rafmacalaba/data-use-mentions-extended huggingface dataset:
spending multipliers in those countries where high-frequency macroeconomic and fiscal data are available.<sup>4</sup> A third strand of the literature has proposed a variety of creative instruments to isolate a plausibly exogenous component of changes in government spending, primarily focusing on subnational government spending in the United States. Papers such as Cohen, Covall and Malloy (2010) and Fishback and Kachanovskaya (2010) have exploited political determinants of federal transfers to states, while Chodorow-Reich, Feiveson, Liscow and Woolston (2011), Serrato and Wingender (2011), and Wilson (2011) emphasize particular institutional features driving federal-state transfers that are likely to be orthogonal to state-level economic activity. Clemens and Miran (2010) and Shoag (2011) study fluctuations in state-level spending driven by variations in the stringency of balanced-budget rules, and pension fund windfalls, respectively.

Finally, two important caveats about these results are worth noting at the outset. The first is that the empirical spending multipliers I estimate are by no means deep structural parameters. As is well-known from a large body of theoretical work, the short-run effects of government spending on output depend on a host of factors including technology, preferences, the nature of spending, the associated burden of current and future taxes, the stance of monetary policy, and a range of other country- and episode-specific characteristics. In light of this, the multipliers that I estimate are best understood as a description of the short-run average empirical relationship between changes in a plausibly predetermined component of government spending and changes in output. This caveat is of course shared with the bulk of the existing empirical literature on the short-run effects of government spending. The second caveat is that, while my identification strategy relies on lending by official creditors, which frequently is a vehicle for foreign aid delivery, the resulting evidence should not be interpreted as contributing to the long-standing empirical debate on the growth effects of aid. In contrast with the aid-growth literature, which has primarily been concerned with the medium- to longrun effects of aid on
Note that since inequalities �7� and �8� use the same poverty line, we can use Proposition 1 to test the comparability of poverty rates derived from them. Indeed, inequalities �7� and �8� satisfy the conditions of Proposition 1. First, the NISR (2016) approach is based on nominal household expenditure, which is constructed the same way in EICV3 and EICV4. Second, the COLI used for deflating consumption ������� expenditure in EICV3 (π����� ) is fully consistent with the index used for deflating consumption ������� expenditure in EICV4 (π����� ), i.e., the base month, the source price data, and the budget weights for the two indices are the same. Therefore, poverty rates estimated from inequalities �7� and �8� satisfy the necessary conditions of comparability, corroborating that the official poverty trend, where headcount poverty declined from 46 percent to 39 percent between EICV3 and EICV4, is credible.

# III.3. Establishing robustness of the declining poverty trend

To substantiate the credibility of the poverty trend based on the NISR (2016) approach, they conducted further analysis using a survey-to-survey imputation method (S2S). When consumption data from two rounds of a household survey are deemed non-comparable, the survey-to-survey imputation approach, as in Christiaensen et al. (2012), is often used to restore the comparability of consumption data and poverty rates. The methodology creates consumption models in a household survey where both consumption and non-consumption data are reliable, and then imputes household consumption expenditures using the models in a different survey where only non-consumption data are reliable. The consumption models use household and individual characteristics such as educational attainment and employment status of household members, household composition and the like. This S2S approach is useful if price adjustments or poverty lines are not comparable over time, but non-consumption data are comparable. Given some key assumptions are satisfied, Christiansen et al
Zeitlin (2014) find that the introduction of electronic machines to record sales transactions of firms improved tax compliance and revenue mobilization in Ethiopia and Rwanda, respectively. Yilmaz and Coolidge (2013) demonstrate that e-filing significantly reduced tax compliance costs for firms in South Africa, but not in Ukraine or Nepal. However, these studies are country specific or compare a few cases at best. Our paper is the first to systematically examine the effects of e-filing cross-nationally and shows that government investments in e-filing systems could substantially increase tax revenue and improve the business climate by encouraging and facilitating tax compliance.<sup>4</sup> Empirical studies of the impact of e-procurement are country-specific or limited to small samples of relatively homogenous cases. For example, Nepelski (2006), using data from several European countries, finds that e-procurement increases the amount of market transactions and improves supply chain management. Lewis-Faupel et al. (2014) find that e-procurement in India and Indonesia improved the quality of public infrastructure projects through the increase in competition among bidders. In this paper, we analyze the effects of e-procurement implementation on public procurement competitiveness for a large sample of low- and middle-income countries.

This paper is also related to the literature on the impact of ICT on corruption. Muralidharan et al. (2014) and Barnwal (2014) show that biometric registration, authentication, and payment systems significantly reduced corruption and inefficiencies in government workfare and fuel subsidy programs in India by automating tasks and improving monitoring. Banerjee et al. (2014), using the evidence from a large field experiment, conclude that e-government reduces fiscal leakages, but does not necessarily improve outcomes of public programs. This paper, by contrast, finds only weak evidence of a reduction in petty corruption attributable to e-government adoption.

