rafmacalaba/datause-encoder-data huggingface dataset:
suggest that policymakers can change the distribution of students’ academic performance by rearranging the groups in which these students interact without changing the marginal distribution of inputs into the education production function. This is attractive in any setting but particularly in resource-constrained developing countries. While the external validity of any result is always questionable, my findings may be particularly relevant to universities serving a diverse student body that includes both high performing and academically underprepared students. This is particularly relevant to selective universities with active affirmative action programs (Bertrand, Hanna, and Mullainathan, 2010).

The examination of peer effects under random assignment also points to fruitful avenues for future research. As in Carrell, Sacerdote, and West (2013), peer effects estimated under random assignment do not robustly predict the effects of a new assignment policy and residential peer effects appear to be mediated by students’ patterns of interaction. This highlights the risk of relying on reduced form estimates that do not capture the behavioral content of peer effects. Combining peer effects estimated under different group assignment policies with detailed data on social interactions and explicit models of network formation may provide additional insights.

# **References**

- Abadie, A. (2005): “Semiparametric Difference-in-Differences Estimators,” _Review of Economic Studies_ , 72, 1–19.

- Abdulkadiroglu, A., J. Angrist, and P. Pathak (2011): “The Elite Illusion: Achievement Effects at Boston and New York Exam Schools,” Working Paper 17264, National Bureau of Economic Research.

- Angrist, J., and K. Lang (2004): “Does School Integration Generate Peer Effects? Evidence from Boston’s Metco Program,” _American Economic Review_ , 94(5), 1613–1634.

- Arnott, R. (1987): “Peer Group Effects and Educational Attainment,” _Journal of Public Economics_ , 32, 287–305.

- Athey, S., and G. Imbens (2006): “Identification and Inference in Nonlinear Differencein-differences Models,” _Econometrica_ , 74(2), 431–497.

- Becker, G. (1973): “A Theory of Marriage: Part I,” _Journal of Political Economy_ , 81, 813–846.

- Benabou, R. (1996): “Equity and Efficiency in Human Capital Investment: The Local Connection,” _Review of Economic Studies_ , 63(2), 237–264.

- Bertrand, M., R. Hanna, and S. Mullainathan (2010): “Affirmative Action in Edu-

37
|Actual|(6)|-.001<br>(.0006)_∗∗_<br>-.001<br>(.002)|.014<br>(.006)_∗∗_|.003<br>(.007)<br>.011<br>(.003)_∗∗∗_|27778<br>.005|.178|_ponds to higher_|_he p-value of an_||
|---|---|---|---|---|---|---|---|---|---|
|Requested|(5)|-.006<br>(.001)_∗∗∗_<br>-.002<br>(.002)|.014<br>(.006)_∗∗_|.0009<br>(.006)<br>.026<br>(.004)_∗∗∗_|27778<br>.024|.123|_o. Lower ranks corres_|_The last row reports t_||
|Actual|(4)||.015<br>(.006)_∗∗_|.003<br>(.007)<br>.006<br>(.001)_∗∗∗_|27778|.14|_ed a value of zer_|_evel of the frm. _||
|Requested|(3)||.020<br>(.007)_∗∗∗_|.0006<br>(.006)<br>.012<br>(.001)_∗∗∗_|27778|.029_∗∗_|_rker and frm are assign_|_of the worker and at the l_|_uggestion are the same._|
|Actual|(2)|-.002<br>(.0006)_∗∗_<br>-.001<br>(.002)||.012<br>(.004)_∗∗∗_|27778<br>.006||_ighest ranked wo_|_ring at the level _|_and the random s_|
|Requested|(1)|-.006<br>(.001)_∗∗∗_<br>-.002<br>(.002)||.027<br>(.004)_∗∗∗_|27778<br>.024||_of model 2. The h_|_for two-way cluste_|_of the algorithmic _|
|||Firm ranking of workers<br>Worker ranking of frms|Algorithm suggestion|Random suggestion<br>Const.|Obs.<br>Efect size: max to min rank|Algorithm = Random|_Notes: This table report the estimates _|_numbers. Standard errors are corrected_|_F-test of the hypothesis that the efect _|

