rafmacalaba/datause-encoder-data huggingface dataset:
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Figure 7. Degree of Competition in Infrastructure ODA Procurements <!-- Start of picture text --> (Roads) (Electricity)<br>0.40 0.40<br>Avg. number of<br>0.35 bidders per 0.35 Avg. number of<br>0.30 auction = 6.1 0.30 bidders per<br>auction = 4.6<br>0.25 0.25<br>0.20 0.20<br>0.15 0.15<br>0.10 0.10<br>0.05 0.05<br>0.00 0.00<br>2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21<br>Median Number of bidders Median Number of bidders<br>(Water and sewage)<br>0.40<br>0.35<br>Avg. number of<br>0.30 bidders per<br>auction = 6.2<br>0.25<br>0.20<br>0.15<br>0.10<br>0.05<br>0.00<br>2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21<br>Median Number of bidders<br>Frequency Frequency<br>Frequency<br><!-- End of picture text --> <!-- Start of picture text --> Source: Author’s calculation based on JBIC and World Bank data.<br><!-- End of picture text -->

# **III. AN EMPIRICAL MODEL AND DATA**

Following the existing empirical auction literature (e.g., Porter and Zona, 1993; Gupta, 2002; Iimi, 2006), the following reduced-form equilibrium bid function is estimated: where _bit_ is _i_ ’s bid amount at auction _t_ . It is noteworthy that our dependent variable is the bid amount of all bidders, i.e., both winning and losing bidders. Note that in theory losing bids are as informative as winning bids to estimate the equilibrium bid function. The ODA-related procurement process normally uses a simple first-bid sealed-price auction format. Therefore,
the monthly Sri Lanka Consumers’ Price Index.<sup>5</sup> Each round also attempted to collect additional information about the firm or owner, in the form of special modules to measure owner ability, risk aversion, labor history, and other characteristics. We will discuss some of these measures in detail later in the paper. In addition, the first, fifth, and ninth and eleventh waves of the panel also included a household survey, measuring household expenditure, school attendance, and work participation of all household members.

Attrition in the SLMS is quite low. 370 of our 387 firms reported profits in the baseline survey. In the fifth wave (one year later), 348 firms reported profits, an attrition rate of only 5.9 percent. In the eleventh wave (three years after the baseline), we still have 319 firms with reported profits, for cumulative attrition of 13.8 percent. We concentrate our analysis on the unbalanced panel of 365 firms reporting at least three waves of profit data. There is no significant difference in attrition rates by gender: 63.5 percent of males are in all 11 waves, compared to 63.7 percent of females, 93.4 percent of males have at least 3 waves and are included in the sample we used after trimming large changes in profits, compared to 95.8 percent of females (p-value = 0.22).

# _2.2. The Experiment_

Firms were told before the initial survey that as compensation for participating in the survey, we would conduct a random prize drawing, with prizes of cash or inputs/equipment for the business. The prize consisted of one of four grants: 10,000 LKR (~$100) in materials for their business, 20,000 LKR in materials, 10,000 LKR in cash, or 20,000 LKR in cash. In the case of in-kind grants, the materials were selected by the enterprise owner, and purchased by research assistants working for the project.<sup>6</sup> Cash

> 5 Source: Sri Lanka Department of Census and Statistics, <u>http://www.statistics.gov.lk/price/slcpi/slcpi_monthly.htm</u> [accessed February 17, 2007]. Inflation was low over the first year of the survey, with a 4.0 percent annual rate. Inflation was higher in the second and third years of the survey, with an annual rates of 18.6 percent between March 2006 and March 2007, and 28.0 between March 2007 and March 2008. The Sri Lankan price indices were revamped in November 2007, and the all island index we use was discontinued. We estimate the March 2008 value of the index by applying the rate of increase in the Colombo area index between March 2007 and March 2008.

