rafmacalaba/data-use-mentions-extended huggingface dataset:
5 working for domestic firms, these firms can benefit from the knowledge and skills that the workers incorporate. An example of this effect is provided by Görg and Strobl (2005), who estimate drivers of productivity for a sample of manufacturing firms in Ghana and identify a productivity premium among firms whose owners worked for MCN affiliates earlier on in their career. Another example is presented by Poole (2013), who uses a matched establishment-worker data set for Brazil and identifies positive productivity effects among domestic firms that employ workers who were previously employed by MNC affiliates.

The third channel consists of inter-firm linkages between MNC affiliates and domestic firms that supply inputs to (or purchase inputs from) the affiliates. These inter-firm linkages are conducive to the creation of productivity spillovers for various reasons. First, MNC affiliates exercise stronger demands on local suppliers regarding the quality of inputs, their cost-effectiveness, specifications, and so on. Even in the absence of technology dissemination, this can lead to productivity effects when domestic firms respond to these stringent demands by improving their performance. Second, input markets are often characterized by frequent contacts and the sharing of information between buyers and sellers, facilitating demonstration effects and unintentional technology flows to domestic firms (UNCTAD 2001). Third, MNC affiliates are often actively engaged in providing support to their suppliers and customers, fostering technology dissemination and productivity spillovers (Jordaan 2016; UNCTAD 2001). An example of this is provided by Jordaan (2017) who presents findings from a survey in northeastern Mexico showing that MNC affiliates provide a variety of types of support to their local suppliers, which according to these suppliers has been very important in generating performance improvements.

The first waves of quantitative FDI spillover studies were concerned with the econometric estimation of intra-industry (horizontal) spillovers, linking the presence of MNC affiliates to productivity of domestic firms operating in the same industries. The evidence on the general prevalence of these intra-industry spillovers is very mixed and inconclusive, ranging from negative to insignificant to positive (Görg and Greenaway 2004; Smeets 2008)
The IV regression results are displayed in **Table 8** . The first-stage IV results (column 1) confirm a positive and significant relationship between the WBL index and each of the instruments. The F-statistic for the excluded instruments is significant at the 1% level and well above the minimum recommended level of 10. The over-identification test based on Hansen's J statistic implies that we cannot reject the null hypothesis that the instruments are valid. The second-stage IV results (columns (2), (3) and (4)) confirm that general equality in the law is strongly positively associated with women’s access to financial products.

We provide additional controls for potential endogeneity using the lagged values of the explanatory variables to provide an additional way to avoid potential endogeneity problems. As our sample is composed of four waves of data, the use of lagged variables leads us to consider only the 2014, 2017 and 2021 waves, thus substantially reducing the size of the sample.

The results presented in **Table 9** indicate that our key finding is preserved: the coefficients for the interaction terms of interest are positive and significant. This provides support to our claims that endogeneity does not drive our results.

# **5.4. Country-level estimations**

So far, we have performed estimations at the individual level as we link the gender of the individual with her/his level of financial inclusion. We only focused on the beneficial effect of gendered laws on women’s financial inclusion. However, one may argue that improvements in gender-related legislation may be part of a global institutional enhancement that could benefit men too. We should therefore verify that the legal framework contributes to decreasing the gender gap in financial inclusion at the national level. To this end, we perform our estimations using the Global Findex country-level data. We measure the gender gap in access to financial services by considering the ratio of the percentage of women having a bank account to the percentage of men with access to formal account ( _Female
<mark>practices were to foment a series of favorable employee attitudes and behaviors – such as work motivation, innovation and performance orientation. Again, our core questionnaire therefore includes their measurement.</mark> <mark>Our core survey thus includes measures that capture key characteristics of</mark> <mark>patrimonialism, Weberian bureaucracy and New Public Management. They enable scholars to understand to what extent governments and different institutions inside government blend different elements of these ‘ideal-types'.</mark> <mark>At the same time, to further ensure that our results are actionable, the GSPS module also contains measures that are core to governmental interests when governments themselves undertake surveys of public servants. To identify these measures, we reviewed the topics covered by six governments that regularly conduct government-wide employee surveys: the U.S., Canada, Australia, the UK, Colombia, and Ireland (see Mikkelsen, Schuster, and Meyer-Sahling 2021, for details of this review). Our review finds that governments measure an overlapping set of management practices and employee attitudes. For instance, in terms of employee attitudes, all governments measure employee engagement and organizational commitment, and all but one measure job satisfaction and turnover intention. In terms of management practices, all governments measure employee perceptions of pay, leadership, and performance management. To ensure we measure indicators of practitioner interest, we thus include in the Global Survey core module those measures which at least five out of six reviewed governments include in their surveys.</mark> <mark>Comparing measures included in government employee surveys and measures of core scholarly interest in academic models of governance, there is some overlap – for instance around performance management or career commitment of public servants. There is also divergence, however, with government employee surveys giving greater pride of place to concepts that are core to organizational psychology – such as job satisfaction or engagement</mark> 7
33|19.40|
|1 child|3.12|3.50|5.37|6.34|3.64|8.34|12.23|5.15|8.24|17.19|16.45|19.85|
|2 children|3.21|3.05|3.75|2.99|3.81|8.97|8.93|7.40|8.50|14.64|16.55|18.56|
|3 and more children|2.12|4.31|6.06|3.21|8.89|9.44|7.50|4.78|8.60|12.41|14.53|19.33|
|singleparent|2.22|4.71|8.00|2.18|2.31|8.43|5.64|6.18|14.42|21.15|17.75|23.15|

