rafmacalaba/datause-encoder-data huggingface dataset:
Banerjee, Abhijit V., and Esther Duflo. "The economic lives of the poor." _Journal of Economic Perspectives_ 21.1 (2007): 141-168.

Blundell, Richard, Luigi Pistaferri, and Itay Saporta-Eksten. "Consumption inequality and family labor supply." _American Economic Review_ 106.2 (2016): 387-435.

Chetty, Raj, and Adam Looney. "Consumption smoothing and the welfare consequences of " social insurance in developing economies _. Journal of Public Economics_ 90.12 (2006): 23512356.

Das, Jishnu, Jeffrey Hammer, and Carolina Sánchez-Paramo. “The impact of recall periods on reported morbidity and health seeking behavior.” _Journal of Development Economics_ 98.1 (2012): 76-88.

De Weerdt, Joachim.“Risk-sharing and Endogenous Network Formation.” in Dercon, S. (ed.) _Insurance Against Poverty_ (2004), Oxford University Press, pp: 197-216.

De Weerdt, Joachim, and Stefan Dercon. "Risk-sharing networks and insurance against illness." _Journal of Development Economics_ 81.2 (2006): 337-356.

Dercon, Stefan, and Pramila Krishnan. “In sickness and in health: Risk sharing within households in rural Ethiopia.” _Journal of Political Economy_ 108.4 (2000): 688-727.

Fadlon, Itzik, and Torben Heien Nielsen. Family Labor Supply Responses to Severe Health Shocks. No. w21352. National Bureau of Economic Research, 2015.

Fafchamps, Marcel. “Solidarity Networks in Preindustrial Societies: Rational Peasants with a Moral Economy”, _Economic Development and Cultural Change_ , 41.1 (1992): 147–74.

Falco, Paolo, William F. Maloney, and Bob Rijkers. “Heterogeneity in Subjective Wellbeing: An Application to Occupational Allocation in Africa.” _Journal of Economic Behavior and Organization_ 111, (2015): 137-153.

Falco, Paolo, Andrew Kerr, Pierella Paci, and Bob Rijkers (2014) Working toward Better Pay : Earning Dynamics in Ghana and Tanzania, Washington DC, World Bank.

Falco, Paolo, Andrew Kerr, Niel Rankin, Justin Sandefur, and Francis Teal. “The Returns to Formality and Informality in Urban Africa”. _Labour Economics_ , 18 (2011): S23-S31.

<mark>Genoni, Maria Eugenia. “Health shocks and consumption smoothing: Evidence from Indonesia.”</mark> _<mark>Economic Development and Cultural Change</mark>_ <mark>60.3 (2012): 475-506.</mark> Gertler, Paul, and Jonathan Gruber. “Insuring consumption against illness.” _The American Economic Review_ 92.1 (2002): 51-70.

Ghana Statistical Service “Women and Men in Ghana: a Statistical Compendium” (2014): 35
|**Country &**<br>**Region**|**Author(s)**|**Infrastructure Type**|**Multiplier Type**|**Multiplier (direct and**<br>**indirect effects)**|
|---|---|---|---|---|
|United States<br>(Montana)|Comings_et al._<br>(2014)|(i)Photovoltaic<br>projects<br>(ii)Wind & energy<br>efficiency|Employment|5 - 9 jobs<br>1.5 jobs|
|United States|Crandall_et al._<br>(2007)|Broadband|Employment|293,000 jobs|
|World|<br>IEA (2020a)|Investment (for $1<br>million):<br>(i) Building retrofit,<br>efficient buildings, PV<br>(ii) Grids<br>(iii) Urban transport<br>and high-speed rail<br>(iv) Gas-fired plants|Employment|10 - 15 jobs<br>5 - 8 jobs<br>7 - 12 jobs<br>4.5 jobs|
|World|IEA (2020a)|Capital spending (for<br>$1 million):<br>(i) Solar PV<br>(ii) Wind power<br>(iii) Upgrades and<br>construction at<br>hydropower<br>(iv) Nuclear lifetime<br>extensions<br>(v) Biofuels and<br>recycling<br>(iv) New vehicles,<br>appliances and<br>batteries|Employment|3 constr & 6 manufacturing<br>jobs<br>1 constr & 1.5 manufacturing<br>jobs<br>3 jobs<br>2-3 jobs<br>11 – 12 jobs (advanced<br>economies), 29 - 46 jobs (the<br>rest of world)<br>6 – 9 jobs (advanced<br>economies),<br>9 – 15 jobs (the rest of the<br>world)|

*includes induced effects in addition to direct and indirect effects

_Source:_ Compiled by authors Table 3 presents the income and employment multiplier results for studies focusing on different countries for the various sub-components of infrastructure investments. Despite the broad variation in estimates across countries, and the fact that a small number of studies refers to developing countries, we can draw a few general insights. Low employment multipliers are typically associated with sectors with high wages and with relatively complex, capital intensive projects whereas sectors with low wage employees and low material costs usually generate high employment multipliers (International Energy Agency, IEA, 2020a).

