rafmacalaba/datause-encoder-data huggingface dataset:
In table 5, we first present the regressions including each set of BE indicators (ES, DB, and GC) separately,<sup>14</sup> and then pull all three sets of BE indicators together to compare the explanatory power of each set of BE indicators. Here, we control only for several basic countrylevel controls; we do not control for country fixed effects because the _Doing Business_ and the Global Competitiveness indicators are collinear with the country fixed effects.The results that contain the coefficients of the firm- and country-level controls are presented in appendix table A1. The patterns of the BE effects tend to be quite similar when using TFP instead of log labor productivity (log LP), although the sample size is smaller (less than half). Our discussion thus centers on log LP.

All three groups of BE indicators have independent explanatory power, but the Enterprise Survey indicators have a slight edge. In terms of adjusted R-squared, the specification with the Enterprise Survey indicators has the highest explanatory power among the three groups, closely followed by the Global Competitiveness indicators: see columns (1) to (3) and (5) to (7). In unreported specifications that are otherwise identical except excluding all BE indicators, the adjusted R-squareds are 0.050 for the employment growth specification and 0.302 for the log LP specifications. In terms of incremental changes in adjusted R-squared, the Enterprise Survey specification again has an edge, surpassing specifications relying on the _Doing Business_ or the Global Competitiveness indicators by more than 100 percent.<sup>15</sup> Moreover, the qualitative results for each group of indicators tend to be similar when they are entered alone and when they are entered jointly with other groups of indicators, indicating a reasonable amount of independent variations for each group of BE indicators.

Competition is associated with lower employment growth and higher productivity. Compared to firms that report no competitors, those facing one or more competitors have lower employment growth. In contrast, relative to firms that report no competitors, those facing one competitor (two or more competitors) have a labor productivity level that is 25 (18) log points higher. When using TFP as the productivity measure, firms facing one competitor also have the highest productivity edge, though those facing two or more competitors no longer have an edge.

_Government Protection_ . Corruption is negatively associated with firm growth. The Enterprise Survey’s Corruption Obstacle indicator is associated with lower firm growth, but

> 14 The World Bank HLO indicator is not part of the Doing Business project. We include it for ease in exposition, and because DB indicators and the HLO indicator are all country-level indicators produced by the World Bank.

> 15 An exception is for firm employment growth. The Enterprise Survey specification surpasses the Global Competitiveness specification only slightly.

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<!-- Start of picture text --> Growth and Investment Performance of Low- and Middle-Income Countries, 1980— 1989<br>Growth of per capita GDP, Alny<br>(percent per year)<br>9<br>8<br>@Korea «= OChins<br>7<br>*Bouwana .<br>6<br>@Taiwan<br>5 @Maucritius<br>Thailand<br>@Yemen AR Cyprus<br>4<br>@india Mala<br>3 Burkina5 Faso-Pakistanwhey @Sri. Lanka @MabysiaTM . a AlnyRe =0.17, = ~2.84(-3.7)n= (40.142!89<br>Pe i}<br>2 *Bysundi wot Aonesi<br>ki 2. #Columtfa bdHungary @Seychelle<br>; Ce atradea ha<br>eBangadeab Shtponia @Lesotho Congo<br>0 Se: Ie Myanmaresunbab Dy @Poland .<br>e@Ugenda neg . Cas aif aie POS | eDominican Repti @Algeria @Yugoehvia<br>eEniodt Sati "Papua New Guinea da<br>; OP<br>Uruguay-+@Benin adap @Ecuador « abtinasy, Maurkania SJOréaa<br>map AtrRep. ®* Philippi<br>-1 @Chana ire Yemen ror ippinesania<br>Honduras+® Mexico ©F pt ae snama<br>~2 . nant @Guatemali @Mabwicone oVeberuelae wantde eSyraTogoyr<br>-3 @Argentina @Madagascar eSuyensNi<br>Bolivia aNicragua<br>-4 onthe dtvoire *cebon<br>5<br>@Trinidgd snd Tobago<br>-6<br>0 5 10 15 20 25 30 35 40 a5<br>Gross investment-to-GDP ratio, f (9%)<br>Note:<br>(a) The line parallel to the z-axis represents the long-run average growth rate of per capita income in the industrial countries,<br>which is roughly 2.0 percent per year. The line parallel to the y-axis, drawn at 21.3 percent, stands for the unweighted average<br>of the investment-to-output ratios for the developing countries in the 1980s. The regression line, with growth rate of per capita<br>GDP as the dependent variable and the investment ratio as the independent variable, is also shown; the estimated coeffidents,<br>t-ratios, the R? value, and the sample size are indicated in the box.<br>(b) The country associated with a data point is given to the right of the bullet, except where indicated otherwise by an arrow.<br><!-- End of picture text -->
reason for this increase in trust was that firms experienced better services from the government than they had expected, while an alternative could be that they were less afraid of being shut down after registering.

