rafmacalaba/data-use-mentions-extended huggingface dataset:
the three rounds of Economic Censuses is not perfect. Depending on the distance buffers, we capture 54 to 60 percent of the places when looking at the patterns in 1998, and 29 to 31 percent of places when analyzing the pre-split trends between 1990 and 1998. In addition, Abeberese and Chaurey (2019) and Chaurey (2017) find similar results on the patterns and trends of employment in manufacturing industries before 2000, using data different from ours and for districts close to the border. Overall, the quasi-natural experiment nature of the state split is supported by our analysis and previous studies on this topic.

24
out of industrialization opportunities sooner than did the early industrializers.

Considering these facts, the objective of the paper is two-fold. First, to what extent does it reflect a statistical artifice whereby what was earlier subsumed in manufacturing value added is now accounted for as service sector contributions to GDP? Second, to the extent that the premature declining share of the manufacturing sector and the increasing share of the services sector is not notional but real, does this matter for development opportunities? The latter has two dimensions. For one, is manufacturing special given the increasing contribution of the services sector to productivity growth? Furthermore, can the services sector can provide growth opportunities in the absence of a manufacturing core?

The paper uses different methodologies and databases to address these questions, which are described in greater detail across each section. First, a growth accounting exercise, based on inputoutput tables for China, India, Brazil, Mexico and the Russian Federation, decomposes services value added growth between 2000 and 2014 to analyze the importance of contracting out of manufacturing to services as an explanation for the latter’s growth. Second, manufacturing and services industries are disaggregated along a set of characteristics that are indicative of international trade, innovation, learning-by-doing and factor use – based on firm-level data for Brazil, China, the Arab Republic of Egypt, India, Nigeria, and Russia – to analyze the potential of the services sector as an alternative source of productivity gains and job creation. For each chosen

> 4 After 2000, structural change contributed positively to Africa's overall productivity growth, accounting for about 40 percent of the total, on average, across the 19 countries in the sample.

3
government has released some reports on the program implementation (see Secretaría de Movilidad 2010), there is no reliable evidence on the effectiveness of the restrictions.

Rationing car use may have other potential benefits; apart from addressing congestion and air pollution, it might also reduce the crash risk and road and parking costs.<sup>2</sup> Nonetheless, studies on the effectiveness of driving restrictions yield conflicting conclusions. Eskeland and Feyzioglu (1997a), Davis (2008), and Gallego, Montero, and Salas (2013) found that the _Hoy No Circula_ (HNC) program in Mexico City, which banned most drivers from using their vehicles one weekday per week, was ineffective. HNC induced many households to buy additional cars (mainly old and highly polluting ones). In contrast, Carrillo et al. (in press) found that driving restrictions in Quito reduced air pollution by 11 percent. In the latter case, the uncertainty about the program’s permanency may have kept households from buying a second car. Viard and Fu (2015) also report reduced air pollution after driving restrictions were introduced in Beijing. They argue that high compliance and vehicle ownership costs may explain the effectiveness of the program. However, around the time of the program implementation, other strict policies, for example, factory closures and suspension of construction projects, were imposed to cut pollution during the 2008 Olympics, and thus the improvements in air quality may not be entirely attributed to driving restrictions. Moreover, these programs are quite controversial from a cost perspective. Using a contingent valuation survey for HNC, Blackman et al. (2015) found that the regulatory costs are substantial (1 percent of drivers’ annual income).

The present study fills a gap in the literature by examining the effects of switching from moderate to drastic restrictions. Although the effect of multiple changes

> 2. Other common arguments are that such policies are easy to monitor, target the rich and the poor equally, and potentially induce use of public transport
rounds of the COV-ES implemented in El Salvador and Georgia, along with the baseline ES. Consequently, the sample within each country is different from the samples we used in Section 5. We use the fixed effect panel regression method to help identify the causal link between the government support policies and the outcome variables of interest.