Transportation spending has often played a prominent role in government efforts to stimulate the economy during downturns. For instance, of the estimated US$ 825 billion over ten years in the American Recovery 14
As we will show in this paper, market reforms have been another important source of another important source of change in environmental performance. The reforms have shifted production away from state-owned-enterprises and toward larger plants. With these changes have come substantial increases in productive efficiency and o decreases in the cost of abating pollution, both important sources of declining pollution intensity. These two factors may have had as great an impact on industrial pollution as changes in direct regulation.

<!-- Start of picture text --> Atmospheric ~~~Sulfur Dioxide. Emissions _ andI I<br>Atimospheric Concentration in Chinese Cities, 1991-1993<br>cn 2.5<br>C 2<br>C<br>O0<br>3 3.5 4 4.5 5 5.5 6<br>S02 Emissions (Log)<br><!-- End of picture text -->

**Figure 1: S02 Emissions and Air Pollution in Chinese Cities**

Although the general trend is positive, there remain great regional disparities in industry's environmental performance. In provinces with stricter regulation and a strong commitment to economic reform, many industrial facilities have already shown the way to a cleaner future. However, the legacy of the past remains strikingly apparent in thousands of highly-polluting plants. With industry expected to maintain rapid growth during the next 20 years, a steep decline in pollution intensity will be necessary just to keep emissions constant.

The consequences of current pollution are tragically apparent in public health statistics for polluted areas. As we will show, the best available evidence suggests that approximately 4,000 people suffer premature death from pollution-related respiratory illness each year in Chongqing; 4,000 in Beijing; and 1,000 in both Shanghai and Shenyang.<sup>2</sup> If current trends persist, we project large cumulative losses in human life through 2020. Figure 2 illustrates the grim stakes: Beijing could lose nearly 80,000 people, Chongqing 70,000 and other major cities could suffer losses in the tens of thousands.

> **2** These estimates are based on the dose-responsr **e** lation established for atmospheric S02 in Beijing and Shenyang by Xu, et. al. (1994). This relation is combined with monitoring data on S02 concentrations to produce estimated individual probabilities of premature mortality by city. City-specific probabilities are multiplied by **current** population estimates to produce estimated annual deaths.

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# **3.4. IS THE POVERTY ENLIGHTENMENT JUST A SPURIOUS CORRELATION?**

A final concern regarding the poverty enlightenment is that the rise in mentions may have been mere coincidence; it could have been driven by a generalized increase in the usage of many other words besides those related to poverty and inequality. We provide evidence to discard this possibility by examining the evolution of terms belonging to two miscellaneous thematic categories. The first one is related with ideals (such as justice, freedom, and prosperity), while the second one related with war, military and the church. These evolutions are presented in Figure 8.

## **Figure 8. Prevalence of miscellaneous terms in presidential speeches**

_(% of speeches that contain each keyword by decade)_ (a) Justice, freedom, security, trust, prosperity (b) War, military, church <!-- Start of picture text --> 100 100<br>75 75 War<br>Trust<br>50 50 Military<br>Justice Security<br>25 Freedom Prosperity 25<br>Church<br>0 0<br>1830 1850 1870 1890 1910 1930 1950 1970 1990 2010 1830 1850 1870 1890 1910 1930 1950 1970 1990 2010<br><!-- End of picture text --> Note: This Figure shows the percentage of presidential speeches on each decade that contained at least once each of the keywords and were calculated pooling the presidential speeches of 10 Latin American countries. See Appendix A for more details about the data.

As an indication that the enlightenment was no coincidence driven by a generalized increase in word usage, we observe that the mentions of ideals such as justice, freedom, or prosperity did not increase during the enlightenment periods. For example, while references to poverty and inequality began to surge in the 1960s, the word prosperity saw its most pronounced decline during this period. A clear difference in trends is also apparent for the terms justice, freedom, trust and security, which, unlike poverty and inequality, have been highly referenced terms since the 1830s, and have not seen any marked increases since the 1960s. The contrast in trends is even greater for war, military, and church, terms which all decline in frequency of usage starting roughly around the 1950s. Considering the poverty and inequality political enlightenment is not matched by a similar enlightenment for other terms, we can conclude that the enlightenment does not seem to have been driven by a generalized increase in the use of other words.

