rafmacalaba/data-use-mentions-extended huggingface dataset:
# Road density

Road density summaries per administrative area convey useful information about infrastructure coverage but are inexact proxies for accessibility. These data sets must be collated, sometimes tediously, from individual District Transport Master Plans (DTMPs) in Nepal. Given that many Nepali roads operate poorly or not at all due to bad maintenance, simple roadway lengths may obscure poor accessibility caused by quality issues in the roadways (RAP3 2018). Researchers can ameliorate such problems by more detailed modeling of road quality or reliance on a reliably maintained subset of roads (e.g. paved ones), as with Thapa and Shively (2017). But this raises the burden of data collection, introduces sources of error from erroneously reported road conditions or reduces the detail of the metric. Additionally, such models implicitly discount the importance of off‐road travel and the varying difficulty of such travel in different areas.

In any case such a summary measure suffers from the same resolution and repurposing limitations of Remoteness Indices: such summaries enable comparisons between areas but not individual, localized analysis, e.g. calculating the shortest route between a given set of points, or local accessibility to a particular type of service. They also obscure accessibility dynamics within such areas; assessing whether new roads reach an important economic center or just a politically powerful constituency is impossible. Road length summaries _do_ communicate facts about remoteness easily to users and a non‐technical audience can quickly grasp their means of tabulation. By using a common unit of measure (kilometers) they are also easily incorporated into spatial models. Therefore, they balance well cost, technical complexity and communicative value, and may be appropriate to analyses oriented at non‐ technical audiences, especially where data is readily available. Overall however they are less detailed, more abstract and more limited in their applications than cost time models.

# Survey responses

Reported travel times to services from survey instruments are easy to collect within a standard survey instrument but are subject to such instruments’ limitations. To begin, collecting quality survey
# **Abstract**

The empirical literature on environmental performance or compliance has followed two strands: one based on the impact of formal regulation as a means of inducing better environmental performance, and another centered on the role of informal regulation which mainly emphasizes the role of communities and capital markets. In this paper, we analyze the impact of environmental news in print media on firms’ environmental performance. Using data from a survey of industrial facilities in South Korea, probit estimation results indicate that the publication of environmental news in print media _and_ the firm’s awareness of this publication are important predictors of a firm’s environmental performance, more so than environmental laws, regulations, and environmental training. This paper thus reemphasizes the key role of media in influencing firms’ environmental performance.

2
reported professional development in mathematics (SC35Q02). A very interesting variable from a policy point of view regards the incentives for teachers. School principals were asked to what extent performance appraisal or other forms of feedback are related to incentives for teachers in seven different forms, from salary and bonus to public recognition and greater job responsibilities. The answers were to be given on a 4 point scale: ‘No change’, ‘A small change’, ’A moderate change’ and ’A large change’. We converted the rating into a Rasch index, scaled to an OECD mean of 0 and standard deviation of 1. The mean for Dev7 for this index, TCH INCENTV was -0.03 for Dev7 and 0.27 for Vietnam, indicating greater presence of teacher incentives in Vietnam. The final set of variables in Table 6 deal with the way that quality assurance regarding teacher performance is carried out, with help of a mentor, peer, supervisor or external inspector. These variables indicate a higher prevalence of oversight for teachers in Vietnam, with the difference being greatest for external inspections (86.64% in Vietnam compared to 58.82% in Dev7 countries).

# **2.7 Pedagogical Practices**

Pedagogical practices are an outcome of a complex interaction between curriculum and related educational policies, economic possibilities and the cultural and historical context. It is difficult to trace differences in these practices in a quantitative survey.<sup>7</sup> Table 7 presents a few variables that seek to capture variation in pedagogical practices. They indicate the higher prevalence of national policies in Vietnam regarding the use of computers in the classroom and the use of a standardized curriculum that specifies what has to be taught each month. There is no difference with regard to the use of a single textbook. There is some difference in the use of formative student assessment, with slightly higher percentage of use of assessments to monitor teachers and schools in Vietnam. COGACT represents an OECD-PISA index variable based on response
locative role of the financial sector (Fisman and Love 2007). We compute these different financial needs for narrowly defined industrial sectors and match them with the disaggregated product-level data on international trade. Given that the explored transmission channels might operate differently in the short term and long term, we examine export survival at time horizons ranging from one to ten years. We also allow for the possibility that the size and the activity of domestic stock markets play different roles in shaping export survival at the product level.

