rafmacalaba/data-use-mentions-extended huggingface dataset:
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calendar, in a third crop season, which is irrigated if there is sufficient water. In Southeast Asia, the introduction of short-season rice varieties allowed farmers to plant the second rice crop with a short-season variety and follow it in the dry season with high-yielding corn or soybeans, which have longer growing seasons (100 days or more) than those of traditional varieties. In north India, farmers were able to follow a short-season rice variety with a short-season wheat variety, thus growing two major grain crops a year.<sup>15</sup> In such instances, nev, rice varieties have allowed farmers to adopt improved varieties of other crops. Improved facilities for local **research** and extension could play a major role in adapting crop varieties **to** fit particular niches in the crop rotation and to develop varieties resistant to local pests and diseases.1 6 3.22 Improvement or modernization of irrigation systems to permit diversification into non-rice crops has been complicated by the sharp drop in rice prices in the early 1980s. Until that time, most rice irrigation projects, including those for which all the infrastructure down to the onfarm water delivery works was built, were viable. Under the economic conditions of the 1980s, the only viable investments in rice irrigation projects are those that take advantage of sunk costs in existing infrastructure, and a detailed analysis of each project would be needed because of the sensitivity of the rate of return to low rice prices. Investment in improving the tertiary system and the distribution system may not be justified unless there is, as a result of using the water saved through more efficient operation, either a substantial increase in rice yields or an increase in cropping intensity, or both. Increased production of rice alone may not economically justify such improvements; the land may have to be planted to higher-value crops. Investment required for crop 15/ See Barker and Herdt, pp. 26-27.

- 16/ This section draws on field surveys conducted in Indonesia and reported in
<!-- Start of picture text --> Figure 4.3b. Urban employment declined in Textile and Chemical Fibers and other 8<br>manufacturing sectors<br>Textiles: # jobs lost: 507,140 Chemical fibers mfg:<br># job lost: 58, 335<br>2900<br>2800 2842 2849 270 263.37<br>8<br>2700 250<br>2600<br>230<br>2500<br>210<br>2400 204.73 205.04<br>2300 2,334 190 3 3<br>2200 170<br>2100<br>150<br>2000<br>20022003200420052006200720082009<br>Source: Banister and Cook, Monthly Labor Review March 2011, and NBS, China Labor Statistical Yearbook 2010<br>(for 2009 data). See Annex 1.<br><!-- End of picture text -->

- Evidently, rising wages in labor intensive industries have _already triggered relocation of low wage jobs overseas_ . Many lower wage countries in China‘s neighborhood such as Vietnam, Laos, Cambodia, and even Bangladesh are emerging as the new growth nodes of the garments, footwear and other labor intensive industries. How many jobs each country can attract depends on the incentives package it offers to investors.

- Perhaps the most critical channel presently is OFDI flows from China and other emerging market countries to the manufacturing sectors in lower wage countries. This is unsurprising. OFDI from South Korea and Hong Kong SAR, China fuelled much of the early investments in China‘s labor intensive industries when their wages increased and China followed them as flying geese. Now it is the turn for nearly all lower income labor abundant countries to fly after the leading dragon. Currently, the relocation of jobs from China‘s labor intensive sectors to Vietnam and other neighboring countries are financed by both transnational corporations including those from China, as well as local entrepreneurs given the
in line with most existing studies on informal firms’ entry and exit, the latter is a novel and important indicator for studying how household businesses cope with economic shocks in the short term. To examine sectoral impacts, we also rely on data on operating industry and location of the business.<sup>10</sup>

