rafmacalaba/data-use-mentions-extended huggingface dataset:
(somewhat surprisingly) to be a _negatively_ related to the existence (a) of an index of institutional restraint on the executive and (b) to a right-wing government and _positively_ to the number of staff in the pre-reform telecom incumbent. In most cases, as one would expect, taking account of endogeneity reduces the t-statistics on the regulatory variable. However, the instrumental variable (IV) estimate for the impact of regulatory independence on network penetration is _increased_ relative to the OLS estimate (but only at a 10% significance level)<sup>40</sup> .

Guasch, Laffont and Straub do not treat the existence of an independent regulator as endogenous; rather, they use the existence of the regulator as an instrument for the concession contract features that they believe are endogenous. As they recognize, this causes problems in the IV estimates of the impact of the regulator when the latter is included as a separate independent variable in addition to its use as an instrument. This points to the problem (emphasized both by Guasch et al and Fink et al) of the acute difficulty in finding appropriate instruments for the estimation of utility and regulatory reform outcomes.

# **5.1.3 The Errors-in-Variables Problem where the Informal Governance Characteristics are Unobservable**

We have earlier identified that there is a potential errors-in variables problem from having data only on the formal characteristics of regulation (the legal framework) rather than data for countries _both_ on the legal characteristics _and_ on the actual development of regulatory practice.

In order to gain an idea of the potential quantitative effect of using only formal measures of the quality of the regulatory institutions in practice, we explored data from Stern and Holder (Table 2 in Section 2.2.1 above) on a range of 12 regulatory institutions in six developing Asian countries in 1998. This study divided the six effects into two groups:

- (a) a group of 3 _formal_ measures setting out features of the legal framework (Clarity of Roles and Objectives, Autonomy, and
million foreign workers in total. As the MOHA work permit data indicate 1.77 million foreign workers during the period, the first estimate implies that the number of irregular foreign workers is approximately 1.39 million. Secondly, our robustness check (Step 5 under ‘Methodology’) estimates a foreign worker population of 2.99 million, of which 1.22 million are irregulars (see Figure 5 on the number by nationality).

**_Figure 5. Estimated number of foreign workers by nationality_**

<!-- Start of picture text --> 1,200<br> 1,000<br> 800<br> 600<br> 400<br> 200<br> 0<br>Thousands<br><!-- End of picture text --> _Source_ : BNM remittance data, authors’ estimations.

# **The distribution of foreign workers by state in our estimates are in line with those reported in the MOHA**

**data** . Foreign workers are concentrated in Selangor, followed by Johor and Kuala Lumpur Federal Territory (Figure 6a). Interestingly, we find that Sarawak takes up a substantially lower share of the foreign worker population in our estimates compared to the MOHA data – 3 percent of the total versus 7 percent (Figure 6b). It may be that foreign workers in Sarawak have a lower propensity to use remittance outlets because of limited accessibility in Sarawak, or that foreign workers in Sarawak opt for alternative money transfer channels such as cash carried by a traveler going back home.

# **As in the MOHA data, Indonesians make up most of the foreign worker population in our estimates**

**(Figure 7a).** However, the second largest group as estimated from the remittance data is not Nepalese but Bangladeshis. This might be explained by two plausible scenarios: (i) not many Nepalese use MSPs, instead using alternative channels to send money, especially in Selangor, and (ii
to unemployment or inactivity._ _** Net labor income gains encompass both the losses incurred from job displacements and the earnings increases resulting from higher wages for those who retained their employment. Since it is assumed that all dismissed workers move to unemployment or inactivity, this represents a lower bound of the net gains (or an upper bound of the earning losses). If workers move to formal or informal employment and have a positive labor income, net labor gains could be higher._ _*** This column presents information on the share of full-time employees who become unemployed or inactive after the minimum wage increase. 95% confidence intervals are provided in parentheses._ _Source: Own simulations based on administrative tax data._ 39
Robb, Alicia, and John Wolken. 2002. “Firm, Owner, and Financing Characteristics: Differences between Female- and Male-Owned Small Businesses.” Finance and Economics Discussion Series Working Paper 2002-18, Board of Governors of the Federal Reserve System, Washington, DC.

