rafmacalaba/data-use-mentions-extended huggingface dataset:
government and private purchases separately using the TiVA data, we confirm the finding that countries with more protectionist procurement laws import less in both public and private markets.

To address some of the potential biases in our cross-country analysis, we adopt a second empirical approach based on a gravity equation for bilateral flows in government procurement, similar to Mulabdic and Rotunno (2022). This approach accounts for standard bilateral determinants of trade costs, such as distance, contiguity, and colonial history, as well as time-varying fixed effects specific to the exporters and to the importers, which absorb the influence of multilateral resistance terms and other country-specific determinants of trade (Head and Mayer 2014). We identify the impact of our country-level measures of protectionism on bilateral imports by interacting them with an indicator for domestic trade. Specifically, we examine whether protectionist measures lead governments, firms and households to buy relatively more from domestic suppliers than from foreign ones – an effect on the so-called “border effect” in gravity models (McCallum 1995).

The gravity estimates confirm the suggestive evidence from the cross-country regressions. The interaction coefficient is positive indicating that the difference between domestic and international trade is larger in countries with protectionist procurement laws. This result is driven by the presence of preferential treatment provisions. For countries that give preferential treatment to domestic bidders, the estimates suggest that domestic purchases are around 16 times bigger on average than international ones, whereas for importers without a preferential treatment clause, domestic purchases are 7 times bigger than international ones.

Industry-level results suggest that the negative relationship between trade and protectionism in government procurement affects industries differently. The correlation is more precisely estimated in the primary and manufacturing sectors than in the services. Using data from the international input-output tables from TiVA, we further find that the negative association between trade and protectionism in government procurement concerns public and private purchases in qualitatively similar ways. This finding corroborates our initial hypothesis that protectionism in government procurement can extend beyond the conduct of procurement auctions and affect the sourcing decisions of private firms as well (notably
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, Direct search, Search through the internet, Search answering job advertisements, Search through informal network or friends and relatives; Type of contract: Unlimited, Seasonal; Tax type: no taxes, don’t know whether paid taxes on his/her job; Training type: Apprenticeship, In new technologies, Other; Frms’ size: 5 or less, 5 trough 9, 10 trough 19, 2 or plus._ _Source: own elaboration on the ILO School-to-work transition survey of Azerbaijan._ 28
has an elasticity close to unity. However, once you include the time dimension, the relationship becomes weaker with elasticities smaller than one.

Pakes and Griliches (1980), Hall et al. (1984) and Hall et al. (1986)were the first to study the relationship between patents and R&D, focusing on the time dependence between these variables at the firm level. A common result in these studies is that the impact of R&D has a "U" shape: R&D invested during the first and the last years tend to have a positive and significant impact on firm patenting, but the expenditure incurred between these years seems to have little effect. The estimation of Pakes and Griliches (1980), performed with a linear model with data from 121 U.S. companies, indicates that the elasticity of the sum of contemporaneous and lagged R&D is significant and close to 0.6. Hall et al. (1984) and Hall et al. (1986) estimate the relationship between patents and R&D using Poisson and Negative Binomial models for a broader group of U.S. firms. They find that when controlling for fixed effects the elasticity of the sum of contemporaneous and lagged R&D is smaller than that found by Pakes and Griliches (1980), with estimates between 0.3 and 0.5. Jaffe (1986), unlike previous work, used only current R&D expenditure in the knowledge production function, as well as technological spillovers. Jaffe’s estimated elasticity of patents with respect to R&D, controlling for fixed effects, is equal to 0.4, but the effect rises with the R&D of other firms.

Blundell et al. (1995) developed an alternative GMM estimator in which the unobservable fixed effect of firms is approximated by the history of patents prior to the period of the estimation sample, namely a pre-sample mean estimator. Blundell et al. (2002) used this estimator
value of UGX 1400 in cash, and all subjects should be willing to buy the card for a price below 1400 but not for a price above; in fact, the authors use this as a rationality test when comparing different elicitation methods. In general, however, a problem for the measurement of subjective preferences is that the researcher cannot distinguish between NSB that is the expression of a very strong preference for one of the options, and NSB that is the result of an error.

A survey of 54 published risk elicitation studies employing MPL designs found that 17.1 percent of observations included inconsistencies in the form of MSB or subjects picking dominated options (Filippin and Crosetto, 2016; Crosetto and Filippin, 2016).<sup>10</sup> In WTP elicitation where the trade is realized later, subjects often ex post decline the agreed-upon price: Maffioli et al. (2020) report a high rate of reneging on MPL outcomes,

> 10A similar systematic review of the MPL for WTP literature is not available. Of the papers we surveyed, a subset of which are shown in Appendix B, MSB was rarely reported and was often suppressed by instrument design, as we discuss in greater detail in Section 2.3. NSB was more commonly reported, and ranged from 1-2 percent to 74 percent of subjects.

