rafmacalaba/datause-encoder-data huggingface dataset:
6 _Table 3. Subsidies Financed.from the Russian Regional Budgets, 1992-95, as % of GDP_

||1992|1993|1994|1995|
|---|---|---|---|---|
|TOTAL|3.38|5.53|6.19|5.23|
|_A. Transfers to the enterprise_|1.25|1.43|1.27|0.86|
|_sector_|||||
|Al.Budget subsidies|1.05|0.84|0.64|0.68|
|- Agriculture|1.05|0.78|0.60|0.68|
|- Others|n.a.|0.06|0.04|n.a.|
|A2. Budget Investment Grants|n.a.|0.29|0.27|0.18<br>|
|- Agriculture|n.a.|0.29|0.27|0.18|
|A3. Budget Loans|0.20|0.30|0.35|0.49|
|_B. Indirect subsidies to households_|2.13|4.10|4.92|3.89|
|B1.Budget subsidies|2.13|4.05|4.87|3.80|
|- Housing & utilities|1.32|3.31|4.17|3.16<br>|
|-<br>Public Transportation|0.42|0.54|0.34|0.63|
|- Consumer goods price subsidies|0.39|0.20|0.36|n.a.|
|B2. Budget Investment Grants|n.a.|0.05|0.05|0.09|
|- Public Transportation|n.a.|0.05|0.05|0.09|
|Memo: Tax arrears and deferrals annual fl|ows n.a.|0.76|0.74|1.14|

Memo: Tax arrears and deferrals, annual flows n.a.

# Source: The World Bank

While regional transfers are mainly targeted at compensating producers affected by locally imposed price controls, there is some evidence that enterprises outside of the three sectors mentioned above also frequently benefit from regional govermment support. However, these kinds of transfers are quite badly documented. Despite the growing role of regionally funded subsidies, there are no reliable public finance statistics to clarify the structure of local spending on the enterprise sector. The growing share of regional subsidies to enterprises is either reflected in the budget items 'loans" and 'bthers" or provided from outside of the regional budget altogether. The latter includes transfers from regional extrabudgetary funds<sup>5</sup> , various local tax benefits, and 5 Serova and Melyukhina (1995) describe the Ulyanovsk model of extensive regional government price control and food rationing. The distinctive feature of the model is the existence of an informal agreement between local enterprises and the administration to comply with regional price and trade controls and provide transfers to the regional extrabudgetary fumd used primarily for price subsidization.
# **5. COVID, Quo Vadis?**

The previous section has posited that the world’s demographic structure is inconsistent with the observed skew in the mortality burden towards HICs. This section will discuss the implications of this finding for the future direction of the pandemic. It will note that while to some degree the contrast between rich and poor countries is simply ‘unreal’, for the most part it will likely be temporary as the full progression of the pandemic is yet ‘unrealized.’

## **Perspective 1: Unreal**

Overshadowing the discussion so far is the specter of poor data quality in dimensions such as accuracy, completeness, consistence, timeliness and validity. The need for adequate measurement and reporting cannot be emphasized enough. Where testing has been limited or untimely, data quality will suffer. Where vital statistics were poorly reported prior the pandemic, the problems will be even worse.

Figure 11. Data Outliers: Countries with Extremely Low Observations of COVID-19 Fatalities by Population Size <!-- Start of picture text --> 60 Congo, Dem. Rep.<br>Niger<br>Thailand<br>Burkina Faso<br>Kenya<br>40<br>Ghana<br>Côte d'Ivoire<br>20<br>Tanzania<br>Uzbekistan<br>Venezuela<br>Sri Lanka Nepal Ethiopia<br>Angola Uganda Vietnam<br>0 Madagascar Mozambique<br>30 60 90<br>Population (millions)<br>Number of COVID−19 deaths<br><!-- End of picture text --> Source: Johns Hopkins University; World Population Prospects. Note: Population is 2020 estimate. Sample restricted to population over 20 million and fatalities under 100.