# **2.2 Entry and exit**

By the nature of the dataset, this analysis focuses only on tax-registered household businesses. While we do not observe HBs that are not tax-registered, data from the latest Vietnam Enterprise Census (VEC) that is collected every five years, the last time in 2017, shows that there are approximately 5 million HBs operating in the country.<sup>11</sup> Table 1 shows the total count of tax filings retrieved from the DoT portal for the January 2018-August 2020 period. The first three columns show records for regular annual filings. Column 1 reports the total number of (once-a-year) annual lump-sum filings, the majority of which usually take place each year in January (approximately 90 percent of records). The number of registered HBs increased slightly from over 908,679 firms in 2018 to 917,917 in 2019. The total registered HBs was on the rise in 2020, with 907,472 filings having been recorded as of August (note that since most filings happen in January including for the year 2020, the existing statistics mostly capture pre-COVID-19 tax filings). Overall, these numbers represent approximately one-fifth of the total household businesses operating in the country.<sup>12</sup> It is, therefore, noted that the majority of household businesses in the country are not tax-registered.<sup>13</sup> In each year, we distinguish between incumbents and new businesses using available identification information (tax ID). “Repeated” (column 2) is the number of filing records in a given year that also appeared in the previous year, and “New” (column 3)
**Table 1. Human Development Opportunity Indicators for Egypt, 2000 and 2009**

|_Category_|_Label_|_Definition_|
|---|---|---|
||Complete primary education on<br>time **|Completion of below intermediate education on time<br>(primaryschooling)|
|Education|Complete secondary education on<br>time **|Completion of intermediate education on time (general<br>or technical secondary schooling).|
||School attendance, 9-15 **|Attended school, 9–15|
||Water **|Access to clean water without interruption,, 0–17|
||Sanitation **|Access to adequate sanitation, 0–17|
|Basic<br>housing|Lighting energy source **|Access to adequate lighting energy source, 0–17|
|<br>services|Cooking energy source **|Access to adequate cooking energy source, 0–17|
||Non-overcrowding, 0-5 **|Children under 5 in non-over-crowded homes|
||Telephone|Access to a telephone, 0–17|
||Assisted birth delivery*|Access to institutionally assisted birth delivery, 0-4|
|Early<br>|Post-natal care, 0-5*|Access to adequate post-natal care, 0-5|
|childhood|Prenatal care, 0-4*|Access to prenatal care for children under age 4|
||Immunization vaccines, 0-4*|Access to complete vaccinations, children under age 4|
||Non-wasting, 0-4 *|Adequate nutrition by weight-for-height measures for<br>children under age 4|
|Nutrition and<br>hunger|Non-stunting, 2-17*|Adequate nutrition by height-for-age measures for<br>children ages 2–17|
||Non-underweight, 0-17*|Adequate nutrition by weight-for-age measures for<br>children 0–17|

* Available from the EDHS 2000 and 2008 surveys. ** Available from the CAPMAS HIECS 2000 and 2008.
would imply that projections (of global impact) using distribution-neutral GDP growth rates of countries are likely to mildly understate the pandemic’s aggregate impact on global poverty and income inequality.

Inequality impacts of the pandemic should not be seen only through the lens of income inequality, but rather as a spectrum of dis-equalizing effects on multiple dimensions of well-being, some of which are likely to be harmful for social mobility and long-run inequality. COVID-19 struck in a world with already high structural inequality and low socioeconomic mobility in most of the developing world. As the shock led to a widening of pre-existing gaps in opportunities and incomes in many countries, it may have triggered processes that continue widening gaps between privileged and vulnerable groups even as economic growth rebounds. This is the reason why major epidemics in the last two decades have been associated with higher within-country inequality five years later (Furceri et al., 2020). While the long-term impacts of COVID-19 on inequality in developing countries cannot be known yet, HFPS data for some countries from the early days of economic recovery can be used to identify patterns in the trajectory of household well-being. An inequitable recovery would foreshadow a higher long-term risk to inequality and social mobility.

As economic activity starts to return where policies are becoming less stringent, there are reasons to be concerned about the pandemic’s more lasting consequences for inequality and social mobility. Globally, the recovery in 2021 appears to be concentrated in the upper half of the global income distribution, while the lower end of the distribution who suffered the most losses in 2020 fall further behind as growth outlook for many developing countries lags the recovery in richer economies. On the positive side, across a sample of 17 developing countries with comparable HFPS data between May-June and August-September (2020) where policies became more conducive to economic activity, significant improvements in employment, incomes and food security are observed. However, the employment recovery appears to be both slow and uneven. Employment among those who suffered larger initial shocks – women, non-college-educated, and urban workers –
evaluations of **enterprises** participating in SME programs are rare, not only in Mexico but elsewhere in industrialized and developing countries as well. An exception are two impact evaluations of the CIMO program conducted by the Ministry of Labor and Social Welfare of Mexico (STPS), one in 1995 the other in 1997, that compared a group of program beneficiaries to a control group of SMEs outside the program.

