rafmacalaba/datause-encoder-data huggingface dataset:
by the ratio of the change in the logarithm of the fraction of employment accounted for by firms with 1,000 or more and 5,000 or more employees, relative to the logdifference of the employment levels, which is equal to -0.2 in the data. Formally, we set _p_ so as to match where _G_ (.) here denotes the cumulative distribution function of the employment weighted firm size distribution in the United States. Targeting this slope translates into a 72% share of employment accounted for by the top 10% largest firms, which is consistent with the data for the U.S.’ manufacturing sector.

Regarding the probability of the exogenous exit shock, this parameter controls the exit rate among the largest firms. Thus, we calibrate it to replicate the exit rate among large firms in the employment-weighted size distribution which, according to the Small Business Administration (SBA)<sup>13</sup> , is equal to 0.02.

With respect to the realization of firm-wide productivity for entering firms, we assume that all entrants get a productivity draw of _e_<sup>_ωe_</sup> = 1 and then fan-out over the space of idiosyncratic productivity according to its stochastic process. The target driving this choice is the average size of an entrant relative to the average incumbent in the U.S.’ size distribution, which Luttmer (2007) reports to be equal to 6%. The entry and fixed production costs are set at _fe_ = 1 and _fc_ = 0.1 respectively. Together with the parameters of the stochastic process for firm-wide productivity, particularly the standard deviation of the shocks to idiosyncratic productivity, the choice of _fc_ and _fe_ imply an exit rate of 5% .

The last portion of the calibration refers to the distribution of distortions. A pervasive feature in developing countries is that idiosyncratic distortions exhibit a of correlation with the distribution of across strong degree physical productivities firms. This is a key property of the data, since it is the one that creates a non-trivial response in the dynamic decisions of the firms, such as the decision to enter and . exit the economy<sup>14</sup> To honor such relationship, we propose the following log-linear functional form for the relationship between idiosyncratic distortions and the id13This is the exit rate that applies to firms larger than or equal to 500 workers in the year 2002. 14It can be shown that uncorrelated distortions, although damaging for allocative efficiency in terms of products and labor, have neutral effects on entry and exit. We resume this point once we explore the quantitative performance of the model.

20
4 Nonetheless the findings of this paper emphasize opportunities to keep up the performance, particularly as reform complexity may increase under the second, third and fourth waves of reforms being undertaking in emerging and developing economies.

# **2. Related literature**

Part of the broader body of literature on the impact of aid and development financing on economic variables makes use of cross-country data and aid/development financing at a very aggregate level. The findings vary significantly. Burnside and Dollar’s (2000, 2004) influential work finds that aid has a positive impact on growth in developing countries with good fiscal, monetary and trade policies, but has little effect when economic policies are inadequate. Clemens _et al._ (2004) find that increases in aid have been followed, with a lag, by modest increases in investment and growth. Yet, Boone (1995) finds that aid has no impact on investment, growth, or human development indicators; but it does increase the size of government. Factors such as the complexity of each country situation, the non-differentiation of the type of financing (e.g., infrastructure investments vis a vis policy-based lending), problems of endogeneity, sample size, missing data, among others, may have contributed to the variation in findings. Smets and Knack (2014) examine the impact of World Bank fast-disbursing lending on the quality of economic policy. They use elements of the Bank’s Country Policy and Institutional Assessment ratings as the dependent variable. Noting that past studies have found only weak effects of fast-disbursing lending on macro stability, they restrict their sample to consider the impact of loans that were focused on macro and fiscal issues. Their key result is that fast-disbursing lending does succeed at improving governments’ economic policy-making.

A second strand of inquiry is the case study approach, commonly used by multilateral banks and bilateral aid organizations for self-evaluation. These studies have the advantage of being able to focus sharply on the quality of the aid delivered within a specific country and sector setting. However, they also bear the disadvantage of a lack of representativeness, so that it is difficult to infer broader lessons for other countries – owing to the necessarily small sample sizes. The “Joint Evaluation of Budget Support” (1994-2004), for example, studied the delivery of joint policy-based lending to seven countries in great detail. It found that this modality of lending (viz. that supported by more than one national or multilateral institution) reinforced preexisting macroeconomic stability and it supported fiscal discipline, without hampering tax effort.
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- Revelle, Roger and Hans Suess. 1957. Carbon dioxide exchange between atmosphere and ocean and the question of an increase of atmospheric CO2 during the past decades. Tellus 9, 1827.

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- Tomz, Michael, Gary King and Langche  Zeng. 1999.  RELOGIT: Rare Events Logistic Regression, Version 1.1. Harvard University, Cambridge, MA.

- Tyndall, John. 1861. On the absorption and radiation of heat by gasses and vapours, and on the physical connection of radiation, absorption, and conduction. Philosophical Magazine Series 4 (22), 169-194.

