rafmacalaba/data-use-mentions-extended huggingface dataset:
# **Reference** s

Aker, Jenny C., Rachid Boumnijel, Amanda McClelland, and Niall Tierney (2011), "Zap it to me: The short-term impacts of a mobile cash transfer program. Center for Global Development Working Paper No. 268 Aker, Jenny C., Rachid Boumnijel, Amanda McClelland, and Niall Tierney (2013) “How do electronic transfers compare? Evidence from a Mobile Money cash transfer experiment in Niger.” Tufts University Working Paper.

Alphonse, Pascal, Jacqueline Ducret, and Eric Séverin (2006) "When trade credit facilitates access to bank finance: evidence from US small business data." Unpublished working paper, Université de Nancy.

Bångens, Lennart and Björn Söderberg, B. (2011). “Mobile Money Transfer and Usage Among Micro and Small Businesses in Tanzania” SPIDER, The Swedish Program for Information and Communication Technology in Developing Regions.

Batista, Catia and Pedro C. Vicente (2013) "Introducing Mobile Money in rural Mozambique: Evidence from a field experiment" NOVAFRICA Working Paper Series No. 1301 Beck, Thorsten, Haki Pumak, Ravindra Ramrattan and Burak R. Uras (2015) “Mobile money, trade credit and economic development: Theory and evidence”, CentER Discussion Paper 2015023.

Bencivenga, Valerie R., Bruce D. Smith, Ross M. Starr (1995), "Transactions costs, technological choice, and endogenous growth," _Journal of Economic Theory_ 67(1): 153–177 Burkart, Mike, and Tore Ellingsen (2004) "In-Kind finance: A theory of trade credit," _The American Economic Review_ 94(3): 569-590 Blumenstock, J. E., Callen, M., Ghani, T., & Koepke, L. (2015). Promises and pitfalls of mobile money in Afghanistan: Evidence from a randomized control trial. In Proceedings of the Seventh International Conference on Information and Communication Technologies and Development (p. 15). ACM. Blumenstock, J.
Metrics including density of networked components, the redundancy and interconnectedness of sub-systems within the electricity grid – as well as linkages to other lifeline networks – are identified as providing insight into system behavior. However, these metrics are not particularly well understood or quantified, especially in smaller systems or those existing in developing economic regions.

Future work in this area, aimed at enhancing decision making and investment for more resilient infrastructure, can focus on the following areas:

- a) Develop data on the connectivity of lifeline infrastructure systems to determine key interdependencies and how these vary geographically or with other parameters such as per capita GDP or HDI;

- b) Use data on ports of entry and transportation infrastructure to identify regions where supply chain bottlenecks could impact lifeline infrastructure;

- c) Use high spatial and temporal resolution global historical data on wind velocities to determine where electricity grids would be particularly susceptible to damage;

- d) Develop a methodology to identify lifeline infrastructure systems that lack important redundancies.

15
# **4b. Which firms and countries benefit most? Conjectures about ‘the middle’**

We have argued that trade credit is a pervasive form of firm financing, which is found in both advanced and lower income countries, and among firms of all sizes. And yet, for reasons illustrated in the short case studies of different countries above, trade credit could be relatively more important in certain contexts and among certain types of firms. Greater reliance on trade credit could be driven by a lack of reliable market-supporting institutions or underdeveloped formal financial institutions in a country, but even the early literature on trade credit in the U.S. suggested that it was better suited to the financing needs of some types of firms: “[T]rade credit represents a substantial fraction of corporate liabilities, especially for middle-market companies. For example, Mian and Smith (1994) report that ‘for the 3,550 non-financial NASDAQ firms covered by COMPUSTAT, accounts payable were 26% of corporate liabilities, at the end of 1992.’” (Biais and Gollier, 1997, pp. 903-904) Our conjecture is that trade credit may be somewhat better suited to medium-sized firms and to firms in countries that are not very poor and have a reasonable level of institutional and financial development. With respect to firm size, this is because informational frictions (related to, for example, lack of credit histories) and lack of collateral imply that smaller firms have less access to bank finance (see, e.g., Beck, Demirguc-Kunt, and Maksimovic, 2008), which makes it harder for them to extend trade credit to customers. And in the absence of reliable courts and other institutions that enable arms-length contracting, small firms are limited by their personal relationships or other informal mechanisms to signal their creditworthiness, which are likely more binding than for larger firms, and thus limit the amount of trade credit they receive. On the other hand, large firms are less subject to informational frictions and are likely to have
several 2000 occupations map into one 1990 occupation, then we assign the 1990 occupation a replaceability value of one if and only if at least one of the corresponding 2000 occupations has a value of one. To arrive at a measure of replaceability at the industry level, we first assign individuals in the 1980 IPUMS Census a replaceability score based on the 1990 occupation they report (assuming the value 1 if the occupation is replaceable, and 0 if it is not). We then assign each individual to one of our 28 EU KLEMS industries based on a crosswalk to the 1990 Census industry classification. We compute the fraction of replaceable hours for each of the 16 robot-using industries by dividing the sum product of replaceability and annual hours worked by the total sum of hours worked (applying person weights both when computing the numerator and the denominator). The replaceability values represent an upper bound to the share of hours that is replaceable, because occupations are classified as replaceable if only a part of their work can be replaced by robots; this part need not be large.

