rafmacalaba/data-use-mentions-extended huggingface dataset:
- Expenditures on transport and transport services during the recall periods

- Ownership of types of vehicles

- Travel mode, distance, time, and cost to different social services or facilities such as schools, health facilities, and workplace

# _Expenditures on transport and transport services_

The questions on expenditures ask whether the households purchased any vehicles or paid for transport-related goods or services during the following periods of time: i) 7days, ii) 1 month, iii) 3 months, iv) 6 months, and v) 1 year, and how much money they spent. Usually, the short-term time frame is used for transport expenditure on nondurables, such as public transport fares, fuels and lubricants, and maintenance and repairs, while the longer time frame is used for transport expenditure on durables, such as purchases of vehicles, spare parts, and accessories. As shown in the first column of Table 3, most countries in the sample collect the transport expenditure information using household survey instruments, however, the richness of the subcategories of expenditure on transport and transport services varies by country, for instance, some surveys do not capture the expenditure on vehicle purchases using the non-food expenditure modules.

# _Ownership of types of vehicles_

The questions on ownership of different types of vehicles are always present in the module of durable goods or household assets. The set of questions typically ask respondents whether their households own a list of vehicles (for example, car, motorcycle, minibus, bicycle, boat, animaldrawn cart), the number of vehicles they own, date of acquisition, purchase price, and estimated current resale price. However, the list of vehicles and the sophistication of questions vary by country, which means that some questionnaires do not collect sufficient information to estimate the annual use value<sup>5</sup> of vehicles, calculated based on the purchase and resell prices, and the date of acquisition. The standard LSMS household survey questionnaires of Albania, Malawi and Nepal even involve a question on whether the vehicle was purchased by the
For example, cargo traffic and rail freight declined, oil demand collapsed, and India’s Purchase Manager Index dropped to an all-time low in April. An excellent discussion of the economic impact of COVID-19 on India’s economy is provided by Dev and Sengupta (2020).

# **3 Data**

## **3.1 Daily Electricity Consumption**

We observe daily electricity consumption from April 1, 2013 to May 31, 2020. The data is measured and collected from the Power System Operation Corporation Limited (POSOCO), which is a government-owned enterprise under the Ministry of Power. It is responsible for ensuring the integrated and reliable operation of India’s grid. POSOCO makes available daily reports of electricity consumption with one-day delay. We download the daily documents and scrap the electricity information to build our electricity consumption database for India. While the total electricity consumption in these documents does not differentiate between different uses (residential, commercial, etc.), it does breakdown the electricity consumption of the different states. This will later allow us to track the specific impact of the lockdown on the different states.

Figure 2 shows India’s daily electricity consumption from April 1, 2013 to May 31, 2020.<sup>9</sup> A couple of features are clearly noticeable. First, until the end of 2019, there is a clear upward trend with electricity consumption on average growing 4.3 percent each year. Second, there is a clear seasonality in the data with electricity consumption being higher between May and September than at the beginning and end of the year. Third, there was a noticeable decline already at the end of 2019, long before the COVID-19 pandemic disrupted economic activity in India.<sup>10</sup> Fourth, around the national lockdown announced on March 24, electricity consumption dropped strongly. Fifth, at the end of May electricity consumption first recovered before falling again.

## **3.2 Nighttime light intensity**

The
# **_iii. Heterogeneous effects across different robot applications_**

The final contribution of the paper is to examine whether certain robots matter more for quality than others. Our robot data contains information on specific robot types, that vary widely in their sophistication within a given application. For example, within handling applications, there are robots that are equipped with sensory devices that allow for product defect detection and others that lift and stack pallets. Similarly, within processing applications, some robots have precision laser cutting, while others are mechanical. Within this section we focus on these examples within cutting and handling applications, contrasting the quality effects across advanced and more rudimentary robots.<sup>26</sup> Unfortunately, the robot application data is not available directly at the country-industry level. We approximate robot applications at the country-industry-level by interacting the (country-level) share of a given robot application with the (country-industry-level) of robot stock. We do so, to avoid country-level regressions and enable a consistent estimation specification across regressions. We construct our instrumental variables in the same way. This results in less variation than our baseline robot stock measure and thus our instruments are somewhat weaker. We present the OLS results below and report the IV results in Table A8 and A9 in the Appendix which find similar results but with weaker instruments.

