rafmacalaba/datause-encoder-data huggingface dataset:
Table 6: Results on Turnover for Power Plants

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Phase 1 Participation|0.439***|0.430***|0.067|-1.417***|
||(4.24)|(6.65)|(0.79)|(-3.85)|
|Phase 2 Participation|0.634***|0.716***|0.299**|-1.161**|
||(5.75)|(8.08)|(2.40)|(-2.14)|
|Phase 1×Log(Surrendered)||||0.144***<br>(3.71)|
|Phase 2×Log(Surrendered)||||0.249***<br>(3.66)|
|Phase 1×Log(Allocated)||||-0.0175<br>(-0.57)|
|Phase 2×Log(Allocated)||||-0.122*<br>(-1.79)|
|Plant Fixed Effects|No|Yes|Yes|Yes|
|Country-by-Year Fixed Effects|No|No|Yes|Yes|
|Observations|4820|4820|4820|4820|
|Adjusted_R_<sup>_2_</sup>|0.016|0.039|0.127|0.140|

Note: Dependent variable is the logarithm of operating revenue. Standard errors are clustered at the firm level and t statistics are shown in the respective parentheses. *, **, and *** indicate significance at the 10, 5, and 1 percent levels.

Our analysis shows that the EU ETS in the first two phases had no statistically significant impact on the number of employees among power plants under the program. Given that electricity markets are mostly national and electricity demand is relatively inelastic, the program is unlikely to hinder the competitiveness of the power plants in the form of reduced demand. Nevertheless, the program increased material costs, most likely due to fuel cost increases from compliance. In addition, the regressions also show a positive impact on firm turnover. Whether the increase in turnover will dominate the increase in material costs and other costs, i.e., the impact of the program on profit, is left for future research.

# **5.2   Cement**

Tables 7-9 present estimation results on employment, material costs and turnover for the cement industry. The model specification in each column is the same as those in the previous section. The fixed-effects model with firm and country-year dummies is again our preferred specification.

16
**Table 10. Climate Change Vulnerability of Fisheries and Coastal Habitats in Countries with the Largest Poor Rural LECZ Populations**

||**Mangrove**<br>|**% of**<br>**Coastal**<br>**Wetlands**|**Vulnerability**<br>**to Climate**<br>**Change**|
|---|---|---|---|
|**Country**|**Loss (%)**<br>**2000-2012**|**Area**<br>**Impacted**|**Impacts on**<br>**Fisheries**|
|India|3.3%|32.3%|Moderate|
|Bangladesh|0.1%|24.3%|High|
|Myanmar|8.4%|50.2%|..|
|Cambodia|4.5%|1.5%|High|
|Nigeria<br>|0.1%|38.8%<br>|High<br>|
|Pakistan|0.3%|61.4%|High|
|Iraq|..|..|..|
|Mozambique|0.2%|47.1%|High|
|Senegal|0.0%|22.0%|High|
|Brazil|0.6%|11.5%|Moderate|
|China|1.9%|39.8%|Moderate|
|Indonesia|3.1%|27.0%|Moderate|
|Philippines|1.3%|45.0%|Low|
|Vietnam|1.1%|29.4%|High|
|Thailand|2.4%|14.7%|Low|
|**Total**|**2.0%**|**31.8%**||

Data on mangrove extent and loss is from Hamilton (2014) "Creation of a high spatiotemporal resolution database of continuous measures of global mangrove tree cover for the 21st Century (CGMFC‐21): A big‐data fusion approach." Available at <u>https://docs.google.com/spreadsheets/d/1wy6uBL8XVXb7wbQ6bzkbZdxWVy50EMr6vmc5 NB3z‐5A/edit?usp=sharing. Total global mangrove extent in 2012 was 81,848.8 km</u><sup>2</sup> ; the above countries account for 55.2% of this total.