**Bilateral trade data** : Product-level bilateral trade data come from BACI. This data set is the World trade database developed by the CEPII, building on original data provided by the COMTRADE database of the United Nations Statistical Division. BACI is constructed using an original procedure that reconciles the declarations of the exporter and importer. This harmonization procedure makes it possible to extend considerably the number of countries for which trade data are available. BACI provides bilateral values and quantities of exports at the HS 6-digit product disaggregation, for 224 countries and is available from 1995 onwards. CEPII developed original statistical procedures to reconcile data reported by almost 150 countries to the United Nations Statistics Division. First, as import values are reported CIF (cost, insurance and freight) while exports are reported FOB (free on board), CIF costs are estimated and removed from imports values to compute FOB import values. Second, the reliability of country reporting is assessed based on the reporting distances among partners
**Table 1. Comparing the SPI and Other Data and Statistics Indexes**

|||**Assessment Type/**|**Country**|**Time**|**Index**|**No. of**|||**Share of i**<br>|**ndicators in**<br>|**eachpil**<br>|**lar**|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**No**|**Index**|<br>**Frequency**|<br>**Coverage**|**Coverage**|**Methodology**|**Indicators**|**Data**<br>**Use**|**Data**<br>**Services**|<br>**Data**<br>**Products**|<br>**Data**<br>**Sources**|**Data**<br>**Infra.**|**Data Sources (Share)**|
|1|Open Data Inventory<br>Indicators & Index (ODIN)|Global/ Annual|192|2016-2022|Nested weight|44|0%|50%|50%|0%|0%|NSO Websites|
|2|Open Data Barometer<br>(ODB)|Global/ Annual|116|2013-2017|Nested weight|46|15%|30%|37%|0%|15%|Expert Survey|
|3|Global Data Barometer<br>(GDB)|
incomes and consumption of middle- and upper-income households (Sulla, 2011). It is likely that the ability or inability of households to use effectively strategies to cope with shocks can influence their subjective perceptions of the crisis: faced with job loss or wage reductions, a household that is able to access social safety-nets, or to borrow from friends and family, or use savings, could have a more benign perception of the impacts of the crisis. Going beyond expenditure and labor supply adjustments, we therefore also examine coping strategies, as declared by households, in particular the extent to which they differed across countries and individuals and how they correlated to subjective crisis impact.

The paper begins by describing the data, household subjective perceptions of the impact of the crisis, and the transmission channels through which they were affected. We then analyze heterogeneity in the use of various coping strategies, distinguishing between strategies to increase earnings, private and public safety nets and expenditure reductions. Last, we examine the relationship between household perceptions of the crisis impact and socio-political outcomes.

# **2. Objective shocks and perceptions of crisis impact**

# **2.1. The data**

The Life in Transition survey was conducted jointly by the European Bank for Reconstruction and Development (EBRD) and the World Bank in 2006 and 2010. Nationally representative samples of between 1,000 and 1,500 households were interviewed in every country. In total, in 2010, almost 39,000 households were surveyed in 34 countries of Europe and Central Asia to assess public attitudes, well-being and the impacts of economic and political change.

