rafmacalaba/data-use-mentions-extended huggingface dataset:
monitors can help provide policy results that are better aligned with the regulatory data.

Data from a spatially dense network of low-cost monitors can be calibrated using at least one regulatory-grade monitor to improve the measurement of PM2.5 levels and of policy impacts. Investing in a combination of low-cost and regulatory-grade monitors can improve the air quality data used for policy evaluation. In the absence of data from regulatory-grade monitors, the results suggest that satellite data can be used to calibrate the PM2.5 measurements from a network of low-cost monitors, although the results may not be as accurate in terms of measurement of PM2.5 levels or policy impacts as when calibrated with regulatory-grade data.

# **6 Conclusion**

In this paper, we compare and evaluate the three principal sources of PM2.5 data in Dakar, Senegal. We find that the low-cost monitors report substantially lower PM2.5 levels due to incomplete measurement of dust and that, at higher levels of temporal aggregation, PM2.5 levels derived from satellite data are closely aligned with PM2.5 levels from regulatory-grade monitors. Using mobility restrictions during COVID-19, we show that all three data sources provide similar estimates of the impact of a policy on PM2.5 at the city-level, particularly when measured in percent changes instead of levels. Finally, we show the value of investing in at least one regulatory-grade monitor. Developing a context-specific calibration formula provides substantial improvement over off-the-shelf calibration formulas in aligning the data from low-cost monitors with data from regulatory-grade monitors. Faced with budget constraints, an air pollution monitoring system based on one well-maintained regulatory-grade monitor complemented with a dense network of low-cost monitors can provide PM2.5 data with high spatial variation that can also be used to accurately estimate the impact of policies. Barring any data from regulatory-grade monitors, calibration of PM2.5 measurements from low-cost monitors using satellite-based estimates of PM2.5 can improve the measurement of PM2.5 levels and policy impacts as long as the calibration is conducted at a lower temporal frequency.

Our results have important implications
5 TRADE, TRANSPORT, AND TERRITORIAL DEVELOPMENT India, we shut down this channel in our model (Munshi and Rosenzweig, 2016; Kone et al., 2018). Instead, internal and external trade costs shape economic activity in our model through movement of labor across sectors _within a region_ .

The rest of the paper is organized as follows. In Section 2, we describe the data and present some stylized facts about the spatial distribution of organized manufacturing in India. Motivated by these facts, Section 3 develops a model of production and trade that combines both internal and external trade costs. In Sections 4 and 5, we provide evidence that is supportive of the model. Section 6 concludes.

# **2. Spatial Distribution of Organized Manufacturing in India: Stylized Facts**

## **2.1 Data**

We use the same plant level information as much of the prior research on the Indian economy, including Duranton et al. (2015) and Ghani et al. (2016). Our main data source is the Annual Survey of Industries (ASI), the annual survey of organized sector manufacturing plants undertaken annually by the Central Statistical Organization, a department in the Ministry of Statistics and Program Implementation, Government of India. We use information on real output, employment and the number of plants for the following years: 1989, 1994, 2000, 2005 and 2009. These plant-level variables are aggregated to the level of a district (details in Appendix B). Following a routine data cleaning exercise, we have an unbalanced panel of an average of 344 districts per year.

We complement the manufacturing data from ASI with population data from the 1991 Census. This data is used to create district-level weights when running the regressions. External trade cost is measured using data on output tariff and effective rate of protection (ERP) from Topalova and Khandelwal (2011), while internal trade cost is measured as distance from the GQ highways.

## **2.2 Stylized Facts**
EApop�� P�EA���� ∑���� EApop�� _PEA_ (1 1)+ _PEA_ (2 1)+ _PEA_ (3 1)+ ....+ _PEA_ (n j)= 1 for each stratum within a pre-war region P�EA��� is a probability of selection for an EA in a specific stratum (Urban or rural) and pre-war regions (e.g. rural Bari), _i_ is an EA number, _j_ is the regional stratum type. EApop�� is the population within an EA in a specific regional stratum, EApop�� is the sum of EAs’ population within a regional stratum, _n_ is the number of EAs within a regional stratum.

# **2.7 Comparison between Manual PESS urban EAs and our automated approach Urban EAs**

In UNFPA’s 2014 PESS, no Rural EAs were created, and the urban EAs were manually digitized based on high-resolution Google Earth Imagery. We compared the results of our automated methodology against those manually digitized EAs in urban areas in both Mogadishu and Hargeisa cities. Since the boundary of PESS urban EAs and their household size are confidential, we were unable to publish a complete comparison. Instead, we compared the distribution of population size and EA area between automatically and manually generated Rural EAs. The population and area were also computed for PESS urban EAs based on our high-resolution gridded population data sets and the populations and area of EAs within Hargeisa and Mogadishu cities were compared.

