rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 10911

# **Abstract**

The arrival of cloud computing provides firms a new way to access digital technologies as digital services. Yet, capital incentive policies present in every OECD country are still targeted towards investments in information technology (IT) capital. If cloud services are partial substitutes for IT investments, the presence of capital incentive policies may unintentionally discourage the adoption of cloud and technologies that rely on the cloud, such as artificial intelligence (AI) and big data analytics. This paper exploits a tax incentive in the UK for capital investment as a quasi-natural experiment to examine the impact on firm adoption of cloud computing, big data analytics and AI. The empirical results find that the policy increased investment in IT capital as would be expected; but it slowed firm adoption of cloud, big data and AI. Matched employer-employee data shows that the policy also led firms to reduce their demand for workers that perform data analytics, but not other types of workers.

This paper is a product of the Office of the Chief Economist, East Asia and the Pacific Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at timothy.destefano@georgetown.edu, nick.johnstone@iea.org, richard.kneller@nottingham.ac.uk, and jtimmis@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of
opportunities in basic housing services, early childhood development, or nutrition and hunger opportunities. Finally, the last part examines the extent to which the evolution of opportunity indices (national and regional) is consistent with the trends in public expenditure by sector and its distribution across regions.

# **_4.1 Opportunity Gaps for Children in the Most Unfavorable Circumstances_**

The first step to assess the link between circumstances and the inequality of opportunities is to examine the access gaps between children in _favorable_ circumstances (90th percentile of circumstances, P90 hereafter) and children in moderately _unfavorable_ circumstances (percentile 30 of circumstances, P30 hereafter). We address three questions. How large are the opportunity gaps and how did they evolve during the decade? Which sectors present the largest opportunity gaps for children in the most unfavorable circumstances? Which sectors have managed to improve access to opportunities by reducing the opportunity gaps for children in unfavorable circumstances? The opportunity gaps for all 16 opportunities are summarized in Table 6 and Figure 7.

**Table 6. Opportunity Gaps between Percentiles P90/P30, Egypt, 2009 and 2000**

||||**_Acce_**|**_ssprob_**|**_ability_**<br>|||
|---|---|---|---|---|---|---|---|
|**_Opportunity_**||**_2009_**|||**_2000_**||**_Change_**<br>|
||**_p90_**|**_p30_**|**_gap_**|**_p90_**|**_p30_**|**_gap_**|**_in gap_**|
|Complete primary education on time|0.99|0.76|0.23|0.97|0.80|0.18|0.05|
|Complete
for SSA, I use the imputed version of Krantz (2023) (Figure A3) and compute the productivity of each city as the inverse-distance-weighted average of cells within 30km of the city centroid. I assume that average household wealth, aggregated at the city level, approximates worker productivity. Footnote 31 argues that national average urban wealth strongly correlates with GDP per capita.

I also calibrate the productivity of international ports so that overall production matches national accounts data. Averaging estimates from the UN National Accounts Main Aggregates database between 2020 and 2022 yields that imports were equal to 26.5% of African GDP. Since my network does not include foreign locations,<sup>32</sup> the imported goods will have to be produced by port cities. Assuming that port outflows in 2020Q1 are proportional to the inflows, multiplying outflows from the 52 largest ports by a factor of 37 yields (precisely) an imports measure summing to 26.5% of the total production volume using the IWI as productivity measure. These imports need to be divided by port city population to yield productivities. Since the framework of Fajgelbaum & Schaal (2020) endogenously allocates labor to different tasks, letting port cities produce both a domestic and international variety would obscure this calibration. Thus, I compound both tasks so that port cities use all labour to produce a mixed international variety at productivity The median intl. productivity is 27 IWI points, but the mean is much higher at 2748, indicating high import volumes in some port cities with small populations. Top of the list is Egypt’s Sokhna Port (towards the Red Sea), with a population of 1000 and intl. productivity of 134,656, followed by Egypt’s Port Said, with a population of 894,850 (within a 30km radius) and intl. productivity of 1,264. Other ports with intl. productivity above 500 include Tanger Med and Walvis Bay. Since utility functions are mildly concave ( _α_ = 0 _._ 7) and the planner
, Gaughan, A. E., Blondel, V. D., and Tatem, A. J. (2014). Dynamic population mapping using mobile phone data. _Proceedings of the National Academy of Sciences_ , 111(45):15888–15893.

