier (2007), Lane and MilesiFerretti (2008), among many others.

> 6 See, for example, Strong and Xu (2003), Cai and Warnock (2006), Eun, Huang, and Lai (2008), and Hau and Rey (2008).

7
**Figure A. 3: Employment status by educational attainment 2008 (Predicted probabilities).**

<!-- Start of picture text --> 100%<br>90%<br>80%<br>70%<br>60%<br>Self-employed<br>50% Wage workers<br>Inactive<br>40%<br>30%<br>20%<br>10%<br>0%<br>female male female male female male female male female male female male<br>No degree Primary school Lower secondary Upper secondary College University and<br>school school higher<br><!-- End of picture text --> Note: these are predicted probabilities obtained from the multinomial logit model. They are calculated holding all other characteristics at their average values.

**Table A 1a: Mean hourly wage and earnings – Thousand VND - 2009**

||Un|deremp|loyed|Not|undere|mployed||Kinh|||Non-K|inh|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||All|Men|Women|All|Men|Women|All|Men|Women|All|Men|Women|
|Employer|17.5|-|-|22.3|-|-|22.2|23.5|19.6|22.2|-|-|
|Self-|8.5|9.7|7.1|9.1|10.2|8.1|9.7|11.0|8.4|6.2|6.8|5.4|
|account|||||||||||||
|workers|||||||||||||
|Wage<br>workers|7.1|7.6|6.4|11.4|11.9|10.6|11.3|11.8|10.5|10.2|10.4|9.9|

_Source: LFS, 2009. Note: - indicates a low number of observations._

**Table A 1b: Mean hourly wage and earnings – Thousand VND - 2009**

||Y<br>|outh(15-24)<br>|||Adult<br>|<br>|
|---|---|---|---|---|---|---|
||All|Men|Women|All|Men|Women|
|Employer|13.8|-|-|22.5|-|-|
|Self-account workers|7.2|8.7|5.9|9.2|10.3|8.2|
|Wage workers|8.9|9.6|8.0|11.9|12.3|11.3|

45
captured by the maritime price data, but restrictions in both are relevant because they could push up the costs of liner services.

The _markup term, q(I, J, k),_ is assumed to depend on the following four variables: _b(I,J,k) = Ak +r CR1 +yl AI + AJ._ _(4)_ The first term, _Pk_ , reflects a product-specific effect that captures differences in transport demand elasticities across sectors. Note that the transport demand elasticities are derived from the final demand for product k in the United States. The second variable is again the variable that captures the existence of cargo reservation policies, which directly limit the extent of competition from foreign liners and thus may push up markups. The third and fourth effects, _AIJ_ and _AIJ,_ are due to the existence of collusive agreements among liner companies on routes between country I and customs district J. We distinguish between two kinds of collusive agreements: price-fixing agreements (which include most conferences), and cooperative working agreements that do not have a binding rate setting authority. A single agreement typically covers routes between the ports of a foreign country and one or more US _coastal_ districts that each consist of several _customs_ districts. Since collusion between liner companies is likely to push up markups, we expect both coefficients sL and<sup>_2_</sup> to show a positive sign. But conference and other price-fixing agreements are likely to be more powerful and to have a greater impact on transport prices than cooperative working agreements, i.e. we expect tV> _i_<sup>_2_</sup> _._ Substituting (4) and (3) into (2), and inserting an error term _enk,_ we obtain: _Pijk = aJ +,Bk+ y T,,k +_ a _d,J + qj + yI/ A,, + VI'A' + o CR] +,pI PS+ p2 PS/2 + k, (5)_ where **_fik_** _(4k +a kY), o (p + r)_ and we expect the coefficients on the three policy indicators, _w,_ qo and ( _2,_ to have a positive sign.<sup>26</sup>

> 26 Since we estimate both product fixed effects and customs district-specific effects, we need to drop one dummy variable (for one customs district) to avoid perfect colinearity among the explanatory variables.

14