# **3. Results: Somalia case study**

# **3.1 Rural EAs**

# **3.1.1 Description of results from our split and merge algorithm**

A total of 253,833 polygons were created in Somalia rural areas after the splitting process. After applying the region merging technique in a rural area, 113,367 EAs were created, with population size ranging from 0 to 750 and a maximum area of 9 km2 (
also applies to quantities. We thus re-computed the volatility for quantities both for individual commodities and manufactures. Figures 6 shows that our main result i.e. that individual commodity prices are less volatile than those of manufactures, holds for import quantities as well.

# **IV.C. Homogeneous versus Differentiated Products**

Rauch (1999) provided an intuitive classification of homogeneous and differentiated goods which goes to the heart of the economic distinction. Homogeneous goods are those which are traded globally in organized exchanges, whereas differentiated goods are those that are not. An intermediate category in Rauch (1999) is composed of goods for which no formal exchanges (organized markets) exist, but for which there are “reference prices.” Rauch provided a concordance between the Standard International Trade Classification (SITC) and his three categories. We used the SITC-HS concordance table in order to then classify our sample of products into Rauch’s three groups. In our sample, 95 percent of manufactured goods appear in the bin of differentiated goods, whereas only 35 percent of commodities were classified as differentiated products. Thus there was a notable overlap, albeit not enough to overturn the main findings: Figure 7 indicates that the most volatile products are differentiated manufactured goods.

# **IV.D Measurement Errors**

One potential caveat to our results is that measurement errors in the unit values may be an important driver of the difference in the observed – as opposed to the true-- price volatility 13
1.2 related literature 7

Stein & Daude (2002) and Daude & Stein (2007) use a broad set of “institutional” variables to find that regulatory burden is an important determinant of FDI location. They draw on a wide range of sources: i) World Governance Indicators (WGI) developed by Kaufmann et al. (2010); (ii) International Country Risk Guide (ICRG) variables on the risk of repudiation of contract, risk of expropriation, corruption, rule of law, and bureaucratic quality; (iii) La Porta et al. (1999)’s index of shareholder rights, and (iv) World Business Environment Surveys on taxes and regulations, policy instability, and corruption.

Bénassy-Quéré et al. (2007) use 2001 survey data from the French Finance Ministry to find that effective bureaucracy and low corruption, among others, attract FDI. Kinda (2010) brings to bear firm-level data to find that institutional problems, together with poor infrastructure and financing constraints discourage FDI in a sample of 77 developing countries. Mottaleb & Kalirajan (2010) use panel data from 68 low-income and lower-middle income developing countries to show that open countries that rely on trade, have large GDP, high growth rate, and are business-friendly tend to be more successful in attracting FDI.

Alfaro et al. (2008) explain the “Lucas Paradox” of inadequate capital flows from rich to poor countries. Despite rates of return being higher in countries where capital is scarce, they argue that poor countries do not receive investment from abroad because of institutional weaknesses. But there are exceptions. Fan et al. (2009) attribute record inflow of FDI into China in recent decades, in spite of the indifferent quality of the country’s institutions, to its stewardship of sustained economic growth.

While this literature confirms the salience of specific institutional variables, it suffers from limitations relating to model mis-specification and variable mismeasurement. The studies mentioned above do not address the problem of sample selection that arises when the pairing
in many key dimensions of poor food access and monetary poverty to overlap.

Specifically, this section adopts the simple framework presented in Jensen and Miller

> 8The FIES is based on a nearly identical measure developed by the United States Department of Agriculture and expanded globally in the Gallup World Poll in 2014 (e.g., Coleman-Jensen et al. 2021). 9Specifically, using the raw score in this way is only possible if the data satisfy the underlying assumptions of the Rasch model, which underpins the FIES approach. Specifically, the infit statistics should range between 0.7 and 1.3 (FAO 2016).

> 10The FIES module and the individual questions on food access can be found at ”https://www.fao.org/in-action/voices-of-the-hungry/fies/en/” (accessed July 2022).

> 11As mentioned above, the initial surveys in which the measure was captured did not include other food access metrics and did not include a variety of other household information that would help to more fully validate the measure. There have been validations of the measure in the United States (e.g., National Research Council 2006; etc.), and some similar measures have been more extensively validated in specific contexts (e.g., Coates et al. 2006; etc.).

