rafmacalaba/data-use-mentions-extended huggingface dataset:
# _<u>Geography</u>_

The physical attributes of shared rivers have long been recognized as important to understanding conflict and cooperation over transboundary water (e.g. Le Marquand, 1977; Toset et al., 2000). In particular, empirical studies considering the river basin as the unit of analysis find that the greater the significance of the particular basin to the respective countries the higher the cooperation evinced. In addition, the more control a country has over a given river basin the less cooperation (or more conflict) is evinced because that country perceives more benefits from unilateral action (Espey and Towfique, 2004; see also Gleditsch et al., 2006).

Following Espey and Towfique (2004), we derive two sets of geographic measures. The first set proxies for the level of control a given country (within the dyad) has over the basin as well as the level of control the entire country dyad has over the basin. The second set proxies for the importance of the basin to a given country (within the dyad) as well as the importance of the basin to the entire country dyad. The measure for control is estimated by calculating the percentage of the total river basin within the boundaries of each country, while the proxy for importance is derived from the size of the river basin within the country, expressed as a percentage of the total area of the country. Two numbers are then obtained for that dyad in order to gauge asymmetry and country-wide nuances: a ratio derived value and a sum-derived value ( **_Basin Control Sum; Basin_**

**_Control Ratio; Basin Importance Sum; Basin Importance Ratio_** ). The variables are calculated from data in OSU’s International River Basin Register. The geography variables are time invariant since physical attributes of a basin, generally, do not change drastically over time. We are able to account for the changes that took place during the collapse of the Soviet Union as well as other major geopolitical changes
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, another year of schooling increases earnings by about 10 percent (Psacharopoulos 1994). But estimated returns to schooling are low in general in centrally planned and transition economies. For example, in China the estimates of the returns to schooling ranged from 1 to 5 percent in the mid 1980s (Jamison and van der Gaag 1987; Byron and Manolato 1990; Meng 1995), and 3 percent in 1989 (Xie and Hannum 1996). Gregory and Meng (1995), in a very useful analysis of rural industrial data, disaggregated their sample into two groups: those who were allocated their jobs and those who found them on their own. Returns to 14
due to armed conflict but for more idiosyncratic reasons. We check robustness of this approach in two ways: (i) using all of the refugee stock observations available in the data set, and (ii) computing refugee flows as the positive time differences in refugee stocks from year to year (setting negative time differences to zero). The results are robust to these two alternatives.

<!-- Start of picture text --> 1987 1992 1997 2002 2007 2012 2017<br>Year<br>20<br>15<br>10<br>Number of refugees (million)<br>5<br><!-- End of picture text --> Figure 1: Global refugee population, 1987-2017 Note: This figure plots the global stock of refugees.

The data on bilateral distance and contiguity come from CEPII. The distance variable refers to the great circle distance between the most populated cities of each country in the pair. The contiguity indicator is equal to one if the two countries share a land border.

Figure 1 charts the global refugee population over time. The sharp increase in the number of refugees over the past decade is evident. Such refugee movements can have significant impacts on the destination countries. Table 1 reports the top 10 destination and top 10 source countries in the most recent available year and illustrates that the 6
- Walton, G. M., and G. L. Cohen. 2011. “A Brief Social-Belonging Intervention Improves Academic and Health Outcomes of Minority Students.” _Science_ 331(6023): 1447–1451.

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- World Bank. 2018. “Why Do Indonesian Adolescent Boys have Poorer Schooling Outcomes than Girls?” _EAPGIL Brief_ 5. East Asia and Pacific Gender Innovation Lab. Washington, DC: World Bank. Available at: http://hdl.handle.net/10986/31487.

- Yeager, D. S., P. Hanselman, G. M. Walton, J. S. Murray, R. Crosnoe, C. Muller, E. Tipton, B. Schneider, C. S. Hulleman, C. P. Hinojosa, D. Paunesku, C. Romero, K. Flint, A. Roberts, J. Trott, R. Iachan, J. Buontempo, S. M. Yang, C. M. Carvalho, P. R. Hahn, M. Gopalan, P. Mhatre, R. Ferguson, A. L. Duckworth, and C. S. Dweck. 2019. “A national experiment reveals where a growth mindset improves achievement.” _Nature_ 573: 364–369.

