rafmacalaba/data-use-mentions-extended huggingface dataset:
while capital is deflated using the sector deflators for gross fixed capital formation. Lastly, there are two significant firm characteristic variables relevant in the analyses of the paper: sector and age. The firm's sector of activity corresponds to the International Standard Industrial Classification (ISIC) sector classification. The age of a firm is calculated as the difference between the observation year and the year of the firm's commencement of operations.

Variables pertaining to workers are measured in a standard manner to facilitate the wage inequality analyses. Worker-level information is available at a monthly frequency in the LDLE. Following relevant papers in the literature (Barth et. al., Criscuolo et al. [2020, 2021, 2022]), only workers that are fully employed for a calendar year are kept in the estimation sample. Wages are constructed as a worker’s daily wage rate from reported monthly wages and the number of days worked in a month. These are deflated by the consumer price index to obtain real wages. To match to the firm-level data, which is at an annual frequency, yearly real wage rates are estimated as the average across months of the real daily wage rate. The paper also utilizes the following variables associated with workers’ job characteristics and human capital: part-time employment, education, age, gender, and ethnicity. A dummy for part-time employment is constructed using the number of days worked in a month. Workers with less than 15 days of employment per month are classified as having part-time employment.<sup>2</sup> For education, a bivariate variable is created to identify if a worker has obtained at least a high school diploma. Last, workers’ age, gender, and ethnicity are provided by the LDLE.

# **3 Motivation Facts: Aggregate Productivity and Inequality Trends in Ecuador**

A concern in Latin American economies is that growth has been unsatisfactory and driven by poor productivity performance, as documented by Busso et al. (2013). Ecuador is no exception to this
# **7.2 Issues for Future Research**

There are a number of issues to consider for future research. First, with our dataset and empirical approach we need to keep in mind both a purely statistical point, as well as one of a more methodological/conceptual nature. The first refers to the limits we have after crossing variables from different datasets (Taylor/UN/EOS) in terms of the overlapping number of observations/cities (N), which for some indicators in Table 1 is very small. Thus, a major challenge in the next stage is to expand this database, and fill in the significant gaps within the existing set of over 400 cities. We expect to be able to collaborate with partners in this initiative. This expanded database would be made available on the web to all researchers and policy-makers (see Annex C for the current list of cities for which this dataset has information on at least some of the variables of interest in this research project).

Second, we need to probe much deeper than was possible in this preliminary exploration on the issue of the dynamics between globalization and governance, and their interface with city performance. For instance, we found that globalization and governance are positively correlated with each other at the city level. Our simple conceptual and econometric model pointed to possible causality from globalization to good governance. Yet it cannot be ruled out obviously that in reality there is bi-directional causality, within an endogenous model where there is a possible virtuous circle between both variables. Within such a framework, an extension of the simple model presented in this paper would be warranted.<sup>19</sup> This requires further research with additional data and a more complex econometric model with instruments, _inter alia_ accounting for endogeneity issues. Furthermore, in this context the brief references to ancient times made earlier are suggestive of the need to probe further with an historical perspective.

Given the constraints in data availability at the city and country level, in this initial research inquiry
coun‐

- tries in which insurance is well developed.

# _Data needs for econometric analysis_

For econometric analysis, long time series with sufficient numbers of events are required to have an ade‐ quate sample. Three main problems are met. First collection of data on natural disasters started to be precise and of large scope in the 90s. Earlier data collection is mainly available for large events, and data are less precise. Second, large natural disasters are, fortunately, scarce. This does not allow for a large sample necessary for econometric analysis.

Third, the socio‐economic baseline may be an important difficulty to distinguish effects of natural disas‐ ters from effects due to socio economic evolution. For instance, effects of natural disasters on economic growth may be difficult to disentangle from macroeconomic shocks, change in population, trends in ur‐ banization, development of utilities networks etc.