9
<!-- Start of picture text --> Madagascar<br>Mozambique<br>50%<br>45%<br>50%<br>40%<br>35%<br>40%<br>30%<br>25%<br>30%<br>20%<br>1997 2003<br>1996 2001 2006 2011 Headcount Gap<br>Headcount<br><!-- End of picture text --> _Source: Authors’ calculations using DHS and MICS._ These results may imply the effects of different policy interventions. Overall, the fact that in most cases the headcount and gap are moving in the same direction (and improving) is supportive of the fact that the policies in place have been effective for all the children below the reference line, not just those closest to it. For example, countries like Colombia that have lowered both the stunting headcount and stunting gap may have targeted their interventions to all children and brought them above, or closer to, the reference line (Figure 1a). Likewise, a country for which the gap is improving but not the headcount may have targeted its interventions to the most malnourished, and the effects of this targeting are not showing up yet on the headcount (Figure 1b). By contrast, if a country wants to prioritize its efforts and investments towards those children who are the closest to the reference line, this would be consistent with an improving headcount without necessarily seeing improvements in the gap measures (Figure 1b).

Figure 1 only provides a handful of examples. To have a comprehensive understanding of the differences in trends in the headcount and gap measures across all developing countries, it is 10
urban dis-amenities in developing countries are similar for pollution and congestion. Our results point to an elasticity of pollution and congestion with respect to city density to be 45 percent and 16 percent respectively in developing countries (compared to 48 percent and 18 percent for developed countries).<sup>15</sup> By contrast, the elasticity of crime, measured by the homicide rate, with respect to city built-up density is significantly higher at +24 percent in developing countries compared with -56 percent in developed countries. The latter suggests that if crime is accounted for in measuring the advantages of locating agglomerations, the net benefits in developing countries would be much smaller.

As a robustness exercise we use city population density from census data (instead of build-up density) for each country.<sup>16</sup> . The results are presented in the Appendix Table A4. Although we find somewhat lower urban cost elasticities for pollution (18 percent overall) and higher for congestion (26 percent), the key messages do not change. We find that the levels of congestion, crime and pollution are larger in developing economies, but the urban cost elasticities are not discernibly different between developing and developed countries.

**_Table 7: Urban cost elasticities and cost levels - across developed and developing countries_**

|Outcome:|**Log PM2.5**|**Pollution**|**Log Hours L**<br>**Ti**|**ost to Travel**<br>**me**|**Log Hom**|**icide Rate**|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Developing Country|0.150|0.252**|0
administrative areas. The skewed distribution principally reflects factors other than country size, since the rank correlation of country area and small-occurrence region species count is only 0.40.

5.4 Global Variations in Territorial Clustering Resources for habitat protection are scarce, so protection is most cost-effective in areas inhabited by occurrence region species on the World Bank country map that includes 38,229 level-2 administrative assign each species to the subnational administrative level 2 (henceforth WB2) unit that has the largest share of its habitat. After assigning all species, we compute WB2 species counts and order each country’s WB2s in descending order by count. We compute the cumulative count and identify the WB2s that collectively account for 90% of the country’s small-occurrence region species. We divide the number of identified WB2s by the total number of WB2s in the country to obtain a concentration measure for smallrespectively. In each table, the rows divide countries into four groups by WB2 concentration.

Table 8: Small-occurrence region species spatial clustering by size class, These are administrative entities that have level-2 units mapped by the World Bank. Lower income countries concentrations by World Bank income classifications
used in the wrong proportions given their prices and marginal products (allocative inefficiency), or both. We do not try to disentangle the two, instead presenting an estimate of overall inefficiency.

Suppose we have data from multiple service-delivery units. We can then generate a scatterplot of _C_ (or average cost) against _y_ —the space of the standard total (or average) cost curve chart in a microeconomics textbook. In services like education and health, it is important
.22|
|Sugar|0.12|0.30|0.08|0.09|0.11|0.19|
|Rest of Food, Beverages and Tobacco|5.89|15.02|3.75|4.11|5.13|9.67|
|Textiles, Leather, Wood, Paper & Editing|3.28|8.25|9.68|2.61|2.89|5.76|
|Gasoline|0.35|0.59|0.28|0.06|0.39|0.45|
|Diesel|0.68|1.20|0.69|0.14|0.87|0.91|
|Biodiesel|0.0037|0.0095|0.0022|0.0009|0.0056|0.0059|
|Bioethanol|0.0001|0.0001|0.00004|0.00002|0.0001|0.0001|
|Refineries: other products|0.90|1.96|0.16|0.21|1.29|1.31|
|Other manufacturing industries|12.13|16.41|59.22|9.02|9.66|16.60|
|Transport|6.19|6.29|11.54|6.38|5.77|6.53|
|Trade, construction & Services|55.97|41.57|12.77|72.15|53.68|47.40|
|Totals|100.00|100.00|100.00|100.00|100.00|100.00|

Source: Own elaboration based on INDEC Biodiesel is a small sector according to 2006 data, but is growing steadily. Though there were many investment projects ongoing, there was no production
12 system, such as early retirement ages and wide coverage, have remained intact and why discussions on possible reforms have remained limited. Thus the first basic question to examine is whether this view is realistic and whether the country can restore the old pension benefit schemes once the economy recovers? If not, two questions arise: would the pension system be sustainable if one were to keep its most recently introduced features or should one envisage deeper structural reforms ?

