rafmacalaba/datause-encoder-data huggingface dataset:
-2-

It should be stressed that the ICP evaluation of a country's relative standing can be very different from one derived from exchange rate comparisons, and the difference is usually bigger, the poorer a country happens to be. It is for this reason that this topic has more than academic interest. For Brazil, Mexico and India, ICP evaluation of per capita ODP performance in 1975 was 25.2, 34.7 and 5.6 per cent of US levels whereas exchange rate comparisons showed 16.0, 20.4 and 2.0 per cent respectively (see Kravis, Heston and Summers, 1982, p. 22).

# The Alternative "Industry-of-Origin" Approach

The expenditure approach is useful for analysis of macro economic performance, but cannot be directly used for sectoral analysis as it does not show real product by industry. This handicaps comparative structural analysis, -fork on labour or total factor productivity, growth accounting. and studies of technological performance. It does not help in deriving weights for world production indices for sectors such as agriculture or manufacturing, nor does it make a clear breakdown between tradeable and nontradeable goods and services which is needed for analysis of competitiveness. The industry of origin approach, which is used here. promises to yield solutions to these problems, as well as providing a crosscheck on ICP results which are sti'll a subject of controversy.

One way of illustrating the difference between the expenditure and the industry of origin approaches is presented in table 1.1. This is derived from the Mexican input-output table for 1975. Ideally, the industry of origin approach should derive PPPs (purchasing power parities) for column (1) of table 1.1 for GDP ac factor cost. For agriculture (see Van Ooststroom and Maddison, 1985) this is possible, but for manufacturing most of our price (unit value) information refers to column (3).

What the expenditure approach does, is to estimate PPPs for the last column of table 1.1, i.e. final expenditure at market prices. In table 1.1, final demand is allocated according to the corresponding production sector for convenience of comparison, but in fact the expenditure approach breaks down final demand by components of private consumption, government consumption, investment, etc. In the expenditure approach of ICP for 1975, 151 categories of final demand were distinguished, of which 82 had a substantial manufacturing content.
_Pt_ is the aggregate price level at time t.

Demand for the products of each sector can be derived: Consumption of good i strictly decreases with its relative price, and strictly increases with real income. And the model assumes income elasticity for the four sectors satisfy the following: This assumption draws upon various estimates of sectoral income elasticities from existing literature (Comin, Lashkari, and Mestieri 2021; Young 2013; Aguiar and Bils 2015). As incomes rise, consumer expenditure patterns tend to shift from goods to services, reflecting a growing preference for experiences over material possessions. Food exhibits the lowest income elasticity, as even the wealthiest individuals have finite nutritional needs. Similarly, manufactured goods have a limited income elasticity, as the utility gained from owning multiple TVs, smartphones, or cars diminishes beyond a certain point.

The challenge lies in estimating the income elasticity for high skill services. First, a major portion of financial services, ICT services, professional, scientific, and technical services primarily cater to businesses rather than individual consumers, making it difficult to derive income elasticity from household expenditure surveys. As an economy’s real income level increases, businesses become more sophisticated, driving up demand for these services to enhance productivity. Second, households often consume such services indirectly through other products or services, making it challenging to isolate and accurately measure the expenditure on these services. Third, some of these services like legal and accounting services are purchased infrequently, such expenses often fall out of the regular expenditures that surveys typically focus on. Fourth, some digital services could be accessed for free or through non-monetary means (e.g., data sharing), which is not captured in traditional expenditure surveys.

By far the highest income elasticity is observed in non-tradable, low-skill services including housing, education, healthcare, tourism, and personal services. Aguiar and M. Bils (2015) estimated that income elasticity in US households is 0.4-0.5 for food, 1-1.5 for manufactured goods, 1.2-1.3 for entertainment equipment and television subscription, 1.65 for entertainment fees, admissions, and reading, 1.6-1.8 for childcare, and 1.6-1.9 for education, as shown in Section 2, Figure 1. These results corroborate the model assumption in Equation 4.