For cutting robots we find gains overall from both mechanical and laser guided cutting machines (see Table 6). Interestingly, for developing countries we find that quality gains are obtained from the more rudimentary robots, with mechanical cutting tools. In contrast, developed countries experience quality gains only from sophisticated laser guided cutters. Even adopting relatively basic robots may increase production quality in developing countries, if for instance, they reduce production errors compared to the pre-existing production technology of labor and machines. For handling robots (see Table 7) we find that quality gains from that robot class are mainly driven by less sophisticated applications, pallet handling, as opposed to more sophisticated handling and

> 26 Handling, processing and welding
an increase of just under 47 percent in 8 years.<sup>5</sup> Significantly, nonoil (oil) exports rose (fell) as a share of GDP, from 5.4 (18.5) percent to 19.1 (11.6) percent. This has been led by the private sector, which now accounts for 92.8 percent of all nonoil exports from the country. The composition of nonoil exports has also moved from raw materials toward intermediate and consumer goods, with the latter two forms accounting for more than half of all nonoil exports in 2007.

At the most superficial level, the number of Syrian exports has grown significantly over the past decade. The number of merchandise products exported in 2006 has more than doubled from the low of 60 product lines in 1999, with these export numbers displaying a solid upward trend; in addition, this trend exceeds both the regional as well as lowermiddle income country average, of which Syria is part (Figure 1).

<!-- Start of picture text --> Number of<br>300<br>products<br>exported<br>250<br>200<br>Middle East and<br>North Africa<br>150<br>Lower Middle<br>Income<br>100<br>50 Syria<br>0<br>1995 1997 1999 2001 2003 2005 2007<br>Source: World Trade Indicators (2010)<br><!-- End of picture text --> Figure 1: Number of products exported, 1995–2008, Syria, regional average, and lowermiddle income country average. Syrian data not available after 2006. Number of merchandise products calculated at 3-digit SITC level, and includes only products whose value exceeds USD $100,000 or 0.3 percent of the country’s total exports, whichever is smaller.

This trend is most pronounced in the period following the start of reform in 2001,
work original in nature;

- The works were written, recorded or made in the form of materials and the creator is a qualified person;

- The works were made in Malaysia or the first publication of the work, is in Malaysia.

- Industrial design was the overall exterior appearance of an item or product. Shape or configuration is three dimensional aspects while decorative patterns or includes two dimensions. The characteristics of three dimensional or two or both which appear on finished goods shall be through the industrial method. These features will provide a unique appearance in an item or product.

- Geographical indication is an indication which identifies any goods as originating from a country or territory, or a region or a place in the national territory or, where quality is determined, or the reputation of the other characteristics of the goods is essentially attributable to their geographical origin. Geographical indications can be used above or natural or agricultural produce discharges or handicraft industry.

- Layout Designs of integrated circuits is the three‐dimensional arrangement of the elements of an integrated circuit and part or all of the relationships that integrated circuits or such three‐dimensional arrangement prepared for an integrated circuit intended to be manufactured. The law that protects the layout design of integrated circuits is the Layout‐Designs of Integrated Circuits Act 2000.

Source: Economic Census Malaysia 2016, Department of Statistics Malaysia.