# 4.1. Methodology and Basic Assumptions

# _A. The Model_

To address these questions, a simulation model has been constructed. It integrates four modules: pension fund, labor market, macroeconomic, and demographic modules (see **Appendix** A for a detailed description of the model). The model covers the period 1995-2030 and provides a consistent framework for analyzing the balance of the Pension Fund under current provisions as well as for assessing the impact of various policy reforms. It allows for taking into account the interactions between the social security system and other key economic variables The Pension Fund module calculates the Fund balance for each year based on expenditure and contribution data provided by the other modules. The number of pensioners depends on demographic factors and eligibility rules set by the pension system. The level of contributions to the fund depends not only on the level of employment, wages and the social security tax but also on the relative importance of the informal sector. It is assumed that workers in the informal sector do not contribute to the pension fund although they may be future beneficiaries either because they have accumulated rights in the past (prior to, or in the early stages of the transition) or because they are eligible for social pensions under the present set of regulations. The Pension Fund is linked to the consolidated government account. So a large and persistent deficit can undermine fiscal balance and threaten macroeconomic stability.

The labor market module defines trends in employment and real wages responding to the evolution of macroeconomic conditions. It calculates total labor income in the formal economy. This
the institutions and services faced by the typical medium-size firm in a country—not on cases where there might be “special conditions or privileges,” such as for firms located in a free trade zone. In Bangladesh, for example, a garment manufacturer located in an export processing zone might be able to clear a container of raw material imports within a day. But for a garment manufacturer located outside the zone, it would take 9 days to clear a similar container through customs alone and another 8 days for port and terminal handling through Chittagong port. It is this case, indicating conditions in Bangladesh for a typical manufacturer, that the survey was designed to capture. To guide the responses of practitioners to reflect these “on the ground” physical, policy-related, and

> 4 Paul Roberts (a former faculty member and director of the Massachusetts Institute of Technology’s Center for Transportation and Logistics) and Peter Yee (with Consilium International Inc.) were involved in designing this questionnaire.

> 5 Panalpina, with a worldwide network of offices and agents, was the primary provider of the data. In some countries other forwarding agencies provided supplementary information.

> 6  Selected key logistics indicators for the remaining 60 countries are also available.  The data for the 80 countries were more comprehensive especially on the cost figures.

7
to Russian ships. Commitments within the context of WTO accession should provide significantly greater access to multinational service providers in these key sectors.<sup>5</sup> In order to estimate the ad valorem equivalence of barriers to foreign direct investment, we first commissioned surveys in telecommunications; banking, insurance and securities; and maritime and air transportation services by Russian research institutes that specialize in these sectors. Using these surveys as well as supplementary data, Kimura, Ando and Fujii<sup>6</sup> employed the methodology explained in the volume by C. Findlay and T. Warren (2000) to estimate the barriers to FDI in the Russian services sector.

For each of these service sectors, authors in the Findlay and Warren volume evaluated the regulatory environment across many countries; the same regulatory criteria were assessed for all countries in a particular service sector. 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 services. Assuming that the international regression is valid for Russia, and using their surveybased assessment of the regulatory environment, Kimura, Ando and Fujii estimated the _ad valorem_ equivalent impact of a reduction in barriers to foreign direct investment in these services sectors. The results are reported in table 2.

> 5   We estimate that the barriers in air and maritime transportation are higher than in other sectors, due to strong barriers to operation within Russia in these sectors. But since there is less international pressure in these sectors for cuts in these barriers, we believe that WTO accession will not have as significant an effect in these sectors.

> 6 The three papers by Kimura, Ando and Fujii as well as the underlying questionnaires are available at <u>www.worldbank.org/trade/russia-wto.</u>

12
can assess performance on the universe of relevant actions. Our findings suggest that providing incentives for some actions also increases effort on unlisted actions by 4 pp, or 14 percent, which is indicative of complementarities in production.

Third, our paper also contributes to research contrasting the effects of loss or gain framing in contracts. This distinction is scientifically and practically important, as penalties can be politically and logistically challenging to implement because they involve withholding or recovering payments. Some experimental evidence—including from LMICs—suggests that identical incentives can be more effective if cast as penalties for poor performance rather than as rewards for good performance because of loss aversion (Kahneman and Tversky, 1984; Kahneman et al., 1991; Fryer et al., 2012; Hossain and List, 2012; Imas et al., 2017; Bulte et al., 2020, 2021). In contrast, other research suggests that framing does not matter very much in general settings (de Quidt et al., 2017; de Quidt, 4