The crisis impact module of the 2010 LiTS elicits subjective perceptions of the impact of the crisis, in addition to collecting information on the shocks experienced, the coping strategies employed, and access to public safety nets. Respondents were asked how much the economic crisis had affected their household in the past two years, with responses coded as follows: 1: “a great deal”, 2: “a fair
in global value chains, an equally important issue associated with upgrading in production networks.

# III. Framework and data

## A. Capabilities that matter for GVC participation

Employing the above methodology, we focus on a set of capabilities that are most common in the theoretical, policy, and empirical literature on GVC trade. These are summarized in Table 1, along with the specific indicators chosen and their data sources. It is worth noting that because this analysis is carried out at the global level, some capabilities that may have a big impact on GVC trade and investment at a bilateral level – such as preferential trade agreements, bilateral investment treaties, common language, and time zone – are not included. The selection of capabilities to include in the analysis, and most importantly the specific indicators chosen to represent them, were also dependent on country coverage of the source data. Our final data set covers 87 countries, which together represent 81 percent of world trade in 2012.

The capabilities fall into three categories:

- **<u>Fixed</u>** :  capabilities that cannot be changed by a country.

- **<u>Long‐term Policy Variables</u>** : capabilities that can be changed gradually over a relatively long time horizon.

- **<u>Short‐term Policy Variables</u>** <u>: capabilities that can be changed directly through a policy shift or</u> negotiations.

5
<!-- Start of picture text --> 250<br>200<br>Korea<br>150<br>Japan<br>100<br>Taiwan<br>50<br>0<br>7 8 ASEAN 9 10 11<br>-50<br>ln GDP per capita<br>India China<br>Relative Rate of Assistance, % -100<br><!-- End of picture text --> Figure 8. RRAs (%) to agriculture and log of real per capita GDP among large Asian economies, 1955<sup>a</sup> –2010. The GDP per capita data are in 1990 international Geary-Khamis dollars, updated from Maddison 2010.

a Because RRA estimates are lacking for earlier years, the starting dates for India are 1965, for ASEAN 1970, and for China 1981.

Source: Updated from Anderson and Martin 2009, Chap. 1, using Anderson and Nelgen 2012b.

58
industries which received more FDI exhibit a greater demand for skilled labor, a fi nding that they interpret as consistent with a model in which production outsourcing from an industrialized to a developing country raises the demand for skilled labor in both countries.<sup>5</sup> Using plant-level data for the 1980s, Harrison and Hanson (1999) fi nd that Mexican exporters and foreign-owned plants tend to employ a higher share of skilled workers, and so do plants that use more imported inputs and machinery. Pavcnik (2003) analyses panel data on Chilean manufacturing plants during the 1980s and fi nds that the use of imported materials, patented technology and foreign technical assistance appear to be unrelated to the demand for skilled labor in fi xed effects and timedifferenced regressions. However, she reports positive effects of those three variables on skilled demand when using the cross-sectional variation in the data, which she interprets as re fl ecting unobserved plant heterogeneity driven, for example, by different degrees of managerial ability which affect both the adoption of foreign technology and the demand for skilled labor.<sup>6</sup> This paper obtains new plant-level evidence from Brazil and China on the effect of international economic activities on the demand for skilled labor. As Harrison and Hanson (1999), we focus on the cross-sectional variation in the demand for skilled workers, and provide separate estimates on the effects of the use of imported inputs, exports and FDI on relative wages and relative employment.<sup>7</sup> In order to account for the unobserved effects of managerial abil-

> 5 In the model proposed by Feenstra and Hanson (1996b), a single fi nal good is produced with a continuum of intermediate inputs, which are traded between two countries, “North” and “South”, with relative abundance of skilled and unskilled labor, respectively. The North specializes in inputs that are relatively intensive in skilled labor while the reverse is true for the South. A fl ow of capital from North to South leads
suspension. By doing so, it lays a foundation for future research that seeks to better understand informal sector activities and performance via high-frequency tax reporting information. In particular, future work should try to better understand both the extent and the factors that lead small firms, and especially household-owned firms, in developing countries to suspend their businesses when faced with shocks that could be idiosyncratic or aggregate. Understanding the performance and dynamics of small firms is key to improving the livelihoods of poor households, generating jobs, and boosting labor productivity in low-income countries.

