rafmacalaba/datause-encoder-data huggingface dataset:
23 THE INTENSIVE MARGIN IN TRADE first, and hence average exports per firm increase with a decline in _τij_ . Since this also increases the number of firms that export (and hence total exports), the result is a positive IME.

We now explore the magnitude of the implied IME in the case where _gi_ ( _φ_ ) is lognormal for every origin country _i_ . Assuming that _gi_ ( _φ_ ) is lognormal with location parameter _μφ,i_ and scale parameter _σφ_ , and letting Φ( _·_ ) be the CDF of the standard normal distribution, then Letting _h_ ( _x_ ) _≡_ Φ<sup>_′_</sup> ( _x_ ) _/_ Φ( _x_ ) be the ratio of the PDF to the CDF of the standard normal, Bas et al. (2015) (henceforth BMT), show that where ̄ _σφ ≡_ ( _σ −_ 1) _σφ_ . Combined with 1 _− Gi_ ( _φ_<sup>_∗_</sup> _ij_<sup>) =</sup><sup>_Nij/Ni_, we have</sup> Thus, the average to minimum ratio of exports per firm for country pair _ij_ only depends on the share of total firms in _i_ that export to _j_ , with the relationship given by the function Ω( _·_ ). As argued by BMT, Ω( _·_ ) is an increasing function, which is consistent with the observation by Melitz (2003) _φ_ ̃( _φ_<sup>_∗_</sup> _ij_<sup>)</sup> above that _φ_<sup>_<u>∗</u>_</sup> _ij_ is decreasing in _φ_<sup>_∗_</sup> _ij_<sup>since</sup><sup>_Nij/Ni_is decreasing in</sup><sup>_φ∗_</sup> _ij_<sup>.</sup> Given values of _σ_ ̄ _φ_ as well as _Ni_ for every country, we can use our data on _Nij_ to compute Ω( _Nij/Ni_ ) for all country pairs. Combined with _xij_ ( _φ_<sup>_∗_</sup> _ij_<sup>)=</sup><sup>_σFij_and imposing</sup><sup>_Fij_=</sup><sup>_F o_</sup> _i_<sup>_F d_</sup> _j_<sup>, we</sup> can use equation (27) to get the model-implied average exports per firm (in logs), In contrast to Observation 1 for the Melitz-Pareto model, under under lognormality we will have a positive IME even with _var_ ( _F_<sup> ̃</sup> _ij_ ) = 0.

We can also compute model-implied fixed and variable trade costs similarly to what we did under the assumption of Pareto-distributed productivity. First, we obtain _F_<sup> ̃</sup> _ij_ from
**Table 2: Estimates of the impact of the change in market access on the change in cropland area**

||(1)<br>OLS|(2)<br>OLS|(3)<br>FE|(4)<br>FE|
|---|---|---|---|---|
|Δ Ln MA_t_|0.019***|0.127***|0.033***|0.088***|
||(0.00)|(0.00)|(0.00)|(0.00)|
|Shrinking cropland_t-_1||-0.346***||-0.205***|
|||(0.00)||(0.00)|
|Δ Ln MA _t_ × shrinking cropland_t-_1||-0.336***<br>(0.01)||-0.272***<br>(0.01)|
|Ln C _t-_1||-0.064***<br>(0.00)||-0.328***<br>(0.00)|
|Avg. rainfall_t_||0.117***<br>(0.00)||-0.201***<br>(0.01)|
|(Avg. rainfall _t_)<sup>2</sup>||-0.011***<br>(0.00)||0.016***<br>(0.00)|
|Ln pop. density _t_-1||-0.129***<br>(0.00)||-0.350***<br>(0.01)|
|Ln dist. to major port||-0.002**<br>(0.00)|||
|Constant|0.012***|-0.164***|0.011***|0.825***|
||(0.00)|(0.01)|(0.00)|(0.01)|
|Country×year dummies|No|Yes|||
|Observations|1,161,664|1,160,235|1,161,664|1,160,235|
|Number of groups|||290,416|290,130|
|R-squared|0.000|0.164|0.000|0.141|