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**Table** 4: Fixed Effects Estimation (5 year lags)

# Dependent Variable: STANDARD DEVIATIONS OF GDP, CONSUMPTION, AND INVESTMENT GROWTH (Annual Rates)

|||_GD_|_P_||||_C_||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|_BANKt-U_|-6.47**<br>(3.59)|...|-||-7.33*<br>(3.43)|.|..|...|-5.06<br>(4.43)|...|...|...|
|_LLYt- 1_|<br>...|5.00<br>(3.59)|...|...|<br>...|7.22*<br>(3.48)|...|...|...|-3.49<br>(8.08)|...<br>i|...|
|_PRIVATEt-1_<br>|...|...|-3.27*<br>(1.47)|.. .<br>|...<br>|...|-2.84**<br>(1.49)|...<br>|...<br>|...<br>|-3.55*<br>(1.65)|.. .|
|PRIVYt-l|...|...|...|-. 010<br>(2.19)|...|..|..|- .704<br>(2.21)|...<br>_|... ....1<br>||(4.97)|
|_GROWTHt_|.187<br>(.234)|.169<br>(.213)|.186<br>(.222)|.175<br>(.220)|.229<br>(.350)|.234<br>(.312)|.252<br>(.333)|.251<br>(.318)|-. 012<br>(.123)|.115<br>(.122)|.024<br>(.120)|.101<br>(.121)|
|_MEANt- 1_|.136<br>(.227)|-.020<br>(.269)|.168<br>(.247)|-. 036<br>(.253)|.238<br>(.414)|.023<br>(.436)|.113<br>(.438)|-.105<br>(.433)|-.574<br>(.560)|-.688<br>(.617)|-. 615<br>(.548)|-.501<br>(.581)|
|_INFMEANt_|-.034|-.025|-.021|-. 028|-.051|-.016|-. 053|-.023|-.015|-. 016|-.025|-. 010|
||(.047)|(.045)|(.048)|(.045)|(.051)|(.049)|(.053)|(.050)|(.081)|(.081)|(.086)|(.081)|
|_INFSTDEVt_|.072**<br>(.036)|.055**<br>(.032)|.055<br>(.035)|.055**<br>(.032)|.106*<br>(.037)|.063**<br>(.034)|.096*<br>(.040)|.064**<br>(.034)|.072<br>(.081)|.045<br>(.079)|.066<br>(.080)|.042<br>(.080)|
|_FXVOLt_|10.5*<br>(4.97)|11.0*<br>(5.14)|12.2*<br>(5.01)|11.8*<br>(5.13)|9.23*<br>(4.38)|8.74**<br>(4.60)|10.7*<br>(4.55)|10.5*<br>(4.54)|17.6*<br>(7.06)|19.4*<br>(6.68)|17.6*<br> (7.13)|19.5*<br>(7.04)|
|_No. of obs._|190|198|188|195|191|198|189|195|190|197|188|194|
|_F`_<br>_2_|.55|.53|.57|.54|.62|.59|.61|.59|.69|.66|.69|.67|

Note: Country-specific and time-specific fixed effects estimate. Heteroskedasticity-corrected standard errors are in parentheses. *, ** respectively denote significance at the 5 percent and 10 percent levels. The variables _GOVMEAN, GOVSTDEV, POLITY, OPEN, OPEN * FXVOL_ are included but not shown.
Two qualifications need to be made regarding the implementation of this method in the case of Vietnam. Researchers at the World Bank have recently been addressing the issue of spatial autocorrelation in the first-stage regressions (equation 1). Analytical solutions for the variance of the headcount are not possible in this case, and it becomes necessary to use complex simulation methods to calculate the estimators and their standard errors (Elbers _et al,_ 2001). Although preliminary analysis indicates the presence of some spatial autocorrelation, we were not able to eliminate it by including community-level variables in the regression analysis. This suggests that there may be some inefficiency in the results of the first-stage regression analysis, though the magnitude of these effects is difficult to assess.

In addition, the estimate of the variance associated with sampling error produced by Stata is only an approximation. Exploratory analysis reveals that the sampling error is relatively small compared to the model error, suggesting that this approximation does not influence the results substantively.

# **3. Factors Associated with Poverty in Vietnam**

As described in Section 2.2, the first step in constructing a poverty map is to estimate econometrically per capita consumption expenditure as a function of variables that are common to the Census and the VLSS. These household characteristics include household size and composition, ethnicity, education of the head of household and his/her spouse, occupation of the head of household, housing size and type, access to basic services, and ownership of selected consumer durables. Table 1 lists the variables and Annex 1 provides descriptive statistics for each of them.

