rafmacalaba/data-use-mentions-extended huggingface dataset:
# **1. Introduction**

Entrepreneurship is essential for the continued dynamism of the modern market economy and a higher entry rate of new businesses can foster competition and innovation (Klapper, et al., 2006; Ciccone and Papaioannou, 2007; Aghion, et al., 2009). To promote private sector growth, many countries have focused on simplifying the registration process, seeking to reduce the costs, days and/or procedures required to formally register a business.

A methodology for measuring the effectiveness of the regulatory framework for firm registration was developed by Djankov, La Porta, Lopez-de-Silanes, and Shleifer (2002). Since 2003, the World Bank’s annual Doing Business report has used this methodology to quantify the registration process in over 170 countries in its “Ease of Starting a Business” section.<sup>1</sup> An outstanding question, however, is whether, and to what degree, there exists an economically meaningful relationship between the costs, days and procedures to start a business and the actual number of new firms that register each year. Given the widespread recognition of the importance of business environment reforms<sup>2</sup> , it is surprising that there is little research, and no crosscountry panel analyses, on the real effect of these regulatory reforms. Our paper aims to address this gap in the literature by examining the impact of institutional reforms on the number of new firms registered.

Understanding the regulatory environment that promotes entrepreneurship is necessary to successfully identify appropriate policies to foster entrepreneurship in local economies. In this paper we empirically investigate the relationship between the regulatory ease of registering a business and actual new business registrations. Next, we explore the magnitude of reform in

> 1 Reports are available on-line at: www.doingbusiness.org.

> 2 For instance, a 2008 report of the Multilateral Donor Committee for Enterprise Development  states, “Reforming the business environment is a priority for development agencies and governments because of the significant influence the business environment has on the
any analysis on the topic. Databases such as the WIOD or GTAP, which are widely used for general equilibrium counterfactual analysis such as the one performed here, do not contain data for the CEFTA countries. The databases generally list the CEFTA countries in regional aggregates.<sup>13</sup> Constructing a general equilibrium model of the CEFTA countries is also

> 12The agreement was originally signed in 1992 but the current members joined between 2006-207 as previous members (Poland, Hungary, Czech Republic, Slovakia, Slovenia, Romania and Bulgaria) left CEFTA once they acceded into the EU. Croatia was still a member in 2006 but left in 2013 when it joined the EU.

> 13The GTAP database only lists Albania as a separate country, while the rest are either in the “Rest of Europe” or “Rest of Eastern Europe” (for Moldova) regional aggregates. The WIOD database lists the CEFTA countries in the “Rest of the World” aggregate.

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impacts.

Likewise, with respect to the empirical literature, numerous studies have been completed—some using sophisticated large-n experimental and quasi-experimental designs—however, few have been able to link Open Data, and OGD in particular, to changes in levels of government accountability or the provision and outcomes of health and education services. Rather, the literature available focuses mainly on the effects of other types of transparency and accountability initiatives—such as community score cards, participatory budgeting, and social audits—and not OGD itself. As is the case with such granular quantitative analysis, many studies focus on particular countries and regions at particular moments in time, which again, reduces their comparability to other contexts.

# **III. CONCEPTUAL FRAMEWORK**

In an attempt to answer the question posed above, this research will evaluate four different propositions— or premises—that can be extrapolated from the literature, including previous theoretical and empirical contributions on transparency, accountability, and service delivery. As described below, this research will also test the political economy “conditions” that are necessary and/or sufficient for the purported relationships to hold—including the role played by the larger information-availability environment (i.e. “publicity” condition) and formal citizen voice (i.e. “political agency” condition) as well as government capacity (i.e. “public sector management” condition) and informal social accountability channels (i.e. “client power” condition).

> 103 C. K. Carruthers & M. H. Wanamaker, "Municipal Housekeeping: The Impact of Women's Suffrage on Public Education," Journal of Human Resources, vol 50(4) (2015) p. 837-872.

