rafmacalaba/data-use-mentions-extended huggingface dataset:
Figure 29: Variance in the task performed of temporary jobs. (Change from the late 90s) <!-- Start of picture text --> 0,8<br>0,6<br>0,4<br>0,2<br>0<br>‐0,2<br>‐0,4<br>‐0,6<br>‐0,8<br>‐1<br>‐1,2<br>Georgia Kyrgyzstan Armenia<br>NRCA NRCI RC RM NRM<br><!-- End of picture text --> Source: Own calculations based on Household surveys.

Note: NRCA refers to Non-Routine Cognitive Analytical, NRCI is Non-Routine Cognitive Interpersonal, RC is Routine Cognitive, RM is Routine Manual and NRM is Non-Routine Manual.

# 4.2.3 Summary of results for Europe and Central Asia

The analysis performed for a set of 7 selected countries shows that the trends of non-standard employment in Europe and Central Asia do not show a homogeneous pattern in the last 10/15 years. This heterogeneous picture is observed in both the prevalence of part-time and temporary employment.

Regarding the profile of NSE, we find several changes in the last two decades. First, from the education perspective, an improvement of the profile of workers employed as NSE can be observed in the countries analyzed, in both part-time and temporary employment. From the point of view of wages, two important concluding changes are identified. On the one hand, a shift to the right of the wage distribution is observed in all the countries analyzed, indicating an increase in their average. Finally, examining the task content performed in jobs, we find a heterogeneous picture. In some countries, NSE evidences a movement towards non-routine cognitive tasks, together with a decreased importance of manual tasks in line with the previous results in the literature for total employment, but we have several exceptions.

Additionally, like in the region of Latin America
left panel). The association also seems to be non-existent between total and average labor income and imports per worker (right panel).

**Figure 2: Exports, imports and average job outcomes, LFP and employment rate**

<!-- Start of picture text --> Exports Imports<br>Labor force participation Labor force participation<br>50 45.5 50 46.8<br>40.2<br>38.9<br>40 40<br>30 High exports 30 High imports<br>20 Low exports 20 Low imports<br>10 10<br>0 0<br>Employment rate Employment rate<br>50 43.3 50 44.5<br>40 38.1 40 36.8<br>30 High exports 30 High imports<br>20 Low exports 20 Low imports<br>10 10<br>0 0<br><!-- End of picture text --> Source: Own elaboration based on Population Census, Integrated Public Use Microdata Series and Customs data. Notes: (1) The sample is restricted to the urban and semi-urban municipalities with complete data in the whole period. (2) A municipality has relatively high exports (imports) if its exports (imports) per 2000 worker ratio in 2015 is above the median across municipalities and low exports (imports) if its ratio lies below the median.

Third, a municipality’s trade integration could strongly matter for migration patterns, both across domestic municipalities and with other countries, specifically the United States. More trade opportunities in a municipality may deter migration outflows, while attracting more migrants from other countries or pulling back Mexican migrants from the United States. In fact, the number of unauthorized migrants from Mexico to the United States declined from 6.9 million in 2007 to 5.6 million by 2015 (Gonzalez-Barrera and Krogstad 2019). Trade in a municipality may also have effects on remittances and the
that the PM10 results in this paper can reasonably be recast as PM2.5 results, simply by dividing them by 2.

**Table 2:  PM2.5/PM10 Ratios for Biomass Fuels**

|Fuel|Ratio|Houses|
|---|---|---|
|Dung|0.52|22|
|Firewood|0.51|18|
|Straw|0.56|4|
|Branches, Twigs|0.56|16|
|Total|0.51|85|

# **4.  Is Exposure Largely Confined to Cooking Areas?**

Analyses of indoor air pollution in poor households often stress the health risks for women who cook and children under their supervision in cooking areas (Rosemarin, 2002; Smith, 2000). Higher health risks are attributed to two factors: higher pollutant concentrations in cooking spaces, and longer times spent indoors. This section examines the first factor, using our 24-hour real time (PDRam) monitoring results for PM10 in kitchens and living rooms. Section 6 reports equivalent results from the MiniVol samplers for a large sample of households. In a forthcoming paper, we will compare times spent indoors by different age / sex groups.

Figure 2a displays the time paths of PM10 concentrations in four representative households. We express concentrations in log form to prevent visual scaling problems in the graphs. Although the 24-hour patterns in the four graphs are quite different, all four exhibit very close tracking of PM10 concentrations in the kitchen and living room. The 2- minute observations for the kitchens exhibit many short-interval “spikes”, and the living room observations closely resemble smoothed versions of the kitchen series.