Some countries with large populations report remarkably few fatalities. Figure 11 shows some outliers of countries with a population of more than 20 million and where fatalities are reported below 100. As of May 23, Mozambique, Uganda and Vietnam for example reported zero fatalities even though their populations count 31, 45 and 97 million people, respectively. Ethiopia reported only 5 fatalities among its 115 million people. While the younger population structure of these countries is expected to considerably lower the death toll, the reported numbers are well below what the demography-based simulations would suggest.

21
# **Global Development Bond**

A Global Development Bond would mobilize private capital investment to developing countries. Certain risks of the bond would be mitigated through guarantees or insurance by governments or agencies. The bond would “not work like foreign aid or other public sector funding (trade, investment, risk mitigation) programs, but will complement them, leverage their funds and further their goals.”<sup>95</sup> Reading: Eckhart 2004

# **Global Lottery**

National lotteries are a source of income for national charities. A global lottery would direct the proceeds from a lottery towards international development. Two forms of a global lottery have been proposed: (i) an international agency would organize a new and genuinely international lottery; or (ii) or an international agency would receive a share of proceeds from national lotteries.

Reading: Addison and Chowdhury 2005, Morgan 2000 See also: Global Premium Bond

# **Global Premium Bond**

A premium bond (or lottery bond is a proposal for a debt instrument whereby people buy savings bonds that do not disburse the interest proceeds but interest proceeds are paid into a lottery. The winners of that lottery would receive payments. Two proposals for a Global Premium Bond exist: (i) A single global bond or coordinated national bonds would direct a share of the proceeds of the lottery toward development. The bond would not lend to developing countries. (ii) A single global bond or coordinated national bonds would lend directly to developing countries. These would receive financing for more favorable term because premium bonds usually pay lower interest to investors than comparable conventional bonds. Investors would have to bear the developing country credit risk.

Reading: Addison and Chowdhury 2005

# **Global Taxes**

A number of global taxes have been proposed, including carbon and other environmental taxes; aviation taxes on the ticket price, flight distance, or jet fuel; a currency tax (the original currency tax proposal was the Tobin Tax); a tax on arms trade; a tax on international shipping; a trade tax on internationally traded goods; a surtax on profits of multinational corporations; a tax on financial transactions of bonds, stocks, and derivatives; a surcharge on domestic taxation; charges on use of outer space, such as a satellite tax; charges on information exchange: mail, telecommunication, or the Internet (bit tax); royalties on minerals mined in international waters; charges for exploration in or exploitation of Antarctica; charges for fishing in international waters; charges for the use of the electromagnetic spectrum.

The proposed global taxes vary in their ambition of including a great number of countries and of being a true tax with obligatory long-term payments. Usually, a tax is considered an obligatory

> 95 Eckhart 2004.

71
Even though it seems obvious that unsafe water and poor sanitation increase both morbiditiy <u>and</u> mortality associated with waterborne diseases, relatively few studies have directly focused on child mortality as a primary outcome of interest. Those that have analyzed the impact of water and sanitation infrastructure on child mortality generally combine national burden of disease accounts with epidemiological estimates of the impact of water and sanitation on morbidity to compute (disability-adjusted) life-years lost due to inappropriate water and sanitation infrastructure (Clasen et al., 2007; Pruess et al., 2002; Pruess-Uestuen et al., 2008). In the most recent study in this area, Pruess-Uestuen and coauthors (2008) estimate that about 3.5 million (child and adult) deaths could be prevented worldwide per year with investments in water, sanitation and hygiene. The studies that have undertaken cost-benefit analyses of improved water and sanitation infrastructure<sup>2</sup> have mostly focused on the benefits from avoided illness cost (and time savings), and only took these indirect estimates of deaths prevented into account (e.g. Hutton and Haller, 2004; Hutton, Haller, and Bartram, 2007; Rijsberman and Zwane, 2008; Whittington et. al, 2008).<sup>3</sup> While diarrhea-focused studies allow some inference about the mortality effects of water and sanitation, the derived links are indirect, and unlikely to reveal the full mortality benefits of water and sanitation infrastructure investment. An extensive literature suggests that the effects of improved water and sanitation on child mortality go beyond their direct diarrheal effect. By lowering the exposure to fecally-transmitted diseases, access to improved water and sanitation does not only lower diarrhea incidence but also considerably lowers the risk of malnutrition (Pruess-Uestuen et al., 2008) as well as the risk of severe infection with other (not fecallytransmitted) diseases, enhancing the chances of survival for protected children (Caulfield et al, 2004; Cutler and Miller, 2005; Ewbank and Preston, 1990; Walker et al, 2007).