# _Data needs for model‐based approaches_

Model‐based approaches require large set of data (e.g., input‐output tables) on the affected economy, and detailed data on which sectors are affected by the disaster. At regional scale, it is particularly rare to 28
MINIMUM WAGES IN CAMBODIA 8 In practice, the changes in employment can manifest in both the extensive margin, through participation rates, as well as intensive margin, through hours devoted to work. If hiring and firing costs are high, then the effect might manifest more in the intensive margin than the extensive margin.

Furthermore, if hiring and firing costs are low, then jobs in the garment sector become more desired. Garment firms could use the opportunity to replace low-productivity workers with higher productivity workers. This could manifest in terms of changed (skill-)composition of those who are employed in the garment sector.

For this analysis, I use data from the annual Cambodia Socio-Economic Surveys (CSES) from years 2007 to 2014.<sup>11</sup> The CSES are nationally representative surveys that collect data or each month of the survey year. Hence, the annual series provides a picture of how the labor market has evolved month to month for the study period. This feature of the survey design will be extremely important in identifying how the outcome measure evolves after a minimum wage increase is enacted.

Since minimum wage regulations is only applied for the garment and footwear industries, the expected share of workers paid above minimum wage should be higher for workers in garment and footwear relative to other jobs in the private sector. Indeed, as Figure 3 indicates, the share of workers earning above the monthly minimum wage is higher for the garment sectors. The proportion of workers earning higher than minimum wages increased from about 87 percent in 2007 to about 95 percent in 2014, though there may have been a decline in 2015. The comparative proportions were 62 and 74 in other private sectors. The share of female workers in other private sector is even lower at 48 percent in 2007 to 62 percent in 2014.

As Figure 3 shows, compliance to minimum wages is quite high in the garment sectors. Before the minimum wage change in Oct 2010, 95 percent of the workers in the garment and footwear sectors were paid above
Learning from Power Sector Reform: The Case of Pakistan Robert Bacon<sup>1</sup> <u>Keywords: power sector reform, electric utility, power generation, energy access, state-owned</u> enterprise, regulation, electricity pricing.

<u>JEL Codes: L9; Q4</u>

> 1 This paper is based on data collected and interviews conducted in Pakistan by Fariel Salahuddin. It also benefited from considerable guidance and input from the World Bank Country Team: Rikard Liden, Mohammad Saqib, Anjum Ahmad, Anh Nguyen Pham, Defne Gencer and Richard Spencer.
**The P2P platform (LocalBitcoins in this application) used only for one of the two legs**

**The amount in Bitcoin of the two legs might differ.**

**The two trades lie farther apart than our time window (five hours in the baseline case) allows** .

**The payment technology in (at least) one country involved is slow.**

**The trade is matched but wrongfully disregarded, because of the probability of it being matched by chance**

**The parties involved in a planned trade cancel the transaction to complete it in cash and avoid the escrow fees**

Imagine a remittance sending agent, working and living in a country with centralized exchanges and sending his remittances to a developing country, where the only platform available for Bitcoin trades is the P2P exchange. It might be cost efficient to purchase the Bitcoin on the lower cost centralized exchange of the sending country, transfer it to the e-wallet of the P2P platform, and then sell it on the P2P platform in the destination country. Our algorithm would not detect this vehicle trade, as only one of two trades is recorded in our P2P data.

The algorithm only identifies a vehicle trade where the amount of Bitcoin for both two legs is identical. Yet, some cases might exist, where an agent uses his wallet both for vehicle trades and speculative purposes, so the two amounts might differ. The same can happen when the best P2P price offer of the second leg is limited to a trade-size Z < X, when the agent to might split the second trade into two.

Our algorithm does not match any two trades when the time difference between them exceeds 300 minutes (for a five-hour window). If the trader has access to a perpetual futures contract, that allows her to wait for better terms of trade on the destination’s country P2P market, this can allow her to accept much longer periods of exposure to Bitcoin price volatility.

Because the clearing time of the
<!-- Start of picture text --> 100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>Source: Universal Postal Union database.<br>Note: Data are from 2015–17. No data were available for Bangladesh, Kyrgyzstan, and Senegal.<br>from a postal establishment<br>Percent of population having to collect mail<br><!-- End of picture text --> In particular, the emergence of cross-border e-commerce calls for reexamining the efficiency of customs processes. Cross-border e-commerce now accounts for 10–15 percent of the volume of global e-commerce, and it is expected to grow at twice the rate of domestic e-commerce until 2020.<sup>84</sup> A simplified customs procedure such as prearrival risk assessment and digitizing the process through electronic data exchange and payment could all contribute to a more cost-efficient customs process.

