rafmacalaba/data-use-mentions-extended huggingface dataset:
# **4.2.3 Governance quality**

Policy makers frequently focus on attracting FDI through various investment incentives, eliminating red tape affecting establishment, and proactive investment promotion. While these aspects are important, evidence gathered from recent WBG surveys suggests that investors are more concerned with irregular government conduct affecting their possibility to maintain and expand their operations in the host country (Echandi, 2019). Such an observation is consistent with recent empirical research suggesting that the bulk of trade costs for services relate to the governance performance of a host country. Indeed, van der Marel and Shepherd (2019) show that the strongest cost variable explaining services trade is captured by governance indicators. Such findings confirm that enhanced regulatory transparency and certainty matter for trade and investment facilitation in services.

A recent WBG research project found that investors - including service suppliers operating through a commercial presence, ranked regulatory risks – i.e. risks deriving from irregular or erratic government conduct - at the very top of the constraints affecting their operations in developing economies.<sup>40</sup> More than 75% of investors faced problems relating to government conduct in developing countries (GIC, 2017). Although most of the reported problems do not escalate into full-fledged grievances triggering investorstate litigation, the impact of unresolved grievances deriving from government conduct can generate significant adverse reputational effects for host countries.

Investor surveys conducted annually between 2009 and 2013 and again in 2017 have shown consistently that more than 25% of investors have withdrawn or canceled FDI expansion projects due to irregular government conduct (MIGA, 2009-13; GIC, 2017). Combining that figure with UNCTAD’s data on the value and number of net-cross border M&A and announced greenfield FDI projects for each survey’s corresponding period, a conservative estimate suggests that, focusing solely on trade in services through commercial presence in 70 developing countries where surveyed investors had operations, irregular government conduct lies behind decisions to withdraw or cancel expansion plans in up to 900 FDI projects a year valued at approximately
|
|**Chemicals (CHEM)**||||||
|Including Zeros|0.00|2.53|98.98|25,112.73|322,014|
|Positive Flows Only|< 0.01|22.20|292.66|25,112.73|36,643|
|**Information and Communicati**<br>|**ons Techno**<br>|**logy (ICT)**<br>||||
|Including Zeros|0.00|15.95|745.95|135,309.85|322,014|
|Positive Flows Only|< 0.01|161.79|2,370.51|135,309.85|31,754|
|**Medical Devices (MED)**||||||
|Including Zeros|0.00|1.43|46.20|11,019.49|322,014|
|Positive Flows Only|< 0.01|13.85|143.06|11,019.49|33,304|
|**Production Technology (PT)**||||||
|Including Zeros|0.00|4.98|257.73|67,061.03|322,014|
|Positive Flows Only|< 0.01|41.86|746.19|67,061.03|38,311|
|**Other**||||||
|Including Zeros|0.00|13.47|592.92|114,855.77|322014|
|Positive Flows Only|< 0.01|91.97|1,547.02|114,855.77|47,161|

_Notes_ : Data reflects bilateral patent applications data for the years 1995–2015.
<!-- Start of picture text --> Figure 1a. Share of SOEs in industrial sector Figure 1b. Share of foreign firms in industrial sector<br>Data sources: Statistical Yearbook of China Data sources: Statistical Yearbook of China<br><!-- End of picture text --> Figure 1c. Share of SOEs in industrial sector: Figure 1d. Share of foreign firms in industrial sector: Inland regions v. coastal regions Inland regions v. coastal regions _Data sources: Statistical Yearbook of China Data sources: Statistical Yearbook of China_ 32
Table D1: Vessel characteristics in the six fishing seasons of 2017, 2018, and 2019

||All vessels<br>(1)|Large-frm vessels<br>(2)|Medium-frm vessels<br>(3)|Singleton vessels<br>(4)|
|---|---|---|---|---|
|A. Average|tons landed|per season|||
|Minimum|3.11|105.45|14.64|3.11|
|Mean|2607.41|6311.44|1842.81|903.56|
|Median|1324.49|6004.34|1303.62|722.86|
|Max|22261.64|22261.64|10852.99|9389.83|
|B. Average|number of a|ctive vessels per sea|son||
|Minimum|708|178|263|256|
|Mean|730.17|182|276.67|271.5|
|Median|731|182|278.5|269|
|Maximum|750|185|283|288|
|C. Vessel le|ngth (m)||||
|Minimum|11.23|15.85|11.3|11.23|
|Mean|26.05|41.64|24.06|17.62|
|Median|20.9|40.48|21.72|17.05|
|Max|77|77|53.75|42.57|