It is reasonable to expect that the factors which "predict" expenditure in rural areas may be different than those predicting expenditure in urban areas. Indeed, a Chow test strongly rejects the hypothesis that the coefficients for the urban sub-sample are the same as those for the rural 11
The data set is compiled from several sources. The primary source is the Maritime Transport Cost data set of the Organisation for Economic Co-operation and Development (OECD).<sup>9</sup> It includes (a) the total cost of transporting a given product in a given year, expressed in dollars; (b) the unit transport cost (cost per kilogram or cost in dollars required to transport 1 kilogram of merchandise); and (c) the ad valorem equivalent, or the transport cost divided by the total import value (the share of transport cost in the total import value of the product).<sup>10</sup> Actual costs include freight, insurance, and other charges (excluding import duties) associated with bringing the merchandise alongside the carrier at the origin port and placing it alongside the carrier at the first port of entry from the importing country (OECD 2008). Charges by specific ports are thus included. The value of imports (cost divided by ad valorem costs) and the volume of imports in kilograms (cost divided by unit cost) are calculated using these data. The value of shipped goods does not always factor in the cost of shipping when costs are based on containers or weight equivalents.

**Table 3 Descriptive statistics of variables used to estimate maritime transport costs**

|_Variable_|_Mean_|_Standard deviation_|_Minimum_|_Maximum_|
|---|---|---|---|---|
|Unit cost (ln)|–1.30|0.94|–9.21|4.95|
|Ad valorem|0.09|0.06|0.00|0.71|
|Value-weight (ln)|1.38|1.09|–2.82|7.83|
|Weight (ln)|12.93|3.43|1.39|20.57|
|Imbalance|–0.44|0.31|–0.85|0.66|
|Oil*Distance (ln)|12.81|0.44|12.04|13.61|
|Efficiency (variable returns to scale)|0.27|0.12|0.00|1.00|
|Connectivity|26.33|16.92|5.07|81.58|
|Containerization|0.63|0.28|0.16|1.00|
|Exporting GDP per capita (ln)|7.06|0.86|5.72|8.88|

_Note:_ Sample summary statistics exclude the omitted data.

We use data only for container traffic and commodities transported in containers, which are disaggregated at the two-digit Harmonized System level for all 99 chapters for 2000–07. Data on distance come from <u>www.sea-distances.org, data on trade imbalance from the UN Comtrade</u>

> 9 The database contains data on bilateral maritime transport costs from 1991 through 2007 at the sixdigit level of the Harmonized System (HS), an international nomenclature for the classification of products developed by the United Nations that allows participating countries to classify traded goods on a common basis for customs purposes. The first two digits identify the chapter in which the goods are classified.

> 10 https://stats.oecd.org/Index.aspx?DataSetCode=MTC.

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# **1. INTRODUCTION**

Multidimensional auctions seem like a natural solution in practice, when auctioneers, governments in the context of this paper, pursue more than one objective in their auctions. In both theory and practice, however, whether multidimensional auctions improve the efficiency of the outcomes remains open to argument. Part of the problem stems from the fact that when multiple criteria are adopted to select a winning bidder, a difficult question to answer is how to aggregate those criteria in the bid evaluation process.

The issue is not only important but also quite current because auctions are becoming a common instrument to contract out public services to private operators under the public-private partnership (PPP) framework adopted by many developed and developing countries. Because PPP transactions are usually valuable, complicated and closely related to living standards of people, the authorities are induced to take advantage of the multidimensional format in designing PPP-related auctions. They generally want to enhance the service provision with a reasonable quality at the lowest costs. Here the objectives are already threefold. Simultaneously, governments may want to require more investment in advanced technology from operators. Often, in addition, governments also wish to protect employment of public enterprises being sold and limit staff reductions.

Some of these objectives are inherently incompatible with every other objective in the wish list of auctioneers. Any objective which increases costs, such as new investment requirements or minimum employment levels, can become a threat to the affordability of prices. This implies that the multiplicity of objectives can represent a risk from a social viewpoint. However, without appropriate investment, the quality of services cannot be improved which can also have a social cost. Similarly, if private operators are required to hire extra employees, the efficiency gains needed to cut costs and hence tariffs have only a limited scope, restricting the potential social payoffs of the PPPs.