Given the growing flow of low value cross-border shipments, customs authorities face more severe challenges on the long-standing trade-off between foregone revenue and the cost of collection and longer clearance times. Many customs authorities around the world have adopted a de minimis threshold—that is, a “valuation ceiling for goods, including documents and trade samples, below which no duty or tax is charged and clearance procedures, including data requirements, are minimal.”<sup>85</sup> How to set a reasonable de minimis threshold has become of special importance. The calculation and collection of customs duties and taxes on low-value shipments disproportionally burden small e-commerce exporters because they are unable to streamline these tasks. Research has shown that a reasonable de minimis threshold can be vital for small business firms that depend on cross-border sales.<sup>86</sup> Among the 21 countries covered under Digital Business Indicators project, Bangladesh, Burkina Faso, Pakistan, Senegal, and
average distribution losses over a three-month period at a representative feeder within JVVNL’s network to be 9.2%. This is lower than the 13.4% average marginal losses calculated using our methodology.

> 25 CO2 baseline database for the Indian power sector produced by the Central Electricity Authority (Version 14), available at: <u>http://www.cea.nic.in/tpeandce.html.</u>

> 26 Because we are using high-frequency plant-wise data, the carbon cost of emission in our calculation for each 15-minute interval is based only on state-owned generators.

20
variations in institutions. Land policies differed across the occupied lands. At various stages, the rulers’ time horizons changed, which affected policies. On the Qing side, fiscal power became decentralized, causing large variations in regional fiscal capacity. All these changes could fundamentally determine long-term regional development (Blattman and Miguel 2010). Third, relative to the cross-country studies of the consequence of conflicts, analysis that uses sub-national units in China offers measurement and research-design advantages (Djankov et al. 2003). Cross-country studies of wars suffer from the selectivity of data: war-torn countries have far less and poorer-quality data; thus, the worst-hit countries are less likely to be represented, reducing the evidence of the impact of war in the very areas where conflict has most probably taken the greatest tolls. We have systematic data at the sub-national level, giving insights into the effects on both war-torn prefectures and other prefectures that were unaffected by the rebellion. Moreover, our data span a period of more than one-and-a-half centuries, and they have the additional advantage of holding constant national-level determinants (i.e., institutions and culture).

To proceed, we draw from the institutional background and the literature to derive hypotheses. We focus on several aspects of the rebellion and Qing’s responses. First, the land policies in the early and the late stages of the rebellion differed markedly. The protection of land property rights was better in the late stage than in the early one, for example. We hypothesize faster post-war population recovery and better long-term development for the late Taiping areas than the early Taiping areas. Second, since the areas near the rebellion’s capital city, Nanjing, were more likely to be viewed as a stationary base for the rebellion, we hypothesize that their governance and policies were likely better than those of other Taiping areas, as Olson’s theory of stationary banditry implies (Olson 1993). Third, the rebellion occurred in years of solid technological progress. We examine whether the loss of life associated with the rebellion
First, it places a large weight on oil and commodity prices, which are volatile; second, it has a zero weight on services. Headline CPI inflation is also affected by volatile commodity prices, albeit to a lesser extent than the WPI. More importantly, food prices account for nearly half of the CPI, and food prices are often heavily affected by sector-specific non-monetary factors such as weather and harvests. Insofar as shocks to food prices are transient, there is an argument that the RBI should look through them.<sup>14</sup> Such arguments favor a core (non-food- non-fuel) CPI. Counterarguments favoring headline inflation include: (i) that it is easier to explain to the public and thus more effective in anchoring expectations; and (ii) that 12 There have been five different CPI series: CPI Industrial Workers (CPI-IW), CPI Agricultural Labor (CPI-AL), CPI Rural Labor (CPI-RL), and the CPI Urban Non-Manual Employees (CPIUNME). The last one of these has been discontinued. The weights of different components in the baskets for CPI combined, and CPI-Industrial worker are similar; whereas the CPI for agricultural labor and CPI for rural workers have a larger weight on food, nearly 70 percent. See Mohan and Ray (2018) for a discussion of the composition and dynamics of different inflation series. 13 When estimating reaction functions, we follow this practice, using the CPI inflation starting 2012 and WPI inflation before that.

