rafmacalaba/data-use-mentions-extended huggingface dataset:
identity of the specific agents participating in a GVC is crucial. Within these GVCs, contracting is often relational in nature, and thus more likely to exhibit persistence than in transactions involving raw materials and homogeneous inputs. An extreme version of this type of relational contracting arises when parties involved in a GVC altogether by-pass the market mechanism and decide to transact within firm boundaries, by having the buyer vertically integrate the seller or vice versa. The prevalence of intrafirm trade flows in world trade flows exemplifies the importance of relational aspects in the growth of GVCs. For instance, U.S. customs data suggest that, in recent years, close to one-half of U.S. imports involve related-party transactions (see Antràs, 2003). At the global level, intrafirm trade has been estimated to account for about one-third of world trade Nevertheless, the internalization of transactions in a GVC is just one of the many organizational responses to the contractual vagaries associated with cross-border transactions. In an influential study, Gereffi , Humphrey, and Sturgeon (2005) elaborate a much more extensive taxonomy of potential governance forms within GVCs, and various researchers have built on their work to shed light on the relative prevalence of these governance forms through a number of interesting case studies.

20
difficult to implement and also subject to frequent changes. This would speak in favor of using standard statistics such as GDP per capita or poverty rates to rank countries and allocate aid so as to capture basic but well understood indicators. Guillaumont, 2008 argues that the poverty-efficiency position is not backed by evidence and that a structural vulnerability approach whereby countries are considered based on their structural and exogenous constraints would be preferable, which is an argument for allocating more aid to the LDCs.

A different stream of the literature (Llavador and Roemer, 2001; Cogneau and Naudet, 2007) focuses instead on equal opportunities. These authors believe that the distribution 5
. We used the first definition because it displays more variation (in terms of both range and standard deviation) than the second. Also, the correlation between liberal and conservative estimates is stronger for the first definition than for the second (0.9799 versus 0.8951). Between the two estimates of this preferred definition, the conservative estimate is given preference over the liberal one as the former has more variation than the latter (standard deviation and range of 0.209 and 0.828 as compared to 0.206 and 0.801, respectively). Nonetheless, all the four statistics (from the two definitions, and the two estimates per definition) are positively and (statistically highly) significantly correlated with one another, and the main results are robust to the use of alternative definitions. Data on other factor intensities (i.e., capital, human capital and natural resource intensity) of the industries are from Manova (2013). Table A.2 provides the average factor-intensities of the 28 industries used in the analysis.

Table A.1 reports summary statistics for these variables. Our main independent variable is the interaction between institutional quality (a country-specific measure) and contract-intensity (an industryspecific measure).

# **5 Results**

We are interested in the effects of institutions on overall trade flows, and the mechanism through which it operates. In this section, we first examine the effect of institutions on main outcomes of interest (probability of exporting, trade volume, product scope, export destination, and export survival rate) using country and industry level characteristics (Subsection 5.1). We then investigate our main hypothesis using more disaggregated data which come from the firm-level database (Subsection 5.2). Even though the estimations in both subsections are done using alternative techniques, we wind up the 9
The major reason to prefer DEA over SFA is that DEA can be used even when conventional cost and profit functions that depend on optimising reactions to prices can not be justified. Since it is likely that regulations and other market imperfections distort prices in the East Asian banking sectors complicating the application of SFA to price and quantity data, it seems that DEA is more suitable for examining the efficiency of East Asian banks. A practical consideration to use DEA instead of SFA is that it avoids having to measure output prices, which are not available for transactions services and fee-based outputs.