6 In order to purchase the goods for these entrepreneurs receiving in kind treatments, research assistants visited several firms in the evening to inform them they had won an in kind prize. The winning entrepreneurs were asked what they wanted to buy with the money, and where they would purchase it. The research assistants then arranged to meet them at the market where the goods were to be purchased at a 7

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tend to oversample large and, therefore, the results should be primarily interpreted in relation to firms of larger size. An additional advantage of the survey is that it collects substantial balance sheet and other information regarding the investment climate, which enables the linkage of innovation efforts to performance and potential obstacles.<sup>8</sup> The standard Enterprise Survey covers topics such as characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. A number of the survey questions objectively ascertain characteristics of a country’s business environment and assess the respondents opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.

The innovation survey differentiates between product and process innovation, and two nontechnological innovations, marketing and organization. However, there is significant confusion when identifying the different types of innovation outcomes by firms in the survey. For example, new marketing processes such as discounts, new packaging or new client segments are sometimes identified with process or product innovations. The fact that interviewees provide a recorded description of the product and process innovations allows us to verify the identified product and process innovation and clean the wrongly attributed cases, or the cases that do not constitute an innovation at all (the detailed methodology to clean the data is described in the appendix). Overall the cleaning exercise results in a decrease in both product and process innovation rates due to cases of either not an innovation or a misclassification.<sup>9</sup> The appendix also contains a description of how we inferred whether process innovations could also be categorized as automation.

including manufacturing and services. In total our estimation sample is based on over 15,000

> 8Sector breakdown is usually manufacturing, retail, and other services. For larger economies, specific manufacturing sub-sectors are selected as additional strata on the basis of employment, value-added, and total number of establishments’ figures. Geographic regions within a country are selected based on which cities/regions collectively contain the majority of economic activity. Enterprise Surveys implemented in Eastern Europe and Central Asian countries are also known as Business Environment and Enterprise Performance Surveys (BEEPS) and are jointly conducted by the World Bank and the European Bank for Reconstruction and Development. For more details see Enterprise Surveys (http://www.enterprisesurveys.org).

> 9Overall both product and process innovation rates fall from 37% to 31%.

13
The second major finding of this paper, beyond that on the further reduction of skill premia and inequality, is that the long awaited rise of the middle class in Latin America is finally happening. According to the 10-50 dollar a day definition of the middle class adopted here, in 2005 less than a quarter (24 percent) of the Latin American population, around 140 million of people, belonged to the middle class. But, by 2030, 310 million, or close to half of the regional population (43 percent) will be in the middle class. There will be significant heterogeneity across countries: the middle class is expected to expand the most in Peru, Chile, Venezuela and Argentina, but small increases will be observed in Mexico, Brazil and Colombia.

More importantly, due to the equalizing changes of within country distributions, middle class members will not anymore be close to the top of the distribution within their own countries. In 2005 and for the Latin America region as a whole, 80 percent of middle class individuals belonged to the top two deciles of the income distribution. By 2030, 40 percent of the middle class members will be either in the seventh or in a lower decile. Being in the middle class (defined in 10-50 US dollar absolute terms) will also mean being closer to the middle (in relative terms) of the distribution. Latin American countries will look much more as true middle class societies.

This encouraging result is not a _certain_ result. In particular, achieving it will be easier for countries with lower initial levels of inequality and progressive growth incidence. But, with inequality close to the high levels of Colombia, growth alone may have a small impact on the expansion of the middle class. Policies that directly contribute to more equity, by means of providing fairer access to productive assets, will be needed and their results may take longer to materialize. After all, it took a few decades for the large education effort to finally impact the skill premium and inequality.

The paper is organized as follows. The next section briefly describes the modeling tools used to assess changes in the global income distribution: the global dynamic computable general equilibrium model Linkage and the Global Income Distribution Dynamics (GIDD) model. It sketches the methodology, assumptions, and data behind the GIDD model. Section 3 presents the macroeconomic results of the baseline scenario. Section 4 presents the micro results, namely the changes in the global income distribution and the changes of the global middle class with special emphasis on Latin America. The final section offers some concluding remarks.