Notes: Large-firm vessels are vessels that belong to one of the seven largest firms, which each own at least 19 vessels. Medium-firm vessels belong to firms that own 2 to 10 vessels. Singleton vessels belong to a firm that owns only one vessel. Data are for the North-Central zone only. Landings data are used to calculate the number
(2021) show that large and energy-intensive sectors in Indonesian manufacturing tend to reduce energy consumption most significantly in response to an energy price hike. Plants react to higher energy prices by updating their capital stock and investing in new and presumably more energy-efficient technology. Using firm-level data of small and micro enterprises from Indonesia for 2013, Rentschler and Kornejew (2018) explore the impact of input price changes of electricity and

> 6The literature distinguishes between different forms of the Porter Hypothesis (Ambec et al., 2013): Under its _”weak”_ form, environmental regulations spur innovations, while under the _”strong”_ version, environmental regulations will lead to increases in firm competitiveness. The _”narrow”_ interpretation states that more flexible regulations may be better at providing the preferable incentive structures to firms than more prescriptive forms.

4
. A. (2017). Egyptian irregular migration in the GCC countries. In _Skillful survivals: Irregular migration to the Gulf._ Cambridge: Gulf Research Centre Cambridge.

- Azose, J. J., & Raftery, A. E. (2019). Estimation of emigration, return migration, and transit migration between all pairs of countries. _Proceedings of the National Academy of Sciences_ , _116_ (1), 116–122.

- Bayer, R. (2006). Diplomatic exchange data set, v2006. 1. Retrieved from `http:// correlatesofwar.org`

- Bean, F. D., Lowell, B. L., & Taylor, L. J. (1988). Undocumented Mexican immigrants and the earnings of other workers in the United States. _Demography_ , _25_ (1), 35– 52.

- Borjas, G. J., Freeman, R. B., & Lang, K. (1991). Undocumented Mexican-born workers in the United States: how many, how permanent? In _Immigration, trade, and the labor market_ (pp. 77–100). University of Chicago Press.

29
.0158<sup>***</sup>|<br>0.125<sup>***</sup>|<br>−0.00584<sup>**</sup>|
||(14.81)|(27.87)|(−45.48)|(32.27)|(−9.17)|(60.57)|(−3.27)|
|Observations|1453795|3991436|1090511|7354974|5005826|4181318|7057757|
|Adjusted_R_<sup>2</sup>|0.746|0.718|0.755|0.708|0.733|0.746|0.704|
|Controls|Munic|Munic|Munic|Munic|Munic|Munic|Munic|

_Source:_ Authors’ analysis based on Economic Census and data from Encuesta Nacional de Ocupación y Empleo and Encuesta Nacional de Empleo. _Note: t_ statistics in parentheses;<sup>*</sup> _p_ < 0.05,<sup>**</sup> _p_ < 0.01,<sup>***</sup> _p_ < 0.001.

The contrasts across educational levels are sharp. For workers with incomplete primary education, the effect on earnings of being employed by larger firms compared with small ones [0–5] is small; the difference with being employed in a small [6–10], medium [ 11-50] or large [50+] one is 7.7 percent, 5.4 percent, and 8.1 percent, respectively (and, in the last case, not statistically significant). This is in contrast with workers with university education: relative to small firms, the difference of being employed by a small, medium, or large firm is 7.3 percent, 13.4 percent, and 20.6 percent, respectively
comparability over time.<sup>4</sup> Introducing the Classification of Individual Consumption According to Purpose (i.e., COICOP) increased the number of food and non-food items from 149 to 263 and 261 to 441, respectively. The data collection method moved from PAPI to Computer Assisted Personal Interviewing (CAPI). Market prices were collected instead of deriving unit values from collected household total expenditure values and quantities, and weighing scales were implemented to ensure the accuracy of household consumed food items. A more rigorous fieldwork monitoring system

> 3 To mention a few examples, the 2010 HIES round redesigned the Remittances and Migration modules, and in the 2016/17 round, the Social Safety Net questionnaire was redesigned and expanded. Another difference between survey rounds is that the PSUs in all rounds but 2016/17 were selected from an Integrated Multipurpose Sample (IMPS) – a master sample updated for each Housing and Population Census. In the 2016/17 round, PSUs came from a list of Enumeration Areas used for the 2011 Population and Housing Census. For further details, see Ahmed et al. (2019).