Data for % of coastal GDP, agricultural area and wetlands exposed to a 1 meter (m) sea‐level rise accompanied by a 10% intensification of storm surges are from Dasgupta, S., Laplante, B., Murray, S. and Wheeler, D. 2009. "Sea‐ Level Rise and Storm Surges: A Comparative Analysis of Impacts in Developing Countries." Policy Research Working Paper 4901, the World Bank, Washington, D.C. April. Available at <u>http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/0,,contentMDK:22270368~pagePK:642148 25~piPK:64214943~theSitePK:469382,00.html</u> Data on vulnerability of fisheries from Allison, E.H., Perry, A.L., Badjeck, M‐C., Adger, W.N., Brown, K., Conway, D., Halls, A.S., Pilling, G.M., Reynolds, J.D., Andrew, N.L. and Dulvy, N.K. 2009. "Vulnerability of national economies to the impacts of climate change on fisheries." _Fish and Fisheries_ 10:173‐196. For the 132 countries, "high" is for the upper quartile (highest vulnerability), "moderate" for the second quartile, "low" for the third quartile, and "very low" for the bottom quartile.

30
partner antimalarial to which resistance has already evolved or is likely to evolve very quickly is likely to lead to more rapid emergence of resistance to the combination. This finding is consistent with those from other recent studies (Watkins, Sibley et al. 2005).

Cotemporaneous use of a compromising monotherapy (either AMT or PMT) was not as detrimental to the emergence of resistance as one might have anticipated. Although resistance emerged faster with cotemporaneous compromising monotherapy (scenario B), the rate of growth of resistance was limited by the deployment of ACTs. This aspect of the model’s results should be explored further in future research.

The model results indicate that when treatment coverage is relatively more sensitive to drug price, moving from the partial to the full subsidy results in fewer averted deaths and diminished cost-effectiveness. This is a consequence of our motivating argument that greater use of ACTs could expedite the emergence of resistance. Depending on the level of demand elasticity (which would have to be empirically determined), it is possible to identify a level of subsidy at which the greatest number of deaths averted. It is important to recognize that a larger subsidy is not necessarily a good thing if it _excessively_ encourages the use and misuse of ACT.

We found that a delayed introduction of a full subsidy program was possibly the worst scenario both from the perspective of averted deaths and cost-effectiveness. The delay would permit continued use of AMT and PMT and emergence of low-level resistance, which would then be magnified through intense selection pressure with the introduction of a full subsidy program.

An important implication of the results is that using a single combination in all regions places greater selection pressure for parasites to become resistant to that combination. Use of different combinations relieves the selection pressure for resistance to evolve to any single combination. In general, the idea of using the same ACT combination worldwide deserves serious reconsideration. Also, different ACT combinations may, if priced lower than monotherapies, be effective in driving out monotherapies by offering 10
The same examination **was** used for admission to both types of general secondary schools (key and non-key) and to the SVS, with the admission cutoff score being highest for key general secondary (the best route to higher education) and lowest for general secondary; SVS scores fell in between. STS and SWS tests were, as discussed above, different and comparisons are not possible.

The data dccument excess demand for secondary places. They also indicate that students applying for SVS were better qualified than those applying to the general secondary schools.

Absent other data, further interpretation is speculative. We do not know what combination of factors led more than half of the applicant pool to select STS and SWS, although the prospect of a job assignment surely plays an important role. Conversations with Anshan educators indicate that the popularity of the SVS among parents has been growing in recent years as the ability of SVS to place students has been demonstrated.

While the planning and execution of skilled manpower requirements and supply are both based on a good deal of formal reporting, decision making, and instructions issued to lower levels, as described above, it is also important to note that all elements of manpower planning are carried on in the context of continuous consultation and discussion. District and municipal labor and education authorities visit schools and enterprises regularly to confer with principals and managers. The extended nature of the planning process requires many meetings, capped by formal provincial level conferences each year. The SVS, particularly, employ many mechanisms for consultation with employers -- labor surveys, formal meetings, shared faculty -- to interact with enterprises.

# Curriculum Planning

General education curricula are prescribed nationally by the State Education Co-mission, with very little local flexibility allowed. These curricula are followed for the general education courses in all three types of vocational schools.

Curricula in the vocational and technical specialties are set by the relevant technical ministries (e.g., by the Ministry of Machine Building for machining courses; the Ministry of Metallurgy for mining and metal testing courses). These are used in both STS and SWS, which are said to have some small flexibility (up to 102 of curriculum hours) to adapt them to local needs. SVS also use these curricula, but they are said to have much greater flexibility for adaptation (up to 30-40%).