Most bank efficiency studies look at the US or other developed countries. Bhattacharyya et al. (1997) have applied such techniques to Indian banks in the first study using data of a developing country. The only bank efficiency studies so far that have used East Asian banking data are Leightner and Lovell (1997), Leightner (1997), Gilbert and Wilson (1998) and Hao et al. (1999). Leightner and Lovell (1997) use linear programming techniques and Thai banking data to show that Thai banks experienced high growth rates in production during the years of 1990-94. They argue that these high growth rates indicate an unusual level of success of the banking system. Leightner (1997) uses identical linear programming techniques on data between 1990-95 for Thailand's finance and securities companies. He shows that, although the finance and security companies enjoyed tremendous profitability and rapid growth, these firms were not fully efficient, i.e. that profits could have been increased even more by changing the output and/or input mix. He also finds strong economies of scale and argues that the finance and security companies are too small to compete with the larger banks. Gilbert and Wilson (1998) use linear programming techniques to investigate the effects of privatisation and deregulation on the productivity of Korean banks over the years 1980-94. They find that Korean banks responded to privatisation and deregulation by altering their mix of inputs and outputs, yielding large changes in productivity.
<br>• "Keep up with the required work" • replacement""Do not forget to put things back in<br>their proper place"<br>Phone call reminder week 5<br>Phone call reminder week 6<br>• "Persist at tasks after meeting setbacks • "Return phone calls in a timelyfashion"<br>or failures"<br>• "Keep up with the required work" • "Try to work extra hard on a task to<br>• "If you are running late, call ahead to • make sure that it is done right""Do not leave a mess in your work<br>notify those who are waiting for you"<br>• "Clean up the surroundings of your • place""If you need to leave the workplace,<br>work place" ask the supervisor first"<br>Phone call reminder week 8<br>Phone call reminder week 7<br>• "Try to give the highest quality in<br>••• "Put things back in their proper place""Put your mind on the task at hand""Carefully follow the instructions •• everything you do""Get to appointments on time""Try to carry out your obligations to<br>the best of your ability"<br>• given to you by your supervisor""Do not forget meetings" • "Do not leave your belongings<br>unattended, for example your helmet,<br>safety jacket"<br>End-line survey Mid-line survey<br>(371) (344)<br>May 2020 · Phone January 2020 · F2F<br><!-- End of picture text --> _Notes_ : This figure expands on Figure 1 and shows the main conscientiousness reminders for each follow-up phone call. The number of respondents is in parenthesis. _F2F_ indicates the survey or intervention was done face-to-face, while phone surveys are
Building prosperity for a majority of Nepalis will entail not just safeguarding and cementing the gains already made, but also boosting productivity of the economy in a manner that will help them realize higher income levels. Work related migration, primarily to overseas destinations, has been a critical driver of mobility experienced by Nepalis over their lifetimes and across generations. But taking it to the next level and building a robust middle class will require the creation of good jobs in a large enough scale for those that remain in Nepal.

# **References**

Alesina, A. and N. Fuchs-Schuendeln (2007), "Good Bye Lenin (or not?) The Effect of Communism on People’s Preferences," _American Economic Review_ , 97:1507-1528.

- Banerjee, A. and E. Duflo (2008). “What is middle class about the Middle Classes around the World”. _Journal of Economic Perspectives_ 22(2):3-28

- Benabou, R. and J. Tirole (2006), "Beliefs in a Just World and Redistributive Politics," _Quarterly Journal of Economics_ , 121(2), 699-746.

- Birdsall, N. (2010). “The (Indispensable) Middle Clsas in Developing Countries; or, the Rich and the Rest, Not the Poor and the Rest”, _Working Paper #207 Center for Global Development_ , Washington DC

- Birdsall, N., F. Ferreira, L.F. Lopez-Calva and J. Rigolini (2011). “The Middle Class in Developing Countries: Concept, Measurement and Recent Trends”. _Mimeo_ . The World Bank, Washington DC

- Chetty, R., J. Friedman, N. Hilger, E. Saez, D. Schanzenbach, and D. Yagan. 2010. “How Does Your Kindergarten Classroom Affect Your Earnings? Evidence from Project STAR.” _NBER Working Paper 16381_ , National Bureau of Economic Research, Cambridge, MA