Recall that, in Round-2 data, the firms that received any government support since the onset of the pandemic, whether before Round-1 or after, are counted as having received government support. This effectively divides the firms that enter in our analysis into three sub-groups: (i) those that did not receive any support in either round of the survey, (ii) those that received support 22
182 countries using real-time Google search data. They find that the crisis led to a 63 percent reduction in demand for hotels and a comparable rate of increase in demand for ICT services. Firms have responded to reduced cash flow and high uncertainty by adjusting their investment (Boone, 2020) as well as their production and delivery technologies. Due to the disruption of supply chains, inventories have also been run down (Boone, 2020; Guan et al., 2020; Bonadio et al., 2020; Inoue & Todo, 2020). Trade has also been affected, possibly permanently (Baldwin & Weder di Mauro, 2020). Given these shocks, the ability to 6
(p-value)|0.141|0.010|0.711|0.777|0.141|0.013|0.712|0.757|0.184|0.038|0.719|0.742|
|Endline control mean|2.4|65|2.9|75|2.4|65|2.9|75|0.|153|0.|275|
|Additional controls|No|Yes|No|Yes|No|Yes|No|Yes|No|Yes|No|Yes|
|(Pseudo)R-squared|0.029|0.489|0.185|0.503|0.005|0.089|0.020|0.056|0.010|0.300|0.037|0.262|
|Observations|1,604|1,604|400|400|1,604|1,604|400|400|1,604|1,604|400|400|

_Source:_ Authors’ analyses based on baseline and endline survey data.

_Note:_ Poisson and probit models (columns (5) to (12)) show average marginal effects (AME). Number of ISFM technologies adopted ranges from 0 to 5. Integrated adoption of full ISFM package is a dummy variable. FREG stands for ‘Farmer research and extension group’. FREG- and non-FREG samples consist of actual FREG respectively non-FREG farmers in treatment mws, and their matched controls. Matching variables are those listed in notes of Table 2 (ITT regressions). Additional control variables identical to those listed in notes of Table 2. One-sided equality tests of T1 and T2 are F- tests or Wald tests. Robust standard errors in parentheses, clustered at the mws level. Significance levels indicated as following: *** p<0.01, ** p<0.05, *
. 2011. “Vulnerability, Risk Reduction, and Adaptation to Climate Change ‐ Vietnam.”

# **9. Appendix**

# **9.1. Appendix 1. National‐level: Flood Hazard Modeling Details**

All the data were produced using the SSBN global flood model, producing flood hazard data at 90m resolution. The SSBN global model couples a flood frequency analysis conducted at the global scale, with a fully 2‐D hydraulic modeling framework. Extreme river discharges are derived from a Flood Frequency Analysis (FFA), applied at the global scale (Smith, Sampson, and Bates 2015). The model also explicitly simulates in‐channel flow, with the FFA also used to estimate bankfull discharge across the channel network (defined as the 1.1 – 2 year event depending on climate zone); these values are used to calibrate the channel conveyance capacity within the hydraulic modeling framework. A number of global data sets are used to derive the inputs to the hydraulic model. Firstly, the Hydrosheds variant of SRTM is used, both at 3 and 30 arc second resolutions. A number of additional corrections are applied to the terrain data including a systematic vegetation correction procedure in vegetated areas and an urban correction procedure in urbanized areas. A detailed description of the modeling framework is provided by (Sampson et al. 2015).

For the coastal simulations, input boundary conditions were derived using estimates of return period surge heights, taken from (Chinh, JianCheng, and Bui 2014). Storm surge hydrographs for each recurrence interval were taken for four tidal gauges located along the Vietnamese coastline. Coastal boundary conditions for the hydraulic model were derived by linearly interpolating between the gauge locations. The hydraulic model was set up so that a coastal boundary condition was implemented for each ‘land’ cell located next to the coast. In addition to the coastal boundary conditions, large river channels were also 24
instrumenting for the pandemic variable (column 4). Higher daily death rates have a significant adverse effect on electricity consumption, as usual. Including daily death rates and instrumenting for it leaves the sign and significance of the speed variable unchanged, however the magnitude is slightly attenuated at about 4 percentage points. According to that specification, an increase in reopening speed by one unit results in a 3.8 percent reduction in electricity consumption.