Equation 3 yields the below: consumption of good _i_ relative to good _j_ decreases with relative price 17
# **Table 4:  Darussalam (CAMS-3) monitor readings: Hourly traffic and weather determinants**

All variables in log form

||PM 2|.5|NO|2|
|---|---|---|---|---|
||Level|Difference|Level<br>|Difference|
|Traffic Speed|-0.355|-0.405|-0.422|-0.357|
||(4.02)**|(6.04)**|(6.21)**|(7.22)**|
|Humidity|-1.013|0.234|-0.729|0.295|
||(12.38)**|(0.99)|(11.79)**|(1.63)|
|Temperature|-3.701|-1.674|-1.861|-0.271|
||(24.20)**|(3.91)**|(14.77)**|(0.83)|
|Wind Speed|-0.436|-0.135|-0.493|-0.051|
||(9.04)**|(1.93)|(12.35)**|(0.90)|
|Constant|22.870|-0.026|14.381|-0.004|
||(35.34)**|(1.16)|(28.80)**|(0.21)|
|Observations|565|485|1,013<br>|964|
|R-squared|0.75|0.18|0.56<br>|0.07|

Absolute value of t statistics in parentheses * significant at 5%; ** significant at 1% We summarize the overall implications of our results in Table 5, which reports pollution predictions across the full range of traffic speeds. The second and third columns report predicted PM2.5 and NO2 for the CAMS-3 area at mean values of the weather variables. The predictions for least congestion (40 km/hr) provide baseline values for PM2.5 and NO2 that incorporate weather effects, vehicular emissions on uncongested roads, and emissions from other sources.<sup>8</sup> Our results suggest very large incremental effects for traffic congestion: From the least- to most-congested cases, PM2.5 more than doubles, from 55 to 124 ug/m<sup>3</sup> . The proportional change is even greater for NO2, which increases from 12 to 31 ppb.

**Table 5:  Predicted NO2 and PM2.5 for the CAMS-3 area**

|Traffic Speed<br>(km/hr)|PM2.5<br>(ug/m<sup>3</sup>)|NO2<br>(ppb)|
|---|---|---|
|4|124|31|
|7|101|25|
|15|77|18|
|40|55|12|

8 We focus on vehicle emissions as a PM2.5 source in this paper, and our results provide strong evidence that the link between daily traffic fluctuations and fluctuations in PM2.5 is highly significant. However, our results do not imply that vehicle emissions have unique significance for PM2.5 pollution in Dhaka. Brickworks are another frequentlycited source of PM2.5 in the region and their emissions are undoubtedly included in the PM2.5 baseline value reported in Table 5. This value is already much higher than the WHO reference standard for PM2.5; vehicle emissions simply add another highly-significant component to the total.

13
markets (as the data below will show).

# **2.2 Market Sampling and Summary Statistics**

Our study was carried out in the Indian state of Madhya Pradesh (MP), one of India’s poorer states, with a GDP/capita of _∼_ $600/year (or _∼_ $1500/year in PPP terms) in 201011 (the period of the study). We first drew a representative sample of 100 villages across 5 districts, stratified by geographic region and an index of health outcomes. We then conducted a household _census_ in these villages, where we asked respondents to name all providers from whom they sought primary care in the past thirty days and their locations (including providers outside the village, but in market clusters on the nearest main road). We then surveyed all providers in all of these locations, regardless of whether or not the providers themselves had been mentioned in the sample villages, thereby obtaining a census of all providers in the healthcare market that catered to sampled villages.

Table 1 (columns 1-3) presents summary statistics based on the provider census (Panel A) and the household census (Panel B) in these markets; columns 4-6 compare villages sampled for the SP study to the representative villages. The table highlights three key features of the health market in rural India. First, villages are served by a large number of providers once the health market is correctly accounted for by including clusters on major roads close to the village. There are 11 primary care providers per market and 46 percent of households reported visiting a primary care provider in the 30 days prior to the survey.