In this paper we focus on child mortality as one of the primary policy objectives within the MDG framework. Given that Sub-Saharan Africa has been lagging behind both with respect to the mortality (MDG 4) and the water and sanitation objectives (MDG 7), we try to answer three simple, but highly policy-relevant questions: First, what is the reduction in under-5 mortality that countries could achieve if all households in a country had access to improved water and sanitation? Second, how much could improved water and sanitation infrastructure contribute to close the gap between the status quo of child mortality and the MDG 4 target?

> 2 Mostly commissioned by the World Health Organization and the Copenhagen Consensus. 3 In these studies, the return to 1 US$ invested in water and sanitation infrastructure was estimated to be between 5 US$ and 30 US$, with substantial variation in the returns across countries.

3
_ 1997. "After Voucher Privatization: The Structure of Corporate Ownership in Russian Manufacturing Industry," _SITE Working Paper No. 120,_ Stockholm School of Economics, Stockholm, Sweden.

Economic Research Centre. 1997. _Privatization in the Baltic Countries,_ Vilnius, Lithuania, unpublished manuscript.

- Estrin, Saul and Adam Rosevear. 1999. "Ownership and Company Restructuring in Ukraine," _European Economic Review,_ May.

- , Alan Gelb and I.J. Singh. 1995. "Shocks and Adjustment by Firms in

- Transition", Journal of Comparative Economics, Vol. 21, pp31-53.

- Frydman, Roman, Cheryl Gray, and Andrzej Rapaczynski. 1997. "Private Ownership and Corporate Performance: Some Lessons from Transition Economies," New York University Working Paper 9827, New York.

- ________ i Marek Hessel, and Andrzej Rapaczynski. 1998a. "Why Ownership Matters?: Politicization and Entrepreneurship in the Restructuring of Enterprises in Central Europe," _New York University, C. V. Starr Centerfor Applied Economics, RR# 98-14._

- ; Cheryl Gray, Marek Hessel, and Andrzey Rapaczynski. 1998b. "When

- Does Privatization Work? The Impact of Private Ownership on Corporate Performance in the Transition Economies, " _New York University, C. V. Starr Center for Applied Economics, RR# 98-32._

- Hausman, J. A. 1978. Specification Tests in Econometrics. _Econometrica,_ 46, 1251-71. Kornai, Janos. 1998. "The Place of the Soft Budget Constraint Syndrome in Economic Theory", _Journal of Comparative Economics,_ March, 11-17.

- Kornai, Janos. 1980. "Economics of Shortage". Amsterdam: North Holland.

- Linz, Susan, and Gary Krueger. 1998. "Enterprise Restructuring in Russia's Transition Economy: Formal and Informal Mechanisms," _Comp. Economic Studies, 40._

- McConnell, John and Henri Servaes. 1990, "Additional Evidence on Equity Ownership and Corporate Value," _Journal of Financial Economics,_ 27: 595-612.

- Morck, R., A. Shleifer and R. Vishny. 1988, "Management Ownership and Market

- Valuation: An Empirical Analysis," _Journal of Financial Economics_ 20, 293-315.