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- 52 -

# FOOTNOTES

1. The calculation includes non-agricultural as well as agricultural debts.

2. The fifth village, being too large tc cover, required a more limited but systematic sample of one side.

3. See Shipton 1987, Appendix on research methods, for more details.

4. Our informants in the 1988 survey, by language, were Mandinko (36Z), Fula (28Z), Wolof (21Z), Jola (82), Serahuli (42), and others (3Z). In the 1983 national census, not a wholly reliable source but the best available, the largest ethnic groups in The Gambia were listed as follows: Mandinko (40.4z), Fula (18.8Z), Wolof (14.62), Jola (10.32), Serahuli (8.2Z), and others (7.7z) including Arabic-speaking Mauritanians (Gambia 1986: 8). International seasonal labcr migrations, among other things, make census-taking difficult. Some have also questioned whether the national census may have under-enumerated Fula for political reasons.

5. I hope to discuss in another study some of the interethnic similarities and differences in Gambian economic life.

6. The clash of cultures in the area of interest rates and ratios is discussed more fully in Shipton 1990a.

7. Patrilineages are kin groups related through males. The castes are in-marrying occupational categories whose members, recruited by heredity, may or may not practice the specified occupations. See Diop 1981 on Wolof castes and their economic importance.

8. See the essays in Moock 1986 on other parts of the continent.

9. For livestock counts see Derman et al. 1985: 112; Mills et al. 1988, Sumberg 1988, Sumberg and Gilbert 1988. As elsewhere in Africa south of the Sahara, livestock loans and (among some groups) secrecy about numbers owned makes livestock tallies difficult.

10. Marriage payments among Gambian peoples are paid mainly in cash and manufactured goods, however, not in cattle as among many eastern African groups.

11. Analogies between livestock and cash are common. When I once asked a Mandinko informant why he preferred large to small stock, he asked, "Would you rather have a 10 dalasi note or a 25?' -- an argument he knew was hard to refute without pedantry. Mandinko say their grandparents historically referred to livestock as fangkanta (lit. self-guard), or reserve; they use the same term now for personal cash savings.

12. This applies to other permanent, heritable lineage property like compounds.
from 1973 to 1990 while those in large plants rose by only 18 percent.<sup>12</sup> By 1987 there was only a small gap in wages (excluding fringe benefits).'<sup>3</sup> Forty-seven garment exporters were surveyed, 27 in Bogota, 10 in Medellin and 10 in Bucaramanga. The largest number were founded in the 1980s (24), a few before the 1970s, and 12 in that decade. About two-thirds of the sampled firms began with less than ten workers, and over a third with less than five (Table 4). The average size at present is 134 worker; the median is sixty.<sup>14</sup> Eight firms have reached a level of 200 workers or more; none of these was less than ten years old and the average age was twenty-three.

The importance of the export market to these firms varies widely. Exports average 28 percent of sales, with 19 of 44 exporting firms exportingjust 1-10 percent of sales, the same number exporting 11-60 percent, four exporting 61-80 percent, and just two exceeding 80 percent (with one of these at 10 percent)).<sup>5</sup> Only four of the 47 firns began to export before 1980, although 19 were founded before that date. Another eight started to export during 1980-87, but the great bulk (33 of 45) began in the burst of activity from 1988 to the preseni Just four of the 47 firms began exporting the year they were founded, four maore one year later, and three more two years later. In general it would appear that few of the garment firms we surveyed were created with the explicit and primary plan of exporting.

Nearly two-Thirds ofthe sampled firms (29 of 47) subcontract work out Subcontacting is no doubt .o encouraged by Colombia's inflexible labour legislation on fiing and seniority, though how important this factor is in relation wo others is less clear. Most of these (21) do so only for specific processes (including assembly, embroidery and sewing), but often on a substantial scale.<sup>16</sup> Of the eight firms subcontracting "2 The increase in average wages of 27 percent between 1973-86 was much greater than the 5.2 percent for manufacturing as a whole.