The results of incorporating the trust variable and estimating equation (5) are presented in Table 4. The first column presents the benchmark regression of equation (3) as a reference. The second column looks at the mediating effect of trust in government institutions, which is measured using the share of individuals having high trust in parliament, as reported in the 2018 round of the European Social Survey or the 2016 Life in Transition Survey.<sup>11</sup> The coefficients of the interaction between the lockdown sequencing dummies and the level of trust are statistically significant. In the case of the dummy indicating a direct transition from full reopening to no restrictions, controlling for trust makes the baseline coefficient significant and larger at 3.9 percentage points. However, the interaction with trust variable results in a negative coefficient, and given that the average share of people having high trust in parliament in countries that opted for a fast reopening is 5.9 percent, the combined effect would imply that the average country that reopened in that way saw a zero or negative change in relative electricity consumption.<sup>12</sup> Hence, once we incorporate trust, for the average country a fast reopening process is associated with a negligible change in relative electricity consumption – qualitatively equivalent to the benchmark results. For the gradual reopening process, the coefficients suggest that higher levels of trust are clearly associated with better outcomes, since the interaction coefficient is now positive. The indicator of trust in parliament is, on average, 3.6 percent in countries that reopened gradually. For the average
as it surveys every establishment that has a fixed location and operates an economic activity. The ensuing microdata is comprehensive and detailed with respect to key establishment characteristics such as location, registration and legal status, age, ownership and management, industrial classification, and employment size. The census covers both formal and informal businesses. An establishment is considered to operate in the formal sector if it is registered with the Rwanda Revenue Authority (RRA) and maintains regular operational accounts.<sup>12</sup> Table 1 summarizes the key features of the census data from these Sub-Saharan African countries. We now turn to the description of each of the datasets. In Burkina Faso, 99,261 establishments hire about 256,000 workers in 2015. The corresponding figures are 88,144 establishments and 430,000 workers in 2008 (Cameroon); 638,234 establishments and 3.4 million workers in 2013 (Ghana), and 154,236 establishments and 493,000 workers in 2013 (Rwanda). Establishments with foreign equity or state ownership are rare in number and employ a small number of workers. Notable exceptions are the employment shares of foreign-owned establishments in Cameroon (17 percent), and stateowned enterprises in Ghana (15 percent) and Rwanda (14 percent).

Manufacturing production involves a small fraction of the establishments and the workforce in the economy ranging from 7 percent (Ghana) to 17 percent (Burkina Faso) and 8 percent (Rwanda) to 21 percent (Burkina Faso), respectively. It also involves a limited number of foreign-owned establishments, but they play a bigger role as sources of manufacturing employment. In Burkina Faso, they constitute about 1 percent of the establishments and 7 percent of the employment in manufacturing. The corresponding figures are 5 and 25 percent in Cameroon, 1 and 7 percent in Ghana, and 1 and 17 percent in Rwanda. Likewise, state-owned establishments are less than 1 percent of manufacturing establishments. However, they contribute a small fraction to manufacturing employment; about 1 percent
.

During the period considered, inequality slightly increases in urban areas while remaining relatively stable in rural ones. Growth in the early 2000s is less volatile than in the previous decade and posts substantially higher annual rates (Clementi et al., 2022). This growth, however, has not been accompanied by rapid economic modernization or significant labor market outcomes. Indeed, the Moroccan economy created an average of 115,000 jobs annually between 2000 and 2010. However, this could not absorb the annual increase in the working-age population (Lopez-Acevedo et al., 2021). Over the same period, the slight increase in inequality resulted from two counter-balancing trends: convergence of development across regions and increased intra-region inequality in some regions. Indeed, inequality increased mainly in the coastal, urbanized regions while decreasing in the — mainly rural — inner and eastern parts of the country (HCP, 2018).

As additional verification of the validity of this trend, we compared inequality measures in rural areas with average annual precipitation data.<sup>9</sup> As the Moroccan economy highly depends on agriculture, we expect a significant correlation between rainfall and inequality. In periods of drought, we expect inequality to increase since most of the agriculture is rainfed and only a few very developed areas (for example the Settat area) are equipped with modern irrigation systems that enable farmers to withstand shocks, which exacerbate rural inequality. In periods of abundant rainfall, we anticipate better performance overall of the agricultural economy and thus a decline in inequality. As expected, the correlation coefficients between the three indices and this data are, respectively, (G=-0.75, T=-0.67, HCR=-0.15). From these, we can deduce that the trend of the indices is consistent with rainfall patterns, confirming the validity of our hypothesis and the economic significance of our estimated results.