Source: Authors’ estimates based on HSS data.

33
were carried out by applying the MEGAS methodology<sup>42</sup> to determine national expenditures in HIV/AIDS. The last study was done with expenditure estimates obtained from a short sample of IPSs, EPSs, DTSs and international donors. Apparently, the reason why the MEGAS methodology was not used for the last study was because it would have required a longer period of time to apply—and the elaboration of the UNGAS 2010 report was urgent.<sup>43</sup> Unlike the PEN budget analyzed in the previous section that was disaggregated into 11 activity categories, the three expenditure studies were disaggregated into eight categories. These were: (i) prevention; (ii) care and treatment; (iii) orphans and vulnerable children; (iv) program management and administration strengthening; (v) human resources; (vi) social protection and social services (excluding orphans and vulnerable children); (vii) enabling environment; and (viii) research. To start with, this discrepancy in categorization makes the assessment of whether programs and services have ultimately been funded as planned extremely difficult.

There were further discrepancies in the data published by the three expenditure studies. For example, the total expenditures of the national response to HIV/AIDS for the year 2007 was 254.454.112.740 COP according to the 2008 report, but 182.849.521.500 COP according to the 2011 report. These discrepancies were present throughout all of the disaggregated figures that were published (e.g., by expenditure category; nature of financing; fraction of public expenditures by territorial level) in all three documents. As suggested by informants, a possible explanation for these discrepancies lies in the fact that each study applied a different methodology – as explained above.

Because of the problems associated with those discrepancies, the Study focused on years 2008 and 2009, which were also central years of the PEN life. Table 4 below shows HIV/AIDS expenditures for 2008 and 2009 disaggregated
# **Patterns and Correlates of Intergenerational Non-Time Transfers:**

# **Evidence from CHARLS**<sup></sup>

Xiaoyan Lei<sup>*</sup> , John Giles<sup>**</sup> , Yuqing Hu<sup>*</sup> , Albert Park<sup>***</sup> , John Strauss<sup>+</sup> , Yaohui Zhao<sup>*</sup>

**Key Words** : Intergenerational Transfers, Population Aging, China, CHARLS

**JEL Codes** : J14, O12, D64, H55, Q12

**Sector Board:** Social Protection (SOCPT)

>  The survey data collection necessary for this research was supported by the US National Institute on Aging (R21AG031372), the National Science Foundation of China (70773002 and 70910107022), the Knowledge for Change Trust Fund at the World Bank. The content reflects the work of the authors and does not represent the official views of any funding agencies.

> *Peking University.

> **The World Bank and Institute for Study of Labor (IZA).

> *** Hong Kong University of Science and Technology and Institute for the Study of Labor (IZA).

> +University of Southern California.
demographic trend alone could account for nearly 30% of the decline in occupant fatalities per VKT during this period.