Both SVS and SWS report developing curricula and course content to meet local needs. For SWS, this latitude is mostly exercised when an owning enterprise introduces new technology -- and then principally for in-service courses. SVS have and do exercise considerably more authority to create new courses, and require only municipal education bureau approval.

- 30 -
This study examines multidimensional poverty in Ethiopia focusing on selected monetary and non-monetary dimensions of wellbeing. It follows previous studies to identify the dimensions of deprivations (Alkire and Roche, 2011). The poverty dimensions considered here are selected systematically through public consensus and empirical evidence about people’s values. There is a disagreement on how to measure poverty using these deprivation dimensions, however. The two alternative approaches are scalar indices of multidimensional poverty (e.g. Alkire and Santos, 2010) and the dashboard approach (Ravallion, 2011) that considers deprivation in each dimension one by one. Each has its own pros and cons. Lugo and Ferreira (2012) propose a middle ground to capture the interdependency across dimensions without aggregating the dimensions into one index and this approach is followed here. It allows an assessment of progress on each aspect of deprivation and also on the degree to which individuals experience deprivation in many dimensions at once.

The study documents levels and trends of selected dimensions of wellbeing and then explores the dynamics of multidimensional poverty in Ethiopia over the last decade using Venn diagrams. It uses the Welfare Monitoring and Household Consumption and Expenditure surveys implemented in 2000, 2005, and 2011, to examine the distribution and overlap of key dimensions for different groups of households in Ethiopia. This approach is graphically compelling to view the trends in multidimensional poverty from 2000 -2011. Each Venn diagram represents a set of three deprivation indicators, showing how deprivation on each dimension has changed over time and how different dimensions of deprivation overlap (Atkinson and Lugo, 2010).

The analysis shows considerable progress on many aspects of wellbeing and reductions in the proportion of households experiencing multiple deprivations at once. The proportion of the 3
two homoskedasticity models yielded generally similar estimation results relative to their heteroskedasticity model counterparts. Hausman test suggested that the difference in coefficients between homoskedasticity model and heteroskedasticity model was systematic, and likelihood ratio test also supported our hypothesis that the models controlling for variance heteroskedasticity substantially improved data fit. Simulation generated slightly but significantly higher average WTPs than the heteroskedasticity models. Homoskedasticity Model 5 based on full sample yielded an average WTP of 23.64 Rupees/month (%95 CI: 21.38-25.78), and an average WTP of 60.41 (%95 CI: 55.31-65.43) is obtained for those who reported WTPs significantly different from zero in homoskedasticity Model 6.

# **6. Conclusion and Discussion**

This paper presents a contingent valuation study of non-motorized transport (NMT) project in Pune, India, which has multi-dimensional benefits, including public health, safety, environment, congestion and convenience, etc. The respondents are presented with a detailed description of the project: the current status and use of the roads, the project activities and objectives, the potential project impacts, etc., and then are asked to vote on whether or not to have such a project under a list of costs to the households. The respondents are reminded that if the project passes the referendum with a total payment higher than the project cost, the project will be implemented and the payments will be enforced by the government via the electricity bill, but if the total payment is less than the project cost, the project would not be implemented. As this study is based upon a real development project under consideration, the respondents are found to take the survey seriously. The econometric analyses show that the survey responses are generally reasonable and are consistent with economic theories.

In the design and implementation of the study, the respondents are assumed to have valuation ranges or distributions, rather than single true values, in their minds. The results show that household income, distance from the renovated roads, current use of the transport service, 22
**Table 6: Estimation results using restricted country samples.**