Notes: This table presents estimates from OLS (columns 1 and 2) and fixed effect (columns 3 and 4) regressions of the change in the natural logarithm of the cropland area between years _t_ and _t –_ 1 on the change in the natural logarithm of market access between year _t_ and _t –_ 1 ( _Δ Ln MA t_ ). Controls included in the OLS regression (column 2): dummy variable indicating a decrease in cropland during the previous period ( _Shrinking cropland t-_ 1), interaction term between the change in the natural logarithm of market access and the dummy variable ( _Δ Ln MA t_  _Shrinking cropland t-_ 1), natural logarithm of lagged cropland area ( _Ln Ct-_ 1), average precipitation over the period ( _Avg. rainfall t_ ) and its square, natural logarithm of lagged population density _(Ln pop. density t-_ 1), natural logarithm of distance to nearest major port ( _Ln dist. to major port_ ), country dummies, year dummies, and country × year dummies. Controls included in the FE regression (column 4): dummy variable indicating a decrease in cropland during the previous period, interaction term between the change in the natural logarithm of market access and the dummy variable, natural logarithm of lagged cropland area, natural logarithm of average precipitation over the period, and natural logarithm of lagged population density. Robust standard errors are in parenthesis, where *** is significance at the 1% level, ** significance at the 5% level, and * significance at the 10% level.

13
Eaton, J., S. Kortum and F. Kramarz (2004). “Dissecting Trade: Firms, Industries, and Export Destinations.” American Economic Review, Vol. 94, No. 2, pp. 150-154.

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25
substitution,<sup>15</sup> as well as the elasticities of flexible input demand with respect to changes in output and capital stock.<sup>16</sup> These elasticities are given by and Estimated elasticities have a standard economic interpretation and capture several separate substitution effects, including within-firm input substitution and within-industry compositional changes.<sup>17</sup> Because we include countryspecific fixed effects, and identify coefficients, _β,_ based on within-country variation over time, the operational response elasticities, _ηjj,_ and, _ηpj,_ capture short-run equilibrium effects. On the contrary, the investment elasticities of input efficiency of capital stock with respect to input price changes, _φ_<sup>_j_</sup> _,_ and exogenous technological change, _ζ,_ incorporate the dynamics of the capital stock and capture medium- and long-run equilibrium effects.

# **3 Data**

The vintage capital model is estimated using panel data from 19 OECD countries between 1990 and 2005 separately for five manufacturing industries - food,

> 15We have also estimated Allen’s and Morishima’s partial elasticities of substitution. Because these elasticities have less straightforward interpretation (Frondel 2004), and can be directly inferred from estimated cross-price elasticities, their estimates are not reported.

> 16To calculate these elasticities one needs the estimates of translog function (12), which is estimated separately.

> 17Sorting out between these effects is however beyond the scope of this paper.

15
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The results of this study reveal that a person who is richer, better educated, doing regular health checks, facing lower future income uncertainty, having relatives diagnosed with cancer, having a higher degree of trust in medicine, or feeling a higher degree of need for the medicine, has a higher WTP in general. VSL estimates are higher for women than men and are higher for younger people. They are also different for different regions in China.

Even though this study can help to provide a better understanding of WTP for risk reduction and VSL, as one can see from the analyses above, this study cannot give a conclusive result for VSL that can be used for policy analyses in China. This study also challenged the validity of some of the previous CV studies on VSL, such as Wang and Mullahy (2006) and Hammitt and Zhou (2006). A more systematic research on VSL is warranted.

19
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Rodrik, Dani. 2016. “Premature Deindustrialization.” _Journal of Economic Growth_ 32, 1-33.

32
Importantly, surveying a segment of the population that operates on the border of legality carries challenges with sensitivities. Non-response is not uncommon. To ensure the participation of respondents, it is important to go beyond convincing them that their responses will be anonymized. In particular, it is important to provide assurances that the information will not be used for prosecution. Questions should be formulated in ways that are the least invasive to respondents. Given these challenges of implementation, the team that implements the survey must be thoroughly trained to administer the questionnaire in the form of a conversation. This not only increases the participation of informal businesses in the survey, but also avoids respondent reticence. The need to approximate a conversation during the survey interview further emphasizes the importance of simplicity throughout the questionnaire.

# **2.3 Questionnaire Composition**

The Informal Sector Enterprise Survey questionnaire was developed following the principles outlined above. It covers a range of socio-economic topics that not only provide a granular picture of informal businesses and their owners, but also discern salient patterns and features of a typical informal business. While the exact set of questions asked during interviews changes across countries, a core set of questions has been consistently asked, enabling crosscountry analysis. In particular, informal businesses are asked about their origin—who started it, the source of initial funding, with questions probing whether or not it was out of the necessity for additional income. A sizeable part of the questionnaire is dedicated to exploring the background of the owners, age, gender, education, household environment, their experience with formal jobs, whether they immigrated from a different region/country, and other aspects of their life that provide information about owners' resources and opportunities as they relate to the informal business.

During the interview, informal businesses are asked questions about their operations in general, along with detailed questions about sales and employment (separating paid and unpaid workforce), collecting information for regular, the slowest, and the busiest months to account for the extent of seasonality that the informal businesses may face. The cost-benefit aspects of the location chosen by informal businesses are also explored. The experience of informal businesses with the physical infrastructure is probed through detailed questions about electrical outages or insufficient water supply incidents.