- Dang, H-Anh and Lanjouw, P. (2013). “Measuring Poverty
Also, of the land reform beneficiaries, 32% had access to pensions, and 6% reported to have earlier accessed the housing grant.<sup>8</sup> To put the characteristics of land reform beneficiaries in perspective, it would be desirable to compare them to those of the country as a whole. For the variables that are available in both surveys, such a comparison can be undertaken using the SALDRU survey. In doing so one has to bear in mind that, with limitations in variable coverage? and an absence of reliable recall data, the ability to make systematic inferences on beneficiaries pre-project status is limited essentially to infrastructure access. Nonetheless, probit regression for land reform participation performed on the combined sample of land reform beneficiaries and the rural non-white part of the 1993 SALDRU survey' suggest that, even within this group, the program was well targeted. The fact that land reform beneficiaries had systematically worse infrastructure access than non-beneficiaries within the target group clearly allows to reject the hypothesis that program benefits are appropriated by non-poor or non-eligible beneficiaries.

Detailed results are presented in table 4. As illustrated in equation (1), land reform beneficiaries' access to social infrastructure is significantly below that of even the remainder of the rural non-white population. Limited access to water and bad roads stand out. Similarly, they are far more distant from good roads than the population average and much more likely to have no toilet. In addition, they have more people in higher age and a lower dependency ratio, with the number of persons aged between 14 and 60 being marginally significant. While the head's age is highly significant, education is not. The high significance of provincial dummies points towards large differences across provinces in the extent of land reform implementation. Adding household assets (in equation 2) indicates that, as noted earlier, land reform beneficiaries are more likely to have access to farm animals (cattle and poultry) as well as electricity, as noted from the descriptive analysis.

All of this suggests
Commission). 2007. _Review of Sector Taxation Policies and Determining the Elasticity of Penetration and Price of the Various Telecommunication Services in Uganda._ Kampala— ——. 2009a. _Status of the Communications Market—December 2008_ . Kampala

- ———. 2009b. _A Review of the Post and Telecommunications Market 2008/09_ . Kampala

- ———. 2010. _Status of the Communications Market—December 2009_ . Kampala

- World Bank. 2009a. _Information and Communications for Development 2009: Extending Reach and Increasing Impact_ . Washington, DC: World Bank.

# Irrigation

- Heidecke, Claudia. 2006. Development and Evaluation of a Regional Water Poverty Index for Benin. IFPRI Discussion Paper 145, International Food Policy Research Institute. Washington DC

- Svendsen, Mark, Mandy Ewing, and Siwa Msangi. 2008. “Watermarks: Indicators of Irrigation Sector Performance in Africa.” AICD Background Paper 4, Africa Region, World Bank, Washington, DC.

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# **2 Related Literature**

Our paper relates to a large literature estimating sequential schooling models under uncertainty, with seminal contributions by Keane and Wolpin (2001), Eckstein and Wolpin (1998), and Keane (2002). This literature models college enrollment, performance, and college outcomes, and uncovers structural parameters based on students’ observed choices during college. In one strand of this literature, researchers model students as acquiring information (learning) throughout college—regarding, for instance, their ability and preferences for college or specific majors, and their expected labor market performance. This literature includes Arcidiacono (2004), Arcidiacono et al (2016), Ozdagli and Trachter (2011), Stinebrickner and Stinebrickner (2014), and Trachter (2015). As in these papers, students in our model adjust their expected graduation probability based on classes completed and choose effort accordingly.

The idea that higher education is risky is not new (Levhari and Weiss 1974, Altonji 1993, Akyol and Athreya 2005), but the recent availability of college transcript data in the U.S. has helped estimate the role of risk in students’ performance. These data reveal substantial and persistent heterogeneity in students’ credit accumulation rates, which are strongly related to graduation probability. According to Hendricks and Leukhina (2017, 2018), based on their credit accumulation rates more than 50 percent of college entrants should be able to forecast whether they are at least 80 percent likely to graduate. According to Stange (2012), the large uncertainty faced by students makes them place a high value on the ability to drop out at any point rather than pre-commit to completing all graduation requirements. Our paper is similar to these in the use of administrative data to track students’ performance, but different in that the risk associated to class completion or college continuity is not fully exogenous as in these papers but depends on an endogenous variable—student effort.