The positive relationship between YOUTH and fatalities per VKT finding agrees with results in the literature, including Peltzman (1975), Noland (2003a) and Page (2001).<sup>20</sup> However, the importance of demographics is more pronounced here than in most within-country studies that are limited to shorter periods of analysis. Using countylevel data for 1970 and 1980, Keeler (1994), for example, finds increases in the young population to increase traffic fatalities but the result is not significant.

An interesting implication of Table 7 is that, because the coefficient on the YOUTH-income interaction term is negative in all specifications, the importance of young drivers diminishes as incomes increase. The elasticity with respect to YOUTH exceeds 2.0 _(0.50)_ for per capita incomes less than $5,900 (1996 international dollars)<sup>21</sup> but falls to 0.08 _(0.26)_ once per capita income reaches $25,000.<sup>22</sup> This result could reflect changes in young people’s attitudes toward risk or an increase in education of young drivers with increases in economic prosperity.

In contrast to the effects of YOUTH, the percentage of driving age population aged 65 and over (ELDERLY) has a small, positive but insignificant effect on occupant

> 20 Peltzman (1975) found the elasticity with respect to the vehicle occupant death rate to be 0.594 (t-stat = 7.002) in the U.S. over 1947-65, although he included motorcyclist deaths with non-occupants.  Page (2001) estimates the elasticity with respect to total fatalities to be 0.83 _(0.11)_ for OECD countries over 1980-94.  Noland (2003a) finds the elasticity ranges from 0.49 (t-stat = 2.17) to 1.11 (t-stat = 6
The use of disaster data from databases such as EM-DAT and NatCatSERVICE for estimating the macroeconomic consequences of natural disasters has been criticized for possible issues related to endogeneity and measurement.<sup>8</sup> An alternative is to use the physical strength of disaster events to measure their intensity. Albala-Bertrand (1993), in a seminal contribution, collected data on 28 events across 26 countries between 1960 and 1979 and argues that natural disasters have a positive effect on GDP. Strobl (2011) constructs a “Hurricane Disaster Index,” by combining estimates of monetary losses, wind speed, as well as local exposure, and finds that hurricane strikes significantly reduced the annual economic growth of coastal counties in the United States between 1970 and 2005. Hsiang and Jina (2014) show that tropical cyclones cause permanently lower levels of GDP, using a data set containing information on the exposure of all countries to all known cyclones between 1950 and 2008. Felbermayr and Gr ̈oschl (2014) construct a data set of physical intensities of earthquakes, volcanic eruptions, storms, floods, droughts, and extreme temperature events from primary geophysical and meteorological information. They find that, on an average, natural disasters have had a substantial, negative impact on the growth of per capita GDP in the years subsequent to the disasters, but that there is a recovery later.<sup>9</sup> Another approach consists of studying specific disasters in case studies. Disasters are treated as “natural experiments” for causal estimation of their impacts on different variables of interest. On the one hand, Coffman and Noy (2012) find that even 18 years after Hurricane Iniki hit Hawaii in 1992, Kauai’s economy had not fully recovered. On the other hand, Heger and Neumayer (2019) find that the 2004 Indian Ocean tsunami depressed economic growth in the Indonesian province of Aceh only for one year after the disaster. They argue that growth was considerably boosted subsequently by reconstruction efforts.

We contribute to this literature by causally estimating
high-skilled as a percentage of the total number of male individuals of 20-64 years of age who have moved residence in the past five years predicted by the two instruments - as in Columns (1) and (4) of Table A4 but excluding the year fixed effect. Figure A7 presents the results, using 2001 census district boundaries. The top panel refers to the 2001 year, while the bottom panel refers to the 2011 year. The maps on the first row of each panel refer to the standard instrument, while the maps on the second row of each panel refer to the residual network instrument.

We draw two conclusions. First, we note little difference between the rows of each panel, reinforcing the claim that the residual instrument method yields similar results as the standard instrument. Second, we note that for most regions, there is little geographical clustering, alleviating concerns regarding any remaining, unobservable, regionally correlated effects.

# **7 Results**

Table 3 presents the correlation between migration and land tenure arrangements, exploiting variation between districts in 2002 and 2012. The dependent variable is the percentage acreage rented in under specific terms. Column (1) refers to fixed rent, column (2) to the sub-category of fixed rent under monetary terms, column (3) to the sub-category of fixed rent under crop terms, column (4) to sharecropping, column (5) to renting from relatives, column (5) to two-year or longer contracts and column (6) to written contracts. All the dependent variables are included in percentage terms, that is, as a percentage of the rented-in acreage.