This paper takes a second critical look at the methodology used previously to evaluate the CIMO program, taking advantage of the fact that the research team was provided access to the raw data collected for both evaluation studies. This re-examination of the CIMO data serves several purposes. First, it provides a broad description of the way in which STPS first designed and implemented the net impact evaluation study and then analyzed the data to arrive at conclusions regarding the impact of program participation on intermediate outcomes and on firm performance. Second, it asks whether the panel data could have been analyzed differently, to get more accurate estimates of the impacts of program participation that would allow calculation of reliable cost-benefit measures of CIMO interventions. Specifically, it addresses the apparent contradiction between the finding that program participation improved intermediate outcomes of CIMO firms, but was nonetheless associated with lower post-program levels of performance. To anticipate the results that follow, this paper concludes that the contradictory result is driven principally by self-selection of weaker firms into the CIMO program.

Section II provides a brief overview of the CIMO program, followed in Section III by a review of the methodology used by STPS in the two impact evaluations of the CIMO program (STPS 1995, 1997). Essentially, STPS adopted a quasi-experimental approach in which two groups of enterprises were followed over time – one group that benefited from the CIMO program and a control group that did not – to measure the impacts of CIMO on enterprise and worker performance. Section IV reports the findings for our re-examination of the data, where production functions were estimated that fully exploited the panel (longitudinal) nature of the firm-level data
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- RAM, R., 1986, "Government Size and Economic Growth: A New Framework and Some Evidence from Cross-Section and Time-Series Data," American Economic Review, 76 (March), p. 191-203.

- RANA, P.B., 1987, "Foreign Capital, Exports, Savings and Growth in Asian Region," Savings and Development, no. 1.

- SINGH, R.D., 1985, "State Intervention, Foreign Economic Aid, Saving and Growth in LDCs: Some Recent Evidence," Kyklos, 2, p. 216-232.

- STEWART, M.B. and WALLIS, K.F., 1981, Introductory Econometrics, 2nd ed., Basil Blackwell, Oxford.

- SUMMERS, R. and HESTON, A., 1984, "Improved International Comparisons of Real Product and its Composition: 1950-80," Review of Income and Wealth, June, no. 30, p. 207-262.

- TYLER, W.G., 1981, "Growth and Export Expansion in Developing Countries," Journal of Development Economics, vol. 9. August, p. 121-130.

- VENIERIS, Y.P. and GUPTA, D.K., 1983, "Sociopolitical and Economic Dimensions of Development: A Cross-Section Model," Economic Development and Cultural Change, , 727-756.

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which interpolated EC values for each cluster location to get groundwater salinity data for each of the BDHS clusters were extracted. Groundwater arsenic concentration and groundwater depth point data values were obtained through the same source and processed by the same interpolation technique.

The geographical distribution of all BDHS clusters from 2000 to 2014 and its categorical salinity level are shown in Figure 1. There are no official guidelines for drinking water in Bangladesh or worldwide considering the human health perspective. Hence the water salinity categories defined by FAO were used. The level of drinking water salinity is color marked at each clusters’ geo-location according to the classification by the Food and Agriculture Organization (FAO) of the United Nations for irrigation water: freshwater (EC<0.7 mS/cm), mild-salinity (EC>=0.7 and <2 mS/cm), moderate-salinity (EC>=2 and <10 mS/cm), and severe-salinity (EC>=10 mS/cm). Salinity is clearly higher in the coastal regions than inland. Barisal division has the highest number of household clusters exposed to severe-salinity (above 10 mS/cm) while Khulna has the second highest number of household clusters exposed to moderate salinity (above 2 mS/cm). Clusters with high level exposure to salinity in Chittagong and Dhaka are mostly located along the coast. For the inland divisions, Rangpur, Sylhet, and Rajshahi, household clusters have drinking water salinity level under 0.7 mS/cm.