The reminder of the paper is structured as follows. The next section describes the data sources and variables. Section 3 outlines the empirical strategy. Section 4 discusses the results and their implications and presents the robustness checks. And Section 5 concludes.

# *
include displaced families and households in departmental capitals and municipalities which either became able to offer the required services or with services accessible in nearby towns. Most recently, during 2007, the program expanded to municipalities with more than 100,000 inhabitants to include other deprived urban areas. The program now covers nearly 2.8 million participating households in 1,093 municipalities, representing almost 65 percent of the target population (Acción Social, 2010b; Attanasio et al., 2009).

An early evaluation of FA demonstrated positive effects on short-term outcomes such as household consumption and children‘s school participation and nutrition status. Indeed, within the first two years of program implementation, household consumption increased by 13-15 percent, school enrollment rates increased by around 5 to7 and 2 percentage points for children in secondary and primary schools, respectively, child labor participation fell by around 10 to 12 percentage points, and health and nutrition outcomes such as morbidity, immunization and anthropometrics also improved (Attanasio et al., 2005, 2006 and 2009; Attanasio and Mesnard, 2005).

# **3. Data**

This paper uses four sources of data (a household survey, a census of the poor, and a database with administrative records of the program) to construct two samples of participant and nonparticipant children of the program FA for the two research strategies. The first approach employs matching methods and household survey data collected for the short-term impact evaluation of FA. This survey is part of an effort to collect longitudinal data from a stratified random sample of eligible families in both treatment municipalities and matched control municipalities. The survey is a standard multi-topic household survey that includes questions on demographics, household structure, education, health, consumption, employment, anthropometry, housing characteristics, shocks, and community education and health facilities. The baseline survey was carried out between June and October 2002.<sup>10</sup>

> 10 Two follow-up surveys revisited the same households in 2003 and 2005.

11
law to obey their husbands. The overlap between the Global Findex and Gallup data and the WBL database is for up to 90 developing countries.

Second, we use data from the OECD Gender, Institutions and Development (GID) database to test whether certain manifestations of gender norms affect the use of financial services. GID indicators attempt to measure the actual situation of women.<sup>14</sup> We use the following two continuous variables measuring (i) the prevalence of early marriage and (ii) violence against women.<sup>15</sup> These variables range from zero to one, with higher values indicating higher prevalence, that is, a more restrictive environment for women. OECD GID data are available for 104 mostly developing countries; the database does not cover high income countries or countries in Eastern Europe. The overlap between the Global Findex and Gallup data and the OECD GID database is up to 86 developing countries.

Table 2 presents summary statistics of these variables. In general, men and women are treated equally by the law in about 80 percent of the countries in our sample for any one of the questions we consider, with the exception that in 11 percent of countries, women are required by law to obey their husbands. The default marital property regime is separation in 35 percent of countries. On average, 21 percent of women enter into an early marriage, and the violence against women variable falls slightly to the right (56 percent) of the midpoint of the no violence to violence spectrum. Appendix B provides more detailed variable descriptions and sources.

# **4. Empirical Methodology**

We next turn to multivariate regression analysis to explore whether gender differences in the use of financial services shown in summary statistics are robust after controlling for

> 14 For details on methodology of OECD GID-DB see http://genderindex.org/sites/default/files/GID_variables.pdf. 15 The OECD GID database contains a total of 12 indicators. However, the other variables
Evidence from China." _J. of Corporate Finance_ , 42, 460-480.

- Dethier, J.J.; M. Hirn, S. Straub. 2010. "Explaining Enterprise Performance in Developing Countries with Business Climate Survey Data." _World Bank Research Observer_ , 258-309.

- Djankov, Simeon, Rafael La Porta, Florencio Lopez-De-Silanes, and Andrei Shleifer, 2002. "The Regulation of Entry." _Quarterly Journal of Economics_ , 177(1), 1-37.

- Djankov, Simeon, Rafael La Porta, Florencio Lopez-De-Silanes, and Andrei Shleifer, 2003. "Courts," _Quarterly Journal of Economics_ , 118(2), 453-517.

- Djankov, Simeon, Carelee McLiesh, and Andrei Shleifer, 2007. "Private credit in 129 countries," _Journal of Financial Economics_ , 84(2), 299-329.

- Djankov, Simeon, Rafael La Porta, Florencio Lopez-de-Silanes, and Andrei Shleifer, 2008. "The Law and Economics of Self-Dealing," _Journal of Financial Economics_ 88, 430-465-329.

- Djankov, S.; T. Ganser; C. Mcliesh; R. Ramalhoand, A. Shleifer. 2010. "The Effect of Corporate Taxes on Investment and Entrepreneurship." _American Econ. J.: Macroeconomics_ , 2(3), 31-64.