14 Relatedly, it has been argued (by inter alia Banerjee 2020) that IT has led to a worsening of the agricultural terms of trade and declining rural/agricultural incomes. Variants of this argument are that the government has grown more reluctant to raise support prices for agricultural products because it wishes to help the RBI to lower inflation, or that it has grown more reluctant because it fears the wider repercussions on the economy of the RBI raising interest rates in response. We find the first variant implausible (helping the RBI hit its inflation target
shocks on household income and poverty due to the lack of granularity in the weather data. Since we are not able to match households with weather data corresponding to their exact (or slightly offset) place of residence, but only at the district level, there may be underlying variation we fail to capture, as there is little to no variation across households living in the same district. Districts in Paraguay are reasonably small and differences in weather shocks may only vary slightly from district to district, so we expect this issue to be small. Also, as Asuncion and Central are the smallest districts, but simultaneously the most populated ones, we expect the results to be more robust in those locations, covering a large share of the Paraguayan population. Still, more geographically-coded survey data, potentially enhanced with self-reported shocks may help overcome this limitation, and remains a topic for future data collection and research. Third, there may be other weather shocks with devastating welfare effects, such as river flooding, which we do not or only imperfectly cover in our analysis.

# **7 Conclusion and Policy Recommendations**

In this study, we find that weather shocks have significant and heterogeneous impacts on poverty and income in Paraguay. Heat shocks emerge as the most pervasive threat, reducing household incomes by 5% in urban areas and 8.8% in rural areas, while increasing poverty rates by 1.7 and 4.2 percentage points, respectively. Urban areas face distinct challenges from flooding, which increases poverty by 1.9 percentage points, while rural areas are particularly vulnerable to both heat and drought shocks. These impacts are especially pronounced for specific groups: femaleheaded households in rural areas experience poverty increases of up to 7.1 percentage points during heat shocks, while households engaged in primary sector activities see income declines of up to 10% during heat shocks and 12.5% during droughts.

The evidence provided in this study suggests that Paraguay’s considerable poverty reduction over the past decades may be threatened by the
<mark>schemes for current employees with co-financing from employers, but the numbers trained under such programs remain small.</mark> Employer assessments of the adequacy of available skills were elicited in the Enterprise Surveys for a large number of countries, including Tanzania, in 2013. Using a common format across countries, employers were asked whether inadequacies in education posed a major obstacle to their operations. Employers were also asked whether they provided formal in-service training to their current workforce, training that might be used to augment deficiencies in (or to upgrade) preemployment skills. Figure 3 presents estimates of the percent of firms reporting these two skill indicators in Tanzania and several other SSA countries, and for comparison, three other East Asian countries. Note that these figures pertain only to manufacturing firms in different time periods ranging from 2007 in Malaysia to 2013 in Tanzania, Kenya and Zambia.

**Figure 3. Employers’ Views on Education and Firm Training:** **<u>Regional and Asian Comparisons</u>**

<!-- Start of picture text --> 60<br>Malaysia<br>(2007)<br>Vietnam Chad<br>(2009) Kenya (2009)<br>(2013)<br>40 Ghana<br>(2013)<br>Philippines Tanzania<br>(2009) Niger (2013) Gabon<br>(2009) (2009)<br>Zambia<br>(2013) Cameroon<br>20 (2009) Mauritius<br>(2009)<br>0<br>0 20 40 60<br>Percent of Firms view Education as a major obstacle<br>Percent of Firms Providing Training<br><!-- End of picture text --> Source: Enterprise Surveys, various years <u>Note: East Asian countries are shown in the graph as red dots, African countries as black dots.</u> Two key observations can
Again the intensive margins play a more significant role in boosting trade. When the _Share(Trade-partner bankijt)_ grows by one standard deviation during the crisis, _Log(Exportsijt_ ) increases by 0.05 standard deviation. The corresponding effect for either the financial development or the extensive margin is more muted at 0.01 increase in the standard deviation of exports.<sup>13</sup> The results are reversed when we examine the spillover effects of banks from the trade partners region, which is in line with the results above that do not control for the crisis period.