# **IV. Methodology and Statistical Analysis**

The BDHS data sets were pooled, and revised sample weights were calculated following denormalization of the standard weights. Next, the survey-weighted proportions of neonatal and infant mortality were computed for each survey year and presented in Table 1 for the period 2000-2014. A general decline in infant and maternal mortality is noted even as the number of live births increased indicating overall declines in both infant and maternal mortality rates. Since our key objective is to evaluate the association between groundwater salinity and neonatal or infant
31 traffic between day and night by railways companies or to model allocation between public and private vehicles in urban settings. These models are generally too aggregate to meet the needs of a regulator but they are used anyway because they can provide useful initial insights. What matters from the viewpoint of a regulator is that the cost account for many of the variables that will be subject to regulatory supervision such as tariff/tolls or government control such a fuels but these are seldom take into account in a sensitive enough way to be useful because they do not account well enough for the different characteristics of the various types of users.

The main aggregate methods can be classified in 2 groups: qualitative or intuitive methods and "mathematical or statistical" methods. Among the qualitative methods, it is worth pointing to a series of techniques based on expert assessment or field surveys of expectations designed to complement the quantitative estimates. The expert assessment is least refined since it assumes an expert can assess the impact of mutliple factors on a potential _new_ business environment-since in the context of privatization, new business opportunities are typically being created.

Field surveys of expectation are targeted to anyone who can be affected by the project and is in a priviledged position to assess the prospects. A refined version of these surveys is provided by the techniques called _Delphi,_ where the experts forecast and get a _feed-back_ on the results from the full sample of people surveyed allowing a series of iterations until some degree of convergence is achieved. This approach is used by IATA or EUROCONTROL for instance for airline traffic forecast. These techniques can be useful at the national or regional level but are unlikely to be useful to forecast traffic and traffic risk on a given corridor. Finally, the technique of _brain-storming,_ quite common in socioliogy, consists in putting together a group, for instance users, and through in a series of question to be discussed by the group. This technique is used by Puertos del Estado in Spain complement the more analytical forecasts of the spanish ports.

The more quantitative
public support for a reduction in energy subsidies across countries is unpacked by examining heterogeneity between respondents based on their prior knowledge and beliefs, such as their perception of their relative income.

Second, this large-scale, online randomized survey experiment adds to the growing body of work using this approach to understand how people reason and how their knowledge and beliefs influence their policy preferences. Seminal work along these lines using large-scale, randomized survey experiments has been conducted in recent years in the United States and Western Europe to examine a range of topics, such as inequality (Kuziemko et al. 2015), social mobility (Alesina et al. 2018), and immigration (Alesina et al. 2023). Two of the latest works using this methodology involved testing the impact of information about climate change on public support for policies in high- and middle-income countries (Dechezleprêtre et al. 2022; Dabla-Norris et al. 2023), but these studies did not examine energy subsidies. The current study extends this literature in several ways. It examines public support for energy subsidy reform, which is somewhat distinct from many other topics, as there is a notable lack of awareness about the existence of subsidies (as opposed to incorrect beliefs or misperceptions), the implications of removing energy subsidies are very tangible (i.e., higher energy prices) and there is a unique legacy of sensitivity around this topic (e.g., riots in many countries as a response to removal of subsidies). It also is designed with several layers of both experimental and nonexperimental variation, which allows for a deep understanding of what drives support for reform, in part by exploiting natural variation across countries (such as variation in the main type of energy subsidized). Finally, this is one of the largest randomized survey experiments in middle-income countries in this literature, and it incorporates best practices for the design of randomized survey experiments from cross-country research in high-income countries.

The paper is structured as follows. Section 2 provides background information about the related literature,
- What definitions are used by the country to classify government expenditures as capital? Are there forms of spending that could be classified as capital expenditures that are not considered as such, for example, rehabilitation?