Second, the majority of providers are private (7 out of 11 or 64 percent), and they account for 89 percent of household visits; excluding paramedical public health workers (typically responsible for preventive, maternity and child care) increases the fraction further to 93 percent. The share of visits to private providers (with or without qualifications) is 88 percent when there is a public provider in the market, and is 83 percent even when there is a public MBBS doctor in the same market.

Third, 48 percent of all providers and 77 percent of all private providers (5.4 per village) have no formal medical training, but account for 77 percent of household visits. There is less than one MBBS doctor per market, and 94 percent are available only outside the village. The distribution of MBBS providers is uneven. Only 30 percent of all villages have recourse to an MBBS provider (public or private) in their market, and only 5 percent within village boundaries. Private unqualified providers remain the dominant providers of care in most settings, accounting for 74 percent of all visits when there is a public provider in the same market, and 60 percent when there is a public MBBS doctor in the same market.<sup>10</sup> MBBS

> 10Note that even public facilities have a substantial number of unqualified providers. While these are typically support staff (who are only supposed to assist a qualified doctor), we find that it is very common

8
6

# **The Case of Ukraine: Summary of the Microevidence**

The formalized analytics and microevidence on the unofficial economy in Ukraine is treated in some detail elsewhere."' We summarize some of the issues and survey-based data here.

# _Administrative Controls Since Independence_

Until the end of 1994, Ukraine had not had a sustained attempt at economic liberalization. A brief and partial attempt took place in late 1992 and early 1993, but it was quickly reversed. In fact, except for that brief liberalization period (when Leonid Kuchma was prime minister and Viktor Pynzenyk was his vice premier for economic reform), the degree of official state administrative controls over markets and economic activity did not differ significantly from pre-independence days. State-imposed restrictions, interventions and distortions in the foreign exchange, trade, and pricing regimes, were extreme over much of the late- 1991 to 1994 period. An administrative control index, summarizing state interventions and controls in various markets in Ukraine, was constructed to trace the dynamics of liberalization during the period and is presented in summary fashion in Figure 1--depicting the evolution of (antiliberalization) administrative controls in various markets and regimes from early 1992 to late 1995 (see Table 1). Breaking from the unreformed past, the new administration embarked in late 1994 on a more ambitious liberalization program than theretofore, but it is still too early for these reforms to have had an impact on the behavior of economic agents. Thus, to understand the dynamics of the official and unofficial economies in early 1995, economic policies since independence through 1994 are critical.

Indeed, until late 1994 the pronounced administrative impediments in the trade, exchange rate, and pricing regimes, in addition to the high tax rates and microregulatory impediments (many at the local level), implied a very high cost of doing business officially in Ukraine--prohibitively high, in fact, for many entrepreneurs and fledgling activities. Thus, many either closed down or became increasingly unofficial. Doing business unofficially has been the strategy for many to reduce the very high cost of operating officially, and, in many instances, of merely surviving.

# _The Costs of Operating Unofficially_

The evidence on the cost of operating unofficially for those who choose to do so underscores just how costly it is to operate officially. To provide a partial picture of these costs, it is telling to review the microevidence on the unofficial "fees" required to overcome official administrative impediments. Table 2 summarizes the responses of seventy-five nonstate small and medium-sized enterprises regarding some of the costs of getting around various administrative regulations. Recent survey work (with a different sample) also provides insight to
indication of a selection bias from unobservables.

Our findings may also contribute to understanding a statistical oddity. The population count in Amhara was 17.2 million according to the most recent census in 2007 and clearly fell short of the offi cial government projection of 19.6 million Amharans for that year. “The 2.5 million missing Amharans”were extensively covered in the national media and eventually resulted in fierce debates in the parliament with both opposition and ruling coalition members of parliament condemning the census as flawed, calling for a redo of the census, as Ethiopia is a federal state and population size affects the budget of its regions. A panel of international experts reviewed the census, but were not able to spot any mistakes in its design or implementation.<sup>3</sup> We conjecture that Ethiopia’s “2.5 million missing Amharans”is due to a violation of a crucial assumption underlying the cohort component method, a method commonly used by statistical agencies to project the total population size for a future date from census data. The method assumes a constant total fertility for the projection period. However, we find a substantial reduction in the total fertility rate from 4.9 to 3.9 in the reform districts, which indicates that the statistical oddity may at least partly be a consequence of the land reform.