> 104 T. Fujiwara, “Voting Technology, Political Responsiveness, and Infant Health: Evidence from Brazil.” Econometrica 83 (2) (2015) p. 423–64.

> 105 M. Kudamatsu, “Has Democratization Reduced Infant Mortality in Sub-Saharan Africa? Evidence from Micro Data
economics, and finance, but on all fronts, including other business and social science topics. The earlier sections of this paper suggest that a number of research papers are in process, forthcoming, and published, and also provide suggestions for future research. We add to this list of suggestions here.

Studying the numerous policy approaches employed in the COVID-19 crisis is likely to be particularly fruitful. There were many different policy measures implemented across the world that impacted bank lending decisions, the banks themselves, and real economic outcomes. As discussed above, there is an active research agenda on these topics in the U.S., but much more can be accomplished across the world. Examining policy measures and bank-level data over time and across countries will likely reveal many important lessons, particularly since researchers tend to learn more where failures occur. Initial findings suggest the impact of policy interventions adopted in different countries have been mixed, and depend on bank and country characteristics. As more detailed bank-level data become available across the world, we can observe how banks behaved during the crisis; to what extent they lent to corporations, small firms, and households; and how banks with different size and ownership characteristics – large versus small banks, and private domestic- versus foreign- versus state-owned banks – behaved differently, and how these dynamics varied across countries.

While we have not observed bank runs or market crashes around the world, if economic recovery is not as swift as in the U.S., and banks in other nations were not as well capitalized and fortified entering the crisis, they may experience deteriorations in their asset quality that eventually leads to deleveraging and credit crunches that can slow the recoveries in their countries. Fiscal and financial pressures may also necessitate that countries reduce their fiscal and monetary supports and wind down their forbearance measures, creating potential vulnerabilities that will 63
As of January 2012, 5,945 of the 7,300 kilometers in the project have been completed, at an estimated cost of US$12 billion.

# **Section 3: Data Preparation**

We employ repeated cross-sectional surveys of manufacturing establishments carried out by the government of India. Our work studies surveys that were conducted in fiscal years 1994, 2000, 2005, and 2007 for the organized sector. In all cases, the survey was undertaken over two fiscal years (e.g., the 1994 survey was conducted during 1994-1995), but we will only refer to the initial year for simplicity. This time span allows us two surveys before and after the GQ upgrades. This section describes some key features of these data for our study.<sup>7</sup>

> 6 The initial two phases were about 90% publicly funded and focused on regional implementation. The NHDP allows for public-private partnerships, which it hopes will become a larger share of future development.

> 7 For additional detail on the manufacturing survey data, see Nataraj (2011), Kathuria et al. (2010), Fernandes and Pakes (2008), Hasan and Jandoc (2010), and Ghani et al. (2011).

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that covers the period 1960 to 2010. Our analysis is conducted at the level of states; we use the individual level data to compute state level measures of inequality of opportunity, overall income inequality, average income, and income growth (at selected percentiles). The same data are used to derive a set of controls including variables on demographics, education and employment. Additional controls are obtained from Marrero and Rodríguez (2013). Different methods are considered for the estimation of the dynamic panel data model (at the state level), specifically pooled OLS and different System-GMM regressions. As part of the robustness analysis we also consider different measures of IO (by varying both the choice of circumstances and the choice of outcomes along which inequality is being evaluated) and vary the choice of control variables.

Total income inequality is found to be negatively correlated with posterior growth of average income per capita when IO is not controlled for. Adding IO to the regression reveals that the correlation with future income growth is largely channeled through IO, leaving the effect of total inequality mostly insignificant.

When we re-examine the relationship between total inequality and income growth for low-, middle- and high income households, not controlling for IO, we find that the relationship is negative for the poor but positive for the rich. However, also here, the significance of total inequality is dramatically reduced when IO is added to the regression. This suggests that it is IO that is limiting the growth prospects of the poor rather than total inequality.