We find that as hypothesized, the out-migration of high-skilled males has a statistically significant positive correlation with the prevalence of fixed rent contracts under money terms, and a negative correlation with the prevalence of sharecropping. The raw association between high-skilled male out-migration and the prevalence of fixed rent contracts paid in produce is negative; as discussed further below, such contracts are in between sharecropping and fixed rent contracts in money terms
<!-- Start of picture text --> China<br>12<br>co}<br>£<br>xe)<br>=©= 10<br>a<br>LD<br>[=<br>32 8<br>=<br>(6)<br>no]<br>2<br>8a 6<br>x<br>ui<br>4<br>0 5 10 15 20<br>Father's years of schooling<br>— Risk Adjusted — Unadjusted<br><!-- End of picture text --> <!-- Start of picture text --> Indonsia<br>15><br>D<br>£<br>xe)<br>3<br>£o<br>7)<br>vn<br>FS[<4 10<br>2<br>cS)<br>ao]<br>2[=]<br>o<br>Qa<br>x<br>wi<br>a aa<br>05 10 15 20<br>Father's years of schooling<br>—— Risk Adjusted —— Unadjusted<br><!-- End of picture text --> <!-- Start of picture text --> India<br>15<br>oS<br>£<br>é6 10<br>cn<br>2<br>3=<br>(6)<br>BSoOo<br>uiax<br>0)<br>0 5 10 15 20<br>Father's years of schooling<br>—— Risk Adjusted —— Unadjusted<br><!-- End of picture text -->
**Figure 11. Trade Complementarity, Russia and Peers, 2004–11**

<!-- Start of picture text --> 100<br>90<br>80<br>70<br>60<br>2004 2006 2008 2010 2012<br>DEU CHN IND JPN KOR MYS PHL<br>Trade Complementarities Index<br><!-- End of picture text --> Source: World Bank Trade in Services Database.

Note: Trade Complementarities Index (TCI) is an index indicating extent to which a country’s export profile is similar to a partner country’s import profile. DEU = Germany, CHN = China, IND = India, JPN = Japan, KOR = Korea, MYS = Malaysia, PHL = Philippines 35
- Fang, Lei, David Peter Wyon, Geo Clausen, and Povl Ole Fanger (2004), “Impact of indoor air temperature and humidity in an office on perceived air quality, sbs symptoms and performance.” _Indoor air_ , 14, 74–81.

- Fesselmeyer, Eric (2019), “The impact of temperature on labor quality: Umpire accuracy in major league baseball.” _Available at SSRN 3421241_ .

- Fletcher, Jason M and Barbara Wolfe (2016), “The importance of family income in the formation and evolution of non-cognitive skills in childhood.” _Economics of education review_ , 54, 143–154.

- Galster, George and Patrick Sharkey (2017), “Spatial foundations of inequality: A conceptual model and empirical overview.” _RSF: The Russell Sage Foundation Journal of the Social Sciences_ , 3, 1–33.

- Garg, Teevrat, Gordon C McCord, and Aleister Montfort (2020), “Can social protection reduce environmental damages?”

- Hallegatte, Stephane, Jisung Park, Mook Bangalore, and Evan Sandhoefner (2018), “Households and heat stress: estimating the distributional consequences of climate change.” _Environment and Development Economics_ .

- Harries, Keith D, Stephen J Stadler, and R Todd Zdorkowski (1984), “Seasonality and assault: Explorations in inter-neighborhood variation, dallas 1980.” _Annals of the Association of American Geographers_ , 74, 590–604.

- Hausman, Jerry A, Bronwyn H Hall, and Zvi Griliches (1984), “Econometric models for count data with an application to the patents-r&d relationship.” Technical Report 17, National Bureau of Economic Research Cambridge.

- Heilmann, Kilian and Matthew E Kahn (2019), “The urban crime and heat gradient in high and low poverty areas.” Technical report, National Bureau of Economic Research.