13 At one-half the level of wages, the fringes are lower than in other sectors of Colombian manufacturing, where in 1989 the average ratio was 83 percent.

14 Sales ranged from about US $15,000 (10 million pesos) to US $25 million (15,000 million pesos), averaging _$1.5_ million (or about $1.1 million withou **t** he largest firm).

"Two finns did not export in 1992, citing the unpromising international market (due to the peso revaluationof 3 percent and the world economic recession) and the need to protect their position in the domestic market against imports as the liberalization proceeds. "<sup>6</sup> SE4A, through the National Textile Center (Centro Nacional Textil) in Medellin and other branches of SENA, is the main extenal source of tramining for the textile and garment industries. It provides training for worker,. supervisors, and technicians in the repair and maintenance of gannent equipment, although the latter service 11
became unionized.<sup>2</sup> According to a survey of almost 600 human resources managers, Cheng and Yang (2010) find that the new Law significantly raises the likelihood of signing contracts, extends the term of contracts, increases the number of open-ended labor contracts, and leads to more cautious recruitment and dismissal decisions. This increases labor costs and restricts labor flexibility to some extent, but the impacts vary among enterprises with different size and ownership. Based on interviews with enterprise managers, Li et al. (2009) investigate the competitiveness of China’s labor-intensive industries after the implementation of the Labor Contract Law. They find that the new Law does not increase the costs of lawabiding enterprises, helps to maintain an orderly employment system, and should not reduce labor demand.

This paper first introduces the two data sources used for analyses of the paper, and then proceeds to a discussion of the implementation of the Law. Next, in section 3, descriptive evidence from both surveys suggests that the Law likely contributed to reversing a trend toward informality in employment relationships, and that this is supported by strong awareness of the Law’s provisions among workers and the sharp increases in labor disputes. Section 4 reviews the implications of the Law’s implementation for both employment and social insurance coverage of China’s urban workers, and a final section concludes.

# **2. Data**

In this paper, we analyze newly collected data from household and firm surveys designed by the authors. The first is urban household survey data from the third wave of the China Urban Labor Survey (CULS) collected in early 2010 by the Institute of Population and Labor Economics (IPLE) of the Chinese Academy of Social Sciences (CASS). Surveys also were conducted in the same five large cities for the first two waves of the CULS conducted in

> 2 A main concern about the survey is its use of an unconventional sampling strategy: workers were intercepted on streets outside work areas and the number of workers sampled per firm was restricted to three or fewer.

5
mobile telecommunications services and maritime transportation services. 12 We supplemented this information based on the policy notes discussed in section II. The Telecommunications Management Group (2007) provided extensive details in telecoms. These questionnaires and papers provided us with data and descriptions and assessments of the regulatory environment in these sectors. In the case of professional services, a World Bank team commissioned separate surveys of the regulatory environment in several East African countries, including Tanzania. These surveys were conducted by local consultants, who interviewed the professional associations in the in 2009. For reasons discussed below, we used engineering services as our proxy for all professional services.

Mircheva (2008) then estimated the ad valorem equivalents of barriers to foreign direct investment in fixed line and mobile telecommunications, banking, insurance and maritime transportation services. The process involved converting the answers and data of the questionnaires into an index of restrictiveness in each industry. Mircheva followed the methodology of Kimura, Ando and Fujii (2004a, 2004b, 2004c) to generate these estimates. The methodology involves classification of the possible restrictions into separate categories with unique weights summing to one, where the weights are determined based on the significance of each category. Next, Mircheva assigned a score to each potential restriction, where the score reflects the level of restriction imposed by the economy. Mircheva estimated two indices: an index of “regulatory barriers” (RB index) where the regulatory barriers impose costs on both domestic and multinational firms in a non-discriminatory manner; and an index of discriminatory barriers against multinational service providers, which we call the foreign discriminatory index (FDR index).13 This methodology further involves building on the estimates and methodology explained in the volume by C. Findlay and T. Warren (2000), notably papers by Warren (2000), McGuire and Schulele (2000) and Kang (2000). For each of these service sectors, the authors evaluated the regulatory environment across many countries. The price of services is then regressed against the regulatory barriers to determine the impact of any of the regulatory barriers on the price of

> 12  We thank Mr. Cyril Pesha and his law firm associates in Dar es Salaam for leading this research effort.