# **2. Methodology**

The empirical analysis in this paper relies on two tools developed at the Development Economic Prospects Group of the World Bank: the LINKAGE global computable general equilibrium (CGE) model and the Global Income Distribution Dynamics (GIDD) microsimulation 4
# **<mark>Exhibit 4</mark>**

<!-- Start of picture text --> Frequency Distributions of Perceived<br>SARS Risk in Taiwan (China)<br>70<br>Fatal Risk<br>60<br>Knowledge<br>50 Controllability<br>40<br>Source: Liu et al<br>(October 2003)<br>30<br>20<br>10<br>0<br>1 2 3 4 5<br>Low/Less More/Higher<br><!-- End of picture text --> Life (VSL, interpreted as the marginal rate of substitution between income and mortality risk) in the range of $4-9 million per life, considerably higher than previous estimates of the VSL in Taiwan (China), which were in the range of $0.5-1.5 million. The authors suggest that the high estimates of VSL from SARS respondents may be attributable to the high degree of salience and concern about SARS, or to the possibility that respondents believed the risk they faced to be higher than the probabilities used in the survey (3 or 5 per 100,000 per month).

Finally, is it the case that, while people may make significant mistakes in forming subjective probabilities about disease events, they will tend to learn and improve these estimates over time? Rabin (1998) notes that while learning is a reasonable conjecture, it is not nearly as valid in many experimental situations as economists generally imagine. The amount of experimenting with new strategies or learning will depend on the opportunity costs of these activities, so that people could well stick with views and choices that turn out sub-optimal in the long run. (Mullainathan and Thaler 2000). However such persistence in error seems less likely in epidemic disease situations, when errors in judgment have significant short run costs. Lau et al (2003)

# **<mark>Exhibit 5</mark>**

<!-- Start of picture text --> Hong Kong: Perceived chance * of infection for<br>self versus new SARS cases on previous day<br>100<br>* Chance perceived as<br>high or very high. April 1<br>80<br>60<br>March 28<br>40 April 8<br>March 21<br>20<br>Source: Lau et al (2003)<br>May 12<br>0<br>0 2 4 6 8 10 12 14 16<br>Perceived Chance of Infection<br>b e r o f S A R s C a s e s<br>N u m<br><!-- End of picture text --> appears to be unique in providing survey data (for Hong Kong) on how perceptions of SARS risk changed over time. Exhibit 5 maps the proportion of people who thought the chance of getting infected was high or very high against the number of SARS infections reported on the previous day between March and May 2003. The proportion of people concerned about a high risk of infection increased rapidly from around 4 to 14 percent of the population in late March, before coming back down to near 4 percent by mid May. These changes in perceptions were not random, tending to rise and fall in association with the number of new infections reported on the previous day. There is also a suggestion in the data that the impact 15
Figure Oa: Predicted<sup>IMR, 1986 tor different levels of</sup> Female Secondary<sup>Enrollment, 1976, 8 GDP pc, 1985</sup> <!-- Start of picture text --> IMR<br>140<br>IMR with Fer. Ed.<br>120 IMR. wth GDPo p<br>100 - - - ~~~~~ - - - - -~~~~~ -<br>100~~~~~~~~~~~~~6<br>80~~~~~~~~~~~~~~6<br>--<br>4 00 800 1900 tB 0029 028009 009800 900480<br>20 e - - t --<br>0 a 10 - 20 - s0 40 so so T0 so t0 H 100<br>300 800 1300 1800 28002800830089004300 4000<br><!-- End of picture text -->

**NoW.s e.g..I.d .. Meoa....Oahi&AoOemy gtem *S.** I **Table atimoaltu**<sup>**4. beMidimof**</sup> Wish **Big elk vs,l.bi..** II)o **gor** aigoita **OaStebi c Ewoelo. our boi61** 04 **TColm .l**