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
||Poisson|Poisson|Poisson|Poisson|Poisson|
|Exporter sample:|Asia|All|Asia|South|South|
|Importer sample:|All|Asia|Asia|South|North|
|LPI (exp.)|0.965**|0.838***|0.176|2.170***|2.484***|
||(0.030)|(0.001)|(0.793)|(0.000)|(0.000)|
|**LPI (exp.) * Parts**|**0.197**|**-0.211****|**-0.201**|**-0.380**|**-0.299**|
||**(0.686)**|**(0.019)**|**(0.664)**|**(0.308)**|**(0.214)**|
|LPI (imp.)|0.328*|1.948***|0.400|0.469*|-0.069|
||(0.065)|(0.000)|(0.327)|(0.080)|(0.733)|
|**LPI (imp.) * Parts**|**0.337****|**0.381****|**0.486****|**1.055*****|**0.348****|
||**(0.014)**|**(0.030)**|**(0.048)**|**(0.000)**|**(0.017)**|
|Parts|-4.669***|-2.887***|-3.267**|-4.649***|-3.175***|
||(0.002)|(0.000)|(0.043)|(0.000)|(0.000)|
|Log(distance)|-0.699***|-1.433***|-3.274***|-1.083***|-0.816***|
||(0.000)|(0.000)|(0.001)|(0.000)|(0.000)|
|Contiguous|0.524*|-1.155***|-1.896***|-0.172|0.704**|
||(0.063)|(0.007)|(0.003)|(0.665)|(0.042)|
|Language|1.577***|1.089***|-0.361|0.590|0.302|
||(0.000)|(0.000)|(0.712)|(0.129)|(0.412)|
|Colony|-0.883**|0.113|-1.509*|0.873*|0.024|
||(0.026)|(0.582)|(0.092)|(0.097)|(0.952)|
|Colonizer|0.025|-0.640|-1447.517|-1.368**|-1.153*|
||(0.958)|(0.158)|(0.195)|(0.030)|(0.079)|
|Log(GDP exp.)|0.805***|0.622***|1.055***|1.011***|1.028***|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|Log(GDP imp.)|0.803***|0.510***|1.261***|0.880***|0.895***|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|Constant|-29.766***|-16.074***|-26.706***|-38.791***|-41.458***|
||(0.000)|(0.000)|(0.001)|(0.000)|(0.000)|
|R2|0.263|0.200|0.055|0.281|0.286|
|Observations|3456|3456|264|22260|27772|

_Note: The dependent variable in each case is exports. All trade costs variables are transformed as per Baier and Bergstrand (2009), as discussed in the main text. Estimation methods are indicated at the top of each column. Prob. values based on robust standard errors adjusted for clustering by country pair are in parentheses beneath the parameter estimates. Statistical significance is indicated by * (10%), ** (5%), and *** (1%)._ 29
countries to self-report on their statistical capacity. These include the EU Snapshot Tool, the UN NQAF self-check tool, and the Paris21 NSDS self-assessment tool. But there is no publicly available information on how many years or how many countries for which these tools have been implemented. The only available information includes the (number of) indicators each tool employs, which we can compare against the SPI’s five pillars. Table S5 in Appendix A provides the links to all the tools discussed above (as well as briefly reviews some other tools on related development topics such as open government data, governance, poverty and human capital).

Several remarks are useful. First, except for the IIAG that focuses on Africa, all the remaining tools are global and use a scale of 0-100, with a larger number indicating better capacity. Regarding the number of countries (and years) coverage, the ODIN comes first (192 countries during 20162022), followed by the SPI (186 countries during 2016-2022), the SCI (145 countries during 20042020), the ODB (116 countries during 2013-2016, and 30 countries for 2017), the GDB (109 countries during 2021), and the IIAG (54 countries during 2010-2019). While the number of countries that an index covers can vary widely over the years, for comparison purposes, we show the number of countries covered by an index for its latest year available. All the indexes are generated annually, except for the GDB that is conducted biennially.

Second, except for the SCI and the IIAG that use simple weighting, all the indexes employ some form of nested weighting method to construct the overall score. The details of the nested structure differ significantly across indexes. The ODIN has a two-level nested structure with 65 indicators being categorized (under 22 smaller sub-groups) in three groups, and the ODIN overall score is an equal weighted average of these three group scores. The GDB also has a nested structure of pillars, indicators, sub-sections, and sub-questions, where the score at each level is a weighted average of its sub-components, which results in an overall weighted score. The SPI has a threelevel nested weight structure, and its overall score is based on a mathematical framework, where desirable properties of the index are explicitly discussed such as symmetry, monotonicity, and subgroup decomposability (Cameron _et al._ , 2021).