11
# **E-Commerce Development and Household Consumption Growth in China**

Xubei Luo, Yue Wang, Xiaobo Zhang<sup></sup> JEL Codes: L81, E21, D23, R12 Key Words: E-commerce, consumption growth, transaction costs, spatial inequality

>  Xubei Luo is a senior economist of the World Bank; Yue Wang is a Ph.D. candidate at the Cornell University; and Xiaobo Zhang is a distinguished chair professor of economics at the National School of Development, Peking University in China, and senior research fellow of International Food Policy Research Institute. The authors thank Shaohua Chen, Samuel Freije-Rodriguez, John Giles, Bert Hofman, Deepak Mishra, Ambar Narayan, Hoon Sahib Soh, and Salman Zaidi for valuable comments and discussions; Zhengwei Jiang, Zhenzhong Sheng, Ruidong Zhang, and researchers from AliResearch for suggestions and for sharing the Alibaba online data for the research; and Xuejiao Xu for research support. The views expressed here are those of the authors and do not reflect those of the World Bank, its Executive Directors, or the countries they represent.
time to home production, especially in the labor participation states. Interestingly, Roma wives do not change their labor market decisions significantly when having children; nonparticipation goes from 82 percent to 83 percent; and, conditioning on labor market state, the share of time spent on home production time increases.

**Some descriptive statistics relevant to the present exercise are the assortative mating**<sup>**21**</sup> **of spouses in terms of the labor market and the mean observed wages** . Table 2 (left panel) presents the male and female labor market states. The data inside the borders is the percentage of households with spouses in the associated labor market states, while the 5<sup>th</sup> column and row represents the percentages of males and females in each labor market state, without conditioning on the spouse labor market state. That panel shows that in 35.2 percent of the Roma households at least one spouse works, in only 2.0 percent both spouses work, and in 28.3 percent only the husband works. The share of households where both spouses are nonparticipants is high (39 percent) compared to international standards.

**Table 2: Regional spouses labor status and mean wages**

|||Fe|males' la|bor state||||
|---|---|---|---|---|---|---|---|
|||NP|UE|PT|FT|All males|**Mean hourly wages (USD 2011 PPP)**|
|te|NP|39|4|1|2|47|PT Males<br>1.5|
|'<br>sta|UE|19|3|1|1|23|FT Males<br>0.6|
|ales<br>or|PT|9|
survey data. To ensure that our model works well for data deprived countries, we check if our model selection and performance are robust to using only the countries with at most three poverty estimates, which reflects the 25% most data deprived countries for which we have some data. These countries tend to be more authoritarian and conflict-ridden but also include a couple of wealthy countries which simply do not share much data (Table A.1).

With respect to _coherence_ , we mean that we are willing to tolerate marginal increases in errors if doing so results in a model that is easier to rationalize. This is in part why we are restricting ourselves to predictions consistent with the log-logistic distribution, but it also matters for the covariates we will select. For example, if we find that a model using GDP per capita in 2011 PPPs performs slightly better than a model using GDP per capita in 2017 PPPs, we will favor the latter as the welfare distributions are expressed in 2017 PPPs, and hence makes for a more consistent model.

The use of these three principles in addition to the error of the model means that, at times, value judgments are needed to assess when an increase in the error may be merited by a greater adherence to the three principles. This complicates the model selection somewhat in contrast to a sole reliance on the model error. As a robustness check, we use machine learning to select a model guided exclusively on model performance as a test of how much accuracy we give up by including these three additional principles (section 5.2).

# 4 Results

Our first objective is to select the main variable to use for the tier 1 model. To that end, we run separate quantile regressions following equation (4) using one candidate covariate at a time, replacing ) in the equation. We evaluate the fit in-sample for reasons of efficiency, since evaluating all models out-of-sample is too computationally intensive. Given that all models are llGG(GGl identical and simple, overfitting is unlikely to be an
**Figure 1 continued** Attainment profiles **for** ages **15** to **19,** by **economic group:** Middle East, North **Africa, Central Asia and Europe**