8
of the terms-of-trade theory across a number of different empirical contexts. They examine tariff variation for a number of WTO _non-member_ countries and conclude that market power helps to explain applied tariffs for countries unconstrained by trade agreements.<sup>16</sup> An alternative theoretical explanation for cross-sectoral variation in applied tariffs is political economy, for which the Grossman and Helpman (1994) structural model of lobbying and endogenous import protection provides a rich set of empirically testable preduictions. However, much of the literature seeking to empirically test the Grossman-Helpman model has focused on the sector-level variation in _non-tariff_ policies - of the sort that we introduce and describe in Section 3.<sup>17</sup>

> 15Some countries have used this flexibility to make relatively high frequency - e.g., weekly, monthly, etc. - changes within years (and thus potentially not captured in the annual data) to applied MFN tariffs on agricultural products, perhaps in light of both political economy concerns and the uncertainty of yields due to weather-related shocks and growing seasons. Recent WTO disputes challenging such policies imposed by Chile and Peru are described in Bagwell and Sykes (2005a) and Saggi and Wu (2016), respectively. On agricultural tariffs more generally, see Hoekman, Ng, and Olarreaga (2002, 2004).

> 16Other research exploring the empirical relevance of the terms-of-trade theory for negotiated trade agreements using applied and bound tariffs includes Bagwell and Staiger (2011), Ludema and Mayda (2013), Nicita, Olarreaga, and Silva (2014), and Beshkar, Bond and Rho (2015). Bown (2015) provides both a survey of these papers and an empirical assessment of some of their implications for the applied and bound tariffs of developing countries.

> 17This literature is surveyed in McLaren (forthcoming). Exceptions for research providing estimates of the Grossman-Helpman model on _tariff_ policies include Mitra, Thomakos, and Ulubasoglu (2002) for Turkey, Bown and Tovar (2011) for India, and Gawande, Krisha, and
2015), _kibarua_ is used for most forms of manual casual labor, and often has a negative connotation in Tanzania.

# 4.2.4. Time diaries

The fourth approach to measure hours worked in paid and unpaid economic activities is a time diary, an approach that was initially developed to measure time use within a reference period (typically the last 24 hours) but can also be used to identify productive activities. Time diaries have several advantages. First, time diaries are more accurate and suffer less from recall bias than stylized questions (Bonke, 2005; Kan & Pudney, 2008). Second, they provide an exhaustive list of all activities undertaken in the last 24 hours (Seymour et al., 2017). Third, given the format of a time diary, enumerators can easily verify that the sum of all activities equals 24 hours, which may reduce measurement error. Fourth, they offer the potential to capture simultaneous activities (for example, women caring for children and working on an agricultural plot at the same time) (Grosh & Glewwe, 2000; ILO, 2018e).

Time diaries increase, however, the complexity and duration on the interview, have high operational costs, and might yield inaccurate response due to respondents’ memory loss and illiteracy. The United Nations Statistics Division (UNSD) Time Use Data Portal<sup>16</sup> identified several methodological issues regarding collecting accurate time use data that are not yet settled such as (1) whether a time diary should be administered to all household member or only to (randomly) selected household members; (2) whether proxy‐reporting of time use is acceptable; (3) how to deal with variation in time use across the week (e.g. interviews on Tuesdays versus on Sundays) and (4) whether the definition of time is context and cultural

> 15 The enumerator manual defines _ganyu_ labor as _“short term labour hired on a daily or other short‐term basis. Most commonly
factors such as gender, income level, location (urban/rural), education level, price of mobile data packages, price of internet-enabled phones, and so on; and (3) perspective factors shaped by the institutional environment, culture, and network effects.

# **3. Data**

In 2017–18, ICT policy think tanks in the Global South, including RIA (Research ICT Africa), LIRNEasia (Learning Initiative for Network Economies in Asia), and DIRSI (el Diálogo Regional sobre la Sociedad de la Información / Regional Dialogue on the Information Society), coordinated a global initiative, conducting household surveys to collect information about ICT access and usage at household and individual levels. Ten African countries (Ghana, Kenya, Lesotho, Mozambique, Nigeria, Rwanda, Senegal, South Africa, Tanzania, and Uganda), six Asian<sup>8</sup> countries (India, Sri Lanka, Pakistan, Bangladesh, Nepal, and Cambodia), and six Latin American countries (Argentina, Colombia, Ecuador, Guatemala, Paraguay, and Peru) were covered (see Annex 1 for more survey methodology details).