- Djankov, S,; E. Miguel; Y. Qian; G. Roland and E. Zhuravskaya. 2005. "Who Are Russia's Entrepreneurs?" _Journal of the European Economic Association_ , 3(2‐3), 587-97.

- Djankov, Simeon; Yingyi Qian; Gérard Roland and Ekaterina Zhuravskaya. 2006. "Who Are China's Entrepreneurs?" _The American Economic Review_ 96(2), 348-52.

- Dollar, D.; M. Hallward‐Driemeier, T. Mengistae. 2005. "Investment Climate and Firm Performance in Developing Economies." _Economic Development and Cultural Change_ , 54(1), 1-31.

- Dollar, David, R. Fisman, R. Gatti
/u> of professionally-managed firms to changes in TFP with an elasticity _ν ≡ θ_ ( _σ−_ 1)<sup>.Thismotivatesthe</sup> following two-step method to map changes in trust to changes in TFP. First, we relate changes in regional trust to changes in the share of professionally-managed firms through the iso-elastic relationship 1 + _λP_ = _α_ (1 + Trust)<sup>_β_</sup> . We estimate the elasticity _β_ via OLS. Second, we combine this with the result in Proposition � _βν_ � 1 to compute changes in TFP resulting from a change in trust as _TFP_<sup>�</sup> = 1 + Trust , where 1 + Trust is a gross percentage change in 1 + Trust. We also perform the same decomposition using the rule of law index � at the country-level, where we posit a semi-elastic relationship of the form 1 + _λP_ = exp( _β_<sup> ̃</sup> Rule of Law) since our rule of law measure takes values less than zero. To obtain a value for _ν_ , we calibrate _σ_ and _θ_ to existing values from the literature and provide results for a range of parameters. In particular, based on the evidence on the firm size distribution cited in Chaney (2008) we use values of _θ, σ_ that match the sales-rank slope of 2. Since this only identifies the ratio, we provide TFP statistics for a range of _θ_ values and compute the _σ_ consistent with this sales-rank slope.<sup>25</sup> Table VI provides estimates of the elasticity _β_ . Consistent with our prior results, we provide results for the full sample as well as separate elasticities for low and high rule of law countries. Column (1) shows that a 10% increase in 1+Trust is associated with a 3.7% increase in 1+ _λP_ . However, columns (2) and (3) show significant heterogeneity across countries with a 4.9% (1
across four types of country GVC participation: commodities, limited manufacturing, advanced manufacturing and services, and innovative activities.

# **3.2 Methodology**

# _Estimation Methodology_

To use the BPS data for assessing the impact of COVID-19 on firm performance in the initial phase and the recovery phase, we estimate the following equation: where _Yict_ is one of a list of outcomes for firm _i_ in country _c_ at the time of the survey _t_ : change in total sales (in the domestic and foreign markets), an indicator of financial fragility (probability of falling into arrears), indicators for changes in employment at the intensive or extensive margin, indicators for increasing the use of digital technology and for engaging in product innovation, and an indicator for accessing public support.<sup>5</sup> The vector of controls _Xi_ includes pre-pandemic firm size categories, sector fixed effects, and an indicator for the firm being covered in the BPS panel, _πc_ designates country fixed effects, _Shockct_ captures the severity of the lockdown in the country at the time of the survey, _LR_ is an indicator for the latest survey round , and _εict_ is an independent and identically distributed error term. By including the interaction between each variable or vector of variables and _LR_ , our specification allows for changes in the coefficients between the pandemic’s initial phase (first survey round) and the recovery phase (latest survey round). Our main regressor of interest is _Engagementi_ which is one of the firm global engagement measures defined below.