- Engstrom, R., Hersh, J., and Newhouse, D. (2017). Poverty from space: Using high-resolution satellite imagery for estimating economic well-being. World Bank Working Paper No. 8284.

- European Commission (2018). Global Human Settlement (GHSL). Retrieved from https://ghsl.jrc.ec.europa.eu/data.php on November 19th 2018.

- Guiteras, R., Levinsohn, J., and Mobarak, M. (2018). Demand estimation with strategic complementarities: Sanitation in bangladesh.

- Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S., Tyukavina, A., Thau, D., Stehman, S., Goetz, S., Loveland, T., et al. (2013). High-resolution global maps of 21st-century forest cover change. _science_ , 342(6160):850–853.

- Harvey, J. (2002). Estimating census district populations from satellite imagery: some approaches and limitations. _International Journal of Remote Sensing_ , 23(10):2071–2095.

- Hastie, T. and Qian, J. (2018). Glmnet vignette. Retrieved from https://web.stanford.edu/ hastie/glmnet/glmnet _alpha.htmlpoi_ on November 19th 2018.

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|43,002|31,905|30,901|27,702|25,195|300,847|
|**Italians**|470,319|495,155|501,083|508,873|484,926|475,036|457,203|486,018|3,878,613|
|**Total**|537,803|550,216|555,291|571,498|528,891|516,777|492,742|517,288|4,270,506|
|_Share of Ukr_<br>_post Feb 2022_<br>_over total_<br>_students_|_0.27%_|_0.23%_|_0.23%_|_0.28%_|_0.17%_|_0.16%_|_0.10%_|_0.06%_|_0.19%_|

Administrative data on enrollment for the academic years 2021-2022 and 2023-2024 are also used to examine the evolution of Ukrainian refugees’ enrollment in Italian schools since February 2022.<sup>10</sup> Figure 1 shows that in 2021-2022, the number of Ukrainian refugees was very low in all grades, with a total of 3,320 Ukrainian refugees that arrived directly after the start of Russia’s invasion of their country. In 2023-2024, the number of Ukrainian refugees enrolled increases in all grades with the exception of Grade 8.<sup>11</sup>

> 10 The distributions of students by grade for academic years 2021-22 and 2023-2024 are shown in Tables B1 and B2 in Appendix B.

> 11 The available data do not allow to estimate the number of refugees enrolled in Grade 6 during the academic year 2023-2024.

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. Schools who received grants in the rst cohort answered a set of questions on the use of the extra funds. To examine the possibility that funds were disproportionately channelled to students preparing to enter secondary school, we also administered written assessments in mathematics and French to a random sample of children who were in 6th grade at follow-up, and also surveyed their teachers.

In the second follow-up, we re-surveyed and tested the same children who were tested at baseline and rst follow-up. In addition, in the second follow-up we administered the Peabody Picture Vocabulary Test (PPVT) to children and their mothers. We did not collect general school 7
> Using data on a vector of relevant characteristics, we find that the Abidjan and non-Abidjan routes in both Mali and Burkina Faso do not differ significantly in the pre-war period, thus allaying the worry that the shifts in the spatial margins of integration and specialization would have been substantially different across different routes even in the absence of the trade shock caused by the civil war in Cˆote d’Ivoire. The panel data allow us to difference out the timeinvariant characteristics using fixed effects, thus addressing the concern that differences in 4For discussions on the double counting problem, see Redding and Turner (2015) and Donaldson (2015).