Our follow-up survey asked firms about their trust and views of government. Individuals were asked on scale of 1 to 10 how much they trust different actors, where 10 denoted most trust and 1 least trust; as well as a question on whether they believe government acts in the interests of the people or in its own interest. Table 9 reports the results of estimating the impacts of our treatment assignments on these outcomes. We see a strong contrast to the results in Sri Lanka: the attempts at formalization in Belo Horizonte appear to have generally worsened trust in government. The results for the communication and free cost treatments all remain significant after controlling the false discovery rate at α=0.10, while the impact of the free cost treatment on believing the government acts in its own interests is also still significant when controlling the false discovery rate at α=0.05.

The impacts are not that large – a reduction of 0.3 to 0.5 points on a 10-point trust scale, which represents a 0.1 to 0.15 change; and an increase of 4 to 10 percentage points in the likelihood firm owners think the government acts in its own interest rather than in the interests of the people. Nevertheless, in an environment of widespread informality, efforts to reach out to particular firms and bring them into the formal system by either carrots or sticks may run the risk of increasing distrust in government if firm owners do not see any benefits from being brought into this formal system. The distrust effect is more significant for information and free cost efforts than for the inspection treatment – possibly because a government initiative that individually invited firms to register is different from usual activities and appears to have aroused suspicion.

# **6. Conclusion**

Despite reforms which make it faster and simpler for informal firms in Brazil to register, the majority of firms remain informal. While simply paying firms to formalize has been found to be have big impacts on formalization rates in Sri Lanka, this is unlikely to be on the policy menu for most governments. Instead there are a range of carrots and sticks that governments can use to attempt to bring firms into the formal sector. Our experiment tests some of the most common ones – informing firms, making it cheaper for them to register, and increasing enforcement of rules. Our findings suggest sticks rather than carrots seem more effective at getting firms to formalize, but also show limits to this approach.

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for differences in access to credit. Therefore it seems the supply side of the external and internal credit markets can not explain the difference in returns.

# _5.4 Differences in Entrepreneurial Ability and Reasons for Going into Business_

The demand for credit will depend on the optimal size of the enterprise. If capital and ability are complements in production, more able owners will have higher optimal sizes. Hence, for a given supply of credit, more able owners will be further away from their optimal size and have higher marginal returns to capital.

Entrepreneurial ability is a multifaceted and nebulous concept, which is unlikely to be captured fully by general measures of ability such as years of education. The SLMS has an extremely rich set of measures of ability, allowing us to consider an array of possible measures for entrepreneurial ability. In Table 7 we show three such measures. Column 5 shows the standard measure, years of education. Column 6 shows Digit-span recall, a measure of short-term processing power, used in Djankov et al. (2005). Table 6 shows that females have significantly more education than males, but significantly less Digit-span recall. Table 7 finds that both these measures are significant in their interactions with the treatment amount, showing larger treatment effects to more able individuals. But again, the basic pattern of returns is unchanged by the inclusion of the ability measures. Males continue to show, on average, high returns and females near zero returns to the treatment.

Our survey also contains many measures developed by industrial psychologists to measure different facets of the entrepreneurial personality. Table 8 examines the robustness of the female interaction term to 19 alternative measures of owner ability and motivation. These include measures commonly found in economic studies, such as mother’s and father’s previous business experience; the time taken for individuals to solve a maze (median time was 53 seconds); entrepreneurial traits such as passion for work, tenacity (both from Baum and Locke, 2004); entrepreneurial self-efficacy; trust (taken from the General Social Survey); the achievement and power motivations of McClelland (1985); Work centrality (Mishra et al, 1990); Impulsiveness, from three questions on the Barratt Impulsiveness Scale; Financial Literacy (from Lusardi and Mitchell, 2006); internal locus of control (Rotter, 1966) and our own questions on 22

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# **_Figure 5: Students Enrolled in Mozambican Universities_**

<!-- Start of picture text --> 20000<br>18000<br>16000<br>14000<br>12000<br>10000<br>8000<br>6000<br>4000<br>2000<br>0<br>2004 2005 2006 2004 2005 2006 2004 2005 2006 2004 2005 2006<br>Social Sciences/Manag./Law Engineering Health Education<br>Public Universities Private Universities<br><!-- End of picture text --> Source: Ministry of Education and Culture statistics on higher education in Mozambique.