# **References**

- **Avdiu, Besart and Gaurav Nayyar** , “When face-to-face interactions become an occupational hazard: Jobs in the time of COVID-19,” _Economics Letters_ , 2020, _197_ , 109648.

- **Banerjee, Abhijit, Dean Karlan, and Jonathan Zinman** , “Six Randomized Evaluations of Microcredit: Introduction and Further Steps,” _American Economic Journal: Applied Economics_ , January 2015, _7_ (1), 1–21.

- **Banerjee, Abhijit Vinayak** , “Microcredit Under the Microscope: What Have We Learned in the Past Two Decades, and What Do We Need to Know?,” _Annual Review of Economics_ , 2013, _5_ (1), 487–519.

- **Bartik, Alexander W, Marianne Bertrand, Zoe Cullen, Edward L Glaeser, Michael Luca, and Christopher Stanton** , “The impact of COVID-19 on small business outcomes and expectations,” _Proceedings of the National Academy of Sciences_ , 2020, _117_ (30), 17656–17666.

- **Beland, Louis-Philippe, Oluwatobi Fakorede, and Derek Mikola** , “Short-Term Effect of COVID-19 on Self-Employed Workers in Canada,” _Canadian Public Policy_ , 2020, _46_ (S1), S66–S81.

- **Bosch, Mariano and William Maloney** , “Cyclical Movements in Unemployment and Informality in Developing Countries,” _World Bank Policy Research Working Paper No. 4648_ , 07 2008
One major challenge is avoiding the double counting of conditional transfers (very likely captured in central government accounts). Transfers to local governments should be netted from central government accounts, and the use of funds recoded as part of the local government data, where the use of resources will be clearly specified.

As mentioned, template 10 should also be filled with local government fiscal data. Identification of relevant local government authorities (for example, provinces, districts, and/or municipalities) and their role in providing infrastructure services should be done in the pre-field stage. Based on this work, the user should have a good sense of whether there is a centralized repository of local government accounts and if they are reported using a common structure.

There two possible options for collection local governments data:

- When there is standardized data reporting to a central unit:

- If local governments use the same budget coding structure as the central government, the user will use the code mapping carried on from the central government to input the data in template 10. But the double counting of conditional transfers (very likely captured in central government accounts) should be avoided by netting out transfers.

- If local governments use different budget coding from the central government and make expenditures in the relevant infrastructure sectors, the user will have to carry out a new recoding exercise before filling in template 10.

- When there is no standardized data reporting to a central unit:

- If aggregate figures for local government are available but without a further economic or functional breakdown, the user should report local government accounts on template 10. As in the above case, the user should avoid double counting. The user should determine whether it can be assumed that most local government spending goes to the relevant productive infrastructure sectors.

- If aggregate figures are not available, the user should select a few of the most relevant/largest local government entities, depending on desired accuracy and resource availability. Only when this has been decided will the user proceed to produce template 10 for the
Wage earners eligible for tax deductions for credit card payments may submit to NTS, via their employers, the credit card tax deduction application form and a credit card transaction report issued by their credit card companies. These materials must accompany the wage earners’ labor income tax settlements filed at the end of the tax year. Credit card companies must issue credit card transaction reports to their customers upon request, or they may voluntarily issue the reports to their customers even without the request.<sup>44</sup> After TIETP was introduced, credit card companies began voluntarily sending their customers annual transaction reports at the end of the tax year as a customer service. In 2000, when TIETP was fully implemented, the Act on the Submission and Management of Taxation Data (ASMTD) became law. According to the act, credit card companies must regularly submit member stores’ credit card or debit card transaction data to NTS. As of 2012, wage earners can claim TIETP tax deductions by confirming prefilled credit card transactions data forms provided by NTS through its Home Tax Service, the NTS tax service internet portal. This service was enabled under ASMTD, which requires credit card companies to submit credit card transaction data to NTS.