39
> - 57 -

Table 4.3L Pindyck's PartLal Own Fuel Price ElasticitLes for the Induotrial Sector

||Coal|Fuel Oil|Gas|Electricity|
|---|---|---|---|---|
|Canada<br>|-1.80|-0.81|-0.33|-0.14|
|France|-1.04|-0.20|-1.49|-0.16|
|Italy|-1.49|-0.29|-1.30|-0.13|
|Japan<br>|-1.32|-0.20|-1.49|-0.12|
|Netherlands<br>|-1.67|-0.11|-1.42|-0.07|
|Norway<br>|-2.08|-0.34|-|-0.08|
|Sweden|-1.26|-0.27|-|-0.12|
|U.K.<br>|-1.12|-0.22|-1.38|-0.15|
|U.S.A.<br>|-2.17|-1.10|-0.52|-0.08|
|West Germany|-1.09|0.03|-2.31|-0.12|

The own prLce elastLclty for electricity Ls uniformly low and that for oL1 is surprLLngly low, but thLi may well reflect the fact that the data does not Lnclude the oLl shock perLods. The model did not impose symmetry so for each pair of fuels there are two elasticitLes of substitutLon. The values are not very dlfferent so just one set is presented.

ZSble 4.4s PLndyck's Cross Price PartLal Fuel ElasticitLes for the Industrial Sector

||C/O|C/G|C/N|o/a|0/3|G/N|
|---|---|---|---|---|---|---|
|Canada<br>|0.90|1.17|-0.28|-0.21|0.61|-0.49|
|France<br>|0.20<br>|0.46|0.39|-0.08|-0.08|-0.51|
|Italy<br>|0.27<br>|0.83|0.39|-0.03|0.11|-0.15|
|Japan<br>|0 a1<br>|0.65<br>|0.45|-0.08|0.02|-0.41|
|Netherlands<br>|0.21<br>|0.98|0.48|-0.10|0.01|-0.22|
|Norway<br>|0.37<br>|1.34|0.37|-0.09|0.30|-|
|Sweden<br>|0.24<br>|0.55<br>|0.46|-0.11|0.12|-|
|U.K.<br>|0.21<br>|0.52<br>|0.39<br>|-0.06|-0.04|-0.33|
|U.S.A.<br>|0.99<br>|1.66<br>|-0.48|-0.72|0.85|0.12|
|WestGermany|0.15|0.43|0.49|-0.18|-0.22|-1.82|

The cross prLce elasticities give a faLrly consistent picture. There ls a low degree of substLtutability of coal for oLl and a low degree also of oLl for electricity except in Canada and the U.S. Coal and gas are strongly substitutable while coal and electricity are moderately substitutable. Gas
countries; that is, foreign R&D is more important for small countries. Coe, Helpman, and Hoffmaister (1997) extend these results based on a sample of 77 developing countries. They find developing countries that do little R&D on their own, have benefited substantially from industrialized country R&D through trade in intermediate products and capital equipment with industrialized countries. Regarding the impact of FDI in services, we have cited numerous papers above that establish that FDI in services increases TFP in the economy.

In summary, this literature shows that the purchase of intermediate inputs from industrialized countries and FDI in services is an important mechanism for the transmission of R&D and productivity growth in developing countries. For small developing countries, trading with large technologically advanced countries is crucial for TFP growth. In our model, the parameter that reflects the ability of a region to increase total factor productivity through the transmission of modern technologies is the elasticity of firm supply with respect to the price. The greater the elasticity of firm supply in a sector the more varieties will be received in response to a price increase with respect to that country. Based on these considerations, in the increasing returns to scale sectors of our model, we assume that the elasticity of firms’ supply with respect to price is 3 for all IRTS sectors in The Philippines, India and the Rest of ASEAN; 4 for China and 5 for all other regions. These values are in a footnote to table 4. We conduct sensitivity analysis on these parameters, to determine the impact of these parameter values on the results.

# **4.2 Ad Valorem Equivalents (AVEs) of the Barriers against Business Services. 4.2.1 Estimates of the AVEs of Barriers against FDI in Business Services.** Our