> 4 As technology and survey design methods evolve, enhancements should be implemented. For instance, Argentina improved its survey instrument and periodicity of data collection in 2003, India made several changes in the late 1990s, Peru and Ecuador made significant changes in their household surveys in 2004 and 2007, and, more recently, Zambia and Bhutan in their 2022 survey round. In the ideal situation, a proper way to implement these changes is to simultaneously conduct old and new methods and then clearly identify their differences to maintain comparability over time. However, this process could be costly, challenging, and complex, leaving most countries with two options: break trends or find an analytical way to tackle this issue after implementing the survey.

2
**The current paper studies recent mobility patterns in the Buenos Aires Metropolitan Area (** **_AMBA for its Spanish acronym_ ) – the largest urbanized area in Argentina and one of the largest in Latin America – to propose specific areas of transport policy that can target women’s travel needs.** To do so, the paper leverages _big data_ and complementary data to identify transport patterns that are distinct between men and women, including in terms of the spatial patterns, distances traveled, the temporal distribution of trips throughout the day, and mode choices. Second, the paper analyzes the gender-differentiated changes in mobility patterns associated with the pandemic, a significant shock that affected both transport supply and travel preferences, some of which have persisted even three years later. Understanding these gender-differentiated responses is important for developing policy solutions that can steer the mobility choices towards more sustainable modes if a similar shock were to occur in the future.

# **2. METHODOLOGY**

**The analysis takes advantage of a number of innovative data sources and methodologies that can provide complementary insights.** These include, first and foremost, Call Detail Record (CDR) – mobile phone – data, that are increasingly recognized as a valuable resource for transport planning. CDR data are observed for every call/text made or received with a timestamp and GPS coordinates of the tower from where the call is made. Such data allows measuring mobility across entire cities or even countries at very fine spatial and temporal levels. The analysis in the current paper is based on CDR data obtained for three different periods (October 2019, October 2020, and October 2021) from a major mobile phone service operator in Argentina, representing 37 percent of the national market, with over 8 million unique subscribers. The methodology fused CDR data with data from public transport validations (the SUBTE smart card in Buenos Aires) and publicly available household mobility survey data from 2010/2018 - _Encuestas de Movilidad Domiciliaria_ (ENMODO). In addition, the analysis incorporates
|(1.00)|1,420|
|Ppl Travelled With (SD)|-0.01|(0.14)|[1.00]|-0.00|(1.00)|1,421|
|Plans to Move? (SD)|-0.16|(0.13)|[1.00]|-0.00|(1.00)|1,416|
|Prep Time before Flee (SD)|0.21|(0.17)|[1.00]|-0.00|(1.00)|1,416|
|Plan to Stay in Current Residence (SD)|-0.03|(0.15)|[1.00]|-0.00|(1.00)|808|
|Confict End in 2 Years? (SD)|0.29**|(0.15)|[1.00]|0.00|(1.00)|1,209|
|Return in 2 Years? (SD)|0.12|(0.13)|[1.00]|-0.00|(1.00)|1,403|
|Return 2 Years After War End? (SD)|-0.02|(0.16)|[1.00]|-0.00|(1.00)|1,393|

**_Notes_** :

- The table shows the regression results on pre-specified migration outcomes using the 2021 in-person data. Each row is its own dependent variable.

- The outcomes that require definitions are: Variables with (SD) are scaled with respect to the control population and (=1) represents indicators. # moves since 2011 reports the number of times the FR’s household moved residences for at least 4 months at a
have significant coefficients, with the jobs total grav taxi coefficient marginally significant at the 6% level. Again, the lesson is that better job access spurs backyarding.<sup>19</sup> If the sample is restricted to just SR2 parcels, the coefficient of parcel area becomes positive. This outcome makes sense given that Census data show SR2 areas as mostly composed of black households with presumably similar incomes, weakening the assumed correlation between parcel size and income. With parcel size no longer a good proxy for income, the offsetting parcel-size effect (the ability of larger parcels to accommodate more backyarders) is able to dominate.