Our three main empirical findings are as follows. First, well-developed stock markets rather than strong banks are key in promoting export survival of products from industries with a high share of intangible assets. This result supports the notion that stock markets have an advantage over banks when it comes to promoting innovative sectors of the economy that face increasing returns to scale and a pronounced technological change (see, e.g., Allen 1993; Aghion et al. 2004; Brown, Martinsson, and Petersen 2013, 2017; Hsu, Tian, and Xu 2014). Second, _active_ stock markets play the most important role for the export survival of products with high liquidity needs, possibly reflecting the role active stock markets have in monitoring the efficiency of working capital management (see, e.g., Gill and Biger 2013; Ben-Nasr 2016; Zeidan and Shapir 2017). By contrast, _large_ stock markets are often dominated by banks in promoting these products, especially when it comes to long-term export survival. Third, trade credit operates as a substitute for external finance from banks but not from stock markets. In addition, this substitution works only for _long-term_ export survival, suggesting that the channel can successfully operate only alongside well-established export links where exporters and their foreign customers already enjoy the mutual trust necessary for an extensive use of trade credit.

Overall, our results suggest that banks, large stock markets, and active stock markets all play different roles in shaping product-level export survival, depending on the examined transmission channel and the time horizon
productivity by 1.0 percentage points in 1992 while it increases productivity by about 0.9 percentage points in 1994.

This particular time-pattern in the regression coefficients -- starting negative and becoming (more) positive -- suggests the following interpretation. Initially, the allocation of financing favored subsequently worse performers, as the soft budget hypothesis would suggest. Politicians thus appear to have influenced bank lending by directing it to loss-making enterprises, leading to a negative relationship with subsequent enterprise restructuring. In later periods, relatively more financing went to firms which subsequently improve more. This suggest that the financial system improved as banks became more discriminating in their lending decisions and lent more to deserving firms, i.e., firms which subsequently improved. Banks thus appear to have become more independent of politicians over time, i.e., their loans became less subsidies and more genuine investments leading to productivity growth.

Comparing regressions with and without the bank financing variables (the latter is not reported) show that the inclusion of the bank lending variable does not diminish the importance of privatization. The privatization coefficients are significantly positive in both regressions and stay about the same while the explanatory power increases. This suggests that privatization and the imposition of financial discipline are complements rather than substitutes and lends further support to the SV model. It also suggests that once the initial productivity gains from privatization are obtained, financing becomes important to sustain TFP-growth.

Including the amount of net transfers each firm receives from the government as a separate variable does not change the privatization coefficients. The coefficients for SUBS are consistently negative, suggesting decreasing productivity growth by between 3.3 and 1.4 percentage points for each 100% change in subsidies. The coefficients do decline over time, however, suggesting that the allocation of subsidies has become more rational and the role of politicians in allocating subsidies has declined. Furthermore, since subsidies tend to be concentrated in only a few firms, especially in the later years, the magnitude of the overall effect of subsidies on overall enterprise
is to identify those features – denoted as _X_ – that offer most predictive power. Some approaches, such as stepwise regression, perform the selection simultaneously with model building, but the two tasks can also be split.

5. _Modelling._ The modelling step involves the development of a supervised learning model _f_ ( _X_ ) that predicts consumption per household member. Below we expand on the PMT approach to variable selection and modelling, and then propose an adjusted algorithm.

6. _Targeting survey & prediction._ Operationalizing a PMT requires the set of variables X to be queried from a list of potential beneficiaries. In addition to the features, this survey may include household characteristics that determine categorical programme eligibility, such as the number of school-age children, verification of household characteristics or identity via inspection of administrative documents. The model _f_ ( _X_ ) is applied to produce consumption estimates for the set of potential beneficiaries. Combining categorical and socio-economic eligibility, the list of beneficiaries is determined either by a ranking of household values (in case of a beneficiary quota) or via an absolute threshold that assigns eligibility if a given household’s income falls below it.

To consider the link between these steps and the design considerations outlined before, note that both cost and verifiability are influenced by the questionnaire design of the targeting survey. The number and detail of questions and the associated verification routines are an important cost lever, especially in urban areas where travel times between households are short for enumerators. In terms of the PMT process shown in fig. 1, verifiability is considered in the pre-selection step. The variable selection aspect of the modelling step also influences costs by shrinking the volume of questions. The implicit policy objective of the PMT algorithm is to achieve the best possible accuracy for a set of pre-selected questions. As such, the emphasis of the standard PMT approach is accuracy, rather than on cost reduction.

The focus of this paper is on modelling, but note that targeting survey design and eligibility determination are also impacted by modelling choices:
prices. However, its size depends on the estimate of pass-through of competitors’ RERs, the correlation of RERs and also their variances which means the size of the bias will likely vary across samples and countries.