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Weyant, John P. 2004. Introduction and overview. Energy Economics 26 (July), 501-515.

- Whalley, John and Randall M. Wigle. 1991. Cutting CO2 emissions: the effects of alternative policy approaches. Energy Journal 12 (1), 109-24.

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World Bank. 2006. Development Data Platform (electronic). World Bank, Washington.

25
# _LGBTI Survey_

|INSTITUTIONS<br>The Constitution and Nationa<br>Under the Constitution:<br> <br>|Bulgaria<br>l Legislation<br>||Mexico<br>||Morocco<br>|Netherlands<br>|Tanzania<br> <br>||Vietnam<br>|
|---|---|---|---|---|---|---|---|---|---|
|Is there a general<br>nondiscrimination<br>clause?<br>Yes|Constitution of the<br>Republic of Bulgaria<br>(1991), Art. 6 Para. 2|Yes|Constitución Política de<br>los Estados Unidos Mex-<br>icanos (1917), Art. 1|No|Yes|Constitution of the King-<br>dom of the Netherlands<br>(2008), Art. 1|Yes<br>Constitution of the Unit-<br>ed Republic of Tanzania<br>(1977), Arts. 9(g),<br>13(1)(2)|Yes|Constitution of Vi-<br>etnam (2013) Art. 5<br>Para. 2|
|If yes, does it explicitly<br>mention sexual orien-<br>tation as a protective<br>status?<br>No||Yes|Constitución Política de<br>los Estados Unidos Mex-<br>icanos (1917), Art. 1|N/A|No||No|No||
|If yes, does it explicitly<br>mention gender iden-<br>tity as a protective<br>status?<br>No||No||N/A|No||No|No||
|Is there a provision<br>that guarantees equali-<br>ty before the law?<br>Yes|Constitution of the<br>Republic of Bulgaria<br>(1991), Art. 6 Paras. 1,<br>2|Yes|Constitución Política de<br>los Estados Unidos Mex-<br>icanos (1917), Art. 4|Yes|Constitution du Roy-<br>aume du Maroc (2011),<br>Art. 6<br>Yes|Constitution of the King-<br>dom of the Netherlands<br>(2008), Art. 1|Yes<br>Constitution of the Unit-<br>ed Republic of Tanzania<br>(1977), Arts. 12, 13(1)|Yes|Constitution of Vi-<br>etnam (2013) Art. 16<br>Para. 1|
|If yes, does it explicitly<br>mention LGBTI indi-<br>viduals?<br>No||No||No|No||No|No||
|Under national legislation:||||||||||
|Is there a specific law<br>on nondiscrimination?<br>Yes|Protection Against<br>Discrimination Act<br>(2004)|Yes|Ley Federal para Preve-<br>nir y Eliiminar la Dis-<br>criminación(2003)|No|Yes|Equal Treatment Act<br>(1994)|No|No||
|If yes, does it provide<br>protection from dis-<br>crimination on sexual<br>orientationgrounds?<br>Yes|Protection Against<br>Discrimination Act<br>(2004), Art. 4 Para. 1|Yes|Ley Federal para Preve-<br>nir y Eliminar la Dis-<br>criminación (2003), Art.<br>1|N//A|Yes|Equal Treatment Act<br>(1994), Sec. 1(b)|N/A|N/A||
|If yes, does it provide<br>protection from dis-<br>crimination on gender<br>identity grounds?<br>Yes|Protection Against<br>Discrimination Act<br>(2004), Art. 4 Para. 1,<br>Additional Provisions,<br>Sec. 1, Subsection 17|No||N/A|No||N/A|N/A||

Anti-Discrimination Law and Shared Prosperity 65
# **2.1 Sampling Design**

Six industries were chosen for the survey: grocery stores, restaurants and food sales, manufacturing of clothing from wool and cloth, transportation of passengers and cargo, manufacturing of clothing from camelid wool (from llamas and alpacas), and manufacturing of furniture from wood. The industries were chosen to represent a large portion of the self-employed and small employers, and to encompass a diversity of sectors. According to the 2005 MECOVI (Bolivian Living Standards Measurement Survey), the industries chosen include four of the top five industries<sup>3</sup> for urban small and medium enterprises and cover approximately 40 percent of all self-employed and employers.

The sample frame consisted of a geographic information database maintained by the survey firm. This database is based on a census of all economic establishments in these cities carried out in August 2005, and includes enterprises operating within households. This was supplemented with data for the transportation sector on all firms that have registered their cars. This provided a reasonably comprehensive sampling frame for urban areas.<sup>4</sup> The sample was stratified across cities and firm size, in order to include a mix of micro firms (with less than five workers), and small firms with 5-20 workers. The sample used here is almost equally divided across the four cities. Groceries, Food, and Transportation each constitute about 20 percent of the sample, Clothing from wool and cloth and manufacturing from wood each constitute 15 percent of the sample, and clothing from camelids the remaining 10 percent.