Figure 8b: Predicted<sup>IMR, 1985 for different levels of</sup> Population per Physician,<sup>1984</sup> <!-- Start of picture text --> 10IMR<br><!-- End of picture text --> <!-- Start of picture text --> go IMR with Pop/Phym.<br>0 8 0 6 20 tO 004<br>20 X t<br>0<br>80aS0@8 500@602000900aeo0oa00CO0oo000o 4000 1000<br>MOte,- 0.i061.t.d 1101 04. S feb10 4. beldiftg all 0th.t<br>.-. aga P01041Bt@a pot 111iaIisea (10491. aoSol. 1mbf isOSei<br><!-- End of picture text -->
An influential paper by Martin, Thierry, and Thoenig (2008) argues that this conventional wisdom is only partially true, and depends crucially on whether trade is bilateral or multilateral in nature. Bilateral trade increases the opportunity cost associated with the loss of trade between two countries, and makes them therefore less likely to engage in war. In contrast, multilateral trade decreases bilateral dependence to any given country and thus the cost of bilateral conflict, making countries more likely to end up in war. The recent war in Ukraine and Russia’s reliance on China to survive the trade disruption caused by sanctions imposed by the West fit this paradigm.

On the other hand, one might counter that multilateralism had been severely compromised prior to the war, and that it was in fact fractures in the world trading system that ultimately enabled the invasion of Ukraine. For instance, one might wonder if China would have been willing to provide a lifeline to Russia if it its economic relationship with the West had not deteriorated so much in the past four years. The decline of multilateralism may not be evident in the trade data yet, though trade between the US and China has declined following the trade war between these two countries. But trade data may take some time to adjust to reflect changes in attitudes and political climate that contribute to armed conflict.

The period leading to World War II provides a case in point. De Bromhead et al (2019) study interwar trade and show that in the 1930s there was a dramatic shift away from multilateral trade towards trade within empires, or informal spheres of influence. For instance, the British Empire accounted for 30 percent of UK imports in 1929, but 42 percent by 1938. Several observers have argued that this changing nature of trade not only reflected, but potentially exacerbated, the international tensions of that period, an era now known as “pre-belligerency.” The changing nature of globalization in the past five years bears an eerie resemblance to that time.

# **III. Conclusion**

The future of globalization is highly uncertain at this point. But one thing is certain: There is no longer support for market-driven, unbridled globalization. Governments are now investing to reallocate international supply chains from a free-market equilibrium. A challenge in this new era is that such investments are motivated by objectives that are hard for researchers and the public to evaluate. When globalization was motivated primarily by the objective of economic 42
and quality of facilities across rich and poor districts, the models are also estimated separately for households from poor and rich districts, with sample sizes of 682 and 1,104 respectively.<sup>13</sup> The 88 districts that GDS-2 households belong to are classified into rich and poor districts using gross regional domestic product (GRDP) per capita for each district – the bottom 50 percent of districts by GRDP per capita are defined as poor districts, while the top two quartiles are defined as rich districts.

For each of the three samples, two types of models are used that are different only in the way household’s expectation of quality or _QE(x)_ is proxied. In model (1), in the absence of a single, readily-identifiable indicator for expectations, we proxy expectations with a range of household characteristics, such as gender, age, education levels, religion, household expenditure and social status. An index of whether respondents have information on bribery and corruption in health services, budget and development plan at the sub district level and the source(s) they rely on for such information is also included. This index indicates the information a household has on governance environment in which the facility operates. Model (1) allows us to see how household level factors influence satisfaction with a health facility, because of the way they influence household’s expectations regarding health services. In model (2), we create a single index from all the variables used as a proxy for expectation (based on the first principal component) to represent expectation. The single index for expectation is useful to see how expectations on the whole matter for household’s satisfaction with a health facility.