The exact channels via which IO might be impacting on future income growth remain to be identified. However, concentrating on IO while tracking growth separately for the poor, the middle class and the rich, denotes a necessary step forward in the dissection of the inequality-growth relationship.

The paper is organized as follows. Building on the literature of opportunity Section 2 develops the necessary distinction between overall inequality and inequality of opportunity. In Section 3 we introduce the database, including descriptives of the key variables used in the analysis.
of unemployed|2,952|0.167|0.482|7,313|0.151|0.447|
|No. of household members|2,952|2.165|1.216|7,313|2.375|1.463|
|Adult equivalent|2,952|1.832|0.961|7,313|1.624|0.639|
|Northern and Eastern Bulgaria|2,952|0.499|0.500|7,313|0.502|0.500|
|South-West and South-Central Bulgaria|2,952|0.501|0.500|7,313|0.498|0.500|

_Notes: The indicators in this table are at the household level. We weigh each observation by household survey weights._ _Source: Own estimates based on HBS (2019) and EU-SILC (2020)._ 22
were randomly selected using a multiple stage probability sampling scheme. In the first stage, 75 primary sampling units were randomly selected from each district with probability proportional to the population in each village (as listed by the 2005 census). For the most part, primary sampling units were villages. Some large villages comprised two or more PSUs. At the second stage, enumerators and the village head drew up a complete household listing and identified eligible households based on the village head’s knowledge of child ages. Fifteen eligible households were randomly selected from each PSU. In cases where the total number of eligible households was fewer than fifteen, all eligible households were sampled. From a target of 4,500 households, successful interviews were conducted with 4,169 households in 263 villages, a 93% response rate.

After the baseline survey, eligible villages were informed of the rollout of the school feeding program and invited to participate. Villages that wanted to participate had to meet minimum participation requirements as described above. Participation in sampled villages with existing schools in 2006 was 35/58 (60%) in Phongsaly, 47/63 in Khua (75%), and 34/59 (58%) in Nhot Ou. There was also considerable variation in the start date of the school feeding program, with some villages beginning in Fall 2006 and others beginning more than a year later. Therefore, children’s exposure to the school feeding program is likely correlated with other village characteristics that are associated with education and health outcomes of interest. We address some of these analytic challenges below.

In Fall 2008, a follow-up survey was fielded. Where possible, the sampled villages and households from 2006 were located and re-interviewed. A total of 11 villages had moved from their 2006 location (due to the government’s village relocation policies), had merged with another village, or could otherwise not be re-interviewed, leading to 119 households lost to 14
activities. We aimed to design an intervention that would _symmetrically_ reduce principal and agent costs of information acquisition _dramatically_ . Even in the presence of free-riding, a large symmetric reduction in costs of information acquisition can increase the general accuracy of agent beliefs in a hierarchy (Aghion and Tirole, 1997; Garicano, 2000; Gabaix et al., 2006).<sup>31</sup> Our intervention is based on a common approach to improving the information of public officials - the evidence briefing. Such briefings are now commonplace as a tool of government or research organizations whose aim is to inform public officials. By condensing research findings, evaluations or survey data into focused communications, evidence briefings aim to inform the decision-making of public officials by reducing the cost of interacting with the raw analysis.<sup>32</sup> Government circulars have been widely used throughout history to provide information to a body of public officials. Recently, forms of evidence briefing have begun to be routinely produced by economics research institutions as diverse as the Bipartisan Policy Center, the Centre for Economic Policy Research, the Institute for Fiscal Studies, JPAL/IPA, and the World Bank Group. The use of evidence briefings is part of a broader effort to make public policy ‘evidence-based’ by informing the beliefs of public officials (Smith, 1996; Pawson, 2006, Parkhurst, 2017).