The marginal effects of the variables are shown in Table 8, using the regression from Table 5 with access variable jobs lowinc 60 taxi. The table shows the hypothetical change in the explanatory variable along with the percentage change in the expected number of backyarders. A 50m<sup>2</sup> reduction in the parcel size (from a mean of 302) leads to a 10% increase in the expected number of backyarders, while a 38,000 increase in the job-access variable (equal to one standard deviation from Table 3) leads to an 11% increase in the expected number of backyarders. Changing a parcel from non-SR1,SR2 status to SR1 or SR2 status raises the expected number of backyarders by 61% or 220% respectively. The marginal effects from the other regressions are similar in magnitude.

To get a sense of the meaning of these percentage changes, recall that the mean of the count variable is 0.323. The 11% increase in the expected number of backyarders due to improved job access translates almost exactly into 11% of this mean, or 0.035. The implication is that the job-access improvement leads approximately to an extra 1/30th of a backyarder per parcel, or a new backyarder for every 30th parcel. The impact of the 50m<sup>2</sup> decrease in parcel area (which yields a 10%,
|-0.6|-1.1|
|Sweden|0.2|0.1|-0.2|-0.4|-1.5<sup>*</sup>|-1.5|0.2|-0.9|

_Notes:_<sup><u>a</u></sup> The table presents the changes in estimated prevalence of informal employment and unemployment between ESS rounds: Round 4 (2008-2009), Round 3 (2006-2007), Round 2 (2004-2005).<sup>b</sup> For Greece and the Czech R., Round 4 is compared to Round 2 (rather than to Round 3). *, **, *** - estimates significantly different from 0 at the 10%, 5%, 1% level, respectively (not shown for LFSbased unemployment rates). _Source:_ Calculation with ESS data.

53
of World Bank projects is to a great extent influenced by a set of factors established at the time the project is planned. Furthermore, it appears that these factors are relatively robust to variations in leadership, stakeholder relations, and context, posing a consistent risk to effective delivery across the portfolio of projects examined.

# **6** Conclusion

Can implementation-driven data on project challenges be used to holistically assess the effectiveness of World Bank lending? This paper took advantage of a wealth of practitioner experience captured in implementation completion reports as a granular and cross-comparable measure of project outcomes and Bank performance. Using a data-driven taxonomy, we devised a novel approach to examining the determinants of project success. By focusing on _how_ projects fail and the specific challenges faced in successful execution, we were able to capture variation hitherto unexplored in the aid effectiveness literature, offering a more precise assessment of the challenges faced throughout the implementation cycle while also providing a cross-cutting measure that reaches across the country-, time-, and sector- based approaches previously employed. Thus, while previous work offered insights into the individual mechanisms or contextual factors that might impact project effectiveness, we jointly tested the obstacles to success using a comprehensive analytic framework that allowed for the benchmarking of dozens of competing theories in a single unified model. Adjusting for alternate explanations and various contextual and structural preconditions, which components of implementation were most likely to impact project success?

Using project-level data from over 5,000 lending projects approved between 1995 and 2015, we tested this question using 42 specific delivery challenges across 14 overarching thematic categories. The 22
found to have increased female empowerment (Afridi _et al._ 2013), reduced <mark>gender-based violence (Amaral</mark> _<mark>et al.</mark>_ <mark>2015), increased school participation by children in primary school age (</mark> Islam and Sivasankaran 2015), leading to better school outcomes, i.e. grade progression and achievement scores (Mani _et al._ 2014).<sup>7</sup> Given the importance of casual labor for India’s poorest groups, wide inter-temporal fluctuations of rural labor demand, and prevalence of gender discrimination in rural labor markets, wage impacts of MNREGS have been a key focus of study. A Difference-in-Difference design using NSS data points towards a program-induced wage increase of about 5% that was, with 8%, significantly higher for females (Azam _et al._ 2012). NSS data point towards program-induced wage increases of some 5 points overall and 9 points in states with good program implementation. No gender-specific effects are found but estimates’ plausibility is increased by the fact that the increase is confined to the dry season although net effect on employment was zero (Imbert and Papp 2015b). <mark>Monthly wage data for 2000-2011 suggest that MNREGS increased growth of real agricultural wages by 4.3% during the peak season in some states with gender wage gaps and skilled wages remaining unaffected (Berg</mark> _<mark>et al.</mark>_ <mark>2014).</mark><sup>8</sup> <mark>Evidence of p</mark> ositive wage effects is not universal, however: a RD for <mark>the transition from phase II to III, using 64</mark><sup>th</sup> <mark>round NSS data, suggests limited or no impact on labor market outcomes or on closing of the gender wage gap, leading to authors
|4|22|
||**Wheat**|||||
||Observations|Mean|Std Dev|Min|Max|
|2011/12|248|8.2|2.58|4.46|15.67|
|2013/14|339|8.96|2.66|4.55|18|
|2015/16|365|10.48|3.43|4|22|
||**Maize**|||||
||Observations|Mean|Std Dev|Min|Max|
|2011/12|268|5.33|2.11|3.5|15.69|
|2013/14|381|6.39|2.4|4|18|
|2015/16|389|6.4|3.18|4|22|