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“survey regression” variables listed in Table 8) and on a number of data series that are published monthly and are readily available (“public data regression” variables in Table 8). If there is a close fit between the public data and per capita income, then the equation would be viable for forecasting purposes. However, the final column of Table 8 shows that such equations never fit well, with values of adjusted R<sup>2</sup> always below 0.15. The fit is substantially better when one uses the survey regression variables (first column of numbers in Table 8), but these are not available in the absence of survey data. When the public data are added to the survey regression variables the improvement in fit is always very small.

One could look more systematically for potential predictors of real per capita income for major groups, but our basic explorations are not promising. There do not appear to be cheaper or easier ways to determine reliably the effect of shocks on households, and so there is a continued need for regular surveys of household living standards.

Losers and Winners in Recession: Thailand 2008-09 25
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- Jarosch, G. and L. Pilossoph (2019
|18.2|
|_Special safeguard_|10|5|2|14.1|21.7|22.2|50.0|20.0|
|Andean|12|3|0|16.9|13.0|0.0|25.0|0.0|
|AEC 24|1|0|1|1.4|0.0|11.1|0.0|100.0|
|**TOTAL**|**71**|**23**|**9**|**100.0**|**100.0**|**100.0**|**32.4**|**12.7**|

1/ The information on safeguards is broken down in accordance with the existing legislation, Decree 152/98 for WTO member countries; Decree 1407/99 for all the so-called special safeguard countries; Andean rules; ACE 24, which is the Agreement between Colombia and Chile within the framework of ALADI, using ALADI ́s Resolution No. 70.

Source: Calculated by the authors based on Ministry of Trade data.

# **_A. Evolution of investigations 1990-2004_**

Between 1990 and 2004 there have been a total of 71 dumping and safeguard related investigations in Colombia. Of these, 37 are dumping investigations and 34 are safeguard

> 17 Finger, J.M. (2002), “Safeguards: Making sense of GATT/WTO provisions allowing for import restrictions” in Development, Trade and the WTO: a Handbook, Bernard Hoekman, Aaditya Mattoo and Philip English eds., World Bank.

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In many developing economies, there exist substantial wage differentials between the formal and informal sectors, and the loss of a high wage job can be sufficient to plunge the entire household into poverty. A few of the most recent studies have attempted to predict not only how many jobs will be lost (or gained) in the formal sector as a result of a trade policy shock, but also which individuals are most likely to lose their job. This level of resolution represents the ultimate goal of the literature in this area, but much more work will be required before such predictions can be made with confidence.

Other research issues needing immediate attention include: (a) the treatment of marketing costs and the associated transmission of border price changes to rural producers and consumers; evidence indicates that limited price transmission can severely limit the gains to the poor from trade reforms; (b) reconciliation of household survey and national accounts data; in the absence of such reconciliation the micro- and macro-predictions can be wildly inconsistent; and (c) the appropriate characterization of consumption behavior. In the longer run, research on trade/poverty linkages will also benefit greatly from independent advances in the literature characterizing the links between trade, trade policy, and economic growth. The latter is the only proven means of obtaining significant longrun reductions in global poverty.

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as the primary input to contract production in response to changes in productivity. These productivity shifts, however, not only contract hours and outputs, they also have a statistically significant negative effect on profits per owner hour worked, which decrease by 16%. As is standard in the literature, these estimates of profits do not exclude income or wages paid to the owner; profit reductions are reductions in earned income for the owner-operators of single-person firms and reductions in profits per owner hour worked are reductions in hourly wages.

On a weekly basis, the analysis cannot reject that outages have no effect on the labor supply of firm owners in firms with workers. Rather, the study documents a dynamic reshuffling of firm owner labor supply across days, suggestive evidence of dynamic adjustments in the production process in response to blackouts. On days with lights following a blackout day, firm owners increase both intensive and extensive labor supply by about 5% each; on the second of two consecutive blackout days, firm owners decrease their intensive labor supply by about 20 minutes; on blackout days following a day with lights, there is no measurable effect on firm owner labor supply.<sup>3</sup>

> 3These intertemporal daily labor supply findings contribute to a debate in labor economics regarding labor supply elasticity across more and less productive work time, though this context is complicated by the fact that firm owners with

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poverty estimate for rural Vietnam of around 7.5 percent. This is considerably lower than the MOLISA rural poverty rate of 19 percent for that same year.