<!-- Start of picture text --> Egypti 1992 Egypt 1995-96 Kazakstan 1995<br>08 ~~~ - } -> 086____+ _0 08<br>0 6 0 0.6 0 6<br>0 4 a. 4 0. 04<br>0.2 02. 0.2<br>o ~2 02 O 0.2 O<br>0 . 0<br>1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9<br>Grade Grade Grade<br>Morocco 1992 Turkey 1993<br>08 4 08<br>02 02 0<br>3 0<br>1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9<br>Grade Grade<br>* Poorest . Middle A Richest<br><!-- End of picture text --> 17
<br>65.4<br>62.4<br>100 57.7<br>10<br>47.8 52.9<br>42.9<br>50 42.0 42.0<br>5<br>30.9 36.2 41.6 48.2 49.8<br>0 0<br>2012 2013 2014 2015 2016 2012 2013 2014 2015 2016 2017 2018<br>Source: BIS; PBC; Wind Info; CEIC; Authors’ Source: Wind Info; authors’ calculations.<br>calculations.<br>Note: Corporate decomposition estimated based on<br>information from bonds and bank credit.<br><!-- End of picture text --> The recent boom in public investment and credit to the corporate sector is reflected in the growing exposure to risk among smaller regional banks and the rapid increase in shadow banking activities. Empirical evidence links the acceleration in shadow banking growth after 2012 with the financing needs of LGFVs, including the rollover of maturing bank loans taken on at the time of the 2009 fiscal stimulus (Chen et al., 2017).

Regional banks now account for a large share of aggregate assets in the banking sector and their portfolios tend to be riskier compared with the Big 4 state-owned banks.<sup>19</sup> While the four largest banks accounted for the majority of assets before the financial crisis, their share fell to 37 percent in 2016 (central policy banks accounted for another 10 percent). Smaller banks held most banking assets, with their assets increasing at double the rate of the Big 4 banks (Figure 22). And the exposure of smaller banks to risk grew rapidly in 2015–16. The share of

> 18 The local government debt swap program was introduced in 2015 to convert LGFV debt recognized as public into local government bonds.

> 19 Bank of China, China Construction Bank, Industrial and Commercial
Hallsworth, M., List, J., Metcalfe, R., Vlaev, I., 2017. The behavioralist as tax collector: Using natural field experiments to enhance tax compliance, _Journal of Public Economics_ 148, 14-31.

Hernandez, M. Jamison, J., Korczyc, E., Mazar, N. & Sormani, R. 2017. Applying behavioral insights to improve tax collection : experimental evidence from Poland. Washington, D.C. : World Bank Group.

Hernandez, M.; Karver, J.; Negre, M.; Perng, J. 2019. Promoting Tax Compliance in Kosovo with Behavioral Insights. Washington, D.C. : World Bank Group.

Mascagni, G. Nell, C., & Monkam, N. (2017). One Size Does Not Fit All: A Field Experiment on the Drivers of Tax Compliance and Delivery Methods in Rwanda (January 2017). ICTD Working Paper 58.

Mascagni, G. (2018). "From The Lab To The Field: A Review Of Tax Experiments," Journal of Economic Surveys, vol. 32(2), pages 273-301, April.

Medina, L. and Schneider, F. (2019), Shedding Light on the Shadow Economy: A Global Database and the Interaction with the Official One. CESifo Working Paper 7981, December 2019. Munich Pomeranz, D. and Vila-Belda, J. (2019). Taking state-capacity research to the field: Insights from collaborations with tax authorities. Annual Review of Economics 11, 755-781.

Pudney S.E., Pyle D, Saruc T., 2000. Income tax evasion: An experimental approach. In: MacDonald A, Pyle D., Illicit activity: The economics of crime and tax fraud. Ashgate: Aldershot.

Schneider, F., & Enste, D. (2000). Shadow Economies: Size, Causes, and Consequences. <i>Journal of Economic Literature, 38 (1), 77-114
**Policy Research Working Paper Series**