Quality of public health services is modeled using the following dimensions of quality measured from the facility survey: (a) the _coverage_ area of the facility; (b) the types of medical

> 13 For example, Duffy (2000) finds that there are a few services that deprived area residents are less satisfied with compared to their counterparts in less deprived districts.

15
Policy Research Working Paper 5912

# **Abstract**

The European Social Survey data are used to analyze informal employment in 30 countries, focusing on employees without contracts and on informal selfemployed workers (who are distinguished from formal workers). Overall the size of informal employment decreases from South to West to East to North. However, working without a contract is more prevalent in Eastern Europe than in the West, except for Ireland, the United Kingdom, and Austria. Between 2004 and 2009, no cases were found when unemployment and dependent informality rates in a country went up together, suggesting that working without a contract is pro-cyclical in Europe. The dependent informality rate is inversely related to skills (measured by either schooling or occupation). Both in Southern and in Western Europe, the highest dependent informality rate is found among immigrants from Central and Eastern Europe and the Former Soviet Union, while in Eastern Europe this group is second after minorities without immigrant background. In the Southern and part of Western Europe, immigrants not covered by European Union free mobility provisions are much more likely to work without a contract than otherwise similar natives. The paper provides evidence that exclusion and discrimination plays an important role in pushing employees into informality, while this seems not to be the case for informal self-employed workers. Both on average and after controlling for a rich set of individual characteristics, informal employees in all parts of Europe are having the largest financial difficulties among all categories of the employed population (yet they fare much better than the unemployed and discouraged), while informal self-employed workers are at least as well off as formal employees. Finally, there is a negative and significant effect of individual-level satisfaction with the national government on the propensity to work without a contract in Eastern Europe, as well as in Western Europe.

This paper is a product of the Human Development Economics Unit, Europe and Central Asia Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at mihazan@lanet.lv.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
ECCAS’S INFRASTRUCTURE: A REGIONAL PERSPECTIVE transmission investments would need to be made in Cameroon and the Republic of Congo, which compose 80 percent of the required cross-border investment.

The CAPP region as a whole would need to spend around 2 percent of GDP to meet power needs, and most countries stand to save money by deepening regional trade (figure 3.2). For individual countries, the impact of adopting trade can substantially influence the burden of power sector development needs on their national economies. Under trade stagnation, the amount that countries need to spend to meet their power sector needs varies. Gabon, Cameroon, and Chad would have to spend between 1 and 2 percent of their GDP to meet their power needs, while the Republic of Congo would have to spend as much as 7.5 percent of its gross domestic product

**Table 3.4 . Additional infrastructure requirements for trade expansion (MW)**

||Cross-border<br>transmission|Additional<br>hydropower (MW)|
|---|---|---|
|Cameroon|831|1,383|
|Central Africa|||
|Republic|0|0|
|Chad|202||
|Congo, Rep. of|498|0|
|Equatorial Guinea|20|0|
|Gabon|111|0|
|_Source:_Rosnes and Ven<br>_Note:_MW = megawatt.|nemo 2009.||

(GDP). Under trade expansion, the pattern of spending shifts. Most countries would spend substantially less to meet their power sector needs than under trade stagnation. Gabon and Chad would need to spend less than 1 percent of their GDP to meet their power needs. Meanwhile, the burden of spending in the Republic of Congo would decrease from over 7 percent to less than 5 percent of the GDP, benefitting the most from trade. But the expenditure burden for Cameroon would increase substantially, reaching 3 percent of GDP. Under the trade expansion scenario, Cameroon becomes the main exporter of hydropower in the region and has to bear the burden of additional investments to fulfill this role.

**Figure 3.2 . Regional spending needs as a percentage of GDP**

<!-- Start of picture text --> 8<br>7<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>Trade Expansion Trade Stagnation<br>Spending as % of GDP Gabon Chad<br>Rep<br>Equatorial Guinea Cameroon Central African Congo Rep.<br><!-- End of picture text --> _Source:_ Derived from Rosnes and Vennemo 2009. _Note:_ GDP = gross domestic product.

37