Although, MOLISA sets up an income poverty line to identify poor households, this poverty line is not applied since collection of income for the whole population is very costly, and almost impossible. In reality, the poverty classification procedure is rather complicated. Basically, a village committee prepares a list of the poor based on their own criteria, which may, for example, include asset levels, food security, type of housing, and school-going of children. The number and nature of the criteria differ widely between villages. The preliminary list is submitted to a commune-level committee of Hunger Eradication and Poverty Reduction (HEPR), which might conduct a very simple income survey for some households on the list. These surveyed households are expected to have income around the poverty line, thus their income data should be collected for crosscheck. The resulting incomes are compared to the income poverty line of the Ministry of Labour, War Invalids and Social Affairs (MOLISA). Those households with higher per capita income than this poverty line are excluded from the list. Finally, the refined list is updated by the village committee and the People’s Committee and People’s Council in an iterative procedure (MOLISA, 2003). Thus there is a large difference between the poverty estimates based on the VHLSS and the poverty incidence reported by MOLISA.

To facilitate comparisons between our income poverty estimates and the incomebased poverty rates from MOLISA, we adjust the income poverty line such that income poverty estimated using the 2006 VHLLS coincides with the MOLISA poverty rate (at around 18.5 percent for rural areas in 2006). The income poverty is set at 3,288,000 VND/person/year (in national real terms).

# **III. Methodology**

The small area estimation method developed by Elbers, Lanjouw and Lanjouw (2002, 2003) is arguably most popular
toolkit to foster inclusive growth, an integrated analysis of the distributional implications of fiscal policy was missing.

The paper finds that Turkey’s overall tax and social spending policy significantly reduces income inequality in the population. The observed inequality-reducing impact is driven primarily by the strong equalizing effect of social spending on education and health. Direct taxes and transfer schemes are also equalizing and help mitigate the inequality-increasing impact of indirect taxes. In contrast, with regards to poverty, the system of direct transfers and direct taxes cannot counterweight the poverty-increasing impact of indirect taxes, and therefore net increases are observed in poverty indicators.

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Jäckle, A., Lynn, P., Sinibaldi, J., Tipping, S. (2013). The effect of interviewer experience, attitudes, personality and skills on respondent co-operation with face-to-face surveys. Survey Research Methods, Vol.7, No.1, pp. 1-15.

Johnson, W.T., Delamater J.D. (1976). Response effects in sex surveys. Public Opinion Quarterly; 40: 165–81 Kalton, G. and Schuman, H. (1982). The effect of the question on survey responses: A Review. Journal of the Royal Statistical Society. Series A (General), Vol. 145 (1), 42-73 Kane, Emily W., and Macaulay, L. J. (1993). Interviewer gender and gender attitudes. Public Opinion Quarterly 57:1–28 Karlan, D. and Zinman, J. (2012). List randomization for sensitive behavior: An application of measuring use of loan proceeds. Journal of Development Economics 98, 71-75 Laajaj, R. and Macour. K. (2017). Measuring Skills in Developing Countries. World Bank Policy Research Working Paper 8000.

Lenski, G. E., and Leggett, J.C. (1960). Caste, class, and deference in the research interview. American Sociological Review 65:463–467 Lupu, N., and K. Michelitch. 2018. Advances in Survey Methods for the Developing World. Annual Review of Political Science 21: 195-214.

McKenzie and Rosenzweig, (2012). Preface for symposium on measurement and survey design. Journal of Development Economics, vol. 98, 1-2 Randall, S., Coast, E., Compaore, N. and Antoine, P. (2013). The power of the interviewer: a qualitative perspective on African survey data collection. Demographic research, 28 (27). 763-792.