# **2.2 Sample characteristics**

Table 1 provides summary statistics for the 469 firms used in this paper. The median firm has been in business for 9 years, although 27 percent have been in business 3 years or

> 3 The only one of the top five industries not covered is construction, where it was felt there was little overlap between formal and informal firms, and where the broad industry grouping is very heterogeneous, covering skilled engineers and architects along with less skilled workers.

> 4 A sample frame was not available for rural areas, and therefore snowball sampling methods were used to survey camelid and wood firms in rural areas. The lack of a representative sampling frame provides a further reason for excluding rural areas in this study.

- 5 -
Table B12: Employment shares across locations

|||Agric|ulture|||Ser|vices||
|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|**Panel A: DOU**|||||||||
|Urban center|-0.507***|-0.494***|-0.392***|-0.133***|0.423***|0.413***|0.315***|0.111***|
||(0.005)|(0.005)|(0.005)|(0.004)|(0.005)|(0.005)|(0.005)|(0.004)|
|Urban cluster|-0.195***<br>(0.006)|-0.191***<br>(0.006)|-0.147***<br>(0.006)|-0.045***<br>(0.004)|0.158***<br>(0.005)|0.155***<br>(0.005)|0.114***<br>(0.005)|0.038***<br>(0.004)|
|**Panel B: DB**|||||||||
|Core|-0.427***|-0.416***|-0.322***|-0.111***|0.358***|0.348***|0.260***|0.093***|
||(0.005)|(0.005)|(0.005)|(0.004)|(0.005)|(0.005)|(0.005)|(0.004)|
|Suburb|-0.326***|-0.316***|-0.239***|-0.079***|0.262***|0.254***|0.182***|0.063***|
||(0.008)|(0.008)|(0.008)|(0.005)|(0.008)|(0.008)|(0.007)|(0.005)|
|Town|-0.079***|-0.076***|-0.048***|-0.018***|0.064***|0.061***|0.036***|0.014***|
||(0.005)|(0.005)|(0.005)|(0.003)|(0.005)|(0.005)|(0.004)|(0.003)|
|Country FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Demographic|No|Yes|Yes|Yes|No|Yes|Yes|Yes|
|Education|No|No|Yes|Yes|No|No|Yes|Yes|
|Employment|No|No|No|Yes|No|No|No|Yes|
|Panel A Adj.R<sup>2</sup>|0.266|0.286|0.372|0.791|0.211|0.227|0.317|0.751|
|Panel B Adj.R<sup>2</sup>|0.232|0.254|0.352|0.789|0.183|0.201|0.303|0.750|
|Nr. of countries|16|16|16|16|16|16|16|16|
|Nr. of hh|119276|119276|119276|119276|119276|119276|119276|119276|

Source: International Urban Poverty Database. Note: *** p < 0.01, ** p < 0.05, *** p < 0.1. Robust standard errors are in parentheses. GHSPOP 1km is used for the DOU and DB method. The dependent variable is a share of household workers employed in a respective sector. The baseline category is “Urban center” in all specifications in Panel A, and “Cores” in all specifications in Panel B. Demographic control variables include household size and household head’s age, sex, and marital status. Education is a categorical control variable that summarizes the education of the household head in seven categories. Employment is a categorical control variable that summarizes the household head’s labor status and employment sector.

70
-7-

positioz. that government infrastructure investment crowds in private investment whereas other public investment crowds out private activitv.'<sup>6</sup> A later study of the effect of public policy on private investment in Turkey by Chhibber and van Wijnbergen used Blejer and Khan's framework, but used actual data on government infrastructure spending.<sup>"</sup> They also calculated real effective interest rates that took explicit account of compensating balances. Compensating balances are a means by which banks circumvent low adrministered interest rates by requiring borrowers to place deposits in non-interest bearing accounts as guarantees for loans,' Their econometric results show significant coefficients for output, the real effective cost of borrowing, and private sector credit as a share of GNP. The other two explanatory variables tried, an index of capacity utilization and the share of infrastructure in total public investment, did not have sigaificant coefficients. They conclude that the effect of governrent policy on private investment is complex and must be analyzed in light of a range of relevant policies including exchange rates and institutional factors such as export promotion programs. The high rate of public investment in Turkey resulted in some inflation and a raising of interest rates; however, it also insured that the economy's adjustment effort was growth-oriented.

In summary, the empirical work on investme:; in developing countries has tended to draw from the standard models in the literature and add elements that are relevant to the economy under 16In contrast, Balassa findb evidence that public investment and private investment are negatively correlated using Blejer and Khan's data set. Balassa, 1988.