To assess whether globally engaged firms experience a differential adjustment in a given outcome we estimate the margins (or marginal effects) for the measure of global engagement, keeping the distribution of firm size, sector, and country constant across the two survey rounds to ensure that our results are not driven by differences in sample composition.<sup>6</sup> For visual clarity, we show the estimated marginal effects from each regression in a figure, along with the corresponding confidence intervals at the
mainly to redistributive processes in the monetary metric of expenses, rather than to economic growth. The fact that the key driver of poverty reduction is a reshuffling of households along the distribution curve, rather than a movement of the curve itself, justifies the need for tools capable of identifying who changes their position within the income (or expenditure) scale during the period considered. Methods based on pseudo-panels allow for precisely this kind of analysis, and significantly contribute to our understanding of the relative importance of the underlying drivers of poverty dynamics. In the case of Bhutan, the results are interesting and, hopefully, useful to policy makers: education level and residence in rural areas are associated with greater overall mobility, both upward and downward, but only residence in rural areas is informative regarding the “structure” of mobility. Families living in rural 2
In a previous paper that focused on the analysis of firm-led renegotiation (Guasch, Laffont and Straub, 2003, referred to hereinafter as GLS), we analyzed a Latin American data set from the World Bank, with 307 concession projects in the sectors of transport and water, in five countries (Argentina, Brazil, Chile, Colombia and Mexico) between 1989 and 2000. We showed that more than half of these projects were renegotiated (162 out of 307) and very fast, on average 3.5 year after the signing of the contract. The paper focused on firm-led renegotiation and built a model of renegotiation that included contract characteristics, regulatory and institutional environment, as well as external shocks. The empirical analysis there confirmed most of the predictions of the model and yielded interesting policy implications, especially with respect to the importance of having a regulatory body in place at the time of awarding a concession and of choosing the appropriate regulatory regime. We showed that the mode of regulation matters and that price caps, which have been the dominant choice of policy makers in Latin America, suffer from a great fragility to shocks and trigger significant renegotiation. As a consequence, there is a growing pragmatic tendency to advocate the abandonment of price cap regulation, a synonym for the higher risk of renegotiation and higher cost of capital, and the return to an hybrid type of regulation, including some elements of rate of return (see for example Estache, Guasch and Trujillo, 2003).

The present paper complements GLS by looking at government-led renegotiations. Private sector participation has often been accompanied by sector restructuring prior to the transfer and by the implementation of a legal and regulatory framework. This is meant to protect investors from arbitrary and politically motivated intervention from the government, to protect users from the abuse of the monopoly or dominant position of the new private operators, and also to protect the competitive new entrants from a dominant incumbent operator. Quite often, the required and necessary investments are highly specific “sunk” type costs that cannot easily be
October 2013. Field trips were made to Jaipur, as well as to districts where the RRLP program was being actively scaled up during the months of our study: Dausa, Tonk, Alwar and Dungarpur.<sup>18</sup> A series of in-depth individual interviews were conducted with various stakeholders including the facilitators from four organizations, facilitators who were working for the RRLP under direct contracts, women participating in SHGs, and RRLP project staff who were involved in all aspects of the program’s design. At RRLP headquarters, we interviewed the project director, the deputy director, the monitoring and evaluation specialist, the Resource Block coordinator and the Intensive Block coordinator. Within the Intensive Blocks, we interviewed the senior staff of the NGOs who were present in the district offices. Within the Resource Blocks, we interviewed the most senior project officer in the state of Rajasthan, who was in charge of coordinating SERP activities along with the government.<sup>19</sup> Three facilitators at each NGO were randomly selected from project rosters to be privately interviewed. All interviews were conducted in a secluded area, respondents were assured that all information would remain confidential, and they had the opportunity to terminate the interview at any time. The open-ended interviews were subsequently recorded (in audio files), then transcribed and translated.

The insights achieved during the qualitative analysis were then used to design a quantitative survey of facilitators.<sup>20</sup> In May 2014, we interviewed 349 RRLP facilitators from the same four districts studied in the qualitative phase. Within the blocks we aimed to interview _all_ active PRPs in the month of our survey. Interviews were conducted by the Indian Marketing Research Bureau (IMRB) at the RRLP field offices. The study was intentionally designed as a comparison of CRPs from SERP versus local NGOs, (PRADAN, PEDO and federations of SHGs).

In Dungarpur, we interviewed 120 CRPs from PEDO. In the three districts of Dausa, Alwar and Dholpur, we interviewed CRPs
reviewed the information, and provided important insights to ensure the accuracy of the information. Teams provided expert knowledge on:

- Corporate legal structures/forms

- Business registry and statistical institute databases

- Government participation in key enabling sectors

The information from World Bank projects, external sources beyond ORBIS, and those provided by country teams greatly improves upon the coverage of any existing BOS database. (The rest of the paper will refer to information used to complement ORBIS data as the _‘SOE Supplementary Database.’)_ With the supplementary database, we were able to (i) identify entities in ORBIS that have links to the state even though the ORBIS ownership files do not identify that link, (ii) substantially expand coverage of financial variables, and (iii) add variables included in the Governance module of the BOS Global Database, such as legal entity type, administrative ministry line, government participation, among others. As shown in Figure 3 using only ORBIS leads to an underestimation of the state footprint across most countries. This is due to at least two issues: (i) _measurement error_ (misclassification of firms with state participation as private firms such as the case of the state airline in Angola), and (ii) _omission error_ given that some firms are not captured in ORBIS. In particular, the multi-phased methodological approach and supplementary databases allowed to compare the results from the GUO variable in ORBIS against the country counterfactual to evidence that there is a substantial number of firms incorrectly classified as privately owned (Figure 2).

> 26 They also collect information from global providers such as MarketLine, Euromonitor International Ltd., Oxford Economics, SBI Securities, etc.

14