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hypothetical situation where the public input provided is of such high quality that it poses a negligible obstacle to the firm’s operations, and the firm’s profit in reality, given the actual quality of public input provided. We show in the Appendix that _Rij_ can be interpreted as the _shadow price_ of shortcomings in the public input _B j_ .

The core predictions of the model (see the Appendix) are that better performing firms (faster growing, higher productivity, etc.)

- ∗

- • spend more on mitigation, _Gij_ (e.g., are more likely to have a generator; are more likely to pay bribes);

- report better public input services _Eij_<sup>∗</sup> in cases where the input service is not a function of firm-level productivity (e.g., are more likely to report fewer delays at customs);

- report higher or lower public input services _Eij_<sup>∗</sup> in cases where the input service is a positive function of firm-level productivity (e.g., outcome depends on the offsetting effects of a higher number of inspections and greater expenditure on bribes);

- report higher costs of public input constraints, _MRCij_<sup>∗</sup> .

# **3. Mapping the framework to the data**

In this section, we show how the framework is matched with the data in the Enterprise Surveys. We begin by identifying a number of proxy variables for unobserved firm productivity and firm growth. We then summarize the variables that are proxies for the reported costs or shadow prices of constraints, _Rij_ , mitigation costs _Gij_ * , the flow of public input services _Eij_ * and the shared business environment _B j_ .

# _Performance variables_

We define the following measures of firm performance that are available in the Enterprise Surveys.

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**Table 3. Direct and indirect exporters**

||Direct<br>Only|Indirect<br>Only|Both Directly<br>and Indirectly|Total<br>Exporters|Total Firms|
|---|---|---|---|---|---|
|2020|18|6|2|27|198|
|2016|25|4|1|30|198|
|2013|18|7|5|30|198|

Notes: Sample is restricted to the 2013-2016-2020 panel and excludes firms missing information on number of employees. The above table reports the number of firms within each survey round that export (directly or indirectly). Firms exporting directly are those that sell to other countries without any intermediary. Firms exporting indirectly are those which sell to a wholesaler or other who then resells to customers in other countries. Source: Authors’ elaboration using Enterprise Survey for Egypt.

**Table 4. Simulated Effects of an International Price Increase**

|Groups|No. of<br>Firms|Average Firm-<br>level<br>Employment<br>Change|Total<br>Employment<br>Change|Average Percent<br>Employment<br>Change|
|---|---|---|---|---|
|Always exporters|46|13.960|642.169|0.067|
|New exporters|59|30.824|1,818.644|0.353|
|Never exporters|176|-0.052|-9.183|-0.003|

Notes: The above table reports the simulated changes to employment following a 5 percent increase in the international price. Never exporters are firms that only sold to the domestic market in periods 1 and 2. New exporters are firms that sold to the domestic market in period 1
# **Table 2. Attrition**

|||Control<br>Group|Treatme|nt|- Control|
|---|---|---|---|---|---|
||Obs|Mean|Coeff.||_p-value_|
|**Panel A. Midline Survey**||||||
|Woman did not complete midline survey|1011|0.075|-0.036|**|<br>_0.014_|
|Husband did not complete midline survey|1011|0.276|-0.022||_0.424_|
|**Panel B. Endline Survey**||||||
|Woman did not complete endline household survey|1011|0.114|0.020||_0.341_|
|Woman did not complete endline weekly survey|1011|0.112|0.039|*|_0.072_|
|Husband did not complete endline household survey|1011|0.215|-0.003||_0.897_|
|Husband did not complete endline weeklysurvey|1011|0.288|-0.012||_0.663_|

Notes _:_ Coefficients are from an OLS regression of the left-hand side variable on a treatment dummy, controlling for strata dummies. ***, **, * indicate significance at 1, 5 and 10 percent.

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exports data. We develop a new index of ―service exports sophistication‖ and examine its relation with growth.