Rocha and Winkler (2019), “Trade and Female Labor Participation,” Policy Research Working Paper 9098, World Bank, Washington, DC.

Rowley, Chris (2013), “What Might Influence Female Manager Careers Success?” Mimeograph, Cass Business School, City University London.

Sabarwal, Shwetlana and Katherine Terrell (2008), “Does Gender Matter for Firm Performance? Evidence from Eastern Europe and Central Asia,” World Bank Working Paper Series No. 4705, World Bank, USA.

Seguino, Stephanie (1997), “Export-Led Growth and the Persistence of Gender Inequality in the Newly Industrialized Countries,” in Janet Rives and Mahmood Youse. (eds.) _Economic Dimensions of Gender Inequality: A Global Perspective_ , pp. 1–33. Westport, CT: Greenwood Press.

Seguino, Stephanie (2000), “Accounting for Gender in Asian Economic Growth,” _Feminist Economics_ , 6:3, 27-58.

Söderbom, Måns, and Francis Teal (2004), “Size and Efficiency in African Manufacturing Firms: Evidence from Firm‐Level Panel Data,” _Journal of Development Economics,_ 73 (February): 369– 94.

Seker, Murat (2012), “Importing, Exporting, and Innovation in Developing Countries,” _Review of International Economics_ , 20(2): 299-314.

Spieldoch, A. (2004), “Women’s Rights and the Multilateral Trading System: The Politics of Gender Mainstreaming at the WTO,” Heinrich Boell Foundation (HBF) and IGTN.

Standing, G. (1989), “Global Feminization through Flexible Labor,” _World Development_ , 17 (7), 1077-1095.

Thomas, Duncan (1990), “Intrahousehold Resource Allocation: An Inferential Approach
Measuring True Sales and Underreporting with Matched Firm-Level Survey and Tax office Data surveys are quite similar to those available from two independent ‘macro’ methodologies.<sup>8</sup> This suggests that the direct approach based on surveys to measuring unofficial activity provides useful information about actual underreporting behavior by firms.

In figure 1 we plot the mean of underreporting by firms based on the direct approach across countries sorted by (log) GDP per capita in 2005. We used all BEEPS, (P)ICS, WBES and Firm Analysis and Competitiveness Surveys (FACS) for 2005 or later that could be freely accessed through the World Bank website<sup>9</sup> and which included information on selfreported underreporting in sales. In case multiple surveys were available for a given country, we selected the most recent one. Figure 1 shows a clear pattern that the mean level of underreporting is decreasing in log of GDP per capita. Underreporting is the highest across the low income countries and the lowest across the high income and OECD countries<sup>10</sup> . However, even at comparable levels of income, there is a large variation in the extent of underreporting by firms across countries, which may reflect genuine countrydifferences in underreporting behavior as well as measurement errors.

Because the survey asks about the underreporting by typical firms in the same area of activity, there may be a “bias towards the average behavior of other firms in that environment” (Dabla-Norris and Koeda 2008, p.10) as firms may report the average amount of underreporting for firms in the same industry. Also they may report the average amount of underreporting as perceived by them in the same locality. We therefore 8 Although one should note that the macro estimates are for the percent of GDP that is unregistered, rather than the percent sales not reported by formal sector firms to the tax authorities.

- 9 www.enterprisesurveys.org

- 10 Based on the World Bank classification of income groups.

8
We consider refugees from various source countries and residing close to local communities (clusters in LSMS). We construct a refugee index which weights the number of refugees in the closest refugee settlements by the inversed distance from those settlements to the clusters. In order to limit endogeneity concerns, we instrument this variable of interest with a shift-share instrumental variable which is based on the distance of the refugee settlements to the closest border crossing points for each source country.