If the credit card tax deduction application is valid, employers, acting as the withholding tax agents as to wage earners’ income, subtract the taxes saved by TIETP together with other tax deductions and credits from the tax due in the month following the year‐end tax settlement.<sup>45</sup> If the withholding tax agents should refund overpaid taxes, they can subtract the refund amount from the taxes due in subsequent months or request a refund from the regional NTS office.<sup>46</sup> The TIETP process differs completely from the receipt compensation process adopted in 1977. People who wanted to receive receipt compensation had to submit to a cumbersome application process. They had to collect their receipts and take them to a regional NTS office or commercial bank commissioned to deal with
Household-Reported Spending Effects. _The B.E. Journal of Macroeconomics_ , 12(1).

- Li, S., & Spencer, A. (2016). Effectiveness of the Australian Fiscal Stimulus Package: A DSGE Analysis. _The Economic Record_ , 92(296), 94–120.

- Liebenau, J., Atkinson, R., Kärrberg, P., Castro, D. & Ezell, S. (2009). _The UK's digital road to recovery_ LSE Enterprise Ltd. & the Information Technology and Innovation Foundation.

- <mark>Liu, P., Mumtaz, H., Theodoridis, K. & Zanetti, F. (2017). Changing macroeconomic dynamics at the zero lower bound,</mark> _Journal of Business & Economic Statistics_ Volume 37, 2019 - Issue 3.

- Mallett, W. J.  (2020). Transportation Infrastructure Investment as Economic Stimulus: Lessons from the American Recovery and Reinvestment Act of 2009. Congressional Research Service, May 5, 2020.

- Mian, A. & Sufi, A. (2012). “The Effects of Fiscal Stimulus: Evidence from the 2009 Cash for Clunkers Program.” _The Quarterly Journal of Economics_ (June 22, 2012).

- Michel, A. (2021). Why Infrastructure Spending Will Not Help the Pandemic Recovery, The Heritage Foundation.

- <mark>Misch, F., & Seymen, A. (2019). The effects of fiscal stimulus: firm-level evidence from selective temporary consumption tax cuts.</mark> _<mark>Oxford Economic Papers</mark>_ <mark>, 71(4), 1026–1049.</mark>

- <mark>Mitra, P. (2010). The Impact of Global Financial Crisis and Policy Responses: The Caucasus, Central Asia and Mongolia.</mark> _<mark>Global Journal of Emerging Market Economies</mark>_ <mark>,
could make the best use of it. Finally, misalignment was also related to slow export growth and slow agricultural growth.

A study of growth in 12 countries from 1965-1985 (Edwards, 1988 and 1989), reinforced these findings.'<sup>2</sup> The greater the misalignment, the lower the growth during the period. Furthermore, exchange controls and trade impediments, proxied by the black market exchange rate premium, were negatively related to growth. 13 In a study of economic growth in 18 Latin American countries between 1950 and 1980, Cardoso and Fishlow (1989) showed that growth was very uneven among the

> **12** The 12 are Brazil, Colombia, El Salvador, Greece, India, Israel, Malaysia, Philippines, South Africa, Sri Lanka, Thailand, and Yugoslavia.

> **13** Faini and de Melo (1990) took a somewhat dimmer view of the impact of the real exchange rate on economic performance. They found a positive, but usually not significant, relationship between devaluations and the improvement of the trade balance for 49 developing countries between 1965 and 1985. However, they also found for a smaller sample, different because of data availability, that a depreciated real exchange rate promoted investment. Furthermore, they found that for adjusting countries during the 1980s, the higher prices of imported intermediates brought about by devaluations were not important determinants of depressed investment.

9
# **Long‐term impacts of an unanticipated risk event : the 2007/08 food price crisis and child growth in Indonesia**

Futoshi Yamauchi<sup>a</sup> and Donald F. Larson<sup>b</sup>

**Keyword** s: food price crisis, child growth, human capital, safety nets, Indonesia **JEL Classifications** : Q11, Q18, O12, O15

**Acknowledgments:** We would like to thank Aart Kraay, Quy‐Toan Do, Emiko Fukase and Will Martin for helpful comments and suggestions. We gratefully acknowledge financial support from the donor‐ supported Knowledge for Change Program hosted by the World Bank. We thank Rizal Shidiq for help preparing the consumption and price data.

> a Development Research Group, World Bank.

b Institute for the Theory and Practice of International Relations, College of William and Mary.