As countries develop, they undergo structural transformation. Traditional theories have focused on growth as transition from agricultural to industrial production, with manufacturing being the prime ―engine of growth‖ (Kaldor 1966, 1967). This has led to a large body of empirical research that has focused on manufacturing export led growth and related industrial policy. This was further motivated by the growth experience of the East Asian Tigers (Rodrik, 1999, 2004; Hausmann et al., 2005; Pack et al., 2003, 2006; UNIDO 2009; Schott, Peter, 2008).

However, as per capita income increases, most countries witness a rising share of services in the total output. The exact cause of this shift and its implications for future growth is still not very well researched. The negligence of services as drivers of growth in the policy and research debate stems from the notion that services are associated with low productivity and are merely inputs in the production of goods. However, the mid 1990s saw two seemingly separate but related developments. First was the revolution in information and communication technology (ICT) and, second, rapid growth in the global forces often referred to as the 3Ts – technology, transportability, and tradability – with the advent of internet age. Both events had a profound impact on the nature, productivity, and tradability of services (Ghani and Kharas, 2010; Baumol,

> 1 The global value cross-border services exports in 2007 was $3.3 trillion, (20 percent of total world trade). However, the share of services rises to almost 50 percent if transactions are measured in terms of direct and indirect value added content—that is if measured in terms of processing of imported components into final products for export (Hubert Escaith 2008). Adding the sales of services by foreign affiliates of multinational firms, then the value of trade in services rises further. Data for fifteen
ar V[ 1 ( 17) When , equals one, both components are equally noisy. Using this definition in (16), and noting that _s = F/(NF+F),_ total expenditure, y, will be a better measure than food expenditure, _f,_ whenever The right hand side of this inequality is always greater than one, which means that it will be advantageous to use non-food expenditure information even if it is somewhat noisier than food expenditure information. This is the benefit of aggregation. The data suggest that non-food information can, in fact, be substantially noisier and still be useful. The RHS of (18) is equal to approximately four for Ecuador and five for Pakistan, using food shares of 0.60 and 0.67, respectively (see Tables 2 and 4, rows 1 and 2). In other words, as long as the relative noise of non-food expenditure is no more than four times that of food in the case of Ecuador, and no more than five times that of food in the case of Pakistan, aggregating these two components into a comprehensive measure of consumption provides a better indicator of welfare than food alone.

The preceding values assume independence across measurement errors and, of course, a positive correlation between them would diminish the advantages of aggregation. However, there are grounds for expecting less than perfect correlation. First, questions on household expenditures are often answered by different family members. In LSMS surveys interviewers are generally instructed to ask questions of those who are best placed to answer them (Grootaert, 1986). This might imply, for instance, that the questions on food expenditures are answered by women, while transport or durable purchase expenditures are described by men. Second, at least some of the non-food expenditures which can be included in the consumption aggregate consist of imputed expenditures, eg. for housing, consumer durables, or certain public services (see for example, Hentschel and Lanjouw, 1996). The errors which these components introduce
2002 2003 2004 2005 2006 2007 2008 2009 2010<br>Source: NBP.<br><!-- End of picture text -->

**Figure 8. Housing loans-to-GDP ratio (quarterly data)**

<!-- Start of picture text --> Housing loans to GDP HP trend (lambda = 400000)<br>% HP trend (lambda = 1600)<br>25<br>20<br>15<br>10<br>5<br>0<br>-5 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010<br><!-- End of picture text --> Source: authors’ calculation.

**Figure 10. Housing loans-to-GDP ratio gap (quarterly data)**

<!-- Start of picture text --> HP trend (lambda = 400000) HP trend (lambda = 1600)<br>p.p.<br>5<br>4<br>3<br>2<br>1<br>0<br>-1<br>-2<br>-3<br>-4<br>1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010<br><!-- End of picture text --> Source: authors’ calculation.