**17** Chhibber and van Wijnbergen, 1988.

i<sup>8</sup> Chibber and van Wijbergen use a technique based on the relationship between commercial bank deposits for transactions purposes and commercial bank loans for transactions uses to assess the importance of compensating balances in Turkey. The excess of deposits over uses reflects the importance of compensating balances. See Chhibber and van Wijnbergen, 1988 for a description of a technique originally proposed by Ersel and Sak, 1989.
variations in institutions. Land policies differed across the occupied lands. At various stages, the rulers’ time horizons changed, which affected policies. On the Qing side, fiscal power became decentralized, causing large variations in regional fiscal capacity. All these changes could fundamentally determine long-term regional development (Blattman and Miguel 2010). Third, relative to the cross-country studies of the consequence of conflicts, analysis that uses sub-national units in China offers measurement and research-design advantages (Djankov et al. 2003). Cross-country studies of wars suffer from the selectivity of data: war-torn countries have far less and poorer-quality data; thus, the worst-hit countries are less likely to be represented, reducing the evidence of the impact of war in the very areas where conflict has most probably taken the greatest tolls. We have systematic data at the sub-national level, giving insights into the effects on both war-torn prefectures and other prefectures that were unaffected by the rebellion. Moreover, our data span a period of more than one-and-a-half centuries, and they have the additional advantage of holding constant national-level determinants (i.e., institutions and culture).

To proceed, we draw from the institutional background and the literature to derive hypotheses. We focus on several aspects of the rebellion and Qing’s responses. First, the land policies in the early and the late stages of the rebellion differed markedly. The protection of land property rights was better in the late stage than in the early one, for example. We hypothesize faster post-war population recovery and better long-term development for the late Taiping areas than the early Taiping areas. Second, since the areas near the rebellion’s capital city, Nanjing, were more likely to be viewed as a stationary base for the rebellion, we hypothesize that their governance and policies were likely better than those of other Taiping areas, as Olson’s theory of stationary banditry implies (Olson 1993). Third, the rebellion occurred in years of solid technological progress. We examine whether the loss of life associated with the rebellion ultimately led to the subsequent Malthusian transition, characterized by income growth accompanied by lower population growth (Galor and Weil 2000; Galor 2005; Voigtlander and Voth, 2013b). Fourth, we note that the Qing government instituted fiscal decentralization to finance local militias against the rebel army; thus, we examine whether this fiscal decentralization acted as taxation that hindered trade, or state capacity that facilitated development (Besley and Persson 2009).

We analyze a data set of 266 prefectures in China that were and were not affected by the rebellion. Our data cover the years from 1820 to the present day. We focus on population levels and cross-sectional development outcomes between 2000 to 2010. We examine the rebellion impact on population growth because it is a common measure of long-term development in the 3
7 Additionally, Denizer _et al_ . (2013) do not distinguish between the old style structural adjustment loans (pre-2004) and the newer development policy lending (post-2004), which have marked differences. Denizer _et al._ (2012) argue that “investment projects do better than policy lending operations” because they note a positive and significant coefficient on a variable for “investment projects” (the left-out category being fast-disbursing lending). Denizer _et al._ (2013) also find a positive coefficient on the “investment projects” dummy, although this is significant at the 10% level only in a data set for 1983-2011, whereas using a data set for 1995-2011 it is statistically insignificant, as they acknowledge (p. 293). There is a straightforward explanation for these findings: the failure rate of adjustment loans was higher, at 30.2% (July 1985 to June 2004)<sup>5</sup> , than that of development policy lending at 19.6% on average (from September 2004 onwards)<sup>6</sup> .

The present paper adopts this third type of approach that examines the impact of official financing on specific program/project development results/outcomes. One advantage of this approach is that the larger sample sizes (i.e., the number of projects/programs, often greatly exceeding the number of countries) permit more powerful statistical testing. Another advantage is that this approach enables a focus on quality of the aid/financing delivered.

This paper attempts to contribute further to the understanding of the impact of development financing on intended development outcomes at the program level by focusing solely on policybased lending, and on these operations post-2004. It also attempts to provide further refinements in specifications to important variables used in the literature. For example, calculating a measure of the quality of a task team leader (TTL) is complicated by the fact that projects often have multiple TTLs over their life span, and the World Bank’s electronic data system does not necessarily list the task team leader(s) that took a project or operation to the Board. As a result, previous studies have been limited to the track records of the task team leaders responsible for implementation, rather than identification and preparation, which are more relevant for the outcome of policy-based loans.

# **3. Data, variables and methodology**

> 5 Computations using the Bank’s electronic record system.  “Failure” is defined as in footnote 3.

> 6 Using the data set constructed for the present paper.