Finally, regarding the number of indicators, the three self-assessment tools as a group have more indicators than the other indexes, with the Paris21 NSDS self-assessment tool leading this group (149), to be followed by the EU Snapshot Tool (131), and the UN NQAF self-check tool (87) (the numbers in parentheses are the number of indicators). For the other tools, the GDB ranks first (55), to be followed by the SPI (51), the ODB (46), the ODIN (44), the SCI (21), and the IIAG 9
both consumers and rural entrepreneurs with easier access to local markets. Applying marketing techniques requires certain business management knowledge to increase market demand and the number of customers. These marketing techniques may involve identifying new customers, by differentiating products or services (finding a market niche), or by using scale economies. Economies of scale can be achieved by informal or cooperative groups of entrepreneurs who provide similar products or services. They may also be achieved through the formation of industrial clusters. Information about the products and services being offered can also be instrumental in stimulating consumer demand by informing consumers where they can go to find what they want to buy. Cell phones, which are rapidly saturating rural areas, can be utilized to provide this type of marketing information. Market information can be improved by providing appropriate management services, including skills and management training to rural entrepreneurs.

# **5.2 Access to Marketplace and Market information**

Access roads, transportation, and available market information enable entrepreneurs to access to market. The World Bank (2009c) emphasizes that roads connect people not only to markets, but also to essential services such as health services and schools. New road or bridge construction improves market access for both suppliers and customers, thus increasing market demand and enabling entrepreneurs to transport more supplies to meet that increased demand. The poor quality and high cost of transportation are an extra burden that diminishes the profitability of small rural business operations. Many entrepreneurs perceived transportation as one of the top four obstacles (figure 3.2). Having access to market information enables existing or potential entrepreneurs and customers to broaden their knowledge and information of the market, take advantage of market opportunities, and make correspondent strategies.

# **5.3 Access to Finance**

Access to finance is one of the most important assets for a business to be successful, especially for the rural poor, who require collateral. The limited availability of much-needed loans remains a principal constraint among rural entrepreneurs because they need loans to start and expand their businesses (Islam 1997).

Improving the access entrepreneurs have to finance can be accomplished in a number of ways. In Yemen, increasing the number of financial institutions and improving the financial literacy of entrepreneurs suggest themselves as ways forward. According to the survey data, 19
looks at districts within two countries, Ghana and Cˆote d’Ivoire, and argues that local production of cash crops, specifically cocoa, spurred urbanization outside of the few largest cities. In his setup, consistent with mine, these secondary towns form primarily as “consumption cities” where farmers sell their products and buy services and imported goods, as opposed to manufacturing centers as is often assumed in models of urbanization and city formation. Unlike all these papers, the present outcome of interest is a proxy for economic activity (lights) that is available for individual cities on an annual basis, as opposed to population, which is typically only available for censuses carried out at most every ten years. This allows me to observe short-run (annual) changes and to control for all potentially confounding country-level variation with country*year In stressing the role played by the largest city in each country, this work also has implications for the study of urban primacy (Ades and Glaeser, 1995; Henderson, 2002) and decentralization. I find that primate cities are growing slower than others on average net of the transport cost effect. Finally, in focusing on the importance of coastal cities, this work relates to the literature on geographic determinants of growth, including Gallup, Sachs and Mellinger (1999) and Collier (2007), which emphasize coastal access and the problems of being landlocked, respectively.

The remainder of the paper has the following structure. Section 2 provides a simple conceptual framework to facilitate interpretation. In section 3, I describe the lights and roads data and the methods used to integrate them. In section 4, I describe the econometric specification used, and in section 5, I report results. Section 6 concludes. An Appendix provides further details on the data and methods used.

# **2 Conceptual framework**

Economists often think about the role of intercity transport costs in city growth in the context of two-region New Economic Geography (NEG) models following Krugman (1991), or one of many variants, including one that adds agricultural transport costs (Fujita, Krugman and Venables, 1999), one that adds a foreign sector accessible from a port in one city (Behrens, Gaign ́e, Ottaviano and Thisse, 2006), and one that is tailored to African urban primacy (Pholo Bala, 2009). While changes in transport costs drive urban growth in these models, they do so by inducing manufacturing firms to change their location from the (ex-post) periphery city to the (ex-post) core, with its larger home-market This is unlikely to be the driving force behind the current growth of most cities 4
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