# _Source: LSMS Survey dataset_

The mean price for all three crops increased considerably between the three waves. For example, the mean price for teff increased from 9.64/kg in wave 1 to 16.42/kg in wave 3; the

> 10 We explored using monthly data collected by the Ethiopian Central Statistical Agency on crop prices at the district level, as used by Woldemichael et al _.,_ (2017). However, in our case we faced the challenge of many missing observations and that results were sensitive to the approach adopted to dealing with these. 11 Table A.2 in the appendix presents the average price for each region.

7
exemptions and deductions. In both systems, information on the order and size of the deductions and exemptions was lacking.

**The PECS 2016/17 also does not specify whether income data is net or gross.** It was assumed that employees would provide their income net of tax, while employers or self-employed workers would be more likely to report their gross income.

A description of the detailed challenges faced for each deduction can be found in Annex B.

## **Pension contributions**

**The latest administrative numbers available on pension income and contributions are a few years out of date, from December 2013 and September 2014.** There were also a number of different schemes which made it complex to understand and implement.

## **Property tax**

**The main limitation for the estimation of the property tax is that there were several pieces of information that were not available in the PECS 2016/17 dataset, including:**

- (i) The area of the building and number of floors. This would be used to estimate the annual rental value of the building.

- (ii) The lease contract information. Having this information would be useful because the value of the tax varies with occupancy status (rented; prepared for rent; inhabited by the owner). To overcome this limitation, the modeling has proceeded with the assumption that all the properties are inhabited by the owners themselves.

- (iii) For Land evaluation, in lieu of the missing survey data, administrative data (by city) on evaluation was used and it was assumed that the valuation value is “average value per property” and not “per square meter”. Due to the lack of update in the evaluation, the evaluation amounts for some

57
Bruce and Alastair Smith (2008). “Political Survival and Endogenous Institutional Change.” _Comparative Political Studies_ , 42, 167–197.

- [19] Bueno de Mesquita, B. and Smith, A. (2010). “Leader Survival, Revolutions, and the Nature of Government Finance.” _American Journal of Political Science_ , 54(4), 936–950.

- [20] Bueno de Mesquita, Bruce, Alastair Smith, Randolph M. Siverson, and James D. Morrow (2003). _The Logic of Political Survival_ . Cambridge: The MIT Press.

- [21] Coale, A. J. (1981). “Population Trends, Population Policy and Population Studies in China.” _Population and Development Review_ , 7, 85-97.

- [22] Cruz, Cesi, Philip Keefer, Carlos Scartascini (2016). “Database of Political Institutions, 2015 Update (DPI2015).” Updated version of Thorsten Beck, George Clarke, Alberto Groff, Philip Keefer, and Patrich Walsh, 2001. "New Tools in Comparative Political Economy: The Database of Political Institutions." _World Bank Economic Review_ , 15, 165-176.

- [23] Dell, Melissa, Nathan Lane, and Pablo Querubin (2018). “The Historical State, Local Collective Action, and Economic Development in Vietnam.” _Econometrica_ , 86(6), 2083-2121.

54
allocate funds amongst its members in case of a payout.

Technological advances may improve the product offering, such as the use of satellite foliage coverage data to offer policies based on area crop yields. The degree of innovation already demonstrated by insurance providers, as well as this potential for further contract

> 23 Giné and Yang (2009) implement a field experiment in Malawi to test whether bundling insurance with credit increased farmers’ willingness to adopt a new agricultural technology. The advantage of the bundled loan over a standard loan is that it would not have to be repaid in case of a payout. As it turns out, uptake among farmers offered the bundled loan was lower than among the control group offered a standard loan. One potential explanation is that farmers were already implicitly insured by the limited liability inherent in the standard loan and hence placed little value in the insurance policy. By insuring loans, however, the lender was unambiguously better off and after the experiment was considering an increase in disbursement and a drop in the interest rate, reflecting the lower risk of lending.

24