|**Title**|**Author**|**Date**|**Contact**<br>**for paper**|
|---|---|---|---|
|WPS2240 The Effects of Land Registration on<br>Financial Development and Economic<br>Growth: A Theoretical and Conceptua<br>Framework|Frank F. K. Byamugisha<br> <br>l|<br>November 1999|E. Gelos<br>37846|
|WPS2241 How Land Registration Affects<br>Financial Development and Economic<br>Growth in Thailand|Frank F. K. Byamugisha<br>|<br>November 1999|E. Gelos<br>37846|
|WPS2242 Confronting Competition: Investment<br>Response and Constraints in Uganda|Ritva Reinikka<br>Jakob Svensson|November 1999|H. Sladovich<br>37698|
|WPS2243 Designing Pro-Poor Water and<br>Sewer Concessions: Early Lessons<br>from Bolivia|Kristin Komives|November 1999|M. Salehi<br>37157|
|WPS2244 True World Income Distribution, 1988<br>and 1993: First Calculations, Based<br>on Household Surveys Alone|Branko Milanovic|November 1999|P. Sader<br>33902|
|WPS2245 Opportunities for Improving<br>Environmental Compliance in Mexico|Susmita Dasgupta|November 1999|Y. D'Souza<br>31449|
|WPS2246 Infrastructure's Contribution to<br>Aggregate Output|David Canning|November 1999|H. Sladovich<br>37698|
|WPS2247 Does Deposit Insurance Increase<br>Banking System Stability?<br>An Empirical Investigation|Ashl DemirgOg-Kunt<br>Enrica Detragiache|November 1999|K. Labrie<br>31001|
|WPS2248 Privatization and Regulation of<br>Transport Infrastructure in the<br>1990s: Successes .
context and time-specific) RMNCH-N service determinants could reduce the fertility rate to 2.5 in certain Asian settings compared to generic interventions.<sup>1</sup> Another <mark>study of diarrhea and pneumonia interventions observed that 15 highly costeffective interventions addressing the top RMNCH-N service utilization determinants – if implemented at scale – would prevent 95 percent of deaths from diarrhea and 67 percent of deaths from pneumonia in under-5 children by 2025.</mark><sup>6</sup> <mark>S</mark> uch specific interventions addressing priority utilization determinants are also proven to be cost effective in improving the RMNCH-N outcomes in a short timeframe. In summary, the existing evidence shows that regular tracking, coupled with prioritized investments in context-specific utilization determinants, can improve RMNCH-N service utilization.

## **1.2 Reproductive, maternal, child health, and nutrition landscape in Bangladesh**

Bangladesh has witnessed significant improvements across key maternal, child health and nutrition indicators over the last few years, with multi-faceted and sector-wide approaches to improving the health of pregnant women and under-five children.<sup>7</sup> Changing fertility behavior, and increased access to and utilization of health services, for example, have been major contributors to the consistent decline in underfive and maternal mortalities.<sup>8</sup> Notwithstanding progress, however, Bangladesh is still far away from reaching a key Sustainable Development Goal (SDG) – “maternal mortality ratio target is 70 deaths per 100,000 live births” (currently at 165).<sup>8</sup> The uptake of certain key maternal and child health (MCH) services has been consistently sub-optimal. For instance, institutional deliveries are only 50% and skilled birth attendance is at 53%.<sup>9</sup> <mark>As per verbal autopsies and household surveys, two-thirds of total maternal deaths occur during the postpartum period, but postnatal care visits are still low at 65%.
Remarkably, Figure 2b shows that the close relationship can hold even when cooking is done outdoors. Table 3 provides log-log regression results for various 2- minute lag structures. The implied adjustment lag is very short, and the overall fit is obviously very strong. Summary evidence for all households indicates that the observations in Figure 2 are very common in our sample. The correlation coefficient for the PDRam households is .93 for median PM10 concentrations in kitchens and living rooms; Figure 3 illustrates the strength of the relationship. To summarize, the PDRam evidence strongly indicates that air pollution from cooking diffuses into living spaces very rapidly, and at similar intensity.

# **Figure 2a:  Comparative PM10 Concentrations in Four Bangladeshi Houses: Kitchens and Living Rooms**

<!-- Start of picture text --> (1) (2)<br>0 5 10 15 20 25<br>24-Hour Time 0 5 10 15 20 25<br>24-Hour Time<br>Log Kitchen Concentration Log Living Room Concentration<br>Log Kitchen Concentration Log Living Room Concentration<br>(3) (4)<br>0 5 10 15 20 25 0 5 10 15 20 25<br>24-Hour Time 24-Hour Time<br>Log Kitchen Concentration Log Living Room Concentration Log Kitchen Concentration Log Living Room Concentration<br>9<br>7<br>8<br>6<br>7<br>5<br>6<br>4<br>5<br>3 4<br>Log Kitchen Concentration/Log Living Room Concentration Log Kitchen Concentration/Log Living Room Concentration<br>7 8<br>6.5<br>7<br>6<br>6<br>5.5<br>5<br>5<br>4.5 4<br>Log Kitchen Concentration/Log Living Room Concentration Log Kitchen Concentration/Log Living Room Concentration<br><!-- End of
the business community, others focus on the opinions of expatriates, and some are broad-based surveys of citizens.