Going beyond other microlevel data sets such as the Living Standards Measurement Study and the Global Findex database, this data set collects rich, in-depth information on ICT access and usage from the demand side. It provides valuable information on mobile phone ownership and usage, internet access and usage, social media activities, digital finance, participation in the gig/sharing economy, as well as the reasons for engaging in those ICT-enabled activities. The surveys are nationally representative, and the data can be disaggregated on the basis of gender, age, location (urban or rural), and income level.

Unfortunately, there is no direct question on mobile internet adoption in the surveys. However, such usage can be captured through combining information gained through multiple survey questions regarding whether respondents: (1) have used the internet or not, (2) own a mobile phone,
very high for these countries (0.99 and 0.96 respectively), we exploit the ADB tax data to extend the WDI series using the growth rates. This is the case for 2017 in Bhutan, as well as for years 1991-1996 and 2012-2017 in Pakistan. In the case of Bangladesh and Nepal, we rely on the full tax series from the ADB, which cover more years than the WDI. For India, we compute consolidated tax revenue from IMF and Reserve Bank of India data. Data on government total expenditure measured as a percentage of GDP is taken from the IMF for all countries, given that the WDI report only central government final consumption. Finally, values for the share of current and capital expenditure in total expenditure come from the ADB. Detailed sources and time coverage for countries are provided in Table A2 in the Appendix.

# **4. Cyclicality of fiscal policy**

The cyclicality of government spending is typically defined in terms of how spending moves relative to the output gap. If government spending decreases with a positive output gap, i.e. when output is above its potential, it is countercyclical. If the spending increases instead, it is procyclical. If public spending increases more than proportional with GDP, there is a so-called “voracity” effect (Tornell and Lane 1999). For taxes, it is important to differentiate between tax rates and tax revenue. Since the tax rate is an instrument rather than an outcome, the former is the correct variable to study instrument cyclicality. For many countries, including those in South Asia, systematic data on tax rates is not available, however. The inflation tax has been proposed as a viable alternative (Phelps 1973; Chari and Kehoe 1999; Calvo and Végh 1999; Kaminsky, Reinhart and Végh 2004).<sup>5</sup> The response of the tax revenue to changes in GDP, on the other hand, is an outcome and depends on the tax buoyancy, which for clarity is referred to
14 Even competitive elections can be influenced by violence, allegations of fraud, contestation of results, and are typically dominated by clientelistic practices of winning political support through promises of provision of private or group benefits (Keefer and Khemani, 2004). Such clientelist practices can have deep roots in historical institutions, as discussed in the previous section. Furthermore, there is also substantial variation in performance in growth and human development across autocratic regimes, which to a large extent overlaps the variation among democratic regimes (Besley and Kudamatsu, 2007). Autocratic and intermediate regimes can still be under political pressures to deliver on development to middle and poorer groups—as exemplified by countries such as Ethiopia and Rwanda that fall into this intermediate category.

A growing body of evidence on citizen participation in elections and other political processes in Africa is being generated through the use of the Afrobarometer surveys.<sup>9</sup> Broad arguments are made on the basis of this data that citizen political behavior in Africa cannot be reduced only to responding to clientelist appeals and ethnic identity, but that performance of governments in managing the economy and delivering development matters as well (see for example, Bratton et al, 2011, and Young, 2009). Average self-reported voter-turnout in the 2008 round of the Afrobarometer survey for both “full democracies” and even intermediate cases, as rated by Polity IV, is higher than 70 percent (see Table 1, below). Such widespread intentions to participate in political processes likely encompass a variety of citizens, some of whom demand broad public services and economic development. In section 3 below we report evidence from experiments undertaken by civil society organizations in Africa to shift citizen demands away from clientelism and towards broad public goods.

# _2.4  Accountability and civil society organization_

There also appears to be a large shift in Africa in organization among citizens. Village-level group formation in Africa increased dramatically over the 1990s when participatory approaches were emphasized in international development paradigms, promoted through aid, and adopted deliberately by country governments to
, “Cities and development,” _Journal of Regional Science_ , 2010, _50_ (1), 515–540. , Adam Storeygard, and Uwe Deichmann, “Has climate change driven urbanization in Africa?,” _Journal of Development Economics_ , 2017, _124_ , 60–82.

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- ILO, “Labor Force Statistics,” Geneva: International Labor Organization 2022.