**Figure 12. Currency structure of loans for nonfinancial sector**

<!-- Start of picture text --> FX loans Zloty loans<br>%<br>100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>2002 2003 2004 2005 2006 2007 2008 2009 2010<br>Source: NBP.<br><!-- End of picture text --> 31
and training for inspectors: GDNT.

4. **_Tax_** _Accounting:-_ The design, reporting procedures, control, and information required on VAT returns: GDiNT.

- _!5 Taxpayer information: GDNT._

- l6. _"Importationst._ To plan on how to deal with VAT on imports, the development of procedures for temporary imports, instructions to importers and information and procedures for Customs staff: CGA and GDNT.

7. _Refimds:_ To plan a general approach for refunds and information required in the VAT return as well as establish procedures witlh the Treasury Department regarding payment of refunds: GODNT and MOF.

8. _Training:_ A detailed plan speci6'ing how and when trainirng for the different components should be delivered: GDNT.

Provided implementation of this plan is not inflexible, the careful plan. detailed timetable and clear specification of responsibilities increase the probability of success of the project. Comparable implementation plans, which typically **_fiII_** within the ambit of Project Implementation Plan (PIP) documents along with detailed cost estimates of project components are available in only S or 6 other technical assistance projects in the sample.

lMongolia, Fiscal Technical Assistance Project, March 16, 1998. Project ID: MN-PE-5 1855 An interesting case study of sequencing of administrative reforms _across loan operations_ in a sequence of three Structural Adjustment Credits (SACs) to Uganda (Box 7). Starting with high 15
consumption derived from these data frequently exclude large, once-in-a-lifetime, expenditures such as weddings and funerals as they tend to distort rankings of individuals, if not properly annuitized over the lifespan of the individual (Deaton and Zaidi, 2002).

A related concern with GDP is that despite significant efforts to establish international standards for the compilation of national accounts, guided by the UN Statistical Division’s System of National Accounts (SNA), there remain substantial heterogeneity in methods and standards across countries. This heterogeneity has recently been particularly pronounced in SubSaharan Africa, where several countries have revised their national accounts estimates to incorporate new methods and data sources in efforts to better capture more economic sectors and include emerging economic activities that were not previously captured. These methodological revisions to national accounts can produce significant breaks in comparability. For example, in 2017, Senegal’s GDP increased by 29 percent when it changed its base year from 1999 to 2014. In 2014, Nigeria’s GDP nearly doubled when it rebased from 1990 to 2010 (Angrist et al., forthcoming). Similar revisions of more than 20 percent occurred in Ghana, Kenya, Senegal, and Zimbabwe (see Kouame et al., 2019). In contrast to estimates from household surveys, the common practice is to revise the entire national accounts series, improving comparability over time within each country.<sup>19</sup> Of potentially more consequence to cross-country comparability of GDP is the shifting of profits from one country to another by multi-national corporations. Paul Krugman coined the term _leprechaun economics_ in 2015, when Ireland reported a 26 percent increase in GDP, which was mostly the result of an accounting maneuver by Apple to shift assets to Ireland on paper. This foreign direct investment in Ireland did not improve the well-being of the Irish in any meaningful way, nor did it increase economic activity, but was simply a tax-avoidance measure that resulted in distorting economic growth as measured by GDP. Damgaard et al. (2019) estimate that up to 40 percent of global
in response to fluctuations in GDP, individual migration records are grouped by year and destination country and combined to create a count of the number of migrants to each destination country annually between 1992 and 2009. Table 1 displays the top twenty OFW destinations averaged over the sample period, along with their average annual flow. Saudi Arabia is the most common destination, accounting for 33% of new hires. It also shows the average monthly wage in US dollars by destination, showing wide differences in the wages Filipinos earn in different locations. Since the micro data contain a few outliers on wages, we trim at the 1<sup>st</sup> and 99<sup>th</sup> percentiles before taking means.

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