> 9https://climateknowledgeportal.worldbank.org/country/morocco/climate-data-historical

14
course of a day as well as over the time the survey progresses (Baird, Hamory, and Miguel 2008). Especially in consumption surveys, a long list of items can lead to enumerators cutting corners and fabricating data (Fiedler and Mwangi 2016; Finn and Ranchhod 2015) as well as prematurely ending interviews (A. Deaton and Grosh 2000). Respondents also become fatigued and, for example, learn to say no to consumption of items to evade more detailed follow-up questions (Kreuter et al. 2011; Eckman et al. 2014).

To overcome the challenges inherent to measuring consumption poverty, we propose a new methodology that combines an innovative questionnaire design with standard imputation techniques.<sup>2</sup> This new methodology allows us to substantially shorten the consumption questionnaire and reduce the interview time (less than 60 minutes for a standard questionnaire) by imputing deliberately absent consumption values for those items that are not explicitly asked about. Poverty estimates can be derived in this way without compromising the credibility of the resulting estimate. This new methodology is particularly useful in fragile states given the significant risks associated with lengthy interviews. It can also be useful to reduce enumerator and respondent fatigue, or to mitigate the problem of high non-response rates.

The most straightforward way to reduce the expected interview time is to skip rarely-consumed items. Another simple strategy is to ask the respondent about an aggregate amount of spending on an entire

> 2 A precursor methodology based on the same principle was previously published in Pape and Mistiaen 2015.

2
et al. (2010) or for example by Rosenberg and Tirpak (2010). Recent firm-level evidence suggests that FX borrowing in the region is not driven predominantly by unhedged customers taking currency bets to benefit from interest rate differentials. Examining the 2005 wave of BEEPS, Brown et al. (2011b) show that only 25% of the loans taken by firms in the ECA region are actually denominated in foreign currency.<sup>8</sup> Importantly, their evidence suggests that those firms which take FX loans are more likely to be hedged against exchange rate risks: FX borrowers are more likely to have export activities, sales to multinational firms or foreign owners than firms which borrow in local currency. This cross-country evidence is backed up loan-level evidence for Bulgaria (Brown et al. 2010) which shows that less risky clients are more likely to apply for and receive an FX loan. At the macroeconomic level both studies suggest that FX borrowing by firms in the region is hardly driven by currency bets: Changes in interest rate differentials over time seem to have little effect on the share of FX loans taken by firms within a country. Indeed, Brown et al. (2011b) find that changes in interest rates over time affects the frequency of FX borrowing in only two countries; Hungary and Serbia.

While FX lending by firms in the region may not be primarily driven by carry-trade behavior, Brown et al. (2011b) point to a non-negligible share of unhedged FX loans in the region. Their analysis suggests that 43% of all FX borrowers in the ECA region do not have

> 8 Evidence from Brown et al. (2010) suggests that the share of FX loans to firms did not further increase in the run up to the crisis. For example, while there was a significant increase in credit volume in Bulgaria between 2005 and 2007, their data shows that the share of FX loans to firms  actually decreased from 37.6% to 33.6%.

27
8%|13%|13%|
||All|53%|61%|83%|55%|82%|
|India|Domestic|53%|61%|83%|55%|82%|
||Foreign|53%|61%|95%|42%|81%|
||All|12%|10%|21%|37%|87%|
|Nepal|Domestic|12%|10%|21%|37%|87%|
||Foreign|28%|28%|28%|55%|100%|
||All|19%|13%|26%|53%|-|
|ECA|Domestic|18%|12%|25%|52%|-|
||Foreign|26%|15%|34%|65%|-|
||All|26%|31%|45%|43%|-|
|Africa|Domestic|27%|31%|45%|43%|-|
||Foreign|21%|31%|41%|41%|-|
|i|All|21%|17%|28%|68%|-|
|Russan<br>Federation|Domestic|19%|17%|26%|64%|-|
||Foreign|50%|22%|71%|96%|-|
||All|5%|6%|9%|63%|-|
|Turkey|Domestic|4%|5%|7%|57%|-|
||Foreign|32%|32%|33%|98%|-|