**Competitors’ Prices** The main mechanism in the model works through changes in foreign competitors’ prices — I show that pass-through of foreign competitors’ prices is around 0.6 to import prices, and 0.16 to US producer prices. Quantitatively, the model is able to explain about a third of this for import prices and two-thirds for producer prices. As an extension in Section 6, I also show that importing firms respond particularly strongly to the prices of US firms in the same sector and, to a lesser extent, other compatriot firms’ prices. This is consistent with a general model of variable markups discussed in Section 2.

1.1. **Related Literature.** My empirical evidence and multi-country model are related to a broad class of models of incomplete pass-through surveyed in Burstein and Gopinath (2014), where a firm’s markup is falling in its price relative to some aggregate/sectoral price (described in Section 2).<sup>5</sup> An empirical role for competitors’ RERs is consistent with this broad class of models, so long as the aggregate/sectoral price is correlated with competitors’ exchange rates.

The results presented here are complementary to contemporaneous work by Auer and Schoenle (2016) and Amiti et al (2016). Using novel market share data, Auer and Schoenle (2016) show that in industry aggregation models and the BLS microdata, own cost pass-through is U-shaped in firm market shares, and competitors’ price pass-through is hump-shaped in firm market shares. Although Auer and Schoenle don’t discuss pass-through of competitors’ exchange rates — and I don’t discuss market shares — one might expect that many of the firms responding to competitors’ prices in Auer and Schoenle are the same firms responding to competitors
# **5. Conclusions**

Accurate measurement of employment is at the heart of designing effective policies that improve economic opportunities for the poor and alleviate gender inequities in access to and returns from productive activities. Leveraging two national surveys that were implemented concurrently in Malawi with different approaches to respondent selection in collecting individual-disaggregated survey data, we find that compared to the best practice of conducting private individual interviews to elicit self-reported information on labor outcomes, the business-as-usual approach that allows for proxy respondents and group/non-private interviews leads to significant underreporting of employment in livestock-related activities and household non-farm enterprises (in management and worker capacity). The effects are stronger for women and under a recall period of 12 months, as opposed to 7 days. The business-as-usual approach also brings about under-reporting in the incidence of wage employment among men.

We further discuss how underreporting is associated with a higher incidence of proxy reporting under the business-as-usual approach, as well as potential difficulties — given less time spent with enumerators — that respondents may face in interpreting and reporting on work that may be seasonal, such as casual wage work, as well as work in enterprises (as evidenced by greater discrepancies in reporting across the labor and non-farm enterprise modules under the businessas-usual approach, with more pronounced differences for women). The extent of under- and overreporting is also systematically associated with household wealth (greater under-reporting of nonfarm enterprise employment for the highest wealth quintile, for example), highlighting the importance of respondent selection on specific socioeconomic subgroups as well as by gender.

23
Table <u>3: Association between household consumption expenditure per capita and wealth</u>

||OLS|OLS|FE|FE|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Household Wealth|0.347***|0.329***|0.099***|0.090**|
||(0.027)|(0.030)|(0.037)|(0.044)|
|Constant|8.111***|8.130***|8.478***|8.646***|
||(0.031)|(0.033)|(0.031)|(0.311)|
|Round FEs|YES|YES|YES|YES|
|Fixed Effects (FEs)|WOREDA|EA|HH|HH|
|Controls|NO|NO|NO|YES|
|R-squared|0.348|0.362|0.021|0.069|
|# of EAs|433|433|433|433|
|N|13391|13391|13062|12937|

_Notes:_ This table provides estimates of the partial association between logarithm of total household consumption expenditure per capita and “started log” of household wealth score. Household sample weights from the ESS2 applied. All columns control for round fixed effects. Further, column (1) controls for woreda FEs, column (2) controls for EA FEs, and the other two columns control for household (HH) FEs. Column (4) additionally controls for 12 time-varying characteristics. The coefficient estimates for these 12 control variables are not reported here, but can be available on request. The overall and the within R-squared are given in the first
WPS3915 RURAL-URBAN MIGRATION IN DEVELOPING COUNTRIES: `A SURVEY OF THEORETICAL PREDICTIONS AND EMPIRICAL FINDINGS<sup>∗</sup> Somik V. Lall**, Harris Selod<sup>+</sup> and Zmarak Shalizi<sup>**</sup>

- ** _Development Research Group, The World Bank_ , 1818 H St. N.W. Washington DC 20433, USA

- + _INRA (Paris-Jourdan), CREST and CEPR_ ,

- 48 boulevard Jourdan, 75014 Paris, France.