> 13 In order to obtain the estimated score for each restriction, the assigned score is multiplied by the corresponding weight. Finally, the estimated scores for all categories are summed to obtain the restrictiveness indices.

24
4 How we selected our sample of firms was crucial for the broader validity of our policy judgements. The key decision was to target the empirical analysis on successes: successful countries, successful subsectors, successful firms. The underlying presumption was that the economic institutions identified by firms as important for successful outcomes are themselves at least reasonably efficient.BI The research followed the lead of other analyses,2/ and used direct or indirect participation in export markets as the primary criterion of success (although, as will be seen, in conducting the research it was not possible to adhere rigidly even to this criterion of export-orientation).

While in general the presumption that the.institutions identified by firms as efficient were indeed so seems reasonable to us, the reader can continully test any policy judgements we draw from our evidence by posing questions as to the cou uribcua. Key questions to keep in mind include: Given that the SMEs surveyed inleed appear efficient is it probable that, in the absence of some co'<sup>1</sup> ective institution identified as impormtan **t** , heir performance would have worsened? Alternatively, should there be reason to qution whether the. surveyed firms indeed are economically efficient, is it nonetheless probable that any collective institution deemed to be making a positive contriLution would still be socially useful in an environment populated by. economically efficient firms?

In principle, variations across subsectors in their tecihologies and patterns of indusrial. .orgnization might influence the role of collective supports. Similarly,. their role could be affected by -variations across countries in the levels of development of their private sectors, and .the manner of their integration into the world economy. To account for these variations, we sampled across a broad range of countries and subsectors.

-- -

* -

. / This presumption is standard in the economic analysis of institutions. See, for example, -Oliver Williamson's (1985, 1975) analyses of transactions costs, and Douglass North's (1981) 3nalysis of the relatonship between property rights and economic growth. While at the limit applications of the presumption can degenerate into tautologies, with careful design it is possible to formulate empirically testable propositions.

92/ For example, Pack and Westphal (1986), Krueger (1984), and the World Bank's recn (1993) study of the _East_ Asia miracle.
in theoretical and actual transfers _within_ municipalities.

# **4 Empirical results**

## **4.1 Validity tests**

One potential concern about the validity of the fuzzy RD design we adopt is potential _−_ manipulation of the running variable for example, if local governments were able to attract more inhabitants to obtain larger transfers, or manipulate the IBGE population estimates sent to the TCU. As we noted above, the way in which IBGE population estimates are constructed makes these sources of potential manipulation unlikely. Even if the official population figures released to obtain the transfers were subject to manipulation, the use of IBGE estimates (rather than TCU data) as an instrument would remove this problem.

We nevertheless inspect for manipulative sorting by formally testing for the presence of discontinuities in the density of IBGE population estimates at the population thresholds we use in our empirical analysis. In line with McCrary (2008), we test for the existence of a density discontinuity at these thresholds by running kernel regressions of the log of density separately on each side of the threshold. We consider all seven thresholds pooled, and also examine the four initial ones separately (for which we have a larger number of observations in the vicinity of each threshold).<sup>10</sup> The results are reported in Figure 2 and do not show evidence that municipalities sort just above the FPM thresholds.

In addition, we perform balance tests on several time-invariant municipal characteristics (reported in the first six columns of Table 5). In the presence of nonrandom sorting, some of these characteristics would likely differ systematically between treated and untreated municipalities around each threshold. The attributes we examine are the area of the municipality (measured in squared Km) and its geographical location (altitude, latitude, longitude, and distances to the state and federal capitals). We inspect for balance by testing for the presence of discontinuities in these attributes at the pooled thresholds. Reassuringly, we do not

> 10Throughout the empirical analysis, we use municipality-year data for the 2000-2006 period, and each municipality enters the estimation sample only once in each year.