As often happens, the challenges are in the implementation details for these auctions. Basic auction theory indicates several risks of implementing multidimensional auctions. This paper explores a set of possible necessary conditions to implement multidimensional auctions successfully. Using data on auctions for road and railway 1
There is no national database for time-series monitoring of groundwater salinity in Bangladesh. Over the years, a few studies have generated some contour maps of groundwater EC at the national scale but there is little detail in the data sets used for mapping. One of these earlier maps on groundwater EC at the national scale was generated by the Master Plan Organization (MPO) under the Bangladesh National Water Plan Phase-I.<sup>9</sup> Later on, Rahman and Ravenscroft<sup>10</sup> presented a groundwater EC map of shallow (<150 m bgl) groundwater in Bangladesh based on collated data on EC from various sources. Bangladesh Water Development Board (BWDB) has a monitoring network of some 118 stations where a set of chemical constituents of groundwater including chloride (Cl) concertation is monitored approximately once a year. Here, we have generated a groundwater EC map at the national scale using data primarily from two sources. First, we collated groundwater EC data from 461 boreholes that were installed recently under a regional-scale hydrogeological study conducted in 19 coastal districts by the Bangladesh Water Development Board (BWDB) between 2011 and 2013 funded by the Bangladesh Climate Change Trust.<sup>11</sup> Secondly, we have digitized and georeferenced the contoured map of groundwater EC<sup>10</sup> and extracted point data of EC at 102 locations throughout the country, predominantly in the northern part where there is limited groundwater EC measurements. Finally, we interpolated the point data ( _n_ =563) at the national-scale using the Inverse Distance Weighting (IDW) algorithm in ArcGIS environment. The interpolation error was 50 μS/cm compared to the data range of 27 to 43,950 μS/cm with a mean of 5,251 μS/cm. We then rasterized, using the ‘R’ programming language, the interpolated EC data at a grid resolution of 2.5-km × 2.5-km (Figure 2b).

# **Depth to dry-season groundwater levels**

We use mean depth to dry-season (December–April) groundwater levels as a hydrological indicator for representing groundwater storage depletion in Bangladesh. This is an important measure of sustainability of shallow groundwater abstraction in Bangladesh using low-lift pumps, for example, the No. 6 hand-operated pump, which is widely used for drinking and domestic purposes. In the Indian Subcontinent, cast-iron made No. 6 suction pumps are traditionally used for the provision of drinking water and small-scale irrigation.<sup>12</sup> More than 10 million tubewells, most of which are predominantly No. 6 pumps, are used to withdraw drinking water throughout Bangladesh<sup>13</sup> and several other derivatives of this pump are available throughout Asia. When groundwater levels in the aquifer goes below 7-8 mbgl, which is the maximum suction limit of the No. 6 pump, these low-lift pumping technologies 26
The potential for biases raises a more general point: statistics arising from firm-level surveys should be kept in perspective. Just as ignoring an important information source can result in costly errors of analysis and policy formulation, reification of statistics may yield errors as well. Once a serious constraint is identified, it is important to confirm independently that some institutional or policy failure is at its root, rather than the normal functioning of market forces.

Strategic Implications of Survey Results Firm-level surveys feed into the recommendations of PSAs, hence into strategies for promoting PSD. We have found constraint scores to be strongly indicative of priorities for reform, at least from the private enterprise perspective. For example, in Brazil, where macro-policy management had made business transactions difficult, there was a powerful tier of three constraints identified as the greatest, all related to macro-reform (see TABLE V). Beyond these constraints stood a second tier of priorities, neatly grouped, all substantiallv higher ranked than the remainirg ones. There, businesses had an urgent sense of priority. The relatively liberal and predictable policy environment of Chile, no one group of constraints stood out from others.

Cost data can be extremely useful in making the case for policy reform. In this regard, surveys may afford an efficient source of information on firm-level costs of regulation. The evidence from the Brazil-Chile study, presented on page 2, demonstrates the resource cost of regulation, not simply in fees, but also in the time cost of entrepreneurs and their employees. Similarly, comparative data on the cost of entry in Brazil and Chile confirmed anecdotal evidence that Brazilians have found an effective institutional substitute for their complex formal process of registration.

Perhaps our most important caution is directed toward those who want a PSD strategy before (or without) carrying out a private sector assessment, including a firm-level survey. The firm-level survey is based on the premise that firms have unique insights into the problems of private enterprise from their daily confrontation with their country's policy and institutional environment. As noted at the outset, empirical findings of past surveys have often challenged assumptions about constraints to PSD. These surprises suggests the importance of these surveys in focusing attention and limited resources on the most constraining features of that environment. Therefore, policy reform should be predicated on an assessment of needs and priorities that includes the perspective of the private sector. A private sector strategy can emerge from the subsequent analysis.

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