While the literature has placed much attention on the role of ability in performance and
NVRB during the commitment period (Table 2). This could be for one of two reasons: either marginal debtors have access to cheaper forms of credit than overdrafts, or marginal debtors are already maxed out on overdrafts.

While the effect of SSP on the debt stock is not significantly different from zero, the point estimate is economically meaningful and very close in magnitude to the treatment effect on savings. As a result, we find no evidence that SSP increased savings net of debt (Table 3, – – column 8). One caveat here is that our survey-based estimates while close to zero are noisy. The 95 percent confidence interval for the impact of SSP on savings net debt easily includes the analogous point estimate on savings with NVRB.

# **3.4 Heterogeneity by Baseline Overdrafting**

The main effects mask strikingly different treatment effects by baseline overdrafter status. This can be seen in Figure 1, which graphs monthly treatment effects on the average daily balance at NVRB by overdrafter status. Here, the first vertical dashed line demarcates the payout month and the second vertical line demarcates the end of survey coverage. Panel B shows that the treatment effect for heavy overdrafters peaked roughly six months _before_ the SSP payout. This could reflect a combination of program dropout (19 percent of heavy overdrafters dropped out early, as compared to 7 percent of light overdrafters) and drawdown of liquid, non-committed NVRB balances. In contrast, the treatment effect for light overdrafters peaked the month before the payout (Panel A). Moreover, treatment effects for light overdrafters re-emerge in the post-endline period after dropping immediately after commitment amounts are released. These patterns are consistent with the hypothesis that light overdrafters became accustomed to making smaller withdrawals from their NVRB accounts and continued with this behavior after the SSP program ended.<sup>15</sup> These stark differences in treatment effects by baseline overdraft behavior are also apparent in the survey data. We examine heterogeneous treatment effects by augmenting equation 1 to include interactions between the different treatment effects and
detailed, more abstract and more limited in their applications than cost time models.

# Survey responses

Reported travel times to services from survey instruments are easy to collect within a standard survey instrument but are subject to such instruments’ limitations. To begin, collecting quality survey data is a complex, expensive and time‐consuming process vulnerable to various types of survey error (for example, see below commentary on GPS error in the Household Vulnerability and Reconstruction Survey (HRVS)). Any of these sources of error can undermine the reliability and validity of the results. Even when surveys are performed well, reported survey times are heavily influenced by individual household dynamics (Ahlstrom et al. 2013). Controlling for fixed effects can offset some of this error but not all effects can be detected. Even then the findings are impossible to generalize beyond the sample frame employed or outside the study area.

Reported travel times offer the precision of a time‐based measure and thus have similar advantages to cost time models in terms of communicative efficiency and analytical flexibility. For this reason, economists commonly employ reported travel times to services from survey instruments to assess the relationship between accessibility and market, household or individual characteristics. Thus, they offer useful but inherently limited looks at accessibility and are most useful when accessibility must be correlated with such characteristics. Cost time models are preferable to reported travel times except where a specific households’ characteristics must be correlated with its specific set of reported times.

# Network analysis

Network analysis is a method of calculating travel times or distances over a road network in a GIS software, measurements which can then be used to look at accessibility in the same manner as a cost time model. It principally requires an accurate, complete roads data set in the area of interest. Accuracy here specifically references the geo‐location of the road centerlines, their surface and quality attributes, and the road speed modifiers attached to these attributes. Where data requirements are met the precision of estimates is high and conveniently scalable to any geographic unit
the second largest GDP of our countries. In terms of disasters, Thailand is mostly at risk to floods and typhoons, but earthquakes happen occasionally, with the largest recorded being a 6.1 magnitude earthquake that occurred in May 2014. The lower risk compared to our other countries is also mentioned by INFORM in their country profile of Thailand (INFORM 2019).