13
All industry characteristics (ExFj, CapIntj, HumIntj) are computed solely from the US data and thus do not vary across the exporting countries. The US market is large, diversi...ed, well-functioning, and comparably frictionless. Industry characteristics based on the US data can thus be interpreted as exogenous technological characteristics that are not driven by various imperfections prevalent in many countries. This idea comes back to the seminal paper of Rajan and Zingales (1998).

We compute the export survival in the US market and the remaining productrelated variables from the BACI<sup>9</sup> dataset developed by the CEPII and described in Gaulier and Zignago (2009). The dataset provides harmonized bilateral trade ‡ows for more than 5,000 HS 6-digit products and 143 countries, over the 19882005 period. In the following, we focus on the 1995-2005 period due to the high number of missing values before 1994, and we consider only exports of manufactured products and tobacco to the USA.<sup>10</sup> Export ‡ows are reported annually in values (US dollars) and quantities. This highly detailed level of information is particularly suitable for survival analysis. Aggregation could introduce a considerable bias, essentially hiding individual export failures at the product level.

The product-related variables include the value of export to the US market in the initial year of the trade relationship t0 (initial_exportckt0), in log terms. This re‡ects the level of con...dence US importers have in the reliability of their trading partner. Additionally, we include the total export value of product k from country c to all countries in the initial year of the trade relationship (total_exportckt0), in log terms. This variable captures the experience the exporting country has in supplying the world market with product k. We also control for the degree of competition for a given product on the US market, incorporating the number of countries exporting product k to the USA in the initial year of the trade relationship (NSupplierskt0). Finally we account for trade relationships with multiple spells, including a multiple spell dummy that takes value one if the spell is a higher order spell (multiple_spellck). This last regressor does not vary according to the

> 9BACI is the French acronym for “Base pour l’Analyse du Commerce International”: Database for International Trade Analysis. See http://www.cepii.fr/anglaisgraph/bdd/baci.htm.

> 10We are using BACI in HS from 1992 that covers the period 1994-2005. As the survival analysis relies on the length of export spells, we cannot use the data from the initial year. This leaves us with the data for 1995-2005 available for survival analysis.

13
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also, the response in employment after the crisis. Results from the event study based on data from the GLSS are shown in Figure 3. First, I do not find any statistically significant differences in the trends in employment between high (treated) and low (control) access districts prior to the crisis. This provides support to the identification strategy that the estimated drop in employment during the crisis is uncorrelated with underlying differences between treated and control districts prior to the crisis. Secondly, between 2013 and 2016 (the crisis period) employment rates fell on average<sup>42</sup> by 7.2 pp relative to the reference period (2006).<sup>43</sup> Interestingly, the employment rate in 2017 (a year after the crisis ended), was about 5.6 pp lower than the reference year: an indication of a slow recovery rate in employment– and plausibly the economy– after years of exposure to the crisis.

The foregoing analysis provides additional causal evidence of the negative effects of electricity outages on employment.

# **4.3.2 Nigeria**

Nigeria is among the leading African countries with the lowest levels of reliability in electricity supply. According to data from the World Bank Enterprise Survey, about 77.6% of Nigerian firms report experiencing outages<sup>44</sup> compared to the SSA average of 75.6. The number of power outages experienced by Nigerian firms in a typical month is 32.8 compared to the SSA average of 8.5. Given this, to what extent is unreliable electricity supply constraining employment in Nigeria?

I leverage unique household panel data from the Nigerian General Household Survey (GHS) to explore the effect of unreliable electricity provision on employment in the country using a fixed effect model specified as follows:

> 42the estimates for 2013 and 2016 are 6.7 pp and 7.2 pp respectively

> 43Since the crisis started briefly in the fourth quarter of 2012, I decided against using 2012 as the reference period.

> 44Based on 2014 data. See https://www.enterprisesurveys.org/en/data/exploreeconomies/2014/ nigeria#infrastructure

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