Our findings with regards to household consumption are similar to those found in Kenya (AlixGarcia et al., 2018), Rwanda (Alloush et al., 2017), and Tanzania (Maystadt & Verwimp, 2014). Our results indicate that rural households, living close to the refugee settlements benefit from the presence of refugees. Similarly, Alix-Garcia and Saah (2009) find that rural

> 1 Uganda National Household Survey carried out in the three waves of 2002–03, 2005–06 and 2009–10.

3
corresponding figures for the South are 39% vs. 24%. By contrast, in Western Europe and especially in the Nordic countries, distributions of formal and informal employees among four household income perception categories are rather similar.

<!-- Start of picture text --> Household Income Perception by type of Employment<br>In European Regions, 2004-2009<br>Employee with a contract Employee without a contract<br>East South West North East South West North<br>Living Very Difficult Living Difficult Living Very Difficult Living Difficult<br>Coping Living Comfortably Coping Living Comfortably<br>Regions sorted descending by share of low-income households among workers without a contract<br>Data not weighted by countries' population: A worker from any country is equally likely to be sampled<br>100 100<br>80 80<br>60 60<br>40 % of workers 40<br>20 20<br>0 0<br><!-- End of picture text -->

# **Figure 17 Perception of household financial situation among formal and informal employees in European regions** _Source:_ Calculation with ESS data.

The data mentioned above refer to the period between 2004 and 2009. For 20082009, round 4 of ESS provides also information on household income decile group within the country, although non-response to corresponding question (unlike the question on income perception) was quite substantial. Figure 18 summarizes this information (in quintile rather than decile form) by European region, separately for contracted and non-contracted employees. In Eastern and Western Europe, 11% and 13%, respectively, of non-contracted employees and just 6.5% of contracted employees live in the bottom quintile households. In Southern Europe these proportions are 9.9% vs. 5.4%, whilst in Northern Europe – 8.6% vs. 2.5%. In other words, while informal workers disproportionally suffer from absolute poverty only in the East and in the South
. The social accounting matrix (SAM), the main database for CGE modeling, accounts data for the formal sector or aggregate sector, which includes both formal and informal activities without distinction. Some existing studies have illustrated how to incorporate the informal sector into the SAM. Rada (2009) is an example. In the absence of official statistics that differentiate the formal and informal economic activities, the study uses the shares of regular and irregular wage income in a given sector to derive an approximate size of informal and formal activities. Because there is no universal definition of the informal sector, for China, the study considers formal workers are those employed by both formal and informal enterprises as defined in the official statistics. Irregular employment, which are not included in the official statistics, is classified as informal labor. In India, the formal sector consists of those enterprises which are 7
Complementing the household survey, we conducted semi-structured life-history interviews with s sub-set of male and female VUP beneficiaries in 2015. The sample of beneficiaries for the qualitative work was selected purposefully from the household survey based on beneficiary status and observed welfare improvements, proxied by livestock accumulation, over time (see Table 1 for the distribution). The sample drew from particular points in the distribution to assess trajectories of welfare improvement or stagnation. The lifehistory interviews allow for more detailed insights into the welfare trajectory of beneficiary households – the process, obstacles and opportunities.

**<u>Table 1</u>** <u>: Sample of beneficiary life-history interviews</u>

|<br>Beneficiary type|Female|Male|Total|
|---|---|---|---|
|Public works|8|17|25|
|_of which also benefited from financial services loan_||_6_|_6_|
|Direct support|13|4|17|
|_of which also benefited from financial services loan_||_1_|_1_|
|Financial services loan||5|5|
|N|21|26|47|

_Source:_ Own data collected in 2015.