The next section discusses the institutional setting and the natural experiment. It also contains some theoretical considerations. Section 3 explains the data as well as the empirical strategy. Section 4 discusses the findings and Section 5 draws some conclusions.

# 2 Institutional setting and some theoretical considerations

## 2.1 Pronatal property rights and land tenure in Amhara

In this section, we argue that the rules governing access to land in the Amhara region were historically pronatal. Having children helped secure access to land in an environment of otherwise weakly defined property rights, no matter whether land governance was communal or statal. However, pronatal policies for land tenure were surprisingly abolished with the most recent land reform. We hypothesize that this policy change might have had a considerable influence on households’fertility decisions.

During the imperial period, a communal system of land governance, known as rist, was widespread in Amhara.<sup>4</sup> The claims of households to land culminated in rist through which they used to acquire usufruct rights to land. Rist rights derived from ancestors who formerly held land in a village.<sup>5</sup> Apart from

> 3 See, for instance, The Ethiopian Review, on June 23rd, June 24th and June 26th, 2009. (URL: http://www.ethiopianreview.net, last accessed on May 20th, 2015).

> 4 It could be found in Gojjam, Gondar, Shoa and Wollo, historic provinces that, by and large, form the region of Amhara today.

> 5 The inheritance of rights to land via rist followed cognatic descent rules, which place children (regardless of their sex) in the descent category of both their mother and father.

4
Policy Research Working Paper 10484

# **Abstract**

The COVID-19 pandemic significantly changed mobility patterns in the Bogotá and Buenos Aires metropolitan areas, as shown by the differences between the October 2019, 2020, and 2021 indicator values derived from call detail record–based origin-destination matrices. The differences between 2019 and 2020 were more notable than between 2019 and 2021 on most mobility indicators, demonstrating a reversal of the pre-pandemic mobility habits. However, by late 2021, the return to pre-pandemic levels was still very partial in the case of public transport use (especially so in Buenos Aires), while in Bogotá the pandemic appeared to have induced a permanent—and increasing—shift to nonmotorized modes. Other mobility indicators that appear to have changed more permanently in Bogotá include the lower average distances traveled and the relatively higher importance of non-home-based mobility. In the Buenos Aires Metropolitan Area, the key persistent changes include the lower overall trip generation rates and specifically peakhour travel, and the higher relative weight of travel to work and school compared to other travel purposes. These findings are partly explained by the underlying policy and regulatory context in the two cities and are relevant for designing transport policy in the post-pandemic context, including in terms of public transport route and schedule planning, cycleway network expansion, and, more broadly, the leveraging of big data as a complement to traditional mobility surveys.

This paper is a product of the Transport Global Practice. 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://www.worldbank.org/prwp. The authors may be contacted at astokenberga@worldbank.org, eivarsson@worldbank.org, and jfulponi@worldbank.org.

_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
support varies substantially across countries and seems to reflect whether men and women have clearly differentiated economic interests in society (Iversen and Rosenbluth, 2006).

# **Government response to demands**

The final link in the chain is how the government responds to demands. Again, digital civic engagement studies have largely assumed government response to be a function of what demands are made, with governments producing public goods directly in response to demands (Shkabatur, 2011; Pak, Chua and Vande Moere, 2017; Mcgee _et al._ , 2018). However, the link between government response and demands will vary with the institutional-design decisions embedded in the platform, and the government’s priorities.