- Islam, Asif, Remi Jedwab, Paul Romer, and Daniel Pereira, “Returns to Experience and the Sectoral and Spatial Allocation of Labor,” Mimeo 2019.

- Jedwab, Remi, “Urbanization without Industrialization: Evidence from Consumption Cities in Africa,” 2013. Unpublished manuscript, GWU.

- and Dietrich Vollrath, “Urbanization without growth in historical perspective,” _Explorations in_

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- and , “The urban mortality transition and poor-country urbanization,” _American Economic_

- _Journal: Macroeconomics_ , 2019, _11_ (1), 223–75.

- , Asif Islam, Paul Romer, and Robert Samaniego, “Human Capital Accumulation at Work: Estimates for the World and Implications for Development,” Working Papers 2020-3, The George Washington University, Institute for International Economic Policy March 2020.

- , Daniel Pereira, and Mark Roberts, “Cities of workers, children or seniors? Stylized facts and possible implications for growth in a global sample of cities,” _Regional Science and Urban Economics_ , 2021, _87_ , 103610.

- , Federico Haslop, Roman David Zarate, Takaaki Masaki, and Carlos Rodriguez, “The Effects of Water Recessions: Evidence from the Lake Chad Post-1945,” _Mimeo, GWU_ , 2021.

- , Jason Barr, and Jan Brueckner, “Cities without
simulations focus on the direct revenue gains which mostly accrue to MNE residence countries, i.e. high-income countries.<sup>25</sup> Instead, we focus on the indirect effects of reduced tax competition, which allows for ETRs to be set at the global minimum tax rate in all countries. We also observe the exact reported profits and ETRs of individual firms and can provide specific estimates of revenue gains from the application of a minimum tax. This contrasts with previous work that relies on aggregate data for residence-source-country pairs, drawn from the Country-by-Country reporting (CbCR) data, and macro estimates of ETRs. These data suffer from several measurement issues (discussed in Cobham et al. 2021 and OECD 2020) and are incomplete for developing countries. Due to the incomplete and confidential nature of the data, the above studies only publish countryspecific estimates of revenue gains for countries appearing in the CbCr data, and group other countries into income-level groups.<sup>26</sup>

# **6 Conclusion**

In this paper, we construct corporate effective tax rates by firm size in a consistent manner across 13 countries, using tax return data. We uncover large economy-wide gaps between effective and statutory tax rates, a rise in ETRs with firm size until the 85-90th percentile of the size distribution, and a fall in ETRs for the largest firms in most countries. The planned global minimum tax provides an opportunity for countries to raise ETRs in a coordinated manner to recover lost tax revenue.

The fact that the top firms currently face lower tax burdens could lead to an allocation of resources away from medium firms, key engines of growth and employment. Further research is needed to examine the efficiency costs of tax expenditures, especially those benefiting the largest firms, and compare them to the intended societal benefits. Another open question is the extent to which tax expenditures are intentionally targeted at large firms or whether large firms are better informed and more skilled in taking up tax expenditures offered to all firms. Future research could
theories and at least 145 proposed regressors as proxies. We turn to the standard growth literature to guide us in this regard and focus on a subset of well accepted growth determinants in our analysis (see annex tables and data description for details).

The baseline empirical growth model consists, in addition to the variable of interest, of four determinants of economic growth - initial income level, rates of physical and human capital accumulation, trade openness and institutional quality. We use data on income per capita from WDI. To account for differences in human capital accumulation we use latest available data on years of schooling from Barro and Lee (2010).<sup>11</sup> We use M2 (as percent of GDP) as a proxy for financial development from WDI. Finally, we use a measure of Rule of Law from World Governance indicators.<sup>12</sup> We use dynamic panel regressions based on three year panel data for each country. The regression specification is the following: where is the natural logarithm of GDP per capita, is the level of GDP per capita at the beginning of each three year period, is the dynamic service export sophistication measure, is the set of relevant control variables for growth determinants, represents time dummies, stands for country fixed effects and is the error term.

Results of fixed effect and System GMM regression for three year periods are presented in Table 3.<sup>13</sup> The convergence effect, human capital, and service EXPY seem to matter for growth only in the last time period (2005-07). We add various controls for growth to our baseline regression for the period. Introduction of the controls does not change the significance of the co-efficient on _SE_ .<sup>14</sup>

> 11 Neoclassical growth model, since the seminal work of Lucas (1988), the concept of capital since is usually broadened from physical capital to include human capital.

> 12 For robustness checks we also tried institutionalized democracy measure