Source: Author’s elaboration from Enterprise Survey (2014) <u>Differences across sectors: Indian and Bangladeshi firms located in the food, apparel, automobile, and<
those who have been exposed to extension services and who have access to the financial markets. Figure 4.3 shows that inorganic fertilizer and pesticide use is slightly higher among those who live in a village in which extension services were available in the past 12 months,<sup>20</sup> and considerably higher in the case of improved seed use. Focus groups conducted by the authors with farmers in the Northern region of Uganda underlined that extension workers provide advice mainly on pesticide and hybrid seeds, and some actually expressed a belief that fertilizer may be harmful for the soil in the longer term.<sup>21</sup> While we do not have data on the exact content of the extension services provided to farmers, it may be important in determining the relative adoption rates among the different inputs considered in this study. Similarly, households that report having taken a formal loan also use pesticide at a higher rate, though not other agricultural inputs. This suggests that access to credit may not be a binding constraint in Uganda.

**Figure 4.2: Weather conditions in Uganda 2005/06 to 2013/14 (Water Requirement Satisfaction Index)**

<!-- Start of picture text --> 100<br>95<br>90<br>85<br>80<br>75<br>70<br>2005/06 2009/10 2010/11 2011/12 2013/14<br>Central Eastern Northern Western<br>WRSI<br><!-- End of picture text --> Source: Staff calculations staff calculations using geoWRSI v 3.0, with global PET and RFE v2 (2001‐2017) time series.

**Figure 4.3: Input use seems higher among those with extension services and those taking formal credit**

**1. Extension 2. Credit**

> 20 This includes extension services provided by NAADS (National Agricultural Advisory Services), input suppliers, NGOs
Identifying reasons for such insecurity which could include concern about non-extinguished or overlapping historical rights or current competition for land from ‘emergent’ farmers and assessing their productivity impact is a priority for further analytical work.

To explore if access to formal documentation is constrained by supply or demand-side factors, 90% of respondents are without a valid title and were asked if they would like to apply for title and, if yes, what they would be willing to pay for it.<sup>19</sup> Overall, 54% of them -71% in urban and 50% in rural areas- want to acquire title and are willing to pay an average of ZMK 754 (ZMK 968 in urban and ZMK 667 in rural areas) for it. Title demand is highest in Lusaka (83%), followed by North (60%), East (59%), West (28%) and South (27%).

Aggregating demand for title or willingness to pay at the village level provides an estimate of the share of households who would like to acquire title as well as mean or total willingness to pay. These two parameters allow us to identify areas where a titling program would be welcome by a given share of the population and, for a given cost structure, could be run on a cost recovery basis or a given subsidy element. Results in table 3 suggest that, while in 71% of the villages respondents would be willing to pay at least ZMK 100 to get title, this holds for 87% in Lusaka and 81% in the East, but for less than half (45%) in the West and about one-third (35%) in the South. Even in Lusaka District more than 40% of the population do not want title in some 11% of villages, a share is that more than two-thirds (68%) in the West and almost that level (65%) in the South. Use of sampled households’ GPS coordinates allows us to map
Table A.4: Descriptive statistics on wedding expenditure from the 2005 India Human Development Survey

|||||**P**|**anel A: **|**By caste**|||||
|---|---|---|---|---|---|---|---|---|---|---|
||||Urban|||||Rural|||
||Brahmin|OBC|SC|ST|Others|Brahmin|OBC|SC|ST|Others|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|
|Expenditure by bride’s family|186,683|120,818|96,038|74,689|165,710|140,575|89,973|64,194|35,007|120,038|
|Expenditure by groom’s family|128,166|74,673|63,616|58,691|108,188|92,365|56,380|43,539|29,176|74,162|
|Diference|58,617|46,145|32,423|15,997|57,522|48,210|33,589|20,655|5,835|45,875|
|N|1,313|5,452|2,322<br>**P**|499<br>**anel B: B**|4,956<br>**y religio**|1,108<br>**n**|10,834|6,011|2,939|6,