Prior to the enumeration of the survey, a random sub-sample of the organizations we study were sent the official administrative data corresponding to our policy variables of interest as a government circular. A set of federal organizations received data for all regions for all indicators, highlighting the median district for each indicator for each region. Similarly, a random sub-sample of district jurisdictions were sent the official administrative data for their whole region for all indicators, also highlighting the median district for each indicator. Since the information package to the district-level jurisdictions had to pass through the regional offices, this meant that all regional officers were treated. Table A11 presents a comparison of treatment
average per capita consumption, or in terms of the headcount rate of poverty) and this quintile also displays the highest degree of variation of inequality across communities. The implication of this finding is that within poor communities, even small ones with populations of 5000 households or less, there are likely to be both poor and non-poor households. Community level targeting that transfers a uniform amount to all individuals within these small communities is thus likely to continue to suffer from leakage. The poverty impact of such targeting will thus fall short of what would have been possible if perfect targeting were available.

# **V.  Discussion**

The recent literature on micro-estimation of welfare based on combined survey and census data offers a promising avenue for analyzing the potential poverty impact from a variety of policy proposals, such as geographically targeted transfer schemes. In this paper we have taken recently completed “poverty maps” for three countries, Ecuador, Madagascar and Cambodia, and have explored the extent to which the availability of local estimates of poverty can help to strengthen targeting performance. We have taken the raw census-level output files from the poverty mapping methodology in these three countries and have simulated the impact on poverty of transferring an exogenously given budget to geographically defined sub-groups of the population according to their relative poverty status. We have asked to what extent effectiveness of targeting in reducing poverty improves as we define these sub-groups at progressively lower levels of spatial disaggregation.

We have found large gains from targeting smaller administrative units, such as districts or villages. We have shown that the largest gains from geographic targeting occur when the overall budget available for transfer is relatively modest, and when the poverty line is not so 28
follows. We describe the data in Section 2. Section 3 discusses the methodology. Our main results are discussed in Sections 4. Section 5 examines the role of risk and Section 6 concludes.

# **2. Data and Descriptive Evidence on Plant Survival and Product Innovation in Chile**

We use a unique dataset on Chilean manufacturing plants and their products (ENIA) collected by the Chilean Statistical Institute (INE) and spanning the 1996-2003 period. The fact that the ENIA is a census of Chilean plants (with more than 10 employees) is crucial for our analysis of plant survival.<sup>9</sup>

> 9 Details on the ENIA are provided in Fernandes and Paunov (2012). Plant survival in the ENIA was studied by Alvarez and Vergara (2010) and Lopez (2006). The fact that the ENIA covers in principle only plants with more than 10 employees could pose a problem for our analysis in that plants might drop out of the dataset not due to failure but due to their employment falling below the 10 employee threshold. However, that principle is in practice more flexible: in our estimating sample for the period 1996-2003 that includes 19439 plant-year observations, 4.8% or 939

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## **_(v) Child Marriage_**

In Mali, it is customary for husbands to pay a bride price to the parents of the new wife. The bride price is a transfer of money and/or livestock from the groom and/or his parents to the bride’s family at the time of marriage (Giuliano and Nunn, 2018). This practice could have negative effects on girls and women, as it could encourage child marriage (Corno et al., 2020), and thus exacerbate gender inequalities. The bride price provides the bride’s family with a source of income that can be used to smooth family consumption or modernize the agricultural production system to improve crop yields. We test this mechanism using DHS (Mali) data of 1995 ́ 96, 2001, 2006 and 2012 ́ 13. We follow Corno et al. (2020), by constructing our marriage variable as a binary variable to 1 if the female had her at _t_ and 0 otherwise. We limit our equal first marriage age sample to women between 12 and 17 years of age.

# **3.4 Drought Data**

Following Harari and Ferrara (2018); Miao and Popp (2014) and Vicente-Serrano et al. (2010), we use the Standardized Precipitation-Evapotranspiration Index (SPEI), to construct a measure of droughts. Our SPEI data are from the SPEI Global Drought Monitor. The SPEI Global Drought Monitor provides information on drought on a global scale. The SPEI time scales provided range from 1 to 48 months and the SPEI calibration period for our data is from January 1950 to December 2019.