A possible concern is the endogeneity of the financial development as the supply and demand channels may influence and determine fluctuations of the variable. The level of fi-

> 13The result can be interpreted through the lenses of Besedeˇs, Kim, and Lugovskyy (2014). They develop a theoretical model to show that credit constraints play a key role in early stages of exporting, but not in later stages. The model is supported by empirical evidence from product-level data on exports to 12 European Union members and the United States. In our case, we cannot control for the duration of export experience, and thus cannot directly test the implications of Besedeˇs, Kim, and Lugovskyy (2014). However, the information channel may have differential impacts on exports depending on the financial conditions faced by the sub-region.

8
., Nelson, A., 2006. Determining Global Population Distribution: Methods, Applications and Data. Advances in Parasitology 62, 119-156.

- Barton, G.A., 2002. Empire Forestry and the Origins of Environmentalism. Cambridge University Press, Cambridge.

- Berry, S., 1988. Property rights and rural resource management: the case of tree crops in West Africa. Cahiers des Sciences Humaines 24 (1), 3-16.

- Bhagwat, S.A., Willis, K.J., Birks, H.J.B., Whittaker, R.J., 2008. Agroforestry: a refuge for tropical biodiversity? Trends in Ecology & Evolution 23, 261-267.

- Bluffstone, R., Yesuf, M., Uehara, T., Bushie, B., Damite, D., 2015. Livestock and Private Tree Holdings in Rural Ethiopia: The Effects of Collective Action Institutions, Tenure Security and Market Access. The Journal of Development Studies 51, 1193-1209.

- Booth, F.E.M., Wickens, G.E., 1988. Non-timber uses of selected arid zone trees and shurbs in Africa, FAO Conservation Guide. Food and Agriculture Organization of the United Nations, Rome.

- Brottem, L., 2011. Rediscovering “Terroir” in West African Agroforestry Parklands. Society & Natural Resources 24, 553-568.

- Cattaneo, A., 2001. Deforestation in the Brazilian Amazon: Comparing the Impacts of Macroeconomic Shocks, Land Tenure, and Technological Change. Land Economics 77, 219-240.

- Center for International Earth Science Information Network (CIESIN) - Columbia University, International Food Policy Research Institute (IFPRI), World Bank, Centro Internacional de Agricultura Tropical (CIAT), 2011. Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Urban Extents Grid. NASA Socioeconomic Data and Applications Center (SEDAC), Palisades, NY.

- Davis, B., Winters, P., Carletto, G.,
3%|0.01|0%|-1.12|9%|
|Capital|1.31|-8%|-0.58|4%|0.02|0%|
|Public|0.00|0%|-1.38|9%|-2.51|20%|
|Public Donations|||-0.45|3%|||
|Public transfers|||-0.90|6%|||
|Pensions|||0.01|0%|-2.51|20%|
|Other non-labor income|||-0.04|0%|||
|**Other**|**-7.50**|**43%**|**-0.78**|**5%**|**2.50**|**-20%**|
|Age/gender|-3.48|20%|-1.17|7%|-1.18|9%|
|Consumption to income ratio|0.93|-5%|-1.73|11%|3.43|-27%|
|Unexplained|-4.95|29%|2.12|-13%|0.26|-2%|
|**Total**|**-17.34**|**100%**|**-16.13**|**100%**|**-12.84**|**100%**|

- Source: Own estimates based on Peru's ENAHO 2004 -2010, Thailand's SES 2000 -2009, and Bangladesh's HIES 2000 -2010.

- 1/ Refers to the secondary occupation of individuals who work as self-employed agricultural workers.