# **Box 4. Quality Enhancement and Innovation Facility (QIF)**

QIF is a competitive fund in operation since 2002 managed by the Ministry of Education and Culture to provide financial support for investments in capacity building and innovation in higher education in Mozambique under three windows (to which the 3 largest public universities cannot apply): (1) Academic staff awards: grants to academic staff to enable them to invest in new skills, teaching methods or learning materials, design and introduction of innovations and improvements in curriculum, delivery of courses and academic support of students; (2) Research awards: grants to support basic or applied research and develop linkages or other forms of collaboration with the Mozambican productive sector, other national or international research and higher education institutions; (3) Institutional awards: grants or repayable loans to higher education institutions to support improvements in quality and efficiency of teaching and management of resources and innovations in the design and delivery of academic programs and courses.

The QIF is demand-driven and is competitive in that only the best proposals are selected for financial support. One recent example of success is the _Instituto Superior de Transportes e Comunicações_ , a private university in Mozambique which reportedly managed to improve its 36
External shocks, fiscal policy and income distribution: Alternative scenarios for Moldova<sup>*</sup> by Jouko Kinnunen, Hans Lofgren, Victor Sulla, Dino Merotto<sup>**†**</sup> JEL classification: C68, E62, O21 Keywords: Computable General Equilibrium, MAMS, Development Strategy, Moldova.

Sector board: Economic Policy

> ***** The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

> **†** The authors are associated with Statistics and Research Åland (Kinnunen) and the World Bank (Lofgren, Sulla and Merotto).
- **Treatment of electricity sector:** In our main results, the electricity sector is not treated as an EITE sector (it is not highly traded). However, in some real-world cases, the electricity sector is given special treatment under carbon pricing. Because of its large contribution to US emissions, and because it offers substantial cost-effective CO2 mitigation opportunities, treatment of the electricity sector is important in determining model results. In Section C.5, we show how model results are affected when the electricity sector is included in the set of EITE sectors. While inclusion of the electricity sector in the set of EITE sectors results in large numerical changes in results, the ranking of policy instruments and general conclusions from the analysis are preserved—notably, that the intensity-based policy variants achieve deeper CO2 reductions than the LSR and OBR policies in the EITE sectors, and that the intensity-based policies attenuate negative impacts of carbon pricing on output relative to the LSR policy.

- **Results for different countries:** Our main numerical analysis calibrates the CGE model to US data. To ensure that our conclusions are not driven by factors idiosyncratic to the US economy, we replicate our analysis after recalibrating our model to benchmark data from other countries in the GTAP data set. We show our analysis in Section C.3 for all G20 countries. While the numerical results differ from the results based on US data, the qualitative conclusions of the analysis remain unchanged: the intensity-based policy variants achieve deeper CO2 reductions in the targeted EITE sectors compared with the LSR and OBR policies and result in smaller curtailment in output in these sectors relative to the LSR benchmark.

- **Detailed subsector results:** In our main numerical results, we aggregate six energyintensive trade-exposed sectors (chemical manufacturing, iron and steel manufacturing, nonferrous metal manufacturing, nonmetal mineral manufacturing, oil refining, and pulp and paper manufacturing) into one aggregate sector for reporting purposes. In Section C.4, we report disaggregate results for each EITE subsector. Again, we find that sector output falls by a smaller amount under the intensity-based rebating variants compared with under the LSR policy, and that intensity-based policy variants achieve deeper greenhouse gas reductions in EITE sectors compared with LSR and

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the demand risk. In fact, the demand risk was exacerbated by the fact that about a third of the anticipated subsidy was linked to the passenger growth achieved.

Figures for actual debt and equity levels in the franchise companies are not publicly available. Table 3 sets out relevant figures that are publicly available. It shows subsidy levels, government book values of operating and infrastructure assets transferred, and the minimum equity and performance bond requirements.

**Table 3: Subsidies and leverage in the Melbourne transport franchises**

A$ million, except for ratios

|Lead company (and franchise)|National<br>Express<br>(Bayside<br>Trains)|Connex<br>(Hillside<br>Trains)|National<br>Express<br>(Swanston<br>Trams)|Transdev<br>(Yarra<br>Trams)|National<br>Express<br>V/line<br>Passenger)|Total|
|---|---|---|---|---|---|---|
|NPV of subsidies|||||||
|Fixed|354|612|286|134|476|1,872|
|Variable|353|259|109|116|98|934|
|Total|707|880|395|251|574|2,806|
|Book values of assets|||||||
|Operating business at transfer||||||663|
|Land and infrastructure||||||3,324|
|Minimum equity requirements|||||||
|Minimum equity levels|10|8|5|5|8|35|
|Performance bonds|30|20|15|15|20|100|
|Minimum equity plus performance<br>bonds as % of operating assets||||||20|
|Minimum equity plus performance<br>bonds as % of operating plus land<br>and infrastructure assets||||||3|

Source: Auditor General of the State of Victoria 2000.