- Is there a definition for rehabilitation expenditure, and is rehabilitation distinguished from other capital spending? (Provide sector nuances as necessary.)

- What is the definition of maintenance spending, and are there forms of spending that could be considered as maintenance that are not classified as such—for example, periodic maintenance? What are the criteria for splitting operating expenditures from maintenance expenditures?

The report should indicate whether the country has a dual budget system (that is, separate recurrent and development budgets) or a unitary budget (as is more common in francophone countries).

The basis for recording ―released‖ expenditure figures in template 10 should be indicated, that is, whether the figures represent supplementary budgets, allocations made by the ministry of finance (Ministry of Finance), or a combination of the two.

# **_c.2 Assumptions_**

It is also important to record all key assumptions<sup>10</sup> made in compiling the quantitative templates.

Where—in the absence of a centralized information source—a sample of sub-national governments or SOEs has been selected, the basis for making the selection should be reported. The selection should generally be made on the basis of the relative importance of the organization‘s spending. Any deviations from this principle should be indicated and explained.

Sometimes it may not be possible to directly map a country‘s functional and economic classifications to the GFSM 2001. In these situations is best to not split expenditures, but instead to allocate the expenditure to the most important function or economic item. Any assumptions of this kind should be carefully documented.

Differences in financial reporting for SOEs between countries following different accounting traditions (for example, Anglophone and Francophone Africa) is frequently an issue, specifically in relation to the income statement. These differences should be
technologies and products of nationally-owned intellectual property rights in high-tech industries limits the profit-making capabilities of domestic enterprises. The growing gap in the capabilities between advanced countries and China defies easy solutions. Promoting creative entrepreneurship and creating an innovative milieu should evolve into key development programs.

# **_III. Targeting innovative cities: comparison between Beijing and Shanghai_**

# **Overview**

Beijing and Shanghai are two of China’s leading cities. Each plays a different role in the national economy and these roles are continuing to evolve.

**Table 1:** Major indicator of Beijing and Shanghai, 2002

||Area<br>|Population*|GDP|GDP/Capita|
|---|---|---|---|---|
||(1,000km<sup>2</sup>)|(1,000)|(RMB billion)|(RMB)|
|Beijing|17|14,230|321.3|28,449|
|Shanghai|6|16,250|540.9|40,627|

_Note_ : * only registered residential population, floating population not included _Source_ : Beijing Statistic Yearbook 2003; Shanghai Statistic Yearbook 2003.

# **Changing roles in the national economy**

Since the establishment of the socialist economy, Beijing has developed into an industrialized city with a fully integrated industrial structure covering the fields of electronics, iron and steel, machinery, chemicals, textiles, automobile manufacturing, etc. But Beijing is constrained from developing large industrial complexes by the lack of water resources. This bottleneck limits Beijing’s industrialization. Still, Beijing has an irreplaceable position in the national economy and is often the first choice for foreign companies wanting to locate in China. These advantages are quite crucial in developing knowledge intensive business services.

Shanghai is ideally located to serve as the gateway to the Yangtze Valley area from the sea. But before the first Opium War between China and the
Yes|Yes|Yes|Yes|
|Initialproductivity|No|Yes|No|Yes|No|Yes|No|Yes|
|Observations|14,999|11,814|15,306|11,950|7,945|6,074|8,150|6,161|

**N** otes: All continuous variables are winsorized at the 1% and 99%. Weeks to continue operating with cash available was only included as a question in the first two rounds of data collection.

Robust standard errors in parentheses

* p<0.10, ** p<0.05, ** p<0.01

-No statistically significant differences across types of informality in Panel B, cols. 3 and 4.

-Differences between necessity firms and the other two types are statistically significant at the 10% level in Panel B, cols. 7 and 8.

-The coefficients of PCA 1 and PCA 2 are statistically different at the 10% level in Panel C, cols. 1 and 2; and at the 5% level in panel C, cols. 5 and 6. Source: Authors’ calculations using data from the World Bank Business Pulse Survey (BPS).