Reese, S.D., Danielson, W. A., Shoemaker
the winter, around 13 percent of rich households qualify for the lifeline subsidy. These findings indicate that a static subsidy scheme throughout the year is failing to protect the poor, and provides an unnecessary benefit to the richest households in the winter months, when electricity affordability is less of a concern.

# **Robustness Checks**

# **_Low match rate_**

Our analysis is predicated on the assumption that the PMT scores matched to the billing data tell us about the patterns of electricity consumption and welfare at the national level. However, only 45 percent of DISCO records could be matched with the PMT score through the NSER.<sup>10</sup> A relatively small share of records could not be matched due to errors in the CNICs records in the DISCO database. The majority of the unmatched households could not be found in the NSER survey data, however, likely because those families did not have a CNIC at the time of the survey in 2010. The survey is currently in the process of being updated, however, meaning that in future the match rate is likely to be significantly higher.

> 10 The unmatched 55% will have similar socioeconomic breakdown or might be skewed towards the better off households as records of the initial NSER survey shows that most refusals came from better off households. The K‐density plot shows the variance in PMT across the matched sample (see Appendix, part E).

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are significantly more likely to find themselves in inadequate, low-quality housing with minimal access to improved facilities. Future research needs to investigate why that is the case.

Our results also indicate that countries need to be more innovative in providing adequate housing to everyone – particularly to vulnerable groups. Creative approaches in housing finance to improve existing housing stock, unlocking land supply, and inclusive urban planning will be required to provide adequate housing to all segments of the current population and the 1.6 billion people who will be added to urban areas by 2030.

The cross-country nature of the analysis and the reliance on household surveys entails several caveats. While household surveys provide a great source of micro-level data, they are expensive to execute and are only available for certain years. As of now, we only take the most recent HH survey into consideration for the computation of the _AHI_ . A next step would be to apply our
The concept of a project design involves Bank staff assessment of the technical and economic viability of the project. For example, Bank staff engineers examine the technical specifications and project economists assess the economic impact – in conjunction with government staff. The first developing country loan proposed to the World Bank underwent substantial revisions following the staff‘s evaluation.<sup>65</sup> The impact of project evaluation and project supervision is inherently difficult to measure. A recent study uses a database of World Bank financed projects to disentangle the impact of the country policy and institutional environment from project specific factors affecting the success of these projects.<sup>66</sup> The authors find that country-level "macro" measures of the quality of policies and institutions are very strongly correlated with project outcomes, confirming a common result from past research on aid effectiveness. At the project level, they find that the success of individual development projects varies much more within countries than it does between countries. Data were collated to identify the project-level "micro" correlates of project outcomes, and the authors conclude that project size, as well as supervision efforts significantly

> 65 See Kapur, Lewis and Webb (1997), page 82.  There were also some controversial issues surrounding arrears clearance to lenders prior to project approval.

> 66 See Denizer et al (2011).

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thus allowing individual legislators to overcome their collective action problem. This data, however, should still be taken with caution.

**Table 10:  Enactment Rates of President’s Bills at the House of Representatives**

|Congress/Administration|President’s PriorityBills|President’s PriorityBills Enacted|Enactment Rate|
|---|---|---|---|
|8th/Aquino|93|54|58.1%|
|12th/Arroyo|20|8|40.0%|

Source: Kawanaka (2010) First, higher enactment rates may come at a price. The frequently made assertion about the politics of legislative process in the Philippines is that the president needs to “pay off” individual legislators to mobilize their votes in favor of his/her priority bills because of the absence of party discipline (Kasuya 2008, Kawanaka 2010). For that reason it is necessary for him/her to be selective of which bills to push. A related concern often voiced by both observers and some political actors, though, is that the process of negotiating legislators’ support sometimes entails not only side payments (e.g., preferential releases of the “pork barrel” budget) but also some substantive compromise in the content of the bill itself. On matters related to decentralization, some are weary that pushing for a technically sound bill, say, to reform the IRA distribution formula, might end up being altered into something far less acceptable in the end.

> 24 The data on the US state bills is from G. Gamm and T. Kousser (2010) “Broad Bills or Particularistic Policy? Historical Patterns in American State Legislatures,” _American Political Science Review_ Vol. 104, No. 1, pp. 151-170.

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