- Heller, Sara B, Anuj K Shah, Jonathan Guryan, Jens Ludwig, Sendhil Mullainathan, and Harold A Pollack (2017), “Thinking
2016; De Loecker et al., 2016; Amiti and Konings, 2007; Handley et al., 2020; Fan et al., 2015; Amiti et al., 2019; Handley et al., 2020b; Fajgelbaum et al., 2020) and non-tariff measures in particular (Ederington and Ruta, 2016; Fontagn ́e et al., 2015; Grundke and Moser, 2019; Kruse et al., 2021). A key message

> 2A unique feature of the Indonesian customs data is that it explicitly keeps track of firms that are producers as opposed to pure trading firms.

4
# **_Length of the school day and the quality of the textbooks_**

The fact that the state-managed network could cover as much school content as the locallymanaged network that remained open is associated with the longer school hours per day (5.3 hours versus 4.9 hours). This difference is equivalent to an addition of three to four school days in the whole school year compared to locally-managed schools (Table A.4).<sup>29</sup> However, the additional time in the classroom due to the longer duration of the classes in the state-managed schools is still inferior to the lost time in the classroom due to the period of the shutdowns. We did not find any source of information that could suggest that the state government extended the length of the school year to compensate for the days the schools were closed. The length of the school year was five days longer in the locally-managed network (Table A.4). These statistics also suggest that teachers of the state-managed network had to rush to cover the school curriculum, probably making it challenging for the students to keep up.

A glance at the descriptive statistics presented in Table A.3 also highlights the challenges faced by the municipal schools affected by the shutdowns. One of the issues that stands out is that these schools could not cover the school curriculum in a shorter time frame. While 55% of municipal schools in municipalities that did not extend the winter break covered more than 80% of the school curriculum, only 45% did so in municipalities that extended the winter break.

Data from _Prova Brasil_ questionnaire show that teachers faced many barriers to successfully covering the entire school curriculum. For instance, students in treated schools had fewer hours of classes per day (4.8 hours _×_ 5 hours). The 12-minute daily difference resulted in children from the affected schools having two days less of school content between the reopening of the schools and the proficiency test.<sup>30</sup> Also
>•<br>Main job is in own business or farming activity<br>•<br>In a business or farm operated by a household member|
|Wage Employment|<br>Individual (> 15 years of age) whose main activity is working as an employee, trainee or intern for<br>someone else outside of the household|
|**_Main explanatory variables_**||
|Gender role attitudes Index|A Z score index derived from responses to 14questions ongender role attitudes|
|Personalitytraits|Responses: Stronglyagree/Agree/ Neither agree nor disagree/disagree/ stronglydisagree|
|Impulsiveness|Iplan tasks carefully (_reverse coded_);I make upmymindquickly;I save regularly (_reverse coded_)|
|Work centrality|I look forward to returning to my work when I am away from work;<br>The most important thing that happens in life involves work.|
|Tenacity|I can think of many times when I persisted with work when others quit;<br>I continue to work on hard projects even when others oppose me.|
|Polychronicity|I like to juggle several activities at the same time;<br>I would rather complete an entire project every day than complete parts of several projects (_reverse_<br>_coded_); I believe it is best to complete one task before beginning another (_reverse coded_)|
|Locus of control|It is difficult to know who my real friends are (reverse code); I never try anything that I am not sure of<br>(reverse code); A person can get rich by taking risks.|
|Achievement|It is important for me to do whatever I’m doing as well as I can even if it isn’t popular with people<br>around me; Part of my enjoyment in doing things is improving my past performance; When a group I<br>belong to plans an activity, I would rather direct it myself than just help
to the International Classification of Diseases, 10th revision (ICD-10). It is important to note that these expenditures primarily reflect the public sector (based on reimbursement rates).

To establish the medical expenditures associated with each risk factor-related disease, we link them to the diseases outlined in the Global Burden of Disease dataset. For each specific disease, we deflate the monthly treatment expenditures incurred during 2018-2022 using Brazil’s National Consumer Price Index and calculate the average, as shown in Table 4. Subsequently, the average medical expenditure associated with each disease related to the risk factor “dietary risks” is determined by computing the average cost across all related diseases and dividing it by the average number of approved Hospital Admission Authorizations (AIH). In other words, the average cost for each disease is calculated as the ratio between the total medical costs for that disease and the number of admitted patients due to that disease, using the ICD classification.

12