Our SPEI value is observed during the 2014 and 2017 rainy seasons in Mali (JuneOctober). We use GPS information from EAC-I data to match each EA to the SPEI grid cell and calculate rainfall shocks at the EA level. Drought occurred if and only the SPEI value is below -1, which captures moderate to extreme droughts (Vicente-Serrano et al., 2010). Interestingly
5.3|3.6|102,378|
|Northeast Urban|0.7|0.2|22,455|
|Central Rural|2.0|1.1|49,644|
|Central Urban|2.2|0.1|62,538|
|Southeast Rural|4.8|8.8|197,767|
|Southeast Urban|0.5|1.1|40,399|
|Persian Gulf Rural|3.4|3.6|90,712|
|Persian Gulf Urban|0.3|0.2|14,949|
|Zagros Rural|4.2|2.9|95,337|
|Zagros Urban|0.6|0.2|18,733|

_Source_ : Authors calculation based on HEIS 2019 First, we focus on the binary outcome of whether a household is labeled as poor or not, under the two alternative deflation scenarios. Taking the SI approach as a starting point, Table 5 shows the proportion of individuals that change their poverty status when the MI approach is adopted. Nationally, 3.7% of individuals who were poor under SI are no longer poor when using MI, while

> 15 We follow, by and large, the analysis presented by Ceriani, Olivieri and Ranzani (2022) in their evaluation of the distributional impact of imputed rent estimation.

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The remainder of the paper proceeds as follows. Section 2 describes the experiment. Section 3 presents the empirical model. Section 4 reports the main results, highlighting how much participants decided to give, which delivery option encouraged more giving, how the transparency-enhancing treatment affected preferences for giving, and how trust and age affected the impact of the treatment and the relative preferences across the different program designs. Section 5 discusses alternative explanations for the increase in giving because of a transparency shock and checks the robustness of the estimates of the interaction between treatment and trust. Section 6 concludes.

# 2 Research design and data

## 2.1 Sample design and selection

The Jordan Gives experiment was carried out with 420 participants in 21 PSUs in Jordan, on a nationally representative sample of the Jordanian middle class. Participants were identified through a three-stage process: (1) 21 PSUs were drawn from a sampling frame of middle-class enumeration areas in Jordan based on the 2004 census; (2) within each PSU, households were selected using a random walk method; and (3) adults were recruited (one per household) to participate in the experiment using a Kish (1949) table. Based on extensive piloting, a protocol was devised to ensure that two groups of 10 randomly assigned individuals each could be constituted in each PSU (10 for treatment, 10 for control) at the same time and place (see Annex 1 for more details).

At the recruitment stage, the invitation letter explained that all participants who appear at the specified place and time (usually a local public school the day after recruitment) would receive a fuel voucher of JD 5 (about US$7.50) as a show-up fee and that there would be a chance to keep JD 10 more in such vouchers, depending on the outcome of the meeting. These vouchers were issued by Jordan Petroleum Refinery Company. They were widely known in Jordan and could be exchanged for gasoline in petrol stations throughout the country. The value of the JD 10 voucher was
> (Figure 1 below). Corporate income tax rates have gone down in all regions over the past decade. While South Asian countries have followed the trend, they started with higher initial rates and reduced them by a smaller percentage than elsewhere in the world. Over the past decade, corporate income tax rates went down by 11% in the four South Asian countries compared to 20% globally (Table 1 below).

One reason why tax rates are relatively high is a narrow tax base. A number of sectors, economic activities and types of firms are exempt from taxation or enjoy reduced rates. To maintain macroeconomic stability and compensate for revenue losses associated with tax incentives, governments need a higher tax rate than what would have been required if all firms were subject to the same tax regulations.

> 3To be reduced to 11% in 2015 budget

> 4 KPMG. 2014. Corporate Tax Rates Table  https://www.kpmg.com/GLOBAL/EN/SERVICES/TAX/TAX‐TOOLS‐AND‐ <u>RESOURCES/Pages/corporate‐tax‐rates‐table.aspx , accessed on November 15, 2014</u>

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