# **_4.2 Empirical strategy_**

The empirical analysis consists of two parts. In line with the conceptual framework we first look at access to the income transfer. Specifically, we investigate the characteristics of the households participating in public works more systematically. We use a probit model to identify the determinants of participation in the public works component in each survey year. The econometric specification used has the following functional form: 13
party access to networks;

- Regulatory reform, including adoption of incentive regulation for the natural monopoly network activities;

- Establishment of an independent regulator;

- Establishment of a competitive wholesale generation market;

- Liberalisation of the retail supply market;

- Privatisation of electricity assets;

- Definition of rules concerning consumer protection, allocation of energy subsidies, and stranded costs.

A World Bank survey on the state of energy reform in developing countries focused on six key steps to electricity sector reforms: (i) corporatisation or commercialisation of the core utility; (ii) enactment of an ‘Energy Law’; (iii) establishment of an independent regulatory authority; (iv) restructuring of the core utility; (v) private investment in greenfield sites; and (vi) privatisation (Bacon, 1999). The survey suggests a sequence of key reform steps in which the most common component is corporatisation and 7
Policy Research Working Paper 6368

# **Abstract**

Efforts to make it easier for firms to register formally are the most common form of business regulatory reform over the past decade. While there is evidence that large reforms have resulted in some increases in registration rates, recent experimental evidence suggests very few informal firms choose to register when given information about how to do so. This raises the question of whether it is productive for governments to continue to extend simplification efforts to all firms, especially those in more remote areas where many of the benefits of registering may be reduced. This study uses administrative data to evaluate the impact of Minas Fácil Expresso, a program in the state of Minas Gerais, Brazil, which attempted to expand a business start-up simplification program to more remote municipalities. Using difference-indifferences with 56 months of registration data for 822 municipalities, the analysis finds introducing these units actually led to a reduction in registration rates, and no change in tax revenues. The paper uses this evaluation to illustrate the design choices and issues involved in using administrative data to evaluate reforms, with the goal of also providing a template that can be used for evaluating similar reforms elsewhere.

This paper is a product of the Finance and Private Sector Development Team, Development Research Group. 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://econ.worldbank.org. The authors may be contacted at mbruhn@worldbank.org and dmckenzie@worldbank.org.

_The Impact Evaluation Series has been established in recognition of the importance of impact evaluation studies for World Bank operations and for development in general. The series serves as a vehicle for the dissemination of findings of those studies. Papers in this series are part of the Bank’s Policy Research Working Paper Series. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations
random sample of 13 households for each selected EA to generate a sample of 1,248 households.

3. Construct sample weights for each household equal to the inverse of their selection probability.<sup>39</sup> 4. Use the ordered quantile normalization to construct normalized non-monetary welfare in the sample.

5. Using the household sample from step 2, the sample weights from step 3, and the normalized welfare measure from step 4, estimate a lasso regression of normalized non-monetary welfare on all candidate geospatial indicators.<sup>40</sup> 6. Using the same inputs as the previous step, calculate the 46.5<sup>th</sup> percentile of the sample distribution of normalized non-monetary welfare to use as the poverty line.

> 38 We selected three regions to use for this exercise because the lasso procedure did not select any variables when using only one or two regions, when mimicking the sample size of the budget survey.  We selected these particular three regions because they are disproportionately poor and because they were the first three regions in numeric order following the capital of Dodoma.

> 39 The household sample weights are the product of two ratios: The number of census EAs in each district divided by 4, and the number of households in each sampled EA divided by 13. These are multiplied by household size to obtain population weights.

> 40 As before, we use the plugin method for selecting lambda in the lasso.

37
|Return period|Likelihood of a person|experiencing eve|nt...|
|---|---|---|---|
|of event|in 10years<br>in 20years|in 50years|in a lifetime|
|10-year|65%<br>88%|99%|99%|
|20-year|40%<br>64%|92%|99%|
|100-year|10%<br>18%|39%|63%|

The hazard datasets used for analysis are summarized in Table 2, including the return periods and intensity thresholds initially considered for each type of event. All datasets are publicly accessible. Different thresholds are initially considered, but for much of the analysis the return period and intensity thresholds are set to specific values discussed further below.