_Vietnam_ . The final country is Vietnam, which is the smallest, but has the third highest population just below 100 million people. In terms of GDP, Vietnam rank fourth among our five countries. When it comes to disaster risk, they are on par with Thailand in that INFORM ranks them low and exposed primarily to floods and typhoons (INFORM 2019).

# _B. VIIRS_

To find and identify areas with economic activity and their exposure to natural hazards, satellite images of nighttime lights will be used as a proxy. This is due to the highly localized nature of natural hazards and how they affect economic activity within populated areas. In an optimal scenario, one would prefer highly spatially disaggregated economic data, but lacking

> 3 Magnitude is defined as: M =  log(D * S * AA), with D being the duration of the flood in days; S is the severity on a scale consisting of 1 (large event), 1.5 (very large event) and 2 (extreme event); and AA is the size of the affected area in square kilometers. Flood events registered by DFO have mainly been derived from news and governmental sources.

6
23 Prices for water rights are left to the buyers and sellers. In a study covering over 700 shares of water in four river valleys in Chile, Hearne and Easter (1995) found that for both intraand inter-sectoral transactions, "market transfer of water-use rights does produce substantial economic gains-from-trade," in the two valleys were transactions were numerous. In the Elqui Valley, for example, annual net gains from trade were calculated (Hearne and Easter 1995) to be in the range of US$5.99 and US$1642.00, with an average of US$826.00 per share of water traded, depending on the type of trading sectors. In the Limari valley the net gains-from-trade were calculated to be in the range of US$1.65 and US$2.85 with an average of US$2.40 per cubic meter. In the Limari Valley I share equals, on the average, 4880 m<sup>3</sup> /year, so that the average gains from trade in the Limari Valley are US$11,700 per share.

# _Drought Water (Market) Bank in California_

A water bank is an institution that offers to buy and sell water under some set of rules regarding prices and quantities, in a given service area. Water banks can mark up water prices to cover transaction costs and can also use it to compensate the area of origin. There are several examples of efficient and equitable transfer of water by water banks (Howe and Goodman 1995). We will present here the California drought water bank of 1991-92.

After five years of continuous drought, an emergency drought water bank (DWB) was set in California, following appropriate legislation (to allow for transfer of water rightsand minimize environmental degradation). The aim of the DWB was to enable transfer of water from agriculture in northern California to urban, municipal, and agricultural sectors in southern California. The principles of the DWB were:

- Voluntary transfers

- Protection of fish and
the strength of the different factors on trends in learning outcomes.

# _Benchmarks for Annual Progress_

As we have data for only two time periods, we compare the learning trend observed from 2019 to 2021 for students in Uzbekistan to the average expected rate of learning per year. The World Bank’s simulations of COVID-19-induced learning loss assume a progress rate of 0.40 SD per year (Azevedo et al., 2021) based on student outcomes data in the Programme for International Student Assessment (PISA). In the United States, Hill et al. (2008) report annual gains for the age range of 8-11 years based on nationally normed tests in math and reading. Their reported annual gains in math are from 0.89 SD at age 8 to 0.41 SD at age 11. Analysis of growth trajectories of reading and math achievement drawing upon multiple sources of national assessment data in the United States shows annual gains of 0.40 standard deviation in math for grades 5 to 8 during the past two decades (Lee 2010). Similarly, in low-middle-income settings in Pakistan, Bau et al. (2021) estimate that when controlling for students appearing in consecutive assessments and for family characteristics, the value of annual learning gains is approximately 0.39 SD. Based on this review, we use the benchmark average annual learning gain of 0.40 SD to compare the learning trend observed for students in Uzbekistan.

4