_Table 1 Different ways governments can respond to demands made through a civic tech platform_

|**Response approach**|**Detail**|
|---|---|
|Engagement dependent|Fixed response after reaching a certain level of engagement. For instance, many<br>government-run petition platforms have a fixed number of signatures that need to<br>be reached to trigger a response.|
|First-come,first-served|Demands met in the order received.|
|Bias-correction|Respond to requests in a way that attempts to correct for biases at earlier stages of<br>the process. For instance, by prioritizing demands from demographically<br>underrepresented users or areas|
|Clientelism|Respond to requests in a way that maximizes the benefits to the ruling party’s core<br>supporters|
|Electoral maximization|Respond to requests in a waythat maximizes the benefits to the median voter|
|Figleaf|Only grant requests that thegovernmentplanned to implement anyway.|
|Ignore|Ignore or reject all demands made through theplatform|

In fact, there are many possible ways a government might respond to demands made through civic platforms. Table 1 highlights seven possible ways in which a government might respond to requests on a civic platform. Each approach will have different effects on how the demands made through a platform translate into who benefits and therefore on how the composition of users on the platform affects who benefits. Although governments decide how to respond to demands, the platforms can play a role in structuring those decisions. Platforms can choose to pre-filter, amplify, or downplay demands, and—by enabling certain actions—allow the users to do the same. For instance, signing petitions, upvoting, liking, commenting, and other user interactions allow certain demands to be emphasized by users, meaning the users play a role in which demands are more or less likely to be met.

7
Table 19: in foreign invested companies the minimum wage is high

||Monthly<br>Average wage<br>(in Dongs)|Ratio minimum wage<br>To average wage|
|---|---|---|
|Total|522,610|0.93 - 1.06|
|Total urban|625,420|0.89 - 1.00|
|Total rural|445,090|1.09|
|Private enterprises|623,430|0.78- 0.89|
|100% FDI|979,550|0.49 - 0.64|
|Joint ventures|524,180|0.93 - 1.19|
|_Source:_VLSS 2 (GSO|, 1999)||

**Table 20: The minimum wage is higher than wages of skilled workers**

||Monthly<br>Average wage<br>(in Dongs)|Ratio minimum wage<br>To average wage|
|---|---|---|
|No diploma|486,230|1.00- 1.28|
|Primary diploma|509,430|0.95-1.23|
|Lower secondary diploma|497,050|0.98-1.26|
|Upper secondary diploma|567,620|0.85 - 1.10|
|College and university|747,840|0.69-0.88|

_Source:_ VLSS 2 (GSO, 1999) To what extent is this minimum wage enforced? According to Vietnam's Ministry of Labor, Invalids, and Social Affairs (MOLISA) minimum salary breaches are widespread in foreign invested companies, mainly in garments, leather tanning, and paper production, as well as in agriculture. Interviews in Haiphong showed that some managers of foreign invested companies or joint ventures have indeed difficulties recalling the level of the minimum wage. Others openly admit paying below mandatory minimum. Most visited foreign companies, however, appeared to comply with regulations (Belser, 1999). This is unsurprising given that foreign invested companies are among the most visible companies, for which monitoring is easiest.

How does this minimum wage affect employment? In theory there are two channels through which high labor costs in foreign invested companies can hurt employment. The first is by inducing companies to substitute capital for labor and adopt less labor-intensive technologies. No such effect has however been reported by managers of foreign companies in Haiphong. Foreign companies in export-oriented sectors are mostly subsidiaries which import raw materials and transform them into finished products. There is thus not much scope for substituting machines for workers. Shoes and clothes have to be stitched together by workers and no machines can replace them.

The second and potentially more important channel through which higher labor costs can hurt employment is through reduced export competitiveness. Many of Vietnam's neighbors (in particular Indonesia) have recently experienced large currency devaluations due to the Asian crisis. This has brought about major reductions in the dollar cost of wages. In addition, many Asian countries have responded to the crisis by improving the business environment for foreign enterprises (World Bank, 1998). This has further eroded Vietnam's regional export competitiveness. Thus, coupled with the effects of the Asian crisis, Vietnam's 21