estimates of the ad valorem equivalents of discriminatory barriers against foreign providers of services in the services sectors are taken from Jafari and Tarr (2015) and shown in table 3. The Jafari and Tarr estimates are based on the World Bank database of discriminatory regulatory barriers in 11 services sectors in 103 countries; that database is described in Borchert, Gootiiz and Mattoo (2014). Borchert _et al_ . produced “Services Trade Restrictiveness Indices,” but did not transform their indices of the regulatory regimes into ad valorem equivalents. The Jafari and Tarr methodology uses the World Bank database for an assessment of the regulatory regimes, but builds on a series of studies, supported by the Australian Productivity Commission, to convert assessments of services regulatory regimes into ad valorem equivalents for all 11 sectors in 103 countries. Most of the Australian studies are published in Findlay and Warren (2000). Jafari and Tarr define mappings from the World Bank database to the scoring matrices of the Australian 22
fall was the result of a conscious effort by Britisb authorities to refuse -- outdoor relief to healthy adult males. The other force was market related rising wages driven by the forces discussed in Section II. The decline in male able-bodied pauperism was neither steady nor continuous. As we shall discuss below, recessions pusbed unemployed workers into pauperism. But it is clear that by the end of the century, we must look beyond the adult male workforce when discussing pauperism and extreme poverty.

In the 19th century as now, the old, the sick, widows, single parents and their children, and those in large families were much more likely to be very poor than other groups in the population. Poverty obeys a life cycle pattern. This is illustrated in Figure 7 (taken from ", 1910, LIII, Appendix XXV, Part II, p.56, 108-9) which shows pauper rates in Rngland and Wales in March 1906 by age group. The solid line shows total pauper rates and the broken line indoor pauper rates.

It is clear that pauper rates rise steeply in old age. Almost one in five of the population over 65 and almost one in four of those over 70 were receiving poor relief at the time of this census. In part this may have been due to more generous state relief policy for the old than for others, but the fact that the proportion of the old in the workhouse was also high suggests that part of the high old age pauper rates was due to old age poverty. Those over 65 constituted 28.3% of all paupers in the 1906 census and 35.3% of those in the workhouses. Unfortunately, there is no data on the ages of outdoor paupers before 1890, but the percentage of paupers who were listed as "not able-bodied" (a category in which 80% were over 60 in 1906) rises from 38.9% in 1850 to a peak of 49.2% in 1900. The percentage of indoor paupers aged over 65 rose in the same period from 19.8% to 36.5% of the workhouse 47
41 admissions, rather than by prolonged hospital stays.<sup>36</sup> This line of argument is consistent with previous theoretical and empirical research on the general effects of this reimbursement method (cf. Ellis and McGuire 1986; Yip and Eggleston 2001; among others). However, our results are also consistent with additional health spending occurring _outside_ the hospital sector. With our data, we are unable to discriminate between these two hypotheses. Of course, both may be true.

Our results certainly suggest that a sizeable part of the rise in health spending 37 caused by a shift from budgets to FFS is due a rise in _private_ spending. Again, this extra spending could be in the hospital sector, or outside the hospital sector. In the latter case, it could be that patients admitted in hospital are incurring expenditures on complementary ambulatory care services or purchasing additional drugs. Or it could be that people are substituting away from hospital care knowing that FFS encourages providers to deliver additional care not all of which may be medically necessary and instead making greater use of ambulatory care and drugs. Our data do not allow us to discriminate between these explanations. And, again, both could be true. Indeed, both are plausible. It does indeed seem to be the case that hospital payment reforms in the ECA countries often entailed not only a decision that the government will pay hospitals differently (leading to higher public spending after the reforms, consistent with the results above), but also a decision that hospitals will be allowed to recover some of their costs from out-of-pocket payments from patients. In many cases, user

> 36 With regard to the absence of FFS impacts on ALOS in our sample, it is worth noting that even hospitals in countries where per-diem was the prevailing reimbursement method may have faced no incentives to increase ALOS, relative to the level observed under historical budgets. For instance, in the case of the Slovak Republic, there is evidence that bed day prices did not cover the real costs of hospitals, with costs exceeding the prices paid by the health insurance companies by up to 30% according to some calculations (Hlavačka _et al._ 2004).

> 37 Out-of-pocket expenditures represented on average 92% of private spending in the ECA countries in 1998, with a similar figure across groups of FFS and PBP adopters. In 2004, those figures were still very high (in excess of 86%). The data were obtained from the WHO’s _Health for All_ database; there is no available data prior to 1998. With only a few exceptions (e.g. Slovenia), voluntary health insurance does not play an important role in the countries of the ECA region.