35
<mark>Fourth, we combine in our questionnaire established measures in the literature where available (e.g., for job satisfaction) with measures developed by ourselves where needed (e.g., to measure whether respondents were hired based on merit). We drew on the</mark> <mark>aforementioned cognitive interviews and a measurement validation framework (Mikkelsen et al., forthcoming) to develop these measures, and continue to undertake methodological work for further questionnaire improvement (cf. Rogger and Schuster, forthcoming).</mark> <mark>Our current dataset brings together responses from over 1,300,000 public servants in over 1,300 government institutions in 23 countries in the Americas, Europe, Africa, and Asia (Table 1). The dataset comprises surveys conducted by the authors in 18 countries, as well as published data from 5 countries that conduct their own surveys (UK, US, Australia, Canada, and Colombia). As a result – and as some of our surveys were conducted by GSPS members before our core module was finalized – the country coverage of different indicators varies. Figures 2 to 11 in this paper thus have varying country coverage (we always show the full set of countries available for an indicator).</mark> <mark>Our online dashboard on https://www.globalsurveyofpublicservants.org/indicators/ enables scholars to compare countries and to assess within-country variation in each indicator – for instance across institutions or demographic groups (e.g., by gender or age group). The data can also be downloaded (at the country, organizational and demographic group level) with confidence intervals (see</mark> <u><mark>https://www.globalsurveyofpublicservants.org/datadownloads/).</mark></u> 10
In 2019, we used Census and labor force survey data to select districts in the Upper River Region (URR) and Central River Region (CRR) that had high levels of irregular migration. These regions are largely rural, and have a driving distance of around 300km or more from the capital city of Banjul, and 450km from Dakar. We then randomly chose 391 settlements in these districts and did a door-to-door listing exercise to identify households with males aged 18 to 33, the prime age for migration. A face-to-face baseline survey in April and May 2019 collected demographic and labor force information, previous migration experience, and migration intentions of 3,641 youth. In September and October 2020, an in-person follow-up survey was conducted. We were able to re-interview 2,757 of the youth (76% of the original sample), which form the sample used for this paper.<sup>9</sup> The first column of Table 1 provides baseline summary statistics for the sample interviewed at follow-up. This sample consists of males with an average age of 23, who are almost all working in agriculture, with only 28 percent having worked for pay in the past month. Schooling levels are low, with an average of just over 3 grades of schooling, and 31 percent are married. Only 3 percent made a previous unsuccessful attempt to migrate to Europe, but 22 percent have relatives in Europe, and on average they know 3 people who have died going the backway and 10 people who have made it. 29 percent were receiving remittances at baseline. The initial desire to migrate to Europe is high. We asked at baseline “Ideally, if you had the opportunity, would you be willing to migrate and live elsewhere outside The Gambia?” If respondents said yes, they were asked which country they would ideally like to move to. 55 percent said they would like to move to somewhere in Europe, and 7 percent would ideally like to move to Senegal. This “ideal” destination may be different
two Belt and Road strategy documents published by Chinese government agencies, and complete an ex-ante economic evaluation of these projects.<sup>2</sup> This paper does not seek to push the theoretical frontier in urban economics, but rather to apply widely-accepted frameworks to study the largest and most geo-politically consequential infrastructure construction program in recent history. To our knowledge, ours is the first analysis to systematically compare the potential economic benefits of individual Belt and Road projects. Project benefits are quantified in terms of expected changes in market access—the sum of the size of all markets on the transportation network, each weighted by the inverse of the ad-valorem trade cost needed to reach it. Theoretically, increases in market access lower the cost of consumption and the cost of production in a location, leading to an increase in the value of land in a location. Total 2 Open access GIS shapefiles of the BRI project database developed for this study are available <u>here. These projects, whose names, locations and status (i.e., proposed, planning,</u> under construction, operational) are listed in Appendix A, are located within 30 kilometers of at least 223 million urban residents, and span 23 different countries, which together produce 24 percent of global GDP. Excluding China, 22 countries and 9% of world GDP. Other estimates of the number of countries covered by the BRI are typically larger, as they include projects in Africa and Western Europe, which do not lie on the corridors identified in the two Chinese government documents on which we base our database. The nodes in our network include all cities described in the UN World Urbanization Prospects for 2015. Note that our database includes only transportation projects, which account for approximately 25% of BRI projects, the remainder of which comprise primarily electric energy projects, and select investments in chemicals, metallurgy and mining (World Bank, 2019). The value of non-transportation projects is outside the scope of this study.

3
in employment and income, access to health and education services, and coping mechanisms to deal with job loss or other shocks related to the pandemic or the measures implemented by governments to mitigate the spread of the disease. The questionnaires also inquired about household knowledge about the disease and the degree of compliance with preventive measures.<sup>3</sup> In each selected household, only one adult aged 18 and above was interviewed. The same respondent was contacted again in the following rounds. Around 1,000 surveys per country were gathered in the first round, 73 percent in the second, and 70 percent in the third.<sup>4</sup> Survey estimates for each country are representative of individuals aged 18 and above who have an active cellphone number or a landline at home.<sup>5</sup> Also, the survey is representative of households with a landline and for which at least one member has a cellphone. Tables 1 and 2 present summary statistics of the main variables in the HFPS for the 13 Latin American countries taken together. According to Mejia-Mantilla et al. (2021), compared to national household surveys, individuals in the HFPS sample are somewhat more educated, younger and more likely to reside in urban areas.

The HFPS were extremely useful in the midst of the crisis, when data from national household surveys (NHS) was not available. But, even when these larger surveys became available, the relevance of the HFPS remained high for various reasons. First, the questionnaire of the World Bank surveys was especially tailored to the crisis and includes a large number of specific questions. Second, unlike most NHS, the HFPS are multi-wave panel surveys that allow tracking short-run changes during the pandemic. Finally, the HFPS were uniform across countries (same questionnaire, same time window, etc.), so the comparability of the results and the possibility to construct aggregate regional measures are enhanced compared to the much more heterogeneous national household surveys.

# **3
# ANNEX B Univariate filters

Univariate statistical filters decompose a series yt into trend, cyclical, and noise components. The trend component is used as a proxy for potential output. Although they are all essentially weighted moving averages of the series yt , they differ in their weights.