It is probably reasonable to assume that actual equity levels were not much above minimum required levels. Proxies for leverage could then be calculated by dividing minimum equity and performance bond levels into the book value of assets.<sup>7</sup> Minimum equity and performance bonds amounted to 20 percent of the book value of the operating assets transferred to the franchisees.

Greater insight can perhaps be gained by comparing equity and bond levels to the value the government hoped to secure and the risks the franchisees were taking. The government expected gains of A$1.8 billion over the contract life, but this was secured by a total of only A$135 million in capital put at risk by the operators. In other words, minimum equity and bond requirements were set at 8 percent of expected gains.

> 7 We include performance bonds as part of equity in these calculations on the grounds that like equity, the performance bonds will be lost if the company defaults on the contract. If performance bonds were excluded from the equity estimate, as is more conventional, the leverage would be even higher.

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|Adj. R-squared|0.005|.097|.061|.064|.097|
|---|---|---|---|---|---|
|Number of schools|845|845|845|845|845|
|Student Characteristics||X|X|X|X|
|Teacher Characteristics||X|X|X|X|
|Classroom Characteristics||X|X|X|X|
|School Characteristics||X|X|X|X|

Note: Clustered, by school, standard errors in parenthesis. *** 1%, ** 5%, * 10% significance. Student controls include sex and age of the student. Teacher controls include sex, age, education, and teaching experience. School controls include class size taught by the teachers and ownership of the school (i.e. public, private).

# 5 Discussion

We use a 4-step validation framework to provide evidence that _Teach_ is a valid measure for practitioners to monitor teaching practices. This evidence is based on data collected from a large representative sample of schools in Punjab, Pakistan. We provide evidence that the measured content has a clear theoretical and empirical foundation (content), that the elements and behaviors are interpreted and used correctly by observers (cognition), that the components relate to one another as expected, that the elements are internally consistent and the score is reliably captured (coherence), and that the score is correlated with other measures, as expected by the literature (correlation). To the best of our knowledge, this is the first paper to use IRT to assess the information and location of each element in a classroom observation tool.

There are several new insights that our analysis reveals. The _Teach_ elements provide substantial information on the quality of teaching practices. Not only that, but this information is distributed evenly throughout the scale, which allows us to use _Teach_ to differentiate among teachers of similar but not equal ability. We can also better understand what information the tool is gathering and identify three key areas for improvement.

First, we noticed Opportunities to Learn has strong ceiling effects, a relatively low level of information, and overlap between the possible response curves. This indicates that for this element, teachers of different latent abilities obtain the same score. Second, since Feedback had only one behavior, it becomes a _de facto_ three-point element. As a result, while Feedback does contain relatively high levels of information, its response curve overlaps, which hinders the extent to which teachers can be differentiated as they rarely score in the 2 or 4-point range. Finally, like Opportunities to Learn, Supportive Learning Environment also has strong ceiling effects; in fact, of these three elements, the least amount of information can be gathered from Supportive Learning Environment.

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cision makers statistically represent the constituent population. In other words, the behavior of randomly selected decision makers reveals how ordinary citizens would act if they were put in a position of responsibility. Randomly selected decision makers or policies have therefore become a standard reference point in the nascent literature on the behavioral effects of elections (Baldassarri and Grossman, 2011; Grossman and Baldassarri, 2012; Corazzini et al., 2014) and voting (B ́o et al., 2010).

Second, random selection of decision makers is a practical alternative to elections, if a political system is at risk of being captured by powerful individuals for their personal advantage. In fact, societies that selected their leaders at random largely did so with the explicit objective of leveling the political playing field (Carson and Martin, 1999; Frey and Steiner, 2014). In medieval Italian city states, the random selection of political leaders ensured the frequent rotation of power between rivaling families. When several Swiss towns began to select their mayors at random in the 17th century, they did so to ensure that nobody would gain disproportionately from holding office (Carson and Martin, 1999, 22). Even in recent years, policy makers have experimented with the random selection of decision makers, for example to prevent local development grants from being captured by village chiefs in Sierra Leone (Voors et al., 2017).

Third, a comparison between elections and random selection is appealing, because both institutions are similarly egalitarian, which distinguishes them from any other method of delegating democratic authority (Table 1). Random selection gives every eligible constituent an equal chance at obtaining a position of responsibility, whereas elections give every eligible voter an equal say in the selection process. Bureaucratic appointments, by contrast, involve exclusionary selection criteria. Selection by consensus, while being inclusive of the constituent population, privileges influential constituents or coalitions via their disproportionate bargaining power. To the extent that procedural egalitarianism matters for the perceived fairness of a political institutions, both elections and random selection might rank highly on procedural fairness, since both are founded on egalitarian premises. This assumption will be verified directly.

7