# World Bank Policy Research Working Paper 3915, May 2006

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> ∗ This research has been co-funded funded by a French Consultant Trust Fund and the Development Research Group of the World Bank. We thank Laurent Gobillon for helpful comments. Author contact information: Lall (slall1@worldbank.org); Selod (selod@ens.fr); Shalizi (zshalizi@worldbank.org)

1
<!-- Start of picture text --> Regional Trade of Selected Selected Regions<br>50.3<br>35.9%<br>30.%<br>25.30<br>20.%<br>15.%10.%10.%<br>59%<br>fm ~ an ms<br>5s 56 6s 6865s 8 &B S288 85 8 42 8<br>aoofo&#ofo&# FR &A A A FR A A A A RR A A<br>meee Seo) meme CEM AC AC ee FAC ee ECOWAS «© eee WAEML<br><!-- End of picture text --> <!-- Start of picture text --> ooo World Export Shares of Selected Export Shares of Selected Shares of Selected of Selected Selected Regions (2002-2016) (2002-2016)<br>8.00%<br>800%<br>5.00%<br>4.00%<br>3.00%<br>200%;; ee<br>1.00% ee eww ww ww 8 ow www en<br>eeso8so88 2 ge 8 8 eats —————2s2s a g<br>8 8 8 & 8 & RRR RR RR RA<br>ma ASEAN me CEMAC ee EAC ee ECOWAS mee VIERCOSUR me WAEMU WAEMU = == 3 regions regions<br><!-- End of picture text --> <!-- Start of picture text --> ooo World Export Shares of Selected Export Shares of Selected Shares of Selected of Selected Selected Regions (2002-2016) (2002-2016) Regional Trade of Selected Selected Regions<br>8.00% 50.3<br>800% 35.9%<br>5.00% 30.%<br>4.00% 25.30<br>3.00% 20
In conclusion, the results from the 2SLS estimates indicate that there is a twoway causality between market-oriented reforns and freedom. These estimates also confirm the crucial role of freedom as a precondition for introducing economic reforms: countries that entered ithe transition process with more democratic institutions and greater civil liberties have been able to implement faster and more comprehensive reform policies.

# **Robustness of the Results**

To test the robustness of our results, in particular on the importance of freedom as a precondition for liberalization, we estimate the same model adopting a different measure for the intensity of economic reforms: we use the liberalization indicator compiled by the EBRD. We aggregated the various indicators published in the EBRD's Transition Report to construci- **_EBRDINDEX._** Unfortunately, since this measure is available only since 1994, initial freedom is measured in 1993 **_(FREEDOM1993)._** Figure 2 plots the value assumed by **_EBRDINDEX_** in 1997 against freedom in 1993 for our sample of countries, indicating a clear positive linear relation between the two variables.

**Figure 2. Liberalization and Initial Freedom**

<!-- Start of picture text --> 20 - FWgary<br>C lovakia d land.<br>Crc*ia "~Slovenia<br>1 -vMcedonia rgiJthuania<br>oD KazakhstA Ro 4 ,rnenia ulgria<br>Nbldava Alb tani<br>_~ 12 - e zerbaijan<br>Q az~~~~bekistaii<br>m - urkrenistan<br>W 8 -Tajikistan<br>#elarus<br>4 -I<br>0 5 10 15<br>Freedom 1993<br><!-- End of picture text --> 16
process for the RAMV census and PEP, including whether each member had PEP (in any version), its issue date, perceived benefits, and reasons why they had registered in RAMV and PEP or had not. Next, the questionnaire included a labor module following the design of the Colombian Labor Force Survey ( _Gran Encuesta Integrada de Hogares_ ) to make it comparable to existing administrative data on monthly and weekly income; this module also collected data on labor history in Venezuela and Colombia. Fourth, the survey included a module on health and access to healthcare that included the EQ-5D-3L, a standardized scale used to assess health across different dimensions, including physical and mental health, via a Likert scale.<sup>9</sup> The final module offered information at household level on these dimensions: (i) migration, (ii) integration into Colombian society and connections with migrant networks, (iii) prosocial preferences, (iv) housing, and (v) expenditure and remittances.

The qualitative findings informed the survey design and data collection protocols. First, during the focus groups, forced migrants reported that although Venezuelans and Colombians both speak Spanish, there are important differences in everyday words and terms that make it difficult for Venezuelans to understand information from local authorities and NGOs. For this reason, Venezuelans reviewed the survey to ensure appropriate language usage. Second, forced migrants also reported high levels of mistrust because they fear deportation and are often targeted by scams and misinformation via text and social media. To build trust and enhance participation, all surveys were administered by Venezuelan enumerators, many of them forced migrants themselves. Furthermore, Venezuelan migrant organizations disseminated information on the objectives and scope of the survey.

On average, the survey was administered over an average of one hour and 40 minutes, and respondents received an incentive of 27,000 Colombian pesos (about $USD 9) for participating. As most forced migrants are excluded from the financial system, it was hard to deliver the incentives during data collection. For