Five univariate filters are applied to estimate potential output: filters based on Hodrick and Prescott (1997), three band-pass filters (Baxter and King 1999; Butterworth 1930 and Gomez 2001; Christiano and Fitzgerald 2003), and a filter based on an Unobserved Components Model. The measures are estimated for 37 advanced economies and 52 EMDEs for 1980Q1-2022Q1 (table 10). Forecasts from the Global Economic Prospects report provide data to 2024. A smaller sample is used in comparisons with other approaches, to ensure consistency of samples (tables 11 and 12).

## Hodrick-Prescott filter

The Hodrick-Prescott (HP) filter minimizes deviations of a series yt from its trend τ t , assuming a degree of smoothness λ of the trend. The HP filter chooses the trend τ t that minimizes: where T is the sample size. A larger λ indicates a smoother trend. For λ =0, the trend is equal to the actual series and for λ >+ ∞ the trend is a linear time trend with a constant growth rate. Typically, the value of λ is set at 1600 for quarterly data. The trend is estimated based on past values as well as projected values of the series yt.

## Band-pass filters

The three band-pass filters aim to isolate fluctuations in a time series which lie in a specific band of frequencies. They eliminate slow-moving components (trend) and very high frequency components (noise) and define the intermediate components as the business cycle. Specifically, the three band-pass filters differ in their approximations of the optimal linear filter (also known as the “ideal” band-pass filter) to deal with finite time series.

The Baxter and King (BK) filter is a moving average of the data with symmetric weights on lags and leads.
which might be consequently reflected in higher informality. For summary of empirical findings see for instance OECD (1997, 2004). In reality, the negative effect might be offset by the extent to which unions and/or firms coordinate their wage determination (Nickell and Layard, 1999; OECD, 1997). Presence of trade unions in a firm might also lead to a more intense oversight of potentially informal activities of the firm. As showed in Zahariev (2003) using Bulgarian data, weak trade unions give more powers to management of companies in raising tax evasion and informal activities without employees’ agreement. As a result, the overall effect of trade unions on informality might be ambiguous.

In most of the European countries, trade unions play an important role in wage determination process. Their power is traditionally measured by the share of workers who are trade unions’ members―trade union density.<sup>24</sup> Overall situation in European countries is depicted in Annex 2. The source of our data is the OECD database mainly, that covers old European countries and NMS-4 (Czech Republic, Poland, Slovakia and Hungary) in longer time series. Data for the rest of NMS group except Malta and Cyprus again come from IZA database and were available for years 1999, 2003 and 2007 only. Therefore, NMS average in the following paragraph and Annex 2 refers to above mentioned four countries only for sake of comparability of development in time.

The data show higher trade union influence in old member countries, which might be on the other hand offset by higher degree of centralization and coordination (see for instance Fialová and Schneider, 2009). Trade union density is in average much lower in the NMS group compared to old European average. Moreover, while the indicator has had an increasing tendency in old Europe, NMS group clearly exhibited an opposite trend. The highest unionization exceeding 50% of wage earners among the examined countries has traditionally been characteristic for northern Europe―Sweden, Norway, Finland, Denmark and
routine preventative health clinic visits, was only collected in the final survey round, so we are unable to examine whether the variable exhibits balance in the baseline round (pre-intervention) across the treatment and control groups.<sup>7</sup> Household attrition was very low between the baseline and one-year follow-up survey (1.42 percent), and increases slightly when comparing the baseline and two-year follow-up survey (4.62 percent). In Table 3, we explore the relative differences between attritor and nonattritor households. Column 1 presents means of the household-level characteristics from the baseline survey for the sample of households that were followed from the baseline to the twoyear follow-up survey (non-attritors). Column 2 presents means for the sample of attritor households, and column 3 presents the average difference in characteristics between attritors and non-attritors, as well as a test of whether the difference is statistically significant. Results suggest that attrition is not likely random, as attritors are more likely to come from smaller households, with fewer adults, are younger, have fewer wives, and are more likely to be female headed households. However, what is more relevant for our analysis is whether attrition differs across treatment and control groups. In columns 4 to 7 of Table 3, we present difference-in-differences regressions for each characteristic comparing the difference between attritors and non-attritors in each specific treatment arm with the same difference between attritors and non-attritors in the control group, and we find few significant differences.

# **3. Empirical Identification Strategy**

The key question we want to answer is whether cash transfers increased the frequency of routine preventative visits to health facilities by young children in recipient households. The experimental design provides a strong identification strategy and allows us to attribute any

> 7 However, we are able to test baseline balance for other health outcomes for which we do have three rounds of data, such as the probability the child was sick during the past month, health clinic utilization, and illness duration, and all of these exhibit balance across randomized