**Table 2: Hazard data and thresholds defining exposed places**

|Hazard|Source|Spatial<br>resolution|Type|Return periods<br>(years)|Intensity thresholds defining<br>extreme events|
|---|---|---|---|---|---|
|Flood|Rentschler, Salhab, &<br>Jafino (2022)|3”<br>(~90 m)|Modelled|100|An inundation depth of at least<br>0.15 m, 0.5m, 1.5m|
|Agricultural<br>drought<br>Heatwave|FAO (2023), and<br>Schiavina, Melchiorri &<br>Pesaresi (2023)<br>Ridder et al. (2017)|~30”<br>(1 km)<br>5’<br>(~10 km)|Historical<br>Modelled|5,10,15,20,40*<br>5, 20, 100|At least 30 percent, and
the significant subsidy embodied in the cheap central bank rediscounting facilities. Providing an RFI with concessional funds is the most common method of subsidization, yet calculating the value of the subsidy implicit in the RFI's concessionally borrowed funds requires information not included in the RF's financial statements. The same is true for the RFI's equity.

In contrast to the profit maximizer, who does not differentiate between profit that is subsidydependent as long as continued subsidization is ensured and profit that is fully subsidyindependent, subsidy dependence is crucial to RFI's performance assessment. The social cost of RFI operations, of which subsidies constitute a significant share, is essential in determining the social justification for their existence and continued operations, because rural RFIs are often public or quasi-public institutions. To illustrate the futility of the current financial reporting system, one may ask, for example, what is the meaning of an RFI's return on equity of 20 percent when 50 percent of the RF's financial obligations constitute concessional borrowed funds from the central bank (rediscounting facilities), carrying an interest rate significantly below market deposit interest rates, and one-third of its payroll cost, 80 percent of its loan losses and all training expenses are assumed by the government.

> _54_ The Subsidy Dependency Index was introduced in Yaron. 1992b. This annex is excerpted from: M. Gurand,

> G. Pederson. J. Yaron. 1994. _Outreach and Sustainability of Six Rural Finance Institutions in Sub-Saharan Africa._ World Bank Discussion Paper No. 248. Washington. DC: Agriculture and Natural Resources Department. World Bank, pp. 72 - 75.

85
<!-- Start of picture text --> 0.500<br>Density of non-RCA Density of RCA<br>0.450 product lines product lines<br>0.400<br>0.350<br>0.300<br>0.250<br>0.200<br>0.150<br>0.100<br>0.050<br>0.000<br>37 29 81 86 79 89 32 33 49 96 18 71 44 23 4 60 20 61 8 7<br>Source: UN COMTRADE (2008), and World Bank staff calculations<br><!-- End of picture text --> Figure 5: Density of product lines with (blue) and without (red) revealed comparative advantage for Syria, 2 digit HS level, 2007. Selected HS codes reported on the horizontal axis correspond to slightly thicker bars.

export with revealed comparative advantage, the average density is 0.299. The overall distribution of product densities, as captured in Figure 5, reflects this distinction well.

It is especially interesting to observe that the density values for many of the sectors which have shown large increases in revealed comparative advantage over the past years are high. This shows that the Syrian economy has taken advantage of the factor substitutability between sectors with a strong export performance and sectors which had previously not found access to international markets. Some examples are miscellaneous chemical products (chapter 38), iron or steel articles (chapter 73), furniture (chapter 94), and miscellaneous manufactures (chapter 96). Other sectors with high density values are live trees (chapter 6), food residue and waste (chapter 23), straw (46), miscellaneous edible preparations (chapter 21) and wadding yarns and twine (chapter 56). While these numbers may indicate export potential for Syria in these sectors, it is important to note that the analysis relies on proximity indicators between products