8
As property prices in the worst affected areas reduced the most, low income households responded by moving into low-rent housing being offered in these locations. On the other hand, middle income households moved away to avoid risk, and the wealthy, for whom insurance and self-protection was the most affordable, did not change where they lived.

Poor people “sort” into low rent locations – which are often at higher risk to natural hazards. The problem is particularly acute in developing countries where there is a divide between the formal and informal markets for land. While formal developments may respect land use regulations, informal settlements are often located in hazard prone locations, such as on hill slopes, close to river banks, or near open drains and sewers. In Dhaka for example, informal settlements are developing across the metropolitan area, with many residents lacking basic public services and in locations at risk from flooding. In fact, most informal settlements do not have access to a public toilet within 100 meters, and 7,600 households in 44 slums live within 50m of the river (World Bank 2005, Dhaka Urban Poverty Assessment).

For the city of Bogotá, we use the same database discussed earlier to examine if poor people are at greater risk from natural hazards – particularly earthquakes. By collecting data on the location of properties, income levels of households, and linking this to information on hazard risk, we find evidence that poor people face disproportionately high burden of hazard risk, as they sort into high density low rent properties, which are located in higher risk locations. Figure 6 shows the distribution of seismic risk on the left panel and residential location of the poor households in Bogotá.<sup>5</sup> In comparison, Figure 7 shows the spatial distribution of the richest twenty percent of the city’s households. From these maps, it becomes clear that poor households are located in areas with higher earthquake risk, which are towards the western and southern parts of the city. On average the city’s poor live in locations that have twice the seismic risk compared to where rich households live.

> 5 We include households who fall in the lowest twenty percentile of the city’s income distribution.

19
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36
# **B. Generation and transmission planning index for Vietnam and comparators, 2015**

||**Colombia**|**Peru**|**Philippines**|**Vietnam**|**International**<br>**benchmark**|
|---|---|---|---|---|---|
|**Planning and Procurement**|95%|77%|59%|59%|70%|
|**Generation Planning**|86%|43%|71%|71%|56%|
|Countryhas ageneration masterplan|||||94%|
|Countryhas an overall energy plan|||||65%|
|Competent entityis responsible forproducingthe|||||88%|
|Inter-governmental committee oversees theplanning|||||29%|
|Powergeneration systemplan is mandatory|||||19%|
|Plan leads to timelyinitiation ofprocurement|||||38%|
|Planning process is transparent andparticipatory|||||59%|
|**Transmission Planning**|100%|75%|50%|100%|72%|
|Competent entityis responsible forproducingthe|||||100%|
|Explicitlylinked topowergenerationplans|||||88%|
|Plan is mandatory|||||29%|
|Planning process is transparent andparticipatory|||||71%|

# **C. Generation and transmission procurement index for Vietnam and comparators, 2015**

||**Colombia**|**Peru**|**Philippines**|**Vietnam**|**International**<br>**benchmark**|
|---|---|---|---|---|---|
|**Procurement of Generation**|95%|90%|100%|50%|85%|
|There is a framework forprocurement|||||82%|
|Country allows International competetive bidding or<br>public auctions forprocurement|||||94%|
|Types ofprocurement methods allowed||||||
|_Unsolicited bids_|||||29%|
|_Direct negotiation_|||||47%|
|_International competitive tendering_|||||88%|
|_Public auctions_|||||41%|
|_Stand-alone capacity market_|||||0%|
|Auction design score|0.86|0.71|NAP|NAP|80%|
|_Country usespublic auctionsforprocurement_|||||41%|
|Clear and comprehensive established rules|||_NAP_|_NAP_|100%|
|Crediblepenalties for violatingthe rules|||_NAP_|_NAP_|86%|
|Guarantees andpenalties to ensure timelycompletion|||_NAP_|_NAP_|86%|
|Standard,non-negotiable contracts|||_NAP_|_NAP_|86%|
|Stapled financingterms or risk mitigation instruments|||_NAP_|_NAP_|86%|
|the auction|||_NAP_|_NAP_|14%|
|Efforts to inform and attract bidders to the auction|||_NAP_|_NAP_|100%|
|**Transmission Procurement**|100%|100%|17%|17%|64%|
|There is a framework for procurement of new<br>transmission lines|||||59%|
|Methods used toprocure new transmission-|||||69%|
|_Competitive tender_|||||65%|
|_Direct negotiation_|||||24%|
|All projects are awarded to the incumbent<br>transmission company|||||47%|

Satisfactory result Unsatrifactory result NAP Not applicable NAV Not available 44