The two types of sources of governance data each have their advantages and disadvantages. The main advantage of polls of experts is that they are explicitly designed for cross-country comiparability, and considerable effort is placed in the benchmarking process which ensures this. However, the difficulties with such measures are also clear. Typically they are based on the opinions of only a few experts per country, and the quality of the country ratings depends to a great extent on the knowledge of experts regarding the countries they are assessing. The ratings are particularly prone to two types of feedback: countries with good economic outcomes may be more likely to receive favourable ratings, and country rankings by other organizations are frequently an input into the rating process of each organization. Country ratings may also be affected by the political or ideological agenda of the organization producing the ratings. Despite these difficulties, we believe that there are at least two reasons to think that on average, such sources provide valuable information on governance. First, we find that the indicators produced by such organizations generally correlate strongly with measures based on surveys of residents and entrepreneurs. Second, we find the fact that commercial rating organizations such as EIU, DRI and PRS are able to consistently sell their assessments to commercial subscribers for considerable feies to be convincing evidence that these sources are in fact producing useful information.<sup>6</sup> The advantage of surveys is that they reflect the opinions of a larger number of respondents that are more cloisely connected with the countries they are assessing. Nevertheless, they suffer from two disadvantages. First, survey questions can be interpreted in context- or culture-specific ways. For example, a response regarding the prevalence of "improper practices" is coloured by country-specific perceptions of what uimproper practices" are perceived to be. This will hinder the cross-country comparability of responses to otherwise identical questions.<sup>7</sup> Second, cross-country 6 For
29 1) Figures 12-15 report the plots of the risk premium for the South American countries and Nigeria on the period of the Mexican crisis (7/29/94 to 7/28/95)31: the plots show that all five countries had a significant response to the crisis. Moreover, NIGPAR is affected by the peaks of MEXPAR but it follows a much more volatile path, and it has a behavior very similar to VENPAR.

<!-- Start of picture text --> 3000 200D__ ____ _______________ ____ _______<br>2500<br>2000<br>1000 ----<br>500<br>0-<br>7/299 10/0194 12116194 2/24/95 5/0195 7114195 7/2Q'94 10/07/94 12/i694 2/24/95 -605/96 7114196<br>NIGPAR ------- MEXPAR - VENPAR MEXDIS- ARGDI<br>Figure 12 Figure 13<br>2000 2500<br>1600 - 2000<br>1200 - 1500<br>800 -- 1000<br>400- 500<br>7/12St94 '10/0Y94 l'f1Vi94 '2i2/495 "6 i0&/9'5 i4/5 7/29194 -10/0i94 '12/1694 'V24195 'J05 ' 7i M4/95<br>- MEXDIS ----- BRADIS - MEXDIS -- ECUDIS<br>Figure 14 Figure 15<br><!-- End of picture text --> Consider now the other countries in our sample, Philippines and Bulgaria, in figure 16-18 . Note how similar to Poland's is the behavior of the Philippines' bond: the difference between MEXPAR and PHIPAR (DIFF) shows the _31_ A first glance at the plots in figure 5 shows that there is no strong evidence of comovements in the risk premium except during periods in which one of the countries
Table 5: Outcomes and Measurement

|Outcome|Measurement|Scale|Survey|
|---|---|---|---|
|VH’s knowledge of laws<br>and regulations|Proportion of questions answered<br>correctly about laws and regulations<br>governing village head’s decision-<br>making (i.e. are there are restrictions<br>on the disputes committed within<br>their geographic jurisdiction over<br>which traditional leaders can preside?)|0-1|VH Survey|
|VH’s support for<br>individual rights|Average stated support for three<br>individual rights (right to speak in defense<br>at court hearings, inheritence rights, and<br>right to protections from arbitrary authority)|1-4|VH Survey|
|VH’s adherence to<br>procedures|Index measuring whether the VH<br>adheres to fve procedures (consultation<br>of RMC, consultation of women’s council,<br>% women on court, no court fees, public<br>court records)|Standardized<br>index (mean=0,<br>s.d. = 1)|VH Survey<br>(and CL Survey)|
|Bias in VH’s decisions|Proportion of respondents with different<br>political views who received food aid<br>Proportion of respondents with different<br>political views who perceived most court<br>decisions to be fair|0-1<br>0-1|HH Survey<br>HH Survey|
|Effcacy of management<br>of problems by VH|Effect of need on receipt of food aid|OLS regression<br>coeffcient|HH Survey|
||Proportion of respondents with unresolved<br>land or livestock disputes|0-1|HH Survey|
|Legitimacy of VH|Index measuring evaluations of VH<br>(trustworthiness,